-------
                            DPA
f
                                for

                                                                          LH

-------
                                                                35
40
                                                                                 —r
                                                                                 45
                 —T
                  50
                                              DPA
pieure "(c.  plot  of residue hazard  (conmon logarithm  of  T dACbF) as a function
            of  tine Mavs post-application,  ""A) for  Fthvl  ^arathlon as
            reported fron  1'ashi npton, ^ont>< Carolina  and Tpxas.
                                                                                          C7\

-------
o
*-
o
       -2-
                           —T
                           10
—T
 15
—T
 20
—r~
 25
 DPA
—r
 30
—T
 35
—T
 40
—T
 45
—T
 50
          ririire  °rf.  "lot of resl^no  hazard (connon  logarithm of T
                      of M*
-------
 1 -
 o-
-1 -
-2 -
                     10
                    15
20
25

DPA
 I
30
35
40
 i
45
 T
50
*>e . "lot  of  residue* ^azarrf fconiwon  logarithm
    of  tl"e  '''nvs nost-annl icat Ion,  ""A)  for
                                                                        as a function
                                                            Tthyl "arathlon as
                                                                                                   CO
-------
 2 i
 1 -
 0-
-2-
   T
   0
 T
 5
—r
 10
—r
 15
—r
 20
—r
 25
—r
 30
—r
 35
—r
 40
—r
 45
—r
 50
10. i»lot of  residue bar.art*  fconnon  logarithm of  *
    of tlr»e  (<*avn nost-ap»»Mcn t f on,  I'M)  for  ''alathion.
                                                                        ns a function
                                                                                                 •sO
-------
DPA
1?. "lot  of

    of  ti"ie
(connon 1o»»arithn of

                for
                         ns a function
                                              Lsl
                                              r>o
                                              o
-------
-2 -
                            0
—T
 30
—T
 35
—T
 40
—T
 45
—r
 50
                    —r
                    10
—r
 15
—r
 20
—i—
 25
 DPA
           lla.  "lot  of residue hazard  (cornon logarithm  of f dA^hr) as n function
                 of  tlr»p fdavB nos t-annl i cfi t i on,  T"»A) for  Methvl  "arathiop wftfi  an
                         Tnn  for  Its  oxon iM^th  that  of  Its parent.
-------
-2
45       50
                    10
                                                           of
                                                                       ns fl  Function
                                                                                             ro
-------
 1 -
 0-
-1 -
   i
   0
i
5
     i
    10
                          15
 i
20
25
 i
30
 i
35
 i
40
45
 T
50
Pt«»ure  1
"lot of
of ti»ie
                      h/irar^  fcoi-»p»on  toparfthn  of ^
                    nos t-apnl 1 ra t ton ,  "''A)  for   "evlnnhos
                                                                              a  function
                                                                                  i n>.
                                                                                                   04
-------
 2 1
 1 -
 0-
-1 -
-2-
    k*
            r
           5
10
15
20
25      30      35       40
 T

45
 T

50
     Ptpure 1'•. i*lot of roslHnp  bazar** fconnon lo»»arithn of ""  ^AChr) ns a Function
               of tfmp ^Havs pos f-n nnl f ca t ton, n"A) for  *'onocrotonho«s  f
                                                                                     LM
                                                                                     fV)
-------
 21
 H
-H
-21
   I
   0
5
 I
10
 I
15
20
25
30
35
40
45
50
          1 S. "lot of  rrsfHue hazard fcownon loirarlthn  of * d.Ar'hr) as a function
              of ttnr  f^avs nos t-annT i ca t f on, ^"M for   "xv^eneton (Metasvs
                                                                                            rv>
                                                                                            c_n
-------
o
its-
CD
         -2 H
1ft. "lot  of rosier h.izarf'  fconnon  loparltfin  of » HAChr)  as

    of  ttr»p Mavs nost-annl f cntion,  HT»A> for   "lienthoate.
                                                                                        function
                                                                                                                ON
-------
o
c
c.
        -2H
                                                        DPA
17. i>1ot of  rflsfrfue hazar^  (rr»inr»on logarithm  of f

    of tine  f^avjs oost-anol \ ca 1 1 on , ^^M  for   ^hosalone
                                                                               as a  function
                                                                                                      ro
-------
     LDACHE
          2H
          1 -
cn
         -1 •
         -2 H
                     T
                     5
—T
 10
—r
 15
—r
 20
—i—
 25

 DPA
—r
 30
—r
 35
—r
 40
45
50
                        "lot  of  rpsl^tie bazar''  (common  logarithm of  *  flAfhP) as a function
                        of  tine  f-*avs  nop t-annt lea t ion,  r»PA)  for  Pnosnhani rton f^
                                                                                                       CO
-------
o
C:
         2 1
         1 -
         o-
        -2-
                             10

—T
 15
—T
 20
                                             25
—T
 30
35
40
45
50
pl«Mire 1°.  W1ot  of
            of  tfr»p
                                        hnznrH  fronnon  logarithm of  *  ^^rhr) as a function
                                       DOB t-a nnl f ra t ton ,  nf»A)  for  T"iosnet fT
-------
 21
  H
 o-t
-H
-24
                                      20
25
35
40
45
30
50
                    of
-------
to
20-
15-
io:

5
0

: •
1 i
c c
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3 ^ 3 1 ° D
A B ? F3 CCB c
\ ?BA|B B C "•
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6 B •
i i 1 i
7 8 9 10
                                                                                               in
                                                AIA
       Figure 21.  Plot of initial residue deposition (ug/cm2) as a function
                  of application rate (Ib AIA) for all chemicals and all  crops.
-------
C\J
    RES
     20
     15
     10H
                     T
                      2
                             A
                                  B
                                  B
                                    3
                                    A
                                    A
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            B

            B
                                                     *
               8Bi
                                                                 e
                             A
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                                                                 n
                                                                 •X-
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 5

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                                                                                  ID
                                                                                  LO
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9
-------
  RES
   20 H
   15-
   10-
   5 -
LT1
    0-
         A
         A
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            B
                                                —I—
                                                  5
                                                 AIA
                                   T
                                   7
T
 9
T
 2
T
 3
T
 4
"T
 6
10
       Figure 2.1. Plot of  Initial  residue deposition (ug/cm2) as a function
                  of application rate  (Ib  AIA)  for  all  chemicals on  peaches,
-------
  15-
  10-
Ln
   5 -
   0-
              A A
                                        ~T
                                        4
—I—
  5

 AIA
 r
10
     Figure 24. ^lot  of  initial  residue deposition (ug/cm ) as a function
                of application rate  (Ib  AIA)  for  all  chemicals on grapes.
                                                                                            CM
-------
00
5 :
o-

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>
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^
.— .
A
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i I I
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i t i i i i i 	 r
3456789 10
                                               AIA


     Figure 25. Plot of Initial  residue  deposition  (ug/cmO as  a  function
                of application rate (Ib AIA) for all chemicals  on cotton.
                                                                                           O4
-------
  ioH
en
\O
   oi
         A
         A
              *
                      T
                       2
T
 3
T
4
 5
AIA
~T
 6
~T
7
T
 9
—T
 10
      FiRure 25. Plot of initial  residue  deposition  (uR/cm2)  as  a  function
                 of application rate (Ib AIA) for all chemicals  on cotton.
                                                                 Osl
                                                                 L/-J
                                                                 ON
-------
APPENDIX A: Standardized Data Sheet  for
            recording pertinent data from
            published report.
  LOCATION OF  STUDY	
  DATE OF STUDY
  TYPE OF CROP(s)	
  CHEMICAL(s)  APPLIED (Check one)
  Single Chemical  Applied	
  Multiple Chemicals Applied	
  Multiple Chemicals Applied Separately
  Multiple Applications  of Chemical(s)	
  CHEMICAL(s)  APPLIED        |
                              APPENDIX A


                    Space for
                    citation information.
                                                                               337
  FORMULATION  (Fill  in  the  blank)
   	 WP  	 EC  	 LF    ! 	 WP
       G   Other            j     G
	 EC
Other
LF
  APPLICATION RATE  (Active  Ingredient per 	 )
  1.	 Total/tree  J2.	 Total/tree
    	 Kg/Ha      j  	 Kg/Ha
    	 Ibs/acre   j  	 Ibs/acre
  FORMULATION ADDITIVES  OR  COMMENTS
  1.	 J2.	
                                                     3.
WP
G
	 EC
Other
LF
                3.
                Total/tree
                Kg/Ha
                Ibs/acre
                3.
  MIXTURE (gallons  per  acre)  	
  SAMPLING PROCEDURE  (check one)
    Dislodgeable  residue	   Other residue_
    Leaf Punch 	  Whole Leaf	   Other
    Leaf Area Calculated  as: (check)   One Side
  EXTRACTION SOLVENT  Aqueous	
    Organic (circle one)  Hex     Cloro     Tol
                         (1)      (2)      (3)
  WEATHER     Data  Present ( Amount, if given)
  Rainfall     	   	
  Temperature  	   	
  Humidity	   	
  Ozone         	   	
  Other         	   	
                     Units
            	   Two Sides  	

             MeCl     Benz     Other
             (A)       (5)      (6)
              Residue data presented
                   in Tables 	
                      Graph   	
                    Equation 	
              Leaf Dust Measured:
                   YES / NO
                Form  completed by
                   Date
                           APPENDIX A:  page  1 of  1
                                                                    60
-------
APPENDIX B: Bibliography for Residue Decay-Response Database.
            Not every one of the following citations either
            contained residue data or was included within the
            data base summarized in Appendix H.

 1. Awasthi,M.D., et al:
    Dissapation of metasystox and monocrotophos in or on
    soybean crop residues.
    Indian J Agric Sci. 48(4): 245-247, 1978.

 2. Berck,B., Iwata.Y., Gunther,F.A.:
    Worker environment research: rapid field method for
    estimation of organophosphorus insecticide residues on citrus
    foliage and in grove soil.
    J. Agric. Food. Chem. 29(2): 209-216, 1981.

 3. Bowman, A.U., Oiler,W.L., Kendall,D.C.,  Gosnell.A.B., Oliver,K.H.:
    Determination of foliar residues for safe reentry of agricultural
    workers in the field.
    Arch.Environ.Contain.Toxicol.  11(4):  447-455, 1982.

 4. Charmillot, P.J. and  Blaser, C.:
    Study of the persistance of acephate, phosmet and deltamethrin used
    for the control of the summer fruit tortrix Adoxpphyes orana F.v.R.
    CA/099/065875C
    Rev Suisse Vitic, Aboric. Hortic.  15(3): 195-201, 1983.

 5. Chen.Z. and Yue.R.:
    Degradative dynamics of pesticides in tea leaves  and the selective
    parameters of safe pesticide design.
    CA/099/138268U
    Zhonggo Nongye Kexue (Beijing). 1: 62-70, 1983.

 6. Davis,J.:
    Potential Exposure to Dislogable Residues of Two Formulations
    of Methyl Parathion to Apple Trees.
    Bull Environ Contam & Tox.  27: 95-100 (1981).

 7. Davis,J.E.,  Staiff.D.C.,  Butler,L.C.,  and Stevens,E.R.:
    Potential exposure to dislodgable residues after application of two
    formulations of methyl parathion to apple trees.
    NTIS/PB82-247537
    Govt Reports Announcements & Index (GRA&I), 23: 1982.

 8. Dikshit.A.K. and  Bhattacharjee.N.S.:
    Residues of carbofuran and malathion in  or on soybean crop.
    Indian J Agric Sci.  New Delhi,  Indian  Council of  Agricultural
    Research. 50(5): 441-443, 1980.
                                                                 APPENDIX B

                                                                     :     338
                       APPENDIX B: page 1 of 9          . 1
                                                        6 I
-------
 9.  Everhart.L.P. and  Holt.R.F.:
    Potential benlate exposure during mixer/loader operations, crop
    harvest, and home use.                                                    339
    J.Agric.Food.Chem.  30(2): 222-227, 1982.

10.  Fitzpatrick.G.E. and  Began,M.D.:
    Residue dynamics of acephate and methamidophos in urban dooryard
    citrus foliage. Pompano Beach Florida, August-September 1978.
    Pestic.Monit.J. 14(1): 3-6, 1980.

11.  Gegenava.N.G.,  Klisenco,M.A., and  Pis'mennaya.M.V.:
    Dynamics of carbophos and phosalone decomposition in grape leaves
    and grapes.
    CA/098/067078Y
    Khim. Sel'sk. Khoz. 12:45-47, 1982.

12.  Gehrich, John L., John A. Burkart, Dennis Y. Takade, Eugene R. Turner,
    Stanley D. Allen.  Final Report:  Assessment of Leaf Surface Residues
    for Selected Organophosphorus Insecticides.  University of Utah
    Research Institute, Salt Lake City, Utah (1976).

13.  Gehrich,J.L.,  Burkart,J.A., Takade,D.Y.,  Turner,E.R., and  Allen,S.D:
    Assessment of leaf surface residues for selected oganophosphorus
    insecticides.  NTIS/PB82-230046
    Govt Reports Announcements & Index (GRA&I), 21: 1982.

14.  Habeebullah.B. and Balasubramanian,M.:
    Dissapation and persistance of certain insecticides on/in cowpea pods
    (var. C. 152)
    CA/097/067761V
    Madras Agric. J. 68(8): 517-526, 1981.

15.  Hafner.M. and  Michel,H.G.:
    Investigations on the drift of sulfur and its residues in plants
    (red clover and apple leaves from the variety "golden delicious").
    Nachrichtenbl Dtsch Pflanzenschutzd. 27(2): 24-27- [Eng. Sum.] 1975.

16.  Iwata, Yutaka, Margarete Dusch, Glenn Carman, and Francis Gunther:
    Worker Environment Research*  Residues from Carbaryl,
    Chlorobensilate, Dimethoate, and Trichlorfon Applied to Citrus Trees.
    J. Agricultural and Food Chemistry, 27:1141-1145 (1979).

17.  Iwata, Yutaka, Glenn E. Carman, and Francis A. Gunther:
    Worker Environment  Research:  Methidathion Applied to Orange Trees.
    J.Agricultural Food Chemistry 27:119-129 (1979).

18.  Iwata, Yutaka:
    Minimizing Occupational Exposure to Pesticides:  Reentry Field
    Data- a Recapitulation.
    Residue Reviews 75: 127-147 (1980).

19.  Katiha.S.M. and Nath.A.:
    Persistance of oxydemeton methyl residues in cauliflower
    CA/099/135479C
    J Entom Res. 5(1): 47-9, 1981.


                       APPENDIX B: page 2 of 9

                                                             62
-------
20. Keil, Julian E., C. Boyd Loadholt, Bob L. Brown, Samuel H. Sandifer,
    and Wayne R. Sitterly:  Decay of Parathion and Endosulfan Residues on
    Field-Treated Tobacco, South Carolina-1971.
    Pesticides Monitoring Journal, 6:73-75 (1972).

                                                                              340
21. Keil, J.E., C.'B. Loadholt, S.H. Sandfer, W.R. Sitterly,
    and B.L. Brown: Decay of Parathion Residues on Field-Treated
    Tobacco South Carolina - 1972.
    Pesticides Monitoring Journal, 6:377 (1973).

22. Kido, H., J.B. Bailey, N.F. McCalley, W.E. Yates, and R.E. Cowden.
    The Effect of Overhead Sprinkler Irrigation on Methyl Parathion
    Residue on Grape Leaves.
    Bull. Environmental Contamination and Toxicology 14:209-213 (1975).

23. Kilgore, Wendell W., Ming-yu Li, Ronald L. Mull, Wray Winterlin,
    Nemat Borhani, Jess Draus, Peter Kurtz, Norman Akesson, and
    Wesley Yates:
    Human Physiological Effects of Organophosphorus Pesticides in a
    Normal Agricultural Field Labor Population, A Preliminary Report,
    II.  Scientific Aspects. Food Protection and Toxicology Center,
    University of California, Davis.   56 pages (1977).

24. Knaak, J.B., K.T. Maddy, M.A. Gallo, D.T. Lillie, E.M. Craine,
    and W.F. Serat:  Worker Reentry Study Involving Phosalone
    Application to Citrus Groves.
    J.Toxicology and Applied Pharmacology 46:363-374 (1978).

25. Knaak, J.B., S.A. Peoples, T.J. Jackson, A.S. Fredrickson, R. Enos,
    K.T. Maddy, J.B. Bailey, M.E. Dusch, F.A. Gunther, and W. L.
    Winterlin:
    Reentry Problems Involving the Use of Dialifor on Grapes in the San
    Joaquin Valley of California.
    Arch. Environmental Contamination and Toxicology 7:465-481 (1978).

26. Kraus,J.F. et al:
    Monitoring of grape harvesters for evidence of cholinesterase
    inhibition.
    J.Toxicol.Environ.Health. 7(1): 19-31, 1981.

27- Leffingwell, J. T., R.C. Spear, and David Jenkins.
    The Persistence of Ethion and Zolone Residues on Grape Foliage in
    the Central Valley of California.
    Arch. Environmental Contamination and Toxicology 3:49-53 (1975).

28. Lynch,V.P., Hudson,H.R., and Pianca.M.
    Identification and determination of mecarbam and its major
    degradation products in water and crops.
    PESTAB/81/1797
    Pestic Sci. 12(1): 65-73 1981.
                       APPENDIX B: page 3 of 9
-------
29. Maddy et al:
    CDFA Report //HS-181  (ACF 59-181)
    Worker Health and Safety Unit. A Study of Parathion and Paraoxon        7 *
    Residue in Citrus Groves Following Applicaton of Parathion at           ^^
    Various Dosage and Dilution Rates (Report //HS-181). California
    Department of Food and Agriculture, Sacramento, CA (ca 1975).

30. Maddy, Keith T., and Clifford Smith:
    A Study of the Decay Rates of Ethyl-Metyl Parathion and Endosulfan
    Applied as a Foliar Spray to a Tomato Field in the Sacramento
    Valley of California.  Report //HS-293.
    Worker Health and Safety Unit, California Department of Food and
    Agriculture, Sacramento, California.

31. Maddy, Keith T., G. Sprock, A. Scott Fredrickson, and T. Jackson.
    Parathion Residue on Orange Tree Foliage in Riverside County,
    California, May-June, 1975,  Report //318.
    Worker Health and Safety IfaiLt, California Department of Food and
    Agriculture, Sacramento, California (ca 1976).

32. Maddy, Keith T., Susan Edmiston, Charles Kahn, Lilia Rivera, and
    Terry Jackson.  A Study of Parathion on the Foliage of Peach Trees in
    Stanislaus County, California, June-July, 1977.  Report // HS-395.
    Worker Heath and Safety Unit, California Department of Food and
    Agriculture,  Sacramento, California (ca 1977).

33. Misra.S.S.,  Verma,S.,  Handa.S.K., and Lal.R.:
    BHC and parathion residues on crop of yellow-sarson (brassica).
    Indian J of Agric Sci. 41(3): 276-279, 1971.

34. Nigg, H.N., J.C. Allen, R.F. Brooks, G.J. Edwards, N.P. Thompson,
    Roy W. King, and A.H. Blagg.  Dislodgeable Residues of Ethion in
    Florida Citrus and Relationships to Weather Variables.
    Arch. Environ. Contam. and Toxicology     :257-267 (1977).

35. Nigg, H.N., J.C. Allen, R.W. King, N.P. Thompson, G.J. Edwards,
    and R.F. Brooks: Dislodgeable Residues of Parathion and
    Carbophenothion in Florida Citrus:  A Weather Model.
    Bull. Environmental Contamination and Toxicology 19:578-588 (1978).

36. Nigg, Herbert N:
    Comparison of Pesticide and Particulate Recoveries with the Vacuum
    and Dislodgeable Surface Pesticide Residue Techniques.
    Arch. Environmental Contamination Toxicology 8:369-381 (1979).

37. Nigg.H.N.,  Reinert,J.A.,  Stamper,J.H., and Fitzpatrick,G.E.:
    Dissapearance of acephate, methamidophos, and malathion from citrus
    foliage.     PESTAB/81/1555
    Bull Environ Contam Toxicol  26(1): 267-272, 1981.

38. Nigg, H.N. and J. H. Stamper:
    Comparative Disappearance of Dioxathion, Malathion,
    Oxydemetonmethyl and Dialifor from Florida Citrus leaf and Fruit
    Surfaces.
    Arch. Environmental Contamination Toxicology 10(4):497-504 (1981).


                       APPENDIX B: page 4 of 9
-------
39. Nigg, Herbert N., Leo G. Albrigo, Harold E. Nordby, and James H.
    Stamper:  A Method for Estimating Leaf Compartmentalization of
    Pesticides in Citrus.                                                 -7/10
    J. Agricultural and Food Chemistry 29:750-756 (1981).                 $ 4 
-------
50. Prasad, Rajendra-P. and  Ramasubbaiah.K.:
    Persistance of phosphamidon in bhendi crop Insecticide.
    Pesticides. Bombay: Colour Publications. 16(6): 25-26, 1982.

51. Pree.D.J.,  Butler,K.P.,  Kimball.E.R., and Stewart,D.K.R.:           343
    Persistance of foliar  residues of dimethoate and azinphosmethyl
    and their toxicity to the apple maggot rhagoletis pomonella.
    J Econ Entomol. 69(4): 473-478, 1976.

52. Rajput,G.B.,  Khaire.J.T., and Dethe.M.D.:
    Influence of dimethoate and endosulfan sprays on level of residues
    in/on brinjal fruits.
    CA/100/019264U
    J. Maharashtra Agric Univ.  8(3): 289-290, 1983.

53. Ramasubbaiah.K. and Lal.R.:
    Studies of residues of phophamidon in okra crop insecticides.
    Indian J Entomol. 36(4): 344-351, 1974 (Pub. Aug 1976).

54. Ramasubbaiah.K. and Lal.R.:
    Studies on residues of phosphamidon in cowpea crop
    drosophilamelanogaster, test insect.
    Indian J of Entomol.  37(2): 179-184, 1975.

55. Ramasubbaiah.K. and Lal.R.:
    Residues of phosphamidon insecticide in cabbage crop.
    Indian  J  Entomol. [New Delhi] 40(2): 182-186, 1978.

56. Ramasubbaiah.K. and  Lal.R.:
    Residues of phosphamidon insecticide in mustard crop.
    Indian  J  Entomol. [New Delhi] 40(3): 285-289, 1978.

57- Scheunert,!.  et al:
    Fate of 14C-allylalcohol herbicide in soils and crop residues.
    J.Environ.Sci.Health [B]. 16(6): 719-742, 1981.

58. Sharma.P.B. and Chopra,S.L.:
    Persistance of malathion residues on the cauliflower crop.
    Punjab Agr Univ J Res. 7(2): 216-220, 1970.

59. Shetgar.S.S., Pawar.V.M., Puri.S.N., Raodeo,A.K. and Patil,V.K.:
    Residues and residual toxicity of monocroptophos in/on okra leaves.
    CA/100/019262S
    J. Maharashtra Agric Univ. 8(3): 260-262, 1983.

60. Shinde,V.K.R. and Yadava.C.P.S.:
    Effect of crop stage on phosphamidon residues dissapation from some
    vegetables Eggplants, chilis, peas.
    Pesticides.  Bombay.  Colour Publications.  15(1): 20-21, 1981.

61. Shpirt.M.B. et al:
    Establishment of differential "wating times" in treating fruit and
    vegetable crops with organophosphate pecticides.
    Vopr-Pitan.  (1): 70-72, 1982.
                       APPENDIX B: page 6 of 9

                                               66
-------
62. Shpirt, M.B., Salpagarof,N.S., and Genis.V.I.:
    Predicting the waiting period for harvesting pesticide-treated
    agricultural crops.
    CA/099/018077J
    Zashch. Rast..(Moscow) 4: 19-20, 1983.                                344

63. Singh,M. and Yadav.P.R.:
    Persistance of dimethoate and methyl-demeton on and on pea pod
    shells and their movement into pea grains.
    KEEP/83/09586
    Indian J Entomol. 43(3): 306-311, 1981.

64. Singh,M. and Gupta,D.S.:
    Dissapation of monocroptophos in/on chickpea crop.
    CA/097/176960E
    Indian J Entomol. 43(4): 373-377, 1981

65. Smith,C.N.  et al:
    The persistance and dissapearance by washoff and dryfall of
    metoxychlor from soybean foliage.--a prelimanary study.
    J.Environ.Sci.Health [B].  16(6): 777-794, 1981.

66. Spear, R. C., T. H. Milby, J. T. Leffingwell and W. J. Popendorf.
    Some Findings on the Exposure and Response of Pickers in Parathion-
    Treated Orange Groves.  Delivered at the Annual Meeting of The
    American Chemical Society, Los Angeles.  April 3, 1974.

67- Spear, Robert C., William J. Popendorf, John T. Leffingwell, and
    David Jenkins.  Parathion Residues on Citrus Foliage.  Decay and
    Composition as Related to Worker Hazard.  Journal of Agricultural
    and Food Chemistry 23:808-810 (1975).

68. Spear,R.C., Lee.Y.S., Leffingwell,J.T., and Jenkins,D.:
    Conversion of organophosphate insecticide parathion to paraoxon in
    toxic foliar residues: effect of dust level and ozone
    concentration.
    J. Agric Food Chem. 26(2): 434-436, 1978.

69. Spencer,W.F., Cliath.M.M., and Davis,K.R.:
    Persistance of parathion and its oxidation to paraoxon on the soil
    surface as related to worker reentry into treated crops.
    Bull Environ Contam Toxicol. 14(3): 265-272, 1975.

70. Staiff, D.C., S. W. Comer, and R. J. Foster.
    Residues of Parathion and Conversion Product on Apple and Peach
    Foliage Resulting from Repeated Spray Applications.
    Bull. Environmental Contamination and Toxicology 14:135-9 (1975).

71. Strankowski.K.J. and  Stanley,C.W.:
    Determination of residues of Mesurol and its sulfoxide and sulfone
    in plant, animal and soil samples.
    HEEP/82/04059
    J Agric Food Chem.  29(5): 1034-1037. 1981.
                       APPENDIX B:  page 7 of 9

                                                 67
-------
72. Thompson, Neal P., Herbert N. Nigg, and Robert F. Brooks.
    Dislodgeable Residue of Supracide on Citrus Leaves.
    J. Agricultural and Food Chemistry 27:589-592 (1979).
                                                                        345
73. Verma.S. and Dikshit.A.K.:
    Persistance of different insecticides against pea leaf-miner,
    Phytomyza atricornis Meige
    Indian J. Agric Sci. 52(1): 4-6, 1982.

74. Ware, G.W., Betty Estesen, and W. P. Cahill:
    Organophosphate Residues on Cotton in Arizona.
    Bull. Environmental Contamination and Toxicology 8:361-2 (1972).

75. Ware, G.W., Betty Estesen, and W. P. Cahill:
    Establishment of Reentry Intervals for Organqphosphate-Treated
    Cotton   Fields Based on Human  Data:  I. Ethyl and Methyl
    Parathion.
    Arch. Environmental Contamination and Toxicology 1:  48-59 (1973).

76. Ware, G. W., Betty Estesen, and W. P. Cahill:
    Dislodgeable Leaf Residues of Insecticides on Cotton.
    Bull. Environmental Contamination and Toxicology 2:434-7 (1974).

77. Ware et al:
    Dislodgeable Leaf Residues of Insecticides on Cotton.
    Bull Env Contam & Tox.  11(5):       1974.

78. Ware, G.W., Betty Estesen, and W. P- Cahill.
    Establishment of Reentry Intervals for Organophosphate-Treated
    Cotton   Fields Based on Human Data:  II. Azodrin, Ethyl and Methyl
    Parathion.
    Arch. Environmental Contamination and Toxicology 2:117-129 (1974).

79. Ware, G.W., D.P- Morgan, Betty Estesen, and W. P. Cahill.
    Establishment of Reentry Intervals for Organophosphate-Treated
    Cotton   Fields Based on Human Data:  III. 12 to 72 Hours Post-
    Treatment   Exposure to Monocrotophos, Ethyl- and Metyl Parathion.
    Arch. Environmental Contamination and Toxicology 3:  289-306 (1975).

80. Westlake, W.E., F.A. Gunther, and G.E. Carman:
    Worker Environment Research: Dioxathion (Delnav) Residues On and In
    Orange Fruits and Leaves, in Dislodgeable Particulate Matter, and
    in   the Soil Beneath Sprayed Trees.
    Arch. Environmental Contamination and Toxicology  1(1): 60-83 (1973).

81. Westlake,W.E., Ittig.M., Ott.D.E., and Gunther,F.A.:
    Persistance of residues of the insecticide phosphamidon on and in
    oranges, lemons, and grapefruit, and on and in orange leaves and in
    dried citrus pulp cattle feed.
    J Agric Food Chen. 21(5): 846-850, 1973.

82. Winterlin, Wray, J. Blair Bailey, L. Langbehn, and C. Mourer:
    Degradation of Parathion Applied to Peach Leaves.
    Pesticides Monitoring Journal 8:263-269 (1975).
                       APPENDIX B: page 8 of 9
                                                         68
-------
83. Winterlin, W., W. Kilgore, C. Mourer, R. Mull, G. Walker, J. Knaak
    and K. Maddy:  Dilodgeable Residues of Dialifor and Phosalone and
    Their Oxygen Analogs Following a Reported Worker-Injury Incident in
    the San Joaquin Valley, California.                                    346
    Bull. Environmental Contamination and Toxicology 20:255-260 (1978).

84. Winterlin, Wray, Gregory Hall, Charles Mourer, and Glen Walker:
    Dissipation of Parathion and Paraoxon on Citrus Foliage Dust and
    Dry Soil Surfaces in a Treated Orchard.
    Arch. Environmental Contamination & Toxicology.  11(1):11-121 (1982).

85. Winkler.V.W.  et al:
    Determination of norflurazon residues in mixed crop matrices.
    J.Assoc.Off.Anal.Chem. 64(6): 1309-1311, 1981.

86. Woodham,D.W., Reeves,R.G., Williams,C.B., Richardson,H.,and Bond.C.:
    Residues of dimethoate and its oxygen analog on and in citrus leaves
    following a helicopter treatment of the trees with dimethoate ultra-
    low volume concentrate and high volume spray.
    J Agric Food Chem. 22(4): 731-733, 1974.

87. Woodrow et al:
    Airborne and Surface Residues of Ethyl Parathion and its Conversion
    Products in a Treated Plum Orchard Environment.
    Arch Env Contam & Tox. 6:175-191 (1977).
                       APPENDIX B: page 9 of 9
                                                             69
-------
                                                              APPENDIX C
Appendix Q: Computer database format for reported residues as
            corresponds to INPUT FILE SPECIFICATION (as used by
            program "REEN1").

                                                         format  column
 LINE "1" (precedes each set of residues)

     chem  = name of chemical (abbreviated)                 A8      1-8
             (see "chemco" file for abbreviation code)
     nart  « article number (within reference system)       12    10-11
     ndset = dataset number (within article)                12    13-14
     nox   = number of oxons or other metabolites           II       16
             reported (one line nameing each oxon
             required after optional comments); nox
             cannot be larger than nor can names differ
             in sequence from those specified in the
             library file "chemco".
     loc   = location by state [and within state]           A3    18-20
               AK = Arkanas
               AZ = Arizona
               CA « California
                  CAi = Imperial Valley. CA
                  CAs - Southern CA
                  CAv « Central Valley, CA
               FL • Florida
               GA = Georgia
               IND- India
               SC = South Carolina
               TX = Texas
               WA = Washington
     crop  = crop code (see "cropco" library file);         A6    22-27
             selective searching by crop is an option
             in some programs, e.g. reen2.
     igph  « blank (0) if data are from a table;            II       29
             1 if data points are taken from a graph.
     form  = formulation (eg. SEC, 25WP, etc.)              A4    31-34
               CP = encapsulated, n * % active by weight
               EC = emulsifiable concentrate, n = pounds
                    active per gallon
               WP = wettable powder, n = % active by
                    weight
     aia   = mixture active ingredient per acre             F5.2  36-40
             (Ibs./acre) [1 Liter/hectare =
             0.892 gal/acrej
     gpa   = gallons water per acre                         F4.0  42-45
     ex    = extraction solvent used:                        II      47
               blank/default = aqueous with surfactant
               1 * hexane      4 » Methylene chloride
               2 s chloroform  5 = benzene
               3 « toluene     6 = other (see comments)
                Appendix C, page  1 of 3

                                                                 70
-------
   unit  = units reported                                  II      49
             blank/default = ug/cm2                                      348
             1 = ng/cm2      3 = ppm
             2 = mg/m2       4 = other
   nside = number of sides of leaf used to calculate       II      51
             residue
             1=1 side      2=2 sides
   dapp  = day of application                              12   53-54
   mapp  = month of application                            A3   56-58
   yapp  = year of application                             12   60-61
   ncomm = number of comment lines [optional up to 6]      II      63
   npun  = number of punches total [if unusual]            13   65-67
   isd   = blank if standard deviation not given;           II      69
           1 if given.

LINE  "2" (comments as specified by "ncomm")
   comm  = [optional] 1-6 comment line(s)                A79    1-79
           usually used to cite source reference
           or observations on application, data, etc.

LINE "3"
   lox   = metabolite name(s), one per line;               A30    1-30
           the number of names is not optional but
           must match "nox" as listed in LINE 1.

LINE "4"
   nsam  = number of residue intervals measured;           12     1-2
           1 line [manditory] corresponding to the
           number of residue lines which follow.

LINE "5" (Residue data)
   dpa   = days post application                          F4.0    1-4
   res   = residue value, in units as given in            F6.0   6-11
           original data set, unless transformed
           to standard units (ng/cm2) by REEN1 or
           similar calculation.
   sd    = standard deviation, if reported;               F6.0  13-18
           negative values are % relative deviation
           (coefficient of variation).
           An example is provided on the following page:
              Appendix C, page  2 of 3
71
-------
          example from file "pholon":
11
column

c see
h che-
e mco
m

1
0
n |n
a |d
r |s
t |e
It


n
0
X


2
0
1
o
c


3 4
0 0
c see |ijf |A Jg
r cro-|g|o |I jp
o pco|p|r |A |a
P Xm I 1
it i i
ii i i
i
(
e|u
x|n
s|i
o!t
1|
> 6
) 0
n|d |m Jy
s|a |a |a
i!p IP IP
d|p IP IP
e| 1 I


njn
c!p
o|u
m|
11

C
i
s
d


                                                                                      349
          ethion  :34.01:1:FL :orgval:  :  4EC: 3.00:1200: :l:2:29:may:75:4:160:1.
          Nigg, et al: Dislodgeable Residues of Ethion in Florida Citrus and
            Relationships to Weather Variables.
          Arch Env Contam & Tox.   6:  257-267,  1977.
          wet season
          ethion monoxon
           6
0: 99.4: 5.5:
1: 61.2: 26.3:
3: 7.4: 5.4:
5: 3.0: .9:
7: 2.8: 2.0:
14: 2.0: .9:
ethion :34.02:1:FL
dry season
ethion monoxon
9
0: 141.6: 25.8:
1: 32.8: 8.7:
3: 23.3: 1.8:
5: 16.6: 2.3:
7: 17.1: .9:
14: 16.7: 4.3:
21: 5.1: 1.1:
28: 3.4: 1.7:
35: 4.1: .7:
ethion :34.03:1:FL
wet season
ethion monoxon
6
0: 284.6: 142.9:
1: 124.6: 52.4:
etc. . .
4.1:
6.0:
3.9:
2.7:
1.7:
1.3:
:orgval:



12.0:
2.5:
3.2:
4.0:
5.1:
4.8:
3.9:
2.2:
2.2:
:orgval:



42.2:
21.7:

2.3:
3.6:
1.4:
.8:
1.1:
.5:
: 4EC: 4.50:1200:



1.9:
.2:
.2:
1.1:
.1:
.5:
.5:
1.5:
.3:
: 4EC: 4.50:1200:



3.2: : :
AD.
*t . O . . .

                                                         :l:2:10:nov:75:1:160:1.
                                                         :l:2:29:may:75:l:160:l.
                          Appendix C,  page   3 Of 3
                                                                          72
-------
                                                             APPENDIX D
Appendix D: Computer library of Unified  Field Model Chemcial Coefficients.

            "CHEMCO" is a tabulation of  chemical codes, their
            dermal LD50 values, the number  of metabolites
            possible for each chemical,  common or trade names,
            and whether the reentry interval is regulated by EPA
            (E) or California (C)  or both.  Data for dial,
            ethion, and mep are replicated  in a second set of
            parameters with the suffix "2"  in which 1D50 values
            for the metabolites were assumed to be different from
            the parent.
                                                                            350
columns allocated to each parameter are as follows:
1-8 10-13 15 17-41(=25) 42-66(=25)

azinme

carbaryl
car bop



chlort



dcroto
demet
dial

dia!2

diaz
dimeth

dioxat
endrin
epn
ethion


ethio2


etp

malat
mep

mep 2

i i
220 1
7
4000
40 3
40
40
40
58 3



42
11
124 1

124 1
12
640
610 1

120
15
127
153 2


153 2
15
7
14 1
1
4444
67 1

67 1
7
i
azinphosmethyl
azinphosmethyl oxon
carbaryl
carbophenothion
carbophenothion oxon
carbopheno. sulfoxide
carbophenothion sulfone
chlorthiophos
chlorthiophos sulfoxide
chlorthiophos sulfone
chlor. oxon sulfoxide
dicrotophos
demeton or demeton-s
dialifor
dialifor oxon
dialifor
dialifor oxon
diazinon
dimethoate
dimethoxon
dioxathion
endrin
epn
ethion
ethion monooxon
ethion dioxon
ethion
ethion monooxon
ethion dioxon
ethyl parathion
ethyl paraoxon
malathion
methyl parathion
methyl paraoxon
methyl parathion
methyl paraoxon

[Guthion]

[Sevin] 63-252 FC59500
[Trithion]



21923-239 TF15900



[Bidrin]
[Systox]
[Torak]

[Torak]

[Spectracide]
[Cygon],[De-Fend]

[Delnav]
-chlorinated HC-
[EPN-300]
[Ethion], [Nialate]


[Ethion], [Nialate]


[Phostox] , [Thiophos]

[Carbophos]
[Metron]

[Metron]

69 71
i i _ i _ i
i i i i
E C
n ii

E C
ii n
n ii
n ii




E C
E C
C
n
C
II
C
C
It
C
E C
E C
E C
n n
n n
E C
n n
ft ti
E C
n n
C
E C
n n
E C
n n
                Appendix D,  page  1  of 2
73
-------
methom
met ion

mevin
monoos
naled
oxyme
phenth
pholon

phorat
phosam
phosmet
tepp
trie

73 1
20
4.5 1
119
800
165
700 1
1530 1
380
4
124
1550
2.4
2000
endosulf
                methomyl
                methidathion
                 methidathion  oxon
                mevinphos
                 beta isomer
                monocrotophos
                naled
                oxydemeton-methyl
                phenthoate
                 phenthoate oxon
                phosalone
                 phosalone oxon
                phorate
                phosphamidon
                phosmet
                tetraethyl pyrophosate
                trichlorfon
  carbosulfan
  chlorpyrifos
  disulfoton
2 endosulfan
   alpha isomer
   beta isomer
  propargite
  oxymyl
  sulphur
[Lannate],[NudrinJ
[SupracideJ

[PhosdrinJ

[Azodrin]                  E
[Dibrom]
[Metasystox-R]             E
Fenthoate 2597-037 AI78750

[Zolone]

[Thimet]
[Dimecron]
[Imidan]
[TEPP],[Vapotone]
[Dylox] 52-686  TA07000

[Advantage]

[Di-syston]
[Thiodan]
                                                       C
                                                       C
                                                             351
                                                       c
                                                       II
                                                       c
                                                       c
                                                       c
                                                       c
c
II
                                         [Omite]
                                         [Vydate]
                chemical requested not on  file
                Appendix D, page  2 Of 2
                                              74
-------
                                                                APPENDIX E
Appendix E: Computer library of Unified Field Model Crop Coefficients.      352

            "CROPCO" is a tabulation of crop codes, their dosing
            coefficient (K,), the full name of the crop, and the
            leaf density (estimated (as noted by ?) when
            otherwise unknown) to be used to convert residue
            reported as ppm to ng/cm2.  For purposes of
            calculation, when the K. was unknown,  a conservative
            (high) default value corresponding to  5.0 (5000
            cm2/hr) was assumed.  Some replicated  crop codes were
            included to match on crops coded within the data base
            which were sometimes right-justified.

            columns allocated to each parameter are as follows:
            1-6        12-15      23-42(=20)           45-48 49
1 1
apple
apple
artchk
cabbag
chili
chili
citrus
cotton
cowpea
grape
grape
graper
grapet
grapew
grapfr
lemon
lemon
lettuc
mustar
okra
okra
orange
orgnav
orgval
peach
peach
plum
plum
sobean
tobaco
tomato
wheat
kd
i i i i i
3.5
3.5




5.1


3.5
3.5
3.5
3.5
3.5
5.1
5.1
5.1
5.1



5.1
5.1
5.1
1.9
1.9
1.9
1.9




=
i i i i i i i
apple
apple
artichoke
cabbage
chili
chili
citrus
cotton
cowpea
grape-unclassified
grape-unclassified
grape-raisin
grape-table
grape-wine
grapefruit
lemon
lemon
lettuce-unclassified
mustard
okra
okra
orange-unclassified
orange-navel
orange- Valencia
peach
peach
plum
plum
soybean
tobacco
tomato-unclassified
wheat
crop not on file

20. ?
20. ?




27.5
25. ?

21.
21.
21.
21.
21.
27.5
27.5
27.5




27.5
27.5
27.5
20. ?
20. ?
20. ?
20. ?

20. ?
17. ?

=
                                                              ug/cm2
                Appendix E,  page  1  of 1
                                                            75
-------
APPENDIX F: A Generalized Pesticide Decay Model Computer Program.        _    353

     In order to interpolate, extrapolate, and tabulate two-component (parent
and one metabolite) residue data from any single study to a preselected
criterion for re-entry days of specific interest to this report, a generalized
four compartment submodel was investigated.  This submodel is depicted
diagrammatically in Figure Fl.  Conceptually, this submodel assumes that
the initial parent residue is partitioned on the leaf into fast and slow
decay compartments.  Each of these compartments can decay by two routes; it
can either become a metabolite (e.g. oxon) or become nonmeasureable (e.g.
by vaporization, hydrolysis, leaf absorption, etc).  One additional route
attributable to material in the fast decay compartment is a transition by
various mechanisms from the relatively unstable (fast) compartment into the
environmentally protected (slow) decay compartment.  The metabolite is also
partitioned into two parallel fast and slow compartments both initially and
as a result of decay from the parent, and both metabolite compartments are
susceptable to transitional pathways identical to their corresponding
parent compartments.
     In nature, the partitioning is dictated by natural forces.  In a model,
the partitioning is accomplished by fitting coefficients of the equations
characterizing each compartment and pathway to the experimental data .
Pesticide decay is most commonly characterized by first-order differential
equations, i.e. that the rate of decay is proportional to the amount material
present (e.g. Popendorf and Leffingwell, 1978).  The subscript numbers
assigned in Figure Fl were chosen pragmatically to permit the modelling of
single component pesticides (those without measureable metabolites) by only
the first 5 coefficients, versus 12 for two component (four compartmet)
residues.  Thus, the amount of material present in each compartment is
designated as follows:
                   fast compartment      slow compartment
     parent              a1                    a^
     metabolite          a..                   a..

The corresponding kinetic coefficients were designated as follows:
                   fast compartment      slow compartment
     parent to           a.                    a,
       nonmeasureable
     parent fast         a..
       to slow
     parent to           a&                    a._
       metabolite
     metabolite  fast    a7
       to slow
     metabolite  to      a.                    a.
       nonmeasureable

     A generalized pesticide decay FORTRAN computer program was developed
during this study to fit the coefficients to the reported data.  A number of
difficulties were encountered with this approach, among which were that it was
time consuming (requiring considerable operator interaction), the data was
often sparse or did not include initial residues, and the improvements in
smoothing the variability among reported residues within any one study was
outweighed by the much larger variability between studies for any given
pesticide.  Nonetheless, the following program can estimate the coefficients of
the model described above.

                                                            76
                     APPENDIX F: page  1 of 22
-------
                                              354
APPENDIX F: page  2 of  22        -      ' '
-------
                                                              355
  "fast"
  Parent
  "fast"
Metabolite

    An
                               Y
                   nonmeasureable
  "slow"
  Parent
   "slow"
Metabolite

    A12
   Figure Fl.   Schematic diagram of generalized pesticide
   decay model with zero or one metabolite.  Coefficients
   defined as  used in accompaning algorithm.
                                                  78
-------
      program REPAID
APPENDIX  F
       356
C	 EPA version of Rose MAIN LINE PROGRAM
C	 originally adapted from ROSENBROCK HILLCLIMB program in
C                'OPTIMIZATION TECHNIQUES WITH FORTRAN'
C                   J.L. KUESTER & J. MIZE PG 386.
C	 THIS SPECIAL HILLCLIMB PACKAGE WAS WRITTEN FOR RESIDUE DECAY ANALYSIS
C     with a model of 10 coefficients.
C	 MODIFICATIONS FOR IBM 1130 BY W. POPENDORF (1974)
C	 further modifications in lower case for FORTRAN 77 by W. Popendorf (1984)
C     USE IN GOOD HEALTH.


C	 THE FOLLOWING VARIABLES can be read from a special RPRAM file
C             [defaults are provided for in all cases following line 36]:
C     LOOPY = MAXIMUM NUMBER OF STAGES TO BE CALCULATED  (10 to 20 IS GOOD)
C     NCOEF = NUMBER OF COEFFICIENTS (UNKNOWNS) WITH FIRST GUESSES
C             [usually set to 0 to use defaults]
C     NOASK = an index setting logical LASK to bypass user options after
C             selecting filenames, thus operating in an unattended batch mode
C     NSTEP - STEP SIZE CONTROLER: 0 FOR ORIGINAL STEP SIZE AFTER ROTATION
C                                  1 FOR RETENTION OF SIZE PRIOR TO ROTATION
C     PR      NUMBER OF STAGES BETWEEN PRINTED OUTPUTS  [3 is default];
C             A stage is when all E's have reversed direction twice.
C             Because 2 is an even number, this routine has a tendancy to
C             overestimate all coefficients (which for pesticide decay tends
C             to underestimate especially oxons); so it is better to
C             underestimate the value of each first guess.
C     delF  = THE ACCEPTABLE LIMITING DIFFERENCE IN THE OBJECTIVE FUNCTION
C             BETWEEN PRESENT AND PRIOR STAGE  [l.OE-6]
C     EV      Sets VECTOR OF INITIAL STEP SIZES [ 0.01 ];
C             original ROSE permitted setting individual E's.
C	 the following are PROGRAMMED VARIABLES
C     DA    = A GENERAL STORAGE VECTOR (MAX LENGTH LIMITED BY DIMENSION)
C     DELE  = THE MINIMUM STEP SIZE BEFORE PLOTTING RESULTS FOR USER
C     LA      MAXIMUM NUMBER OF NCOEF PERMITTED BY ARRAY LIMITS AS WRITTEN
C     MM    = +1 FOR MAXIMIZATION	 -1 FOR MINIMIZATION
C     NCC   = NUMBER OF VARIABLES PLUS IMPLICIT CONSTRAINTS (SPECIFIED BY CX)
C     N     = NCC (see line 40-2)
C     NinDA = NUMBER OF DATA POINTS TO BE READ AND STORED IN DA
C     NIV   = NUMBER OF INPUT VARIABLES (KNOWNS) WITHIN STORED DATA SET
C     NPAR  = MAXIMUM NUMBER OF DA PERMITTED BY ARRAY LIMITS AS WRITTEN
C     X       MULTIPLICATION or Sealer FACTORS UPON FIRST GUESSES;
C             these are the variables actual optimized.
C
C	 INPUT FILE SPECIFICATION (same file as for "REEN1)
C     chem  = name of chemical (abbreviated)                  A8
C             (see LDvals file for abbreviation code)
C     nart  = article number                                  12
C     ndset - dataset number                                  12
C     nox   = number of oxons or other metabolites reported   II
C     loc   = location by state (except for CA: location by   A3
C               region within state, eg.


                     APPENDIX F:  page  3 of 22               79
-------
C               AZ = Arizona
C               CA « California                                         357
C                  CAi • Imperial Valley, CA
C                  CAs « Southern CA
C                  CAv = Central Valley, CA
C               FL = Florida
C               SC = South Carolina
C               TX = Texas
C               WA « Washington
C     crop  = crop code (see cropco file)                     A6
C     igph  * blank (0) if data are from a table,             II
C              1 if data points are taken from a graph
C     form  » formulation (eg. SEC, 25WP: etc.)               A4
C               CP = encapsulated
C               EC * emulsifiable concentrate
C               WP = wettable powder
C     aia   * active ingredient per acre (Ibs./acre)          F5.2
C     gpa   = gallons water per acre                          F4.0
C     ex    = extraction solvent used:                        II
C               blank/default * aqueous
C               1s hexane      4 « Me chloride
C               2     - chloroform  5 » benzene
C               3     - toluene     6 = other (see comments)
C     unit  = units reported                            *     II
C               blank/default « ug/cm2
C               1     * ng/cm2      3 * ppm
C               2     « mg/m2       4 « other
C     nside = number of sides of leaf used to calculate       II
C               residue
C               1=1 side      2 « 2 sides
C     dapp  = day of application                              12
C     mapp  = month of application                            A3
C     yapp  = year of application                             12
C     ncomc «= number of comment cards, up to 6                II
C     npun  = number of punches total                         13
C     isd   = blank if standard deviation not given,          II
C             1 if given
C     comm  = comment line                                    A80
C     lox   = metabolite name                                 A30
C     nsam  = number of residue intervals measured            12
C     dpa   = days post application                           F4.0
C     res   = residue value, in units as given in             F6.0
C             original data set
C     sd    * standard deviation, if given                    F6.0
C

      INTEGER      PR.NE(IO)
      REAL         LC,DA(120)
      real         AL(10),B(10t10).BX(10),D(10),E(10),EINT(10).H(10)(
     +             PH(10),V(10,10),W(10,10),X(10),Z(10)
      integer      ex, unit, dapp, yapp
      real         dpa(15), res(15,3), sd(15,3), adif(3),pdif(3)
      character*!  file
      character*3  loc, mapp
      character*4  form
                     APPENDIX F: page  4 of 22
80
-------
       character*6   crop
       character^S   chem
       character'" 12  input, output, newin
       character*30  lox(2)
       characterise  spec, comro(6), data(15)
       logical      lfile,lask,init,term

 C	  ni = unit specifier for input filename
 C	  no =  "      "       "  output   "  various fit results
 C....  nu =  "      "       "  user (screen and console)
 C	nx =  "      "       "  new input file with coefficients
 C	npram =      "       "  rpram  "    "  (rose parameters)
       NU    =0
       NI    =2
       NO    =3
       NX    = 4
       NPRAM = 5
       maxc  = 8
       open (npram,file='rpramlO')

     2  write  (nu,1003)
  1003  format (' Type pesticide INPUT filename, up to 12 characters:1)
 C....  (for code, see LDvals library file)...
       read   (nu.lOOA) input
  1004  format (a!2)
       if     ((input .eq. 'quit').or.(input .eq. 'exit').or.
     +       (input .eq. 'stop').or.(input .eq. 'end')) go to 30000
  1006  format (al)
       open   (ni, file=input)
       rewind ni
       xv    =0.0

       write  (nu,1007)
  1007  format (/,' A duplicate inputfile SHALL be created herein with new
     + model coefficients',/,' Type NEW filename, up to 12 characters:')
       read   (nu,1004) newin
       open   (nx, file=newin, status='new')

       write  (nu.1008)
  1008  format(/,' Do you want model results also written to disk? Y/N ')
       read   (nu,1006) file
       call yes(file.lfile)
       if      (.not. Ifile) go to 20

       write  (nu,1009)
  1009  format  (' Type general OUTPUT filename,  up to 12 characters:1)
       read    (nu,1004) output
       open    (no, file=output, status='new*)
       rewind  no

   20 continue
C.... reading data specification line
      read   (ni,2001,end=24) chem,nart,ndset,nox,loc,crop,igph,form,
     +                      aia,gpa,ex,unit,ns ide,dapp,mapp,yapp,ncomc,
     +                      npun.isd
        358
                     APPENDIX F: page  5 of 22
81
-------
      write  (nu,2001      ) chem,nart,ndset,nox,loc,crop,igph,form,
     +                      aia.gpa,ex,unit,nside.dapp.mapp,yapp,ncomc,
     +                      npun.isd
 2001 format (a8,Ix,2(12,Ix),il,lx,a3,Ix.a6,Ix,il,lx,a4,lx,f5.2,Ix.f4.0
     +        ,lx,3-(il, Ix),i2,lx,a3,Ix,i2,lx.il,Ix,i3,lx.il)
      backspace ni
      read   (ni,2002) spec
      nres  = nox+1
      NCOEF « 4+(2*nox)
      if     (nsam .eq. 2 .and. nox .eq.  0) NCOEF=2

C.... reading up to 6 comment lines
      read   (ni,2002) (comm(i),i=l,ncomc)
      write  (nu,2002) (comm(i),i=l,ncomc)
 2002 format (a80)
C.... reading the name of the oxons or other metabolites
C.... and model coefficients 9 and 10
      read   (ni,2003) lox,da(9),da(10)
      write  (nu,2003) lox,da(9),da(10)
 2003 format (2a30,2el0.4)
C.... reading the number of samples in the following set of data,
C.... also the number of previous runs and goodness of  fit  indices
      read   (ni,2004) nsara,nruns,(pdif(kj.k*!,nres),(adif(k),k=l,nres)
      write  (nu,2004) nsam,nruns,(pdif(k),k=l,nres),(adif(k),k=l,nres)
 2004 format (I2,i3,6el0.4)
C.... reading residue data ...
      do 21 j = l.nsam
      read   (ni,2005) dpa(j),(res(j,k),sd(j,k),k=l,nres)
      write  (nu,2005) dpa(j),(res(j,k),sd(j,k),k=l,nres)
      backspace ni
      read   (ni,2002)   data(j)
   21 continue
 2005 format (f4.0,lx,6(f6.0,lx))
C.... reading model coefficients 1-8
C.... do-loop sets da s previous A (or Z)
C.... unless this is the first run of program with new  data  (pesticide)  file
C.... then loop sets da = 0 in preparation for subroutine "TX".
      DO 22 i = l.maxc
      if     (xv .ne. 1.0) z(i)=0.0
      da(i) = z(i)
   22 continue
      if     (nruns .eq. 0) go to 23
      READ   (NI.2006) (DA(i),i=l,maxc)
      write  (nu,2006) (DA(i),i=l,maxc)
 2006 FORMAT (8E10.4)

   23 if     ((nsam*nres) .ge. ncoef) go  to 35
      write  (no,1013) nart.ndset
      write  (nu,1013) nart.ndset
 1013 format ('  The data for article1,i3,' dataset',i2,
     +       '  are insufficient to model!1)
      go to 20
   24 write  (nu,*) 'Reading end of old input datafile.'
      go to 2
                     APPENDIX F:  page  6 of 22              Q2
-------
 C....  subroutine  to convert data to ug/cm2 projected area
 C....  units  may be nonstandard and must be individualy converted.
    35  call units(res,sd,nsam.nres,unit,nside,crop)
       if      (unit  .It. 4) go to 36
       write   (no,1014) nart, ndset
       write   (nu,1014) nart, ndset
  1014  format (' Nonstandard units in article1,i3,' dataset',i3,/,
     +        ' - further calculations are discontinued!1)
       go  to  20
    36  continue

       CALL tx(DA,dpa,res,nsam.nres,ncoef)

       lask  = .true.
       rewind npram
       read   (npram,4001) loopy,nco,noask,nstep,pr.delF.ev
  4001  format (5i2,2fl0.9)
if
if
if
if
if
if
if
LA
dele
MM
NCC
next
niv
NinDA
(loopy .eq.
(nco .ne.
(noask .eq.
(nstep .ne.
(pr .eq.
(delF.eq. 0
(ev .eq. 0
= 10
= l.e-8
= -1
= ncoef
= 1
= 2+nox
0)
0)
0)
0)
0)
.0)
.0)






loopy =
ncoef =
lask •
nstep =
pr
delF -
ev =






20
nco
.false.
1
3
l.e-6
0.01






= NCOEF+(nsara*niv)

                                                                        *
                                                                        *
   37 CONTINUE                                                          *
      XV    = 1.0                                                       *
      DO 200 K = l.maxc                                                 *
      E(K)  = EV                                                        *
      X(K)  = XV                                                        *
      Z(K)  =0.0                                                       ft
  200 CONTINUE                                                          *
  300 CONTINUE                                                          *
      WRITE  (nu,3013) nart, ndset,ncoef,nsam,chem,crop                 *
 3013 FORMAT (///,' Article Number1,13,', data set #',I3,/,f Results of1*
     +,i3, ' coefficient decay model for ',i2,lx,a8,' sample points on '*
     +,a6, '.')                                                         *
      if     (.not. Ifile) go to 39                                     *
      write  (no,3013) nart, ndset,ncoef,nsam,chem,crop                 *

C	 pseudoORIGINAL ROSE BEGINS HERE
   39 INIT   - .true.
      TERM  . = .false.
      LAP    =0
      LOOP   « 0
      KOUNT  = 0
      Fl     = 0.0

                                                              :       83
                    APPENDIX F: page  7 of 22
-------
      DO 40 K= l.NCC
   40 AL(K)  = (CH(X,DA,NCC,NinDA,K)-CG(X.DA,NCC,NinDA,K))*.001
      DO 60 J= l.NCOEF                                                   361
      DO 60 1= l.NCOEF
      V(I,J) = 0.0
      IF       (I-J) 60,61,60
   61 V(I,J) = 1.0
   60 CONTINUE
      DO 62 K= l.NCOEF
      EINT(K)= E(K)
   62 CONTINUE
C...
   64 continue
      write  (nu,1020)                                                  *
 1020 format (' Stage/Limit Stage/Print_Limit  #_F._Evals.   Avg._F_Error*
     +     Avg. Step Size1)            ~        ~                       *
   65 DO 70 K  = l.NCOEF
C.... line 65 starts new stage
C	 Nstep=0 means return to original step size (EINT) after rotation
      IF     (NSTEP-0) 67,66,67
   66 E(K)     - EINT(K)
   67 NE(K)    = 0
   70 D(K)     « 0.0
      FBEST    - Fl
C.... an implicit loop on I from 1 to ncoef starts here, ends line 441.  .  .
   80 I        =1
      IF     (INIT)  go to 120
   90 DO 95  K = l.NCOEF
   95 X(K)     = X(K) + E(I)*V(I,K)
  100 DO 110 j " 1,ncoef
      XC       • CX(X,DA,NCC,NinDA,J)
      LC       = CG(X,DA,NCC,NinDA,J)
      UC       = CH(X,DA,NCC,NinDA,J)
      if (xc .le. Ic) go to 420
      if (xc .ge. uc) go to 420
  110 continue

  120 Fl       = MM * F(X,DA,NCOEF,NinDA.NIV.dpa,res,nres.nsam)
      KOUNT    • KOUNT + 1
      IF (INIT) FO=MM*l.E+38
      IF (ABS(FBEST-Fl) .le. delF) go to 125
  122 TERM     - .true.
      GO TO 450
  125 CONTINUE

C.... an implicit loop on J from 1 to ncoef starts here, ends line 211.  .  .
      J        - 1
  130 h(j)     - fO
*     the following section preceded by * was bypassed from the original prog.
*     BW    '   • AL(J)
*     XC       • CX(X,DA,NCC,NinDA,J)
*     LC       - CG(X,DA,NCC,NinDA,J)
*     UC       = CH(X,DA,NCC,NinDA,J)


                     APPENDIX F: page  8 of 22
                                                                   84
-------
C ---- remember, F1=MM*F. FO=lastFl, and MM=-1 for minimum error fit;
C ---- thus, it is desired that Fl be .gt. FO; else, change direction.
      IF (Fl .It. FO) go to 420
*     IF (XC .It. (LC+ALU))) go to 160
*     IF (XC .gt. (UC-AL(J))) go to 170
*     GO TO 210
* 160 PW    = (LC+BW-XO/BW
*     GO TO 180
* 170 PW    = (XC-UC+BVO/BW
* 180 PH(J) = 1.0-3.0*PW+4.0*PW**2-2.0+PW**3
* 190 Fl    = H(J)+(F1-H(J))*PH(J)

* 210 CONTINUE
*     IF (J-NCC)        211,220,211
* 211 J     -  J+l
*     GO TO 130
C.... end of implicit J loop ..................
  220 INIT  = .false.
            = 3.0*E(I)
      FO    = Fl
      IF (NE(I) .EQ. 0) NE(I) » 1

  230 DO 240  K - l.NCOEF
      IF (NE(K) .LT. 2) GO TO 440
C.... note a "stage" is when ALL X advances have changed direction twice.
  240 CONTINUE
C	 AXES ROTATION  . . to line 420 ...
C	 BMAG » progress
C	 BBMAG = lateral progress
      DO 250 Kl = l.NCOEF
      DO 250 K2 = l.NCOEF
  250 W(K1,K2) = 0.0
      DO 260 Kl = l.NCOEF
      DO 260 K2 - l.NCOEF
      DO 265 K3 = Kl.NCOEF
  265 WU1.K2) = D(K3)*V(K3,K2)+W(K1,K2)
  260 B(K1,K2)  = W(K1,K2)
      BMAG      = 0.0
      DO 280 K '= l.NCOEF
      BMAG      = BMAG+B(1,K)**2
  280 CONTINUE
      BMAG      = SQRT(BMAG)
      BX(1)     = BMAG
      DO 310 K  = l.NCOEF
  310 V(1,K)    = B(1,K)/BMAG

      DO 340 Kl = 2.NCOEF
      DO 340 K2 = l.NCOEF
      SUMVM     » 0.0
      DO 330 K3 = 1.K1-1
      SUMAV     - 0.0
      DO 320 K4 « l.NCOEF
  320 SUMAV     = SUMAV+W(K1,K4)*V(K3,K4)
                     APPENDIX F: page  9 of 22       '       05
-------
  330 SUMVM     = SUMAV*V(K3,K2)+SUMVM
  340 BCK1.K2)  = W(K1,K2) -SUMVM

      DO 360 Kl = 2.NCOEF                                                 363
      BBMAG     = 0.0
      DO 350 K2 = l.NCOEF
  350 BBMAG     = BBMAG+B(K1,K2)**2
      BBMAG     - SQRT( BBMAG)
      DO 360 K2 = l.NCOEF
  360 V(K1,K2)  - B(K1,K2)/BBMAG

      EA        = 0.0                                                   *
      DO 399  k = l.ncoef                                               *
      EA        - EA + abs(E(k))                                        *
  399 continue                                                          *
      EA        » EA / ncoef                                            *
      Ferr      = FO / (nsam*nres)                                      *
      LOOP      * LOOP+1
      LAP       = LAP+1
      write  (nu,1021) loop, loopy, lap, pr.kount, Ferr, EA                  *
 1021 format (3x,i2,' / ',i2,5x,i3,' /' ,i2,10x,i5,8x, Ipel2.5,5x,lpel2.5)*
      IF (LAP-PR)               65,450,65
C. . . . line 420 etc either (1) lists coefficients and indicates starting point
C. . . . has violated constraints if INIT is true, or
C. . . . (2) undoes array step advance (E) and reverses E(I) 2/3 of a step.
  420 IF (INIT) go to 450
  421 DO 430 K = l.NCOEF
  430 X(K)     « X(K) - E(I)*V(I,K)
      IF (abs(E(I» .It. DELE)   go to 122
      IF (NE(I) .ge. 1)          NE(I) » 2
      GO TO 230

  440 CONTINUE
      IF (I-NCOEF)        441,80,441
  441 I        = 1+1
      GO TO 90
C.... end of implicit I loop ..............
  450 continue
      DO 455 I * l.NCOEF                                                *
  455 Z(I)     « X(I)*DA(I)                                             *
C ____ PRINT CURRENT VALUES OF X AND Z (COEFFICIENTS)
      WRITE  (nu,3005)
 3005 FORMAT (/,'  Sealers to 1st Guesses,  Model Coefficients,     and S*
     +tep Sizes')
      WRITE  (nu,3006) (I.X(I).I.Z(D.I.E(I), 1=1, NCOEF)
 3006 FORMAT (: ,4X,2HX( ,I1,4H) - ,OpF10.6,5X,2HA( ,I1,4H) = ,  1PE11.4,
     +                                    3X,2HS(,I2,4H) - .  1PE12.4)

      LAP      • 0
  461 IF (INIT)        go to 470
  462 IF (TERM)        go to 480
  463 IF (LOOP-LOOPY)  64,480,480
                     APPENDIX F: page  10 of 22
-------
  470 WRITE  (nu,007)
    7 FORMAT (///, 2X,
     + 'THE STARTING POINT APPEARS TO HAVE VIOLATED THE CONSTRAINTS')
               -o.o                                                        354
      go to 37

  480 CONTINUE
      if (.not. Ifile) go to 601
      WRITE  (NO,3003)
 3003 FORMAT (' At exit1, /,2X,5HSTAGE,4X,8HFUNCTION,5X,8HPROGRESS,5X,
     +         16HLATERAL PROGRESS,3X,'# of F EVALS.1  )
      WRITE  (NO,3004) LOOP,FO,BMAG,BBMAG,KOUNT
 3004 FORMAT (1H .I4.3E15.5,10x,I5)
      WRITE  (NO,3005)
      WRITE  (NO,3006) (I,X(I),I,Z(I).I,E(I),  I=1,NCOEF)                 *

C	This section TO LIST AND PLOT THE MEASURED AND PREDICTED VALUES.
C	THE TELL SUBROUTINE WAS DEVELOPED DURING THE INITIAL PLANNING (1974),
C	BUT RPI WAS DEVELOPED FROM 'DKRP1 DURING 1976.   SEE PROGRAM DK.

  601 continue
  605 CALL RPI  (   z.ncoef,dpa,res,nsam,nres,nart,ndset,next,lfile)
      CALL TELL (da,z,ncoef,dpa,res,nsam,nres.nart.ndset,next,Ifile,
     +           adif.pdif)

C.... ask if coefficients are OK,  then
C.... recalulate if necessary or go on to next set of  data
      if (lask) go to 611
  607 write  (nu,3021)
 3021 format (' Type ''//'' of any coefficient you wish to reset,',
     +      /,'    a ''II11 if you wish to reoptimize  from here,  or1,
     +      /,'    a "0" if this is OK and to continue:1  )
      read   (nu,*) next
      next = next +1
      go to  (611,612,612,612,612,612,612,612,612,612,612,619),  next

C—. the following write statements  recreate the specification line,
C.... comment line(s), metabolite-name line,  sample-number line,
C.... residue lines, and coefficient  lines,  respectively.
  611 nruns = nruns+1
      write  (nx,2002)  spec
      write .(nx,2002) (comm(i),i=l,ncomc)
      write  (nx,2003) lox,z(9),z(10)
      write  (nx,2004) nsam,nruns,(pdif(k),k=l,nres),(adif(k),k=l,nres)
      write  (nx,2002) (data(i),i=l,nsam)
      write  (nx.2006) (z(j),j=l,maxc)
      next  = 0
      CALL RPI  (   z.ncoef,dpa,res,nsam,nres.nart.ndset,next,Ifile)
      CALL TELL (da,z.ncoef,dpa,res,nsam,nres.nart.ndset,next,Ifile,
     +           adif.pdif)
      go to 20

 612 next  = next - 1
      write  (nu,3023) next.z(next)
 3023 format ('  The current value  of  coef(',i2,') = MpelO.4,/,


                     APPENDIX F: page  11  of 22
-------
     +        '  Type the desired new value; minus value to end1)
      read   (nu,*) z(next)
C.... a "backdoor" exit with filesave is provided here for user to manually     _
C.... set any coefficient to a MINUS value.  Use it in good health.             365
      if     (z(next))   615,613,614
  613 z(next) = da(next)*x(next)
      go to 607
  614 da(next)= z(next)
      x(next) =0.0
      write  (nu,3024)
 3024 format ('  Type "//" of another coefficient you wish to reset,1,
     +      /,'     a "11" to see fit with reset coefs, or1,
     4-      /,'     a "0" to reoptimize from here,1  )
      read   (nu,*) next
      next = next +1
      go to (619,612,612,612,612,612,612,612,612,612,612,605), next

  615 z(next) * da(next)*x(next)
      nruns   = nruns+1
      write  (nx,2002)  spec
      write  (nx,2002) (comm(i),i=l,ncomc)
      write  (nx,2003) lox,z(9),z(10)
      write  (nx,2004) nsam,nruns,(pdif(k),k=l,nres),(adif(k),k=l,nres)
      write  (nx,2002) (data(i),i=l,nsam),
      write  (nx,2006) (z(j),j=l,maxc)
      next * 0
      CALL RP1  (   z,ncoef,dpa,res,nsam,nres,nart,ndset,next,Ifile)
      CALL TELL (da,z,ncoef,dpa,res,nsam,nres.nart.ndset,next,Ifile,
     +           adif.pdif)
      go to 2

  619 next = 1
      DO 620 j = l.ncoef
  620 if (x(j) .ne. 0.0) da(j)-da(j)*x(j)
      go to   37

C	 A few notes on the logic of "next"
C     initially set next * 1 at line 36+7.
C     in RP1  line 130+2: if next=0 (and other conditions) the plot is copied
C                      onto file NO for later examination.
C     in TELL line 1+2: unless next=0, results will not be written to file NO;
C             line 96: if next=0, model error is not typed to the screen (in
C                      otherwords, next should = 0 only on last pass thru TELL)
C     in REPA line 607+1: read next from screen, il, therefore -Knext<10;
C                  607+2: next=next+l and used in computed goto;
C        if next=0, next reset=0,
C                   call TELL (for final output),
C                   goto 20 and on to 36+7 as initially run;
C        if 0
-------
      subroutine units (res,sd.nsam.nres,unit,sides,crop)
C	 to convert residue units to ug/cm2 and 1-side (projected area)         "^ 6 6
C       unit   = units reported
C                  blank/default = ug/cm2
C                  1       ng/cm2      3 = ppm
C                  2     = mg/m2       4 = other
      integer     sides, unit
      real        res(15,3), sd(15,3)
      character*6 crop

      if (unit .eq. 0) go to 17
       do 16 k=l,nres
          do 15 j=l,nsam
             if (unit.gt.l) go to 12
             res(j,k) = res(j,k)/1000.
             go to 15
   12        if (unit.gt.2) go to 13
             res(j.k) = res(j,k)/10.
             go to 15
   13        if (unit.gt.3) go to 20
             call conppm (res,sd,crop,unit,nsam.nres)
   15        continue
   16     continue
   17  if (sides.ne.2) go to 20
       do 19 k=l,nres
          do 18 j=l,nsam
             res(j.k) = res(j,k)*2.
   18        continue
   19     continue
   20  continue
       return
       end
C	
      Subroutine conppm (res,sd,crop,unit,nsam.nres)
C.... to convert ppm to ng/cm2
      integer     unit
      dimension   res(15,3), sd(15,3)
      character*6 crop
C.... for now, hand calc...
      write (nu,*) ' residue data must be converted from ppm1
      unit * 9
      return
      end
C	
      subroutine tx (da,dpa,res,nsam,nres,ncoef)
C.... to provide preset guesses into DA as a first starting point
C     if the coefficients in input datafile were zero (previously
C     estimated coefficients will be used after the first dset), and
C	 to copy dpa and residue data into remaining DA array expected by ROSE;
C     in the process, it is assumed that any dpa-0 (exactly) can in reality
C     be no less than 0.1 (or two hours post application).

      real da(120),dpa(15),res(15,3),wag(10)
      data wag/1.,.3,.3,.3,.05,.1,.3,.05,.05,.1/

                                                               89
                     APPENDIX F: page  13 of 22
-------
      if (da(l) .ne.  0.0) go to 20
      do 10  k = l.ncoef
      da(k)    = wag(k)
   10 continue                                                          '      7 £ 7
   20 do 30  j = l.nsam                                                       ^ ° '
      k        = ncoef+l+((l+nres)*(j-l))
      da(k)    = dpa(j)
      do 30  i = l.nres
      da(k+i)  = res(j.i)
   30 continue
      if (dpa(l) .eq. 0.0) da(ncoef+l)=0.1
      return
      end
C	
      FUNCTION  F(X,DA,N,NinDA,NIV,dpa,res,nres,nsam)
      DIMENSION X(10),DA(120),A(10),dpa(15),res(15,3)
      DO 2 I - 1,N
      A(I)   = DA(I)*X(I)
    2 CONTINUE
      FX     = 0.
O»»USER WORKING AREA	««««««««««««««««««
   27 CONTINUE
      A23    = a(2)+a(3)
      A234   = A23 +a(4)
      A56    = a(5)+a(6)
      A78    = a(7Ha(8)
      Alx3   = a(l)*a(3)
      A13d6  = Alx3/(A56-A234)
      AlxA   = a(l)*a(4)
      A14d8  - AlxA/(A78-A23A)
      if (nres .gt. 3) STOP 'NRES error in FUNCTION F1
      DO 70 i= l.nsam
      di     = dpa(i)
      if (dpa(i) .eq. 0.0) di=0.1
      go to (55,53,51),nres
   51 Stop 'No model is provided for 2 metabolites!1
   53 F2     =                (A14d8*(exp(-A234*di)-exp(-A78 *di)))      XI
     + +(((a(7)*A14d8)+(a(6)*A13d6))*(exp(-A234*di)-exp(-a(9)*di))/
     +                                                     (a(9)-A23A))  X2
     + +(((a(7)*AUd8/(a(9)-A78)))  *(exp(-A78 *di)-exp(-a(9)*di)))      X2
     + +((a(6)*(a(10)-A13d6))       *(exp(-A56 *di)-exp(-a(9)*di))/
     +                                                     (a(9)-A56))   X2
      IF (res(i,2) .gt. 0.0 .and. F2 .gt. 0.0)
     +    FX = FX + exp(ABS(alog(res(i,2)/F2))) -1.

   55 Fl     = (a(l) *exp(-A234*di))
     + +   (A13d6*exp(-A234*di)) + ((a(10)-A13d6)*exp(-A56*di))
      IF (res(i.l) .gt. 0.0 .and. Fl .gt. 0.0)
     +    FX - FX + exp(ABS(alog(res(i,l)/Fl))) -1.
   70 continue
O»»USER WORKING AREA	«««««««««««««««««««
    1 CONTINUE
      F  « FX
      RETURN
      END


                     APPENDIX F: page  14 of 22

                                                                    90
-------
      FUNCTION CX(X,DA,N,NinDA,K)                                          368
      DIMENSION X(10). DA(120)
      CX = X(K)
      RETURN
      END
C	
      FUNCTION CG(X,DA,N,NinDA,K)
      DIMENSION X(10),DA(120)
      CG = 0.0
      RETURN
      END
C	
      FUNCTION CH(X,DA,N,NinDA,K)
C—. to limit the upper bounds of X
      DIMENSION X(10),DA(120)
      GO TO (10,10,50,50,100,50,100,10,50,10),K
   10 CH = 10.
      RETURN
   50 CH = 50.
      RETURN
  100 CH = 100.
      RETURN
      END
C	
      SUBROUTINE RP1 (a.ncoef,x,yor,nsam,nres,nart,ndset,next,lfile)
      character*! MARK(8). LINE(62,16)
      real x(15),y(15,3),yor(15,3),a(lO),vx(7)
      logical Ifile
C	            12345678
      DATA MARK/' + Vo1,'//',' ', '*'.'.'.'-', 'x'/
      TLOG(X)=ALOG(X)12.30258

      NU    =0
      NO    =3
C.... on the last pass thru RP next will = 0,
C	 resulting in plot printed onto 'output'  instead of user screen.
      if (( next .eq. 0) .and. Ifile ) nu - no
C.... line marks for Blank, Asterisk,  Dot, hyphen, etc.
      LB    = A
      LA    =5
      LD    =6
      LH    =7
      LT    =8
C.... limits of vertical Y axis and horizontal X axis are set and arrays + 1
      Ix    = 50
      ly    = 15
      Ipx   = lx+1
      Ipy   = ly+1

      WRITE  (nu,205) nart, ndset
  205 FORMAT (//,'  PLOT:   article1,i3,',  set ',i2,
     +':   Parent  Ist-Metab.  2nd-Metab.      Other1,/,llx,
     ^'SYMBOLS Measured:     +         o           f/       * = Overlay',/
     + ,19x,  'Modelled:     -         .           x       x = initial +')


                     APPENDIX F: page   15 of 22

                                                               91
-------
C.... the following finds max and min (greater than zero) residues reported
      YMAX    = -1.0E30
      YMIN    =  1.0E30
      DO A7 L = l.nsam
      DO A 7 M • l.nres
      y(l,m)  = 0.0
      if (yor(l.m) .le. 0.0) go to A7
      y(l,ra)  = tlog(yord.m))
   A3 IF (y(l,ra) .gt. YMAX) YMAX - y(l,m)
   A5 IF (y(l,m) .It. YMIN) YMIN «= y(l,m)
   A 7 CONTINUE
      yy      = tlog(a(l)+a(7))
      if (yy .gt. YMAX)     YMAX • yy

      xll     • 0.
      xul     = fnext2(x(nsam) )
      YUL     - FLOAT(IFIX(YMAX+1.))
      YLL     = FLOAT(IFIX(YMIN))
      if (YMIN .It. 0.0)     YLL = YLL-1.
C ---- we want yul-yll to be either I,3,or5 orders-of-magnitude (logs of Y)
C.... to be spaced conveniently on the screen.
   50 logy    = ifix(yul-yll+.0001)
   51 if (logy - 1)                    5A,59,52
   52 if (logy - 3)                    5A.60.53
   53 if (logy - 5)                    5A.60.59
   5A IF (ABS(YUL-YMAX)-ABS(YMIN-YLL)) 55,57,57
   55 YUL     = YUL+1.
   56 GO TO 50
   57 YLL     - YLL-1.
   58 GO TO 50
   59 logy    = 5
   60 continue
      kl      - ly/logy

      YI      = (YUL-YLL)/ly
      XI      = (XUL-XLD/lx
   63 continue
w • * • • •   •   •   •   •   •   •   »   •   •    •   •    •    *    •    •    •
C     The following bigins plotting array "line"
C     with i subscript for row
C          i subscript for column
C          k index  for X and Y labels
C          L subscript for samples
C          M subscript for residues within samples
C     characters start blank
C     borders are added (dots and pluses) in lines 6A-68
C     reported data are scanned and added in lines 68-91
C     the model is run and dots are added when in plot in lines 91-110
C         MARK   1   2   3   A   5   6   7   8
C               l + 'lnlly/ltl
w • * • •            T f  w y If f

      DO   6A I  « l.lpx
      DO   6A J  - l.lpy
      LINE(I.J)  •  MARK(LB)
                     APPENDIX F: page  16 of 22                    Q2
-------
   64 CONTINUE
      DO   65 I  = l.lpx
      LINE(I.l)  -  MARK(LD)                                              37Q
      LINE(I.lpy)-  MARK(LD)
   65 continue
      DO   66 I  *'l,lpx,5
      LINE(I.l)  =  MARK(l)
      LINE(I.lpy)»  MARK(l)
   66 continue
      DO   67 J  = l.lpy
      LINE(l.J)  *  MARK(LD)
      LINE(lpx.J)-  MARK(LD)
   67 continue
      DO   68 J  * l.lpy.kl
      LINE(l.J)  =  MARK(l)
      LINE(lpx,J)=  MARK(l)
   68 continue
C.... mark the model initial parent with an x
      yy         * (yy-YLL)/YI
      J          » lpy-ifix(round(yy,0))
      LINE(l.J)  =  MARK(LT)

      DO  91 L   = l.nsam
      xx         * (x(L)-XLL)/XI
      I          = 1 + ifix(round(xx,0))
      if ((I .It. 1) .or. (I .gt.  Ipx)) go to 91
      DO  90 M   ,= l.nres
      if (yor(L.M) .le. 0.0) go to 90
      LM         = M
      vy         = (y(L,M)-YLL)/YI
      J          = Ipy-ifix(round(yy,0))
      if ((J .It. 1) .or. (J .gt.  Ipy)) go to 90
      IF (LINE(I.J) .ne. MARK(LB)) LM=LA
      LINE(I.J)  = MARK(LM)
   90 continue
   91 continue

C.... find values of model
C....   DI = x interval (i.e. day post-application)
C	  PYn = plotted value of model at DI
   27 CONTINUE
      A23  = a(2Ha(3)
      A234 • A23 +a(4)
      A56  * a(5)+a(6)
      A78  = a(7)H-a(8)
      Alx3 = a(l)*a(3)
      A13d6* Alx3/(A56-A23A)
             Alx4/(A78-A234)
      DO 110 I = l.lpx
      DI   = XI*FLOAT(I-1)
      go to (155,153,151),nres
  151 Stop 'No model is provided for 2 metabolites!'
  153 F2   =                 (A14d8*(exp(-A234*di)-exp(-A78 *di)))      XI
     + -l-(((a(7)*AlAd8)+(a(6)>*A13d6))*(exP(-A234*di)-exp(-a(9)*di))/


                     APPENDIX F: page  17 of 22
-------
     +                                                     (a(9)-A234))  X2
     + +(((a(7)*A14d8/(a(9)-A78)))  *(exp(-A78 *di)-exp(-a(9)*di)))      X2
     -t- +((a(6)*(a(10)-A13d6))       *(exp(-A56 *di)-exp(-a(9)*di))/
     +                                                     (a(9)-A56))   X2     37]

  155 Fl  = (a(l) *exp(-A234*di))
     + +    (A13d6*exp(-A234*di)) + ((a(10)-A13d6)*exp(-A56*di))
      if (Fl .le. 0.0) go to 100
      PY1 - TLOG(Fl)
      yy  = (PY1-YLD/YI
      J   - lpy-ifix(round(yy,0))
      if ((J .It. 1) .or. (J .gt. Ipy))  go to 100
      IF (LINE(I.J) .eq. MARK(LB)) lined,J)  - mark(LD)
  100 if (DI .le. 0.0 .or. F2 .le. 0.0)  go to 110
      PY2 - TLOG(F2)
      yy  « (PY2-YLD/YI
      J   « Ipy-ifix(round(yy,0))
      if ((J .It. 1) .or. (J .gt. Ipy))  go to 110
      IF (LINEd.J) .eq. MARK(LB)) lined,J)  - mark(LH)
  110 CONTINUE
  111 CONTINUE

      k   = kl-1
      nkl - 0                                                           !
C	 DUMMY K STARTS«kl-l AND PUTS unit  labels
C	 ON EVERY  3RD or 5TH Y, AND 10TH X
      DO 125  J = l.lpy
      k   - k+1
      if (k-kl)           121,123,121
  121 if (J .le. ncoef+nkl) go to 122                                   !
      WRITE  (nu,206) (LINE(I,J),I=l,lpx)
      go to 125
  122 nc  - j-nkl
      WRITE  (nu,209) (LINE(I,J),I=l,lpx),nc,a(nc)
      go to 125
C	 VY IS MANTISSA AND iPY IS CHARACTERISTIC ON BASE  10  LOG  (TLOG)
  123 k   - k-kl
      nkl = nkl + 1
      YY  = YLL + (float(lpy-j)*yi)
      iPY = IFIX(ROUND(YY,0))
      VY  • 10.**(YY-iPY)
      VY  • ROUND(VY,2)
      WRITE  (nu.207) VY.iPY,(lined.J),I-l,lpx)
  125 CONTINUE
  206 FORMAT (1H ,12X,61A1)
  209 FORMAT (1H ,12X,51A1,  2x,'A',11,'•'.elO.A)
  207 FORMAT (1H .1X.F5.2,1  E1,13,lx,61al)
      DO 130 I - 1,7
      VX(I)    « XLL+(XI*10.*float(I-l))
      VX(I)    = ROUND(VX(I),1)
  130 CONTINUE
      WRITE  (nu,208)  (VX(I),I»1,6)
  208 FORMAT (1H ,  4X,7(5x,F5.D)
  150 RETURN
      END
                     APPENDIX F:  page  18  of  22
94
-------
c	  372
      function fnext2 (x)
C	 to find the next smallest multiple of x among 2,4,6,8,orlOx
      xd     = (10.**ifix(aloglO(x)))
      do 1 n = 1,5
      fnext2 = 2.*float(n)*xd
      if (fnextZ .ge. x) go to 2
     1 continue
     2 return
      end
C	
      function round(r,i)
C	 where r=number to be rounded and
C....       i=intergers remaining after decimal
      round = 0.0
      n     = 1
      rO    = 10.**i
      if (i .eq. 0)          rO = 1.
      if (r)                 11,9,1
   11 n     = -1
     i rl    = r*rO*float(n)
     2 il    = ifix(rl)
     3 r2    = rl-float(il)
     4 if (r2-0.5)             8,5,7
     5 r3    = float(il)/2.
     6 if (r3-ifix(r3)-.25)    7,7,8
     7 il    = il+1
     8 round = float(il*n)/rO
     9 return
      end
C	
      SUBROUTINE TELL (da.a.ncoef,dpa,res,nsam,nres,nart,ndset,next,
     +                 lfile.adif.pdif)

C	 ROUTINE WILL LIST PREDICTED POINTS AND COMPARE THEM TO INPUTS
C	 IT IS IDEALLY SUITED TO TIME SERIES DATA IN WHICH TIME IS FIRST
C	 USER MUST SUPPLY DEFINITIONS OF Fl, F2, F3, IN USER'S WORKING AREA

      DIMENSION X(10), DA(120), A(10), dpa(15), res(l5,3)
      integer nnzr(3)
      real pred(3),dif(3),pdif(3),chi2(3),adif(3)
      logical Ifile.lhold,match

      nu      =0
      NO      =3
      do 1 i  = l.nres
      PDIF(i) - 0.
      CHI2U) = 0.
      ADIF(i) = 0.
      nnzr(i) = 0
     1 CONTINUE

C	 a Holding status is introduced into file to hold printing of model results
C	 until the last pass through TELL.
      Ihold = Ifile
                     APPENDIX F: page  19 of 22              >-      Q _
-------
      if (next .ne. 0) Ifile - .false.
      if (.not. Ifile) go to 23
      WRITE  (NO, 100)
  100 FORMAT (/,' MODEL RESULTS',7('.'),'parent',12('.').lx,12('.'),
     +          'metabolite(s)',10('.' ),'>',
     +  /,'  TIME   ',2(   9HPREDICTED,2X,8HMEASURED,3X,9HPCT.DIFF. ),
     +  /,'  days',   2(5x.'ug/cm2',4x,'ug/cm2I.8x,'%',lx))
C.... format 100 will currently only accept 2 residues; 3 OK on wide paper.

   23 CONTINUE
      list   = 61
C	 PROGRAM REQUIRES INPUT DATA TO BE CHRONOLOGICALLY ORDERED
C	 lastd SET AT 1.5 TIMES THE LAST INPUT TIME
C.... but list of days shall not exceed 61
      lastd  - IFIX(dpa(nsam)*1.5)
      NT     = 1
   15 IF ((lastd/NT)-list)  17,17,16
   16 NT     = 2*NT
      GO TO 15
   17 CONTINUE

      i      =0
      A23    - a(2)+a(3)
      A234   = A23 +a(4)
      A56    = a(5)+a(6)
      A78    - a(7)+a(8)
      Alx3   = a(l)*a(3)
      A13d6  » Alx3/(A56-A234)
      AlxA   = a(l)*a(4)
      AlAdS  « Alx4/(A78-A234)
C.... This is a BIG 'double' (i and j) do loop down to line 90
      DO 90 j-NT.lastd,NT
   18 match  = .false.
      DI     = FLOAT(j-NT)
      if (i+1 .gt. nsam) go to 20
      if (dpa(i+l) .gt. float(j)-(.5*float(nt))) go to 20
      i      = i+1
      DI     = dpa(i)
      if (dpa(i) .eq. 0.0) di=0.1
      match  = .true.
   20 CONTINUE
O»»THIS IS THE USER'S WORKING AREA...««««««««««««««««
O»»WITHIN ITS BOUNDS, DEFINE pred(l)=OP. pred(2)=metabolite, etc.««
   27 CONTINUE
      go to (55,53,51),nres
   51 Stop 'No model is provided for 2 metabolites!'
   53 F2      -               (A14d8*(exp(-A234*di)-exp(-A78 *di)))      XI
     + +(((a(7)*A14d8)+(a(6)*A13d6))*(exp(-A234*di)-exp(-a(9)*di))/
     +                                                     (a(9)-A234))  X2
     + +(((a(7)*A14d8/(a(9)-A78)))  *(exp(-A78 *di)-exp(-a(9)*di)))      X2
     + -l-((a(6)*(a(10)-A13d6))       *(exp(-A56 *di)-exp(-a(9)*di))/
     •••                                                     (a(9)-A56))   X2
      ored(2)  = F2

   55 Fl      = (a(l) *exp(-A23A*di))


                     APPENDIX F:  page   20 of 22
-------
     + +   (A13d6*exp(-A234*di)) + ((a(10)-A13d6)*exp(-A56*di))
      pred(l) = Fl
                                                                           374
C	 THIS model WAS DEVELOPED TO ESTIMATE 7 COEFFICIENTS
C     PARENT     P. =     PI +    PI
C         d(P)/d(t) = -(a2+a3+a4)*Pl + (a3*Pl) - (a5+a6)*P2
C     METABOLITE X  =     XI +    X2
C         d(X)/d(t) =  a4*Pl -I- a6*P2 + (a3*Xl) - a2*Xl - a5*X2
C
C     AT  t = 0.
C     Pl(0) = Al
C     P2(0) = A7
C     Xl(0) = X2(0) = 0.
C     TO model parent only, SET DA(4)=0.0
C                               DA(6)=0.0
O»»THIS IS THE END OF THE USER'S WORKING AREA. ..<««««««««««
   80 CONTINUE

      if (.not. match) go to 86
C.... the following composite values are determined and reported
C.... pdif - percent error in observed over expected
C.... chi2 = sum of squares of dif (Chi-squared)
C.... adif = percent absolute error in observed over expected
      do 82 k = l.nres
      if     (res(i.k) .eq. 0.0) go to 82
      if     (pred(k)  .le. 0.0) go to 82
      dif(k)  = (pred(k)- res(i,k))/pred(k)
      chi2(k) = chi2(k) -t- (dif(k)**2)
      dif(k)  = dif(k) * 100.
      pdif(k) = pdif(k) + dif(k)
      adif(k) = adif(k) + abs(dif(k))
      nnzr(k) = nnzr(k) + 1
   82 CONTINUE

      if     (.not. Ifile) go to 18
      WRITE  (NO,102) di.(pred(k),res(i,k),dif(k),k=l,nres)
  102 FORMAT ( F7.2,2x,3(:,lpe9.3,2x,lpE9.3.1X,Opf7.2,3x))
      go to 18
   86 if     (.not. Ifile) go to 90
      WRITE  (NO,101) DI,(pred(k),k=l,nres)
  101 FORMAT (F7.2,2x,3(:, lpE9.3,:,22X))
   90 CONTINUE

      do 92 k = l.nres
      if     (nnzr(k) .le. 0) go to 92
      pdif(k) = pdif(k)/FLOAT(nnzr(k))
      adif(k) = adif(k)/FLOAT(nnzr(k))
   92 CONTINUE

      if     (.not. Ifile) go to 96
      WRITE  (NO,103) (chi2(k),k=l,nres)
      WRITE  (NO,104) (pdif(k),k=l,nres)
      WRITE  (NO,105) (adif(k),k=l,nres)
  103 FORMAT (/,14X,         'CHI SQUARE =  ' ,2x,3(IpElO.3,:,20X))
  104 FORMAT (   8X,   'MEAN   %   ERROR =',     3(2pE12.4,:,18x))


                     APPENDIX F: page  21 of 22                *
-------
  105 FORMAT (   8X,    'MEAN Z ABS ERROR « ',     3(2pE12.4,:,18X))

   96 if     (next .eq.  0) go to 98
      write  (nu,106)  (k.pdif(k),k«l,nres)
  106 format ('  MEAN   %  ERROR: Res(',il,')»',f6.1,
     +                    2(:,' ResC.il,')='.f6.1))
      write  (nu,107)  (k.adif(k),k«l,nres)
  107 format ('  MEAN  |%J  ERROR: Res(',il,')=',f6.1,
     +                    2(:,' ResC.il.')-'.f6.D)

   98 Ifile « Ihold
      RETURN
      END
C
      subroutine yes  (letter,choice)
      character*! letter
      logical choice
      choice ** .false.
      if (letter .eq.  'y') choice = .true.
      if (letter .eq.  'Y') choice = .true.
      return
      end
                     APPENDIX F:  page  22 of 22
                                                               98
-------
                                                                 APPENDIX G


Appendix G: Computer Program to Standardize Residues and Tabulate Responses    376
            Using the Unified Field Model.
            A short description of each symbol is given at the end of this •
            appendix (see also Appendix C).

      program REEN

c.... version 3 (to create a one- line/sample file containing
c         chem,nart,ndset,loc,crop,aia and form [as sped],
c         dpa , ( res ( i ) , i=l , 4 ) , den , dAChE , kdcom , Idass

c**************ft****************^
c                                                                             c
c     Purpose: To estimate AChE inhibition [optionally for a                  c
c              given crop and pesticide] for a given level(s) of              c
c              residue.   Estimations are determined using the                 c
c              'unified field model':                                         c
c                                                                             c
c              A compilation of dislodgeable foliar residue                   c
c              studies serves as the data base, along with                    c
c              various other coefficient and toxicity files.                  c
c                                                                             c
c     Dose:  D = kd*t*R/m                                                     c
c                where D    = dose, mg/kg                                     c
c                      kd   = crop specific dosing constant                   c
c                      t    = duration of exposure (hrs)                      c
c                      R    = residue, ug/cm2                                  c
c                      m    = body mass, = 70  kg (50 %ile man)                c
c                           .                                                  c
c     Response: dAChE = 1 - exp(-ke*D/LD50)                                   c
c                where dAChE = a fraction (Z/100) of RBC cholinesterase       c
c                              inhibited                                      c
c                       LD50 = acute toxicity, mg/kg                          c
c                       ke   = enzyme constant, =6.0                         c
c                                                                             c
c                                                                             C
      integer      ex, unit,  dapp,  yapp,
     +             fileO, filel,  fileZ,  file3,  file4,  fileS,  file6
      real         dpa(30) ,res(30,4),sd(30,4) ,LD50(A) ,dAChE(30) .kd.leafd
      character*!  file, den, kdcom
      character*3  loc, locrq,  mapp
      character*4  form
      character*6  crop.croprq
      character*8  chem,chemrq
      character*12 input, output, spec!
      character*20 cropname
      character*25 chemname(4),comname
      character*30 lox(3)
      character*79 comm(6)
      logical      crmat.chmat


                                                                  99
                     Appendix G,  page   1   of 9                     ' '
-------
c.... file 1 = user screen and console...format 1000 series reserved I/O.
c              (PC assumes this device to be "0")                             "^77
c	 file 2 = pesticide residue data base (filename =  'INPUT')              J ' '
c              (filename specified by user)
c	file 3 = the output file             (  "      =  'OUTPUT')
c              (filename specified by user)
c	 file 4 = crop coefficient library     (   "      =  'cropco.lib1)
c.... file 5 = chemical coefficient library (   "      =  'chemco.lib1)

       fileO=0
       file2=2
       file3=3
       file5=5
       file6=6

c     limits set for max number of requested effects (array),  coefficients,
c     number of samples and residues within each sample.
      maxr   «= 4
      maxs   = 30
      crmat  = .false.
    1 continue

      DO 3 i = l.maxs
         DO  2  j = l.maxr
            res(i.j) =0.0
            sd(i,j)  « 0.0
            Id50(j)  = 0.0
    2       continue
    3    continue

      chmat  = .false.
      write  (fileO,1003)
 1003 format (' Type residue INPUT filename, up to 12 characters:')
      read   (fileO.1004) input
 1004 format (a!2)
      if     ((input .eq. 'quit*).or.(input .eq. 'exit').or.
     +        (input .eq. 'stop1).or.(input .eq. 'end'))  goto  30000

      open   (file2, file = input)
      open   (file4, file='cropco.lib')
      open   (fileS, file=lchemco.lib1)
      rewind file2
      rewind file4
      rewind fileS

    5 continue
      write  (fileO.1005)
 1005 format (' A specific chemical (coded) can be requested;',/,
     +        ' type chemical (a8) or ''all11  for all crops:')
      read   (fileO,1006) cherarq
 1006 format (a6)
      write  (fileO,1007)
 1007 format (' A specific location (coded) can be requested;',/,


                     Appendix G, page  2  of 9

                                                           .     100
-------
     +        '  type location (a3) or ''all11  for  all  locations:')
      read   (fileO,1008) locrq
 1008 format (a3)
      write  (fileO,1009)
 1009 format ('  A specific crop (coded)  can be requested;1,/,
     +        '  type crop (a6) or "all"  for  all  crops:')
      read   (fileO.1010) croprq
 1010 format (a6)

      write  (fileO.1011)
 1011 format ('  Type data OUTPUT filename,  up  to 12  characters:1)
      read   (fileO,1004) output
      write  (fileO,1012)
 1012 format ('  Type 0 to show input data  on screen',/,
     +        '    or 1 to exclude this option:1)
      read   (fileO.1013) filel
 1013 format (il)
      if     (filel .eq.  0) goto 7
      open   (filel)
      rewind  filel
    7 open   (file3, file = output,  status='new')
      rewind  file3

c	 READ DATA SPECIFICATION FILE 	
   51 read  (file2,2001,end=85) chem,nart,ndset,nox,loc,crop,igraph,
     +form,aia,gpa,ex,unit,nsides,dapp.mapp,yapp,ncomm,npunpr.isd
 2001 format(a8,lx,2(I2,lx),il,lx,a3,lx,a6,lx,il,lx,a4,lx,f5.2,lx,f4.0,
     +      Ix,3(il,lx),i2,lx,a3,lx,i2,lx,il,lx,i3,lx.il)
      write (filel,2001      ) chem,nart,ndset,nox,loc,crop,igraph,
     +form,aia,gpa,ex,unit,nsides,dapp.mapp,yapp,ncomm,npunpr.isd
      backspace file2
      read  (file2,2011)  spec!
 2011 format(34x,a!2)
      call chemck (chem.noxa,Id50,chemname,comname,chmat,file5)
c.... the above subroutine searches  to match chemical  with  data  in  chemco file
      nres = nox + 1
      Idass = 0

c.... reading up to 6 comment lines
   52 if    (ncomm .le. 0) goto 53
      read  (file2,2002,end=9002) (comm(i),i=l,ncomm)
      write (filel,2002)           (comm(i),i=l,ncomm)
 2002 format(a79)

c.... reading the name of the oxons  or other metabolites
   53 if    (nox .le. 0)  goto 54
      read  (file2,2003,end=9003) (lox(i),  i=l,nox)
      write (filel.2003)           (lox(i),  i=l,nox)
 2003 format(a30)

c	 reading the number  of samples  in the following set of data
   54 read  (file2,2004,end=9004) nsam
      write (filel,2004)           nsam
 2004 format(i2)
                     Appendix G,  page  3  of 9
101
-------
c.... reading residue data ...
      if       (nsam .le. 0) goto 56
      DO 55 j=l,nsam
         read  (f Ue2,2005,end=9005) dpa( j ),(res( j ,k),sd( j ,k),k=l,nres)
         write (filel.2005)          dpa(j),(res(j,k),sd(j,k),k=l,nres)
   55    continue
 2005 format(f4.0,lx,8(f6.0,lx))

C.... QC-tolerance checks follow (line 56 to line 71):
   56 continue
      if    (chemrq .ne. chem .and. chemrq .ne.  'all     ')  goto 51
      if    (croprq .ne. crop .and. croprq .ne.  'all   '   )  goto 51
      if    (locrq  .ne. loc  .and. locrq  .ne.  'all1      )  goto 51
      if    ( nox   .gt. noxa)  goto 9015
      if    ( nres  .gt. maxr)  goto 9016
      if    ( nsam  .gt. maxs)  goto 9017
      if    (.not. chmat)       gotti 9018
      if    (Id50(l) .le. 0.01  goto 9019
      if    (nox .le. 0) goto 64
      do 58 k=2,nres
         if (Id50(k) .ne. 0.0) goto 58
         write  (fileO.1021) chemname(k),nart,ndset
 1021    format (' The LD50 for ',a25,' in article ',12,'  data set ',i2,
     +         /,' is unknown but asssamed * parent.1)
         Idass » Idass + 1
         Id50(k)=ld50(l)
   58    continue

   64 kdcom • ' '
      call cropck (crop,kd.cropname,leafd,den,crmat,file4)
c.... the above subroutine searches to match crop with data  in cropco file
      if    (.not. crmat) goto 9028
   65 if    (kd .ne. 0.0) goto 66
      write (fileO,1026) crop,nart,ndset
 1026 format(' Dosing coefficient (kd) for ',a6,'  in article ',i2,
     +' dataset ',i2,/, '  not listed in cropco library!  Default value e
     + 5000 cm2/hr.')
      kd = 5.0
      kdcom = '?'
   66 continue

   70 call units (res,sd,nsam,nres,unit,nsides,crop,leafd)
c.... above subroutine to convert to ug/cm2 projected area
c     units may be nonstandard and must be individualy converted.
      if    (unit  .ge.   4) goto 9014
      if    (leafd .le. 0.0) goto 9029

   71 call dosres  (dpa,res,LD50,dAChE,nres,nsam,kd)
c.... above subroutine to convert from residue to dose and AChE...
                     Appendix G, page  4  of 9

                                                                   102
-------
C.... the following write statements create the modified (one-line)
C     "output" file
      DO 75 j=l,nsam
C                                 spec! equivalent to :aia:gpa:
         write  (file3,3005) chem,nart,ndset,loc,crop,specl,
     +                       dpa(j),(res(j,k),k=l,maxr),den,dAChE(j),
     +                       kdcom.ldass
c	            V       V       V  <-- potentially removable delimiters
 3005 format(a8,':',2i2,':',a3,a6,a!2,fA.I.':',
     +       4(f6.3,':l),al,f7.3,al,il)
         do 74 k=l,maxr
C           arrays reset to avoid carry-over of "oxon" values between data sets
            res(j.k) * 0.0
            sd(j,k)  = 0.0
   74       continue
   75    continue
      goto 51

   85 write (fileO,*) 'Reading end of requested chem.-input datafile.'
      goto 1

C.... The following lines are various error and data-set reject  modes:
 9002 write (*,*)  '  Unexpected End-of-file  while reading comment lines!1
      goto 1
 9003 write (*.*)  '  Unexpected End-of-file  while reading "oxon"  lines!1
      goto 1
 9004 write (*,*)  '  End-of-file while reading number-of-samples  lines!1
      goto 1
 9005 write (*,*)  '  End-of-file while reading sample-data lines!1
      goto 1
 9014 write (fileO,1014) nart, ndset
 1014 format('  Nonstandard units in article ',i2,' dataset ',i2,/,
     +       '  - no further calculations are made on this data.')
      goto 51
 9015 write (fileO,1015) nart,ndset
 1015 formatC  More metabolites in article  ',12,' dataset ',i2,
     +       '  than listed in chemco.1)
      goto 1
 9016 write (fileO,1016) nart,ndset,maxr
 1016 format('Metabolites in article ',i2,' dataset ',i2,' exceed array
     •KLimit of ',il)
      goto 1
 9017 write (fileO.1017) nart,ndset,maxs
 1017 format('Samples in article ',i2,' dataset ',i2,' exceed array limi
     +t of «.i2)
      nsam = maxs
      goto 64
 9018 write (fileO,1018) chem,input,input
 1018 formatdx.aS,1  as listed in ',al2,
     +' was not found within chemco library.',/,
     +' Please check ',al2,'  for proper code or update cheraco.lib.')
      goto 51
 9019 write (fileO.1019) chem
 1019 format(Ix,a8,'  found within chemco library but without LD50!1)
                     Appendix G,  page  5  of 9
103
-------
 9028 write (filed,1028) crop
 1028 format(Ix,a6,'  not found within cropco library.  Please  check  listi
     +ng for proper code.1)
      goto 51
 9029 write (fileO,1029) crop,nart,ndset
 1029 format('  Unable to convert ppm for ',a6,'  in article  ',12,
     +       '  dataset ',12,' toug/cm2')                                      381
      goto 51

30000 STOP 'Have a good day1
      END
C	
      subroutine units (res,sd,nsam,nres,unit,nsides,crop,leafd)
c ... to convert residue units to ug/cm2 and 1-side (projected area) values
C       unit   = units reported
C                0/blank = ug/cm2 [default]
C                1       « ng/cm2      3 * ppm
C                2       = mg/m2       4 * other
      integer     unit
      real        res(30,4),  sd(30,4),leafd
      character*6 crop

       if (unit .eq.  0) goto 17
       do 16 k=l,nres
          do 15 j^l.nsam
             if (unit .gt. 1) goto 12
c....        to convert from ng/cm2
             res(j.k) • res(j,k)/1000.
             goto 15
   12        if (unit .gt. 2) goto 13
c....        to convert from mg/m2
             res(j.k) - res(j,k)/10.
             goto 15
   13        if (unit .gt. 3) goto 20
c....        to convert from ppm
             if (leafd .eq. 0.0) goto 20
             res(j.k) « res(j,k)*leafd/1000.
   15        continue
   16     continue
       unit = 0
   17  if (nsides .ne. 2) goto 20
c....  to convert from residues per 2 sides of a leaf
       do 19 k=l,nres
          do 18 j=l,nsam
             res(j.k) • res(j,k)*2.
   18        continue
   19     continue
       nsides « 1
   20  continue
       return
       end
                     Appendix G,  page  6  of 9
                                                                  104
-------
      Subroutine cropck (crop,kd,cropname,leafd,den,crmat,file4)
c—.  to find crop match and transfer pertinent parameters
      character*!  den
      character*6  .crop,code,stdcode
      character*20 cropname
      integer      fileA
      logical      crmat
      real         kd.leafd

      crmat - .false.
      rewind fileA
    1 read  (file4,4001,end=10) code,kd,cropname,leafd,den,stdcode
 4001 format(a6,5x,f4.1,7x,a20,2x,f4.1,al,2x,a6)
      if (crop .ne. code) goto 1
      crmat = .true.
      crop  = stdcode
   10 return
      end
c
      Subroutine chemck (chem,noxa,ld50,chemname,comname,chmat,fileS)
c....  to find chemical match and transfer pertinent parameters
      character*8  chem.code
      character*25 chemname(A),comname
      integer      fileS
      logical      chmat
      real         Id50(4)

      chmat = .false.
      rewind fileS
    1 read  (file5,5001,end=10) code,ld50(l),noxa,chemname(l),comname
 5001 format(a8,Ix,f4.0,Ix,il,Ix,a25,a25,2x,al,lx,al)
      if (chem .ne. code) goto 1
      do 3 i - l.noxa
         read  (file5,5002,end=10)   Id50(i+l),   chemname(i+l)
 5002 format(   9x,f4.0,      3x,a25                )
    3    continue
    9 chmat = .true.
   10 return
      end
c
      Subroutine dosres (dpa,res,LD50,dAChE,nres,nsam,kd)
c....  to convert residue to dose (mg/kg) and dAChE (%) ...
      real dpa(30),res(30,4),LD50(4),dAChE(30),kd,mass
c....  kd   = crop specific dose rate, from cropco.lib file
c	  LD50 = dermal toxicity(s),      from chemco.lib file
c....  mass = 70 kg for 50Zile man
      mass = 70.
c....  workday = 8 hours
      work =8.0
c....  ke   = enzyme constant =6.0
      ke   = 6.0"

      do 35 i=l,nsam
         sum =0.0
                     Appendix G, page  7  of 9                        105
-------
         do 30 j«=l,nres
            if (mass .eq. 0.0 .or.
     +           mass, j, Id50(j)
            D=kd*work*res(i,j)/mass
            sum - sum + (D/ld50(j))
   30       continue
         dAChE(i)=100.*(1.-exp(-ke*sum))
   35    continue
       return
       end
                            Id50(j) .eq. 0.0) write (*,*)
                                                                   383
Name   Type
AIA
CHEM
CHEMNA
CHEMRQ
CHMAT
COMM
COMNAM
CRMAT
CROP
CROPNA
CROPRQ
DACHE
DAPP
DEN
DPA
EX
FILED
FILE1
FILE2
FILE3
FILE4
FILES
FILE6
FORM
GPA
I
IGRAPH
INPUT
ISO
J
K
KD
KDCOM
LD50
LDASS
LEAFD
LOG
LOCRQ
LOX
MAPP
MAXR
REAL
CHAR
CHAR
CHAR
LOGI
CHAR
CHAR
LOGI
CHAR
CHAR
CHAR
REAL
INTE
CHAR
REAL
INTE
INTE
INTE
INTE
INTE
INTE
INTE
INTE
CHAR
REAL
INTE
INTE
CHAR
INTE
INTE
INTE
REAL
CHAR
REAL
INTE
REAL
CHAR
CHAR
CHAR
CHAR
INTE
Variables use in main program REEN1

Active Ingredient per Acre
coded CHEMical name
full CHEMical NAme
CHEMical ReQuested by user
CHemical MATch
COMMents (up to 6 lines)
COMmon chemical NAMe
CRop MATch
coded CROP name
full CROP NAme
CROP ReQuested by user
delta AChE (%)
Date of Application
symbol for surety of leaf DENsity
Days Post-Application
coded foliar residue Extraction solvent
input/output device
input file on disk
output file on disk
input file on disk
input file on disk
input file on disk
input file on disk
FORMulation of parent chemical
Gallons mixture Per Acre applied
subscript
code for Input data originally from a GRAPH or equation
INPUT file name
code designating statistical parameters on residues
subscript
subscript
Dosing coefficient
symbol for surety of Dosing coefficient
dermal Lethal Dose 50%
number of metabolite LDSOs assumed equal to parent
LEAF Density (mg/cm2)
coded LOCation
coded LOCation ReQuested by user
name of metabolites [Label of OXon]
Month of Application
MAXimum number of Residues permitted by array definition
                     Appendix G, page  8  of 9
                                                                      106
-------
MAXS   INTE      MAXimum number of Samples permitted by array definition
NART   INTE      citation Number of ARTicle                                _ o  .
NCOMM  INTE      Number of COMMent lines                                   384
NDSET  INTE      Number of DataSET within cited article
NOX    INTE      Number of metabolites (OXons)  in study
NOXA   INTE      maximum Number of "OXons" Already in chemco.lib
NPUNPR INTE      Number of PUNches within sample (if not nominal  48-60)
NRES   INTE      Number of RESidues reported in study [= NOX+1]
NSAM   INTE      Number of SAMples in study
NSIDES INTE      Number of SIDES used to calculate ug/cm2
OUTPUT CHAR      name of OUTPUT file
RES    REAL      RESidue values
SD     REAL      Standard or relative Deviation of residues
SPEC1  CHAR      dummy array to avoid write errors
UNIT   INTE      UNITs of residue reported
YAPP   INTE      Year of Application
                     Appendix G,  page  9   of  9

                                                              107
-------
                                                               APPENDIX H
Appendix H: Compilation of Reported Residue and  Calculated Response Data.

            Tabulation format includes the chemical name  (coded),
            the article (citation)  number, the study number
            within the article (sequential),  the location
            (coded), crop (coded),  application rate (Ib AIA),
            mixture (gallons/acre), the day post-application, 4
            residues (ug/cm ), an optional "?" when the residues
            were converted from ppm with only estimated leaf
            density, the calculated 8-hour cholinesterase
            response (% dAChE), a second optional "?"  for crops
            for which the default dosing coefficient was  assumed
            (default = 5000 cm /hr), and a single digit
            indicating the number of metabolites whose dermal
            toxicity was assumed equal to the parent.
385
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
: 2
: 2
: 2
: 2
: 2
: 2
: 2
: 2
: 2
: 2
: 2
: 2
1 : CAsOrange
1 : CAsOrange
1 : CAsOrange
1 : CAsOrange
1 : CAsOrange
1 : CAsOrange
2: CAsOrange
2 : CAsOrange
2 : CAsOrange
2 : CAsOrange
2 : CAsOrange
2: CAsOrange
3 : CAsOrange
3 : CAsOrange
3 : CAsOrange
3 : CAsOrange
3 : CAsOrange
3 : CAsOrange
4 : CAsOrange
4 : CAsOrange
4 : CAsOrange
4 : CAsOrange
4 : CAsOrange
4 : CAsOrange
1 : CAvPeach
1 : CAvPeach
1 : CAvPeach
1 : CAvPeach
1 : CAvPeach
1 : CAvPeach
1 : CAvPeach
1 : CAvPeach
2 : CAvPeach
2 : CAvPeach
2 : CAvPeach
2 : CAvPeach
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:06.00
:02.00
:02.00
:02.00
:02.00
:02.00
:02.00
:01.00
:01.00
:01.00
:01.00
:01.00
:01.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:03.00
:0100:
:0100:
:0100:
:0100:
:0100:
:0100:
:1200:
:1200:
:1200:
:1200:
:1200:
:1200:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0500:
:0105:
:0105:
:0105:
:0105:
:0105:
:0105:
:0105:
:0105:
:0100:
:0100:
:0100:
:0100:
3.0:20.200:
10.0:11.400:
17.0:10.600:
31.0:10.400:
44.0:
59.0:
3.0:
10.0:
17.0:
31.0:
44.0:
59.0:
3.0:
10.0:
17.0:
31.0:
44.0:
59.0:
3.0:
10.0:
17.0:
31.0:
44.0:
59.0:
.0:
4.0:
6.0:
10.0:
13.0:
14.0:
16.0:
20.0:
.0:
1.0:
3.0:
4.0:
9.400:
7.600:
9.200:
3.200:
2.600:
1.860:
2.000:
1.600:
4.000:
1.400:
1.240:
.940:
.760:
.600:
1.560:
.600:
.560:
.400:
.280:
.240:
5.800:
3.600:
2.000:
1.360:
.960:
4.600:
4.000:
3.000:
5.000:
5.200:
5.600:
5.800:
.078:
.066:
.106:
.090:
.076:
.012:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
30.
19.
19.
18.
17.
11.
13.
4.
4.
2.
3.
2.
6.
2.
1.
1.
1.
•
2.
•
•
.
•
•
3.
2.
1.
•
.
2.
2.
1.
2.
3.
3.
3.
237 0
280 0
865 0
964 0
088 0
909 0
605 0
960 0
049 0
913 0
129 0
511 0
161 0
201 0
952 0
483 0
201 0
949 0
449 0
949 0
886 0
634 0
444 0
381 0
376 0
109 0
177 0
802 0
567 0
687 0
341 0
761 0
918 0
033 0
262 0
376 0
                     Appendix H,  page  1
                                                             108
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azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
azinme
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: 2 2:CAvPeach
: 2 2:CAvPeach
: 2 2:CAvPeach
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: 2 2:CAvPeach
: 2 2:CAvPeach
:77 1:AZ Cotton
:77 1:AZ Cotton
:77 1:AZ Cotton
:77 1:AZ Cotton
:77 1:AZ Cotton
:51 l:CANApple
:51 l:CANApple
:51 l:CANApple
:51 l:CANApple
:51 l:CANApple
:51 l:CANApple
:51 2:CANApple
:51 2:CANApple
:51 2:CANApple
:51 2:CANApple
:51 2:CANApple
:51 2:CANApple
:51 3:CANApple
:51 3:CANApple
:51 3:CANApple
:51 3:CANApple
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:51 5:CANApple
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:51 6:CANApple
:51 6:CANApple
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0100: 6.0: 5.400: .000: .000: .000:? 3.147 0
0100: 9.0: 5.000: .000: .000: .000:? 2.918 0
0100:11.0: 4.400: .000: .000: .000:? 2.572 0
0100:14.0: 4.200: .000: .000: .000:? 2.457 0
0100:17.0: 3.600: .000: .000: .000:7 2.109 0
0100:20.0: 4.200: .000: .000: .000:? 2.457 0
0009: .0: .843: .000: .000: .000:? 1.30570
0009: 1.0: .568: .000: .000: .000:7 .88170
0009: 2.0: .289: .000: .000: .000:7 .44970
0009: 3.0: .229: .000: .000: .000:7 .35670
0009: 4.0: .149: .000: .000: .000:7 .23270
: .0: 1.920: .000: .000: .000:7 2.073 0
: 3.0: .968: .000: .000: .000:? 1.050 0
: 7.0: .392: .000: .000: .000:? .427 0
:10.0: .380: .000: .000: .000:7 .414 0
:14.0: .224: .000: .000: .000:? .244 0
:21.0: .144: .000: .000: .000:7 .157 0
: .0: 3.720: .000: .000: .000:7 3.977 0
: 3.0: 1.364: .000: .000: .000:7 1.477 0
: 7.0: 1.228: .000: .000: .000:7 1.331 0
:10.0: .560: .000: .000: .000:7 .609 0
:14.0: .464: .000: .000: .000:? .505 0
:21.0: .148: .000: .000: .000:7 .161 0
: .0: 1.440: .000: .000: .000:7 1.559 0
: 3.0: .712: .000: .000: .000:7 .774 0
: 7.0: .532: .000: .000: .000:7 .579 0
:10.0: .272: .000: .000: .000:7 .296 0
:14.0: .424: .000: .000: .000:7 .461 0
:21.0: .148: .000: .000: .000:7 .161 0
:28.0: .068: .000: .000: .000:7 .074 0
: .0: 2.940: .000: .000: .000:? 3.156 0
: 3.0: 1.932: .000: .000: .000:? 2.086 0
: 7.0: 1.228: .000: .000: .000:7 1.331 0
:10.0: 1.176: .000: .000: .000:7 1.275 0
:14.0: .652: .000: .000: .000:7 .709 0
:21.0: .348: .000: .000: .000:? .379 0
:28.0: .196: .000: .000: .000:7 .214 0
: .0:17.000: .000: .000: .000:7 16.927 0
: 3.0:13.200: .000: .000: .000:7 13.411 0
: 7.0: 7.200: .000: .000: .000:7 7.554 0
:10.0: 4.600: .000: .000: .000:7 4.894 0
:14.0: 3.600: .000: .000: .000:7 3.851 0
:21.0: 2.400: .000: .000: .000:7 2.584 0
:28.0: 1.800: .000: .000: .000:? 1.944 0
:35.0: 1.400: .000: .000: .000:? 1.516 0
:42.0: 1.200: .000: .000: .000:7 1.301 0
: .0:11.000: .000: .000: .000:? 11.308 0
: 3.0: 9.000: .000: .000: .000:7 9.352 0
: 7.0: 5.400: .000: .000: .000:? 5.721 0
:10.0: 3.000: .000: .000: .000:? 3.220 0
:14.0: 2.000: .000: .000: .000:? 2.158 0
:21.0: 1.400: .000: .000: .000:? 1.516 0
:28.0: .800: .000: .000: .000:7 .869 0
:35.0: .600: .000: .000: .000:7 .652 0
Appendix H, page  2
                               109
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azinme  : 3
azinme  : 3
azinme  : 3
azinme  : 3
az inme  : 3
azinme  : 3
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carbaryl: 3
carbaryl: 3
carbaryl: 3
carbaryl: 3
carbaryl: 3
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carbaryl: 3
carbaryl: 3
carbaryl: 3
carbaryl: 3
carbop  :12
carbop  :12
carbop  :12
carbop  :12
carbop  :12
carbop  :12
carbop  :12
carbop  :12
carbop  :12
carbop  :12
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carbop  :35
carbop  :35
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2:AZ Orange:
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2:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
3:FL Orange:
3:FL Orange:
3:FL Orange:
3:FL Orange:
3:FL Orange:
3:FL Orange:
4:FL Orange:
4:FL Orange:
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                     Appendix H, page  3
                                                             110
-------
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.400:
.800:
.360:
.140:
.150:
.044:
.000:
.800:
.200:
.140:
.540:
.860:
.260:
.740:
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.540:
.660:
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.340:
.660:
.400:
.214:
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.121:
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.922:
.650:
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.384:
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.076:
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.044:
.042:
.028:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.340:
.260:
.164:
.140:
.116:
.086:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.032:
.044:
.050:
.056:
.064:
.042:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:?
.000:?
.000:?
.000:?
.000:?
.914
.709
.556
.255
.224
.100
.093
19.279
11.061
5.931
6.169
5.453
3.040
.805
7.091
6.006
5.896
4.797
3.536
2.409
1.422
7.807
4.797
5.018
4.280
2.560
1.269
.771
.497
.486
.321
3.328
2.567
1.816
1.400
1.077
.926
.562
.377
.225
.152
.101
.959
.402
.116
.071
.959
.231
.047
.016
.437
.181
.118
.041
.035
0
0
°388
0
0
0
0
3
3
3
3
3
3
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
0
0
0
0
0
Appendix H, page  4
                                      111
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dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
'dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dimeth
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:51
:86
:86
:86
:86
:86
:86
:86
:86
:80
:80
:80
:80
:80
:80
:80
:80
l:CANApple
2:CANApple
2:CANApple
2:CANApple
2:CANApple
2:CANApple
2:CANApple
3:CANApple
3:CANApple
3:CANApple
3:CANApple
3:CANApple
3:CANApple
3:CANApple
4:CANApple
4:CANApple
4:CANApple
4:CANApple
4:CANApple
4:CANApple
4:CANApple
5:CANApple
5:CANApple
5:CANApple
5:CANApple
5:CANApple
5:CANApple
5:CANApple
5:CANApple
5:CANApple
6:CANApple
6:CANApple
6:CANApple
6:CANApple
6:CANApple
6:CANApple
6:CANApple
6:CANApple
6:CANApple
1:TX Orange
1:TX Orange
1:TX Orange
1:TX Orange
2:TX Orange
2:TX Orange
2:TX Orange
2:TX Orange
1 : CAsOrange
1 : CAsOrange
1 : CAsOrange
1: CAsOrange
1: CAsOrange
1 : CAsOrange
2: CAsOrange
2: CAsOrange
*
.
.
.
.
*
.
.
*


*
.
.
*
.
.
.
.
.
.
.
.
*
.
.
.
.
.
.
.
.
*
.
.
.
.
.
.
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
5.00
5.00
5.00
5.00
5.00
5.00
5.00
5.00
:21.0:
: .0:
: 3.0:
: 7.0:
:10.0:
:14.0:
:21.0:
: .0:
: 3.0:
: 7.0:
:10.0:
:14.0:
:21.0:
:28.0:
: .0:
: 3.0:
: 7.0:
:10.0:
:14.0:
:21.0:
:28.0:
: .0:
: 3.0:
: 7.0:
:10.0:
:14.0:
:21.0:
:28.0:
:35.0:
:42.0:
: .0:
: 3.0:
: 7.0:
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:14.0:
:21.0:
:28.0:
:35.0:
:42.0:
5: 1.0:
5: 2.0:
5: 7.0:
5:14.0:
0: 1.0:
0: 2.0:
0: 7.0:
0:14.0:
100: 4.0:
100:10.0:
100:18.0:
100:31.0:
100:46.0:
100:59.0:
100: 4.0:
100:10.0:
.012:
2.456:
.936:
.476:
.264:
.324:
.040:
1.028:
.600:
.332:
.136:
.100:
.052:
.068:
2.256:
1.616:
.564:
.436:
.316:
.084:
.024:
.192:
.184:
.132:
.056:
.044:
.024:
.008:
.008:
.004:
.196:
.136:
.096:
.044:
.028:
.008:
.004:
.004:
.004:
.432:
.248:
.011:
.001:
1.922:
1.274:
.042:
.004:
2.600:
2.200:
1.400:
1.600:
1.600:
1.200:
2.600:
2.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
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.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.012:
.010:
.002:
.000:
.018:
.039:
.011:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
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.000:
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.000:
.000:
.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.005 0
.962 0
.368 0
.187 0
.104 0
.127 0
.016 0
.404 0
.236 0
.131 0
.053 0
.039 0
.020 0
.027 0
.884 0
.634 0
.222 0
.171 0
.124 0
.033 0
.009 0
.076 0
.072 0
.052 0
.022 0
.017 0
.009 0
.003 0
.003 0
.002 0
.077 0
.053 0
.038 0
.017 0
.011 0
.003 0
.002 0
.002 0
.002 0
.254 1
.148 1
.007 1
.000 1
1.106 1
.750 1
.030 1
.002 1
7.297 0
6.210 0
3.998 0
4.556 0
4.556 0
3.437 0
7.297 0
5.662 0
                                             385
Appendix H, page  5
                              112
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dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
:80 2:
:80 2:
:80 2:
:80 2:
:80 3:
:80 3:
:80 3:
:80 3:
:80 3:
:80 3:
:80 A:
:80 A:
:80 A:
:80 A:
:80 A:
:80 A:
:80 5:
:80 5:
:80 5:
:80 5:
:80 5:
:80 5:
:80 6:
:80 6:
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:80 9:
:80 9:
:8010:
:8010:
:8010:
:8010:
:8011:
:8011:
:8011:
:8011:
:38 1:
CAsOrange :
CAsOrange :
CAsOrange :
CAsOrange:
CAsOrange:
CAsOrange :
CAsOrange:
CAsOrange :
CAsOrange :
CAsOrange :
CAsOrange:
CAsOrange:
CAsOrange :
CAsOrange:
CAsOrange :
CAsOrange :
CAsOrange :
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CAsOrange :
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CAsOrange :
CAsOrange :
CAsOrange:
CAsOrange :
CAsOrange:
CAsOrange:
CAsOrange :
CAsOrange :
CAsOrange:
CAsOrange:
FL Orange:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
5.00:
A. 00:
100:
100:
100:
100:
100:
100:
100:
100:
100:
100:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
1250:
100:
100:
100:
100:
100:
100:
100:
100:
750:
18.0:
31.0:
A6.0:
59.0:
A.O:
10.0:
18.0:
31.0:
A6.0:
59.0:
A.O:
10.0:
18.0:
31.0:
A6.0:
59.0:
A.O:
10.0:
18.0:
31.0:
A6.0:
59.0:
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10.0:
18.0:
31.0:
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59.0:
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10.0:
18.0:
31.0:
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59.0:
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10.0:
18.0:
31.0:
A6.0:
59.0:
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10.0:
18.0:
31.0:
A6.0:
59.0:
7.0:
13.0:
27.0:
35.0:
A.O:
10.0:
38.0:
A6.0:
1.0:
1.200:
l.AOO:
1.000:
1.600:
3.200:
2.600:
1.600:
l.AOO:
1.200:
l.AOO:
1.800:
2.000:
1.800:
1.600:
1.800:
1.000:
2.200:
2.000:
1.600:
l.AOO:
l.AOO:
1.000:
1.800:
1.600:
2.000:
l.AOO:
1.200:
.600:
1.000:
.800:
.600:
.800:
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1.200:
1.000:
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.600:
.600:
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1.000:
.800:
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2.600:
2.200:
1.800:
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2.800:
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.000:
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.000:
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.000:
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.000:
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.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
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.000:
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.000:
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.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
3.A37
3.998
2.872
A. 556
8.90A
7.297
A. 556
3.998
3.A37
3.998
5.111
5.662
5.111
A. 556
5.111
2.872
6.210
5.662
A. 556
3.998
3.998
2.872
5.111
A. 556
5.662
3.998
3.A37
1.733
2.872
2.30A
1.733
2.30A
1.159
1.159
3.A37
2.872
1.159
1.733
1.733
1.159
2.872
2.30A
1.159
1.159
1.159
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7.297
6.210
5.111
3.998
7.836
A. 556
5.662
3.998
1.733
0^
0390
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Appendix H, page  6
                                    113
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dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
dioxat
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
:38
:38
:38
:38
:38
:38
:38
:38
:38
:38
:38
:27
:27
:27
:27
:27
:27
:27
:27
:27
:27
:27
:27
:27
:27
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:47
:12
:12
: 12
:12
:12
:12
:12
:12
:12
:12
:12
:12
1:FL Orange:
1:FL Orange:
1:FL Orange:
1:FL Orange:
1:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
1 : CAvGrapes :
1 : CAvGrapes :
1 : CAvGrapes :
1 : CAvGrapes :
1 : CAvGrapes :
1 : CAvGrapes :
1 : CAvGrapes :
2 : CAvGrapes :
2 : CAvGrapes :
2 : CAvGrapes :
2: CAvGrapes:
2 : CAvGrapes :
2 : CAvGrapes :
2 : CAvGrapes :
1 : CAvOrange :
1 : CAvOrange :
1 : CAvOrange :
1 : CAvOrange :
1: CAvOrange:
1 : CAvOrange:
2 : CAvOrange :
2 : CAvOrange :
2 : CAvOrange :
2: CAvOrange:
2 : CAvOrange :
2: CAvOrange:
3 : CAvOrange :
3 : CAvOrange :
3: CAvOrange:
3: CAvOrange:
3 : CAvOrange :
3 : CAvOrange :
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
1:AZ Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
1.0:
1.0:
1.0:
1.0:
1.0:
1.0:
1.0:
1.25:
1.25:
1.25:
1.25:
1.25:
1.25:
1.25:
3.0:
3.0:
3.0:
3.0:
3.0:
3.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
4.0:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
4.00:
4.00:
4.00:
750: 2
750: 5
750:10
750:20
750:30
750: 1
750: 2
750: 5
750:10
750:20
750:30
30:
30: 1
30: 3
30: 7
30:14
30:21
30:28
200:
200: 1
200: 3
200: 7
200:14
200:21
200:28
500: 2
500: 5
500: 9
500:16
500:23
500:33
500: 2
500: 5
500: 9
500:16
500:23
500:33
500: 2
500: 5
500: 9
500:16
500:23
500:33
350:
350: 1
350: 3
350: 5
350: 7
350:14
350:21
350:28
350:42
350:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
350: 1.0:
350: 3
.0:
.460:
.326:
.250:
.192:
.164:
.080:
.056:
.036:
.024:
.018:
.014:
.800:
.600:
.200:
.065:
.021:
.019:
.015:
.900:
.700:
.350:
.070:
.032:
.020:
.012:
1.102:
.475:
.236:
.149:
.078:
.037:
.516:
.754:
.342:
.548:
.298:
.230:
1.771:
.834:
.669:
.268:
.176:
.127:
18.136:
17.612:
15.848:
10.392:
12.040:
9.420:
7.398:
4.442:
2.356:
10.252:
9.072:
7.856:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.070:
.072:
.078:
.055:
.025:
.011:
.007:
.080:
.092:
.105:
.058:
.030:
.019:
.010:
.100:
.087:
.064:
.048:
.024:
.011:
.028:
.054:
.034:
.090:
.042:
.034:
.110:
.076:
.112:
.063:
.044:
.034:
.172:
.548:
.930:
.944:
1.220:
1.386:
1.412:
1.238:
1.006:
.122:
.130:
.142:
.uuu:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.005:
.020:
.048:
.060:
.050:
.035:
.004:
.004:
.011:
.039:
.045:
.039:
.032:
.000:
.029:
.041:
.032:
.028:
.029:
.008:
.012:
.011:
.047:
.039:
.044:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.022:
.070:
.066:
.106:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
. uuu .
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
^ . _/...-
.946
.726
.558
.477
.233
.163
.105
.070
.052
.041
1.356
1.057
.466
.263
.166
.125
.089
1.532
1.241
.728
.262
.168
.122
.085
2.710
1.340
.777
.523
.297
.175
1.255
1.858
.881
1.554
.862
.702
4.207
2.058
1.769
.754
.501
.369
34.195
34.005
31.962
22.942
26.325
21.885
18.239
12.175
7.397
21.111
18.969
16.708
0
°391
0
0
0
0
0
0
0
0
0
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Appendix H, page  7
                                     114
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ethion
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ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
ethion
U2
:12
:12
:12
:12
:12
:12
:12
:12
-.12
: 12
:12
: 12
: 12
:12
: 12
:12
:12
:12
: 12
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
:34
2:FL
2:FL
2:FL
2:FL
2:FL
2:FL
3:TX
3:TX
3:TX
3:TX
3:TX
3:TX
3:TX
3:TX
3:TX
4:CA
4:CA
4:CA
4:CA
4:CA
4:CA
4:CA
4:CA
4:CA
1:FL
1:FL
1:FL
1:FL
1:FL
1:FL
2:FL
2:FL
2:FL
2:FL
2:FL
2:FL
2:FL
2:FL
2:FL
3:FL
3:FL
3:FL
3:FL
3:FL
3:FL
4:FL
4:FL
4:FL
4:FL
4:FL
4:FL
4:FL
4:FL
4:FL
5:FL
Orange:
Orange:
Orange:
Orange:
Orange :
Orange:
Orange :
Orange :
Orange:
Orange:
Orange:
Orange :
Orange:
Orange :
Orange:
Orange:
Orange :
Orange :
Orange:
Orange :
Orange:
Orange:
Orange :
Orange :
Orange:
Orange:
Orange :
Orange:
Orange :
Orange :
Orange :
Orange :
Orange:
Orange:
Orange:
Orange :
Orange:
Orange :
Orange :
Orange:
Orange:
Orange:
Orange :
Orange :
Orange :
Orange :
Orange :
Orange:
Orange:
Orange:
Orange:
Orange:
Orange :
Orange:
Orange:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
3.00:
3.00:
3.00:
3.00:
3.00:
3.00:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
350: 5
350: 7
350:14
350:21
350:28
350:42
350:
350: 1
350: 3
350: 5
350: 7
350:14
350:21
350:28
350:42
350:
350: 1
350: 3
350: 5
350: 7
350:14
350:21
350:28
350:42
1200:
1200: 1
1200: 3
1200: 5
1200: 7
1200:14
1200:
1200: 1
1200: 3
1200: 5
1200: 7
1200:14
1200:21
1200:28
1200:35
1200:
1200: 1
1200: 3
1200: 5
1200: 7
1200:14
1200:
1200: 1
1200: 3
1200: 5
1200: 7
1200:14
1200:21
1200:28
1200:35
1200:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
5.498:
3.024:
1.954:
.844:
.726:
.368:
6.776:
4.534:
3.846:
2.952:
1.968:
.420:
.226:
.126:
.030:
4.336:
3.900:
3.504:
2.894:
2.274:
.988:
.476:
.290:
.072:
.199:
.122:
.015:
.006:
.006:
.004:
.283:
.066:
.047:
.033:
.034:
.033:
.010:
.007:
.008:
.569:
.249:
.050:
.009:
.003:
.005:
.265:
.116:
.079:
.061:
.059:
.053:
.020:
.015:
.008:
.505:
.124:
.092:
.072:
.076:
.062:
.044:
.102:
.090:
.092:
.092:
.084:
.062:
.048:
.042:
.012:
..104:
.110:
.106:
.126:
.116:
.072:
.082:
.064:
.026:
.008:
.012:
.008:
.005:
.003:
.003:
.024:
.005:
.006:
.008:
.010:
.010:
.008:
.004:
.004:
.084:
.043:
.010:
.009:
.005:
.004:
.033:
.005:
.008:
.010:
.013:
.012:
.011:
.010:
.006:
.024:
.000:
.001:
.001:
.008:
.007:
.006:
.000:
.000:
.000:
.000:
.003:
.007:
.013:
.014:
.007:
.000:
.000:
.000:
.005:
.006:
.005:
.015:
.032:
.021:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
.000:
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.000:
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.000:
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.000:
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.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
12.059 2
6.876 2
4.527 2
2.100 2
1.800 2
.952 2
14.548 2
10.030 2
8.608 2
6.722 2
4.589 2
1.112 2
.653 2
.416 2
.111 2
9.651 2
8.759 2
7.921 2
6.681 2
5.329 2
2.405 2
1.300 2
.878 2
.273 2
.472 1
.307 1
.052 1
.026 1
.021 1
.015 1
.700 1
.161 1
.121 1
.094 1
.101 1
.098 1
.041 1
.026 1
.029 1
1.483 1
.667 1
.138 1
.041 1
.018 1
.020 1
.678 1
.277 1
.199 1
.163 1
.165 1
.148 1
.071 1
.057 1
.031 1
1.203 1
                                            392
Appendix H, page  8
                              115
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ethion
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etp
etp
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:34 5:FL Orange:
:34 5
:34 5
:34 5
:34 5
:34 6
:34 6
:34 6
:34 6
:34 6
:34 6
:34 6
:34 6
:34 6
;34 7
:34 7
:34 7
:34 7
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:34 7
:34 8
:34 8
:34 8
:34 8
:34 8
:34 8
:34 8
:34 8
:34 8
:34 9
:34 9
:34 9
:34 9
:34 9
:34 9
:3410
:3410
:3410
:3410
:3410
:3410
:3410
:3410
:3410
:18 1
:18 1
:18 1
:18 1
:18 1
:18 1
:18 1
:18 1
:18 1
:18 1
:18 1
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
:FL Orange:
.•CAsOrange:
: CAsOrange :
: CAsOrange:
: CAsOrange :
: CAsOrange:
: CAsOrange :
: CAsOrange :
: CAsOrange:
: CAsOrange:
: CAsOrange:
: CAsOrange:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
4.50:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
9.00:
12.50:
12.50:
12.50:
12.50:
12.50:
12.50:
12.50:
12.50:
12.50:
12.50:
12.50:
1200: 1.
1200: 3.
1200: 5.
1200: 7.
1200:14.
1200: .
1200: 1.
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1200: 5.
1200: 7.
1200:14.
1200:21.
1200:28.
1200:35.
1200: .
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1200: 7.
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1200: 7.
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1200:28.
1200:35.
2000: .
2000: .
2000: 1.
2000: 1.
2000: 2.
2000: 3.
2000: 4.
2000: 5.
2000: 6.
2000: 7.
2000: 8.
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
5:
8:
0:
5:
0:
0:
0:
0:
0:
0:
0:
.126:
.034:
.027:
.022:
.009:
.468:
.203:
.103:
.058:
.021:
.044:
.010:
.009:
.007:
.416:
.095:
.048:
.024:
.015:
.011:
.405:
.190:
.222:
.108:
.041:
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.014:
.016:
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.635:
.275:
.116:
.018:
.016:
.009:
.752:
.316:
.237:
.262:
.164:
.042:
.024:
.024:
.016:
4.200:
3.600:
2.400:
2.800:
2.600:
1.940:
1.420:
1.400:
1.620:
1.540:
1.160:
.014:
.006:
.003:
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.049:
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.032:
.000:
.056:
.086:
.066:
.068:
.090:
.086:
.070:
.000:
.000:
.000:
.000:
.000:
.000:
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1








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64
59
50
50
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54
44
44
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41
.320 1
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.976 0
.313 0
.905 0
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.404 0
.318 0
.430 0
.296 0
.613 0
.407 0
                                                 39
Appendix H, page  9
                                 116
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CA Orange:
CA Orange:
CA Orange:
CA Orange:
CA Orange:
CA Orange:
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                    Appendix H, page  10
                                                               117
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1:SC tobaco:0.375: : 3.0:
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2:SC tobaco: 0.375: : 1.0:
2:SC tobaco: 0.375: : 3.0:
2:SC tobaco:0.375: : 5.0:
3:SC tobaco: 0.375: : 1.0:
3:SC tobaco: 0.375: : 3.0:
3:SC tobaco:0.375: : 5.0:
4:SC tobaco:0.375: : 1.0:
4:SC tobaco:0.375: : 3.0:
1:FL Orange: 0.75: 100: 1.0:
1:FL Orange: 0.75: 100: 6.0:
1:FL Orange: 0.75: 100: 8.0:
2:FL Orange: 0.75: 100: 1.0:
2:FL Orange: 0.75: 100: 2.0:
2:FL Orange: 0.75: 100: 3.0:
2:FL Orange: 0.75: 100: 7.0:
2:FL Orange: 0.75: 100: 9.0:
3:FL Orange: 2.00: 100: 1.0:
3:FL Orange: 2.00: 100: 3.0:
3:FL Orange: 2.00: 100: 6.0:
3:FL Orange: 2.00: 100; 8.0;
4:FL Orange: .75: 100: 1.0:
4:FL Orange: .75: 100: 3.0:
4:FL Orange: .75: 100: 6.0:
4:FL Orange: .75: 100: 8.0:
l:CAsPeach : 2.00: 400: .0:
l:CAsPeach : 2.00: 400: 3.0:
l:CAsPeach : 2.00: 400: 7.0:
l:CAsPeach : 2.00: 400:14.0:
l:CAsPeach : 2.00: 400:21.0:
l:CAsPeach : 2.00: 400:28.0:
l:CAsPeach : 2.00: 400:70.0:
2:CAsPeach : 1.00:0400: .0:
2:CAsPeach : 1.00:0400: 3.0:
2:CAsPeach : 1.00:0400: 7.0:
2:CAsPeach : 1.00:0400:14.0:
2:CAsPeach : 1.00:0400:21.0:
2:CAsPeach : 1.00:0400:28.0:
2:CAsPeach : 1.00:0400:70.0:
3:CAsPeach : 1.00:0400: .0:
3:CAsPeach : 1.00:0400: 3.0:
3:CAsPeach : 1.00:0400: 7.0:
3:CAsPeach : 1.00:0400:14.0:
3:CAsPeach : 1.00:0400:21.0:
3:CAsPeach : 1.00:0400:28.0:
3:CAsPeach : 1.00:0400:70.0:
1:AZ Cotton: 1.00: 9: .0:
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                                                  39j
Appendix H, page  11
                                     118
-------
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                   396
        Appendix H,  page   12
119
-------
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5: CAvCitrus: 10. 00: 1600: 4.0:
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6: CAvCitrus: 10. 00: 1600: 4.0:
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l:CAvPeach : 2.00: 50: 9.0:
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2:CAvPeach : 1.30: 17: .5:
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Appendix H, page  13
                              120
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35.0:
1.0:
3.0:
5.0:
7.0:
14.0:
.0:
1.0:
3.0:
5.0:
7.0:
14.0:
21.0:
28.0:
42.0:
.0:
1.0:
3.0:
7.0:
14.0:
28.0:
42.0:
.0:
1.0:
3.0:
7.0:
14.0:
28.0:
42.0:
.0:
1.0:
3.0:
5.0:
7.0:
14.0:
21.0:
28.0:
42.0:
.440:
.040:
.025:
.021:
.011:
.008:
.008:
.003:
.002:
2.719:
.551:
.174:
.102:
.041:
.023:
.019:
.008:
.002:
14.086:
3.604:
2.102:
.836:
.286:
11.246:
8.590:
6.126:
4.130:
3.832:
1.832:
.674:
.186:
.086:
3.642:
2.036:
.890:
.272:
.060:
.010:
.004:
3.212:
1.924:
.974:
.218:
.064:
.012:
.006:
3.280:
2.552:
.786:
.540:
.286:
.112:
.034:
.026:
.004:
.022:
.015:
.013:
.011:
.005:
.002:
.004:
.000:
.000:
.085:
.034:
.030:
.016:
.006:
.006:
.003:
.000:
.000:
.262:
.170:
.134:
.094:
.092:
.038:
.134:
.222:
.228:
.302:
.152:
.122:
.090:
.090:
.034:
.052:
.114:
.090:
.050:
.014:
.006:
.034:
.058:
.064:
.036:
.022:
.008:
.006:
.018:
.048:
.024:
.028:
.026:
.008:
.006:
.012:
.004:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
17.097
5.988
4.906
4.272
2.135
.821
1.517
.085
.060
62.386
22.728
13.798
7.880
3.147
2.569
1.640
.195
.055
98.814
77.570
62.979
41.583
32.509
94.724
92.679
90.040
83.943
86.646
62.812
44.845
30.316
28.554
64.251
49.864
46.259
31.797
17.291
5.016
2.174
60.198
49.512
37.319
16.502
8.874
3.050
2.223
58.616
55.306
24.442
20.770
14.987
5.442
2.905
4.730
1.488
0
0
0
0
o 39C
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
                     Appendix H, page  14
121
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etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
etp
12 6:CA
12 6:CA
12 6:CA
12 6:CA
12 6:CA
12 6:CA
   6:CA
:12
:12  6
:12  6
:12
:12
:12
:12
:12
:12
:12
:12
:12
     :CA
     :CA
     lAZ
     :AZ
     ;AZ
     :AZ
     :AZ
     :AZ
     :AZ
     :AZ
     :AZ
   7
   7
   7
   7
   7
   7
   7
   7
   7
12 8:CA
12 8:CA
12 8:CA
12 8:CA
12 8:CA
12 8:CA
12 8:CA
12 8:CA
12 9:CA
12 9:CA
12 9:CA
12 9:CA
12 9:CA
12 9:CA
12 9:CA
1210:FL
1210:FL
1210:FL
1210:FL
1210:FL
1210:FL
1210:FL
1210:FL
1210:FL
    :TX
    :TX
    :TX
    :TX
    :TX
    :TX
    :TX
    :TX
    :TX
    :AZ
    :AZ
    :AZ
:75
:75
:75
:75 1:AZ
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Grapes:
Grapes:
Grapes:
Grapes:
Grapes:
Grapes:
Grapes:
Grapes:
Apple  :
Apple  :
Apple  :
Apple  :
Apple  :
Apple  :
Apple  :
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Cotton:
Cotton:
Cotton:
Cotton:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
  .50:
  .50:
  .50:
  .50:
                       350:
  5:
  5:
  5:
  5:
350
350
350
350
350
350:14.0:
350:21.0:
350:28.0:
350:42.0:
350
350
350
350
                            7.0
350: 7.0:
350:14.0:
350:21.0:
350:28.0:
350:42.0:
350
350
350
350
350
350:14.0
350:28.0
350:42.0
350
350
350
350
350
350:14.0
350:42.0
350
350
350
350
                             .0:
                            1.0:
                            3.0:
                            5.0:
                            7.0:
                       350:14.0:
                       350:21.0;
                       350:28.0:
                       350:42.0:
                       350
                       350
                       350
                       350
                       350
                       350:14.0
                       350:21.0
                       350:28
                       350:42
                            7.0
  0;
  0:
 .0:
 .5
1.0:
     7.440:
     5.396:
     2.102:
     1.346:
      .792:
      .202:
      .068:
      .024:
      .004:
    11.200:
     6.646:
       826:
       642:
       918:
      .578:
      .270:
      .156:
      .040:
    15.378:
    14.086:
 3.
 2.
 1.
                                 3,
                                 2.
   604:
   102:
  .836:
  .286:
  .052:
  .008:
18.690:
11.970:
 3.892:
 1.636:
 1.286:
  .056:
  .010:
10.276:
   508:
   342:
   624:
   964:
  .560:
  .226:
  .128:
  .048:
11.530:
   426:
   490;
   668:
   166:
   098:
   024:
   010:
   004:
   020:
   750:
   580:
     5.
     3.
     2,
     1.
          7.
          2.
          2.
          1,
                                 4.
                                 2.
                                 2.
                            2.0:  1.960
.030:
.118:
.050:
.060:
.038:
.010:
.006:
.008:
.004:
.126:
.216:
.212:
.274:
.274:
.134:
.110:
.080:
.034:
.188:
.262:
.170:
.134:
.094:
.092:
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.004:
.162:
.292:
.382:
.230:
.176:
.040:
.012:
.056:
.034:
.058:
.072:
.078:
.042:
.038:
.026:
.014:
.070:
.104:
.074:
.104:
.060:
.016:
.008:
.006:
.002:
.020:
.040:
.040:
.050:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
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.000:
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.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:
.000:
.000:
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.000:
.000:
.000:
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.000:
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.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:?
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.000:?
.000:?
.000:?
.000:?
85. yo/ 0
82.805 0
50.338 0
42.077 0
28.160 0
8.188 0
3.726 0
3.340 0
1.488 0
96.077 0
91.068 0
81.679 0
80.174 0
76.244 0
45.828 0
36.373 0
27.294 0
12.093 0
95.438 0
95.233 0
64.150 0
49.437 0
30.852 0
23.649 0
7.773 0
1.091 0
97.248 0
93.625 0
79.485 0
56.502 0
47.421 0
10.022 0
3.005 0
93.688 0
77.570 0
64.571 0
59.637 0
53.391 0
24.931 0
17.250 0
11.565 0
5.913 0
95.606 0
89.125 0
58.554 0
64.305 0
39.413 0
7.728 0
3.340 0
2.321 0
.796 0
65.11370
55.54170
53.65170
47.87070
             Appendix  H,  page   15
                                                        122
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etp
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etp
etp
etp
etp
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etp
etp
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etp
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etp
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:75
:75
:75
:75
:75
:75
:76
:76
:79
:79
:79
:84
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:84
1:AZ Cotton:
2:AZ Cotton:
2:AZ Cotton:
2:AZ Cotton:
2:AZ Cotton:
2:AZ Cotton:
1:AZ Cotton:
1:AZ Cotton:
1:AZ Cotton:
1:AZ Cotton:
1:AZ Cotton:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
l:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
2:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
3:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
4:CAvCitrus:
5:CAvCitrus:
5:CAvCitrus:
5:CAvCitrus:
.50:
.50:
.50:
.50:
.50:
.50:
1.00:
1.00:
1.00:
1.00:
1.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
5: 3.
5: .
5: .
5: 1.
5: 2.
5: 3.
9: 1.
9: 1.
9: .
9: 1.
9: 2.
100: .
100: 1.
100: 2.
100: 3.
100: 7.
100:10.
100:14.
100:21.
100:28.
100: .
100: 1.
100: 2.
100: 3.
100: 5.
100: 7.
100:10.
100:14.
100:21.
100:28.
100:57.
100:63.
100: .
100: 1.
100: 2.
100: 3.
100: 5.
100: 7.
100:10.
100:14.
100:21.
100:28.
100:35.
100:63.
100: .
100: 1.
100: 3.
100: 7.
100:10.
100:14.
100:21.
100:28.
100: .
100: 1.
100: 3.
0:
0:
5:
0:
0:
0:
0:
5:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
0:
1.240:
.920:
.760:
.590:
.440:
.380:
.350:
.370:
2.330:
.270:
.150:
9.000:
.000:
3.200:
1.400:
.000:
.360:
.120:
.060:
.036:
8.000:
.000:
4.000:
3.000:
1.700:
.900:
.520:
.300:
.066:
.000:
.020:
.000:
7.000:
.000:
5.000:
1.800:
1.040:
.600:
.240:
.140:
.044:
.000:
.034:
.014:
.780:
3.200:
1.600:
.340:
.180:
.060:
.030:
.018:
8.000:
4.400:
1.400:
.040:
.000:
.010:
.010:
.010:
.010:
.004:
.002:
.000:
.017:
.012:
.110:
.380:
.000:
.300:
.340:
.320:
.200:
.140:
.104:
.044:
.200:
.000:
.540:
.540:
.400:
.440:
.360:
.160:
.110:
.000:
.080:
.050:
.120:
.000:
.280:
.180:
.220:
.240:
.220:
.044:
.032:
.000:
.012:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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.000:
.000:
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.000:
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.000:
.000:
.000:
35
20
19
16
13
11
9
9
43
11
7
92
73
55
75
69
70
51
39
31
88
50
63
92
90
80
81
73
43
31

24
85
34
71
76
58
60
59
55
15
10

4
17
55
32
8
4
1


86
66
29
.649?0
.173?0
.78170
.37170
.24170
.95770
.46570
.22570
.48270
.69870
.49270
.813 0
.524 0
.038 0
.312 0
.548 0
.151 0
.780 0
.625 0
.113 0
.378 0
.313 0
.182 0
.848 C
.105 0
.283 0
.150 0
.655 0
.787 0
.934 0
.498 0
.404 0
.389 0
.273 0
.320 0
.041 0
.905 0
.118 0
.313 0
.262 0
.199 0
.587 0
.846 0
.444 0
.703 0
.038 0
.946 0
.142 0
.397 0
.488 0
.747 0
.449 0
.444 0
.683 0
.511 0
                                            400
Appendix H, page  16
                              123
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etp
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:84 5:CAvCitrus:
:8A 5:CAvCitrus:
:8A 5:CAvCitrus:
:8A 5: CAvCitrus:
:8A 5
:8A 5
:8A 6
:8A 6
:8A 6
:8A 6
:8A 6
:8A 6
:84 6
:8A 6
:8A 6
:67 1
:67 1
:67 1
:67 2
:67 2
:67 2
:67 2
:67 3
:67 3
:67 3
:67 3
:67 4
:67 A
:67 A
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:67 5
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:67 6
:67 6
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:67 7
:67 7
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:67 8
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:CAvCitrus:
:CAvCitrus:
:CAvCitrus:
: CAvCitrus:
:CAvCitrus:
:CAvCitrus:
:CAvCitrus:
: CAvCitrus:
: CAvCitrus :
:CAvCitrus:
: CAvCitrus:
:CAvOrange:
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange:
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange:
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange:
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange:
: CAvOrange :
: CAvOrange :
: CAvOrange :
: CAvOrange:
: CAvOrange:
: CAvOrange :
: CAvOrange:
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
8.00
6.0
6.0
6.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
2.25
2.25
2.25
2.25
2.0
2.0
2.0
2.0
2.0
2.0
2.5
2.5
2.5
1.5
1.5
1.5
1.5
1.5
1.5
1.3
1.3
1.3
2.0
2.0
2.0
2.0
3.1
3.1
3.1
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
: 100
:1200
:1200
:1200
:1000
:1000
:1000
:1000
:1000
:1000
:1000
:1000
: 900
: 900
: 900
: 900
: 300
: 300
: 300
: 300
: 300
: 300
:1000
:1000
:1000
: 750
: 750
: 750
: 600
: 600
: 600
: 500
: 500
: 500
: 200
: 200
: 200
: 200
:1250
:1250
:1250
: 5.0:
: 7.0:
:10.0:
:1A.O:
:21.0:
:28.0:
: .0:
: 1.0:
: 3.0:
: 5.0:
: 7.0:
: 9.0:
:13.0:
:20.0:
:3A.O:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
:23.0:
: 2.0:
: 9.0:
:16.0:
:23.0:
: 2.0:
: 9.0:
:16.0:
:23.0:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
: 2.0:
: 9.0:
:16.0:
:22.0:
: 2.0:
: 9.0:
:16.0:
.500:
.300:
.090:
.056:
.020:
.020:
5.000:
A. 800:
1.200:
.800:
.A20:
.130:
.120:
.OAO:
.036:
.26A:
.030:
.010:
.398:
.055:
.025:
.008:
.A13:
.095:
.050:
.011:
1.A3A:
.311:
.11A:
.OA2:
.181:
.023:
.007:
.171:
.017:
.009:
.150:
.006:
.006:
.191:
.013:
.003:
.050:
.007:
.001:
.252:
.027:
.010:
.187:
.021:
.007:
.003:
.10A:
.023:
.008:
.000;
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.019:
.013:
.007:
.032:
.033:
.009:
.006:
.030:
.012:
.010:
.006:
.109:
.065:
.050:
.020:
.090:
.025:
.007:
.071:
.020:
.008:
.109:
.026:
.010:
.011:
.003:
.002:
.006:
.001:
.001:
.03A:
.020:
.010:
.053:
.017:
.007:
.005:
.021:
.009:
.007:
.C!OG;
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
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• v>l/"w •
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
7.220
2.223
1.389
.A98
.A98
71.320
69.851
25.900
18.114
9.960
3.195
2.953
.994
.895
12.289
5.027
2.635
19.079
12.122
3.684
2.316
18.695
6.262
4.669
2.250
52.293
26.250
18.395
7.650
30.128
9.040
2.698
25.362
7.295
2.938
34.179
8.816
3.572
8.102
1.293
.638
3.378
.622
.255
16.552
7.348
3.703
20.654
6.253
2.425
1.830
9.582
3.745
2.717
0*401
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Appendix H, page  17
-------
etp     :6713:CAvOrange:  1.9: 750: 2.0:  .175:  .035:  .000:  .000:  15.337 0
etp     :6713:CAvOrange:  1.9: 750: 9.0:  .028:  .014:  .000:  .000:   5.449
etp     :6713:CAvOrange:  1.9: 750:16.0:  .011:  .009:  .000:  .000:   3.491
etp     :6714:CAvOrange:  2.5: 300: 2.0:  .295:  .034:  .000:  .000:  17.431 0
etp     :6714:CAvOrange:  2.5: 300: 9.0:  .033:  .012:  .000:  .000:   5.034 0
etp     :6714:CAvOrange:  2.5: 300:16.0:  .006:  .007:  .000:  .000:   2.467 0
etp     :6715:CAvOrange:  3.0:1200: 2.0:  .089:  .023:  .000:  .000:   9.779 0
etp     :6715:CAvOrange:  3.0:1200: 9.0:  .020:  .006:  .000:  .000:   2.624 0
etp     :6715:CAvOrange:  3.0:1200:16.0:  .013:  .002:  .000:  .000:    .977 0
etp     :6716:CAvOrange:  2.0: 500: 2.0:  .241:  .021:  .000:  .000:  12.471 0
etp     :6716:CAvOrange:  2.0: 500: 9.0:  .044:  .018:  .000:  .000:   7.161 0
etp     :6716:CAvOrange:  2.0: 500:16.0:  .008:  .007:  .000:  .000:   2.691 0
etp     :6717:CAvOrange:  1.9: 750: 2.0:  .688:  .025:  .000:  .000:  22.974 0
etp     :6717:CAvOrange:  1.9: 750: 9.0:  .048:  .011:  .000:  .000:   4.972 0
etp     :6717:CAvOrange:  1.9: 750:16.0:  .011:  .007:  .000:  .000:   2.731 0
etp     :6718:CAvOrange:  1.9: 750: 2.0:  .229:  .052:  .000:  .000:  21.168 0
etp     :6718:CAvOrange:  1.9: 750: 9.0:  .058:  .025:  .000:  .000:   9.681 0
etp     :6718:CAvOrange:  1.9: 750:16.0:  .012:  .012:  .000:  .000:   4.232 0
etp     :6719:CAvOrange:  2.0: 300: 2.0:  .483:  .167:  .000:  .000:  50.491 0
etp     :6719:CAvOrange:  2.0: 300: 9.0:  .012:  .054:  .000:  .000:  17.388 0
etp     :6719:CAvOrange:  2.0: 300:16.0:  .005:  .021:  .000:  .000:   7.338 0
etp     :6720:CAvOrange:  7.5:1800: 2.0: 1.297:  .227:  .000:  .000:  67.336 0
etp     :6720:CAvOrange:  7.5:1800: 9.0:  .120:  .135:  .000:  .000:  39.492 0
etp     :6720:CAvOrange:  7.5:1800:16.0:  .039:  .021:  .000:  .000:   8.011 0
etp     :6720:CAvOrange:  7.5:1800:21.0:  .009:  .017:  .000:  .000:   6.095 0
etp     :6721:CAvOrange:  2.0: 300: 2.0:  .173:  .328:  .000:  .000:  69.551 0
etp     :6721:CAvOrange:  2.0: 300: 9.0:  .021:  .066:  .000:  .000:  20.967 0
etp     :6721:CAvOrange:  2.0: 300:16.0:  .033:  .021:  .000:  .000:   7.698 0
etp     :6722:CAvOrange:  2.0: 300: 2.0:  .439:  .396:  .000:  .000:  77.570 0
etp     :6722:CAvOrange:  2.0: 300: 9.0:  .043:  .072:  .000:  .000:  23.060 0
etp     :6722:CAvOrange:  2.0: 300:16.0:  .002:  .018:  .000:  .000:   6.146 0
etp     :6723:CAvOrange:  1.9: 750: 3.0:  .170:  .001:  .000:  .000:   4.582 0
etp     :6723:CAvOrange:  1.9: 750:10.0:  .015:  .004:  .000:  .000:   1.660 0
etp     :6723:CAvOrange:  1.9: 750:17.0:  .005:  .003:  .000:  .000:   1.139 0
etp     :6724:CAvOrange:  1.9: 750: 2.0:  .153:  .016:  .000:  .000:   8.875 0
etp     :6724:CAvOrange:  1.9: 750: 9.0:  .008:  .005:  .000:  .000:   1.768 0
etp     :6724:CAvOrange:  1.9: 750:16.0:  .004:  .002:  .000:  .000:    .965 0
etp     :6725:CAvOrange:  2.5:1000: 2.0:  .417:  .025:  .000:  .000:  17.439 0
etp     :6725:CAvOrange:  2.5:1000: 9.0:  .038:  .016:  .000:  .000:   6.474 0
etp     :6725:CAvOrange:  2.5:1000:16.0:  .004:  .005:  .000:  .000:   1.806 0
etp     :6726:CAvOrange:  2.0: 250: 2.0:  .771:  .366:  .000:  .000:  77.026 0
etp     :6726:CAvOrange:  2.0: 250: 9.0:  .069:  .051:  .000:  .000:  17.821 0
etp     :6726:CAvOrange:  2.0: 250:16.0:  .021:  .025:  .000:  .000:   8.994 0
etp     :6727:CAvOrange:  4.6:1850: 2.0:  .387:  .011:  .000:  .000:  12.768 0
etp     :6727:CAvOrange:  4.6:1850: 9.0:  .043:  .016:  .000:  .000:   6.289 0
etp     :6727:CAvOrange:  4.6:1850:16.0:  .012:  .005:  .000:  .000:   1.928 0
etp     :6728:CAvOrange:  7.5:1500: 2.0:  .618:  .321:  .000:  .000:  72.081 0
etp     :6728:CAvOrange:  7.5:1500: 9.0:  .067:  .115:  .000:  .000:  34.296 0
etp     :6728:CAvOrange:  7.5:1500:16.0:  .024:  .058:  .000:  .000:  18.848 0
etp     :6728:CAvOrange:  7.5:1500:22.0:  .010:  .018:  .000:  .000:   6.373 0
etp     :6729:CAvOrange:  2.3: 900: 2.0:  .363:  .032:  .000:  .000:  18.360 0
etp     :6729:CAvOrange:  2.3: 900: 9.0:  .020:  .013:  .000:  .000:   4.981 0
etp     :6729:CAvOrange:  2.3: 900:16.0:  .004:  .007:  .000:  .000:   2.535 0
etp     :6730:CAvOrange:  1.9: 750: 2.0:  .200:  .145:  .000:  .000:  42.706 0
etp     :6730:CAvOrange:  1.9: 750: 9.0:  .024:  .022:  .000:  .000:   8.088 0
                     Appendix H, page  18
125
-------
etp
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etp
etp
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:45 0:CAvOrange:
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:45 0:CAvOrange:
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:45 0:CAvOrange:
:45 0:CAvOrange:
:45 OrCAvOrange:
:45 OrCAvOranger
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:46 IrCAvOranger
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:46 l:CAvOranger
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:46 IrCAvOranger
:46 2:CAvOranger
:46 2:CAvOrange:
:46 2:CAvOrange:
:46 2rCAvOrange:
:46 2rCAvOrange:
:46 2rCAvOrange:
:46 3:CAvOrange:
:46 SrCAvOrange:
:46 SrCAvOrange:
r46 3:CAvOrange:
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:46 4:CAvOrange:
:46 4:CAvOrange:
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:46 6rCAvOrange:
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:46 6:CAvOrange:
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.326:
.235:
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.090:
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71.624
56.547
20.727
27.288
11.117
11.910
8.864
12.306
11.716
11.604
5.983
13.609
9.210
8.104
37.081
21.662
10.432
7.751
2.752
69.611
39.167
29.272
6.850
1.028
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23.934
7.244
2.614
2.406
1.162
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13.093
3.660
1.607
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52.966
28.611
11.289
7.320
3.359
1.332
71.673
61.165
46.971
41.692
15.768
12.083
4.291
81.947
72.534
63.215
46.284
25.580
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0
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0
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0
0
0
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0
0
0
0
0
0
0
Appendix H, page  19                      1 O^
                                          I CO
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:4613:CAvOrange:
:4614:CAvOrange:
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:4614:CAvOrange:
:4615:CAvOrange:
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:4615:CAvOrange:
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6.3:
6.3:
7.5:
7.5:
7.5:
7.5:
7.5:
2.0:
2.0:
2.0:
2.0:
2.0:
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4.0:
4.0:
4.0:
4.0:
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                     Appendix H, page  20
                                                      127
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10.788
50.881
61.257
50.064
37.178
15.832
8.349
7.301
46.366
43.237
13.742
18.928
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0
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0
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Appendix H, page  21
                                  128
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8:CA Grapes: .75: 100: 3.0:
8:CA Grapes: .75: 100: 7.0:
9:CA Grapes: .75: 25: .0:
9:CA Grapes: .75: 25: 1.0:
9:CA Grapes: .75: 25: 3.0:
9:CA Grapes: .75: 25: 7.0:
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1:AZ Cotton: 1.00: 9: .0:
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1:AZ Cotton: 1.00: 9: 2.0:
1:AZ Cotton: 1.00: 9: 3.0:
1:AZ Cotton: 1.00: 9: 4.0:
l:CAvtomato: .019: 10: .0:
l:CAvtomato: .019: 10: 1.0:
l:CAvtomato: .019: 10: 2.0:
l:CAvtomato: .019: 10: 3.0:
1:AZ Orange: 8.00: 350: .0:
1:AZ Orange: 8.00: 350: 1.0:
1:AZ Orange: 8.00: 350: 3.0:
1:AZ Orange: 8.00: 350: 5.0:
1:AZ Orange: 8.00: 350: 7.0:
1:AZ Orange: 8.00: 350:14.0:
1:AZ Orange: 8.00: 350:21.0:
1:AZ Orange: 8.00: 350:28.0:
1:AZ Orange: 8.00: 350:42.0:
1:AZ Cotton: .50: 5: .0:
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2:AZ Cotton: .50: 5: .0:
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                                            406
Appendix H, page  22
129
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B*i 0
951 0
869 0
280 0
384 0
137 0
260 0
728 0
316 0
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369 0
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643 0
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124 0
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678 0
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850 0
379 0
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283 0
968 0
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611 0
796 0
105 0
115 0
496 0
291 0
132 0
743 0
                                               407
Appendix H, page  23
                                  130
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3.75
7.00
7.00
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3.75
3.75
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5.63
5.63
5.63
5.63
5.63
5.63
11.30
11.30
11.30
11.30
11.30
11.30
5.63
5.63
5.63
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5.63
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11.30
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5.63
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5.63
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:1500
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: 100
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: 3.0:
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.078:
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1.980:
1.080:
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2.600:
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10
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                                             408
Appendix H, page  24
                               131
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: 1720: CAvOrange: 11. 30: 2250: .0
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: 1725: CAvOrange: 3.63:1450: .0
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Appendix H, page  25
                              132
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.478 0
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.030 0
.056 0
.020 0
1.332 0
.764 0
.535 0
.325 0
.115 0
.030 0
.034 0
2.647 0
1.804 0
1.143 0
.830 0
.134 0
.059 0
.041 0
1.427 0
.354 0
.096 0
.077 0
.066 0
.040 0
.057 0
1.332 0
.316 0
.079 0
.067 0
.057 0
.057 0
.045 0
2.890 0
.512 0
.152 0
.176 0
.093 0
.115 0
.205 0
.239 0
                                            410
Appendix H, page  26
                              133
-------
metion
metion
metion
metion
metion
metion
metion
metion
metion
metion
metion
metion
metion
metion
metion
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metion
metion
metion
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metion
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monoos
monoos
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monoos

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74
74
74
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78
77
77
77
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7:FL Orange: 2.30:1200: 1.0:
7:FL Orange: 2.30:1200: 3.0:
7:FL Orange: 2.30:1200: 5.0:
7:FL Orange: 2.30:1200: 7.0:
7:FL Orange: 2.30:1200:14.0:
7:FL Orange: 2.30:1200:21.0:
8:FL Orange: 4.60:1200: .0:
8:FL Orange: 4.60:1200: 1.0:
8:FL Orange: 4.60:1200: 3.0:
8:FL Orange: 4.60:1200: 5.0:
8:FL Orange: 4.60:1200: 7.0:
8:FL Orange: 4.60:1200:14.0:
8:FL Orange: 4.60:1200:21.0:
9:FL Orange: 6.90:1200: .0:
9:FL Orange: 6.90:1200: 1.0:
9:FL Orange: 6.90:1200: 3.0:
9:FL Orange: 6.90:1200: 5.0:
9:FL Orange: 6.90:1200: 7.0:
9:FL Orange: 6.90:1200:14.0:
9:FL Orange: 6.90:1200:21.0:
1:CA Orange: 5.60: 100: .0:
1:CA Orange: 5.60: 100: 3.0:
1:CA Orange: 5.60: 100:10.0:
1:CA Orange: 5.60: 100:17.0:
1:CA Orange: 5.60: 100:30.0:
1:CA Orange: 5.60: 100:45.0:
1:CA Orange: 5.60: 100:59.0:
2:CA Orange: 5.60:2250: .0:
2:CA Orange: 5.60:2250: 3.0:
2:CA Orange: 5.60:2250:10.0:
2:CA Orange: 5.60:2250:17.0:
2:CA Orange: 5.60:2250:30.0:
2:CA Orange: 5.60:2250:45.0:
3:CA Orange: 7.50:1500: .0:
3:CA Orange: 7.50:1500: 3.0:
3:CA Orange: 7.50:1500:10.0:
3:CA Orange: 7.50:1500:17.0:
3:CA Orange: 7.50:1500:30.0:
1:CA Citrus:003. 5:0100: 7.0:
1:CA Citrus:003. 5:0100:14.0:
2:CA Citrus:003. 5:1000:11.0:
2:CA Citrus:003. 5:1000:14.0:
1:AZ Cotton: 1.00: 9: .0:
1:AZ Cotton: 1.00: 9: .5:
1:AZ Cotton: 1.00: 9: 1.0:
1:AZ Cotton: 1.00: 9: 2.0:
1:AZ Cotton: 1.00: 9: 3.0:
1:AZ Cotton: 1.00: 9: 4.0:
1:AZ Cotton: 1.28: 9: 1.0:
1:AZ Cotton: 1.28: 9: 1.5:
1:AZ Cotton: 1.00: 9: .0:
1:AZ Cotton: 1.00: 9: 1.0:
1:AZ Cotton: 1.00: 9: 2.0:
1:AZ Cotton: 1.00: 9: 3.0:
1:AZ Cotton: 1.00: 9: 4.0:
Appendix H, page 2




















9
6
1




1
1




1








4
3
3
3
2
1


1
1
1


7
.010:
.015:
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.024:
.038:
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.032:
.022:
.024:
.192:
.054:
.074:
.056:
.044:
.050:
.044:
.200:
.800:
.540:
.660:
.220:
.066:
.020:
.960:
.120:
.260:
.110:
.052:
.010:
.760:
.920:
.200:
.096:
.030:
.240:
.080:
.320:
.100:
.900:
.950:
.750:
.125:
.750:
.792:
.460:
.560:
.420:
.480:
.100:
.770:
.700:

.000:
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.098:
.144:
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.000:
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.070:
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.094:
.012:
.000:
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.052:
.030:
.000:
.000:
.000:
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.360:
.140:
.060:
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.006:
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.000:
.000:
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.000:

.000:
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34










































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7
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35.
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344 0
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105 0
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029 0
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4V
-------
monoos
monoos
monoos
monoos
oxyme
oxyme
oxyme
oxyme
oxyme
oxyme
oxyme
oxyme
oxyme
oxyme
phenth
phenth
phenth
phenth
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phenth
phenth
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phenth
phenth
phenth
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pholon
pholon
pholon
pholon
pholon
pholon
pholon
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pholon
pholon
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pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
:79
:79
:79
:79
:38
:38
:38
:38
:38
:38
:38
:38
:38
:38
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:18
:24
:24
:24
:24
:24
:24
:24
:24
:24
:24
:24
:24
:48
:48
:48
:48
:48
:48
:48
:48
1:AZ Cotton:
1:AZ Cotton:
1:AZ Cotton:
1:AZ Cotton:
1:FL Orange:
1:FL Orange:
1:FL Orange:
1:FL Orange:
1:FL Orange:
1:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
2:FL Orange:
1 : CAsOrange :
l:CAsOrange:
1: CAsOrange:
1 : CAsOrange :
1 : CAsOrange :
1: CAsOrange:
1 : CAsOrange :
1 : CAsOrange :
2 : CAsOrange :
2 : CAsOrange :
2: CAsOrange:
2: CAsOrange:
2: CAsOrange:
2: CAsOrange:
2 : CAsOrange :
3 : CAsOrange :
3: CAsOrange:
3 : CAsOrange :
3: CAsOrange:
3: CAsOrange:
3 : CAsOrange :
1 : CAvOrange :
1 : CAvOrange :
1 : CAvOrange :
1 : CAvOrange :
1 : CAvOrange :
1 : CAvOrange :
2 : CAvOrange :
2 : CAvOrange :
2 : CAvOrange :
2 : CAvOrange :
2 : CAvOrange :
2 : CAvOrange :
l:CAvPeach :
l:CAvPeach :
l:CAvPeach :
IrCAvPeach :
l:CAv Peach :
l:CAvPeach :
l:CAvPeach :
2:CAvPeach :
1.00:
1.00:
1.00:
1.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
4.00:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
7.50:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
6.00:
4. :
4. :
4. :
4. :
4. :
4. :
4. :
4. :
9
9
9
9
750
750
750
750
750
750
750
750
750
750
100
100
100
100
100
100
100
100
1500
1500
1500
1500
1500
1500
1500
1500
1500
1500
1500
1500
1500
600
600
600
600
600
600
600
600
600
600
600
600
30
30
30
30
30
30
30
375
: .0:
: 1.0:
: 2.0:
: 3.0:
: 1.0:
: 2.0:
: 5.0:
:10.0:
:20.0:
:30.0:
: 1.0:
: 2.0:
: 5.0:
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: 2.0:
: 9.0:
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: 2.0:
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: .0:
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: 1.0:
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:19.0:
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:23.0:
: 1.0:
: 8.0:
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:23.0:
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n*
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1.280:
1.060:
.630:
.430:
.400:
.274:
.164:
.112:
.076:
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.003:
.001:
.000:
4.000:
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.400:
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.140:
.048:
.000:
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1.800:
.660:
.140:
.046:
.010:
.000:
7.000:
4.300:
5.100:
3.800:
3.800:
2.800:
6.500:
4.800:
4.100:
2.600:
3.200:
2.400:
6.484:
5.358:
3.094:
2.024:
4.026:
4.326:
5.518:
10.906:
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3.621?0
3.00870
1.79970
1.23170
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2.029
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1.587
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1.159
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1.475
1.091
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0
0
0
0
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1
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0
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0
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0
0
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                                               41;
Appendix H, page  28
                               135
-------
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
pholon
phosam
phosam
phosam
phosam
phosam
phosam
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
phosmet
:48 2:CAvPeach
:48 2:CAvPeach
:48 2:CAvPeach
:48 2:CAvPeach
:48 2:CAvPeach
:48 2:CAvPeach
:48 2:CAvPeach
:48 2:CAvPeach
:48 3:CAvPeach
:48 3:CAvPeach
:48 4:CAvPeach
:48 4:CAvPeach
:48 4:CAvPeach
:48 4:CAvPeach
:48 4:CAvPeach
:48 5:CAvPeach
:48 5:CAvPeach
:48 5:CAvPeach
:48 5:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 6:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:48 7:CAvPeach
:81 l:CAsOrange
:81 l:CAsOrange
:81 l:CAsOrange
:81 l:CAsOrange
:81 l:CAsOrange
:81 l:CAsOrange
: 3 1:AR Peach
: 3 1:AR Peach
: 3 2:AR Peach
: 3 2:AR Peach
: 3 2:AR Peach
: 3 2:AR Peach
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: 3 3:AR Peach
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4. :
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4. :
4. :
4. :
4. :
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4. :
4. :
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01.00:
01.00:
01.00:
01.00:
01.00:
01.00:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
0.716:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
375:
200:
200:
200:
200:
200:
200:
200:
200:
200:
200:
250:
250:
250:
250:
250:
250:
250:
250:
0200:
0200:
0200:
0200:
0200:
0200:
0150:
0150:
0150:
0150:
0150:
0150:
0150:
0150:
0150:
0150:
0150:
0150:
.0:
5.0:
13.0:
13.0:
14.0:
14.0:
15.0:
15.0:
7.0:
14.0:
.0:
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3.0:
3.0:
5.0:
.0:
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7.0:
11.0:
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Appendix H, page  29
                                     136
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         Appendix H, page  30
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3.998 0
3.012 0
2.114 0
1.774 0
2.207 0
3.519 0
2.102 0
5.540 0
3.544 0
3.455 0
6.399 0
3.611 0
4.056 0
2.060 0
1.418 0
1.077 0
36.532 0
41.802 0
45.884 0
38.774 0
45.306 0
41.635 0
39.243 0
32.305 0
25.053 0
23.108 0
21.154 0
19.158 0
14.32Z 0
8.705 0
6.007 0
4.018 0
3.396 0
Z.143 0
16.361 0
11.717 0
10.359 0
8.508 0
6.393 0
2.718 0
Z.259 0
1.947 0
.696 0
11.605 0
10.845 0
9.950 0
9.337 0
7.875 0
4.100 0
3.680 0
3.684 0
1.803 0
.639 0
.557 0
.221 0
Appendix H, page  31
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ethioZ
ethioZ
ethioZ
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1:FL
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.130 0
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3.206 0
1.559 0
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1.366 0
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1.699 0
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2.188 0
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1.633 0
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Appendix H, page  32
                                   139
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                                           417
ethio2
ethio2
ethioZ
ethioZ
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ethio2
ethio2
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ethio2
ethio2
ethio2
ethio2
mep2
mep2
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mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
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mep2
mep2
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mep2
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.200 0
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1.899 0
1.181 0
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3.723 0
.905 0
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1.036 0
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1.218 0
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1.694 0
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1.278 0
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1.479 0
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Appendix H.  page 33
14Q
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mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
mep2
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mep2
mep2
mep2
mep2
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mep2
mep2
mep2
mep2
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mep2
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mep2
mep2
mep2
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mep2
map 2
mep2
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2:AZ
2:AZ
2:AZ
1:AZ
1:AZ
1:AZ
1:AZ
1:WA
1:WA
1:WA
1:WA
1:WA
2:WA
2:WA
2:WA
2:WA
2:WA
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Orange:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Cotton:
Apple :
Apple :
Apple :
Apple :
Apple :
Apple :
Apple :
Apple :
Apple :
Apple :
.75:
.75:
.75:
.75:
1.00:
1.00:
1.00:
1.00:
1.00:
1.00:
.019:
.019:
.019:
.019:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
8.00:
.50:
.50:
.50:
.50:
.50:
.50:
.50:
.50:
.50:
.50:
1.00:
1.00:
1.00:
1.00:
01.50:
01.50:
01.50:
01.50:
01.50:
01.50:
01.50:
01.50:
01.50:
01.50:
100:
100: 1
100: 3
100: 7
9:
9:
9: 1
9: 2
9: 3
9: 4
10:
10: 1
10: 2
10: 3
350:
350: 1
350: 3
350: 5
350: 7
350:14
350:21
350:28
350:42
5:
5:
5: 1
5: 2
5: 3
5:
5:
5: 1
5: 2
5: 3
9: 1
9: 1
9:
9:
0400:
0400: 1
0400: 2
0400: 3
0400: 7
0400:
0400: 1
0400: 2
0400: 3
0400: 7
.0:
.0:
.0:
.0:
.0:
.5:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.5:
.0:
.0:
.0:
.0:
.5:
.0:
.0:
.0:
.0:
.5:
.0:
.5:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.0:
.155:
.055:
.015:
.004:
2.650:
.498:
.250:
.153:
.127:
.098:
.242:
.151:
.064:
.010:
18.162:
14.550:
9.208:
6.158:
4.392:
.846:
.204:
.070:
.014:
5.610:
3.310:
2.840:
1.890:
1.090:
1.370:
1.090:
.810:
.560:
.490:
.150:
.060:
2.370:
1.630:
4.740:
1.704:
1.042:
.710:
.284:
5.600:
4.396:
3.136:
3. 080:
1.400:
.000:
.000:
.000:
.000:
.014:
.015:
.007:
.002:
.002:
.000:
.000:
.004:
.000:
.000:
.072:
.186:
.244:
.238:
.226:
.192:
.128:
. 096 :
.014:
.050:
.120:
.070:
.060:
.050:
.020:
.020:
.010:
.010:
.010:
.004:
.002:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.000:?
.. 418
.554 0
.197 0
.054 0
.014 0
13.278?0
3.23070
1.60970
.87770
.74570
.50070
1.23170
.96470
.32770
.05170
62.617 0
57.360 0
45.257 0
35.617 0
28.976 0
13.071 0
7.188 0
5.031 0
.770 0
26.77070
20.40070
16.44170
11.84870
7.71370
7.67970
6.34770
4.52970
3.30070
2.95370
.95970
.40470
11.42170
8.00370
15.616 0
5.921 0
3.664 0
2.511 0
1.012 0
18.176 0
14.570 0
10.625 0
10.446 C
4.891 0
Appendix H, page  34
                              141
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                                                         419
      The Effects of Organophosphate Pesticide
     Residue Variability Upon Reentry Intervals

             Preliminary Phase II  Report
                      July 1986

                          by
               William Popendorf,  Ph.D.
University of Iowa,  Institute of Agricultural Medicine
-------
Table of Contents;
                                                                          420
Abstract
Introduction
Background
Methods
Results and Discussion
                                                                     2
                                                                     2
                                                                     4
                                                                    10
Conclusion ............................   13
References ...........................  '•   14
Table I
Table II
Table III
Table IV
Table V
Table VI

Figure  1
Figure  2
Figure  3
Figure  4
Figure  5
Figure  6

Appendix A:
Appendix B:
Appendix C:
Appendix D:
            parameter notation and subscripts  	   16
            parameter mean and variability	17
            cross-sectional variability of foliar residues  ....   18
            simulated chronic response 	  ....   19
            simulated acute response 	   20
            parathion use history  	   22
            AChE activity versus
            AChE activity versus
            AChE activity versus
            AChE activity versus
            AChE activity versus
            AChE activity versus
time for  1% daily delAChE  ...   23
time for  27. daily delAChE  ...   24
time for  4Z daily delAChE  ...   25
time for  8Z daily delAChE  ...   26
time for 167. daily delAChE  ...   27
time for 0 residue variability  .   28
            Wylber simulation program  	  A-l
            PC simulation program  	  B-l
            PC health analysis summary program 	  C-l
            Example results of PC health analysis summary program  D-l
-------
                 The Effects of Organophosphate Pesticide                  ^ *- '
                Residue Variability Upon Reentry Intervals
Abstract;
     A stochastic simulation program was written to study the importance of
residue   variability   in  preventing  anti-cholinesterase   overexposure,
excessive  chronic AChE inhibition,  or acute illness.   A range  of  daily
inhibitions and residue variability were explored, and the simulated cohort
response  was compared to the historical record of chronic and acute  data.
The  resulting  chronic  and  acute  AChE  response  patterns  are  largely
displayed in Tables IV and V, respectively.

     It  was concluded that residue variability has only a slight effect on
the  mean  AChE health status of a working cohort,  in comparison  to  mean
daily  inhibition.   Residue variability has a slightly  stronger  although
still  secondary  effect upon the overall variability of the cohort's  AChE
activity.   The  fraction  of  the cohort whose  seasonal  AChE  inhibition
exceeded  a relatively arbitrary chronic threshold of 50% was again largely
controlled  by  the  daily mean inhibition,  but at 4% per  day  and  above
virtually  the  entire  cohort exceeded that limit and  below  4%  per  day
residue variability had an increasing important role.

     On  the other hand,  residue variability appears to have a very strong
effect  upon the uniformity of the AChE activity within the  cohort.   This
nonuniformity has both chronic and acute AChE implications.   For instance,
for residue variability even below a geometric deviation of 2.0,  the crews
seasonal  AChE  inhibitions are not expected to  be  statistically  uniform
(with 997. confidence) until half way through a season;  and for variability
of  3.0  and  above,  the crews will be dissimilar throughout  the  season.
Thus,  it  is possible to have several crews below an  administrative  AChE
inhibition  threshold (or even potentially with clinical symptoms) while the
cohort  mean is only marginally different from normal.   This  pattern  has
similar implications to both the design and interpretation of epidemiologic
surveys among this population.

     Acute  responses,  in terms of individual and group AChE responses  in
excess of potential clinical symptoms, exhibit a fairly clear boundary as a
function  of both residue mean and variation.   In the low mean range of 1%
to  2% per day,  no acute individual or group incidents were predicted  for
geometric  variations  below  2.5;  however,  a  set  of  random  parathion
commercial application residues collected on days 2,  9,  and 16 all showed
variations  of  around  2.6,  just  sufficient  to  induce  sporatic  acute
responses.

     This pattern of acute effects under conditions of low chronic response
and  the  practical  boundary of a geometric deviation  of  2.5  (+  150%),

suggest  that consideration to both the mean anti-cholinesterase effect and
the  variability of the foliar residues should be considered  when  setting
administrative reentry intervals.
                                Draft                            ph2.doc
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                                                                            422
Introduction;

     The 35 year history of harvesters being poisoned while working in a
field "recently"-sprayed with an organophosphate (OP) insecticide has been
sporatically documented from scattered case reports during their earliest
use beginning circa 1950 [1-4] to whole summaries in the last 10 years
[5-10].  The consensus of opinion is that these poisonings have resulted
from excessive field residues, most likely on the foliage of the plants
being harvested rather than on the crop, per se.  The focus of interest for
the control of this occupational health hazard has been to require an
adequate time period between insecticide application and crop harvest (or
other activity) for the residue to "decay" to levels not harmful to the
harvest workers.  This time period has come to be referred to as the
"reentry interval".

     One particular review of the history and development of reentry
intervals for OP pesticides [9] resulted in a conceptual and quantitative
model which will be the basis for the study described herein.  This
"Unified Field Model" could predict short-term anti-cholinesterase effects
from either single exposures or a series of uniform exposures to
insecticides of known dermal toxicity, and was proposed to be used to set a
foliar residue limit or "reentry interval" associated with a preselected
and acceptable anti-cholinesterase threshold.  One of the key limitations
of this original proposal was the uncertainty of setting an "acceptable"
administrative threshold for daily cholinesterase inhibitions, given the
fact that real exposures are neither daily nor uniform.

     This report describes a study using this Unified Field Model to
explore the effects of variations in both the levels and frequencies of OP
exposure upon the cholinesterase activity of a harvesting cohort throughout
a harvest season.  The method used in this exploration has been Monte Carlo
simulation.  This report first reviews the background of the model; then
the methods used in these explorations; and finally their findings and
implications.

Background;

     A comprehensive report describing the reentry problem and integrating or
"unifying" the major factors controlling it, was first published in 1982 as
the Unified Field Model [9].  This basic model originally had three submodels
[9 p.132], as shown below.   Later elaborations and clarifications of this
model [11] broke out a fourth submodel [9 p.180, 11], essentially Equation
3 as follows:

                                             —k T
     Residue Decay:                R « R  exp  r                     (1)

     Dose Deposition:             D1 = k.Rt                          (2)

     Dose Absorption-Distribution: D = k  D1 / m                     (3)

     Toxic Response:         delAChE « 1 - exp"keSum(Di/LD50:i)      (4)
                                     2         2
     where R  = foliar residue, ug/cm  or ng/cm , at some point in time T
                after application.
                  Draft Report Page 2 of 28                     ph2.doc
-------
     R  = initial foliar residue, ug/cm  or ng/cm  at the time of      423
      0   application.                                 ,
     k  « pesticide exponential decay coefficient, day  ; in
          practice, multiple coefficients may be used [12], or other
          than exponential submodels or a non-mathematical (e.g.
          graphical) method may be used [9].
     T  * the time (usually in days) after application of the
          pesticide; viz. the reentry interval.
     D1 • topical dermal dose, ug of pesticide (which in a mixture
          would be subscripted i).
     k , = a crop (and possibly activity) dependent dosing
          coefficient, whose units are dependent upon those of R, D,
          and t; e.g. if units of R were ug/cm , D were ug, and t
          were hours, then k. would be cm /hr [see ref. 11],
     t  = the length of exposure, hours (assumed herein to be a
          nominal 8 -hour workday).
     k  = a dermal absorption coefficient presented in most
          pesticide literature as a percent of deposited dose [9]
          but is toxicologically more related to a permeation rate
          coefficient [13]; however, use of the latter would require a
          more detailed scenario of the total time the dose would
          remain unwashed upon the skin.  Use of the model herein
          (with submodel Equation 4 and k =6) assumes k «1.
     m  = the mass of the exposed person, kg (nominally 70 kg).
     D  = the toxicological, dermally deposited dose, mg/kg.
     k  = an enzyme coefficient relating the degree of red blood
      e   cell (RBC) acetylcholinesterase (AChE) activity to the LD5Q
          of an OF-  This submodel is an extension of an original
          finding by Grob and Harvey [14].  K  » 6 was used herein
          with a rat dermal LDcn-            e
     cg * the dose (mg/kg) of cnemical necessary [or sufficient] to
          kill 50% of the exposed animals; this submodel expects the
          use of a dermal LDcn> the subscript i for LDcn and dose D
          implies that the ACRE response to multiple, simultaneous
          OPs is additive in this fashion.
deLAChE = the fractional, acute change in AChE enzymatic activity
          relative to a pre-exposure baseline, i.e.

              delAChE = (E  . - E ) / E  .                     (5a)
                          n-l    n     n-l

                      " <*n-l 'W  -(En/En-l>           (5b)
              delAChE •      1         - (E  / E  .)           (5c)
                                           n    n~l
          and

              E /E  . - 1 - delAChE                            (5d)
               n  n-l

where E • the measurable AChE enzyme activity on post-exposure day n
          and the pre-exposure activity on day n-l.  Note also that
          the previous day (n-l) may or may not necessarily be the
          person's unexposed baseline (see later discussion circa
          Equations 12-16).
            Draft Report Page 3 of 28                      ph2.doc
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                                                                             42'
     While not essential to the development of this particular study, a
number of alternative submodels were discussed in the original document [9]
and its later elaboration [11].  For instance, exponential decay (submodel
1) is a very common temporal pattern of environmental decay for pesticides,
but it may not always apply; procedures were in fact outlined therein for
dealing with graphical or even tabular decay data.  A more complex (and
potentially far-reaching) variation upon submodel 4 may be necessary to
deal with non-cholinergic effects; one suggestion to extend the Unified
Field Model to non-cholinesterase pesticides was to use the allowable
absorbed daily or chronic dose which is typically established for all
pesticides [11 p.337].  While the quantitative Dose-Response submodel for
risk assessment might employ any of several criteria, such as a
carcinogenic extrapolation risk assessment, a generalized submodel for
acceptability (replacing Equation 4) could be viewed as follows:


     _  .  _               .  ,.,..      dermally absorbed            /•,>.
     Toxic Response:  acceptability «	*	           (.o)

                                          allowable

     where acceptability is simply the ratio of actual to allowable daily
           dose (e.g. its NOEL) for each pesticide (or analogue subscripted
           i as above); this approach is equivalent to the ACGIH TLV and
           OSHA's PEL procedure for mixtures [15,16].

     Of more direct relevance herein are the consequences of repeated
variable residues upon AChE and the associated incidents of clinical
poisoning.  The consequences of daily repeated equal residues and of
variability in single daily residues upon AChE were originally discussed
separately on pages 137-140 and 186-191 [9].  A later manuscript [11]
described the temporal pattern of chronic (seasonal) AChE response in more
detail but was still restricted to constant residues and doses.  As it is
the purpose of this report to describe the effects of repeated, variable
residues and doses, the mathematical description of the methods used herein
shall begin with the model and terminology as developed in the original
report and presented above.

Methods;

     The historical focal point of health studies on people exposed to
anti-cholinesterase chemicals has been the enzymatic activity of AChE in the
body, which is most conveniently and routinely measured in the blood by
various laboratory procedures [17].  In health research settings, the effect
on a person's AChE is commonly expressed as a change relative to the study
subject's individual baseline activity, viz. delAChE as shown in Equation 5a
or 100 x delAChE expressed as a percent [6-8].  This concept reflects the
fact that individuals differ in their enzymatic activity but that health
effects accrue from changes in their activity relative to either their
normal (unexposed E ) or pre-exposure baseline (E  ,).  Note also that a
"pre-exposure baseline" implies that there may have been exposures with some
enzyme inhibition prior to the exposure in question and that normal and pre-
exposure levels are only equal for the first exposure (dose) of the season.

     An alternative to delAChE which is mathematically and biochemically
more convenient, is to look directly at the individual's relative activity
En^En-l °r En^Eo where En» En-l' and Eo are the Person's current, pre-


                  Draft Report Page 4 of 28                     ph2.doc
-------
                                                               29 Jul 86
exposure, and personal normal baseline activities, respectively [14,17].
One might think of this ratio as the person's health status (in fact this
shall later be called "H").  The relationship defined in Equation 5d
permits the direct use of the basic Unified Field Model Equations 1-4 to
also predict E /E _..  Thus, Equations 2 through 5 may be combined into one
complete equation, as follows:
     E /E   . - exp'W s^V" ^50, i)  - 1 - delAChE             (7)
      n  n~l

It may be convenient at this time to introduce the fact that values of many
of the model's variables and coefficients will differ among the chemical
components  within a residue (i), among the people within the cohort (j),
and from day to day (n).  These values are subscripted in the following
rewrite of  Equation 7:

      E.  /E.   . - wtp^duWn suffl(Ri,n ' nj LD50:i)              (8)
       j »n  j ,n i
     where  the following subscripts when used with subscripted coefficients,
     follow a colon:
            i = chemical component of the residue,
            j » person within the cohort,
            n = day within the season

     As noted above in Equations 5d, 7 and 8, the enzyme "health" status
ratio E.  /E,   . is relative to a generalized pre-exposure E  1 enzyme
activity 'valuenwnich may be either a true "baseline" (E ) or an already
partially inhibited level of activity.  Clinical health°effects are often
related to  this acute change in activity [14,17], but focus for standards
requiring infrequent biological monitoring of AChE is chronic or cumulative
seasonal changes relative to a person's unexposed baseline, E  [9].  As a
notational  convenience to aid the reader, the acute fraction E.  /E.   , for
a given person "j" on a given day "n" as defined by Equation 8Jw?llJ '
hereafter be noted by K,   (similar to a K notation without subscripts
used in the original repdrt [9]), as follows:
                                                     »J LD50:i)      (9)
Thus,

     EJ.n ' KJ.n EJ.n-l
And as another notational convenience, the fractional activity relative to a
normal baseline E.  /E,   will be noted by H.    which can easily be related
to the acute pre-exposufi effect K,   via Eqia?ion 10, as follows:
                                  j»n
     Hj.n-EJ.n/I!J.o   ' «,.„ WVo  -  KJ.n (Ej.n-l'Ej.o>
     But before using Equations 9-11 to predict long-term (i.e. cumulative
seasonal) changes in E, two biochemical and physiologic processes must be
included within the model.  These are (a) reversible inhibition or
reversion, the fact that recently inhibited enzymes are bound somewhat
reversibly, and that over a few hours a generally small fraction of the
enzymes will revert or return to their active state; and (b) regeneration,
the normal process of erythropoiesis (red blood cell production) which will
result in the generation of new RBC AChE and the accompanying process of


                  Draft Report Page 5 of 28                     ph2.doc
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                                                                            126
removal of a proportional fraction of inhibited RBC AChE.  In the original
report [9], these two processes were termed o1 and o, respectively.

     Although the detailed process and temporal pattern of reversion is not
completely understood, it may proceed for 6 to 30 hours or so after
exposure.  Values for o1 range from 0 to 10% for the strong inhibitors such
as TEPP and Sarin studied by Grob [14], to circa 15 to 20% for parathion
[9], to nearly 100% for most carbamates [15].  The modeled effect of
reversion is that the post-exposure enzyme activity E/E  is increased
after one day (24 hours) to a new fraction E'/E  by the reversion of a
certain fraction of the recent acute inhibition:

     reversion = o1 (1 - KR) - c-' delAChE                            (12)

     where o1  * the fraction of recently inhibited enzymes which becomes
                  unbound.

     The process of regeneration of RBCs is believed to be independent of
exposure and inhibition, as is the accompanying process of removal of old
RBC by the liver which is assumed to remove cells with both active and
inactive AChE indiscriminately.  Values of o for man range from 0.008 to
0.012 per day (average RBC life times of 85 to 130 days) [18].  In the
context of enzyme activity, the overall effect is one of replacement of
some old, inhibited enzymes with fresh, uninhibited enzymes.  The net effect
on the long-term model is that each day a fraction (o) of new RBC and
associated AChE are produced and an equal fraction of old RBC are removed
along with a somewhat lesser amount of active AChE proportional to the bulk
blood activity (or o x E /E ).  Here a mathematical approximation is made to
the model to account for the fact that E /E  may be changing throughout the
day due to the on-going process of reversion of recently inhibited enzymes.
As a convenient first-order approximation, the linear average relative
enzymatic activity over this period is assumed.  Thus,

     regeneration = o - (o/2 (E /E  + E'/E ))                        (13)
                    \\nono

     where E1 - E  + a slight improvement after 24 hours by virtue
            n    of reversion, see Equation 12.

     These processes were modeled within the original report only to
predict the net effect of repeated equal exposures [9 p.137-140].  Herein,
they are used to predict the entire pattern of the cumulative seasonal
response (E.  /E.  ) which would result from a random series of
variable reslaues'?R.  ).  To predict the cumulative effect of variations
in repeated unequal occupational exposures, one begins with responses
(K.  ) predicted from Equation 9 and the post-exposure enzyme health status
predicted by Equation 11.  Subsequent to each exposure and predicted acute
response, the body will undergo a level of recovery so that the next day's
"pre-exposure" baseline is slightly improved over that at (or shortly
after) the end of the previous day's work.  This improved enzyme activity
shall be defined as H' n (or E'. n/E.  ).  Therefore, to the initial post-
exposure health status'predicted by^Equation 11 shall be added the effects
of reversion (Equation 12) and regeneration (Equation 13) with the
appropriate person subscripts "j" inserted as needed:
                  Draft Report Page 6 of 28                     ph2.doc
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     Ej.n/Ej.o
Or.
     Ej.n/Ej.o - "WE3.o(1 - */2> + Vj<> * Kj,n>
                                                  2 (Ej.n/Ej,o>
And now solving for E*  /E.   which appears on both sides of Equation 14:
                     J »n  j ,o
     EJ.n"j.o(1 + ?/2) - Ej,n/Ej,o(1 -
  /E.  (1 - o/2) + o!(l - K.
*S.J*2 ..... i ...... & ...... 4iD
                                                   ) +
      J'n  J'°                   (1 +o/2)

     As indicated circa Equation 5d, it is this slightly recovered enzyme
activity level of Equation 16 which becomes the pre-exposure value for
succeeding exposures (E.   ./E.   in Equation 11), or
                       J»n-i  j,o

     H. n-1 - E. n.1/E. Q - E! n/E. Q - H'n_1                        (17)


     The above iterative sequence of daily inhibition (Equation 9-11) and
partial recovery (Equation 16) lends itself nicely to a digital program
which re-iterates this calculation, day-by-day throughout the season.  A
stochastic or Monte Carlo simulation computer program was written to permit
the parametric random variation of many of the factors described above (see
Appendices A-C).  In principle, the Monte Carlo simulation process could
create a heterogeneous population of values for any model parameter
distributed about a mean value with virtually any specified variability [19J.
Table I summarizes the terms within this study which are varied and fixed,
their notation within the text, and the subscripts assigned to those
parameters permitted to vary during this study.

     A number of modeled factors were either not varied or not used at
all, in particular, the residue application and decay coefficients.  The
initial plan for this project intended to begin these variations from the
point of residue application, i.e. to randomize R  and the decay
coefficients (k ) as used in a multicomponent decay model [12].  The
intended decay model for paraoxon follows:

                   K|K-                 Ky K«
     R         , —_i.±i9_- exp-klT + —S-fi2. exp-k3T +
      paraoxon    .     ,                .     .
                  K5 " Kl              K5 " *3


                       (R_	*---	12__) exp-k5T        (18)
                         3'°    k  - k      k  - k
                                K5    1      5    3
                  Draft Report Page 7 of 28                     ph2.doc
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     where the subscripts it to                                              "eg
            k,, indicate one of five k  coefficients used in this particular
             " model [12], and       r
          R..   indicate one of two portions of the initial paraoxon residue
           ff'° [12].

Considerable difficulty with this approach resulted from the existence of a
"pole" in these equations (i.e. when the denominator approaches zero, the
value of the  residue becomes impossibly large).  When the residue at
selected points in time was calculated using the above decay submodel with
randomly varying coefficients based on field data [12], such impossibly and
unrealistically high  values sporadically resulted.  To avoid this
difficulty, the residue at initial reentry R was randomized directly;
therefore neither k  nor T was used within this simulation, as noted in
Table I.           r

     For other reasons k  was also not used within this simulation (since a
dermal LD_Q value was aslumed, the absorption coefficient k  would have been
set to unity as intended by the original Unified Field Model.  Various
other parameters in the Unified Field Model were used but not permitted to
vary.  For example, Values for dermal toxicity were not varied since only
one generic OP was examined and variations in interpersonal susceptibility
was already accounted for by k  ., m., o1, and o.  As a first approximation
and to obtain a more clear understanding of the effects of variability
caused only by people and their daily residue, the length of the workday
was assumed constant.  Later elaborations of this study could include more
daily variations or even an interaction as from a hypothetical effect of
decreased enzyme activity upon the harvester's physical ability to sustain
an 8-hour workday (t) and a uniform work-rate (equivalent here to the
dosing coefficient k,).

     The concept of Monte Carlo simulation is that any factor can be varied
at random in any of a wide range of possible distributions [19].  This
particular study assumed that the factors listed as "varied" in Table I
were assumed to be either normally or log-normally distributed (the
logarithms of log-normally distributed values are themselves normally
distributed).  The mean and variability of each of the varied terms is
listed in Table II.  Most of these factors are assumed to be log-normal,
although for small deviations (equivalent coefficients of variation less
than 50%) it makes little difference whether normal or log-normal
variability is assumed.

     The particular form and magnitude of the parametric characterization of
R was selected from experimental experience with environmental samples
generally and foliar residue samples in particular [9],  Such samples are
invariably distributed in a skewed manner approximating a log-normal
distribution.  The largest available set of multiple foliar residue samples
collected on the same day(s) post-application but from a variety of
commercial applications is listed in Table III.  It is clear from the
relative size of the standard deviations compared to the arithmetic mean
values, that these data are not normally distributed.  The acceptability of
fit of these data to a log-normal distribution was confirmed by a Univariate
Analysis on the pooled data.  The pooled geometric deviation for all six
sets of samples is 2.6 or 160%, a point of reference for later comparisons.
                  Draft Report Page 8 of 28                     ph2.doc
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                                                                    --  429
     Two versions of the simulation program (Appendices A and B) were
utilized during this study.  Version A was designed to run on a large
mainframe computer (viz. an IBM 370/168 (with VM/CMS operating system)) and
utilized two commercially available subroutines (IMSL).  This version can
only be operated- in the batch mode and generates its model parameters by
randomly drawing separate sets of personal characteristics and field
residues for each crew from pseudo-infinite, parametrically distributed
universes for each respective model parameter.  The benchmark runs were made
with Version A, primarily because of its earlier availability.

     To expand portability to other computers and add further flexibility to
the exposure patterns which could be simulated, a second version was written
for Fortran-77 which can be (and was) run on an IBM - PC.  It utilizes two
published subroutines [20-21] to create parametrically distributed sets of
personal characteristics for the entire cohort and all field residues, then
randomly distributes this cohort and field residues among the crews.

     There are a number of differences between these two approaches: the
latter version consistently creates an entire study population of harvesters
or residues which fits the desired parametric distribution virtually exactly
(versus an F(°°,n) sampling error in the cohort created by the former version
which is a function of the cohort size, n; for 216 harvesters the 99%
confidence limit on achieving the parameter variability requested is + 15%
and for 916 field residues is + 6%).  At the same time, the variability of
each crew created by the latter method is only slightly larger than the
former (a sampling error which is a function of both the cohort and crew
sizes; for the population cohort of 216 and crew size of 12 used within
this study, the crew sampling error for both approaches is about 2-fold
(+ 98% versus + 99%, respectively)).

     Operationally, the simulation program (Appendix B) first creates a
cohort of harvesters.  Each harvester is randomly characterized in terms of
work habits (k.), weight (m), enzyme susceptibility (k ), and reversion-
regeneration coefficients.  This population is then distributed among
"ncrews" with "npersons" per crew.  An array of parametrically distributed
residues at reentry is also created and randomly assigned to each field.
For this series of simulations, each harvest crew works alternately two or
three days for 8 hours within two fields each week (five days per week).
Initially H.   • H.   • 1.  Each day the acute K.   is determined by
Equation 9,J4nd H.J'°by Equation 11.  At the startnof the next exposure day,
H1.   is determined'By Equation 16; and the process, beginning with acute
inhibition, is repeated.  Non-exposure days are handled in much the same
manner (except of course K  =1.0 for all j).  The program records the
enzyme health status (H) fcr each harvester within each crew from field to
field for a 26 week (six month) harvest season.

     Finally a second program (Appendix C) was written to analyze this
detailed personal health history to determine the following:

     0AM and OGM = the overall arithmetic and geometric mean delAChE of the
         cohort, respectively.
     PSD and PGD = the pooled standard and geometric deviations of the
         cohort, respectively.
     F * an analysis of variance F test statistic characterizing the
         uniformity or dispersion of delAChE within the crews versus among


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                                                                              43C
         the crews.  It was expected that the crews will be significantly
         different from each other as a function of residue variability but
         will become more uniform with passing time.
     Poi// * the daily incidence of individual OP "poisoning" cases based on
         one of four threshold criteria:
          (1) acute response, a delAChE of at least 507. in 1 day,
          (2)   "      "      "   "     "  at least 65%  " 2 days,
          (3)   "      "      "   "     "  at least 75%  " 3 days,
          (4) chronic  "      "   "     "  at least 50% versus E.  .
                                                                J»°
An example of the print-out from this program is shown in Appendix D.  The
first three of the above poisoning counters are also summarized by the total
number of poisoning cases, the number of days (nominal number of fields) in
which the above cases occurred, and the number of potentially reportable
incidents (assumed here to require at least one-half of the crew to have
exceeded one of the above criteria in one day).  In practice the 1-day acute
and seasonal chronic "poisoning" will be the primary focus of discussion.

Results and Discussion;

     A depiction of the cohort mean delAChE response throughout the season
is presented in Figures 1-5 grouped by daily mean inhibition (with residue
variability as a co-factor) and in Figure 6 grouped by variability equal to
1.0 (with daily mean inhibition as a co-factor).  A summary of the end-of-
season (chronic) AChE conditions are tabulated in Table IV.  By comparing
the vertical spread in the cohort mean response lines within Figures 1-5
with those in Figure 6, it can be stated that variations in the daily mean
inhibition (l-K ) have a greater impact on the chronic state of inhibition
than does residue variation, per se.  The rate at which these simulated
cohorts approached their seasonal lows varied from "half-response" times of
about 2 months for low daily inhibitions (1%) to about 2 weeks for high
daily inhibitions (16%).

     These chronic response patterns are similar to earlier predictions [11,
p. 330] except that they assumed uniform exposures 7-days per week.
Another feature not seen before is the weekly cycle of inhibition and
partial recovery as the level of inhibition approaches 60% or greater; for
relatively high daily inhibitions (circa 8 to 16%), the combination of
reversion and regeneration results in recoveries of as much as 4% of the
baseline normal over a weekend, which becomes more visible on the expanded
scale near the bottom of these figures.

     Based on the first row of data in Table IV, it appears that the only
practical daily inhibition (i.e. residues with any variability at all) for
which seasonal inhibition will be less than 50% is 1% per day.  This is
similar to the prediction in reference 9 (p. 140) of 1 to 2% per day for
40% seasonal inhibition given a 7-day per week exposure pattern.  The
variability in the seasonal inhibition is indicated by the second row of
data, the geometric deviation.  It appears that the relative variability in
the seasonal low AChE activity is reduced primarily as the daily
inhibitions increase and secondarily as the variability in the residues
increases.  This pattern is explainable by the overwhelming importance of
the magnitude of the daily inhibition in relationship to the speed of
enzyme reversion and replacement.  The impact of variability on the
fraction of the cohort whose seasonal inhibition exceeds 50% is indicated


                  Draft Report Page 10 of 28                     ph2.doc
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                                                               29 Jul 86


by the third row of data  in this table: the trade-off between low levels or -^ '
daily inhibition and relatively high levels of variability causes there to
be some fraction of the cohort which exceeds 50% under all conditions,
although again this fraction increases primarily with increasing levels of
daily inhibition.

     As it will be discussed in relation to acute responses, the
significance of these simulated chronic responses in relation to future
human experience is best  judged in relation to past experience.
Unfortunately the history of past chronic cholinesterase studies among
harvesters has hardly been reported.  One rather unique study of one East
coast migrant crew by Owens and Owens [24] was referenced in the
elaboration of the Unified Field Model [11] showed seasonal inhibitions of
30 to 40%, but the more detailed analyses of their data has not been
accomplished.  Another known report was a student master's thesis of some
822 California central valley harvesters in 1970 which showed seasonal
inhibition of 5 to 8Z [25].  In both studies neither the intensity nor
frequency of residue exposure was known; therefore, direct comparisons of
the chronic response between this simulation and human experience is barely
possible.

     In general, such chronic longitudinal studies are difficult to
initiate, organize, maintain and analyze.  Of practical importance is the
effect on data analysis of the relative size (and numbers) of individual
crews into which the whole cohort is distributed.  Included in the results
printed by the data summary program is the analysis of variance F statistic
indicating the uniformity between the crews versus within the crews (and
the cohort as a whole).   Initially these test statistics are quite large,
indicating statistically  greater variation between crews than within crews
(except of course, when the variability in the residues is 0 (geometric
deviation of 1.0).  Over  time, the crews become more and more consistent,
and the daily F statistic decreases.  A value of about 2.0 indicates
statistical uniformity with 99% confidence.  The fourth row of Table IV
indicates the number of days into the season necessary for such inter-crew
uniformity to be established.  From this data it is clear that residue
variability is the dominant factor characterizing inter-crew uniformity and
that statistical uniformity is not achieved within a six-month season for
levels of variability of  3 or more.  This conclusion implies that an
adequate interpretation of harvester cholinesterase survey data must take
into account the grouping of that data by crew; similarly, some crews
should be expected to be  significantly more inhibited than others or than
the group as a whole.

     The preceding discussion of chronic response variability is directly
relatable to acute "clinical" responses which represent the high "tails" of
the daily statistical distribution.  A summary of acute response data are
depicted in Table V only  (rather than in figures).  The first row of this
table indicates the frequency with which individual harvesters might have
RBC AChE shifts sufficient to induce clinical symptoms.  It appears that
while the incidence of chronic seasonal inhibition is high under many of
the scenarios investigated, the incidence of clinically acute responses is
undetectable under a much broader range of residue conditions.  Practical
conditions without incidents begin at 8% per day if the variability can be
kept at or below 1.5; at  4% per day, below 1.5; 27. per day of at or below
2.0; and 1% per day if variability approaches 3.0.  It also appears that


                  Draft Report Page 11 of 28                     ph2.doc
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once conditions of daily mean or residue variability are sufficiently
to cause one individual acute case, multiple cases (the second row) and
incidents involving at least half the crew (the third row) begin to occur;
this pattern is relatable to the inter-crew versus intra-crew uniformity
discussed above.•  Therefore, a reasonable administrative target is to
prevent any individual cases of anti-cholinesterase poisoning sufficient to
cause clinical symptoms.

     Fortunately the significance of these simulated acute responses in
relation to future human experience is more readily judged in relation to
past experience than was true for chronic cholinesterase effects.  Several
tabulations of "reported" poisoning incidents from the literature are
available to provide a first estimate of past field experience [3,6,8].
These data indicate an incidence of about 25 harvesters and 1 "incident"
reported in California per year from 1948 to 1977; although two other
independent reports indicate the above values "represent perhaps 1% of of
the persons who suffered less severe symptoms, received medical treatment,
but remained unreported" [9].  Most (but not all) of these reported cases
involved parathion.

     The denominator for these cases can be estimated from the roughly
74,000 acres of Valencia oranges in California [26] (the variety harvested
during the April-September prime parathion application period; see Table VI)
and reported individual harvest rate data [27], which indicate about 7400
harvesters are actively engaged in harvesting the seasonal crop most
commonly involved in reported residue poisoning incidents [3,6,8].  The
denominator for these incidents can be closely approximated from California
Pesticide Use Reports, Table VI, which for the early 1970s was about 2000
fields and circa 60,000 acres of oranges (of which about 50% was summer
valencias) sprayed per year [28].  Thus, on an annual average over the
thirty year history, about 25/7400 = 0.34% of the orange harvesters in
California have been involved in a reported residue poisoning per year and
1/1000 = 0.1% of the field applications have resulted in reported incidents.

     Recall also that the variability in parathion residues on citrus was
2.6 (Table III); furthermore, the equivalent anti-cholinesterase power of
the residues on day 9 was about 8% and on day 16, about 4%.  Since
California had, prior to 1970, an administrative harvest - reentry interval
for parathion of 14 days, a mean daily inhibition of 4% is the worst
expected scenario to simulate historical experience.  Although it is
unlikely that every field was harvested as soon as its reentry interval had
elapsed, it is possible that a great many of these fields could have been
harvested between that time and 2 weeks later (or about 2 half lives and
l/4th the AChE effect later).

     Locating these conditions in Table V indicates a reasonably good
agreement between the simulation and historical record.  The simulation
indicates a somewhat higher incidence of individual overexposures than the
historical record shows, but well within the higher range estimated by the
"critics" of the established reporting system.  On the other hand, the
simulation indicates an incidence of "potentially reportable" group
incidents somewhat lower than reported.  There are many possible
explanations for this latter difference, among them are (1) a difference in
the ratio of number of crews and crew size from that modeled, (2) an overly
conservative definition of "incident" (i.e. at least 50% of the crew having


                  Draft Report Page 12 of 28                     ph2.doc
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an AChE shift of 50% or more), and (3) other than a log-normal distribution  A ? 7
of foliar residues (i.e. a bimodal distribution with unexpectedly more
frequent high residues under some relatively unique combination of
environmental and/or application conditions, or possibly some combination of
the above.  Whatever the reason, the differences are relatively slight;
proving the value of this stochastic simulation procedure.

Conclusion;

     A stochastic simulation program was written to study the importance of
residue variability in preventing anti-cholinesterase overexposure,
excessive chronic AChE inhibition, or acute illness.  A range of daily
inhibitions and residue variability were explored, and the simulated cohort
response was compared to the historical record of chronic and acute data.
The resulting chronic and acute AChE response patterns are largely displayed
in Tables IV and V, respectively.

     It was concluded that residue variability has only a slight effect on
the mean AChE health status of a working cohort, in comparison to mean daily
inhibition.  Residue variability has a slightly stronger although still
secondary effect upon the overall variability of the cohort's AChE activity.
The fraction of the cohort whose seasonal AChE inhibition exceeded a
relatively arbitrary chronic threshold of 50% was again largely controlled
by the daily mean inhibition, but at 4% per day and above virtually the
entire cohort exceeded that limit and below 4% per day residue variability
had an increasing important role.

     On the other hand, residue variability appears to have a very strong
effect upon the uniformity of the AChE activity within the cohort.  This
nonuniformity has both chronic and acute AChE implications.  For instance,
for residue variability even below a geometric deviation of 2.0, the crews
seasonal AChE inhibitions are not expected to be statistically uniform (with
99% confidence) until half way through a season; and for variability of 3.0
and above, the crews will be dissimilar throughout the season.  Thus, it is
possible to have several crews below an administrative AChE inhibition
threshold (or even potentially with clinical symptoms) while the cohort mean
is only marginally different from normal.  This pattern has similar
implications to both the design and interpretation of epidemiologic surveys
among this population.

     Acute responses, in terms of individual and group AChE responses in
excess of potential clinical symptoms, exhibit a fairly clear boundary as a
function of both residue mean and variation.  In the low mean range of 1% to
2% per day, no acute individual or group incidents were predicted for
geometric variations below 2.5; however, a set of random parathion
commercial application residues collected on days 2, 9, and 16 all showed
variations of around 2.6, just sufficient to induce sporatic acute
responses.

     This pattern of acute effects under conditions of low chronic response
and the practical boundary of a geometric deviation of 2.5 (or + 150%),
suggest that consideration to both the mean anti-cholinesterase effect and
the variability of the foliar residues should be considered when setting
administrative reentry intervals.
                  Draft Report Page 13 of 28                     ph2.doc
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                                                                             434
References;

 1. Abrams, H.K., and A.R. Leonard: Toxicology of Organic Phosphate
    Insecticides. Calif. Med. 73:183-186, 1950.
 2. Ingrain, F.R.: Health Hazards Associated with Use of Airplanes for
    Dusting Crops with Parathion.  Amer. Ind. Hyg. Assoc. Quart. 12:165-
    170, 1951.
 3. Quinby, G.E., and A.B. Lemmon: Parathion Residues as a Cause of
    Poisoning in Crop Workers.  J. Amer. Med. Assoc. 166:740-746, 1958.
 4. Milby, T.H., F. Ottoboni, and H. Mitchell: Parathion Residue Poisoning
    Among Orchard Workers.  J. Amer. Med. Assoc. 189:351-356, 1964.
 5. Milby et al.: Occupational Exposure to Pesticides.  A Report of the
    Federal Working Group on Pest Management, Washington DC, 1974.
 6. Spear, R.C., W.J. Popendorf, J.T. Leffingwell, and D. Jenkins:
    Parathion on Citrus Foliage: Decay and Composition as Related to Worker
    Hazard.  J. Agr. Food Chem. 23:808-810, 1975.
 7- NIOSH: Proceedings; Pesticide Residue Hazards to Farm Workers. U.S.
    Dept. HEW Pub. No. (NIOSH) 76-191, 1976.
 8. Gunther, F.A., Y. Iwata, G.E. Carman, C.A. Smith: The Citrus Reentry
    Problem: Research on its Causes and Effects, and Approaches to its
    Minimization.  Residue Reviews 67:1-139, 1977.
 9. Popendorf, W. and J.T. Leffingwell: Regulating OP Pesticide Residues
    for Farmworker Protection.  Residue Reviews 82, 125-201, 1982.
10. Dermal Exposure Related to Pesticide Use; Discussion of Risk
    Assessment, ed. by R.C. Honeycutt, G. Zweig, N.C. Ragsdale. American
    Chemical Society, Washington DC, 1985.
11. Popendorf, W.P.: Advances in the Unified Field Model for Reentry
    Hazards, p. 323-341, op cit., 1985.
12  Popendorf, W. and J.T. Leffingwell: Natural Variations in the Decay and
    Oxidation of Parathion Foliar Residues.  J. Agric. Food Chem. 26:437-
    441, 1978.
13. Scheuplein, R.J.: Percutaneous Absorption After Twenty-five Years: or
    "Old Wine in New Wine Skins." J. Invest. Dermat. 67:31-38, 1976. (not
    his latest).
14. Grob, D. and A.M. Harvey: Effects in Man of the Anti-cholinesterase
    Compound Sarin (Isopropyl Methyl Phosphonofluoridate). J. Clin. Inv. "
    37:350-368, 1958.
15. ACGIH Threshold Limit Values and Biological Exposure Indices for 1985-
    86. TLV for Mixtures, p. 47, Amer. Conf. Governmental Industr. Hyg.
    Cincinnati, OH, 1986.
16. OSHA Safety and Health Standards (29 CFR 1910.1000) U.S. Dept. Labor
    Pub. No. (OSHA) 2206, Washington DC, 1983.
17. Wills, J.H., and K.P. Dubois: The Measurement and Significance of
    Changes in the Cholinesterase Activities of Erythrocytes and Plasma in
    Man and Animals. CRC Critical Reviews in Toxicol. 1:153-202,1972.
18. Geigy Scientific Tables Vol. 3, 8th Ed., edited by C. Lentner, Ciba-
    Geigy, W. Caldwell NJ, 1984.
19. Rubinstein, R.Y.: Simulation and the Monte Carlo Method. John Wiley &
    Sons, New York, 198T~~
20. Odeh, R.E. and J.O Evans: The Percentage Points for the Normal
    Distribution, AS 70. Appl. Statist. 23:96-97, 1974.


                  Draft Report Page 14 of 28                     ph2.doc
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                                                               29 Jul 86


21. Wichmann, B.A. and I.D. Hill: An Efficient and Portable Pseudo-random     435
    Number Generator, AS 183. Appl. Statist. 31:188-190, 1982.
22. Gage, J.G.: The Significance of Blood Cholinesterase Activity
    Measurements.  Residue Reviews 18:159-173, 1967.
23. Gaines, T.B.: Acute Toxicity of Pesticides. Toxicol. Appl. Pharmacol.
    14:515-534. 1969.
24. Owens, E.W. and S.Y. Owens. Science, submitted 1984.
25. Ray, R. Occupational Exposure to Organophosphate Pesticides among
    Agricultural Workers and their Families.  MS Thesis, University of
    California, Berkeley CA, 1972.
26. California Crop and Livestock Reporting Service, 1981.
27. Popendorf, W. and R.C. Spear: Preliminary Survey of Factors Affecting
    the Exposure of Harvesters to Pesticide Residues.  Amer. Industr. Hyg.
    Assoc. J. 36:374-380, 1974.
28. Pesticide Use Reports, California Dept. Food and Agriculture,
    Sacramento CA, for the years noted (1972-1982).
                  Draft Report Page  15 of  28                      ph2.doc
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                                                                             436
Table I.  Equivalence of the terms and notation used in the text of this
report versus the notation used in the programs listed in Appendix B and C.
Terms are listed according to the subscript by which they were varied (or
if in parentheses, by which they could have been varied).
Terms not used:
  initial residue
  reentry interval
  absorption coef.
                          m
                    text subscript
                          text
                         notation
terms varied:
  reentry residue
  daily field residue
  dosing coef.
  body weight
  enzyme coef.
  reversion coef.
  regeneration rate
terms not varied:    .
  residue decay coef.
  work day
  dermal tox.
  enzyme measurement
                           r
                          LD
                            50 :
                          T
                          k.
                                    chem.
                                     i
                                    (x)
                                            crew
(x)a

(x)



(x)a

(x)
                  program subscript  mm
                                    chem.
               person
                 j
                                             x
                                             x
                 X
                 X
                 X
                 X
                 X
                                             i
                                            crew
 (x)

  j
person
         day
          n
          x
          xa
         (x)
         (x)a
                         k
                        day
program
notation

  res
   r
   kd
   wt
   ke
   PP
   P

(x)

(x)

(x)

xb
half
hwpd
Id50
vlab
 program
 notation
  footnote:
     a) term effectively varied by variations in R  above.
     b) capability to vary laboratory measurement technique was built in to
        program, but unused throughout the majority of the  study.
                  Draft Report Page 16 of 28
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                                                                            437
Table II.  A summary of the mean and deviation for each model parameter
used within this study.  Deviations followed by "x" denote geometric
deviations (multipliers and dividers of the mean); those with units are
geometric deviations (the normal distribution).
terms varied:

  reentry residue

  dosing coef.
  body weight
  enzyme coef.
  reversion coef.
  regeneration rate

terms not varied:    .
  residue decay coef.
  work day
  dermal tox.
  enzyme measurement
                           i.n
                           ., ,

                           '"
                          t
                          LD
                                   mean
                            50:i
5.1 cm
70  kg
6.0
0.15 day-1
.893 Z/day
  7  days
  8  hours
 10. mg/kg
            deviation
1.0 to 4.0 x

 1.41  x
+ 7 kg
"1.3   x
 1.01  x
 1.046 x
                reference
[6,12]

[9]
[9]
[9]
[9,14,15]
[18]
                  [12]
                  [15,16]
                  [9,22]
                  [9,17,23]
  footnote:
     a) initial mean reentry residue levels were determined from the Unified
        Field Model based upon the mean daily delAChE response specified by
        the user of the program; each of the following combinations of mean
        residue and residue variability were investigated:
        geometric deviation 1.0
                            1.5
                            2.0
                            3.0
                            4.0
                                  mean delAChE
                                   1%   2%   4Z
               8Z   16Z
                  Draft Report Page 17 of 28
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Table III .  Summary of foliar-dislodgeable parathion (thion) and paraoxon
(poxon) concentrations, ng/cm  from commercial citrus groves sampled on the
same day post-application [reference 6].
                                                                              438
       day  thion    poxon
day  thion    poxon
day  thion    poxon








































arth
std.

geom
geom
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
.mean =
dev. =
N =
.mean =
. dev . =
264.1
398.5
412.6
1434.
180.8
170.9
149.7
190.7
49.75
252.3
186.7
103.5
174.7
294.7
89.13
240.5
688.5
229.2
483.4
1297.
172.6
438.6
152.8
417.3
771.0
386.7
617.8
363.1
199.7
482.8
893.0
562.9
216.0
1724.
303.6
327.2
418.5
193.9
234.6
607.1
419.3
365.1
40
316.0
2.12
18.63
32.07
29.71
109.2
89.60
71.44
108.9
10.54
6.272
33.72
52.82
21.41
35.13
33.72
23.06
20.91
25.46
51.64
166.5
227.3
327.7
396.1
15.66
24.99
365.5
11.44
320.7
32.07
145.0
325.7
276.8
38.02
24.70
92.55
159.7
262.6
62.19
90.48
96.08
210.7
111.2
114.6
40
63.31
3.08
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9
9











29.94
55.17
95.49
311.2
22.85
17.38
6.319
13.49
7.451
26.64
20.77
22.73
27.59
32.77
19.64
43.62
48.34
57.77
12.05
119.8
21.06
42.68
7.710
38.20
69.32
42.91
67.20
20.30
24.05
15.51
45.39
15.59
92.84
80.76






46.31
54.40
34
31.65
2.33
12.61
33.01
11.67
64.84
25.46
20.42
25.94
2.759
1.252
19.92
16.98
9.290
14.05
12.43
6.201
18.13
11.13
24.99
53.76
135.1
65.78
71.91
4.551
16.41
51.17
15.51
115.3
13.16
22.40
65.31
95.79
9.549
27.62
40.67






33.38
32.75
34
21.16
2.83
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16










9.526
24.52
49.75
113.9
7.474
9.148
5.965
3.466
1.250
9.785
7.144
7.946
10.87
6.272
13.46
8.205
11.48
11.95
5.376
39.14
32.54
2.358
3.843
3.631
20.84
11.93
24.05
4.409
8.583
13.03
10.49
3.773
18.04
35.96
24.73





16.42
20.44
35
10.51
2.52
6.956
8.983
10.12
49.99
7.286
7.875
9.974
1.582
.6413
10.09
6.508
7.309
9.384
6.696
1.846
7.215
7.097
11.51
21.41
21.08
20.58
17.97
2.499
4.951
25.46
4.716
58.00
7.026
13.16
90.19
19.54
4.362
20.45
26.23
29.77





15.96
18.04
35
10.00
2.76
Pooled geometric deviation = 2.61
                  Draft Report Page 18  of 28
                                  ph2.doc
-------
                                                               29 Jul 86
                                                                         439
Table IV. Chronic Response to exposures 5 days per week distributed among 18
crews of 12 persons each working alternately 2 and 3 days per field (see
also Figures 1-6):
   1) The typical mean pseudo-equilibrium AChE activity expressed as a
      percent of normal baseline of each individual for the harvester cohort
      as a whole  in mid- to late in the last week of the season.
   2) The geometric deviation for the above data, expressed as a percent +
      of the mean.
   3) The prevalence (expressed as percent) of harvesters who have exceeded
      50% inhibition of RBC AChE by the end of the season.
   4) The number of days into the 182 day (26 week) season necessary for
      the analysis of variance F statistic to decrease to or below 2.00
(the critical F
                     ._
                     ii i
Geometric

Deviation
1.0
1.5
           2.0
           3.0
4.0
                            test statistic for 99% confidence of uniformity).
          1%

          35
         +30*
         "6-7%
           0

          37
         +29%
         "6-8%
          38

          40
         +27%
         12-18%
         117
  54
 +17%
 69-74%
>182
                               Daily    Mean   delAChE
                               27.        4%        87.
            50
           +20%
           53-56%
             0

            52
           +19%
           58-63%
            39
            65
           +12%
           "97-99%
             0

            66
           +11%
           98-99%
            38
                                                   75
                                                 +7%
                                                 "lOO%
                                                    0

                                                   76
                                                 +6%
                                                 100%
                                                   37a
55
+17%
69-74%
119
68
+10%
> 9g%
140b
77
+ 6%
100%
>182
47
+22%
41-46%
175
61
+13%
90-94%
>182
71
+ 8%
> 98 %
>182
78
+ 5%
100%
>182
  66
 +10%
 95-97%
>182
                                         74        80
                                        +6%    +4%
                                        99-100% " 100%
                                       >182      >182
                                                                  167.

                                                                   82
                                                                  +4%
                                                                  "lOO%
                                                                    0

                                                                   82
                                                                  +3%
                                                                  1002
                                                                   35°

                                                                   83
                                                                  +3%
                                                                  100%
                                                                 >182

                                                                   84
                                                                  + 3%
                                                                  100%
                                                                 >182

                                                                   85
                                                                  3%
                                                                  100%
                                                                 >182
      footnotes:
         a) not consistently uniform thereafter.
         b) infrequently uniform thereafter.
            Draft Report Page 19 of 28
                                                                 ph2.doc
-------
                                                                       440
Table Va. Acute Response (in absolute numbers)  to exposures 5 days per week
distributed among 18 crews of 12 persons each working alternately 2 and 3
days per field:
   1) The number of harvesters experiencing  a 1-day AChE inhibition of >50%
      (believed capable of inducing clinical symptoms);  values in excess of
      216 indicate individuals multiply exposed to high  levels of residue.
   2) The number of days throughout the season  in which  the above
      inhibitions occurred (this will be between 1 and 2 times the number
      of fields, depending upon the frequency and severity  of the
      "poisoning").
   3) The number of sprayed fields  per season in which the  above
      inhibitions were clustered into potentially reportable "incidents"
      (involving at least one-half  of the crew).
    Geometric

    Deviation
1.0
                 1.5
                 2.0
                 3.0
                 4.0
                              Daily   Mean   delAChE
                           1Z        2%        4%
 0
 0
 0

 0
 0
 0

 0
 0
 0

 1
 0
 0

20
 5
 2
 0
 0
 0

 0
 0
 0

 0
 0
 0

12
 5
 1

82
22
 5
  0
  0
  0

  0
  0
  0

  1
  1
  0

 84
 26
  6

288
 36
 18
 8Z

  0
  0
  0

  0
  0
  0

 39
 16
  2

383
 48
 32
                                                        42
16Z

  0
  0
  0

 46
 22
  3

317
 79
  5

 *
 *
"76

 ft
 ft
 ft
                 2.6
           0
           0
           0
           2
           2
           0
          28
          10
           1
                  Draft  Report Page 20 of 28
                                                ph2.doc
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                                                                  JUJ. OO
                                                                  .      441


Table Vb. Acute Responses (in rates per hundred) to exposures 5 days per
week distributed among 18 crews of 12 persons each working alternately 2 and
3 days per field:

   1) The incidence (percent of 216) of harvesters experiencing a 1-day
      AChE inhibition of >50Z (believed capable of inducing clinical
      symptoms); values in excess of 100% indicate individuals multiply
      exposed to high levels of residue.
   2) The percent of 182 days throughout the season in which the
      above inhibitions occurred (this will be between 1 and 2 times the
      number of fields, depending upon the frequency and severity of the
      "poisoning").
   3) The percent of the 916 sprayed fields per season in which the  above
      inhibitions were clustered into potentially reportable "incidents"
      (involving at least one-half of the crew).

                              Daily    Mean   delAChE
                           1%        2%        4Z        8Z       16Z

    Geometric    1.0        0         0         0         0         0
                            00000
    Deviation               00000

                 1.5        0         0         0         0        21%
                            0         0         0         0        12%
                            0         0         0         0        .3%

                 2.0        0         0        .5%       18Z      147Z
                            0         0        .5Z        9Z       43Z
                            0         0         0        .2%       .5%

                 2.6        0        .9%       13%
                            0         1Z        5Z
                            0         0        .17.

                 3.0        .1Z       6%       39Z      177Z       *
                            0         37.       14%       26%       *
                            0        .1%       .7Z      3.5Z     "8.3%

                 4.0        9Z       38Z      133Z       *         *
                            3%       12Z       20Z       *         *
                           .2Z       .5Z      2.0Z     ~4.6%       *
    footnote *) frequencies become unreliably too high to be representative.
                  Draft Report Page 21 of 28                     ph2.doc
-------
                                                                        442
Table VI. Reported use history of  parathion on oranges in California
[Source Pesticide Use Reports, California Dept. Food and Agriculture, for
the years noted}.
     Year
 Number of
Applications
Founds
Acres
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
Tulare County
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
1982
2206
2135
1554
921
1000
744
638
443
476
681

548
Use Report,
0
1
271
128
165
260
182
158
83
67
21
5
160 377
194 061
161 233
124 049
77 956
90 240
57 111
69 722
50 051
55 677
54 171

49 848
Oranges, 1972.
0
1
22 045
6 867
15 640
25 335
11 975
11 174
20 778
6 462
1 520
559
52 855
65 777
63 574
45 189
30 742
29 106
21 765
23 314
14 199
14 446
21 845

17 579

0
1
9 905
3 092
4 662
7 086
4 357
3 682
2 919
1 900
1 520
155
Pounds/Acre
                                                      2.84
                                                      2.23
                                                      2.22
                                                        .35
                                                        .58
                                                        ,75
                                                        .03
                                                        ,12
                                                        .40
                                                      3.55
                                                      3.60
                                     3.
                                     3.
                                     2.
                                     3.
                                     7.
                                     3.
           totals   1444
               122  737   38  199
                       3.21
                  Draft  Report Page 22 of 28
                                               ph2.doc
-------
I
NJ
     o
     
                                                                                                                      f-60  -
                                                                                                 to
                                                                                                 ac.

                                                                                           f-BO  u.
                                                                                                 o
                                                                                                                             o:
                                                                                                                             UJ
                                                                                                                             Q-
                                                                                                                        •90
                                                                                                                182
-------
                   DAYS
WITHIN    SEASON
Figure 2.  Plot of AChE activity on the Y axis versus seasonal time in
           days on the X axis for 2% daily delAChE, with residue geometric
           deviation increasing progressively from the top to bottom line
           from 1.0 to 1.5, 2.0, 3.0, and 4.0, respectively.
-------
100-

 BO-

 60-


 4O-
    rt

    UJ
I    UJ
N)   v>
        10
                 —T
                  14
                   —T
                    28
—T
 42
—T
 56
70
                                               DAYS
—T
 B4
98
—T~
 112
126
140
154
—I—
 168
                                                   WITHIN   SEASON
                            Figure 3.  Plot of AChE  activity on the Y axis versus  seasonal time in
                                       days on the X axis for 4% daily delAChE, with residue geometric
                                       deviation increasing progressively from the top to bottom line
                                       from 1.0 to 1.5, 2.0, 3.0, and 4.0 respectively.
                                                                                                                   •o

                                                                                                                   •20

                                                                                                                  -4O
                                                                                                                  _     OQ
                                                                                                                        I
                                                                                                                  -60  -
                                                                                                                         X
                                                                                                                         o
                                                                                                                        CO
                                                                                                                        Of

                                                                                                                  •BO  u.
                                                                                                                        o
—T
 182
                                                                                                             go
                                                                                                                 CD
-------
                                                                                         30
                                                                                      182
                    DAYS
MlTHIN    SEASON
Figure 4.  Plot of AChE activity on the Y axis versus seasonal time in
           days on the X axis for 8% daily delAChE, with residue geometric
           deviation increasing progressively from the top to bottom line
           from 1.0 to 1.5, 2.0, 3.0, and 4.0, respectively.
-------
1CM
                                        DAYS
WITHIN    SEASON
                      Figure 5.  Plot of AChE activity on the Y axis versus seasonal time in
                                 days on the X axis for 16% daily delAChE, with residue geomtric
                                 deviation increasing progressively from the top to bottom line
                                 from 1.0 to 1.5, 2.0, 3.0, and A.O, respectively.
-------
                   DAYS
WITHIN    SEASON
Figure 6.  Plot of AChE activity on the Y. axis versus seasonal time in days
           on the X axis for 0 residue variability, with daily delAChE
           increasing progressively from the top to bottom line from 1% to 2%,
           4%, 8%, and 16%, respectively.
                                                                                           00
-------
                                                               25 Jul 86

                                                                           449
Appendix A: listing of Fortran simulation program (with comments) to be run
            on an IBM 370 with VS operating system.  Lines following
            //GO.FT01F001 DD *  are input data for batch mode operation.

// JOB (,25),'F1-FREY',TIME=(002),MSGLEVEL-(1,1)
/'PASSWORD PPSU8
/*ROUTE PRINT WYLBUR
// EXEC FORTVCLG,FVREGN«1200K,GOREGN-1024K
//FORT.SYSIN DD *
c
c Reentry Simulation Program , IBM 360 Version 1
c
c input used for this simulation problem:
c
c  i.   means and sd (geometric means and sd for kd,p,pl,res.eq.coeff.)
c       1. rmp, regeneration of rbc and their enzymes [usually 1-2%]
c          rmpl, reversion of rbc  [usually 0-15]:
c          rmp,sdp,rmpl,sdpl                            (4F10.5)

c       2. kd dose coefficient, ke enzyme coefficient:
c          rmkd.sdkd, rmke.sdke                         (4F10.5)

c       3. mass (body weight) of workers:
c          rmwt,sdwt                                    (2F10.5)

c
c  ii.  parameters determing pattern of field exposure
c       1. nf = number of fields worked per crew:       (i3)
c       2. nc = number of crews to be placed in fields:  (i3)
c       3. nm = number of members per crew:             (20i3)
c       4. te « time (days) of initial re-entry into each field
c               after spraying:                         (flO.5)
c       5. tw * time (hours) worked per day :           (flO.5)
c       6. Id50 = LD50 for parent and each oxon:        (4fl0.5)
c       7. nd = number of days to complete each field:  (i3)
c
c  iii. input residues of parent [and oxon]:
c       1. read mean and geometric deviation of parent and ditto for oxons
c                                                       (4F10.5).
c
c  iv.  other input variables
c       1. dseed = an integer value (1-2147483647) typed in double
c                  precision, to be used to generate random number:
c                                                       (flO.O)
c
      CHARACTERS  NMC(20)
      CHARACTER*40 INPUT,OUTPUT,RESDUE
      DOUBLE PRECISION DSEED
      REAL  P(18,12),P1(18,12),KK(18,12,100),LD50(10),
     +     KD(18,12),KE(18.12),WT(18,12),DEL(18,12,100),
     +     RP(301),RKE(301),RKD(301),RWT(301),RAA(301),RP1(301),
     +     R(18,18),H(18,12,100),H1(18,12,101),HE(12),
     +     HM(18,100),HSD(18,100)

c     lun is a vestigal parameter from a F77 version directing output:
      LUN -  4
      READ  (1,10) RMP,SDP,RMP1,SDP1
      READ  (1,10) RMKD.SDKD,RMKE.SDKE


                   Appendix A  Page 1 of 6
-------
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
   READ  (1,10) RMWT.SDWT

   print means and sd

   WRITE (LUN.20)  RMKE,SDKE,RMWT,SDWT,RMP,SDP,RMP1,SDP1,RMKD,SDKD
20 FORMATdX,/,
  +   IX,'MEANS AND DEVIATIONS GIVEN ON INPUT'   /
  +   7X,'FOR NORMALLY DISTRIBUTED VARIABLES'    /
  +  1OX,'ENZYME COEFFICIENT KE1,    T45.2F10.5  /
  +  10X,'WORKERS WEIGHT',           T45.2F10.5  /
  +   7X,'FOR LOGNORMALLY DISTRIBUTED VARIABLES '/
  +  1OX,'REGENERATION, P1,          T45.2F10.5  /
  +  1OX,'REVERSION,PI1,             T45.2F10.5  /
  +  10X,'DOSING COEFFICIENT KD',    T45.2F10.5  /)

   input other parameters describing field
   READ  (1,25) NF
   READ  (1,25) NC
   READ  (1,30) NM
   READ  (1,10) TE
   READ  (1,10) TW
   READ  (1,10) LD50(1)
   READ  (1,30) ND
   READ  (1,10) RESSS,REGED
   READ  (1,40) DSEED
   input formats
10 FORMAT(4F10.5)
15 FORMAT(8F10.5)
25 FORMAT(I3)
30 FORMAT(20I3)
40 FORMAT(FIO.O)

   output parameters describing field
   WRITE (LUN.35) NC.NF.ND.TW.TE,DSEED,LD50(1),RESSS,REGED
35 FORMAT( IX,'OTHER PARAMETERS GIVEN ON INPUT1,
  +       lOX.'NO. OF CREWS',
  +       lOX.'NO. OF FIELDS PER CREW',
  +       lOX.'NO. OF DAYS TO COMPLETE FIELD1,
  +       10X,'NO. OF HOURS WORKED PER DAY',
  +       10X,'TIME OF RE-ENTRY INTO FIELDS',
  +       10X,'INPUT VALUE FOR DSEED1,
  •f       10X,'LD50 FOR PARENT1,
  +       10X,'MEAN RESIDUAL VALUE1,
                                                                        450
                                                             .I3
                                                             .I3
                                                             .I3
                                                             .F10
                                                             .F10
                                                             .E13
                                                             .F10
                                                      T41
                                                      T41
                                                      T41
                                                      T40.
                                                      T40.
                                                      T60.
                                                      T40.
                                                      T60.F10.5 /
                                                                    /
                                                                    /
                                                                    /
                                                                    /
                                                                 .5 /
                                                                  5 /
                                                                  7 /
                                                                  5 /
             1 OX, 'GEOMETRIC DEVIATION FOR RESIDUAL VALUE1 ,T60,F10.5)

      notation and documentation of arrays
     i.  for crew i, member j
           P  (i,j)  per cent regeneration
           pi (i,j)  per cent reversion
           rkd(i.j)
           rke(i.j)
           wt
ii.
         for crew i, member j, day 1 (field k)
         del(i,j,l)  represents the percent of enzyme activity inhibited
                   Appendix A  Page 2 of 6
-------
                                                               25 Jul 86


c                    after one dose
c        kk (i,j,l)  ratio of active enzyme after 1 dose « 1- del(i,j,k)
c        h  (i,j,l)  health (ratio to initial of enzyme remeaining after
c                    the kth dose)
c        hi (i,j,l)  ratio of enzyme after recovery of 1-1 doses
c                    and therefore also the ratio before the 1th dose
c                    and health at beginning of the kth day
c
c   iii. for coefficients of residue equation
c        cf(n,k)  n coefficients for the k fields worked per crew
c        r(i,l)  is residue to parent (i-1) or oxon (i»no. oxon+1)
c                 for day 1
c
c     get characteristics for each individual from using either a
c     lognormal or normal random no generator (imsl routine)
c
c     get random values for wt, and ke using the normal dist.,  imsl ggmnl
c
c
      DO 500 1=1,NC
         CALL LGNM (DSEED.NM.RMP, SDP, RP)
         CALL LGNM (DSEED,NM,RMP1,SDP1,RP1)
         CALL LGNM (DSEED,NM,RMKD,SDKD,RKD)
         CALL GGNML(DSEED.NM.RWT)
         CALL GGNML(DSEED.NM.RKE)
c
c        now assign each member of field a random no.  chosen above
c
         DO 400 J « l.NM
            KD(I,J) - RKD(J)
            KE(I,J) « RKE(J)*SDKE+RMKE
            WT(I,J) - RWT(J)*SDWT+RMWT
            P (I,J) - RP (J)
            P1(I,J) - RP1(J)
  400       CONTINUE
  500    CONTINUE
c
c     for each crew member get the ratio of the percent of active
c     enzyme to the initial amount of active enzyme after nf fields
c     have been harvested.
c
c     parameters used here
c
c     h(i,j,l) fraction of depleted enzyme after 1 days (in kth field)
c        for crew i,member j, field 1 (health after 1 days in kth field)
c     hl(i,j,l) fraction of active enzyme 24 hours after the 1th dose
c        or the fraction of active to start the (l+l)th day (kth field)
c        for crew i, member j, 1 days in field k
c
c     set health for initial to 1  (i.e. hli.j.lM for all i,j)
      DO 700 I • l.NC
         DO 710 J • l.NM
            H1(I,J,1) «= 1
  710       CONTINUE
  700    CONTINUE
                   Appendix A  Page 3 of 6
451
-------
                                                               25 Jul 86


c                                                                        452
c     print table discribing events
c
      DO 1000 I i l.NC
         WRITE (LUN.1001) I
         WRITE (LUN.1010) (WT(I,J),J=1,NM)
         WRITE (LUN.1020) (KE(I,J),J=1,NM)
         WRITE (LUN.1030) (KD(I,J),J=1,NM)
         WRITE (LUN.1040) (P(I,J),J-1,NM)
         WRITE (LUN.1050) (Pl(I.J),J=1,NM)
 1001 FORMATUX ,////,
     +
     +  5X,
     +  T33, 'l',T42,
     +  TlOZ.'S'.TllZ,
 1010 FORMAT(T28,'WT«
 1020 FORMAT(T28,'KE=
 1030 FORMAT(T28,'KD=
 1040 FORMAT(T28,'  P*
 1050 FORMAT(T28,'P1«
 RESULTS OF ANALYSIS FOR CREW ',13,
 WHERE INFRACTION OF ENZYME INHIBITED1,//
 FIELD CONDITIONS',T28,'CREW MEMBERS'/
2',T52, '3',T62 ,'4',T72/ '5',T82, '6',T92,
9',T122,'10I // )
 F6.2.T41.F6.2,  8(4X,F6.2))
 F7.3.T41.F7.3,  8(3X,F7.3))
 F7.3,T41,F7.3,  8(3X,F7.3))
 F9.5.T41.F9.5,  8(1X,F9.5))
 F9.5.T41.F9.5,  8(1X,F9.5))
         DO 850 K = l.NF
            NIII = 50
            CALL LGNM (DSEED,NIII,RESSS,REGED,RAA)
            IF (RAA(l).GE.RESSS) FPER=3
            IF (RAA(l).LT.RESSS) FPER=2

            DO 777 L «= l.ND
c     calculate dose for each residue (from parent and oxon)
c     note r(mm,l) is residue for 1th day for parent(mm=l) or
c                             oxon number mm-1
c
c     determine residue for each of parent and oxons
               DO 803 MM » 1,1
                  IDDD    - L*5+MM
                  R(MM,L) = RAA(IDDD)
                  IF (L.EQ.3) R(MM,L)*R(MM,2)*EXP(-0.074)
                  IF (L.EQ.4.AND.FPER.EQ.3) R(MM,L)-R(MM,2)*EXP(-0.148)
                  IF (L.EQ.5.AND.FPER.EQ.2) R(MM,L)=R(MM,4)*EXP(-0.074)
                  IF (L.EQ.6.AND.FPER.EQ.2) R(MM,L)=R(MM,4)*EXP(-0.148)
                  IF (L.EQ.6.AND.FPER.EQ.3) R(MM,L)=R(MM,5)*EXP(-0.074)
                  IF (L.EQ.l) R(MM.L) - 0.
                  IF (L.EQ.7) R(MM,L) - 0.
  803             CONTINUE

               DO 800 J = l.NM
                  SUM = 0
                  DO 801 MM - 1,1
                     D   = (KD(I,J)*R(MM,L)*TW)/(WT(I,J)*1000.)
                     SUM - (D/LD50(MM))+SUM
  801                CONTINUE
                  DEL(I,J,L) = 1-EXP(-KE(I,J)*SUM)
                  KK(I.J.L)  = l-DEL(I.J.L)
                  H(I.J.L)   = KK(I,J,L)*H1(I,J,L)
                  P2         - l.
                   Appendix A  Page 4 of 6
-------
                                                               25 Jul 86
                  P3
                  Rl
                  R2
                  TOP
   800
                  H(I,J.L)
                  HE(J)
                  CONTINUE
                               H(I,J,L)*P2
                               P1(I,J)*DEL(I,J,L)
                               R1+R2+P(I,J)
                               TOP/P3
                               l.-H(I.J.L)
                               H1(I,J,L-H)
                                                                          453
   802
               SUMH   - 0.
               SUMH2  = 0.
               DO 802 J - l.NM
                  SUMH  - SUMH+H(I,J,L)
                  SUMH2 « SUMH2+H(I,J,L)*H(I,J,L)
                  CONTINUE
               HM(I,L)  - SUMH/NM
               HSD(I.L) = ((SUMH2-HM(I,L)*SUMH)/(NM-1))**0.5
               WRITE (LUN,1060)K,L,R(1,L),(H(I,J,L),J=1,NM).
                               HM(I,L),HSD(I,L)
  1060
  777
               FORMATUX, 'W ,13, 'D1,13,Til, 'RESIDUE-1 ,F8.3,T28, 'H=',
                      F6.4,T37,F6.4,12(1X,F6.4))
               CONTINUE
            DO 888 J « l.NM
               H1(I,J,1) - HE(J)
  888          CONTINUE
  850       CONTINUE
 1000    CONTINUE
      END

      SUBROUTINE LGNM(DSEED,NF,A,B,X)
      DOUBLE PRECISION DSEED
      DIMENSION X(301)
      S  - ALOG(B)
      XM « ALOG(A)
      CALL GGNLG(DSEED,NF,XM,S,X)
      RETURN
      END

//GO.FT04F001 DD DSN=WYL.CMD.SIM.AAA,UNIT=DISK,VOL*SER=WYLB02,
// DCB=(RECFM=FB,LRECL«133,BLKSIZE«6118),
// SPACE=(TRK,(27,2)),DISP=(NEW,CATLG)
//GO.FT01F001 DD *
                       0.15000   1.01000
                       6.00000   1.30000
 0.0089286
   5.10000
  70.00000
026
018
012
   7.00000
   8.00000
  10.00000
007
 119.00000
3857100000
 1.0457
1.41000
7.00000
             2.00000
                   Appendix A  Page 5 of 6
-------
Appendix B: Listing of the simulation program run on the IBM-PC with       454
            Microsoft Fortran compiler.  Lines following the last "end" are
            a separate input file called "simlib" .

      program simS
c     unified field model simulation program , "version 5.2" [23 Jul 86]
c     comprising submodels 2-3 with variability in the H measurement added
c        submodel 1: R   * Ro exp(-Kr T)
c        submodel 2:D   = R Kd t / m
c        submodel 3: del « 1 - exp(Ke sum(D / LD50))
c     therefore      R   « -LD50 ln(l - del) m / Kd Ke t
c     This version groups and prints (with no option) all crews by day to
c        facilitate operation of summary program pp5, and staggers the working
c        pattern experienced by each crew.

c  batch file input for this simulation program in a file to-be-named:
c
c  i. input the field residue conditions: mean daily inhibition,
c     geometric deviation of that residue, and short-term decay rate:
c      1. percent daily inhibition "delbar"                            (flO.2)
c      2. geometric deviation of the residue "gdres"                   (flO.2)
c      3. half-life [days] of residue during harvest "half"            (flO.2)
c      4. AChE measurement (interday intraperson) variability          (flO.2)
c  ii. means and sd of worker parameters:
c      5. gmp, regeneration of rbc and their enzymes, usually 1-2%
c         gmpp, reversion of rbc, usually 0-15%:
c         "gfflpV'gdpV'gmppV'gdpp"                                   (AflO.5)
c      6. kd dose coefficient, ke enzyme coefficient:
c         "gmkd","gdkd","gmke","gdke"                                 (4fl0.5)
c      7. arithmetic mean and standard deviation of mass of worker:
c         "rmwtV'sdwt"                                               (2fl0.5)
c  iii. parameters determing field exposure
c      8. nw    = number of weeks worked per crew:                        (13)
c      9. nc    • number of crews to be placed in fields:                 (i3)
c     10. nm    = number of members per crew:                           (2013)
c     11. dpa   = time (days) of initial re-entry into
c                 each field after (post) spraying:                       (13)
c     12. hwpd  = time (hours) worked per day :                           (13)
c     13. nd    = number of days to complete each field
c                 (a repeatable pattern of from 1-10 values
c                  ending in 0; any negative values are accepted
c                  as specifying days with no additional exposure):     (1013)
c     14. Id50  = LD50 for parent (and each of up to 3 oxons):        (4fl0.5)
c  iv.  other input variables
c     14. iseed = three integer values (1-2147483647)
c                 to be used to generate random numbers:
c  to input and output data to and from this program:
c     1) the program will ask the user the name of the file which has
c        data for input (assigned as file 1);
c     2) the program asks the user if output is to be written on the
c        termianal or to be saved as an output file;
c     3) the file number and name are then given by the user.
c        If user enters 0 then the terminal receives the output;
c        If  "     "    1 and a file name, health only output is saved  f6.4


                   Appendix B  page 1 of 10
-------
                                                              23 Jul 86

                                                                           455
         If  "     '     2 and a file name, more complete output is saved f5.3

      character*14 input, output
      integer      iseed(3),nd(10),dpa,hwpd,filel,file2,
                   ipat(18),ires(18),m(18),noff(18)
      real         res(2000),    r(4),ld50(4),
                    p(18,12),pp(18,12),wt(18,12),kd(18,12),ke(18,12),
                   rp(216), rpp(216), rwt(216), rkd(216),  rke(216),
                   kk(18,12),
      filel  « 1
      file2  - 2
c     indicate the name of the file to find input data
      write  (*,101)
  101 format ( ' Enter name of input file :   '  )
      read   (*,102) input
  102 format (a)
c     indicate the name of the file to receive the worker health output.
*     write  (*,103)
* 103 formatC Enter either 0 for the output to return to the terminal1,
*    +  /,8x,' or 1 if health status  only  is to be saved as a file1,
*    +  /,8x,' or 2 if more complete output is to be saved as a file:1)
*     read   (*,104) lun
      lun    - 1
  104 format (il)
      if     (lun .eq. 0) go to 106
      write  (*,105)
  105 format (' Enter the name of the health status output file :  '  )
      read   (*,102) output
      open   (file2,file»output, status* 'new1 )
      rewind  file2
  106 open   (filel, file=input)
      rewind  filel

c     read average daily inhibition, its variability, and
c     the within field residue decay rate (half life);
c     followed by other means and deviations
c     (geometric for lognormal distributions p, pp, kd, ke, and (arith) wt);
c     and finally other input parameters describing field.
      nr     « 1
      mnp    • 10
      read  (1,10) delbar,gdres,half , gdlab
      read  (1,10) gmp,   gdp,  gmpp, gdpp
      read  (1,10) gmkd, gdkd,  gmke, gdke
      read  (1,10) rmwt, sdwt
      read  (1,25) nw
      read  (1,25) nc
      read  (1,30) nm
      read  (1,25) dpa
      read  (1,25) hwpd
      read  (1,30) nd
      read  (1,10) (Id50(nres),nres=l,nr)
      read  (1.45) iseed
   10 fonnat(4f!0.5)
   25 format(i3)
                   Appendix B  page 2 of 10
-------
   30 fonnat(20i3)
   40 fonnat(flO.O)
   45 format(4ilO)

      npp   = 0  '
      ndinp = 0
      do 50 i « l,mnp
         ndinp  * ndinp + abs(nd(i))
         if     (nd(i) .gt. 0) npp * npp + 1
         if     (nd(i) .eq. 0) go to 51
   50    continue
   51 np    = i-1
      nf    = nc * (npp * (nw * 5) / ndinp)
      npop  = nm * nc
*     nlab  = npop * (nw * 7)
      gmres = -Id50(l)*alog(l.-(delbar/100.))*nnwt / (gmke*gmkd*hwpd)
      if    (gdlab .le. 1.0) gdlab -1.0
      do 53 i - l.nc
         ipat(i) - mod(i.np) + 1
         ires(i) = i
         m(i)    = 1
         noff(i) * 0
   53    continue
c     internal variables defined above:
c     mnp   = maximum number of "within field harvest" patterns.
c     nd    - (array) repeatable pattern of the number of days to complete
c             each field.  Note nd<0 means to work in field with no anti-AChE
c             residues; weekends (iday = 6 and 7) are also no-exposure days.
c     np    = number of patterns specified by user.
c     npp   = number of positive pattterns (fields with residues) per  cycle.
c     ndinp = total number of working days within all patterns.
c     nf    = total number of fields required to be simulated.
c     npop  - total size of population (cohort) required to be simulated.
c     ires  = (array) residue (or field) counter stepping res() up to  nf.
c     nlab  = number of simulated laboratory measurements (assumed to  be each
c             day of season) and associated measurement variations.
c     noff  * (array) number of weekend days (off) during which residue decays
c     gmres = geom. mean residue corresponding to the mean delta AChE  specified

c     get characteristics for each individual in population and
c     field in the entire season by using
c     either a lognormal or normal random number generator (subroutine) :
  500 write (*,*) 'Creating body weights'
      call   nml  (iseed,npop,rwt,rmwt,sdwt)
      write (*,*) 'Creating dosing coefficients'
      call  Ignml (iseed,npop,rkd,gmkd,gdkd)
      write (*,*) 'Creating enzyme coefficients'
      call  Ignml (iseed,npop,rke,gmke,gdke)
      write (*,*) 'Creating RBC regeneration rates'
      call  Ignml (iseed,npop,rp ,gmp ,gdp )
      write (*,*) 'Creating RBC reversion rates'
      call  Ignml (iseed,npop,rpp,gmpp,gdpp)
      write (*,*) 'Creating residues'
      call  Ignml (iseed.nf,res, gmres,gdres)
                   Appendix B  page 3 of 10
-------
                                                              23 Jul 86


      if    (lun .eq. 0) go to 600                                     457
      write (*,*) 'Beginning simulation:'                               < ------
      write (*,*) 'Day     of     Crew     Residue      of
c
c  notation and documentation of subsequent arrays
c    for crew i, member j (day k in season, day m(i) in field)
c     P  (i»j) " per cent regeneration / 100.
c     pp (i,j) « per cent reversion  / 100.
c     rkd(i,j) » dosing coefficient
c     rke(i,j) = enzyme response coefficient
c     wt (i,j) = body weight (mass)
c
c     kk (i,j) « enzyme activity after any one dose • 1- del(j),
c                relative to pre-dose activity
c     h  (i,j) * health (enzyme activity remaining after the kth dose
c                relative to initial activity)
c     hi (i,j) « relative enzyme activity after 24 -hr recovery of kth dose
c                and therefore also the pre-dose activity before the k+lth
c                dose
  600 CONTINUE
      k    - 0
      do 1000 iwk - l.nw                                                WEEKS

c        A "pattern" do loop could not be constrained either internal to
c        or external from the week loop (used to define weekends off).
c        Thus, each new ipat is set prior to line 870 to another field
c        (ires) whose initial reentry residue (day m-1 in the field) is
c        selected from the random array of nf residues created earlier
c        but which also undergoes decay after each (m) harvest-working
c        day in that field plus any intervening (noff ) days off at the
c        half-life specified until the harvest has been completed
c        (m » number of days in nd(ipat(i))).

         do 880 iday « 1,7                                              DAYS
            k  • k + 1
            do 870 i - l,nc                                             CREWS
               if ((iday .eq. 6). or. (iday .eq. 7)) noff(i) » noff(i) + 1
*              if (lun .eq. 0) go to 630
               write (*,1065) k,nw*7,i.ires(i),nf
  630          do 800 j - l,nm                                          MEMBERS
                  if ((iwk  .ne. 1) .or. (iday .ne. 1)) go to 700
                        ) = rwt(((i-l)*nm)+j)
                        ) « rkd(((i-l)*nm)+j)
                        ) = rke(((i-l)*nm)+j)
                  P (i.j) »  rp(((i-l)*nm)+j)
                  pp(i,j) • rpp(((i-l)*nm)+j)
                  set initial health to 1  (i.e. hl(i,j) « 1 for each j)
  700             sum     * 0.0
                  if      ((iday .eq. 6) .or. (iday .eq. 7)) go to 702
                  if      (nd(ipat(i)) .It. 0) go to 702
                  r(l)    = res(ires(i)) / (2.**((m(i)+noff (i)-
                  do 701 mm * l,nr                                      CHEMRES
                     d       - (kd(i,j)*r(mm)*hwpd) /
                     sum     * (d/ld50(mm)) + sum
                   Appendix B  page 4 of 10
-------
  701                continue
  702             kk(i,j) « exp(-ke(i,j)*sum)
                  p2
                  p3
                                     I p3
c                 process validation print test
*                 write (*,739) k,i,j,m(i),nd(ipat(i))
*    6            ,ipat(i),noff(i),ires(i),res(ires(i))
*    6            ,r(l),d,sum,kk(i,j),h(i,j),hl(i,j)
*    6            ,p2,p3,p(i,j),pp(i,j),wt(i,j)
*    6            ,kd(i,j),ke(i,j)
*739              format(/lx
*    6            , 'day, cr//, mem//, m,nd(i),i,,noff, ires -' ,/lx,8i3,/lx
*    6            ,'res,r(l),d,sum,kk,h,hl «'       ,/lx,7f 11.7,/lx
*    6            ,'p2,p3,p,pp,wt,kd,ke «'          ,/lx,7fll.7)
c                 end print test

c                 an expected level of laboratory AChE measurement variability
c                 has been integrated into version 4 and later updates, which
c                 affects output via "h" but not the actual health via "hi".
                  vlab    * gauinv(random(iseed),ifault)
                  if     (ifault .eq. 1) stop 'ifault error in lab var. '
                  h(i,j)  - 1. - (h(i,j)*(gdlab**vlab))
  800             continue
* 820          if    (lun .eq. 1) go to 821
*              write (lun,  1060) i,iwk,iday,r(l),(h(j), j-l,nm)
*              go to 830
  821          write (file2,1061) i,iwk,iday,r(l),(h(i, j),j-l,nm)
  830          if    ((iday .eq. 6) .or. (iday .eq. 7)) go to 870
               m(i)    • m(i) + 1
               if    (m(i) .le. abs(nd(ipat(i))))       go to 870
               ipat(i) = ipat(i) + 1
               if    (nd(ipat(i)) .It. 0)               go to 870
               if    ((ires(i)+nc) .le. nf) ires(i) = ires(i) + nc
               m(i)    « 1
               noff(i) - 0
               if    (ipat(i) .gt. np) ipat(i) - 1
  870          continue
  880       continue
 1000    continue
c     print residue and toxicologic means and deviations
c     followed by other parameters describing field
      write (file2,1054) rmwt,sdwt,gmkd,gdkd,gmke,gdke,
     +                   gmp , gdp , gmpp , gdpp , delbar , gdlab , gmres , gdres
      write (file2,1055) nm,nc,npop,nw,nf .nd.hwpd.half ,(ld50(i),i=l,3),
     +                   iseed
c     print individual crew descriptors unless the condensed
c     output file (lun=l) was requested.
      if (lun .eq. 1)  go to 2000
      do 1100 i • l,nc
         write (file2,1001) i, ( j , j=l,nm)
         write (file2,1010) (wt(i, j) ,j=l,nm)
         write (file2,1020) (ke(i,j), j=l,nm)


                   Appendix B  page 5 of 10
-------
                                                              23 Jul 86


         write (file2,1030) (kd(i,j),j-l,nm)
         write (file2,1040) ( p(i,j),j=l,nm)
         write (file2,1050) (pp(i,j),j=l,nm)
 1100 continue
 2000 stop ' Normal termination of Sim5'

c --- THE LAST PORTION OF THIS PROGRAM SPACE IS RESERVED FOR FORMAT STATEMENTS
 1054 format(lx,/,lx,' Means and deviations given on input1/
     +   7x,'for normally distributed variables:1/
     +  lOx,'workers weight1,                 t45,2f!0.5/
     +   7x,'for lognormally distributed variables:  '    /
     +  lOx,'dosing coefficient kd1,          t45,2f!0.5/
     +  lOx,1enzyme coefficient ke1,          t45,2f!0.5/
     +  1Ox,'regeneration, p1,                t45,2f!0.5/
     +  lOx,1reversion, pp1,                  t45,2f!0.5/
     +  lOx,'mean daily inhibition, X1,       t45,lfl0.5/
     +  lOx,'variability in AChE measurement1,t55,If10.5/
     +  lOx,'reentry residue, ug/cm2',        t45,2f!0.5)
 1055 formatdx,1 Other parameters given on input:',    /
     +  lOx,'number of members per crew ',    t46,i3    /
     +  lOx,'number of crews',                t46,i3    /
     +  lOx,'total size of population    ',   t46,i3    /
     +  10x,'no. of weeks worked per crew',   t46,i3    /
     +  lOx,'total no. of fields sprayed1,    t39,ilO    /
     4-  lOx.'no. of days to complete field',  t46,10i3  /
     +  lOx.'no. of hours worked per day1,    t46,i3    /
     +  lOx,'subsequent half-life, days',     t45, flO.5/
     +  10x,'LD50 for OP pesticide(s)',       t45,3f!0.5/
     +  lOx,'input values for iseed',         t39,3ilO  )
 1001 formatdx ,//lx,
     +'Fraction Acetyl Cholinesterase inhibition for crew *,i3,
     +/lx,'Field conditions:',t22,'Crew members:',
     +/,t22,36(i2,3x)
1010 formate tlS.'wt*
1020 formate t!8,'ke-
1030 formate t!8,'kd=
1040 formate t!8,'p «
1050 formate t!8,'pp«
1060 formate'C',i2,'W
1061 formate'C',i2,'W
                           36ef5.1,0x))
                           36ef5.2,0x))
                           36(f5.2,0x))
                           36ef5.4,0x))
                           36ef5.4,0x))
                                            f6.4,tl9,'H«',14ef5.3,Ox))
                                            f6.4,tl9,'H-',14ef6.4,lx))
 1065 formatei+Day'ti4,' of',i4,' Crew'.iS,1  Residue',i5,'  of',i5)
      end
^^^ — ^ — — — — — — — — — — — «•• • • • • V • V • V •• V * V • V • V • V • •*• •
      subroutine nml (iseed,nx,x,a,b)
      dimension  iseed(3),x(2000)
      s    - b
      xm   -a
      call mcarloeiseed,nx,x,xm,s)
      return
      end
*                         ••••••
      subroutine Ignml (iseed,nx,x,a,b)
      dimension  iseed(3),x(2000)
      s    * alog(b)
      xm   = alog(a)
                   Appendix B  page 6 of 10
-------
      call mcarlo(iseed,nx,x,xm,s)
      do 1 i = l.nx
         x(i) = exp(x(i))
    1    continue.
      return
      end
C [[[
      subroutine mcarlo (iseed,nx,x,a,b)
c     creates a random sequence of 'nx1 values of 'x* which taken as a whole
c     are EXACTLY normally distributed between 0 and 1 in steps of 1/nx
c     (see line 001 taken from U.S. HEW (NIOSH) Publ. //77-173)
      real      x(2000),  y(2000)
      integer   iseed(3),iy(2000)

      do 10 i - l,nx
         y(i) - random(iseed)
   10    continue
      call    rankc (nx,y,iy)
      do 20 i = l,nx
  001    p    = (float(i) - 0.5) / nx
         y(i) = gauinv(p.ifault)
         if    (ifault .eq. 0) go to 20
         write (*,1001)  i.a.b
         stop 'Due to fault error in INVGAU from MCARLO1
   20    continue
      do 30 i = l.nx
         x(i) - a + (b*y(iy(i)))
   30    continue
      return
 1001 format  (' A fault error resulted when processing the ',15,
     +     'th value with mean of ',gl2.4,' and deviation of ',g!2.4)
 1002 format  (' A no-match error resulted when searching for "min"1
     +         ,/,' of ',15,' values with mean of ',g!2.4,
     +            ' and deviation of ',gl2.4)
      end
C [[[
      FUNCTION RANDOM(iseed)
*      FUNCTION RANDOM(IX,IY,IZ)

C     ALGORITHM AS 183 modified FROM B.A. WICHMANN and I.D. HILL
C     An Efficient and Portable Pseudo-random Number Generator.
C     APPL. STATIST. 31:188-190, 1982.
C     incorporating the amendment proposed by A.I. McLeod
C     APPL. STATIST. 34:198-200, 1985.

C     On input IX.IY.IZ are seed integers between 1 and 30,000
C     RETURNS A PSEUDO -RANDOM NUMBER RECTANGULARLY DISTRIBUTED
C     BETWEEN 0 AND 1.

-------
  -                                                           ^J JUl 86


       iz *  iseed(3)

       IX =  171 * MOD(IX,177)  -  2*(IX/177)
       IY -  172 * MOD(IY,176)  - 35*(IY/176)
       IZ -  170 * MOD(IZ,178)  - 63*(IZ/178)

       IF (IX  .LT. 0) IX - IX  + 30269
       IF (IY  .LT. 0) IY - IY  + 30307
       IF (IZ  .LT. 0) IZ - IZ  + 30323

C      IF INTEGER ARITHMATIC UP OT 5212632 IS AVAILABLE,
C      THE PRECEDING 6 STATEMENTS MAY BE REPLACED BY

*      IX -  MODU71 * IX, 30269)
*      IY -  MOD(172 * IY, 30307)
*      IZ -  MOD(170 * IZ, 30323)

C      ON SOME MACHINES THIS MAY SLIGHTLY INCREASE THE SPEED,
C      THE RESULTS WILL BE IDENTICAL.

       iseed(l)=ix
       iseed(2)=iy
       iseed(3)=iz
       RANDOM  = AMOD(FLOAT(IX)/30269.+FLOAT(IY)/30307.+FLOAT(IZ)/30323.,
     +             1.0)
C      McLeod  amendment follows:
       IF (RANDOM.GT.0.0) RETURN
       RANDOM  * DMOD(DBLE(FLOAT(IX))/30269.DO + DBLE(FLOAT(IY))/30307.DO
     +             + DBLE(FLOAT(IZ))/30323.0DO,1.0DO)
       IF (RANDOM.GE.1.0) RANDOM - 0.999999
       RETURN
       END
C	
       FUNCTION GAUINV (P, IFAULT)

C      ALGORITHM modified FROM R.E. ODEH and J.O. EVANS
C      The Percentage Points of the Normal Distribution. AS 70
C      APPL. STATIST. 23:96-97. 1974.

C      Note  the additional following reference provides a polynomial
C           for (0.8 .le. p .It. infinity) if needed:
C      M.E.  Tarter:
C      Inverse Cumulative Approximation and Applications.
C      Biometrika 55:29-41, 1968.
C      See also AS 111, APPL.  STATIST. 26:118-121, 1977 for an alternative form.

C     AS 70 was originally called GAUINV:
C      GAUINV  FINDS PERCENTAGE POINTS OF THE NORMAL DISTRIBUTION
C       P on  input is the lower tail area p
C       IFAULT is a fault indicator :
C         ?' - 1 and gauinv «  0 if (E-20 .le. p .le. 1.- E-20)
C             (ERROR: the requrested x exceeds the outer limits of p
C                     for which the inverse is accurate to within E-7)
C         " « 0 and gauinv *  0 if (p .eq. 0.5)
C             (the true value but not calculable from the polynomial)


                   Appendix B page 8 of 10
-------
                                                                        462
          " = 0 in all other cases.

      DATA            PO,   PI,             P2,                 P3
     +   /-.322232431088, -1.0, -.342242088547,  -.204231210245E-1/
      DATA       "        P*,               QO,             Ql
     +   /-.453642210148E-4, .993484626060E-1,  .588581570495/
      DATA            Q2,            Q3,               Q4
     +   I .531103462366, .103537752850,  .38560700634E-2/
      IFAULT - 1
      GAUINV =0.0
      PS     = P
      IF     (P .GT. 0.5)      PS - 1.  - PS
      IF     (PS .LT. l.OE-20) RETURN
      IFAULT - 0
      IF     (PS .EQ. 0.5)     RETURN
      YI     • SQRT(ALOG(1./(PS*PS)))
      GAUINV • YI + ((((YI*P4+P3) *YI+P2) *YI+P1)  *YI+PO)
     f            / ((((YI*Q4+Q3) *YI+Q2) *YI+Q1)  *YI+QO)
      IF     (P .LT. 0.5)      GAUINV - -GAUINV
      RETURN
      END

      subroutine rankc (nx,x,ix)
      dimension x(2000),ix(2000)

      do 1 i = l,nx
         ix(i) - 0
         continue
      do 3 j = l,nx
         ilast - 2000
         xmin  - 10.**30
         do 2 i * l,nx
            if ((x(i) .It. xmin) .and.  (ix(i)  .eq.  0))  then
            ix(ilast) « 0
            xmin      * x(i)
            ilast
            end if
    2       continue
    3    continue
      return
      end
Input file, typically called simlib:
      4.00      3.00      7.00      1.0 >delbar,gdres,half,gdlab
  .0089286    1.0457       .15      1.01>gmp (regen.),gdp,gmpp (revers.),gdpp
      5.10      1.41      6.00      1.30>kd,gdkd,ke,gdke
     70.        7.                      >wt,sdwt
 26>nw eeks
 18>nc rews
 12                           >nm embers per crew
 14>dpa (days post-application)
                   Appendix B  page 9 of 10
-------
                                                          23 Jul 86

                                                                      463
8>hwpd (hours worked per day)
2-3  3-2                 >nd (pattern of number of days in each field)
   10.00                             >LD50
   25784       985     12919          Mseed
                 Appendix B  page 10 of 10
-------
                                                                           464
Appendix C: Listing of the daily health status analysis and summary program
            written to be run on an IBM-PC with Microsoft Fortran compiler.
            Lines following last "end"  are an external input file typically
            called "pplib" .
C
C
C
C
C
C
C
C

C
*
*
*
ft
*
*
ft
ft
ft
ft
ft
ft
*
ft
ft
*
ft
ft
ft
A
ft
ft
ft
ft
*
ft
ft
ft
ft
ft
ft
ft
ft
ft
ft
*
*
Program PP2
Phasell Program 2, Version 5
to read simulation (SIMS) output option //I files;
  (1) scan daily through all crews for "illness" using four
      threshold criteria as specified in a separate "pplib" file,
  (2) tabulate and calculate daily summary health statististics, and
  (3) conduct analysis of variance among crews for health status
      in both arithmatic and geometric modes, optional to do
      every day or only on each clinic day of each week (see inclin)

Defined variable list follows:
CPOI   counter for poisoning cases within day (see also fpoi and inpoi)
DEL    delta AChE
F      F test statistic for arithmatic distribution
FILEO  assigned file: keyboard and screen
FILE1     "      "  : input data
FILE2     "      "  : output of analysis of variance
FILE3     "      "  : input library of run parameters (pplib)
FILE4  unused
FPOI   counter for fields in which poisoning cases occurred
G      F test statistic for geometric distribution
GD     geometric deviation for group
GM     geometric mean for group
GX     log-transformed values of x
H      health (enzyme activity) = 1-x
I      index for days
IDAY   day of week within input sequence
II     "del" counter
IWK    week within input sequence
INCLIN (from pplib) day of the week crews are in clinic for "h" samples
INPOI  counter for incidents of poisoning (defined as .gt. 1/2 of crew)
INPUT  character name of input file
J      index for crew
K      index for person within crew
LINE   line of narrative text; a maximum of 79 characters
M      index for running cumulative days, equivalent to nthres
Nl     degrees of freedom for numerator   of arithmatic F
N2     degrees of freedom for denominator of arithmatic F
N3     degrees of freedom for numerator   of geometric  F
N4     degrees of freedom for denominator of geometric  F
NCREW  crew number as listed within data
NCREWS (from pplib) number of crews included within the study design
       (from pplib) day of the programmed "week" exposure starts
       total number of days in study = nwks*7
       overall number of geometric  data points
NDAYO
NDAYS
NG
NLINE1 (from pplib) number of narrative lines to be copied at end
        of input file
NLINE2 (from pplib) number of narrative lines to be skipped at end
        of input file
NN     overall number of arithmatic data points
                Appendix C  page 1 of 7
-------
                                                              23 Jul 86
*
ft
ft
ft
ft
*
*
*
*
ft
*
*
*
ft
ft
*
*
ft
*
*
ft
ft
ft
NPERC
NTHRES
NWKS
NX
0AM
OGM
OUTP2
PDAY
PGD
PINC
PSD
RES
S2SG
S2SX
SD
SIMAN
SSG
SSG2
SSX
SSX2
TCPOI
THRES

X
XM
(from pplib) number of people per crew
(from pplib)
(from pplib) number of weeks in study
                                                                          465
overall arithmatic mean
overall geometric  mean
character name of anova output file » file2
integer number of previous days within study (max=nthres)
pooled geometric deviation
counter for poisoning cases within a crew-day (see also cpoi)
pooled arithmatic deviation
residue for each exposure day (not manipulated)
(see anov)
(see anov)
standard deviation for group (array)    >
external library of program run parameters
(see anov)
(see anov)
(see anov)
(see anov)
counter for seasonal total cases of poisoning within each  category
(from pplib) quantitative poisoning criteria for 1-AChE (see
 "Parameters from pplib" description below)
level of inhibition (read from input)
arithmatic mean for group (array)
      character*14 input,outp2
      character*79 line
      dimension
      dimension
      integer
      integer
      logical
             h(4,18,12),x(12).gx(12),thres(4)
             xm(18), sd(18),gm(18), gd(18)
             fileO,filel,file2,file3,day,pday
             cpoi(4),fpoi(4),inpoi(4),tcpoi(4),pinc(4)
             negx
C»>»   INPUT FORMAT FROM SIMS option 1
 1000 format (a79)
 1001 format (4x,i2,lx,il, 3x,f6.4,3x,14(f6.4,lx))
*     +      ,(/,20x,14(f6.4,lx)),(/.20x,14(f6.4,lx)))
C 1W.1D1 R« .1986 H- .0817  .0781 -.0195  .0429  .2360
                                                  .1964  .1505  .0969  .304
      fileO
      filel
      file2
      file3
      file4
        0
        1
        2
        3
        4
                                                           user
                                                           input
                                                           output
                                                           pplib
                                                           unused
C.... ask for and read the name of input and output files.
  100 continue
      write  (fileO.1005)
      read   (filed,1004) input
      if     ((input .eq. 'quit').or.(input .eq. 'exit').or.
     +       (input .eq. 'stop').or.(input .eq. 'end')) go to 999
      write  (fileO,1007)
      read   (fileO,1004) outp2
                Appendix C  page 2 of 7
-------
      open   (filel, file=input)
      rewind  filel
      open   (file2, file=outp2, status='new')
      rewind  file2
      open   (file3, file-'pplib')
      rewind  file3
      write  (fileO,1009) input,outp2

C	 READ the operating PARAMETERS FROM PPLIB (file3)
C     ncrews • number of crews included within the study design;
C     nperc  = number of people per crew;
C     nwks   « total number of weeks expected to be read from "input";
C     ndayO  « day of the week exposure starts, assuming 1 equals Monday;
C     inclin » day of the week blood samples are taken in the clinic (0=all);
C     thres  - criteria for 1-AChE ( or x(k) within this program) at
C              which person i considered "overexposed".  Criteria are
C              initially set based on    Daily Inhibition
C                    Simple      day 1  .5     .4     .35
C                    Cumulative  day 2  .75    .64    .58
C                    Effect      day 3  .875   .78    .725
C              therefore, respective values of thres in array
C              (1) a single daily inhibition, x .ge. 0.5
C              (2) a 2-day cumulative  "    , x .ge. 0.65
C              (3) a 3-day     "       "    , x .ge. 0.75
C              (A) a cumulative reduction in h below 0.5
C               m subscript used
C               to store h      and    to calculate del h
C               1: today's h              single daily inhibition (h2-hl/h2),
C               2: yesterday's h          2-day cumulative  "     (h3-hl/h3),
C               3: two day's ago h        3-day     "       "     (h4-hl/h4),
C               4: three day's ago h      cumulative reduction in h
C     nlinel = number of narrative lines to be copied at end of file (input)
C     nlineZ = number of crew narrative lines to be skipped

      read   (file3,3001) ncrews,nperc,nwks,ndayO,inclin,nthres,thres
     +                   ,nlinel,nline2,nline3

C     type input parameters, output table, and screen headers
      write  (file2,3001) ncrews,nperc,nwks,ndayO,inclin,nthres,thres
     +                   ,nlinel,nline2,nline3
      write (file2,2002) 'Wk','Day1,'0AM1,'PSD','F','nl1,'n2','OGM',
     +                   'PGD','G','n3','n4','pol','po2','po3','po4'
      write (file2,2002) •--•,• —•.• — •, • —', •-•, •„•, t__. f ,___i §
     J.                   t___l l_l l__l l__l •___! I	I I   II   I
     T                        »•»»»»   ~ ,
      write (*,*) 'now on crew//    and day     of

C	 set health array (m,j,k) equal to 1.0 (each individual's "normal")
C     subscript i = day within study (season)            limit : ndays = nwks*7
C               j - crew                                         ncrews
C               k = person within crew                           nperc
C               m = running day (1 = today, 2 = yesterday, etc)  nthres
      do 152 j = 1,ncrews
         do 151 k = 1,nperc
            do 150 i « 1,nthres
               h(i,j,k) = 1.0


                Appendix C  page 3 of 7
-------
                                                              23  Jul  86

                                                                        467
  150          continue
  151       continue
  152    continue
      do 153 m « .1 .nthres
         fpoi(m)  - 0
         tcpoi(m) • 0
         inpoi(m) - 0
  153    continue

C - - Begin daily analysis of all crews: ----------------
      iday     - 7
      ndays    • nwks * iday
      do 450 i - 1,ndays                                               DAY >
         negx  » .false.
         iday  • iday + 1
         if    (iday .gt. 7) iday - 1
C        zero the poisoning cases for that day counter
  210    do 215 m » 1,nthres
            cpoi(m)  « 0
  215       continue
C        initialize anova arrays if anova is to be run for the day
         if    ((iday .ne. inclin)  .and. (inclin .ne. 0)) goto 220
         call  anovO (ssx,ssx2,s2sx,nn,ngpn)
         call  anovO (ssg,ssg2,s2sg,ng,ngpg)
C        day i for crew "j" read "k»l,nperc" daily health values
  220    do 300 j * l.ncrews                                           CREW >
            write (*,1111) j,i,ndays
  222       read  (filel,1001,end=501) iwk,iday,res,(x(k),k«l,nperc)
*           write (*,    1001        ) iwk,iday,res,(x(k),k=l,nperc)
            do 223 m « l.nthres
               pinc(m) * 0
  223          continue
C           talley cases in 'Poisonings IN Crew* counter.
            do 6 k = l.nperc                                           MEMB.>
               if  (negx)     goto 1
               if  (x(k) .le. 0.0) then
                   negx = .true.
                   goto 1
                   endif
               gx(k)  = alog(x(k))
    1          do 2 m * l,nthres-l
                  h(nthres-m+l,j,k) « h(nthres-m,j,k)
    2             continue
    3          h(l,j,k) - 1. - x(k)
               do 4 m • l,nthres-l
                  del « (h(mfl,j,k)-h(l,j,k))/h(m+l,j,k)
                  if (del .gt. thres(m)) pinc(m) « pinc(m)+l
    4             continue
    5          del -    (1. -     h(l,j,k))/l.
               if (del  .ge. thres(nthres)) pinc(nthres) » pinc(nthres)+l
    6          continue                                                 
-------
                                                                 Jui oo
            do 7 m = l.nthres
               cpoi(m) * cpoi(m) + pinc(m)
               if (pinc(m) .gt. 0) fpoi(m) • fpoi(m) + 1
               if (float(pinc(m))/nperc .ge. .5) inpoi(m) - inpoi(m) + 1
    7          continue
C           if desired (inclin .ne. 0) anova may be run only on clinic days
            if ((iday .ne. inclin) .and. (inclin .ne. 0)) goto 300
            call  anovl (x, nperc,xm,sd,ssx,ssx2,s2sx,nn,ngpn)
            if    (negx) goto 300
            call  anovl (gx,nperc,gm,gd,ssg,ssg2,s2sg,ng,ngpg)
  300       continue                                                    
-------
                                                              23 Jul 86


 2003 format (13,i2,lx, 2(2x,2f8.5,2x,f5.2,i3,i4), 2x,4i4)
 2004 format (i3,12,lx, I(2x,2f8.5,2x,f5.2,i3.i4),34x,4i4)
 2005 format (13,i2,lx, 2(32x                   ), 2x,4i4)
 2006 format (lx///,39x,'Total number of poisoning cases: '. 3i4,/,
     +              36x,'Days on which a poisoning occurred: ',3i4,/,
     +              38x,'Potentially reportable incidents: *,3i4)
 3001 format (6i4,4f4.2,3i4)
      end
c	
      subroutine anovO ( ssx,ssx2,s2sx,nn,ngp)
c     sx   » sum of x within group
c     sx2  « sum of x**2 within group
c     ssx  * sum of sums of x within group
c     ssx2 » sum of sums of x**2 within group
c     s2sx *
c     nn   • cumulative number of observations in groups l,ngp
c     ngp  * cumulative number of groups
      ssx  - 0.
      ssx2 » 0.
      s2sx - 0.
      nn   - 0
      ngp  « 0
      return
      end
C	
      subroutine anovl (x,nx,xm,sd,ssx,ssx2,s2sx,nn,ngp)
      dimension  x(nx),xm(ngp),sd(ngp)
c     x (i)= array of x values within group ngp
c     nx   = number of observations within group j
c     xm(j)= mean within group j
c     sd(j)« std. dev. within group j
c     sx   * sum of x within group
c     sx2  = sum of x**2 within group
c     ssx  * sum of sums of x within group
c     ssx2 = sum of sums of x**2 within group
c     s2sx =
c     nn   * cumulative number of observations in groups l.ngp
c     ngp  = cumulative number of groups
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
c                                                          c
c  Note :  it is possible for nx (no. of prsons) to equal  c
c          zero, which in turn would cause division by     c
c          zero in mean and s2sx variables.  If there is   c
c          such a possibility, if could be fixed with an   c
c          "IF...THEN"  statement.                         c
c                                                          c
cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
c
      sx   - 0.
      sx2  * 0.
      do 1   i • 1, nx
         sx    = sx+x(i)
         sx2   - sx2+(x(i)**2)
    1    continue
      nn   • nn+nx
                Appendix C  page 6 of 7
-------
      ngp   = ngp + 1
      fn   - float(nx)                                                 47Q
      ssx   « ssx+sx
      ssx2  * ssx2+sx2
      s2sx  - s2sx+((sx**2)/fn)
      xm(ngp)* sx/fn
      sd(ngp)» sqrt((sx2-((sx**2)/fn))/(fn-l.))
     2 return
      end
C	
      subroutine anov2  (ssx,ssx2,s2sx,nn,k,oam,psd,f,nl,n2)
c     k     « total number of groups  [ngp in anovl]
c     ssx   * sum of sums of x within group
c     ssx2  = sum of sums of x**2 within group
c     s2sx  *
c     oam   = over-all-mean
c     psd   «= pooled standard deviation
c     f     » F statistic
c     nl    = numerator  degrees of freedom, k - 1 * ngp - 1
c     n2    = denominator degrees of freedom, nn - k
      oam    « ssx/float(nn)
      totss - ssx2-((ssx**2)/float(nn))
      betss » s2sx-((ssx**2)/float(nn))
      witss - totss-betss
      betms = betss/float(k-l)
      witms » witss/float(nn-k)
      psd    • sqrt(witms)
      f      = 9999.99
      if (witms  .ne. 0)  f = betms/witms
      nl     • k-1
      n2     « nn-k
      return
      end
Listing of input file pplib:
  18  12  26   1   0   4 .50 .65 .75 .50  23 114
ncrwnpernwksdayOinclnthrthrs   2   3   41inllin2
                Appendix C  page 7 of 7
-------
                                                             27 Jul 86
Appendix D:  listing of a typical output  from  the health analysis summary
            program (Appendix C); this particular run was for a daily mean
            response of 4% with a residue variation of 3.0 (plotted as the
            second line from the bottom  in Figure 3).
                                                                                 471
 Wk Day    0AM
PSD
nl  n2
OGM
PGD
G   n3  n4   pol po2  po3  po4
1 1
1 2
1 3
1 4
1 5
1 6
1 7
2 1
2 2
2 3
2 4
2 5
2 6
2 7
3 1
3 2
3 3
3 4
3 5
3 6
3 7
4 1
4 2
4 3
4 4
4 5
4 6
4 7
5 1
5 2
5 3
5 4
5 5
5 6
5 7
6 1
6 2
6 3
6 4
6 5
6 6
6 7
7 1
7 2
7 3
7 4
7 5
7 6
.03603
.06132
.11174
.17631
.24283
.22551
.22351
.26962
.29544
.32077
.34635
.36641
.35558
.35241
.36939
.37835
.39645
.45244
.47523
.45783
.45376
.48126
.49771
.52123
.54419
.55989
.54372
.53889
.56026
.56846
.57354
.58424
.59814
.58172
.57654
.59733
.60104
.61392
.62627
.63371
.61678
.61130
.63185
.63794
.64973
.65380
.65166
.63887
.01988
.03254
.05850
.08352
.09752
.08994
.08917
.10039
.10221
.10551
.11053
.11393
.10940
.10843
.11314
.11392
.11553
.12241
.12176
.11608
.11506
.11940
.11983
.12135
.12285
.12216
.11613
.11511
.11840
.11741
.11612
.11670
.11592
.11036
.10938
.11272
.11036
.11063
.10989
.10823
.10310
.10220
.10590
.10426
.10203
.10062
.09948
.09625
19.65
20.37
15.86
16.32
19.88
18.86
18.85
24.60
28.26
23.56
18.18
16.26
17.06
17.06
15.42
15.14
16.38
13.06
15.79
14.34
14.34
15.06
14.55
14.76
9.83
9.14
9.61
9.61
9.11
8.94
8.80
8.20
8.29
8.23
8.23
9.78
9.98
8.90
7.70
7.14
6.97
6.97
5.26
5.11
7.78
8.59
6.67
6.31
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
17 198
.02608
.04489
.08421
.13742
.19112
.17892
.17733
.21348
.24231
.27309
.30271
.32424
.31452
.31172
.32915
.33864
.35519
.41731
.43807
.42399
.42022
.44724
.46482
.48866
.51783
.53540
.52029
.51567
.53713
.54613
.55204
.56371
.57812
.56301
.55800
.57701
.58135
.59574
.60978
.61842
.60248
.59712
.61861
.62536
.63620
.64034
.63942
.62734
1.57011
1.55964
1.53532
1.50343
1.47487
1.47140
1.47139
1.45621
1.44281
1.42929
1.41401
1.40100
1.39808
1.39808
1.39214
1.38479
1.37696
1.35599
1.34167
1.33822
1.33822
1.33211
1.32171
1.30919
1.29359
1.28051
1.27598
1.27597
1.27244
1.26592
1.26034
1.25225
1.24382
1.23949
1.23946
1.23727
1.23152
1.22561
1.21847
1.21168
1.20741
1.20741
1.20606
1.20067
1.19554
1.19174
1.18870
1.18619
28.68
28.68
31.22
31.56
38.00
36.97
36.97
40.27
29.99
23.58
20.31
19.20
19.64
19.64
18.57
18.37
19.31
12.68
14.83
13.91
13.91
13.07
12.72
12.96
9.11
8.55
8.87
8.87
8.48
8.36
8.16
7.82
8.10
7.96
7.96
9.41
9.60
8.31
7.06
6.44
6.46
6.46
4.81
4.57
6.24
6.60
5.63
5.39
17 198
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11
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0 0
0 1
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0 17
0 10
0 10
0 22
0 25
1 33
0 38
0 44
0 42
0 40
0 44
0 48
0 54
1 80
5 92
0 85
0 84
0 92
0 102
0 114
0 126
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                Appendix D  page 1 of 4
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.63318
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.63861
.65286
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.67431
.65403
.64821
.65964
.66059
.67096
.67860
.68954
.66900
.66305
.67675
.68077
.68229
.68312
.68311
.66969
.66373
.67367
.67417
.68439
.68765
.68540
.67174
.66576
.67827
.68072
.68977
.69414
.69613
.68074
.67469
.68659
.68713
.68651
.68931
.69022
.67655
.67054
.67358
.67428
.67816
.68484
.68636
.67134
.66537
.68046
.68286
.68617
.69337
.69376
.09541
.09654
.09585
.09750
.09723-
.09480
.08864
.08785
.09082
.08973
.08978
.08880
.08815
.08267
.08194
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.08394
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.08110
.07786
.07718
.08035
.07974
.08111
.07995
.07791
.07409
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.07696
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.07109
.07047
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.07235
.07170
.06818
.06760
.06914
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.07026
.07160
.07072
.06626
.06569
.07031
.07002
.07002
.07022
.06930
6.31
6.57
6.52
7.25
7.31
8.05
6.62
6.62
6.78
6.84
6.90
5.96
7.65
6.51
6.51
8.59
8.73
7.50
7.49
7.63
7.28
7.27
6.60
6.55
7.45
8.13
7.21
7.32
7.31
4.66
4.29
3.52
3.10
3.53
2.99
2.99
3.57
4.59
2.87
3.05
3.38
3.10
3.10
3.27
3.43
3.71
4.14
5.05
4.23
4.23
2.68
3.29
3.75
4.10
4.82
17 198
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.62175
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.67601
.66999
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.68190
.68177
.68451
.68540
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.67334
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.66684
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.67829
.68151
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.68891
1.18620
1.18639
1.18477
1.18097
1.17597
1.17004
1.16466
1.16465
1.16609
1.16346
1.16089
1.15713
1.15319
1.14835
1.14835
1.14998
1.14807
1.14577
1.14411
1.14249
1.13967
1.13968
1.14198
1.14017
1.13925
1.13649
1.13373
1.13020
1.13021
1.13209
1.12985
1.12901
1.12653
1.12442
1.12094
1.12094
1.12278
1.12105
1.12061
1.12061
1.11946
1.11609
1.11611
1.11798
1.11794
1.11904
1.11945
1.11789
1.11374
1.11376
1.11789
1.11652
1.11576
1.11543
1.11394
5.39 17
5.54 17
5.53 17
6.15 17
5.95 17
6.41 17
5.44 17
5.44 17
5.57 17
5.65 17
5.93 17
5.25 17
6.61 17
5.72 17
5.72 17
7.25 17
7.38 17
6.57 17
6.53 17
6.62 17
6.36 17
6.35 17
5.94 17
5.95 17
6.74 17
7.31 17
6.72 17
6.72 17
6.72 17
4.37 17
4.10 17
3.31 17
2.89 17
3.24 17
2.80 17
2.80 17
3.24 17
3.99 17
2.69 17
2.81 17
3.09 17
2.86 17
2.86 17
3.01 17
3.18 17
3.47 17
3.89 17
4.66 17
3.96 17
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Appendix D  page 2 of 4
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                                         Jul 86
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.67845
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A. 00
3.99
5.39
3.80
3.77
A. 58
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A. 25
A.2A
3.95
A. 50
A. 82
9.25
11.00
7.55
7.53
8.52
8.56
10.18
11. 5A
1A.A6
11. OA
11.03
9.23
9.23
10.12
10.18
7.36
7.81
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6.92
7.08
7.1A
6.39
6.62
5.82
5.81
6.2A
7.06
7.06
7.A7
7.79
6.78
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5.6A
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7.93
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1.11009
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1.10990
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1.10941
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1.10826
1.10828
1.10476
1.10061
1.10064
1.10376
1.10324
1.10453
1.10567
1.10218
1.09475
1.09476
1.09836
1.09742
1.09700
1.09658
1.09590
1.09309
1.09311
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1.09584
1.09655
1.09836
1.09787
1.09401
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1.09831
1.09855
1.09743
1.09242
1.09245
1.09788
1.09730
1.09700
1.09596
3.76 17
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3.43 17
3.40 17
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4.84 17
3.77 17
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3.51 17
3.98 17
A. 32 17
8.00 17
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6.68 17
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12.98 17
10.19 17
10.19 17
8.91 17
9.05 17
9.92 17
9.38 17
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6.7A 17
6.75 17
5.78 17
5.90 17
5.28 17
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5.60 17
6.25 17
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6.53 17
6.79 17
5.99 17
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.68964
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6.05
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6.87
7.56
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5.68
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5.58
5.58
7.84
9.64
17.02
16.44
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9.78
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1.09628
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1.09814
1.09742
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1.09694
1.09200
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1.09655
1.09523
1.09504
1.09489
1.09422
1.09072
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5.49
5.55
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6.14
5.32
5.18
5.23
5.23
7.36
8.87
13.18
12.69
13.08
8.35
8.34
.9.75
10.24
10.30
9.15
9.48
9.22
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1
0
0
0
0
0
0 213
0 213
0 213
0 213
0 213
0 213
0 213
0 213
0 213
0 212
0 212
0 211
8 213
8 214
7 214
0 214
0 214
0 214
0 213
0 213
0 213
0 213
0 213
0 213
                                      Total number of poisoning cases:
                                   Days on which a poisoning occurred:
                                     Potentially reportable incidents:
Means and deviations given on input
     for normally distributed variables:
        workers weight
     for lognormally distributed variables:
        dosing coefficient kd
        enzyme coefficient ke
        regeneration, p
        reversion, pp
        mean daily inhibition, %
        variability in AChE measurement
        reentry residue, ug/cm2
Other parameters given on input:
        number of members per crew
        number of crews
        total size of population
        no. of weeks worked per crew
        total no. of fields sprayed
        no. of days to complete field
        no. of hours worked per day
 70.00000   7.00000
5.10000
6.00000
.00893
.15000
4.00000

.11673
1.41000
1.30000
1.04570
1.01000

1.00000
3.00000
 12
 18
216
 26
936
  2
  8
332000000
              Appendix D  page 4 of 4
-------
Pesticide Exposure of Harvesters  of Blueberries,
  Blackberries, and Raspberries
        Research performed by

        University of California
        Richmond, CA  94804

        October 15, 1985
-------
                                                               476
                            Abstract
During the 1983 growing season in California three field studies
were conducted on the exposure of harvesters of berry crops to
pesticide residues.  These studies were designed to compare dermal
exposure to children (10-12 years old) and adults harvesting
these crops.  In all three studies, methiocarb on blueberries,
benlate on blackberries and benlate on raspberries, a consistent
relationship between age and exposure was observed.  When exposure
is measured as total weight of pesticide deposited per hour
worked, there is an increase of exposure with age.  When the
exposure measure is normalized by body weight there is no
difference in exposure as a function of age.  One study where
work rate was available, provided evidence that differences in
total exposure with age are attributable to differences in work
rate.
-------
                                              Section No. 2
                                              October  15, 1985
                                              Page  1 of  2
                      2.  TABLE OF CONTENTS
Section                                    Page Reference
   1.  Title  page	1  page
   2. Table of contents	2  pages
   3. Project description and
        administrative summary	2  pages
   4. Harvester Exposures in Blueberries	19  pages
       4.1 Introduction	1  of 19
       4.2 Study site and experimental  design....2  of 19
       4.3 Sample storage/  handling  and
           preparation	5  of i9
       4.4 Analytical procedures	5  of 19
       4.5 Crew characteristics	7  of 19
       4.6 Results	9  of 19
   5. Harvester Exposures in Blackberries	18 pages
       5.1 Introduction	1  of 18
       5.2 Study site and experimantal  design....2  of 18
       5.3 Sample storage,  handling  and
           preparation	6  of 18
       5.4 Analytical procedures	«	7  of 18
       5.5 Crew characteristics	8  of 18
 c
       5.6 Results	10  of 18
   €. Harvester Exposures in Raspberries	17  pages
       6.1 Introduction	1  of 17
       6.2 Site and  experimental design	2  of 17
       6.3 Sample storage,  handling  and
           preparation	8  of 17
-------
                                                            478

                                               Section  2
                                               October  15,  1985
                                               Page  2 Of  2
       6.4 Analytical procedures	..8  of  17

       6.5 Crew characteristics	8  of  17

       6.6 Results	9  of  17


Appendices

   A. Methods: Quality Assurance Project  Plan....52 pages

   B. Correspondence regarding  urinary
      metabolite analyses	17 pages
   C. Data files	22
pages
   D. Consent forms and  participant
      instructions	.... .9 pages
-------
                                                                 479
                                               Section  No.  3
                                               October  15,  1985
                                               Page 1 of  2
        3. PROJECT DESCRIPTION AND ADMINISTRATIVE  SUMMARY
     During the 1983 growing season the California PHAP Project
conducted three field studies on the exposure of the harvesters
of berry crops to pesticide residues.  These studies were design-
ed to compare the dermal exposure of children (10-12 years  old)
and adults harvesting these crops.  Secondly an attempt was to be
made to compare dermal exposures as measured by the patch techni-
que and glove monitors with exposures quantified by the urinary
excretion of the pesticides and their metabolites.

     The scope of these studies was limited, where possible, to
the analyses of exposures to the pesticides  applied to  the  crops
most recently before harvesting commenced.  These  pesticides
turned out to be methiocarb on  blueberries and  benomyl  on black-
berries and raspberries.   Approximately twenty  workers  were in-
volved  in each of these studies.  In addition to the collection
of data on dermal exposures, foliar residue  data were also  col-
lected.
                                          *

     The principal failure in achieving the  goals of these
studies is that no urinary metabolite data can  be reported. The
background behind this failure is detailed in the correspondence
included here as Appendix B.  At this time these  samples  remain
in storage awaiting analysis by EPA or its designee. As a result,
the individual study reports, Sections 4,  5,  and  6, deal  with  the
patch, glove and foliar  residue data only.  Included as Appendix
-------
                                                              480
                                               Section No.  3
                                               October 15,  1985
                                               Page 2 of 2
C is the information needed for  subsequent  analysis of the  meta-
bolite results when they become  available.

     A consistent relationship between exposure and age was
observed in all  three  studies.  When exposure is measured as
total weight of pesticide deposited per hour worked, e.g. mg/hr,
there is an increase of exposure with age.   When the exposure
measure is normalized by the body weight of the worker,  i.e.
mg/kg/hr, then there is no difference in exposure as a function
of age.   The blueberry study,  where  information  related to  work-
rate was available, provided some evidence that the differences
in total exposure with age are attributable to  differences  in
workrate between children and adults.
     The staff of the  California PHAP was assisted  in all phases
of the field studies by Dr. James M.  Witt of the Department of
Agricultural Chemistry, Oregon State  University, Corvallis, Ore-
gon,  and Ken Brown, Extension Agent,  Oregon State  University,
Salem, Oregon.  Through  their  knowledge  of  the agriculture  in the
region and their  liason with many growers,   they and their  staffs
were able to locate suitable field sites and enlist the coopera-
tion of the owners.  John Reinhold,  working under Dr. Witt's
aegis, took foliar samples prior to  our  arrival in Oregon and
assisted the PHAP staff in conducting the monitoring studies.  We
are grateful for their  assistance.
-------
                                                             481
                                               Section No. 4
                                               October 15, 1985
                                               Page 1 of 19
*       4.  HARVESTER EXPOSURES TO METHIOCARB  IN BLUEBERRIES
>*
 4.1 Introduction

      In a continuing effort to develop experimental data on the
 exposure to pesticides of fruit harvesters of different ages, a
 study was conducted involving the exposure of blueberry har-
 vesters to residues of the pesticide methiocarb  (Mesurol).  The
 volunteers for this study were divided into  two groups, one
 provided with cotton gloves and dermal patches to measure dermal
 exposures and the other not so provided so that there would be no
 unnatural barrier to their exposure.   Urine samples were  collect-
 ed from all subjects to be analyzed for metabolites of the
 pesticide.

      The purpose of the study was two-fold.  The primary intent
 was to measure the worker's dermal  exposures and determine
 whether a significant difference exists between the exposures
 experienced by children and adults.  Second, an attempt was to be
 made to correlate dermal exposure to methiocarb as determined by
;patch and glove monitors with that  determined by the concentra-
"L
-tion of the metabolite of the pesticide excreted in the urine of
 the exposed workers.   An  additional,  but secondary goal,  was to
 contrast the  absorbtion of the pesticide, as measured by the
 urinary metabolite concentration, between the group wearing
gloves with that not so protected with the object of determining
 the degree of protection afforded.
-------
                                               Section No. 4
                                               October 15, 1985
                                               Page 2 of 19
4.2 Study site and experimental  design

     A fifteen acre plot of the  Bluecrop variety of blueberries,

located about two miles north of Salem, Oregon, was chosen as the

site of the study.   Twenty  five  harvesters,  including men, women

and children, participated  in  the study on a voluntary basis.

They were paid $20 for completing the five day  course of monitor-

ing and urine collection.   Detailed consent  forms and instruc-

tions were handed to each participant before the study began.

The participation of all  minors  required the signed consent of

the parents.


     On Friday,  22  July 1983, methiocarb had been applied to the

blueberries between 0800 and 0900 hours by fixed wing aircraft.
                                                          -—~" ""*"" ~~ *
A 75% wettable powder formulation was applied  at a rate/or 1.5
                                                       ^^^^•^^^^^^
Ib/A.   This plot had been previously  treated with methiocarb at

the same  rate on 5  July 1983.  The harvesters were permitted to

enter the field on Monday,  25 July, the day that the study

commenced.   Weather  conditions were recorded and are given in

Table 4.1.


     The  study was designed to last five days.  None of the

subjects,  as far as  could be ascertained, picked blueberries on

the preceding Saturday or Sunday.  All subjects were instructed

to collect a urine specimen before they entered the field on

Monday to serve as a pre-exposure control.   On  Monday the workers

were divided into two groups,  A  and B.  Group A was provided

light-weight cotton gloves, similar  to those used  in photographic
-------
                                                              483
                                               Section  No.  4
                                               October  15,  1985
                                               Page  3 of  19
                            Table 4.1
                       Meterological Data
           Blueberry Site, 2 miles N of Salem,  Oregon
  Date
DPA
Time
     Temp.  C
RH
Weather
7/22/83
7/25/83
 0
 3
7/26/83   4

7/27/83   5
7/28/83   6
    0925
    0730
    0918
    1105
    1325
    1508
          21.0      70%
          18.0      80
          18.5      70
          19.0      80
          21.2      60
          22.0      60
          18.3      80
1128      21.0      58
    not recorded
0800      18.0      90
1115      21.0      50
              partly cloudy
              heavy overcast
              heavy overcast
              partly sunny
              partly sunny
              sunny
              partly sunny
              partly sunny
              heavy rain
              sunny
              sunny
                                                                   8
-------
                                                               484
                                              Section No. 4
                                              October 15, 1985
                                              Page 4 of 19
darkroom work, to be worn  throughout the workday while picking
berries. During the lunch  break  the gloves were removed and new
gloves  issued after the break.  Also, new gloves were provided if
a pair  became too soiled or wet.
     On Tuesday Group A was outfitted with cotton gauze-patch
monitors, in addition to the cotton gloves, to measure total
dermal  exposure.  Details  of the placement and handling of the
patches and gloves are contained in  Appendix A. Group b wore
neither gloves  nor patches at any  time  during  the study.

     The collection of urine specimens was scheduled to begin on
Wednesday when it was assumed  excretion would have reached some-
thing near steady state.   Starting Tuesday after work all sub-
jects were provided with 1-liter plastic specimen bottles and
intructed to collect their urine for the reminder of the 72 hours
of the study in  the following regimen: night samples to go from
the termination of work to through the next morning's void;  day
samples from that point through  the  termination of work.  On
Wednesday, 26 July,  about  half the subjects did not pick berries
due to a heavy rainfall that commenced about 8 AN and lasted for
about one hour.   The subjects  from group A who did harvest
berries despite the rain were  provided with gloves  ana patches.

     On Thursday, 27 July, all participants worked  in the field.
Group A was provided with  gloves only, but not patches.  None of
the subjects picked  on Friday, 28 July but they did  deliver their
-------
                                                                 485
                                              Section No. 4
                                              October 15, 1985
                                              Page 5 of 19
final overnight urine sample that morning.
     Throughout the study foliar  residue samples were collected
according to the procedures detailed in Appendix A. On three
occasions participants were also  outfitted with personal air
samplers to measure pesticide residues existing as aerosols.
These procedures are also detailed in Appendix A.
4.3 Sample storage handling and preparation
     Urine samples were stored on ice for no more than 4-6 hours
and transported to the laboratory the same day as they were
received from the subjects.   Individual  urine sample volumes were
measured and duplicate 20 mL aliquots  were pipetted into glass
ampules to which 1.5 mL of concentrated hydrochloric acid was
added as a preservative resulting in a final pH of less than
0.5).  The ampules  were sealed and  stored at room  temperature.
     Gloves and patches were collected from participants by  pro-
ject personnel and stored in zip-loc plastic bags. (See section
6.7 of  the  QA  Plan  for sample preservation  procedures.)

4.4 Analytical procedures
     Extraction of samples was as detailed in section 9 of the
Quality Assurance Plan.
     Methiocarb residues were analyzed by reverse-phase HPLC
using a  Waters 6000A dual  pump Solvent Delivery System, a WISP
Model 710A Automatic Sample Processor, a Waters Model 720 System
                                                         1     10
-------
                                                                 486
                                               Section No.  4
                                               October 15,  1985
                                               Page 6 of 19

Controller with a Mode 730 Data Module and a Model  4530  Variable
Wave-length Detector.  A Supelco C^g reverse-phase column (25 cm
x 4.2 mm ID) was  capable  of separating each of  the  three com-
pounds reported to be associated  with methiocarb residues
{methiocarb:  3,5  dimethyl-4-(methylthio)phenyl-N-methyl  carbarn-
ate; methiocarb sulfoxide: 3,5 dimethyl-4-(methylsulfonyl)phenyl-
N-methyl carbamate; methiocarb sulphone:  3,5 dimethyl-4-(methyl-
sulfonyl)phenyl-N-methYl  carbamate} without appreciable interfer-
ence from extraneous materials originating in  the field. The
mobile phase was a mixture of acetonitrile and water and the
optimum chromatographic conditions  for each compound  are listed
in Table 4.2.
                            TABLE 4.2
                   Chromatographic  Parameters
                             for  the
                       Analysis of  Mesurol
                               and
                        Related Compounds

         Column              25 cm  X 4.6  mm C,« Supelco  LC-18-DB
                             with a C^g Guard-PAK precolunm
         Mobile Phase        65%  Acetonitrile,  35%  Water
         Flow Rate           0.9  ml/min
         Detecrtor           Wavelength:   265  nm
         Parameters          Sensitivity:  0.02 AUFS
         Integration         Peak Width:   20
         Parameters          Noise  Rejection:   7.5
                             Chart  Speed:  0.5  cm/min
                             Run  Time:  10 min
                                                       tr
                                                             11
-------
                                                                 487
                                               Section No. 4
                                               October 15, 1985
                                               Page 7 of 19
4.5 Crew characteristics
     The crew characteristics, including sex, height, weight,  age
and computed body surface area are given in Table 4.3.  In additon,
the crew included six Asian workers in Group A and two in Group B.
     The owner of the blueberry farm selected his harvesters
individually, and allowed only approved personnel to work in his
plots; because of this procedure, he maintained a relatively
stable work crew, year-to-year.  The owner adhered to this prac-
tice because the blueberry bush is a perenial that is not cut
back heavily each year like the other types of berries included
in this series of studies; and damage caused by careless workers
could cause long-term losses in productivity for the plants.

     Upon arrival at the study site it was discovered that the
grower had preselected the crew for the exposure study.   These
individuals came from the growers regular crew, and included
relatives and friends of his family.  The entire crew was com-
prised of 24 individuals, ranging in age from 10 to 47 years old.
Four (17%)  were at the age of ten, while ten of the subjects
(42%)  were between 11 and 15 years, and the remaining ten were 16
years or older.  In Group A (the 13 individuals wearing gloves
and patches), three (23%) were ten years old; five (39%) were
between 11 and 15 years; and the remaining five were over 15.
                                                12
-------
                                               488
                              Section No.  4
                              October 15,  1985
                              Page 8 of 19
            Table 4.3

         Blueberry Study

Physical  Characteristics of Crew
IDI
2
3
4
5
6
7
8
9
10
11
12
17
26
1
14
15
16
18
19
20
21
22
23
25
Group
A
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
B
B
B
Sex
F
F
M
F
M
M
F
F
M
M
F
M
F
F
F
F
M
M
M
F
M
F
M
M
Age weight (kg)
15
10
14
10
14
20
18
14
16
10
47
11
28
40
14
16
14
15
11
30
17
37
14
10
52.2
31.8
48.5
36.3
54.4
63.5
45.4
45.4
53.5
34.0
45.4
35.8
60.0
61.2
54.4
61.7
47.6
59.4
27.2
61.2
49.9
72.6
79.4
37.6
Height (cm)
160
114
152
147
170
165
152
152
163
140
152 ~*
137
162
168
168
168
168
146
137
165
160
175
187
127
Area (m2)
1.50
1.00
1.45
1.20
1.60
1.65
1.40
1.40
1.55
1.15
1.40
1.15
1.60
1.65
1.65
1.65
1.50
1.55
1.05
1.65
1.50
1.85
2.00
1.15
                                             13
-------
                                                              489
                                               Section No. 4
                                               October 15, 1985
                                               Page 9 of 19
4.6 Results
     As noted above, only on Tuesday was there a complete set of
both patch data and glove data.  On all four days, however, glove
data was collected.  Au important issue then, is the degree of
correlation between the glove exposure and total exposure.  Fig-
ure 4.1 shows the scatterplot of patch exposure vs. glove expo-
sure.  The two variables are positively correlated and the re-
gression is significant, but  the r2 value of 0.40 is not parti-
cularly impressive. However, as will be discussed below, about
50% of the total exposure is to the hands.  Hence, glove exposure
will be a much better predictor of total exposure than of patch
exposure alone.
     It is clear that the degree of exposure to foliar residues
is a function of the residue level and the activity of the work-
er.  Because of the method of payment of the workers in blue-
berries, it was possible to obtain data on the mean daily har-
vesting rate in Ibs/hr for each worker.  Because all workers were
engaged in harvesting it seems reasonable to hypothesize that the
                                           *
mean daily yield should provide a good index of the activity
related effect on exposure. It seems highly likely, however, that
yield is a strong function of age.  Indeed, it seems likely that
the principal effect of age on exposure among workers carrying
out the same task will be through the workrate variable.
                                                                14
-------
                                               Section  No.  4         490
                                               October  15,  1985
                                               Page 10  of  19
     Figure 4.2 and 4.3 show the mean  yield  rate  for  the  entire
period of the experiment vs. age for males and  females  respec-
tively. In both cases there is an increase of yield with  age.
                                                                  15
-------
                                                                                                     491
                                                                          Section 4
                                                                          October 15, 1985
                                                                          Page  11 of 19
                                       Figure  4.1

nsoa s.oo    BunsENur SWOT, FKKH DUOS, us GUVE EXPOS.  («yw)« DM 2   nut B««303-2P  REV* 7

ODttMNDt ILOT
mssac VALUE IMMXMTI uswxss
             0.00000     0.900000     1.60000     2.40000      3.20000     4.00000      4.80000
                  0.400000      1.20000      2.00000     2.80000     3.60000     4.40000
       4.80000  4
       4.70000  4
       4.60000  4
       4.50000  4
       4.40000  4
       4.30000  4
       4.20000  4
       4.10000  f
       4.00000  *
       3.90000  +
       3.80000  +
       3.70000  4
       3.60000  4
       3.50000  4
       3.40000  4
       3.30000  4
       3.20000  4
       3.10000  4
       3.00000  4
       2.90000  4
       2.80000  4
       2.70000  4
       2.599*9  4
       2.49999  4
       2.39999  4
       2.29999  4
       2.19999  4
       2.09999  4
       1.99999  4
       1.69999 4
       1.79999  4
       1.69999  4
       1.59999  4
       1.49999 4
       1.39999 4
       1.29999 4
       1.19999 4
       1.09999 4
      0.999994 4
      0.899994 4
      0.799994 4
      0.699994 4
      0.599994 4
      0.499994 4
      0.399994 4
      0.299994 4
      0.199994 4
   9.99938E-02 4
       0.00000 4
            0.00000    0.800000      1.60000      2.40000      3.20000     4.00000     4.80000
                  0.400000     1.20000     2.00000     2.80000     3.60000      4.40000


                                   c cuvn
                                                                                                      16
-------
                                                                   Section  4
                                                                   October  15, 1985
                                                                   Page 12  of 19
                                                                     492
ABSTAT 3.00

COMMAND: PLOT
                                    Figure 4.2
BLUEBERRY STUDY, MEAN YIELD  (KG/HR) VS AGE> MALES
                                                                            FILE:  8303-PH
0
4
M
E
A
N
Y
L
D
              0.00000     8.33333      16.6667      25.0000      33.3333      41.6667      50.0000
                     4.16667      12.5000      20.8333      29.1667      37.5000     45.8333
20.0000
19.5833
19.1667
18.7500
18.3333
17.9167
17.5000
17.0833
16.6667
16.2500
15.8333
15.4167
15.0000
14.5833
14.1667
13.7500
13.3333
12.9167
12.5000
12.0833
11.6667
11.2500
10.8333
10.4166
9.99998
9.58332
9.16665
8.74998
8.33331
7.91665
7.49998
7.08331
6.66665
6.24998
5.83331
5.41665
4.99998
4.58331
4.16664
3.74998
3.33331
2.91664
2.49998
2.08331
1.66664
1.24998
0.833311
0.416644
0.00000

4
4
4
4
4
4
4
4
4
4
4
4
4 1
4
4
4 1
4
4 1
4
4
4
4
4
4
4
4 1
4
4
4 1
4 1
4
4
4
4
4 11 1
4
4 1
4
4
4 11
4
4
4
4
4
4
4
4
4
_4 	 4 	 4 	 4 	 4 	 4 	 4 	 4 	 4 	 4 	 4 	 4 	
               .00000      8.33333      16.6667      25.0000      33.3333      41.6667      50.0000
                    4.16667      12.5000      20.8333      29.1667      37.5000      45.8333


                                      2 ACE
                                                                             r-
                                                                                     17
-------
                          Section  4
                          October  15, 1985
                          Page 13  of 19
                                            493
Figure 4.3
ABSTAT 3.00
COMMAND: PLOT
0

















0
4


H
C
A
N
T
L
D
























20.0000
19.5633
19.1667
18.7500
18.3333
17.9167
17.5000
17.0833
16.6667
16.2500
15.8333
15.4167
15.0000
14.5833
14.1667
13.7500
13.3333
12.9167
12.5000
12.0833
11.6667
11.2500
10.8333
10.4166
9.99998
9.58332
9.16665
8.74998
8.33331
7.91665
7.49998
7.08331
6.66665
6.24998
5.83331
5.41665
4.99998
4.58331
4.16664
3.74998
3.33331
2.91664
2.49998
2.08331
1.66664
1.24998
0.833311
* 0.416644
0.00000

0.

BLUEBERRY STUDY, MCAH YIELD (KC/BR) VS ACE, FEMALES PILEi 8303-PP
.00000 6.33333 16.6667 25.0000 33.3333 41.6667 50.0000
4.16667 12.5000 20.8333 29.1667 37.5000 45.8333
4
4
4
+
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4 1
4
4
4
4
4
4
4 1
4
4 111 1
4
4
4 1
4 1
4 1 1
4
4 1
4
4
4 1
4
4
4
4
4
4
4
-4— 	 4 	 -4-- 	 4 	 4-- 	 4 	 4- — — 4 	 4 	 4 	 4 	 4 	 4
00000 8.33333 16.6667 25.0000 33.3333 41.6667 50.0000
4.16667 12.5000 20.8333 29.1667 37.5000 45.8333
  2 ACE
                                               18
-------
                                                               494
                                               Section No. 4
                                               October 15, 1985
                                               Page 14 of 19
The age range for females is sufficient to suggest a paateau in
the neighborhood of 8 kg/hr, but no such plateau is seen for
males because of the limited age range of the workers. In any
case there is clear evidence that yield rate is a function of age
and sex.
     If, then, we consider exposure a function of residue level
and yield rate, age and sex are taken into account through their
non-linear effect on yield rate.  Table 4.4 contains the results
of a multiple linear regression of the log of residue and the log
of the yield rate against the log of the glove exposure rate
which we use here as a surrogate of the total exposure rate.  The
logarithmic relationship is suggested by the fact that without
residue there can be no exposure as is the case with work rate.
Hence a multiplicative relation is plausible and the logarithmic
transform appropriate.

     As can be seen in Table 4.4 the F value indicates that both
regression coefficients are non-zero and that these two variables
account for about 60% of the variability in the data.  The foliar
residue is the more important predictor of exposure as indicated
by the standardized coefficients.  These numbers indicated the
change in the dependent variable resulting from a change in the
independent variable of one standard deviation.  Hence, a one
standard deviation change in the log of the yield rate changes
the log of the glove exposure by 0.376 as contrasted with a
change of 0.745 with a one standard deviation change in the log
                                                                19
-------
                                 Table 4.
ABSTAT 3.00   BLUEBERRY STUDY, MULTIPLE REGRESSION, GLOVE VS RESIDUE  &  YIELD

COMMAND: REGR

MISSING VALUE TREATMENT: LISTWISE

                     *** MULTIPLE LINEAR REGRESSION  ***

DEPENDENT VARIABLE:  10 LNGLRATE               34  VALID CASES
COEFP OF DETERMINATION:    0.578869
MULTIPLE CORR COEFF:       0.760835
                        ESTIMATED CONSTANT TERM:      -1.61601
                        STANDARD ERROR OF ESTIMATE:   0.717036
ANALYSIS OF VARIANCE  FOR  THE  REGRESSION:
                      DEGREES OF      SUM OF
SOURCE OF VARIANCE      FREEDOM      SQUARES
      REGRESSION
      RESIDUALS
      TOTAL
           2
          31
          33
VARIABLE
12 LNYLDRAT
13 LNRES

DURBIN-WATSON
 REGRESSION
COEFFICIENT
   0.853255
   0.759902

    2.26362
 MEAN OF
 SQUARES
 10.9541
0.514140
       21.9082
       15.9383
       37.8465
              CORRELATION
STANDARDIZED      WITH
 COEFFICIENT    DEPENDENT
    0.376589     0.218159
    0.745907     0.665919
 F TEST
21.3057
                                  -o o t/>
                                  o» n rt>
                                  to n- o
                                  n> o r»-
                                    cr -*•
                                  —< o> o
                                  01 1 3
                                  o —• .&
                                  -h en
                                                                                     vo
                                                                                     oo
                                                                                     en
                                                                                      LTI
-------
                                                               496
                                               Section No. 4
                                               October 15, 1985
                                               Page 16 of 19
of the residue level.
     A second regression was carried out with the log of age
included as a third predictor variable to see if there was evi-
dence of any independent influence of age other than through work
rate. As shown in Table 4.5 the result is essentially unaffected
as measured by the coefficient of determination (r2).  The appro-
priate F test applied to the residuals in the two  variable vs.
the three variable case indicates that the small increase in r
is only what one would expect from random variation. Here age and
yield rate have a similar influence on the outcome as might be
expected because of the high correlation between the two as
evidenced by Figure 4.2.  Hence, we conclude that there is no
evidence that age is an important variable except thru its in-
fluence on work rate.

     This conclusion is supported by a different analysis in
which each individual's average glove exposure,  normalized for the
weight of the individual (mg/kg/hr), is calculated over the course
of the experiment and regressed against age.  Figure 4.4 shows
the scatter plot.  The F-value is 0.009 and r2 about 10~^
indicating an almost totally random relationship between these
variables.  That is, exposure rate on a per unit weight basis is
virtually unrelated to the age of the worker. This finding sup-
ports the interpretation that workrate is the important variable
and that younger workers, who tend to be smaller, work at lower
rates and thus receive less total exposure than adults.
                                                                 21
-------
                                                                        Section 4
                                                                        October 15,  1985
                                                                        Page  17 of 19               497
                                          Figure  4.4
ABSTAT 3.00      BLUEBERRY BTDDY, WEIGHT NORMALISED CLOVE EXPOSURE VS ME      PILEi Bi8303-Cl   REV! 7

OOmARDl PLOT

NI8SIRG VALUE TREATMBTt LI6WISC

             0.00000      1.33333      I«.«f7     25.0000     33.3333      41.Hit      50.0000
                   4.1CC67     12.5000      20.8333      29.HC7      37.5000      4S.B333
                •4——4-—-4——4——4——4——4——4—--4———4« -—4——4——4
   •.OOOOOE-02  4
   7.87500E-02  4
   7.75000E-02  4
   7.C2499E-02  4
.













































P.49999E-02
.37499E-02
.24999E-02
.12499E-02
.99999E-02
.B7499E-02
.74999E-02
.C2499E-02
.49999E-02
.37499E-02
.24999E-02
.12499E-02
.99999E-02
.87499E-02
.74999E-02
.62499E-02
.49999E-02
.37499E-02
.24999E-02
.12499E-02
.99999E-02
.87499E-02
.749991-02
.C2499E-02
.49999E-02
.37499E-02
.24999E-02
.12499E-02
.99999E-02
.87499E-02
.74998E-02
.62498E-02
.49998E-02
.37498E-02
.24998E-02
.12498E-02
.99998E-02
.87498E-02
.74998E-02
.(2498E-02
.49998E-02
.37498E-02
.24998E-02
.12498E-02
.OOOOOE-02
0.
4
4 1
4
4
4
4
4
4
4
4
4
4
4
4
4 1
4 11
4
4
4 1
4
4 11
4
4 1
4
4
4 1
4 1
4
4 1
4 1
4
4
4
4
4
4
4
4
4
4
4
4
4
4 1
4
00000 B. 33333 1C.CCC7 25.0000 33.3333 41.CCC7 50.0000
                   4.1C6C7     12.5000      20.B333      29.1M7      37.5000     45.8333


                                    3 ACE
                                                                                                   22
-------
ADSTAT 3.00

COMMAND: REGR
                                         Table 4.5
                            BLUEBERRY STUDY,  MULT.  REGR. ,  GLOVE VS RESIDUE,  YIELD & AGE
             MISSING VALUE TREATMENT:  LISTWISE

                                 *** MULTIPLE LINEAR REGRESSION ***
             DEPENDENT VARIABLE:  10 LNGLRATE

             COEFF OF DETERMINATION:   0.595609
             MULTIPLE CORR COEFF:      0.771757
                                             34 VALID CASES

                                       ESTIMATED CONSTANT TERM:
                                       STANDARD ERROR OF ESTIMATE:
                                        -2.24593
                                        0.714256
             ANALYSIS OF VARIANCE FOR THE REGRESSION:
             SOURCE OF VARIANCE
                   REGRESSION
                   RESIDUALS
                   TOTAL
                      DEGREES OF
                       FREEDOM
                          3
                         30
                         33
        SUM OF
       SQUARES
       22.5417
       15.3048
       37.8465
            VARIABLE
            11  LNAGE
            12  LNYLDRAT
            13  LNRES

            DURBIN-WATSON
                REGRESSION
               COEFFICIENT
                  0.348166
                  0.679906
                  0.749882

                   2.37323
STANDARDIZED
 COEFFICIENT
    0.149566
    0.300080
    0.736071
      MEAN OF
      SQUARES
      7.51390
     0.510161

CORRELATION
    WITH
  DEPENDENT
   0.267307
   0.218159
   0.665919
 F TEST
14.7285
                •o o to
                o» o n
                 O ct-
                  cr -••
                —• ro o
                oo -i a
                o —• *>
                -»• tn
                                                                                             vo
                                                                                             oo
                                                                                             en
rv>
                                                                                              oo
-------
                                                               499
                                               Section No. 4
                                               October 15, 1985
                                               Page 19 of 19
     Table 4.6 shows the anatomical distribution of methiocarb
exposure.  Here less of the exposure was to the hands than was
the case in the strawberry studies reported previously.  Since
the blueberry variety involved in these studies grew on bushes as
tall as 1.7 meters, there was a substantially greater potential
for body contact than is the case with strawberries.  There is a
considerable difference in the data for the two different days,
presumably  because of the substantial rainfall on the third  day
of  the  study.   The data on day 4  post-application  should  be
regarded as more representative of the normal exposure situation.
                            Table 4.6
          Anatomical Distribution of Dermal Exposure to
               Methiocarb on Blueberry Harvesters

                                   Days Post-Application
Body Part                             4            5
Head+Neck                        0.28  (7.4)*    0.13 (6.2)
Back+Shoulders  "                 0.13  (3.4)     0.19 (8.8)
Chest+Stomach                    0.23  (6.0) •    0.23 (10.6)
Lower Legs                       0.23  (6.0)     0.34 (15.9)
Upper Arms                       0.22  (5.8)     0.20 (9.7)
Lower Arms                       0.64  (16.8)    0.74 (34.6)
Hands                            2.05  (53.9)    0.31 (14.3)
Total                            3.80           2.14
*Tabled numbers are exposure rates in mg/hr followed by the
percent of the total in parentheses.
-------
                                             Section  5
                                             October 15,  1985
                                             Page 1  of  18         5QQ

       5.  HARVESTER EXPOSURES TO BENLATE IN BLACKBERRIES

5.1  Introduction
     In a continuing effort to develop experimental data on the
exposure to pesticides of fruit harvesters of different ages,  a
study was conducted involving the exposure of blackberry harves-
ters to residues of the pesticide Benlate (benomyl).   The volun-
teers for this study were divided into two groups,  one provided
with cotton gloves and dermal patches to measure  dermal exposures
and the other not so provided so that there would be no unnatural
barrier to their exposure.   Urine samples were  collected  from  all
subjects to be analyzed for metabolites of the pesticide.
     The purpose of the study was two-fold.   The  primary  intent
was to measure the worker's dermal  exposures  and  determine wheth-
er a significant difference exists  between the  exposures  experi-
enced by children and adults.  Second, an attempt was  to  be made
to correlate dermal exposure to benlate  as  determined  by  patch
and glove monitors with that determined by the  concentration  of
the metabolite of the pesticide excreted in the urine  of  the
                                              •
exposed workers;  An additional, but secondary  goal, was  to
contrast the absorption of  the  pesticide,  as  measured  by  the
urinary metabolite concentration, between the group wearing
gloves with that not so protected with the  object of determining
the degree of protection afforded.
                                                                    25
-------
                                             Section   5             501
                                             October  15,  1985
                                             Page  2   of   18
5.2 Study Site and Experimental Design
     The site chosen for an exposure study among blackberry
harvesters was located within a plot of about 30 acres of the
Marion variety near Independence,  Oregon.   Over the growing sea-
son this field had been treated with a variety of  insecticides,
herbicides and fungicides;  and the spray history is delineated in
Table 5.1.  The most  recent treatment  had  been with Lannate and
Thylate applied to various portions of the plot on 6  and  9 July.
However, for several practical reasons,  the 1 July treatment was
chosen as the pesticide application to follow with our measure-
ments.  First,  the entire plot was treated in  one day, offering
the possibility of more homogeneous foliar residues.   Second, in
addition to  Lannate and Thylate,-benomyl had  been applied on
1 July, and this happened to be the same compound followed in the
raspberry study conducted the  previous week, meaning  that the
same residue and metabolite analytical methodology could  be uti-
lized for both  studies.  Third,  no readily detectable  urinary
metabolites  could be expected  from Lannate, and we did not know
what dermal  adsorption and  urinary excretion patterns might be
expected from Thylate;  whereas,  we did know some of the pertinent
toxicological and  metabolic  information  regarding benomyl.
     The study  lasted for five days, running from Monday, 18 July
1983 through  Friday,  22 July 1983.  On-site weather observations
for the study site covering 19 through 22  July are found  in
Table 5.2.  There was one heavy  rainfall early in the  study,
having come  during Monday night.  Although the field was wet on
                                                                   26
-------
                                             Section  5
                                             October 15,  1985
                                             Page 3  of  18
                                        502
                            TABLE 5.1

                      1983 Spray Schedule*
                     Marion Blackberry Field
      Date
 Product
Application Rate
    and Mode	
     3 March

     17-18 March
     28 March

     13 April


     15 April
     6-9 May
     13-16 May

     14 May

     5 June

     1 July

     6, 9 July
   Lime Sulfur
    Spray-Aid
    Parathion
 Karmex (diuron)
    Paraquat
    X77 (sic)
     Dinitro
   WDX77 (sic)
     Roundup
     Guthion
     Dinitro
   WDX77 (sic)
     Ronilan
     Thiraro
     Benlate
     Lannate
     Benlate
     Thiram
     Lannate
Thylate (thiram)
 7.5 gal/A in 100 gal
 0.25 gal/A
 1 Ib/A
 2.4 Ib in 4* band
 1.1 pt
 3.2 oz
 2.0 qt/100 gal
 50 gal/A
 1 pt
 General Burn-back
 0.5 gt on centers
 0.5 Ib/A
 Burn-back
 1 pt
 1.75 lb/100 gal
 1.3125 Ib
 on West 1/2
 8 oz
 3- lb/100 gal
 1 Ib
 0.5 gal/100 gal
 1 Ib
 3 Ib
 0.5 gal
 3.0 Ib
* This table does not contain all  of  the
terminates at the time of the study.
                 1983 spray history,  but
                                                                  27
-------
                                             Section   5
                                             October  15,  1985
                                             Page  4   of   18
                                                     503
                            TABLE 5.2

                      Weather Observations
                     Marion Blackberry Field
   Date
Time
Dry Bulb
  (QC.)
Wet Bulb
  (QC.l
% RH    Description
19. July
1430
   22.8
   19.4     73    Cloudy and
                  partly sunny;
                  had rained
                  the night
                  before.
20 July
21 July
22 July
1300
1408
0730
1008
0925
21.1
23.3
14.2
21.1
21.1
15.8
20.0
13.1
17.2
17.8
57
74
89
67
72
Sunny with
spotty clouds.
*
*
*
* Although no information was recorded for  these days, the
weather was generally clear  and  sunny  for the duration of the
study.

Tuesday morning,  relatively  warm weather that day dried the
foliage within a  reasonable  time, allowing  the crew to work
without dealing with very wet gloves.
     Consent  forms approved  by the Committee for the Protection
of Human Subjects at the  University  of California at Berkeley
(see  Appendix  D) were distributed to each participant along with
detailed instructions  for their  particular  subgroup  (Appendix
D).   in order  for anyone to be allowed to join the Study, they
were  required to  return their consent  form  signed; and if they
were minors, their form had to be signed by their parents, as
                                                                    28
-------
                                             Section  5           504
                                             October 15, 1985
                                             Page 5  of  18
well.  Each participant was paid a bonus of $20.00 for  the  com-
pletion of the study if all urine samples were collected as
instructed.  This was done, not as an inducement to participate,
but to offset the inconvenience and potential aggravation of
providing total urine collection for up to 72 hours.
     As with  the blueberry  study  (See Section 4.2), the volun-
teers were divided into two subgroups.   The first,  Group A,  was
assigned to wear patch monitors and gloves,  while the second were
to have no unusual  impediments to exposure,  which the gloves
might constitute.  Thus,  Group B wore neither gloves nor patches
at any time during the study.   All subjects were instructed to
collect a urine specimen before they entered the field on Monday
to serve as a pre-exposure control.   On  Monday Group A  was  pro-
vided light-weight cotton gloves to be  worn throughout  the  work-
day while picking berries.  During the  lunch break the  gloves
wer.e removed and new gloves issued after the break.   Also,  new
gloves were provided if a pair became too soiled or wet.
     On Tuesday Group A was outfitted with cotton gauze-patch
monitors, in addition to the cotton gloves,  to  measure total
dermal exposure.  Details of the placement and handling of  the
patches and gloves  are contained in Appendix A.
   *
     The collection of urine specimens was scheduled to begin on
Wednesday when it was assumed excretion would have reached  some-
thing near steady state.   Starting Tuesday after work all sub-
jects were provided with 1-liter plastic specimen bottles and
instructed to collect  their urine for the remainder of the  72
                                                                  29
-------
                                            Section  5
                                            October 15, 1985
                                            Page 6  of  18
hours of  the study in the following regimen:  Night samples to go
from the  termination of work to through the next morning's void;
day samples from that point  through the termination of work.
     The  owner of this plot  did not select individuals for his
crew, but allowed anyone who wished to do so to come and pick; he
merely decided which portions of  the  field would be harvested
each day.   In  spite of the fluid nature of the work force,  there
were a number  of family groups that either came from the sur-
rounding  area  or  followed the  hand harvest crops through Oregon
and Washington as migrants,  and these groups made up a relatively
stable population at the study site for the  duration of the
experiment.  This characteristic of the work force also meant
that there were  children available for inclusion in the study who
                              •
were younger than the 12-year  old legal age  limit for children
who can be hired directly by a grower.  Also, the task of re-
cruiting  the participation of  youngsters with parental approval
was greatly simplified when  the parents were also participating.

5.3 Sample  Storage Handling  and Preparation
     Drine samples were stored on ice for no more than 4-6 hours
and transported  to the laboratory the  same day as they were
received  from  the subjects.   Individual urine sample volumes  were
measured  and duplicate 20 mL aliquots  were pipetted into glass
ampules to which 1.5  mL of concentrated hydrochloric acid was
added as  a  preservative  (resulting in a final pH of less than
0.5).  The ampules were sealed and stored at room temperature.
                                                            "     30
-------
                                             Section  5
                                             October 15,  1985     5Q6
                                             Page 7   of   18
     Gloves and patches were collected from participants  by  pro-
ject personnel and stored in zip-loc plastic bags.  (See  section
6.7 of the QA Plan for sample preservation procedures.)

5.4 analytical Procedures
     Extraction of samples was as detailed in Section 9 of the
Quality Assurance Plan.
     Benomyl residues were analyzed by reverse-phase HPLC using a
Waters 6000A dual pump Solvent Delivery System, a  WISP Model 710
A automatic sample processor, a Waters Model 720  System Control-
ler with a Model 730 Data Module  and a Model 4530  Variable Wave-
length Detector.  A nBondapak C18 reverse-phase column (25 cm X 2
mm ID) was capable of separating  benomyl from interference by
substances originating in the field.   The mobile  phase found to
be most effective was 65% acetonitrile and  35% water.  Chromato-
graphic conditions for benomyl analysis are  in Table 5.3.
   ?
     Since benomyl spontaneously  converts to  Carbendazim in  the
environment, it is the latter compound that is found in all per-
sonal and environmental samples,  if present at all.  Benomyl has
a substantially longer retention  time than  does Carbendazim  under
the chromatographic conditions describe above, and it is desir-
   s
able to convert the Carbendazim back to benomyl in order to
better separate the analyte  of interest from interferences.  This
was accomplished by the addition  of 20 microliters of butyl
isocyanate to each sample as  it was  prepared  in its autosampler
vial.   This treatment assured a large,  stable benomyl peak,  in

                                                              '     31
-------
                                             Section  5            en-?
                                             October 15, 1985      ~>U/
                                             Page 8  of  18
standards,  spiked blanks and samples, alike.

                            TABLE 5.3
                   Chromatographic Parameters
                             for the
                       Analysis of Benomyl
          Column              25 cm X 2.0 mm C18 pBondapak with
                              a Ci8  Guard-PAK precolumn
          Mobile Phase        65% Acetonitrile, 35% Water
          Flow Rate           2.0 ml/min.
          Detector            Wavelength:  292 run
          Parameters          Sensitivity:  0.02 ADFS
          Integration         Peak Width:  30
          Parameters          Noise Rejection:  3.0
                              Chart Speed  0.5 cm/min
                              Run Time:   10 min
5.5 Crew Characteristics
   \  Nearly thirty  volunteers  were recruited  from  among the  work
force of more  than  80 which was found already working at the
site.   Twenty-two subjects completed enough of the study to be
included in the  data set;  although,  only sixteen lasted through
the entire study.   The  physical characteristics of the partici-
pants in the blackberry study  are contained in Table 5.4.  As  can
be seen, five  (22.7%) of the volunteers  were  ten years old or
below, and another  five were between ten and fifteen.  Of the
twelve people  in Group  A (wearing gloves and patches), there were
three (25%) who  were ten or less, while  two  (16.7%)  were between
ten and fifteen.
                                                                   32
-------
                                                               Section 5
                                                               October 15, 1985
                                                               Page  9  of 18
                                                                         508
                                      Table 5.4
ABSTAT 3.00
BLACKBERRY STUDY, PERSONAL CHARACTERISTICS OP THE CREW
                                                                        FILE: 8302-1      ftEVI 4
COMMAND* PRINT DATA
VARIABLES*
CASE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
21
22
1 SUBJECT
1.00000
2.00000
3.00000
4.00000
5.00000
6.00000
7.00000
8.00000
9.00000
10.0000
11.0000
12.0000
13.0000
14.0000
15.0000
16.0000
21.0000
22.0000
23.0000
24.0000
28.0000
29.0000
2 GROUP
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
3 SEX
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
1.00000
1.00000
2.00000
2.00000
2.00000
1.00000
2.00000
1.00000
2.00000
4 AGE
37.0000
31.0000
49.0000
25.0000
10.0000
7.00000
11.0000
9.00000
21.0000
39.0000
19.0000
15.0000
11.0000
8.00000
33.0000
30.0000
45.0000
11.0000
42.0000
28.0000
12.0000
10.0000
5 HGBTKG
113.400
68.0000
93.4000
56.2000
22.7000
20.4000
31.8000
34.0000
68.9000
57.2000
117.900
94.8000
36.3000
31.3000
99.8000
73.0000
68.0000
49.0000
56.7000
59.0000
68.0000
58.1000
6 BEIGHTCM
180.003
190.000
170.000
168.000
128.000
118.000
140.000
143.000
170.000
153.000
162.000
154.000
141.000
129.000
175.000
173.000
170.000
157.000
187.000
162.000
154.000
159.000
7 AREAM2
2.35000
1.85000
2.05000
1.60000
0.900000
0.800000
1.20000
1.20000
1.80000
1.55000
2.30000
2.00000
1.20000
1.05000
2.20000
1.85000
1.75000
1.45000
1.70000
1.60000
1.70000
1.60000
                                                                                       33
-------
                                             Section  5            rrn«
                                             October 15, 1985      JU9
                                             Page 10 of  18
5.6 Results
     All of the dermal patch data was below the limit of detec-
tion for benomyl.  Foliar residues and amounts of benomyl in the
gloves of the workers were, however,  sufficient  to guantitate.
Foliar residues were collected on days 17, 19 and 20 post appli-
cation.  Figure 5.1 is a scatter-plot of these residue values
versus day post-application.   The corresponding regression ana-
lysis, Table 5.5, results in an F value of 4.21 which indicates
that the regression is significant at the 90% level.
     Dsing the regression equation to estimate the decay curve
for all five days allows an investigation of  the  relation between
hand exposure,  as measured by the glove residues, and the residue
on the foliage.   Figure 5.2 shows  a  scatter-plot  of  the  daily
exposure rate,  averaged across the entire crew, and  the  estimated
residue level for that day.   Table 5.6 shows  the  result  of  the
corresponding regression which is significant at above the 95%
level.
     Table 5.7 contains  the glove  exposure rate,  in  mg/hr,  by day
and individual  worker.   The average  exposure  rate was calculated
                                              •
for each worker.  These values are  also  given in Table  5.7.
Figure 5.3 is a  scatter-plot of the  average individual  glove
exposure rate vs.  age which suggests that the hand exposure rate
is less for  young workers than for adults.  Taking age twelve as
the dividing line between children and adults,  for present  pur-
poses,  a Mann-Whitney U test  was  performed to test the  hypothesis
that the distribution  of hand  exposures was the same for children

                                                                    34
-------
                                              Section   5
                                              October 15,  1985
                                              Page 11 of   18            510
and  adults  against  the  alternate  hypothesis that the exposure  of
the  children was less.  The 0 value was calculated to  be  5 which,
for  4 children and 8 adults,  would be observed with probability
0.036 under BQ<  Hence, we conclude that the  children  do  have  a
lower  average  hand  exposure than  the  adults.  In contrast to the
blueberry study,  the absence of yield data makes it impossible to
verify that differences in workrate account for this difference
in exposure, but it seems highly  likely that  this is the  case.
     As was done in the case of blueberries,  the average glove
exposure for each individual was  normalized by body weight,
resulting in a exposure rate expressed in mg/kg/hr.   This value
was  regressed  against age with the corresponding scatter-plot
shown as Figure  5.4.  The value of the F  statistic was 0.355  with
the  corresponding r2 equal to 0.0034,  indicating an  essentially
random relation  between these variables.  Hence, as  in the blue-
berry study, adults have a higher total exposure than children?
but,  on a mg/kg/hr basis, there is no evidence of differences in
exposure as a function of age.
                                                                   35
-------
                                                                   Section  5
                                                                   October  15, 1985
                                                                   Page 12  of 18
                                       Figure  5.1


                    BLACKBERRY  STUDY, RESIDOE DECAY (NG/CM2)  VS  DPA
                                                                              PILE: PDNCH2
XBSTAT 3.00

COMMAND: PLOT

HISSING VALUE TREATMENT: LXSTVISE

             15.0000      16.6667      18.3333      20.0000      21.6667      23.3333       25.0000
                    15.8333      17.5000      19.1667      20.8333      22.5000      24.1667

       500.000  *
       497.917  +
       495.833  +
       493.750  +
       491.667  +
       489.583  +
       487.500
       485.417
       483.333
       481.250
       479.167
       477.083
                                 1
                                                                                        REVI12
I
G
C
H
2
                +
                •f
475.000
472.917
470.833
468.750
466.666
464.583
462.500
460.416
458.333
456.250
454.166
452.083
450.000
447.916
445.833
443.750
441.666
439.583
437.500
435.416
433.333
431.250
429.166
427.083
425.000
422.916
420.833
418.750
416.666
414.583
412.500
410.416
408.333
406.250
404.166
402.083
400.000
             15.0000      16.6667      18.3333       20.0000      21.6667       23.3333       25.0000
                    15.8333      17.5000      19.1667      20.8333      22.5000      24.1667


                                      1 DPA
                                                                                            36
-------
                                 Table 5.5


ABSTAT 3.00          BLACKBERRY STUDY, RESIDUE DECAY  (NG/CM2) VS DPA

COMMAND: REGR

MISSING VALUE TREATMENT: LISTWISE

                    *** MULTIPLE LINEAR REGRESSION  ***

DEPENDENT VARIABLE:  4 NGCM2                  6 VALID CASES
                                                                               FILE:  PUNCB2
COEFP OF DETERMINATION:    0.513016
MULTIPLE CORR COEFF:       0.716252
                                       ESTIMATED CONSTANT TERM:        741.793
                                       STANDARD ERROR OF ESTIMATE:     22.8753
ANALYSIS OF VARIANCE FOR THE REGRESSION:
                      DEGREES OF      SUM OF
SOURCE OF VARIANCE     FREEDOM       SQUARES
      REGRESSION
      RESIDUALS
      TOTAL
                                                 MEAN OF
                                                 SQUARES
                                                 2205.00
                                                 523.277
VARIABLE
 1 DPA

DURBIN-WATSON
                REGRESSION
               COEFFICIENT
                  -15.3704

                   2.71818
1         2205.00
4         2093.11
5         4298.11
                 CORRELATION
   STANDARDIZED      WITH
    COEFFICIENT    DEPENDENT
      -0.716251    -0.716251
 F TEST
4.21383
                                                                                 -O O
                                                                                 U3 c* O
                                                                                 fl> O r*
                                                                                   «T -••
                                                                                 —• n> o
                                                                                 <*> -I 3
                                                                                 o —• in
                                                                                   to
                                                                                   oo
                                                                                   en
                                                                                        U1
-------
                                                                    Section 5                     tr i
                                                                    October 15,  1985             ^ '
                                                                    Page 14 of 18
                                        Figure 5.2
ABSTAT 3.00   BLACKBERRY STUDY, AVERAGE EXPOSURE RATE VS ESTIMATED RESIDOE5    FILEi  PUNCH 3      REVI16

COMMAND: PLOT

HISSING VALUE TREATMENT! LISTWISE

             400.000      416.667      433.333      450.000      466.667      483.333      500.000
                   408.333      425.000      441.667     458.333      475.000      491.667

















0
7


A
V
E
I
P
0
s





















0.300000
0.295833
0.291667
0.287500
0.283333
0.279167
0.275000
0.270833
0.266666
0.262500
0.258333
0.254166
0.250000
0.245833
0.241666
0.237500
0.233333
0.229166
0.225000
0.220833
0.216666
0.212500
0.208333
0.204166
0.200000
0.195833
0.191666
0.187500
0.183333
0.179166
0.174999
0.170833
0.166666
0.162499
0.158333
0.154166
0.149999
0.145833
0.141666
0.137499
0.133333
0.129166
0.124999
0.120833
0.116666
0.112499
0.108333
0.104166
l.OOOOOE-01
*
+
+
+
+
+
+
•f
•+
+
+
+
+
+
+
+
4
+
+
•»•
+
4
+
+
+
+
•f
+
+
+
•f
+
•f
+
+
+
+
+
+
+
+
4.
+
+
+
+
4.
•f
4
             400.000      416.667      433.333      450.000      466.667      463.333      500.000
                   408.333      425.000      441.667     458.333      475.000      491.667
                                     6 EST
                                                                                         38
-------
                                     Table 5.6

ABSTAT 3.00   BLACKBERRY STUDY, AVERAGE EXPOSURE RATE VS ESTIMATED RESIDUES

COMMAND: REGR

MISSING VALUE TREATMENT: LISTWISE

                    *** MULTIPLE LINEAR REGRESSION ***

DEPENDENT VARIABLE:  7 AVEXPOS                5 VALID CASES
                                                                FILE: PUNCH3
COEFF OF DETERMINATION:   0.776790
MULTIPLE CORR COEFF:      0.881357
                        ESTIMATED CONSTANT TERM:
                        STANDARD ERROR OF ESTIMATE:
      -0.839192
      3.423E-02
ANALYSIS OF VARIANCE FOR THE REGRESSION:
                      DEGREES OF     SUM OF
SOURCE OF VARIANCE     FREEDOM      SQUARES
      REGRESSION
      RESIDUALS
      TOTAL
                                  MEAN OF
                                  SQUARES
                                1.223E-02
                                1.171E-03
VARIABLE
 6 EST

DURBIN-WATSON
 REGRESSION
COEFFICIENT
  2.285E-03

    1.33459
1       1.223E-02
3       3.515E-03
4       1.574E-02
                 CORRELATION
   STANDARDIZED      WITH
    COEFFICIENT    DEPENDENT
       0.881357     0.881357
 F TEST
10.4403
                      "O O l/»
                      o> o n
                      10 r* O
                      (D O it
                        cr -••
                      —•mo
                      on 3
                      O —'01
                      -n 01
                                                                                     Co —•
                                                                                      vo
                                                                                      CO
                                                                                      01
                                                                                         c_n
-------
                                          Table 5.7
ABSTAT 3.00
BLACKBERRY STUDY,  GLOVE EXPOSURE DATA, ALL DAYS
                                                                              FILEi  CtB302-P    REVC12
COHHANDi PRINT DATA
HISSING VALUE TREATMENTi INCLUDE
VARIABLES i
CASE
1
2
3
4
5
6
7
8
9
10
11
12


1 SUBJECT
1.00000
2.00000
3.00000
4.00000
5.00000
6.00000
7.00000
8.00000
9.00000
10.0000
11.0000
12.0000



0
0
0
0
0
0
0
7 GL1
.549846
.342769
.223716
.198595
.161276
.245500
.120154
8.4S896E-02
9.240S3B-02
0.604182
0.251091
0.139273




8 GL2
0.469895
0.230706
0.382164
0.214153
0.232982
0.258432
0.161390
0.210842
0.163817
0.432267
0.255733
0.139733


9 GL3
0.342956
0.261391
0.244348
0.130957
6.92174E-02
0.128522
9.79131E-02
6.50435E-02
9.65000E-02
0.207500
8.45000E-02
8.85000E-02


10 GL4
0.139692
0.203692
0.162000
0.143077
0.129231
0.167692
9.92308B-02
7.75385E-02
HISSING
HISSING
HISSING
HISSING


11 GL5 12 AVGLRATB
0.113778
0.231556
0.179755
0.120444
0.109778
0.183778
7.93334E-02
7.95556E-02
HISSING
HISSING
HISSING
HISSING


0.323233
0.254023
0.238396
0.161445
0.140497
0.196785
0.111604
0.103514
0.117574
0.414649
0.197108
0.122502


2
3
2
2
6
9
3
3
1
7
1
1


13 WGLRATB
.85038E-03
.73563B-03
.55242E-03
.87269E-03
.18929E-03
.64631E-03
.50957E-03
.04452E-03
.70644E-03
.24912E-03
.67182E-03
.29221E-03











•o O  O fD
(O r* O
n o rt-
a- -••
— i a> o
Oh 1 3
o — • in
-h in
00 —•
00
en
-------
                                                                      Section  5
                                                                      October  15, 1985
                                                                      Page 17  of 18
                                                                                                  516
                                           Figure 5.3
 ABSTAT 3.00      BLACKBERRY STUDY, AVERAGE EXPOSURE RATE  (MG/HR) VS AGE       FILE: Cz8302-P    REVI12

 COMMAND:  PLOT

 HISSING VALUE TREATMENT: LISTKISE

               4.00000      12.0000      20.0000      28.0000      36.0000      44.0000      52.0000
                     8.00000      16.0000     24.0000      32.0000      40.0000      48.0000

        0.440000  4
        0.432500  4
        0.425000  4
        0.417500  4
        0.410000  -I-                                                        1
        0.402500  4
        0.395000  +
        0.387500  4
        0.380000  4
        0.372500  4
        0.365000  4
        0.357500  4
        0.350000  4
        0.342500  4
        0.335000  4
        0.327500  4
        0.320000  4                                                     1
 1       0.312500  4
 2       0.305000  4
        0.297500  4
        0.290000  4
 A       0.282499  4
 V       0.274999  4
 G       0.267499  4
 L       0.259999  4
JL       0.252499  4                                           1
 A       0.244999  4
 T       0.237499  4                                                                       1
 E       0.229999  4
        0.222499  4
        0.214999  4
        0.207499  4
        0.199999  4
        0.192499  41                  1
        0.184999  4
        0.177499  4
        0.169999  4
        0.162499  4
        0.1S4999  4                                 1
        0.147499  4
        0.139999  4          1
        0.132499  4
        0.124999  4
        0.117499  4                  11
        0.109999  4           1
        0.102499  4        1
    9.49993E-02  4
    8.74993E-02  4
    8.00000E-02  4

               4.00000      12.0000      20.0000      28.0000      36.0000      44.0000      52.0000
                     8.00000      16.0000     24.0000      32.0000      40.0000      48.0000


                                       3  AGE
-------
                                                                                             517
                                                                   Section  5
                                                                   October  15, 1985
                                                                   Page  18  of 18
                                      Figure 5.4
llBSTAT 3.00   BLACKBERRY STUDY, AVERAGE EXPOS. NORMALIZED FOR WIEGBT VS ACE    FILEt C:8302-P   REVI12

BMARDi PLOT

IISSING VALUE TREATMENT: LISTWISE

            4.00000      12.0000      20.0000      26.0000      36.0000     44.0000      52.0000
                   8.00000     16.0000      24.0000      32.0000      40.0000      48.0000












I
J


II
5
L
K
It
I
E





















l.OOOOOE-02
9.81249E-03
9.62499E-03
9.43749E-03
9.24999E-03
9.06249E-03
8.87499E-03
8.68749E-03
8.49999E-03
6.31249E-03
8.12499E-03
7.93749E-03
7.74999E-03
7.56249E-03
7.37499E-03
7.18749E-03
C.99999E-03
C.81249E-03
6.62499E-03
6.43749E-03
6.24999E-03
6.06249E-03
5.87499E-03
S.68749E-03
S.49999E-03
S.31249E-03
5.12499E-03
4.93749E-03
4.74999E-03
4.56249E-03
4.37499E-03
4.18749E-03
3.99999E-03
3.81248E-03
3.62498E-03
3.43748E-03
3.24998E-03
3.06248E-03
2.87498E-03
2.68748E-03
2.49998E-03
2.31248E-03
2.12498E-03
1.93748E-03
1.74998E-03
1.56248E-03
1.37498E-03
1.18748E-03
l.OOOOOE-03
4
*
+
+
+
•«•
+
•*•
+
4
+
+
^
•f
4-
+
4.
4.
•f
+
4
4
4
4
4
4
4
4
4
4-
4
4
4.
4
4
4
4
4
4
4
4.
4
4
4
4

                                                   _ _+ ______ + _____ + ______ + _____ + ______ + _____ +

              00000    *"l27oOOO     20.0000      28.0000      36.0000      44.0000      52.0000
                   8.00000      16.0000      24.0000     32.0000      40.0000     48.0000
                                     3 ACE
                                                                                         42
-------
                                             Section  6
                                             October 15, 1985
                                             Page 1  of  17
       6.  HARVESTER EXPOSURES TO BENLATE IN RASPBERRIES

6.1 Introduction
     In a continuing effort to develop experimental data on the
exposure to pesticides of fruit harvesters of different ages,  a
st.udy was conducted involving the exposure of raspberry harves-
ters to residues of the pesticide Benlate (benomyl).   The volun-
teers for this study were divided into two groups,  one provided
with cotton gloves and dermal patches to measure dermal exposures
and the other not so provided so that there would be no unnatural
barrier to their exposure.   Urine samples were collected from  all
subjects to be analyzed for metabolites of the pesticide.
     The purpose of the study was two-fold.   The primary intent
was to measure the worker's dermal  exposures  and determine wheth-
er a significant difference exists  between the exposures experi-
enced by children and adults. Second, an attempt was  to be made
to correlate dermal exposure to  benlate  as  determined  by patch
and glove monitors with that determined by the concentration of
the metabolite of the pesticide  excreted in the urine  of the
exposed workers;  An additional, but secondary goal, was to
contrast the absorption of the pesticide, as  measured  by the
urinary metabolite concentration, between the group wearing
gloves with that not so protected with the  object of determining
the degree of protection afforded.
                                                                43
-------
                                             Section   6            5 1 Q
                                             October 15, 1985
                                             Page 2  of  17
6.2 Site and Experimental Design
     The site chosen for an exposure study among raspberry har-
vesters was a 50 acre plot of the Canby variety located on a
berry farm in Troutdale, Oregon. It was  late in the season for
this variety, and the plot had  been  picked over  at least one time
prior to the commencement of the study.  This field had been
treated with very few insecticides,  herbicides or fungicides; but
the spray history up to the study date, such  as  it was, is
delineated in Table 6.1.  The most recent  treatment had been with
Lannate on the first and second of June,  some 40 days prior to
our crew's entry.   Even  though  it was 60  days post application,
the benomyl treatment was chosen as the one to use in the moni-
toring study, since no readily  detectable  urinary metabolites
could be expected from Lannate.  However,  we  did know some of the
pertinent metabolic information regarding benomyl.
                            TABLE 6.1

                      1983 Spray Schedule*
                      Canby Raspberry Plot
Date
25 February
5-7 April
15-18 Hay
1-2 June
Product
Orthrex (sic)
Karmex (diuron)
Paraquat
Benlate
Lannate
Application Rate
3 gal/A
1.6 Ib/A
1 qt/A
2 Ib/A
25 gal/A



(sic)
  This table  does  not  contain  all  of  the 1983 spray history, but
terminates at the  time of the study.
                                                                    44
-------
                                             Section   6            con
                                             October 15, 1985      ^u
                                             Page  3  of  17
     The study lasted for four days,  running  from  Monday, 11 July
1983 through Thursday, 14 July 1983.  On-site weather  observa-
tions for the study site covering 11  through  14 July are found in
Table 6.2.   This particular  study was plagued with frequent
rains, cutting the workdays short and keeping the  foliage, the
subjects, and the glove and patch monitors wet much of the time.
Table 6.2 also includes  information about the crew in  addition to
weather data.  For a number of reasons, individual times for
entry to and exit from the field were not recorded, obviating the
assignment of individual exposure times.  This arose,  in large
part, due to the fact that  as part of a school bus operation this
group arrived at the field  all at one time, and the PBAP staff
was obliged to conduct its  business  (collection of forms, taking
down; personal information,  applying patch monitors and gloves,
etc.) to  all  the  subjects at once and in as  small  a time span as
possible; therefore, movement into and  out  of the  field was taken
for the group, altogether.
     On Thursday, July 14th,  the Canby plot had been completely
harvested out soon after the crew began working in it; so the
entire operation was moved to a plot  adjacent to the Canbies that
happened to be the Meriam variety.  This plot was made up of
considerably older plants than the Canbies  and had considerably
less foliage.  Less  foliage  resulted  in lowering the potential
for the workers to contact  and pick up  residues.   In addition, it
was impossible to determine whether this particular plot had
received the same pesticide regimen as  the  Canby plot.
                                                                    45
-------
                                                     Section   6         521
                                                     October  15,  1985
                                                     Page 4   of   17
                                   TABLE 6.2
                        Weather and General Observations
                               of Conditions in the
                               Canby Raspberry Plot

   Date     Time     Dry Bulb   Wet Bulb   % RH       Description of Weather
	(PC.)	(PC.)	and Other Observations
11 July     0630                                  Rain the night before, heavy
                                                  dew on leaves.  School bus
                                                  arrived, collected evening
                                                  (pre-exposure) urines.
            0730                                  Completed patching Group A.
            0735        15.3        14.2     91    Sunny and
                                                  clear, light wind.
            0855                                  Dew beginning to dry.  Workers'
                                                  shirts are wet from dew.
            1200                                   Crew left field.
        r
12 July     0640                                   Crew arrived. Sunny with
                                                  spotty clouds. Heavy dew.
            0655                                   Group A completely patched.
            0915        18.9
            0945                                   Heavy Clouds have moved in.
                                                  Worker 11 arrived.
            1000                                   Drizzle begun.
         1010-1015                                Crew leaves field for 1/2 hour
   v                                              lunch.  Gloves are very wet;
                                                  Lower legs dry; Lower arms wet.
            1250                                   Crew leaves field.
Table 6.2 continued on Page 5.
-------
                                                                  522
                                             Section  6
                                             October 15,  1985
                                             Page 5  of  17
 TABLE 6.2
Weather and General Observations of Conditions in the Canty Raspberry Plot oont.
Date Time
13 July 0640
0947
1020
14 July 0630
0700
0800
0845
1000

r
1115
1130

Dry Bulb Wet Bulb t PS Description of Weather
(°C.) (°C.) and Other Observations
Crew into field. Drizzle.
18.6
Drizzle turns to heavy rain;
crew leaves field for the day.
Crew into field.
Worker 21 arrived.
Canty plot picked out; Crew
moved to an adjacent plot,
Heriaro variety.
15.0 10.0 53 Good weather, no clouds.
Crew leaves field for 1/2 hour
lunch.

18.1 14.7 72 No clouds.
Meriams picked out; crew leaves
and will not return Friday.
     Consent forms approved by the Committee for the  Protection
of Human Subjects at the University of California at  Berkeley
(see Appendix D)  were distributed  to each participant along with
detailed instructions for their particular  subgroup (Appendix D).
In order for anyone to be allowed to join the Study, they were
required to return their consent form signed; and if they were
minors, as was this entire crew, their form had to be signed by
their parents, as well.  Each  participant was paid  a  bonus of
$20.00 for the completion of the study if all urine samples were
-------
                                             Section  6
                                             October 15,  1985
                                             Page 6  of  17
collected as instructed.   This  was done,  not  as  an inducement to
participate, but to offset the  inconvenience  and potential aggra-
vation of providing total urine collection for up to 72 hours.
     As with the blueberry study  (See Section 4.2),  the volun-
teers were divided into two subgroups.  The first,  Group  A,  was            M
assigned to wear patch monitors and gloves, while the second were
to have no unusual  impediments  to exposure, which the gloves
night constitute.  Thus,  Group  B wore neither gloves nor  patches
at any time during the study.   All subjects were instructed to
collect a urine specimen  before they entered  the field on Monday
to serve as a pre-exposure control.   On Monday Group A was pro-
vided light-weight cotton gloves to be worn throughout the work-
day while picking berries.  During the lunch  break the gloves
were removed and new gloves issued after  the  break.   Also,  new
gloves were provided if a pair  became too soiled or  wet.  How-
ever, adhering  to this  policy was difficult in this  particular
study,  because  of the heavy moisture on the foliage  due to the
great deal of dew,  drizzle and  rain experienced  during the week
of 11 to 14 July.
     On Tuesday Group A was outfitted with cotton gauze-patch
monitors, in addition to  the cotton gloves, to   measure total
dermal exposure.  Details  of the  placement and handling of the
patches and gloves  are  contained in Appendix  A.   The initial
distribution of subjects  between the two  groups  was sufficiently
imbalanced (14  to 10) that one  person (Subject 13) was  moved from
Group A to Group B on Tuesday.   Table 6.3  does not reflect this
                                                                         48
-------
                                            Section  6
                                            October 15, 1985
                                            Page 7  of  17
 shift of one subject from one group to another,  but  simply shows
 Subject 13 as part  of Group 2 or B.
     The collection of urine  specimens was scheduled to begin on
 Wednesday when it was assumed excretion would have reached some-
 thing near  steady state.  Starting Tuesday after work all sub-
 jects were  provided with 1-liter plastic specimen bottles and
 instructed  to collect their urine for  the remainder of the 72
 hours of the study in the following regimen:  Might  samples to go
 from the termination of work to through the next morning's void;
 day samples from that point through the termination of work.
     The owners of the raspberry farm  had both a drive-up work
   ;
 force and a school bus operation.  The former is much the same as
 was described for the Marion  blackberry field,  where just about
 anyone who wished to do so could come and pick.  These people
 were kept segregated from the monitoring study and did not work
 in the same plot with our crew at any time.
     The school  bus  crew  was designated to work  with the monitor-
 ing study and was constituted the same as the crews  that had
 worked with this organization in strawberries in Corvallis,  Ore-
 gon,  during 1981  and 1982.  The  grower  contracts with a  Crew Boss
 for a crew.  The  Crew Boss recruits a school bus driver  who
 contracts with the school district to  rent one of  the district's
busses for the summer.  A crew of thirty to forty children is
 recruited from the local  school(s)  (with parental consent,  and/or
urging).  On work days the Crew Boss and Driver  go to  each
 child's house and picks them up  before  work  and returns  them home
-------
                                             Section  6
                                             October 15, 1985       525
                                             Page 8  of  17
 after work.   In  the  field,  the  harvesters are paid piece rate,
 and the  Crew Boss is credited for the produce harvested.
 6.3 Sample Storage Handling and Preparation
     Drine samples were stored on ice for no more than 4-6 hours
 and transported to the laboratory the same day as they were
 received from the subjects.  Individual urine sample volumes were
i
 measured and duplicate 20 mL aliguots were pipetted into glass
 ampules  to which 1.5  mL  of  concentrated hydrochloric acid was
 added as a preservative  (resulting in a final pB of less than
 0.5).   The ampules were  sealed and stored at room temperature.
   •  Gloves  and patches were collected from participants by pro-
 ject personnel and stored in  zip-loc  plastic bags.  (See section
 6.7 of the QA Plan for sample preservation  procedures.)
 6.4 Analytical Procedures
     Extraction of samples was as detailed in Section 9 of the
 Quality  Assurance Plan.  A description of the chromatographic
 analysis of  benomyl  is contained  in Section 5.4, including a
 listing  of the chromatographic  conditions in Table  5.3.

 6.5 Crew Characteristics
     This group,  because of  the  fact that it was a school bus
 operation, was made up almost exclusively of youngsters;  only two
 individuals were older than 16 years, and they were friends or
 related to the Crew Boss.  Table 6.3 shows the  physical  charac-
 teristics of  the entire crew of volunteers for  the monitoring
                                                                 .-»•
                                                                       50
-------
                                             Section  6               526
                                             October 15, 1985
                                             Page 9  of  17
 study which consisted of 24 individuals,  of which 13 were
 assigned to Group A (wearing glove and patch monitors) while 11
 made up Group B.
      Taking the crew as a whole,  the ages distributed as follows:
 Ten years or less, 1 (4%); 11 and 12 years, 6 (25%); 13 - 15
 years, 12 (50%); and 16 years and older, 5 (21%).  They were
Ndivided evenly between the sexes, and ranged in weight from 31 to
 86 kg with the bulk  (54%) falling into the 40 - 60 kg range.
      The group wearing patches  (Group A),  numbering 13, ranged in
 age from 9 to 16 and were distributed thus:  Ten years or less, 1
 (8%); 11 and 12 years, 4 (31%); 13 - 15 years, 5 (38%); and 16
 years, 3 (23%).  This subgroup was made up of seven  males and six
 females.  Weights ranged from 32 to 77 kg, again with the great-
 est number of subjects (69%) falling into the 40 to 60 kg range.
 6.6 Results
      Because this field had been treated with benomyl 60 days
 prior to entry,  the  foliar residues  were much lower  than was the
 case in the blackberry study.  As in that  case,  all  of the  dermal
 patch data was below the limit of detection fof  benomyl.   The
 foliar residue data  is shown in Table 6.4.   No clear time trend
 would be expected in this case since  the sampling  interval  was
 over only two days and sampling variability is high  when residue
 levels are very low.   Hence, the residue environment is best
 characterized by the  mean of all sample values which was
 175 ng cm~^»
                                                                      51
-------
                 ABSTAT 3.00
                                         RASPBERRY STUDY, PERSONAL DATA ON THE CREW
FILEI 0301-1
                                                                                                                  REVt 4
                 COMMANDI PRINT DATA
Ln
VARIABLESi
CASE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1 SUBJECT
1.00000
2.00000
3.00000
4.00000
6.00000
7.00000
12.0000
15.0000
16.0000
17.0000
18.0000
19.0000
20.0000
5.00000
8.00000
9.00000
10.0000
11.0000
13.0000
14.0000
21.0000
22.0000
23.0000
24.0000
2 GROUP
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
3 SEX
1.00000
2.00000
1.00000
1.00000
1.00000
2.00000
1.00000
2.00000
1.00000
1.00000
2.00000
2.00000
2.00000
1.00000
2.00000
2.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
1.00000
1.00000
4 AGE
12.0000
9.00000
IS. 0000
15.0000
16.0000
13.0000
13.0000
16.0000
16.0000
15.0000
12.0000
12.0000
12.0000
15.0000
15.0000
13.0000
14.0000
14.0000
11.0000
14.0000
12.0000
28.0000
19.0000
13.0000
5 MGHTKG
43.1000
31.8000
77.1000
61.2000
77.1000
58.1000
44.0000
52.2000
56.7000
59.0000
48.5000
51.3000
54.0000
45.4000
61.7000
63.5000
43.1000
81.6000
35.4000
49.0000
36.3000
86.2000
77.1000
52.6000
6 HEIOHTCM
142.000
135.000
176.000
175.000
175.000
162.000
157.000
157.000
170.000
173.000
160.000
170.000
165.000
168.000
150.000
160.000
152.000
183.000
141.000
156.000
152.000
162.000
180.000
164.000
7 ARBAM2
1.30000
1.10000
1.90000
1.70000
1.90000
1.60000
1.40000
1 .50000
1.60000
1.65000
1.50000
1.55000
1.55000
1.50000
1.60000
1.65000
1.35000
2.00000
1.20000
1.45000
1.25000
1.95000
1.90000
1.55000















ti O 
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aa «-•• o
n> o r+
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-h en
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en
ro
-------
                                             Section  6
                                             October 15, 1985
                                             Page 11 of  17
528
                            TABLE 6.4
                       Foliar Residue Data
                         Raspberry Study
Sample
Number
8301-P-61.1
. 8301-P-61.2
8301-P-62.1
8301-P-62.2
Total
Micrograms
66.6
45.1
43.0
68.8
Number of
Leaf Disks*
43
43
47
48
Average
s
% RSD
Residue
ng/cm2**
219
148
129
203
175
43
25
* 3.0 cm diameter.
** Single side basis.
     As in the blackberry study, the measure of exposure is the
residue found in the gloves.  Table 6.5  contains  the  glove expo-
sure rate, in pg/hr, by day and individual worker.  The average
glove exposure rate was calculated for each worker for the entire
course of the study. These values are also  shown in  Table 6.5.
Figure 6.1  is a  scatterplot  of  this  average exposure  rate vs age,
which is mildly suggestive of the same positive correlation
between exposure and age which was seen in both the blackberry
and blueberry studies.   The regression results are given in Table
6.6  and  indicate an F value  on  the verge  of  significance,  but a
very low r2 value  of 0.27.
     As  in the blueberry and blackberry studies,  even this weak
correlation between exposure and age disappears if the exposure
measure is normalized by the body weight of the individual
-------
                                            Section  6
                                            October 15f 19B5
                                            Page 12 of  17
worker.   Figure 6.2 shows the scatterplot of exposure in
ng/kg/hr, versus  age.  As expected, the F value  declines to  0.40
with an  r2  of  0.17 as shown  in Table  6.7.  Note  that these
exposure  values are given in micrograms rather than in milligrams
as in the previous studies.  Therefore, despite the very low
foliar residues and the adverse weather conditions encountered in
this study, the conclusion is the same:  Older workers tend to be
exposed to  a greater total residue than younger workers, but when
exposure is measured on a mg/kg basis, there is no evidence of an
age-related difference  in  exposure.
                                                                       54
-------
                                                          Table  6.5
                 ABSTAT 3.00
                                       RASPBERRY STUDY,  GLOVE EXPOSURE DATA, ALL DAYS
riLEs 8301-P     REVI22
                 COMMANDi PRINT DATA
                 MISSING VALUE TREATMENTi INCLUDE
VARIABLESi
CASE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1 SUBJECT
1.00000
2.00000
3.00000
4.00000
6.00000
7.00000
12.0000
13.0000
15.0000
16.0000
17.0000
18.0000
19.0000
20.0000
7 GL1
51.2000
27.2000
22.0000
112.200
83.0000
145.000
34.0000
53.8000
92.0000
72.4000
23.2000
37.8000
67.8000
38.6000
8 GL2
19.4445
7.11111
21.8519
30.7408
MISSING
22.0370
23.3333
MISSING
0.00000
0.00000
22.7778
14.0000
21.1111
HISSING
9 GL3
37.0270
20.3514
25.4324
33.5135
35.1351
14.0541
17.6487
HISSING
73.2433
79.1892
22.3243
25.3514
22.2703
47.2973
10 GL4
32.0000
35.5556
82.0000
22.8889
54.0000
28.4444
28.8889
MISSING
40.6667
32.8889
71.5556
26.4444
49.5556
36.6667
11 AVGLRATE
34.9179
22.5545
37.8211
49.8358
57.3784
52.3839
25.9677
53.8000
51.4775
46.1195
34.9644
25.8990
40.1842
40.8547
12 NGLRATE
0.810160
0.709262
0.490546
0.814310
0.744207
0.901616
0.590175
1.51977
0.986159
0.813395
0.592617
0.533999
0.783319
0.756568








"O O t/»
o> o rt>
«o n- o
m o n-
o- -••
— '(0 O
CO -I 3
O — •• (T>
-+i en
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10
00
en

en
-------
                                                                     Section  6
                                                                     October  15,  1985
                                                                     Page 14  of 17        531
                                          Figure 6.1


ISTAT 3.00         RASPBERRY STUDY, MEAN EXPOSURE RATE  (UU/HR)  VS AGE         PILE:  8301-P      REV«22

HWANDi PLOT

;SSIHG VALUE TREATMENT] LISTWISE

           • .00000      9.50000      11 .'0000      12.5000       14.0000       15.SOOO      17.0000
                  8.75000      10.2500      11.7500      13.2500     14.7500       16.2500

   .  SB.0000  4
     57.2500  *                                                                      1
     56.5000  4
     55.7500  *
     55.0000  4
     54.2500  4
     53.5000  *                          1
     52.7500  4
     52.0000  4                                            1
     51.2500  +                                                                      1
     50.5000  4
     49.7500  4                                                              1
     49.0000  4
     48.2500  4
     47.5000  4
     46.7500  4
     46.0000  4                                                                      1
     45.2500  4
     44.5000  4
     43.7500  4
     43.0000  4
     42.2500  4
     41.5000  4
     40.7500  4                                   1
     40.0000  4                                   1
     39.2500  4
     38.5000  4
     37.7500  4                                                              1
     37.0000  4
     36.2500  4
     35.5000  4
     34.7500  4                                   11
     34.0000  4
     33.2500  4
     32.5000  4
     31.7500  4
     31.0000  4
     30.2500  4
     29.5000  4
     28.7500  4
     28.0000  4
     27.2500  4
     26.5000  4
     25.7500  4                                   11
     25.0000  4
     24.2500  4
     23.5000  4
     22.7500  4
     22.0000  4         1

           8.00000      9.50000      11.0000      12.5000       14.0000       15.5000      17.0000
                  8.75000      10.2500      11.7500      13.2500     14.7500       16.2500
                                    3 AGE
                                                                                                56
-------
                               Table 6.6


ABSTAT 3.00              RASPBERRY  STUDY,  MEAN EXPOSURE RATE VS AGE


COMMAND: REGR

MISSING VALUE TREATMENT:  LISTWISE


                     ***  MULTIPLE LINEAR REGRESSION ***


DEPENDENT VARIABLE:  11 AVGLRATE               14 VALID CASES
COEFF OF DETERMINATION:    0.270291
MULTIPLE CORR COEFF:       0.519896
ANALYSIS OF VARIANCE  FOR THE  REGRESSION:
                      DEGREES OF      SUM  OF      MEAN OF
SOURCE OF VARIANCE      FREEDOM       SQUARES      SQUARES
      REGRESSION           1          447.116      447.116
      RESIDUALS          12          1207.08      100.590
      TOTAL              13          1654.20
                                            CORRELATION
                REGRESSION   STANDARDIZED      WITH
VARIABLE       COEFFICIENT   COEFFICIENT    DEPENDENT
 3 AGE             2.70261       0.519895     0.519895
                                               8301-P
ESTIMATED CONSTANT TERM:       4.91215
STANDARD ERROR OF ESTIMATE:    10.0295
                        F TEST
                       4.44492
                                                                                •o o v>
                                                                                0> O rt>
                                                                                »Q r* O
                                                                                rt> O rt-
                                                                                  O" -••
                                                                                —« CD O
                                                                                O1 -1 =>

                                                                                O —* 
-------
                                                                   Section 6
                                                                   October 15,  1985
                                                                   Page  16 of 17                 533
                                        Figure 6.2


ABSTAT 3.00   RASPBERRY STUDY, EXPOS. RATE NORM. FOR WGHT. (OG/KG/HR)  VS AGE   PILE.  8301-P      REVI22

COMMAND* PtOT

MISSING VALUE TREATMENTI LISTWISE

             8.00000      9.50000      11.0000      12.5000      14.0000      15.5000      17.0000
                    8.75000      10.2500      11.7500      13.2500      14.7500      1C.2500

       l.COOOO  4
       1.S7500  4
       1.55000  4
       1.52500  4
       1.50000  *                          1
       1.47500  4
       1.45000  4
       1.42500  *
       1.40000  4
       1.37500  4
       1.35000  4
       1.32500  4
       1.30000  4
       1.27500  4
       1.25000  4
       1.22500  4
       1.20000  4
1      1.17500  4
2      1.15000  4
       1.12500  4
       1.10000  4
W      1.07500  4
C      1.05000  4
I      1.02500  4
It     0.999998  4
A     0.974998  4                                                                    1
T     0.949998  4
B     0.924998  4
      0.899998  4                                           1
      0.874998  4
      0.849998  4
      0.824998  4
      0.799997  4                                   1                         11
      0.774997  4                                   1
      0.749997  4                                   1
      0.724997  4                                                                    1
      0.699997  4         1
      0.674997  4
      0.649997  4
      0.624997  4
    .  0.599997  4
    :  0.574997  4                                           11
      0.549997  4
      0.524997  4                                   1
      0.499997  4
      0.474997  4                                                             1
      0.449997  4
      0.4249*7  4
      0.400000  4

             8.00000      9.50000      11.0000      12.5000      14.0000      15.5000      17.0000
                    8.75000      10.2500      11.7500      13.2500      14.7500      16.2500
                                      3  AGE
                                                                                            58
-------
                                          Table 6.7

         ABSTAT  3.00    RASPBERRY STUDY,  EXPOS. RATE NORM.  FOR WGHT.  (UG/KG/HR)  VS AGE

         COMMANDS REGR

         MISSING VALUE  TREATMENT: LISTWISE

                              *** MULTIPLE LINEAR REGRESSION ***

         DEPENDENT  VARIABLE:  12 WGLRATE               14 VALID CASES
                                        FILE: 8301-P
         COEFP OF  DETERMINATION:   3.226E-02
         MULTIPLE  CORR COEFF:       0.179615
ESTIMATED CONSTANT TERM:       1.06819
STANDARD ERROR OF ESTIMATE:   0.258549
         ANALYSIS  OF VARIANCE FOR THE REGRESSION:
                                DEGREES OF     SUM OF      MEAN OF
         SOURCE  OF VARIANCE     FREEDOM      SQUARES      SQUARES
               REGRESSION          1       2.674E-02    2.674E-02
               RESIDUALS          12        0.802173    6.684E-02
               TOTAL              13        0.828915
                                                     CORRELATION
                          REGRESSION   STANDARDIZED      WITH
         VARIABLE        COEFFICIENT    COEFFICIENT    DEPENDENT
          3 AGE           -2.090E-02      -0.179615    -0.179615
                        F TEST
                      0.400043
                                                                                         "OO 
                                                                                         o» o n>
                                                                                         IO r+ O
                                                                                         fl> O «-»•
                                                                                           cr -*.
                                                                                         —•mo
                                                                                         -•4 -J 3
                                                                                         o —• o*
                                                                                         -•> 01
                                                                                           vo
                                                                                           00
                                                                                           in
LTI
-------
                                                     535
         APPENDIX A
QUALITY ASSURANCE PROJECT PLAN
                                                   60
-------
                                                          •w W I J I VII  I1U «
                                                         Date:   'November  10. 1982^
                                                         Page      1     "bT
                                                                        536
                  PESTICIDE EXPOSURE BY HARVESTERS
                   OF BUSHBERRIES, TRAILING-  AND
                             CANEBERRIES
                                by

                        John T.  Leffingwell
                          Hugh R.  McLean
                          Gunther  Zweig
                   Quality Assurance Project  Plan
                 Pesticide Hazard Assessment  Project
                       University of California
                        Berkeley, California
Approval:
Principal Investigator:	Date
Project QA Officer:	Date
EPA Project Officer:	Date_
EPA QA Officer:	Date
                                                                             61
-------
                                                                       re-
                                                      Section No.	2
                                                      Revision No.	0
                                                      Date:    November 10.  1982
                                                      Page    i     of    3
                      2.  TABLE OF CONTENTS

Section                                                       Page Reference
    1.  TITLE PAGE	   1 page
    2.  TABLE OF CONTENTS	
    3.  PROJECT DESCRIPTION	   2 pages
    4.  PROJECT ORGANIZATION	   2 pages
    5.  QUALITY ASSURANCE OBJECTIVES 	   3 pages
    6.  SAMPLING PROCEDURES                                      6 pages
        6.1  Dermal Exposure to Pesticides	   1 of 6
        6.2  Personal Aerosol Monitors   	   2 of 6
        6.3  Area Aerosol and Vapor Monitors	   2 of 6
        6.4  Foliar Samples	   2 of 6
        6.5  Soil Samples	   3 of 6
        6.6  Urine Samples	   4 of 6
        6.7  Sample Preservation	   5 of 6
        6.8  Forms, Notebooks,  Recordkeeping 	   6 of 6
    7.  SAMPLE CUSTODY                                           5 pages
        7.1  Field Sampling Operations 	   1 of 5
        7.2  Laboratory Operations	   4 of 5
    8.  CALIBRATION PROCEDURES  AND FREQUENCY                     4 pages
        8.1  Field Equipment	   1 of 4
        8.2  Laboratory Equipment	   2 of 4
    9.  SAMPLE PREPARATION                                       4 pages
        9.1  All Samples	   1 of 4
        9.2  Gauze Pads	   1 of 4
        9.3  Glove Samples	   1 of 4        62
-------
Section No.
538



Section
9 4 Aerosol Samples 	
9 5 Leaf Punch Samples 	
9 6 Soil Samples 	
9.7 Urine Analysis 	
10. DATA REDUCTION, VALIDATION AND REPORTING .
11. INTERNAL QUALITY CONTROL CHECKS 	
12. PERFORMANCE AUDITS 	
13. PREVENTIVE MAINTENANCE
13.1 Field Equipment 	
13.2 Laboratory Equipment 	
13.3 Spare Parts Inventory 	
14. SPECIFIC ROUTINE PROCEDURES USED TO ASSESS
PRECISION, ACCURACY AND COMPLETENESS
14.1 Field Sampling 	
14.2 Laboratory Analyses 	
14.3 Further Reduction 	
15. CORRECTIVE ACTION 	
16. QUALITY ASSURANCE REPORTS MANAGEMENTS . .
APPENDICES
A. Field Personnel Sampling Form 	
B. UCB Sample Identification Code 	
C. Laboratory Sample Log 	
D. Dermal Data Sheet 	
E. Monthly Laboratory Status Report 	
F. Study/ Investigation Monthly Status Report
G. Aerosol Data Form 	
Revision No. 0
Date: November 10, 1982
Page 2 of 3
Page Reference
	 1 of 4
	 2 of 4
	 2 of 4
	 3 of 4
	 5 pages
	 2 pages
	 1 page
2 pages
	 1 of 2
	 1 of 2
	 2 of 2
DATA -
2 pages
	 1 of 2
	 1 of 2
	 2 of 2
	 1 oaae
	 1 page
	 1 oaae
	 l nage


.... 1 oaae
	 1 page
	 1 cage
-------
Section
APPENDICES (Continued)
    H.  Leaf Punch Data Sheet .
    I.  Soil Sample Data Sheet
    J.  Crop Sample Data Sheet
    K.  Meteorology Data Sheet
                                                                        2
                                                                        0
Section No._
Revision No.."	
Da te:   	November 10, 19R2
Page	3     of   3
     Page Reference

        1 page
        1 page
        1 page
        1 page
53'
                                                                             64
-------
                                                                                    54(
                                                          Section No.	
                                                          Revision No.
                                                          Date: November 10, 1982
                                                          Page   1   of	2
                          3.  PROJECT DESCRIPTION
     The purposes of the proposed field studies to be conducted by the
California PHAP during the summer of 1983 are several fold:  1) The harvesting
activities of children in the cane-, bush- and trailing berry crops in all
likelihood presents a different pesticide exposure pattern to pesticides than
does strawberries because of substantial differences in the physical charac-
teristics between the former set of crops and strawberries.  Therefore, as an
extension of the "youth- in-agri culture" line of monitoring studies we will
attempt to determine the nature and extent of pesticide exposure suffered by
children or youths harvesting these crops.  This information will be compared
and contrasted with like information for corresponding groups of adults.
2) It is of considerable general interest to compare the excretion of pesticide
metabolites with whatever measures of dermal exposures that can be made on
workers.  Toward that end, two groups of subjects will be monitored in each
crop type.  One group will be monitored for dermal exposure to one or more
pesticides, while the other group will give urine samples for metabolite analy-
sis.  In each study both groups will engage in both activities so that they will
act as their own controls.  As usual cognizance will be taken of age, height,
weight and sex of the individual subjects in these studies.
     Since the pesticides under consideration are generally compounds with low
volatility (e.g., captan), exposures are expected to result from dermal contact;
consequently, this route of exposure will be given major emphasis in the con-
templated field studies.  Dermal dosimeters currently in use in this laboratory
consist of 12-ply, 3x3 inch surgical sponge (gauze pad) backed by a polythylene
                                                                                    65
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                                                                                  541
                                                          Section No.      3	
                                                          Revision No.     0
                                                          Date:  November 10,  1982
                                                          Page   2   of   2	
moisture shield enclosed in a paper envelope that has a circular face  opening
               2        2
to expose 28 cm  (4.3 in ) of the gauze pad.  This configuration allows for
rapid assembly of the dosimeter and easy attachment to carrier garments such
as T-shirts.  The potential for inhalation exposure will not be ignored,
however.  Both aerosol and vapor samplers will be placed in the field  for
general  monitoring.   At least two of the subjects will carry "breathing zone"
personal aerosol monitors.  These monitors will  be rotated among the subjects
at two hour.intervals.
     Since urine grab samples are of limited utility in interpreting metabolite
outputs, complete urine collections will be requested of the cooperating sub-
jects over the desired monitoring period.  These will be done in as close to
12 hour blocks ("day" and "night") as the subjects can manage.
     Environmental  samples will be comprised of foliar leaf discs (48  x 3 cm
diameter punches per sample), soil samples (6 scoops of 8 x 10  x 1 cm  deep
making in all  some 600-800 g of soil) representative crop samples and  area
aerosol  collections  which are backed up with charcoal tube vapor traps.  All
environmental  samples will be collected in the vicinity of the  workers  who are
being monitored.
     All samples will be placed on dry ice immediately after they have  been
collected.   At the completion of sample collection they will be transported on
dry ice  to the laboratory, transferred to a freezer and maintained at  -10°C or
colder until just prior to extraction.
                                                                                  66
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                                                          Section No.
                                                                                542
                                                                             o
                            Revision No.
                            Date:   November 10, 1982
                            Page   l
                                                                        of
                          4.   PROJECT ORGANIZATION
     The following chart shows the organizational  structure  for  developing and
implementing QA Project Plans within the Berkeley PHAP.   Acceptable  QA  procedures
will be developed in cooperation with, and under the supervision of, the OPP Quality
Assurance Officer.  It is understood that the EPA project officer (Dr.  C.W. Miller)
will function as the Quality  Assurance Officer in  terms  of:
     1)  providing guidance to the project on QA,
     2)  facilitating interlaboratory QA, and,
     3)  approving QA project plans.
The responsibility for the design and implementation of  acciptable QA procedures
lies with the Project Director of the Berkeley PHAP.
                             Quality Assurance
                              Officer OPP/HEB
                            EPA  Project Officer
                                NPHAP/HEB
                            Project Director
                             Berkeley PHAP
       Committee for the
 Protection  of Human Subjects
     Chief Chemist
Statistician
Field Studies
  Supervisor
                                                                                    67
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                                                          Section No.       4
                                                          Revision No.      0
                                                          Date;   November 10, 1982
                                                          Pa ge    2     of    2
        The Chief Chemist,  with  guidance  and concurrence of the Project Director,
is responsible for the design  and  implementation of QA procedures within the
laboratory.  He is responsible for supervising the laboratory's participation
in any inter!aboratory quality control  programs.  He also must design, schedule
and evaluate interlaboratory QA  procedures  to  insure confidence in the methodology
and facilities used for all  analyses.
                                                                                     68
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                                                                            544
                                                          Section No.      5	
                                                          Revision No.     0
                                                          Date;  November 10,  1982
                                                          Page  1    of    3
                       5.  QUALITY ASSURANCE OBJECTIVES
     The measurements to be attempted in this study center on the estimation
of dermal exposure of pesticides undergone by workers harvesting cane-, bush-
and trailing berries.  Since there is no standardized methodology for accom-
plishing this task, it is impossible to estimate accuracy.  However, components
of the method can be tested for precision and accuracy by employing the device
of spiked blanks.  These components include recovery of pesticide from gauze
patches, gloves, aerosol and vapor samplers, and the analytical  procedures used
to assay the recovered residues.
     For environmental samples, accuracy can be gauged by the taking of repli-
cate samples.  Spiked blanks are required here, as well, to determine precision
and accuracy.  Table 1.5 shows the best current estimates for the QA objectives
for the measurements to be made during the berry harvester studies.
     In reference to Table 1.5, since this study does not focus  on only one
pesticide or class of pesticides, the detailed methods of extraction and
analysis cannot be foretold, and, in fact, can be developed and  validated only
after the exact combination of pesticides applied to a given field (to be
monitored) have been reported.  In general, however, the following references
are applicable to Dermal Dosimeters:
     1)  McLean, H. R.; Futagake, S.; and Leffingwell, J. T.
         Loss of Paraoxon in aqueous acetonitrile extractions.  Bull.
         Environ.  Contam. & Toxicol.  18:247, 1977.
     2)  Popendorf, W.
         Exploring citrus harvesters exposure to pesticide contaminated
         foliar dust.  Am. Industr. Hyg. Assoc. 0.  41:652, 1980.
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                                                                           545

                                                         Section No.      5
                                                         Revision No.     o
                                                         Date; November 10, 198?
                                                         Page    2   of    3
to Aerosol  Monitors and Vapor Traps (for total  dust  and  various  pesticides):

     National  Institute for Occupational Safety &  Health
     NIOSH  Manual  of Analytical  Methods, 2nd Ed.

         vol.  1   DHEW (NIOSH) Publ.  No. 77-157-A
               2     "            "       77-157-B
               3     "            "       77-157-C
               4     "            "       78-175
               5     "            "       79-141
               6     "            "       80-125

to Soils:

     1)  Spencer,  W.  F., Cliath, M. M.,  Davis,  K.  R., Spear, R.C., and
        Popendorf, W.  J.
        Persistence of Parathion and its oxidation  to paraoxon  on the soil
  ?      surface as related to worker reentry into treated crops.  Bull.
        Environ.  Contain. Toxicol. 14:265,  1975.

     2)  Spencer,  W.  F., Iwata,  Y., Kilgore,  W.  W.,  and  Knaak, J. B.
        Worker reentry into treated  crops II:   Procedure for the deter-
        mination  of pesticide residues  on the  soil  surface.  Bull.  Environ.
        Contam.   Toxicol.   18:656, 1977.

to Foliar Surface  Residues:

 *   1)  Iwata, Y., Knaak,  J.  B., Spear, R.  C.,  and  Foster, R. J.
        Worker reentry into pesticide treated  crops I:  Procedure for the
        determination  of dislodgeable pesticide residues.  Bull.  Environ.
        Contam. Toxicol.  18:649, 1977.

     2)  Popendorf, W.  J.,  and Leffingwell,  J.  T.
        Procedures for the determination of dislodgeable dust on foliage as
        related to worker reentry hazards.   Bull.   Environ.  Contam.  Toxicol,
        18:787, 1977.

to Body  Surface Area:

     1)  Popendorf, W.  and  Leffingwell,  J. T.
        Regulating OP  pesticide residues for farmworker protection.  Residue
        Reviews 82:125, 1982.
                                                                                   70
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             TABLE  1.5

Quality Assurance of Objectives
Measurement EPA Experimental
Parameter Reference Conditions
Dermal
Dosimeters
Gauze
Gloves
Aerosol Monitors
Vapor Traps
Soils
Foliar Surface
Residues
Urine
Body Surface
Area
Time Of
Exposure

Spiked Blanks
Spiked Blanks
Spiked Blanks
Spiked Blanks
Spiked Blanks
Spiked Dust
Spiked Blanks


Pr(RSD)°n Accuracy Completeness

±5%
+ 5%
t 5%
is*
i 10% - 10%
+ 5*
i 10%
1 20%
1 5 Min. - 15 Min.
(2%) (5%)
                                                                                     •O O 30 t/>
                                                                                     Dl OJ  (T> 
                                                                                    U3 <-<• < O
                                                                                     (T> fD  —'• r*
                                                                                          -i. O
                                                                                          O 3

                                                                                       z   z
                                                                                       O Z O
                                                                                       < O •
                                                                                       tt>
                                                                                       n>
                                                                                              C_T
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                                                                                 b4/
                                                           Section  No.	6	
                                                           Revision No.       0
                                                           Date:    November  10, 1982
                                                           Pa ge    1     o f   6	
                          6.  SAMPLING PROCEDURES

6.1  Dermal  Exposure to Pesticides
     This project employs a gauze pad as  a  dermal  dosimeter for all areas of
the worker's body except the hands.   This dosimeter consists of a  12-ply 3x3
inch gauze surgical  sponge.  A polyethylene "moisture  barrier" is  placed on the
side of the pad facing the skin of the subject.  All of this is held  in a glossy
paper envelope.  The side of the envelope facing away  from the skin has a circular
                                     2
hole 60 mm in diameter exposing 28 cm  of the gauze pad.
     Body locations for mounting the gauze pad dosimeters are as follows:
     Head — mounted on the side of the head, roughly  over one ear, either stapled
             to a stretchable head band or taped to the inside of  the brim of the
             subject's hat (1);
     Chest — mounted over sternum between the pectoral muscles  (1);
     Back — mounted over backbone between the scapulae (1);
     Upper Arm ~ mounted over the deltoid muscles (2);
   l'  Lower Arm ~ mounted roughly midway between the elbow and wrist  on the
                  dorsal surface (2);
     Upper Leg — mounted roughly midway between the hip and the knee on the
                  anterior surface (2);
     Lower Leg — mounted roughly midway between the knee and  the  ankle on the
                  anterior surface (2).
     For ease of mounting and dismounting the patches, the  chest,  back and  upper
arm dosimeters are stapled to T-shirts which are dispensed  to  the  subjects  at
the beginning of the work period and collected at  the  end.   The  T-shirts  are to
be worn next to the skin of the subject so that the dosimeters will  be exposed to
                                                                                     72
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                                                                                548
                                                           Section No.__6____
                                                           Revision No.       0
                                                           Date:    November 10.  1982"
                                                           Page    2     of    6.

only that portion of the residues that would eventually reach the skin.  Lower
arm and upper and lower leg patches are taped directly to the skin in the appro-
priate location after the T-shirt is donned.  The subjects then wear whatever
clothing they would normally wear while working, except that if they were to strip
to the waist (which some male workers in California do) they would continue to
wear the T-shirt bearing the dosimeters.  A hand dosimeter consists of a light-
weight cotton glove.
6.2  Personal Aerosol Monitors
     Personal breathing zone air samples will be taken on at least two subjects
each working period of two hours.  An open-face, 37 mm Milltpore cassette
(0.8 y pore size) is mounted in a subject's breathing zone and is aspirated at
2.0 t 0.2 Lpm with a belt-mounted portable pump.
6.3  Area Aerosol and Vapor Monitors
     An open face 37 mm Millipore cassette (0.8 w pore size) will be stationed
centrally in an area of the field under harvest by our cooperative subjects.
This cassette will be backed up by a charcoal tube vapor trap as insurance against
vapor break-through from the filter.*
6.4  Foliar Samples
     Foliar sampling is accomplished by using a leaf punch equipped with a 3 cm
diameter die.  The punch-through action of the device pushes the leaf disk into
a 4-oz wide-mouth jar which is attached to the punch and which subsequently serves
as the sample storage container.  The punch is also equipped with a resettable
counter.
*It should be noted that the experience of this laboratory is that Millipore filters
possess an appreciable capacity for absorption of pesticide vapors.  However, since
the vapor retention characteristics of the filter for the particular pesticides1'
being studied here are unknown, a back-up charcoal tube (#226-01, SKC-West, Inc.)
is employed.
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                                                           Section No.	6_
                                                           Revision No.       0
                                                           Date:    November 10.  1982
                                                           Page    3     of   6
     Sample collection is accomplished by striking out diagonally across the area
to be sampled, stopping every three or four rows to take a single leaf sample.
The sampling points are to be distributed throughout the areas of the plants
that the harvester will actually contact.  This includes all parts of the plant,
both outer and inner canopy leaves, from either side of the row, and from the
center.   The standard sample size is 48 disks.  If the edge of the field is reached
before the full complement of leaf disks has been obtained, the person collecting
the sample merely reflects back into the field on a new diagonal.
6.5  Soil  Samples
     The soil sampling device has two parts: a three-sided form 10 cm long by
8 cm wide and 8 cm high, which when pressed into the soil surface blocks out an
          2
area 80 cm ; and a small rectangular shovel which fits just inside the form and
has a 1  cm high rim around the sides and back.  See Figure 6.1
     Sampling is accomplished by first shoving the form into the soil several
centimeters.  The shovel is then inserted vertically into the soil at the open
face of the form, likewise, several centimeters; and the soil is scraped away
from the form with it to a depth of several centimeters.  The shovel is then run
into the form horizontally so that it picks up a layer of surface soil the area
of the form and 1 cm deep.  The sampling pattern utilized for
taking soil samples is the same as for taking foliage samples, being collected
on a diagonal across the area being harvested by the cooperating pickers.  How-
ever, since there are only six "scoops" taken, rather than the 48 sampling sites
for the leaf punches, samples are taken every 8 to 10 rows.   Furthermore, samples
are taken in the area between the planted rows, which is where pickers are
physically located, and where they contact the soil.  Soil samples  are held in
a paper sack (#4 lunch bag) which is in turn placed in a plastic bag  to  reduce ___
moisture loss in frozen storage.
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                                                          Section  No.
                      550
                                                                             o
Revision No.
Date:    November 10, 1982"
Page	A
                                                                         of
Figure 6.1:  Soil Sampler
6.6  Urine Samples
     Subjects are requested to give all  of their urine in  approximately 12  hour
segments for at least 72 hours after exposure has terminated.   Initially they  are
supplied with three wide-mouth, 500 ml Nalgene bottles:  1) One  for the first period
of collection; 2) one for the next 12 hour period; 3)  and  one back-up for the  event
that it is ever needed.  The bottles are labeled with  the  subject's name, and
those that are intended for a specific time period have  the proper date and the
designation "day" or "night" on them.  In addition, there  is label  space for the
subject to write the actual times of first and last use  on the  label.  Thus, each
subject should have a full 24 hour's worth of bottles  and  a back-up to start out.
     The subjects are instructed to fill out the label on  each  bottle as it is
used in its appropriate time period and to either bring  the bottle to project
staff or to store it .refrigerated until  they can do so.  Each subject is given
a new set of bottles to replace the ones brought in to project  personnel  until -
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                                                           Section  No.	6	
                                                           Revision No.       0
                                                           Date:    November 10,  198T
                                                           Page     5     of   6
the 72 hour time  period is exhausted.
     Bottles are prepared by washing fn hot water with a strong laboratory
detergent.   After appropriate water rinsing, the bottles may be rinsed with
dilute hydrochloric acid if visual Inspection shows deposits.  Finally, they
are rinsed with acetone to remove traces of soluble organic material, air-dried
and returned to service.
6.7  Sample Preservation
     All  samples, regardless of type, are placed on dry ice as sampling is
completed.   They are kept thus in ice chests until they are delivered to the
laboratory, where they are transferred to a standard freezer chest maintained
at -10°C.   Samples are generally hand delivered to the laboratory by the field
study personnel  (which often includes laboratory personnel).   If the samples
cannot be  inventoried by the laboratory personnel  immediately upon arrival, the
samples are stored until the next working day in a different freezer from the
one customarily used for sample storage.  This procedure minimizes the possibility
of not logging a sample entering the sample storage freezer.
     In the unexpected event that samples are shipped by common carrier rather
than being  hand carried by project personnel, arrangements will be made between
the person(s)  shipping the samples and the laboratory to reduce the chance of
losing samples en route.  For short distances, our laboratory has found that
the "next bus  out" service of Greyhound Package Express is reliable and provides
overnight  (cool) service from anywhere in Northern California.  For longer distances
an appropriate air courier service is chosen.  Once the shipment has been made  and
the laboratory has been telephoned to confirm that face, the Chief Chemist arranges
for someone to meet the shipment at its expected time of arrival.
i
                                                                                     76
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                                                                                   55
                                                           Section  No.	6" '
                                                           Revision No.       0
                                                           Date:    November TO.  1982^
                                                           Page    6      of   6
     Samples are removed from the storage freezer only for the purpose of
inventorying and analysis.  During inventories, small numbers of samples are
removed at one time to prevent their thawing during identification and counting.
When samples are removed for analysts, they are withdrawn from the freezer in
groups only the size of the numbers of samples to be extracted, allowing the
minimum thawing time needed for room temperature equilibration.
6.8  Forms, Notebooks, Recordkeeping
     A form has been developed in this laboratory to record pertinent field
data on cooperating harvesters, and is included here as Appendix A.   This form
records a subject's personal data such as age, height, weight, his/her clothing,
work habits, and production (yield).  The form also provides for accumulation of
exposure data (contact time, times and flow rate for air samplers, and for
comments on irregularities in sampling, or subject's work).
     A field notebook is maintained as well  as individual  data sheets on the
subjects.  This book records the time, location, and quantity of all  environmental
samples taken, including data on all foliar, soil, and area air samples, regardless
of whether they were taken before, during, or after a harvester exposure study.
                                                                                77
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                                                          Section No.       7    553
                                                          Revision No.      0
                                                          Date:   November 10, 1982
                                                          Pa ge    1     of    5
                             7.   SAMPLE  CUSTODY
7.1   Field  Sampling Operations
     A.   Preparation of Sampling Supplies
         1)  Preparation of the  dermal dosimeters is described in Section 3
             of this document.   The  gauze sponges are preextracted by soxhlet
             in order to eliminate possible  interferences which this laboratory
             has previously encountered  with some batches of the sponges.  Once
             the samplers are assembled  they are labeled with their sample identify-
             ing code and stapled, when  appropriate, to the T-shirt carrier.   All
             head,  lower arm, and leg patches must be attached to the subject as
             he/she is about to  enter the study.  Lower arm and leg patches are
             taped  in place. Head patches are either taped to the subject's  hat,
             if one is worn, or  stapled  to a project-supplied hat or head band
             which  is worn as a  carrier.
         2)  The Millipore filters used  both for personal samplers and for area
             monitoring are prepared as  follows;
             Pre-weighing Procedure
             —Prior to use in the field, the filters are weighed in order to
             establish initial weights.  Six control filters are weighed at the
             same time in order  to quantify  weight gained due to moisture in the
             laboratory.
             —The  test filters  are  removed  from the sealed packaging and allowed
             to sit out on the laboratory bench for approximately 10 to 20 minutes,
             in order to equiibrate  with room moisture.  A paper is placed over
                                                %
             the filters to prevent any dust  from settling on them.  The control
             filters are prepared for weighing in the same manner.  The cassette
                                                                                    78
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                                              Section No.	7    554
                                              Revision No.	0
                                              Date:    November 10, 1982^
                                              Pa ge   2      o f    5
holders are prepared at this time and an identification number is
assigned to each one.  Once the filters are placed in the cassettes
they will be referenced by this number.
—An automatic electro balance having a digital readout in milli-
grams with four significant figures is used to weigh the filters to
1 5 micrograms.  The balance is calibrated using a standard 20 mg
weight prior to any filter weighing.  The calibration is repeated
intermittently during the weighing of both the control and test
filters to assure an accurate reading.  The filters are handled with
blunt-tipped forceps.  The weights for both the test and the control
filters are recorded and logged into a laboratory notebook.  The
test filters are entered and referenced by the number given to the
cassette in which they will be placed.  The control filters are
referenced by a number on the petri dish in which they are stored.
After the weight has been recorded the filters are assembled into
the cassettes and are then ready for field use.
Transport From Field
--At the completion of aerosol sampling the cassettes are placed
upright in a styrofoam holder to prevent Toss of dust from the
filter.  The holder is placed fn an ice chest with dry ice which
is then transported to the laboratory.
Post Weighing
—The post-weighing procedure is identical to the pre-weighing
procedure with the exception that the filters are placed in
individual, dessicating jars which contain anhydrous calcium sulfate.
                                                                    79
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                                                                           ;     55l
                                                      Section No.	7
                                                      Revision No.       Q
                                                      Date;    November 10,  1982~
                                                      Pa ge     3     of    5
        After removal of the moisture caused by the refrigeration process,
        the filters are placed on the laboratory bench and allowed to equili-
        brate with the room moisture.  The control  filters are prepared in
        the same manner.  The difference in weight  between pre- and post-
        weighing are logged into the notebook for each filter.  The same is
        done for the control filters.  The resulting dust weights are obtained
        by the difference in the pre- and post-weight minus the average weight
        gain for the six control filters.  The filters are then placed back
        in their cassettes and held in the freezer  to await chemical  analysis.
    3)  Leaf punches are cleaned of the build-up of leaf debris and dirt
        which accumulates on the punch and die while a sample is being
        collected.  This cleaning is performed with a household scouring pad
        made of either copper or stainless steel turnings.  Cleaning  is per-
        formed between samples and reduces chances  of any cross contamination
        between samples.
    4)  Vapor samplers are obtained commercially and are opened only  as they
        are to be used.  They are resealed immediately after sampling with
        the caps provided by the supplier.
B.  Procedures and forms for Recording Sample Acquisition Data
    This information  is put forth in Section 6.
C.  Documentation of Specific Sample Preservation Methods      ^  ^7
    Sample preservation methods are described in SectionsS of this document.
D.  Sample Labeling
    Each study is preassigned a "field" or study number.  This number,
    combined with the year, yields a unique study number.  Appendix B is
    the document supplied to the field personnel describing label generation.
                                                                                  80
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                                                          Section No.       7   556
                                                          Revision No.	0
                                                          Date    November  10, 198T
                                                          Page    4     of   5
     E.  Field Tracking Forms
         The subject data sheet and the field notebook act  as  field tracking
         devices.
7.2  Laboratory Operations
     A.  Laboratory Sample Custodian
         The Chief Chemist is the laboratory sample  custodian  and  as such  is
     responsible for inventorying samples  held for analysis or other processing
     and for maintaining all  necessary documents  pertaining to sample custody.
     These documents include  any shipping  receipts or  bills of lading and  a
     sample log book (see Appendix C).
         The sample log book  provides  for  the notation of sample identity,  date
     of sampling if known, date recieved,  date extracted, and  date analyzed.
     Sample numbers used within the laboratory are those assigned  in the field
     since those identifiers  are unique and  specify  useful  and pertinent data
     about the sample as well  (i.e., days  post application, sample type).
         Sample flow through  our laboratory,  and  thereby sample custody, follows
     the general pattern discussed hereinafter: when samples first arrive  at the
     laboratory they are placed in a specified freezer, "A", until  they can be
     logged into the laboratory log book.  After  they  are logged in they are trans-
     ferred to a second freezer, "B".   The  person responsible for extraction pulls
     batches of samples from  freezer "B",  noting  this  in the log book, performs the
     appropriate extraction procedure,  prepares the  sample  for analysis, and turns
     the batch over to the analyst.  The analyst  is  responsible for proper documenta-
     tion of the chromatograms and maintenance of sample integrity while he/she
     has possession of them.   The anaylst  also must  note the date  of analysis in
     the log book.   When analysis of the batch is complete, the samples are  r
                                                                                   8
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                                                     Section No.	7
                                                     Revision No.      0
                                                     Date:   November 10, 1982
                                                     Page    5     of   5
returned to the person who performs  the extraction and the samples are

prepared for archival  storage  and  replaced in freezer "B".
                                                                            82
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                                                          Section  No.	8    558
                                                          Revision NoT0
                                                          Date:    November 10, 1982
                                                          Page    1     of    4
                  8.  CALIBRATION PROCEDURES AND FREQUENCY

8.1  Field Equipment
     A.  Personal Sampling Pumps
         The personal sampling pump shall  be calibrated  before  and  after each
     day of sampling.
     1)  Allow the pump to run 5 minutes prior to voltage  check and calibration.
     Check the voltage.
     2)  Assemble the polystyrene cassette filter holder using  the  appropriate
     filter for the sampling method.   Ensure that the  luer adaptor  does  not come
     in contact with the back-up pad.
     3)  Connect the collection device,  tubing,  pump and calibration apparatus.
     The length of hose should be the  same as that used  in the  sampling  train
     (approximately 1 meter).
     4)  Check the seals on all Tygon  tubing connections.
     5)  Wet the inside of a 1-liter buret with  a soap solution.
     6)  Turn on the pump and adjust the pump rotometer  to the  appropriate flow
     rate setting.
     7)  Momentarily submerge the opening  of the buret in  order to  capture a
     film of soap.
   ;  8)  Draw two or three bubbles up  the  buret  in order to ensure  that  the
     bubbles will complete their run.
     9)  Visually capture a single bubble  and time the bubble from  0 to  1000 ml.
    10)  The timing accuracy must within t 1  second of the time corresponding to
     the desired flow rate.
                                                                              83
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                                                          Section No.        8       559
                                                          Revision No.       0
                                                          Date:   November  10,  1982~
                                                          Page   2	o f   4	
    11)   If the time is not within the range of  accuracy, adjust the flow  rate
    and  repeat steps 9 and 10 until  the correct  flow  rate is achieved.
    12)   Steps 9 and 10 shall be performed at least twice.
    13)   While the pump is still  running,  mark the position of the pump rotometer
    14)   A calibration curve can then be calculated.  The flow rate in LPM is
    placed on the x-axis and the rotometer reading on the y-axis.
     B.   Other Field Equipment
         In general, the relatively crude  measurements taken in the field, such
     as  height and weight of subjects, and time  worked, are effected with  devices
     whose calibration are not checked.  This includes carpenter's rule, a bath-
  ;   room scale, and various researchers'  wrist  watches.  The thermometers of the
     psychrometers, the thermo-anemometer  and any other meterological instruments
     are used generally uncalibrated, as well, since their data is used only for
     background information to describe the quality of the working conditions.
8.2   Laboratory Equipment
     A.  Balances
     1)   Electrobalance: the electrobalance used to weigh membrane filters for
     aerosol  monitoring is calibrated as described in Section 7 of this document.
                                                      •
     2)   Analytical  Balance:  the balance used to weigh analytical standards and
     smaller samples (SlOg),  when necessary,  is  a Mettler Model B-6 which  is good
  v*
     on  its vernier to at least 0.02 mg.   It  is  kept in a balance room out of
     normal  traffic flow and  laboratory activities.  The laboratory which  houses
     PHAP activities contracts for an annual  cleaning and calibration from a
     private  contractor.
     B.   Volumetric Glassware
         Whenever practical or necessary,  volumetric  glassware  is  Class  A or
     Class A serialized quality.  Further  calibration is  not  attempted.   In
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                                                                         _    56C
                                                      Section No.	8	
                                                      Revision No.       0
                                                      Date;    November 10,  1982
                                                      Pa ge    3     o f   4
non-critical applications such devices as tilt-dispensers and graduated
cylinders are employed.
C.  Analytical  Instruments
    The chromatographs are checked continually as they are used by injection
of standards.   When manual injections are done, more frequent standardization
is required (every three to five samples) than when a mechanical injection
device is used.  Furthermore, the analyst  is  required to choose standards
that clos:ely match the samples being injected.  When automatic injection is
being done,less frequent standardization is called for (every ten samples).
D.  Calibration Standards
    Chromatographic standards are obtained, whenever possible, from the
EPA repository  at Research Triangle Park, NC.  Failing that, they are
obtained from the following sources in the order of preference listed:
1)  Commercial  suppliers (e.g., Chem. Services, Westchester, PA) as
    crystalline solids or neat liquids.
2)  Pesticide manufacturers as crystalline solids or neat liquids.
3)  Commercial  suppliers as a solution in organic solvent (e.g., Nanogens,
    Supelco, Van'an Associates, etc.).
4)  Pesticide manufacturers as technical grade materials.
5)  Pesticide manufacturers as formulated pesticides.
    Standards,  unless obtained as a solution, are weighed out with an accuracy
sufficient to give at least four significant figures.  Dilutions are made in
hydrocarbon solvents, at least for the concentrated standards.  This is done
to minimize the possibility of chemical reactions between solvent and solute.
If reactive solvents, such as ketones, alcohols, or nitrogen containing
compounds, are  required by the analytical method being used, they are used
only to make up the working standard.
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                                                     Section No.	8   56 I
                                                     Revision No.       0
                                                     Date;    November 10, 1982"
                                                     Pa ge    4     o f   4	
    As few dflution  steps as possible are used to obtain a working standard,

thus reducing errors inherent  in such operations.
                                                                           86
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                                                                                   56;
                                                           Section No.	9
                                                           Revision No.      0
                                                           Date;    November 1o, 1982"
                                                           Page    1     of   4
                      9.  SAMPLE PREPARATION PROCEDURE

9.1  All Samples
     Sample preparation date and extraction volume are entered in the spaces
provided in the sample log book.
9.2  Gauze Pads
     Samples consist of one or two pads (one for main trunk or two for limb sample
sites) stapled inside paper application packs and stored in an RPE Zip-lock bag
in the freezer.  After the staples are removed, the pad together with the plastic
moisture barrier is transferred to a 125 ml LPE wide-mouth bottle.  Thirty ml of
toluene, some of which is used to rinse the bag, are added and the sample is
shaken at about 200 Hz for one hour.  A ten ml aliquot of the analyte  is reserved
in a glass polyseal vial and an auto-sampler vial is prepared from the remainder.
9.3  Glove Samples
     These are treated in a manner similar to the patches.   The gloves are frozen
one pair to a sample bag and 100 ml of toluene is used to extract a pair.  If a
subject wore more than one pair, the solvent is increased only to the extent that
an aliquot can be easily removed and the actual amount of solvent is noted.
9.4  Aerosol Samples
  S  These are Millipore disposable cassettes with 37 mm membrane filters.  An
extraction bottle is chosen so that the filter can be dropped directly in from
the cartridge without handling.  Loose dust is washed off the cassette with hexane
because the plastic is soluble in toluene.  The hexane is allowed to evaporate and
the pesticide extracted with 30 mL of toluene.  The sample is stored as above
under the procedure for gauze pads.
                                                                              87
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                                                           Section No.       9
                                                           Revision No.      0
                                                           Date:    November 10, 1982
                                                           Pa ge    2     o f   4
9.5  Leaf Punch Samples
     The standard leaf punch sample consists of 48 - 3 cm leaf disks frozen in
a glass jar with a water-tight plastic cap.  After a half-hour thawing period,
the leaves are dumped into a one pint square Mason jar with the standard lid and
ring closure.  Six drops of a 20 mg/L solution of dioctyl sodium sulfosuccinate
is added to the sample jar.  The surfactant and dust are transferred quantitatively
to the Mason jar with 100 ml of distilled water.  The leaves are shaken for 30 min.
on a shaker table at about 140 Hz and the liquid decanted into a 500 ml separatory
funnel containing 50 ml methylene chloride (dichloromethane), using a narrow-stemmed
funnel to avoid transferring leaves.  The process of washing the leaf disks with
surfactant and water is repeated twice more.   Then the leaves are counted and
discarded.  The separatory funnel is shaken 30 times and the organic layer is
drained through a small funnel plugged with glass wool and filled with anhydrous
sodium sulfate into a 500 ml round-bottomed f 24/40 flask.  The extraction proced-
ure is repeated twice more with fresh 50 ml aliquots of solvent and the combined
solvent is rotary evaporated to about 1 ml.  Ten ml of toluene is added and
evaporated.   This process is repeated twice more.  The final residue is quantita-
tively transferred to a 10 mL volumetric flask and made up to volume.  The sample
is ready for gas chromatographic analysis.
     The dust which was washed from the leaf surfaces remains in the interfacial
layer in the separatory funnel.  This material is filtered onto a pre-weighed
glass fiber  filter, dried at 110°C overnight and cooled in a dessicator.  Post-
weighing of  the filter yields the foliar dust weight.
9.6  Soil  Samples
     The sample is weighed and sifted through a #10 sieve (2 mm hole size) to break
up lumps and remove rocks, twigs and leaves.   The trash is weighed. The sifted    Qg
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                                                           Section  No.        9
                                                           Revision No.       0
                                                           Date:    November 10.  198
                                                           Pa ge     3     o f   4
sample is mixed and a 250 ml portion 1s transferred to a tared beaker and weighed;
the beaker is then placed in an ambient-temperature vacuum desiccator and dried
for 24 hours or more and reweighed until the residual  moisture is less than 0.5%.
A glass soxhlet thimble is prepared by placing 1.5 cm of acetone washed sand in
the bottom to protect the extra-course frit from fouling by soil fines.  The
thimble is tared and about 30 gm of desiccated soil is added, the weight being
taken to four significant figures.  The thimble is then placed in a 250 mL soxhlet
extractor and cycled for four hours.  The solvent is azeotropic acetone-hexane
C59* - 41%).  After extraction the solvent is removed by rotary evaporation and
replaced by a solvent compatible with the analytical method to be used - toluene
for GC only, acetronitrile for GC plus HPLC.  This method is applicable only to
those low-volatility chemicals expected to be found during this study.
9.7  Urine Analysis
     A.  Captan
         Tetrahydrophthalimide (THPI) is the major urinary metabolite of captan,
     with tetrahydrophthalamic acid being a closely related minor metabolite.
     There are two analytical methods for THPI.  The former Idaho PHAP project
     developed a method (Brokopp, c.D.   Annual Progress Report, Idaho Epidemiologic
     Studies Program, EPA Cooperative Agreement, #78-CX-0363, April 1980) and a
     newer version is being published by Schoen and Winterlin (Schoen, S.R. and
     W.L.  Winterlin. "Gas Chromatographic Determination of the Captan Metabolite
     Tetrahydrophthalimide (THPI)in Urine," submitted for publication, 1982.
         The major difference between the methods is the fact that the THPI is
     derivatized for EC analysis in the former, while in the latter, the metabolite
     is analyzed as underivatized THPI on a nitrogen-phosphorous detector equipped
     gas chromatograph.  The clean-ups for the two methods diverge somewhat due to
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                                                      Section No.	9      565
                                                      Revision No.       0
                                                      Date     November 10,  1982
                                                      Page     4     of   4
the facts that they were developed for analysis on different detectors and
that they were developed in different laboratories.  We will develop the
Shoen-Winter!in method in our laboratory first, given that the elimination
of a derivatization step simplifies the procedure.
B.  Organophosphate Insecticides
    There are six alkyl phosphate metabolites commonly observed as a
consequence exposure organophosphate pesticide.  One or two of these are
possible from any given OP compound, depending on its structure.  Reid
and Watts have published a method for derivatizing these metabolites without
the use of the explosive and powerfully carcinogenic reagents (diazoalkanes)
required by older methods [Reid, S.J. and R.R. Watts.  "A Method for
Determination of Dialkylphosphate Residues in Urine."  J. Anal. Toxicol.,
5, 126 0981)].
                                                                              90
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                                                                                   c//
                                                            Section No.       10    JOD
                                                            Revision No~0
                                                            Date:    November 10,  1982
                                                            Page     i     of   5
                         10.  DATA REDUCTION, VALIDATION
                                   AND REPORTING
 10.]. Agricultural Chemical Samples
     Most samples yield four (4) data items:
     1)  Sample vol., is the final  amount of  solvent in which the
         entire amount of analyte from the sample is contained.  This
         number is determined by the technician who prepares  the sample
         and records it with the extraction date in the sample log.
     2)  Injection vol., is the amount of sample actually injected
         into the GC or HPLC.   This number is recorded  by the instrument
         operator along with the sample number on the recording tape of
         the HP3390A (GC) or the Water's Data Module (LC) Integrator,
         i.g., 2 yL of a 1:1000 dilution are  injected,  the operator
         records, inj.  vol. = 0.002 yL.
     3)  Counts per injection:  This is the area under  the peak in yV-sec.
         as determined by the integrator for  each injection.
     4)  Response factor:  This is  an arithmetical  expression of the sensitivity
         of the entire analytical system to the injection of  a standard of
         known volume and concentration and has the units- R  = C/ng.   If C~  is
         the average count for 2 or more identical  standard injections with a
         RSD < 5% then R = C~ * inj. vol. * std. cone, proof:
                          __L-x   M  v ML  = J_
                            inj  *    yL  * ng    ng
     At the conclusion of a day's run the integration record  is logged in thus:
The values for each standard are entered, averaged  and  the RSD verified.  The
response value is calculated.
                                                                                  91
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                                                            Section  No.    10
                                                            Revision No.       0
                                                            Date:    November  10.  1982
                                                            Pa ge      2    o f   5
    The sample  number,  Injection volume and the replicate peak areas are
recorded,  then the sample number 1s looked up 1n the sample log and the analysis
date recorded there, finally the extraction volume 1s transferred from the log
to the laboratory notebook.  Since we want the final result to be 1n yg of
analyte per sample the following formula 1s used:
                                                                ug
                T inj volume  T  resp factor x ext volume =   sample
Note that prior to multiplication by the extraction volume ngA± convert £§r_
acidens to yg/mL.  Proof:
     The principal criteria used to validate data integrity will be agreement
 between the records and calculations and transfer checks done by the analytical
 chemist on randomly selected samples,
     For the purpose of this study, an outlier  is defined as an analytical
 data set with a relative standard deviation greater  than 10%.  Because  several
 samples are taken from different parts of each  subject's body, the  unacceptable
 sample is held until the rest are completed and the  whole body dose calculated.
 The effect of the uncertainty on the whole body dose can then be estimated  and
 a proper decision made as  to whether the sample must be cleaned and concentrated.
     The following data flow and reporting scheme refers to  the Sample/Data
 Flowchart, Figure 10.1.
                                                                                 92
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Figure 10.1:    Sample/Data Flowchart
                                                                            568
                                                                    ro
                                                                      0
                                 Section No.
                                 Revision No."	
                                 Date: November 10. 1982
                                 Page    3     of   5
    Subject
     Data
    Sheets

    Field
  Notebooks
Sample Collection
       and
Number Assignment
        I
                  Sample
                 Storage
                 Sample
                Extraction
               Chemical
               Analysis
               Chemical
             Calculations
              Industrial
              Hygiene
              Evaluation
            Statistician
                  JL
                Samples
                              Sample
                              Log
                                              Laboratory
                                               Notebook
                            Data
                            Sheets
                              J
                          Computer

                          Work-up
                                 1
                            Final Report
Laboratory
 Archives
                                                                          93
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                                                            Section No.     10
                                                            Revision No"!       5
                                                            Date : _ November 10, 1982
                                                            Page      4    of  5
     The process begins in the field when the Industrial hygienist fills
out a field data sheet on each worker and assigns a subject number to him/her.
A specimen field data sheet is in Appendix A.  As each sample is collected a
number is assigned to it in accordance with the protocol described in Appendix
B.  The samples are placed in dry-ice chests for the trip to the laboratory.
The field data sheets and the spray history are given to the senior scientist
for later use.
     Upon arrival at the laboratory, the samples are transferred to the deep-
freeze for storage and the sample log is filled out through the storage date
column.  The Chief Chemist and the analytical chemist later verifying the log
against the samples with a physical inventory.  The samples are turned over to
the technician who organizes them by type for extraction.  As each sample is
extracted the date and volume is entered in the log and the extracts are turned
over to the analyst.  After the extracts have been run, they are returned to the
technician for storage.   The raw data is transferred from the instrument print-
out to the laboratory notebook,and the printout is dated, coded and filed.  The
extraction volume and any special data (e.g. crop weight) are entered into the
laboratory notebook from the sample log and the analysis date entered in the log
book.  The calculations are performed and the results entered in the laboratory
notebook and the data sheets (see Appendix D).  The data sheets are checked
against the laboratory notebook by the analytical chemist and given to the senior
scientist who uses the field data sheets to perform additional calculations.  The
completed data sheets are turned over to the statistician who enters  the data
on the computer and does the statistical work-ups.  The computer output and all
the data sheets finally go to the Project Director for use in preparing the
final report.                                                                _(
                                                                                   94
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                                                                              570

                                                          Section No.    10	
                                                          Revision No.      0
                                                          Date:    November  10, 1982]
                                                          Page     5     of  5	
     The field notes, data sheets, and laboratory notebooks are retained by

the senior project chemist or/and project director for seven years.
                                                                             95
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                                                            Section  No.   n     g 7 i
                                                            Revision No"!       o^ ' '
                                                            Date:    November 10.  1982"
                                                            Page       i   of  ?
                      11.  INTERNAL QUALITY CONTROL CHECKS

     As  many samples as possible are collected in duplicate.  However, the
majority of the personal monitoring samples are unique.  Leaf punch, and soil
and airborn pesticide samples are regularly collected in duplicate or more.
     In  the laboratory, method checks are conducted by analysis of replicated
spiked samples and blanks.  These method checks are employed during routine
analysis, as well  as regular calibrations described in Sections 7 and 8 of
this document.  Reagent (solvent blanks) are also a regular feature of the
internal checks employed by this laboratory.
     Replicates and frequent calibrations are the backbone of our quality
assurance program  for chromatographic analysis.  At least duplicate injections
are used whether manual or automatic sample introduction is used.  The analyst
is required to check results for each sample for reproducibility and if the
relative standard  deviation exceeds 10% (5% is the laboratory goal) then
additional  injections are required until satisfactory results are achieved.
     Spiking leaf  punches, soil  samples, and to some extent, dermal dosimeters,
will be  accomplished by the use  of pesticide-laden dust.  This material will
be formulated by dosing a quantity of pre-sieved soil dust which has been
checked  for freedom from residues of the compound(s) of interest.  In this way
a supply of dust carrying a known and verified concentration of pesticide(s)
can be kept on hand for spiking  into the various substrates which will be analyzed.
A supply of unspiked dust from the same source will  be kept on hand for blanks.
     This technique offers advantages over spiking pesticides carried in organic
solvent, especially in the case  of checking foliar dislodgeable residue
methodology.
                                                                                  95
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                                                                                  572
                                                           Section No.    n
                                                           Revision NoT      0
                                                           Date :   November 10, 198
                                                           Page _ 2_of__2
     The schedule of internal quality assurance samples to be run varies
for different types of samples.  The bulk of the samples to be analyzed are
dermal pads.  They are run in batches of 30 samples at a time and two of
those samples will be either a blank and a spiked blank or two spikes.  Since
aerosol samples are extracted and analyzed in an identical fashion as gauze
pads, they will be included with the gauze pads for quality assurance purposes.
     Since soil sample processing is not consistently a batching process,  a
target of 10% of those processed will be QA samples.   Leaf punches are run in
batches of up to fifteen samples in number, and one of each batch, at least,
will be either a blank or a spiked blank.  Since only two or three vapor traps
are extracted at a time, at least one spiked blank will  have to be included in
the process.
     The results of these quality assurance sample analyses will  be accumulated
in a laboratory notebook especially set aside for this purpose.   A summary of
these results will be reported monthly along with the regular monthly reports
forwarded to the EPA project officer.
                                                                                  96
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                                                                           573
                                                          Section No.    12
                                                          Revision No.      0
                                                          Date:    November 10.  198T
                                                          Pa ge	]_p f   i	
                            12.  PERFORMANCE AUDITS

     A plan  for external performance audits 1s currently being developed
with the  cooperation of the chemists at the Pesticide Hazard Assessment Project
located at the University of Iowa, and under the guidance of our Project
Officer.  When this plan 1s complete*it will be forwarded for inclusion in
this document.
                                                                                  97
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                                                           Section No.     13     574
                                                           Revision No.      0
                                                           Date;   November  TO, 1982"
                                                           Pa ge	L__° f_2	
                           13.  PREVENTIVE MAINTENANCE
13.1  Field Equipment
     Generally, cleaning and recalibration (for air sampler pumps) provides
project personnel an opportunity to inspect field sampling equipment for
deficiencies before use.  Leaf punches require sharpening at long intervals
(dnce every two or three seasons) in order that they continue to cut the tough
fibers in xeomorphic leaves (e.g., citrus).  This is performed  on an as
needed basis.
13.2  Laboratory Equipment
     The analytical balance used by the project received an annual cleaning
and recalibration (see Section 8).
     Gas chromatographs are maintained in the following ways:  All carrier
gases are passed through moisture and oil traps to prevent fouling the columns
and detectors, and the trap elements are changed every four (250 SCF) cylinders.
Carrier gas intended for electron capture detectors is passed through an oxygen
scrubber, as well, which is changed after six cylinders of gas have passed
through it.  Electronics are checked by performing an electrometer zero and
noise check monthly or whenever a new method is set up.  The voltage profile
for the ECD is also checked and recorded.
     The digital integrator-printer-plotters used by the project perform a self
check every time they are turned on.  They require a cleaning of paper debris
each time a new role of plotter paper is installed.
     The auto sampler is operated on compressed air which is passed through
a particulate and water trap before use.  The performance of the auto sampler
is checked daily by careful examination of results obtained from calibration
standards and solvent blanks which are interspersed among samples.           •-
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                                                           Section No.   13
                                                                               I	71"
                                                           Revision No.      o J / J
                                                           Date:   November 10, 1982"
                                                           Pa ge     2    o f2	
     The liquid chromatograph automatically does a self diagnostic test when
powered up.   Solvents are prefiltered through a 0.22 y filter to prevent
particulate  damage to the system.
13.3  Spare  Parts Inventory
     Air monitoring pumps use rechargeable battery packs, which periodically
fail, so spare battery packs are kept on hand.
     The gas chromatographs have spare EC power supplies (3), a fan motor,
                                                                     \
heater cartridges for detectors, and injectors and an FPD igniter coil.   There
are three spare tritium ECD cells of unknown condition.  Regular supplies such
as septa, columns, and packings, are procured as necessary on an ongoing basis.
     The integrators have ho spare parts, except the thermal  printer/plotter
paper they consume.
     The auto sampler is backed up with extra syringes and needles, air filter
cartridges and consumable (vials, caps, and septa).
     The liquid chromatograph has a spares kit supplied by the manufacturer
which is kept up when pieces are used.
                                                                                99
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                                                                               576
                                                           Section No.   14	
                                                           Revision No.      0
                                                           Date:   November 10. 198T
                                                           Pa ge	L__° f   ?	
              14.  SPECIFIC ROUTINE PROCEDURES USED TO ASSESS DATA
                       PRECISION, ACCURACY AND COMPLETENESS

14.1  Field Sampling
     Standardized sampling procedures are employed to assure accurate
environmental monitoring (i.e., respirable dust and pesticides,  dislodgeable
residues, soil residues, crop residues, and meteorological  conditions).   The
patch technique used as a dermal dosimeter is unproven, although it is^ generally
accepted as the best technology available at present.   Therefore, the accuracy
of the data generated by the technique is unknown.
14.2  Laboratory Analyses
     All chromatographic analyses are run at least in duplicate.  Relative
standard deviations are calculated and any samples giving greater than 10% RSD
are re-analyzed.  At the discretion of the analyst, a lower RSD  criterion may
be used.  The general precision goal for the laboratory is  five  percent.
Standards are weighed by the most experienced chemist in the group.  Working
standards are cross-checked against one another.
     Calculations are recorded in the laboratory .notebook  assigned to the
project and are double checked by the analyst as he/she performs them by  re-
calculating every third or fourth sample.  The data is then triple-checked by
another person by their recalculating 10% of the samples.
     An absolute quality criteria is used independent of any statistical  test,
viz., any recovery and duplicate analyses not meeting the objectives specified
in Section 5 will cause the corrective actions described in Section 15 to be
initiated.
                                                                             100
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                                                           Section No.   14     577
                                                           Revision No.       0
                                                           Date:    November 10,  1982
                                                           Page    2      of   2
14.3  Further Data  Reduction
     Results  1n  term of mass of target chemical  (pesticide)  reported  by  the
laboratory are then transcribed into computer-readable  format  for  further
calculations.  This operation is also double  checked  either  on a 10%  or  100%
basis depending  upon the computer employed.   Finally,the  results are  tran-
scribed onto  appropriate data sheets and forms  as  indicated  by Appendices F
through J  for aerosol,  leaf punch, soil, crop,  and meteorology data,
respectively.  The  dermal  data reduction sheet  was previously  shown in
Appendix D.
                                                                            101
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                                                           Section No.    15       578
                                                           Revision No.      0
                                                           Date:   November 10. 198JT
                                                           Page	i   of   i	
                              15.  CORRECTIVE ACTION
     Whenever any evidence appears to indicate trouble or insufficiency  1n
sampling, analytical or data reduction activities or equipment,  efforts  are
mounted to trouble shoot and correct any problem to the satisfaction  of
responsible project personnel.   Specific procedures depend upon  the nature
of the problem and the ability of the personnel  dealing with  it  to interpret
the symptons.
     Acceptable limits for the performance of equipment, and  thereby  the data
produced by it, is described in other sections of this document.  The res-
ponsible person for initiating corrective action is that person  who detects
the problem, be it malfunctioning equipment or data that does not appear
correct or consistent.   Of course,  the ultimate  responsibility lies in the
hands of the Chief Chemist and  the Project Director.
                                                                                  102
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                                                           Section  No.    16      579
                                                           Revision No.      0
                                                           Date:    November 10. 1982
                                                           Pa gei	of    i	
                16.   QUALITY ASSURANCE REPORTS TO MANAGEMENT

    Quality  assurance  results will be accumulated  1n a QA notebook.  These
results will  be  summarized  1n the  Monthly  Report format which  1s sent to the
PHAP Project  Officer (see Appendix E).  Monthly reports are prepared jointly
by the Project Director and the  Chief Chemist.
    The  final report will  Include a QA section which summarizes the Monthly
Reports and discusses any QA Issues which  come from an analysis of the'QA
data.
I
                                                                             103
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                                                                    Date:   10 November  1982
                                                                    Page      1     of   1
                                   University of California
                                   School of Public Health
                        Biomedical  and  Environmental Health Sciences
                                    Berkeley, CA  94720
                                                                                        580
                                Field  Personnel Sampling Form
une and Number of Experiment:

tte of Experiment:

             Subject  Name
                                             Subject  Number     Sex    Age    Weight    Height
iration  of Exposure:

      Time In:           Time Out:
                                           Time  In:
                                                            Time Out:
Total Hours:
lothing Description  (type,  parts  of body not covered, hat, etc.):
    Habits:   (Working  position, observed foliar contact, etc.)
lusual  Observations:
amp!ing Patches (Nos.):
                                                              Pump No.:
ead       	
hest
ack       	
pper arm  	
Dwer arm  	
pper leg  	
Dwer leg
jnds (glove?]
ther
                (L)
                (L)
                          (R)
                          (R)
                                                              Collector Type

                                                              Flow Rate:
                (L)        (R)
                                                                                      m3/hr
                                                       Name of Recorder (Observer)

                                                                   .     104
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                                                           section HO. Appendix  B
                                                           Revision No.     0
UCB SAMPLE IDENTIFICATION CODE                             Date:  10 November 1982
                                                           Page     1     of   1
                                                                                  581,
Year (a)      Plot (b)       Sample  Type  (c)     Days Post-     Replicate (e)
                                               Appl. (d)
(a)  Last two digits  of year,  e.g.,  80,  81, or 82
(b)  Plot number (2 digits)  assigned by  project supervisor
(c)  Sample Type
     A = aerosol
     C = crop sample
     P = punch sample
     S = soil
     V = charcoal  or  other vapor collector

     Patches, etc.
     H = head                     Ch =  chest
    UA = upper arm                UL =  upper leg
    LA = forearm                  LL =  lower leg
    St = stomach                  Sh =  shoulder
                                  LB =  lower back
(d)  Days post application,  0  =  day  of application, 1 * first day after,  etc.,
     (PA is preapplication).
{e)  Replicate number for  duplicate  sample, different people, etc., as necessary
     and recorded  in  field notes.
                                                                           105
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               t—i

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              Laboratory Sample
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-------
                                                               Section No.  Appendix  p
                                                               Revision No.     0
                                                               Date:  10_Noyember 1982
                                                               Page _
1
of   1
(7/81) DERMAL DATA SHEET
                                                                                   583
STUDY:
DATE:
LAB LOG:
(b)
chen. mass



*
pads



(c)
time
COMPOUND:

Pad Area:
(d)=(a)(c) (e=(b)/(d)
hr-cm2 rate density

cm2 (a)
(f)
LOC AREA

(h)=(e)(f)
rate
{cation/ ID
• HD
• neck
*
' SH
• BA
**BA
' CH
St
**CH
hips
UL
LL
«>
*
feet
UA
LA
GL
( 9)

















n

















hours



































( q/hr.cm2)

















cm2
1075
230
*1300
1305
1540
**2190
1540
720
**2190
1750
3460
2590
*6050
1230
1860
1290
1075
( 9/hr)
•
















    Indicates area as  sum of previous two locations.

    Areas to be used where no shoulder or stomach pads included.
                                                                               107
-------
                                                                   Date:  10 November 1982
                                                                   Page     1     of   1
                                               Date Report Prepared:
                             MONTHLY LABORATORY STATUS REPORT
                                                                                          584
-ticipating  Pesticide  Hazard Assessment Projects
ile of Study/Investigation:	
-1od of Report:	
to
Substrate
(List chemical residue
to be analyzed for
or
test to be performed)







Number
of
Samples
on
Hand






\
Number
of
Samples
Received
or
Collected
During

Report
Period


Total
Number
of
Samples
to be
Analyzed






Number
of
Sampl es
Completely
Analyzed
During
Report
Period




Numbers
of
Samples
Remaining
to be
Analyzed





j
-------
                                                                 section no. appendix
                                                                 Revision No.     0
                                                                 Date:  10 November  1982
                                                                 Page     1     of   1
                      STUDY/INVESTIGATION MONTHLY STATUS REPORT


*Title of Study/Investigation:	
 Participating  Pesticide Hazard Assessment Project
 Period of Report	to .	Prepared by

 Cognizant HEB  Staff Member	
iI.  Ltst Tasks  Completed During Report Period:
II.  List Tasks Started on Schedule During Report Period:
 II.  Tasks Behind Schedule:
 IV.  Why are Tasks  Behind Schedule? - Account for each Task:
 V.  Action  or Assistance Needed to Complete Tasks - Include New Start and/or
    Completion Dates.
                                               Date Report Prepared:	585
I
                                                                                      109
-------
                                                     	10IX
                                           Revision  No.	
                                           Date:   10 November 1982
                                           Page      1     of
                          1
          University of California
          School of Public Health
Biomedical  and  Environmental Health Sciences

            Aerosol Data Form
                           586
Study ID#
/Chemical
VOL
PERSONAL ID# SAMPLE ID# TIME AIR (L)
"







































DUST
CONC.
Wt(mg) mg/m3




















PESTICIDE
CONC.
Wt( g) g/m3




















POOLED
GROUPS

>








                                                             110
-------
                                                                Section No.  Appendix  H
                                                                Revision No.     0
                              University of California           Date:   10 November 1982
                              School  of Public  Health            Page
                     Biomedical  and Environmental Health Sciences
                                       T
     of    1
                                                   587
                                 Leaf Punch  Data  Sheet
                    Study ID*
                          /Chemical
                             (Area of 3 cm punch  =  7.07 cm)
I.  Preapplication Samples:

                        f OF
    SAMPLE ID#   DATE  PUNCHES
AMOUNT OF              99
PESTICIDE  CONC.  yg/cirT   DUST mg/cnT
CONC. ON
DUST, ppm
II. Post Application
1. Interim Decay Samples
# OF AMOUNT OF ? ? C0fi;c- ON
SAMPLE ID# DATE PUNCHES PESTICIDE CONC. pg/cnT DUST mg/cnT DUST, ppm




























2. Field Study Samples
f OF AMOUNT OF 22 CONC' OI>!
SAMPLE ID# DATE PUNCHES PESTICIDE CONC. yg/cuT DUST mg/cirf DUST, ppm













•














3. Post- Field Study Samples
f OF AMOUNT OF 22 CONC* ON
SAMPLE ID# DATE PUNCHES PESTICIDE CONC. yg/cnT DUST mg/cm DUST, ppip



	 	























11
-------
                                                                                         T
                                                                   Revision No.      0
                                    University of California       Date:   10 November 1982
                                    School of Public Health        Page
                          Biomedical and Environmental Health Sciences
                                        1
                                    of
                          Study  ID#_
                                       Soil Sample Data Sheet
                                     (Area per scoop = 77.4 cm )
. Pre Application Samples
NO. OF SOIL * AMOUNT OF CONC.
SAMPLE ID# DATE SCOOPS WT.(g) H20 PESTICIDE vg/cm2 PPM











,




'II.  Post Application
     1.  Interim Decay Samples
                            NO. OF   SOIL
     SAMPLE  ID#       DATE  SCOOPS  WT. (g)
            %
           H20
       AMOUNT OF
       PESTICIDE
                 CONC.
                vg/cm2
                  PPM
      2.  Field Study Samples

                            NO. OF
     SAMPLE ID#      DATE   SCOOPS
 SOIL
WT. (g)
 %
H20
AMOUNT OF
PESTICIDE
 CONC.
yg/cm2
PPM
      3.  Post Field Study Samples
NO. OF SOIL % AMOUNT OF CONC.
SAMPLE ID# DATE SCOOPS WT. (g) H20 PESTICIDE vg/cm2 PPM





-


























                                                                                        112
-------
                                                             Section No.  Appendix  j
                                                             Revision No.      0
                           University of California          Date:   10 November 1982
                           School of Public Health           Page     1      of    1
                  Biomedical and Environmental Health Sciences
                              Crop Sample Data Sheet

                    Study  ID#	/Chemical
589
Preapplication  Samples

                         NO.  OF
SAMPLE ID#       DATE     FRUITS     FRUIT WT.  (g)     PESTICIDE (  g)  yg/cm2
 PPM
Post Application
1.  Interim Decay Samples
NO. OF
SAMPLE ID# DATE FRUITS FRUIT WT. (g) PESTICIDE ( g) yg/cm2 PPM




























2.  Field Study Samples
NO. OF
SAMPLE ID* DATE FRUITS FRUIT WT. (g.) PESTICIDE ( g) yg/cm2 PPM




























                                                                              113
-------
                       University of California
                       School of Public Health
           Biomedical and Evironmental Health Sciences
                    Meteorology Data Form
                                                                          0
           Study ID#
           Section No._
           Revision No.
           Date:    November 10.  198T
           Page	
                                                                      of
                                590
      M     D    Y

DATE     /    /
                         Wind
Temperature
AVG.
TIME *DIRECTION SPEED





















RANGE
FPM







HUMIDITY
WET F .DRY F %














\






SUN CON-
DITION







    *NOTE  relation to work operation
                                                                      114
-------
          APPENDIX B



CORRESPONDENCE REGARDING URINARY



      METABOLITE ANALYSES
-------
                                                                592
                                      14 December 1984
Dr. Geraldine Fristrom
FSSP Laboratory Coordinator
EAB/HED/OPP  (TS-769-C)
United States Environmental Protection Agency
401 N Street, SW
Washington, D.C.  20460                           RE:  CR-810691-02-0

Dear Gerrie:

      Your letter of 10 October 1984 was appreciated; it is essen-
tially correct.    Here is a summary of progress to date.

      Save for  some  ironing out of a few  minor  quality assurance
issues, I feel  that we have run the benomyl environmental  and person-
al samples in sufficient numbers to  know exactly  what  we have.  All
of the 8301 and 8302 glcve samples were positive, though low.  The
8301 samples ranged  from about 50 to 1000 micrograms,  while the 8302
?loves were 200 to 2000.  Recall  that the gloves from  the  strawberry
 ields where benomyl was  applied ran in the vicinity of 10 to 30
milligrams.   A selection of 48  patches from the 8302 study  (40%)
resulted  in  no detectable (not  "too low to quantitate") residues.
All the air  samples from  both  the  studies  gave the same result.
Finally,  all the  leaf punch samples from  the two benomyl studies
(8301 and 8302) have been completed, along with all the  associated
quality assurance  samples.

      I feel  that we could safely expect that  there is  no  further use
in analyzing any more of the patches.  The indications  to  me are that
there will probably be no detectable metabolites in  the urines, as
well.  However, as we have discussed by telephone,  John Tessari's
laboratory  will select a few samples based  on  the glove data and
verify this prediction.

     The  mesurol urinary  metabolite method that we have been putting
together  has proved itself reasonably reliable with spikes and stan-
dards, so far; and, although it  is getting  close  to the deadline, I
remain optimistic  that we will be able to complete that  task satis-
factorily.  Only one experiment  remains to be  done before the actual
samples go into  the system.  That one is  to  determine whether or not
we must hydrolyze  conjugates as  a first step in the sample work-up.

      I looked into  the  issue of instrument rentals.   It turns out
that there is one major purveyor of rental equipment  in this area,


                                                               116
-------
                                                                  593
Dr.  Geraldine  Fristrom
Page 2
14 December  1984
named USI;  and they handle most major manufacturers.   When one  looks
at short-term  rentals, as opposed to leases of a year or more (usual-
ly with purchase options),  there are some interesting,  though  logi-
cal,  restrictions applied.  If one goes into a long-term arrangement,
you can get a  system configured any way you want,  because  the lessor
will go out and buy exactly what you stipulate.  On the other  hand,
the short-term renter takes what they have "on the shelf."   What they
stock for rental customers  is the  top of the line equipment.  This
way, they minimize their inventory; the fanciest equipment is the
most versatile,  and that minimizes their  capital outlay. Anyway, the
upshot of all  this is that it would cost us approximately  $1700 per
month to rent  a High Pressure Liquid Chromatograph to do the analyses
we presently are carrying out. That is at the academic rate of  5% of
the retail price per month instead of the 10% charged to industrial
clients.

      That is  generally quite a  bit more than I have been  paying in
for the upkeep of the present  equipment.   I do not see  being able to
afford such an expense,  and  the machines have hung in there the last
few months with only minor troubles.

      I spoke  with Dr.  Zweig some time back,  now,  and he informed me
that he will  not be working under Dave Severn;  rather,  he is now
assigned to a one-year project in Registrations.   That  creates a
problem here in the final report department, because, as I pointed
out previously, there  is no way of our  getting these analyses all
completed in time to have final reports written prior  to  the termina-
tion date.  I  am sure that no one has a taste for these data  to go
uninterpreted.  Dr. Spear and I have discussed this issue,  and we
have agreed to submit a request  for a no-cost extension under sepa-
rate  cover.

     Bowever,  the funds are,  in fact,  coming out close to the budget,
and it certainly would  improve the  situation here if there could be
some supplementary  funding from  the PHAP program to facilitate the
last steps of  finishing the reports  and seeing to the transfer of
equipment to Jim Seiber's shop.

                             Sincerely
                             John T. Leffingwell, Manager
                             California PHAP
cc   B.C. Spear
                                                               117
-------
                                                                 594
                                       17 December  1984

Dr. Geraldine FriStrom
FSSP Laboratory Coordinator
EAB/HED/OPP  (TS-769-C)
United States Environmental Protection Agency
401 M Street, SW
Washington, D.C.  20460                        RE: CR-810691-02-0
Dear Gerrie:
      Attached  is a preprint of a manuscript titled, "The Rela-
tionship Between  Dermal  Pesticide  Exposure  By Fruit Harvesters
And Dislodgeable Foliar  Residues."  It will  be appearing shortly
in The. Journal o_f Environmental Science and Health. P_ajLt B.  It
contains a wrap-up of much of the work that  we have conducted
under the aegis of the Youth in Agriculture program, summarizing
most  of  the dermal exposure data collected over  the last four
years.
      Incidentally,  the Mesurol  (methiocarb) dermal  data  is
included in this paper, and the write-up will  serve as the basis
of our final report on the 1983 blueberry study.
                             Sincerely
                             John T. Leffingwell, Manager
                             California PHAP
                                                                118
-------
                                                                  595
                                      11 January 1985
Dr.  Geraldine Fristrom
FSSP Laboratory Coordinator
EAB/HED/OPP   (TS-769-C)
United States Environmental Protection Agency
401  M Street, SW
Washington, D.C.  20460                       RE: CR-810691-02-0

Dear Gerrie:

     Developments in the matter of mesurol metabolite analysis
are  such that I deem it desirable to report them to you in some
detail and seek relief in the deadlines we  face at present.

     As you know from previous telephone conversations and cor-
respondence, we were required in 1983 to change the proposed work
plans which we had submitted to the NPHAP staff to  drop the idea
of doing more  work  on strawberry harvesters in favor of workers
in three other berry crops.  This meant that we would have to
focus on populations of workers and  crops that  were quite distant
from our laboratory and of which we knew  almost nothing.  The
consequence was that  almost all control  over  such  critical fac-
tors as the  choice of the field site  and the  timing of  our
studies in relationship to pesticide applications  was lost  to  us.
In fact, when we  left for Oregon in July 1983, we even had not
been able to determine what pesticides we would be working  with.

     As good fortune  would have it, the blueberry grower who was
cooperating with us happened to be treating one plot of his farm
with mesurol just days before we were to begin our  study, and he
allowed our group of  harvesters to work in that newly treated
plot (it was  a legal  reentry).  In  due  course we collected the
urine samples according  to the approved  protocol,  along with
other personal and environmental samples needed  to complete the
study.

     Since we did not  know what pesticide(s) to expect, we could
not  have methods of  analysis developed and  in place at our labor-
atory before  the  collection of samples.  Consequently, we pre-
served the  urine samples in a manner consistent with our previous
experience; namely, we took 20 mL aliquots of the urines, dosed
them with  1.5  mL  of concentrated hydrochloric acid and sealed
them in 25  mL ampules.  This  style of preservation had worked
excellently for urines containing p-nitrophenol.
                                                             119
-------
                                                                596
 Dr. Geraldine Fristrom      Page 2              11 January 1985


      Alternate methods of preserving  urine samples were  not
 acceptable to roe.  The use of  sodium fluoride would cause severe
 problems  with subsequent acid  hydrolysis of conjugates.   The  use
 of .thymol promised  to give  massive  interference in the analysis
 of  phenolic metabolites  (such  as  those of mesurol).  And, we
 could not handle the  logistics of  freezing, shipping and storing
 the hundreds of urine samples that  were to be  generated in  the
 1983  studies.

      This last Fall, as you already know, we began development
 work  on an analytical method to deal with the realities  of roes-
 urol metabolism  {It leads  to three related phenols:  3,5-dimethyl-
 4-methylthiophenol,  3,5-dimethyl-4-methylsulfinylphenol  (the
 sulfoxide) and 3,5-dimethyl-4-methylsulfonylphenol  (the sulfone),
 reflecting step-wise oxidation of  the  sulfur.} and  the  (acid)
 state of  the one hundred plus samples on hand.  My approach was
 to oxidize the three metabolites all to  the last one and analyze
 for it by HPLC.

      The development process started  from  the  sulfone; with
 standards from the manufacturer in hand,  we first  confirmed that
 we  could analyze that compound by HPLC.  then,  we worked on
 oxidation procedures that  would take the methylthioether  and  the
 sulfoxide to the sulfone.   Finally, having done that, we had to
 anticipate that these phenols could be present in the urines as
 conjugates with  glucose or  sulfate and would require  hydrolysis
 prior to analysis.   This is the stage where we were just prior to
 the Christmas break.

      It  was possible that  conjugate hydrolysis had already  oc-
 curred spontaneously during the samples' standing for over one
 year at a pH of less than 0.1.  The only way we could test for
 the necessity of a  hydrolysis step was to heat an aliquot  of one
 or more actual samples and compare them  to aliquots that had not
 been subjected to this treatment.  The results of that  experiment
 was zero  in all  samples, even the spikes run  for quality assur-
ance.   Subsequent experiments  with  spiked  samples,   including p-
 nitrophenyl-p-D-glucuronide  and  p-nitrophenyl sulfate as  surro-
 gates, showed that  the hydrolysis of the conjugates works per-
 fectly;  however, serious,  if not complete, loss of  the sulfoxide
and sulfone occurred (0 to 40% recoveries,  respectively).

      A review of the chemistry of this  type of sulfur compound
 indicates that  treatment  with strong acid causes the aromatic
 carbon-sulfur bond to  be hydrolyzed,  such that we could expect to
have 3,5-dimethylphenol as  a product  (either conjugated or not).
To confirm this hypothesis, samples of  acid-treated standards
have been submitted to the analytical services laboratory  of  the
College  of Chemistry  on the Berkeley Campus for GC-MS analysis.
We are expecting results back by the  middle of this  month.
                                                                  120
-------
Dr. Geraldine Fristrom       Page  3               11 January 1985


     The set-back that this development represents means that  we
are nearly back  to  square one in the analysis of the mesurol
metabolite  samples.   If our  hypothesis holds,  and 3,5-dimethyl-
phenol  is our analyte,  there is a whole new set of parameters  to
pin down.   What method  of chromatography (gas or liquid)?   If
capillary gas chromatography is the separation method of choice,
what  detector?  This compound has  no substituents that are amena-
ble to detection with the BCD, FPD or NPD,  and would require
privatization with  a  halogen  or  phosphorous containing reagent.
Will  clean-up be required to  remove interferences?

     To resolve these questions and  run the pending  samples,  we
will need time beyond our current  ending date of 31 January  1985,
as well as  salary and supply  money  for  the laboratory personnel
who will be needed to complete the work.   If all  the steps fell
into place, the minimum time  to implement a method would be a
month form now.   Analysis of the  samples would take another
month.  A reasonable estimate of  completion of these  tasks  would
be the  end  of March 1985.

                            Sincerely
                            John T. Leffingwell, Manager
                            California PHAP
cc  R.C. Spear
    Marion Lentz
                                                                   121
-------
                                                                598
                                       24 January 1985
 John Tessari, Manager
 Colorado Pesticide Hazard Assessment Project
 Colorado State University
 Fort Collins, CO
 80523

 Dear John:

      Enclosed are three standards for your use in working with
 the analysis of Benomyl urinary metabolites:   Carbendazim and
 benomyl from the  EPA Standards Repository,  and 5-hydroxy-2-benz-
 imidazolecarbamate from du Pont.   The  later is  the metabolite of
 interest,  although,  I am  surprised that the carbamate moiety is
 still intact at the 2 position.

      The first two are different forms of  the active  fungicide;
 benomyl  decomposes  rapidly in  the environment and  in protic
 solvents,  as well, to carbendazim.   Carbendazim  can be converted
 to  benomyl by reacting  it with  n-butylisocyanate. This technique
 is  useful  in manipulating  these compounds for HPLC analysis;
 benomyl elutes substantially later  than carbendazim on a reverse
 phase C18 column, and  changing the elution time of the analyte
 has been useful  in eluding interfering  peaks.   I  presume  that the
 same reaction would go with the 5-hydroxy-2-benzimidazolecarbam-
 ate.  For  the carbendazim/benomyl analysis, we use an acetoni-
 trile-water mixture (65:35) @ 2.0  ml  per minute on a 25 cm Cj
 column.  The butylisocyanate has to be present in the sample a
 about 2 to 5 ppm  to maintain the compound as benomyl.  Detection
 is by UV at  292 nro.
                                             •
     Good  luckl

                             Sincerely
                             John T. Leffingwell, Manager
                             California PHAP
cc:  G. Fristrom
Tessari2.1tr                                                     122
-------
                                                                  599
                                       25 January 1985
Dr. Geraldine  Fristrom
FSSP Laboratory  Coordinator
EAB/HED/OPP  (TS-769-C)
United States  Environmental Protection Agency
401' M Street,  SW
Washington, D.C.  20460           RE:  Mesurol Metabolite Analysis

Dear Gerrie:

      The answer has come back from  the GC/MS  lab that the only
thing found in the  treated standard we took them was a dimethyl-
phenol.   Given that we started with 3,5-dimethyl-4-methylsulfin-
ylphenol,  it is  reasonably  safe to  infer that the product of the
decomposition  is 3,5-dimethylphenol.

      Since we have been following  Reed  and Watts'  method for
urinary  alkyl  phosphates  using pentafluorobenzylbromide  (PFBB) as
a derivatizing reagent in conjunction with our work on the fluor-
escent tracer  project, and  since  PFBB is reputed to be an excel-
lent derivatizing  agent  with  phenols  for electron capture detec-
tion, we  have undertaken  to develop a  method utilizing  this
reagent.

  •  As way of background, 10 mL of the acidic urine samples will
be diluted with 5 mL of  water and heated to liberate any conju-
gates.   The 3,5-dimethylphenol will be extracted into methylene
chloride.   The derivatization  reaction is carried out in a polar
solvent, such  as an alcohol, acetone or acetonitrile; so, we will
convert the methylene chloride to acetonitrile.  Catalysts for
the reaction are solid anhydrous potassium carbonate and 18 crown
6 ether; the former generates the potassium salt of the phenol,
while the  later  solvates the  potassium ion  away from the phenol-
ate ion, promoting its reactivity  toward the benzylbromide.

      Before he  started,  Mr.  McLean contacted a technical person
at Supelco, our  supplier  of PFBB, to  obtain advice on approaches
to removing the  unused derivatizing  reagent from a sample after
reaction with  the analyte of  interest has  been  completed.   PFBB
is a  neutral molecule; and,  as such,  cannot be separated from the
derivative of  the phenol by commonly employed  extraction tech-
niques,  such as  manipulation of  pH or use of adsorbents to dif-
ferentiate  between  polar  and  non-polar species.   Furthermore, it
is highly  electron  capturing  (response factor of about 10 counts
                                                                    123
-------
                                                                    600
Dr. Geraldine Fristrom       Page  2               25  January 1985


per femptogram on our GC at present), and it will be present in
great excess over the analyte of interest.  Therefore, an unusual
approach is needed in order to  utilize this reagent with an BCD
that was not needed with the alkyl phosphate analyses using the
flame photometric detector.

     The Supelco person  recommended that we use a strong cation
exchange resin in the acid form.  The free PFBB would react with
the benzene sulfonate  groups on the resin and would  be, thereby,
removed from the sample.  The Supelco person had in mind that we
would use that company's disposable solid phase  extraction/clean-
up cartridges loaded with HPLC-type strong cation exchange pack-
ing.   Since  we  did not have this item  in  hand ($2.00  ea.  in
packages of 50), but  did have a  good quality cation  exchange
resin  (Bio-Rad AG  50W-X8).  For ease  of  sample handling,  we
decided to  try the resin as a slurry, rather than  in  a column.

     It did not work.   No matter  how much resin was put in the
sample, no reduction in the quantity of PFBB was seen.  We even
set up a resin column,  and saw no reduction.  So,  back  to our
contact at  Supelco, and his reaction was that he had assumed that
we would be working in an aqueous medium.  Now,  he and another
person at Supelco have given us  a  new procedure.

     The treated sample in  acetonitrile  is to be diluted  with
water and extracted with hexane.  The hexane  extract  is to be put
onto a silica gel  extraction/clean-up cartridge,  eluted  with
additional hexane to remove all  PFBB and then eluted with 20%
hexane in toluene to elute the derivatized phenol.  Mr. McLean is
attempting  this new procedure as of this writing.

     If you think that  there is  a particularly knowledgeable
person within EPA or the NPHAP group,  I would be glad to  talk
with them by telephone.  I am afraid that by the  time copies of
this letter get around, and interested  parties take time  to
respond *ith their  ideas,  it will be  much too  late for  us to
effectively put them into practice. Give me a call when you have
read through this  and have an idea or  two about  people I might
contact directly for additional  suggestions.   Thanks.

                             Sincerely
                            John T. Leffingwell, Manager
                            California PHAP
                                                                 124
-------
                                                                601
                                       14 March 1985
Dr. Geraldine Fristrom
FSSP Laboratory Coordinator
EAB/HED/OPP   (TS-769-C)
United States Environmental Protection Agency
401 M Street, SW
Washington,  D.C.  20460                       RE: CR-810691-02-0

Dear Gerrie:

      It has been some time,  now, since we last talked by tele-
phone.   I did promise you an update on the Kesurol  urinary meta-
bolite methods development work.

      As explained  in  earlier correspondence,  we had developed a
method  for  the  analysis of  mesurol metabolites  based on the
literature,  which indicated that the compounds to be anticipated
were threefold:   Mesurol phenol (3,5-dimethyl-4-methylthiophe-
nol),  the sulfoxide (3,5-dimethyl-4-methylsulfinylphenol) and the
sulfone (3,5-dimethyl-4-methylsulfonylphenol).  The  last step in
the method development showed that not only did real samples lack
any of these phenols, but spiked blanks  lacked  them,  as well.  A
review of the chemical literature on sulfur containing phenols
led us to believe  that  the strong acid  conditions we used to
preserve the samples  cleaved  the  sulfur-carbon bond at the ring.
Subsequent GC/MS analysis of  a  treated spike  confirmed that
hypothesis.

      Work on a second method was undertaken during January, but
had to be terminated when Mr. McLean had to be  laid off due to
lack of funds. The  approach we were taking was to derivatize the
3,5-dimethylphenol with something  that would  allow  it  to be
analyzed  with a  gas chromatograph equipped with an element-
specific  detector, eg. electron  capture or flame photometric
detectors.   The ultra-violet  spectrum of  3,5 dimethylphenol did
not give any distinct peaks at  which we could set the variable
wavelength detector for the HPLC,  rendering that analytical tech-
nique of  questionable applicability for  this problem.

     Since we have  had relatively good success  with the use of
pentafluorobenzylbromide in conjunction with the malathion uri-
nary metabolite work  that we have been doing of late, we decided
to give that a try; we were fairly familiar with its chemistry
and we had a stock  of  the necessary  reagents on  hand.  However,
                                                                  125
-------
                                                           V  602

Dr. Geraldine Fristrom       Page  2                 14 March 1985


contrary to the malathion metabolite work,  which was done on the
flame photometric detector,  this work would be done on the elec-
tron capture detector; and we would have to devise a scheme to
purge the samples,  once treated, of  excess reagent,  which, itself
is extremely electron capturing, and renders the detector useless
for hours if passed through it in  any  quantity.

      As described in earlier correspondence, we sought advice
from our supplier  (Supelco) on approaches to handling this prob-
lem, since they tout the material as a good derivatizing agent
for phenols.   Most  of  the  problems  were  worked out successfully
using blanks and spikes, and we had a reasonably  good clean-up
for clean  samples  with about a 90% recovery.  However, at the
point where we had to terminate our work we were experiencing
disturbing  occurrences of excessive contamination in  a large
proportion  of our blanks.   The few  spiked urines we had attempted
to run through the procedure had chroroatograms similar to the
contaminated blanks making it impossible  to tell whether  the
urines were contaminated  as well, or whether the  procedure was
simply inadequate for treating urine samples.

      Under the circumstances, the only position that  I  could
take was that we might have a usable method, but that it is quite
possible that  more or different  clean-up  would  be necessary.
Worse yet,  an entirely new approach  to the problem might be
required i_f what we saw in the spiked urine was not an artifact
similar to what had appeared in many of the blanks.

      At this point, I think it is  urgent  that we discuss whether
or not I will be taking  the  samples to John Tessari in Colorado.
Time is running short for  me in the near  future, since  I  will be
leaving  for  a field study  late  in May.   I  have most of  the
reagents in hand for continuation  of the  Mesurol methodology, if
the chemists at the Colorado PHAP  wish  to  continue along  that
line.

                             Sincerely
                            John T. Leffingwell, Manager
                            California PHAP
cc:  John Tessari
                                                               126
-------
                                                               603
                                       26 April 1985

John Tessari,  Manager
Colorado Pesticide  Hazard Assessment Project
Colorado State University
Fort Collins,  CO
80523
Dear John:
      Enclosed is a copy of the provisional mesurol metabolite
method, as it stood at the  point where we had to quit working on
it.  If it works out that I shall bring the samples to you, I do
have PFBB and 18 crown 6 ether (hexaoxacyclooctadecane)  that I
could bring along, as well as potassium carbonate and the phenol,
itself.  However, as my letter to Gerri Fristrom points out,  this
method may yet be a blind alley, and an entirely new approach may
be required,  to include  the  possibility of running  these samples
on a capillary/FID set-up.  I do not think that the uv spectrum
of the 3,5-dimethylphenol  is good  enough to  do it by HPLC;  al-
though, I would not shy away from re-running  the spectrum of it
again, just in case my crew blew it in preparing the standard for
the spectrophotometer.
                             Sincerely
                             John T.  Leffingwell
                             University of California
                             Bldg.  112, Richmond Field Station
                             47th & Hoffman Blvd.
                             Richmond, CA  94804
                                                                   1 27
Tessari3.1tr
-------
                 Mesurol Urinary Metabolite Meth
                                                                604
                    MESUROL URINARY METABOLITES

 fifltfifi

      The pertinent analytical methods in the literature were for the
 simultaneous determination of Mesurol and its two oxidized forms as
 Mesurol sulfone.  Our goal was to apply this type of analysis to
 Mesurol phenol and its two oxidized forms as they would be found in
 urine.

      Our first findings indicate that the potassium  permanganate
 oxidation method used by Mobay quantitatively destroys  MP  (mesurol
 phenol), MPX (mesurol phenol sulfoxide)  and MFN (mesurol phenol
 sulfone).

      We next found that the m-chloroperoxybenzoic acid (mCPBA) oxi-
 dation  method recovered both MP and MPX as MPN.   The  recovery was
 low,  but no  lower than for MPN, itself, which led us to suspect the
 extraction rather than the oxidation.

      The pH  of the extraction solution turned out to be the problem.
 Mesurol has  no ionizable molecular site,  so that  drastic methods
 could be used to prevent co-extraction of unwanted acidic  materials.
 Up to 40% of the  MPN can be lost at the high pH values used for
 extraction of oxidized mesurol.   By using magnesium  sulfate solution
 to slightly  lower the pH, recoveries very close to 100% have now
 been  obtained.

 Analytical Method

      Equipment and Reagents

 a)  Tilt dispensers:  1 X 10 mL
                      1 X 15 mL   •
                      2 X 20 mL
                      1 X 25 mL
 b)  1 mL high speed pipettor (Brand).
 c)  Rotary evaporator with water  bath.
 d)  13 X 100 mm screw-top culture tube with teflon lined cap (1 per
    sample).
 e)  Test tube rack for 13 mm tubes.
 f)  125 mL separatory funnel with LPE stopper and teflon plug (1 per
    sample).
 g)  Separatory funnel rack.
 h)  250 mL, S 24/40 Round-bottom  flasks  (2 per  sample).
 i)  « 24/40 Stoppers (2 per  sample).
 j)  117 mm OD X 60 mm ID Cork rings  (1 per sample).
 k)  35 mm Polypropylene analytical funnel (2 per  sample).
 1)  Small volumetric flasks with LPE stoppers (1 X 10 mL Qi 1 X 5 mL
    per sample).
m)  4 Dram vials  with teflon lined caps  (1 per  sample).


                               Page  1              6 September 1984
-------
                         Urinary Metabolite  Method


n)   10 mL Volumetric pipefcs (1 per  sample).                 "~
o)   Wash bottle for methylene chloride.
p)   Wash bottle and dropper bottle  for acetonitrile.
q)   Glass wool.
r)   Pasteur pipets (2 per sample).

    Reagents

All solids ace Analytical Grade; all  liquids are HPLC Grade.

a)   CH2Cl2 ~ Methylene Chloride.
b)   CH3CN - Acetonitrile.
c)   H20 - Class ?? Reagent Grade Water  (Milli-Q).
d)   mCPBA - 1% in CH2C12-
e)   MgS04 - 250 g/L In H20.
f)   NaHCC>3 - Aqueous Saturated Solution.
g)   Na2sc>3 - Aqueous Saturated Solution.
h)   Na2SC>4 - Anhydrous crystals.
i)   Dry ice and coolant (2-propanol)  for rotary evaporator.

Prpcedure

     Pipet 10 mL of prepared urine* into a 125 ml separatory funnel;
then add 15 ir.L MgS04 and 20 ml NaHC03. Extract sequentially with 3
X 25 mL portions of CH2Cl2r filtering each through a 35 mm funnel
plugged with glass wool and containing Na2SC>4 into a 250  round
bottom flask, stopper and set aside for rotary  evaporation.

     Rotovap sample to ~  0.25  to 0.50  mL final  volume.  Transfer  to
a culture tube with a pasteur pipet using 4  X 1 mL portions of 1%
mCPBA to rinse the flask.   Seal  the tube and allow the contents to
react at room temperature for at least 20 minutes, but no more than
30  minutes.

     Quantitatively  transfer  the tube contents to a 125 mL separa-
tory funnel containing  20 mL Na2SC>3 solution and shake well to
destroy any  remaining  organo-peroxide.  Then add 15 mL saturated
Na2S04 and 20 mL NaHC03.   Extract with CH2C12 as described above.

     Rotovap  to * 0.5 mL and add 10 mL CH^CN.  Repeat twice more.
Transfer  with CHjCN and pasteur  pipet  to a small volumetric flask (5
or  10 mL)  and make up  to volume. Shake well and put in a 4 dram
vial with proper label.  Turn  the sample over to the HPLC operator
for analysis  of total  MPN.
                              Page 2               6 September 19
-------
DRAFT                     Page 1
                   Mesurol Urinary Metabolite
                        Analytical Method

                   A Provisional Method Using
                    Pentafluorobenzylbr oroide
                         to Derivatize
                       3 , 5-Dimethy Iphenol
 introduction
      While  at the field  study site,  I  decided to store  the
urines in a fashion that had served us well in the past when we
were dealing with phenolic urinary metabolites:  We placed dupli-
cate 20  roL aliguots of  each  subject's  urine  samples in 20 mL
ampules,  adding 1.5 mL of concentrated hydrochloric acid as  a
preservative.   This approach to storage obviates the need  for
refrigeration/  eliminates leak-prone screw-cap closures,  and sets
the sample up for future  hydrolysis of conjugates.  However, good
evidence  exists to show  that the storage  of urine samples con-
taining metabolites of mesurol  [mesurol phenol  (3,5-dimethyl-4-
methylthiophenol) ,  the sulfoxide (3,5-dimethyl-4-methylsulf inyl-
phenol)  and the sulfone (3,5-dimethyl-4-methylsulfonylphenol)J in
strong acid  causes these compounds  to undergo a reaction that
cleaves the sulfur-carbon bond,  leaving the product,  3,5-dimeth-
y Iphenol.

      In an attempt to produce an analyte that could be quanti-
tated by gas chromatography,  I  decided to derivatize  with  penta-
fluorobenzylbromide (PFBB)  and utilize the electron  capture  de-
tector.   I recognize that this approach  is fraught with many
pitfalls;  ECD's are notoriously sensitive to many extraneous
materials that might be  present in the urine samples, and rea-
gents used to hang a handle on an otherwise non-capturing mole-
cule usually derivatize many unwanted compounds,  as  well.  It is
possible  that a  good quality flame ionization detector coupled
with a capillary column  would give sufficient sensitivity  for
underivatized  3,5-dimethylphenol to eliminate the need for  the
BCD and its attendant hypersensitivities.   I did  not  have  such  a
set-up;  so, decided to press on with the  PFBB procedure.

Materials and Methods

      The first step is taken to hydrolyze any remaining conju-
gates of the phenol.  Ten mL of urine is transferred to a 20 mL
ampule and 5 mL of water  is added.  The ampule is sealed  and
heated under pressure (15 Ib. in a standard household pressure
cooker  or 20 Ib.  in a laboratory or clinical autoclave) for 2  hr.
The ampule is opened and the contents are quantitatively  trans-
ferred to a 125 mL separatory funnel with about 40 mL of  water.
Extract  three times with  about 25 mL of methylene chloride.

     At  this point the  methylene  chloride can  be removed  and
replaced  with acetonitrile by rotary evaporation.  (With  care  not
to let the  solvent go completely  dry,  good recoveries of  the


Mesurol  Urinary Metabolite Analytical Method       26 April 1985
-------
                                                         DRAFT


relatively volatile  phenols can  be  realized doing  a  solvent
volume  reduction on  a rotary  evaporator.)   It has not  been
tested, yet,  to determine  whether or not the  derivatization
reaction can be carried out in  the roethylene chloride, either
with or without a prior drying step.  At this  point, the conver-
sion to acetonitrile  is compatible with the subsequent  clean-up
procedure utilizing hexane/water  partitioning.

     Whether the  reaction is to  be  carried out in  methylene
chloride or in acetonitrile (It will also go equally  well in
acetone.),  the  volume of  the sample should be brought to about
1 roL.  Add  20  pL of pentafluorobenzylbromide, 20 mg  potassium
carbonate and 20 mg 18 crown 6 ether.  Seal (We use Teflon-lined,
screw-capped culture  tubes.)  and heat 2 hours at  100° c.   Add
10 mL of hexane and shake well.   Add 5 mL of  water and, again,
shake thoroughly; then allow to settle.

     Pre-clean a silica gel Sep-Pak by running 10 roL of HPLC or
pesticide grade hexane through  it.  Draw off a 3 mL aliquot of
the hexane  layer of the sample with a gas tight syringe and push
very slowly through  the pre-cleaned  silica gel Sep-Pak.   Follow
it with 5 mL of clean hexane. Discard the eluate;  it contains
about 90% of the  residual PFBB.   Finally,  elute the Sep-Pak  with
5 mL of a toluene/hexane  mixture  (70/30 v/v).  Collect  the el-
uate; bring it to a convenient volume; and analyze for the deriv-
ative of the phenol by EC gas chromatography.   We found the HP-
5880A, using a 50 micron Megabore capillary  column,  gave us a
very nice peak with 4 to 10 feroptograms of the derivative.   Un-
fortunately, the same holds true  for the PFBB,  as  well; so, it is
important to have most  of  the  reagent removed before the sample
hits the BCD.
Mesurol Urinary Metabolite Analytical Method        26 April 1985       _.
-------
                                             608
       APPENDIX C
   DATA FILES  RELEVANT TO.
URINARY METABOLITE ANALYSES
                                                 132
-------
                                                                   609
                                         Section  Appendix C
                                         October 15,  1985
                                         Page  1   of  22
                       APPENDIX C

                      Drine Volumes
                         TABLE 1

       Raspberry  Study, Pre-Exposure Urine Samples*

Sample ID        Subject ID          Group           Volume
8301-U-60.
8301-U-60.
8301-0-60.
8301-D-60.
8301-D-60.
8301-D-60.
8301-D-60.
8301-0-60.
8301-D-60.
8301-D-60.
8301-U-60.
8301-U-60.
8301-U-60.
8301-U-60.
8301-0-60.
8301-0-60.
8301-0-60.
8301-0-60.
8301-0-60.
8301-0-60.
8301-0-60.
8301-0-60.
8301-0-60.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
A
A
A
A
B
A
A
B
B
B
B
A
A
B
A
A
A
A
A
A
B
B
B
170
208
630
230
380
300
177
190
209
480
680
310
186
230
630
380
310
252
186
214
300
146
210
     morning void prior to entry  into the field, 11 July 1983.
                                                                   133
-------
                                             Section  Appendix C    / 1 n
                                             October 15, 1985       61 U
                                             Page 2  of  22
                 -.            TABLE 2

         Raspberry Study, First Urine Sample Collection*

   Sample ID        Subject ID          Group            Volume
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
"8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
8301-0-61/62.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
A
A
A
A
B
A
A
B
B
B
B
A
B
A
A
A
A
A
A
B
B
790
305
790
620
380
680
550
234
530
740
740
730
710
450
380
515
620
415
290
290
335
* Overnight samples, Day Two to Day three, 12 to 13 July 1983.
-------
                                             Section  Appendix C      611
                                             October 15, 1985
                                             Page 3  of  22
                             TABLE 3

       Raspberry Study, Second Urine Sample Collection*

  Sample  ID        Subject ID          Group            Volume
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
A
A
A
A
B
A
A
B
B
B
B
A
B
A
A
A
A
A
A
B
B
194
104
216
100
124
N/S
N/S
N/S
N/S
224
280
172
114
150
410
175
N/S
N/S
N/S
N/S
N/S
* Samples collected during working hours of Day Three, 13 July 1983.


                                                                       135
-------
                                            Section  Appendix C
                                            October 15,  1985
                                            Page 4  of  22

                            TABLE 4

         Raspberry Study, Third Drine Sample Collection*

   Sample ID        Subject ID          Group            Volume
612
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
8301-0-62/63.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
A
A
A
A
B
A
A
B
B
B
B
A
B
A
A
A
A
A
A
B
B
770
345
710
270
470
221
153
138
300
700
570
655
435
550
285
730
865
240
281
274
Lost by Subject
* Overnight sample,  13  to 14 July 1983.
                                                                   136
-------
                                            Section   Appendix C     & 1 7.
                                            October  15,  1985         ° 'J
                                            Page 5   of   22
                           TABLE  5

      Raspberry Study, Fourth Urine Sample Collection*

 Sample ID        Subject  ID          Group             Volume
8301-U-63.
8301-0-63.
. 8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
8301-0-63.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
A
A
A
A
B
A
A
B
B
B
B
A
B
A
A
A
A
A
A
B
B
123
190
280
92
138
400
265
80
170
430
380
72
232
156
190
170
250
132
170
214
218
Samples collected during working hours of Day Four, 14 July 1983.


                                                       137
-------
                                             Section  Appendix  C
                                             October  15,  1985        L \ A
                                             Page 5   of   22         ° ' H

                             TABLE 5

        Raspberry Study, Fourth Drine Sample Collection*

   Sample ID        Subject ID          Group             Volume
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
8301-0-62.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
A
A
A
A
B
A
A
B
B
B
B
A
B
A
A
A
A
A
A
B
B
123
190
280
92
138
400
265
80
170
430
380
72
232
156
190
170
250
132
170
214
218
* Samples collected during working hours of Day Four, 14 July 1983.
                                                                  138
-------
                                            Section  Appendix C      , ,  ,_
                                            October 15, 1985         6 I  5
                                            Page 6  of  22
                            TABLE  6

          Blackberry  Study, Pre-Exposure Urine Samples*

   Sample ID       Subject ID          Group            Volume
8302-D-17.
8302-0-17.
8302-D-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-18.**
8302-0-18.**
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-18.**
8302-0-17.
8302-0-17.
8302-0-17.
8302-0-17.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
21
22
23
24
28
29
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
***
***
B
B
B
B
B
B
615
390
740
235
277
306
224
275
930
950
515
178
264
204
335
450
110
254
395
255
430
366
260
390
* First morning  void prior to entry  into the field, 18 July 1983
** Subjects  15,16,  and  22 joined the study on Day 2.
*** Subjects 17  and 18  were dropped  from the study.
                                                                  139
-------
                                             Section Appendix C
                                             October 15,  1985
                                             Page  7   of   22

                             TABLE 7

        Blackberry Study, First Urine Sample Collection*

   Sample ID        Subject ID          Group           Volume
8302-0-18/19.
8302-U-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19.
8302-0-18/19*
8302-0-18/19.
8302-0-18/19.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
21
22
23
24
28
29
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B .
B
B
B
B
B
B
930
780
750
400
148
266
182
224
800
584
1040
242
130
160
720
380
470
580
960
326
455
480
* Overnight samples,  Day Two to  Day  Three,  19 to 20 July 1983
6\i
                                                                    140
-------
                                             Section  Appendix C      £ 1 7
                                             October 15, 1985         ° ' '
                                             Page 8  of  22
                             TABLE 8

       Blackberry  Study,  Second Urine Sample Collection*
                  \
  Sample ID         Subject ID          Group            Volume
8302-D-19.
8302-U-19.
8302-D-19.
8302-D-19.
8302-0-19.
8302-U-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
8302-0-19.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
21
22
23
24
28
29
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
B
B
290
730
102
345
32
144
214
180
175
870
172
230
55
160
190
135
358
N/S
138
290
378
N/S
* Samples collected during working hours of Day Three,  20  July 1983.

                                                                       141
-------
                                             Section  Appendix C
                                             October 15,  1985        , . .
                                             Page 9  of   22          618
                             TABLE 9

        Blackberry Study, Third Drine Sample Collection*

   Sample ID        Subject ID          Group            Volume
8302-D-19/20.
8302-U-19/20.
8302-0-19/20.
8302-D-19/20.
8302-0-19/20.
8302-D-19/20.
8302-D-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
8302-0-19/20.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
21
22
23
24
28
29
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
B
B
650
670
405
228
254
258
328
250
N/S**
N/S**
N/S**
N/S**
N/S**
N/S**
840
760
860
495
800
520
335
660
* Overnight samples, Day Three to Day Four,  20  to  21  July  1983.
** Subjects 9, 10, 11, 12,  13 and 14 dropped out of the  study.
-------
                                         Section  Appendix C
                                         October 15, 1985
                                         Page 10 of  22
                        TABLE  10                           t
     Blackberry Study,  Fourth Orine Sample Collection*
Sample ID        Subject ID         Group            Volume
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
8302-0-20.
Samples collected
1
2
3
4
5
6
7
8
15
16
21
22
23
24
28
29
during working hours of
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
Day Three,
178
N/S
248
256
126
178
228
305
195
130
700
66
220
190
365
430
20 July 1983.
                                                                     143
-------
                                             Section  Appendix C
                                             October  15, 1985
                                             Page  11  of  22
                            TABLE 11

        Blackberry Study, Fifth Drine Sample Collection*

   Sample ID        Subject ID          Group           Volume
62C
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
8302-0-20/21.
1
2
3
4
5
6
7
8
15
16
21
22
23
24
28
29
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
375
800
790
355
220
210
176
315
588
740
820
315
730
710
1040
810
* Overnight samples,  Day Four  to Day Five, 21 to 22 July 1983.
                                                                   144
-------
                                             Section  Appendix C
                                             October 15, 1985
                                             Page 12 of  22

                             TABLE 12

       Blackberry  Study,  Sixth  Orine Sample Collection*

  Sample ID        Subject  ID          Group            Volume
8302-U-21.
8302-0-21.
8302-D-21.
8302-D-21.
8302-0-21.
8302-D-21.
8302-D-21.
8302-0-21.
8302-0-21.
8302-0-21.
8302-0-21.
8302-0-21.
8302-0-21.
8302-0-21.
8302-0-21.
8302-0-21.
1
2
3
4
5
6
7
8
15
16
21
22
23
24
28
29
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
172
360
160
166
110
43
140
66
80
80
410
N/S
220
610
420
370
* Samples collected during working hours of Day Four, 21 July 1983.
                                                                   145
-------
                                             Section  Appendix C   622
                                             October 15, 1985
                                             Page 13 of 22

                            TABLE 13

          Blueberry Study, Pre-Ezposure Urine Samples*

   Sample ID        Subject ID          Group            Volume
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3. •
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
8303-0-2/3.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
25
26
B
A
A
A
A
A
A
A
A
A
A
A
B
B
B
A
B
B
B
B
B
B
B
A
126
190
230
140
690
154
510
830
390
810
640
820
226
320
460
265
305
250
130
340
410
340
380
N/S**
  First morning void prior to entry into the field, 11 July 1983.
** Subject 26 was the same person as Subject 24 in the Blackberry
Study (8302); therefore, use sample 8302-0-21.24 as this person's
pre-exposure sample for this study.
-------
                                           Section  Appendix C
                                           October 15, 1985       £23
                                           Page 14 of  22         D^J
                          TABLE 14
       Blueberry Study,  First Urine  Sample  Collection*
 Sample ID        Subject ID         Group           Volume
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
8303-0-4/5.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
25
26
B
A
A
A
A
A
A
A
A
A
A
A
B
B
B
A
B
B
B
B
B
B
B
A
77
270
330
700
440
266
540
355
490
480
620
810
350
640
990
590
800
360
700
430
920
1340
670
860
Overnight  samples.  Day Two to Day Three, 26 to 27 July 1983.
                                                                 147
-------
                                              Section  Appendix C    , . ,
                                              October 15, 1985       624
                                              Page 15 of  22
                             TABLE 15
        Blueberry Study,  Second Urine Sample Collection*
   Sample ID        Subject  ID          Group            Volume
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
8303-0-5.
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
25
26
B
A
A
A
A
A
A
A
A
A
A
A
B
B
B
A
B
B
B .
B
B
B
B
A
260
640
240
N/S
N/S
N/S
N/S
N/S
N/S
N/S
172
300
N/S
194
N/S
N/S
N/S
320
340
N/S
760
910
380
810
* Samples collected during working hours of Day Three, 27 July 1983.
-------
UNIVERSITY OF CALIFORNIA
                        625
BERKELEY • DAVIS • IRVINE • LM ANGELES • RIVERSIDE • SAN DIECO • SAN FRANCISCO
                                                      SANTA BARBARA • SANTA CRUZ
COLLEGE OF ENGINEERING
SANITARY ENGINEERING
 RESEARCH LABORATORY
RICHMOND FIELD STATION. BLDG. 112
47TH Jr HOFFMAN BLVD.
RICHMOND. CALIFORNIA MS04
413-231-MOO
                                 GROUP B
            INSTRUCTIONS FOR PARTICIPANTS  IN UNIVERSITY STUDY
         You have volunteered to participate in an important field
    study  in  which  we are  trying to  investigate  the absorption
    of pesticides through the skin of persons working in fields which
    have been  sprayed with pesticides. As fruit pickers, you may have
    been exposed to  very small quantities of  pesticides which may
    remain  on leaves  and fruit  from  a previous  spray to control
    insects or plant diseases.
         Both Group  B,  to which you belong, and Group A (the other
    participants)  will be collecting their  urine throughout the study.
         The study in which you are participating will commence on
    Sunday night and  will be  completed  at the end  of  the work  day on
    Friday  of that  week. It  is  important that you  follow  these
    instructions and that you try to complete ALL SIX DAYS  of the
    study.  If you must drop  out of the  study for  one reason or
    another,  please  notify your  foreman  or any  of  the University
    people who  will  be working with you during this week. But, we
                                                                     149
-------
                                                                    626
urge you to try to work with your fellow participants and tough
it outl
     Here then are the simple instructions  which we will ask you
to follow.  Again, if you  have any questions or run  into any
trouble, please contact  your  foreman or any of the  University
people right away.
                    Sunday Eight and Monday
     At the  end of  this  briefing  you  will receive 2  plastic
bottles.  One has  black markings  (Night Bottle) and the other
is a collapsible container marked "Specimen Storage  Container"
(Overflow Container).  We will now demonstrate how to assemble
the Overflow Container.
     On Sunday night before you go  to bed and on Monday  morning
as you wash  up, we want you to collect all of  your  urine into
your black-marked Night Bottle.  If your Night Bottle ever becomes
full, deposit all  excess urine  into  your Overflow Bottle.  Please
store  these bottles  in  a cool  place (for  example,   in  your
refrigerator).  Bring  both of your bottles into the field  on
Monday morning and give  them to the University  person in charge
of bottle collecting.
                           Tuesday

     At the  end  of your work day, return to the  Control Station
where we shall  give you a  new  Night Bottle and a new Overflow
Bottle to take home. Please collect ALL  OF  YOUR URINE into these
bottles,  storing them in a cool  place, just like  before. When you
return to work on  Wednesday morning, bring  both  of these bottles
                                                               '    150
-------
                                              GROUP B

                                                                 627
vith you and hand them to the personnel at the Control Station.

                 Wednesday.  Thursday. j| Friday

     On the mornings of each  of  these three days, before  you
enter the field, please give  your  Night and Overflow  bottles,
which you have brought with you  from home,  to the University
person on duty. You  will then be  handed  a new white plastic
bottle  (your Day Bottle) which  will  be marked with your  name  and
number.  We  want  you to collect all  of  your urine into this
bottle during the  time that you are in the field.   Next  to  the
toilet  facilities,  we have provided  several ice chests   in which
we want you to store your Day Bottle while not in use.
     At the  end of  the work day on Wednesday and Thursday, we
will issue you a new  Night  Bottle and a new  Overflow Bottle in
which we want you  to  collect all  of your urine until you  return
to the  field in the morning  with the bottles, just like before.
     On Friday,  the experiment will be over at the end  of  the
work day.  At that  time you  give your last Day Bottle to us.
IP YOU HAVE  ANY QUESTIONS, PLEASE  ASK ANY OP THE UNIVERSITY
PERSONNEL,  AND  THEY  SHALL GLADLY ANSWER  ANY  AND ALL OF YOUR
QUESTIONS.
    Thank  you very much  for  agreeing to participate in this
important study  which is significant for the  health of all
agricultural field workers  in Oregon and across the country.
         State University  of Oregon, Corvallis
         University of California, Berkeley
                                                                151
-------
                         TABLE  16

      Blueberry Study,  Third Urine

Sample ID        Subject  ID
                                         Section  Appendix C
                                         October 15, 1985
                                         Page 16 of  22
Sample Collection*

  Group            Volume
                             628
s-
8303-D-5/6.
8303-0-5/6.
83 03-D- 5/6.
8303-D-5/6.
83 03-D- 5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
8303-0-5/6.
* Overnight samples,
** Subject 6 dropped

1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
25
26
Day Three to Day
out of the study.

B
A
A
A
A
A
A
A
A
A
A
A
B
B
B
A
B
B
B
B
B
B
B
A
Four, 27 to

148
62
430
910
420
N/S**
214
174
400
580
480
590
330
450
630
1010
1030
188
122
960
430
660
230
1000
28 July 1983.
-------
                                             Section  Appendix C
                                             October 15, 1985
                                             Page 17 of  22
                            TABLE 17
        Blueberry Study, Fourth Urine Sample Collection*
   Sample ID        Subject ID          Group            Volume
8303-D-6.
8303-0-6.
8303-U-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
8303-0-6.
1
2
3
4
5
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
25
26
B
A
A
A
A
A
A
A
A
A
A
B
B
B
A
B
B
B
B
B
B
B
A
N/S
N/S
N/S
N/S
N/S
266
154
330
270
N/S
380
N/S
N/S
N/S
N/S
190
N/S
N/S
N/S
N/S
N/S
159
N/S
* Samples collected during working hours of Day Four, 28 July 1983.
                                                                    153
-------
                                            Section  Appendix C
                                            October 15, 1985
                                            Page 18 of  22

                            TABLE  18

         Blueberry Study,  Fifth  Urine Sample Collection*

   Sample ID        Subject ID         Group            Volume
8303-D-6/7.
8303-0-6/7.
8303-D-6/7.
8303-D-6/7.
8303-D-6/7.
8303-D-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
8303-0-6/7.
1
2
3
4
5
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
25
26
B
A
A
A
A
A
A
A
A
A
A
B
B
B
A
B
B
B
B
B
B
B
A
395
447
152
940
435
1010
635
298
608
146
595
505
620
415
685
1015
120
235
425
780
1230
750
805
* Overnight samples,  Day  Pour to Day Five, 28 to 29 July 1983.

     Sample Volumes marked "N/S" mean that no sample was collec-
ted for that time period.  This was the case for many subjects
who did not urinate during the  "Work" period.  Thier total urine
out-put was collected,  but in the  "Night" or  "Off Work" period.
630
154
-------
                                                            Section Appendix C
                                                            October 15,  1985
                                                            Page 19 of 22
                                                                                    63f
                                      Table 19
ABSTAT 3.00
RASPBERRY STUDY, TIME WORKED DATA
FILE:  8301-B
REVIU
COMMAND* PRIHT DATA
HISSING VALDE TREATMENTt  INCLUDE
VARIABLES!
CASE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1 SUBJECT
1.00000
2.00000
3.00000
4.00000
€.00000
7.00000
12.0000
15.0000
16.0000
17.0000
18.0000
19.0000
20.0000
5.00000
8.00000
9.00000
10.0000
11.0000
13.0000
14.0000
21.0000
22.0000
23.0000
2 GROUP
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
•
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
3 BOURS1
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
5.00000
4 BOURS2
5.40000
5.40000
5.40000
5.40000
MISSING
5.40000
5.40000
5.40000
5.40000
5.40000
5.40000
5.40000
MISSING
5.40000
5.40000
5.40000
5.40000
2.30000
5.40000
5.40000
5.40000
5.40000
5.40000
5 BOURS3
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
3.70000
6 BOURS4
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.50000
4.00000
4.50000
4.50000
                                                                                   155
-------
                                                             Section Appendix C
                                                             October 15,  1985
                                                             Page 20 of 22
                                       Table  20
ABSTAT 3.00
BLACKBERRY STUDY, TIME WORKED DATA
PILEs 8302-H
REVI 7
COMMAND: PRINT DATA
MISSING VALOE TREATMENTS INCLUDE
VARIABLES :
CASE
1
2
3
4
5
6
^
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
1 SUBJECT
1.00000
2.00000
3.00000
4.00000
5. 00000
6.00000
7.00000
8.00000
9.00000
10.0000
11.0000
12.0000
13.0000
14.0000
15.0000
16.0000
21.0000
22.0000
23.0000
24.0000
28.0000
29.0000
2 GROUP
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
3 BOURS1
6.50000
6.50000
5.83330
6.83300
6.83300
5.83300
6.50000
6.83300
5.83300
5.50000
5.50000
5.50000
5.50000
5.50000
0.00000
0.00000
5.20000
0.00000
5.20000
4.60000
6.50000
6.50000
4 BODRS2
4.83300
4.83300
4.83300
4.83300
4.83300
4.83300
4.83300
4.83300
3.33300
3.75000
3.75000
3.75000
3.80000
3.80000
4.90000
5.00000
0.00000
5.00000
0.700000
1.00000
6.50000
6.50000
5 BOORS3
5.75000
5.75000
5.75000
5.75000
5.75000
5.75000
5.75000
5.75000
4.00000
4.00000
4.00000
4.00000
4.10000
3.90000
2.60000
2-.80000
6.40000
2.80000
6.40000
4.70000
7.80000
7.80000
6 BODRS4
6.50000
6.50000
6.50000
6.50000
6.50000
6.50000
6.50000
6.50000
MISSING
MISSING
MISSING
MISSING
MISSING
MISSING
4.60000
5.10000
4.10000
5.10000
4.30000
MISSING
5.90000
5.90000
7 BOORSS
4.50000
4.50000
3.83300
4.50000
4.50000
4.50000
4.50000
4.50000
MISSING
MISSING
MISSING
MISSING
MISSING
MISSING
2.70000
2.70000
4.80000
1.40000
4.90000
3.10000
5.10000
5.10000
                                                                                   156
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                                                            Section Appendix C
                                                            October 15,  1985
                                                            Page 21 of 22
                                                                                      633
                                       Table 21
ABSTAT 3.00
BLUEBERRY STDDT, TINE WORKED DATA
FILEi  8303-HT
REVI  9
COMMANDi PRINT DATA
HISSING VALUE TREATMENTI  INCLUDE
VARIABLES s
CASE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
21
22
23
24
1 SUBJECT
2.00000
3.00000
4.00000
5.00000
6.00000
7.00000
8.00000
9.00000
10.0000
11.0000
12.0000
17.0000
26.0000
1.00000
14.0000
15.0000
16.0000
18.0000
19.0000
20.0000
21.0000
22.0000
23.0000
25.0000
2 GROUP
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
3 HOORSl
7.27000
6.40000
4.85000
7.67000
4.88000
7.72000
4.98000
7.55000
7.52000
5.98000
4.980.00
4.93000
6.80000
7.27000
7.89000
7.58000
7.73000
7.77000
7.73000
7.67000
7.73000
7.65000
7.65000
7.60000
5 BOORS 2
7.28000
6.57000
5.75000
6.28000
6.02000
7.62000
5.77000
7.42000
7.75000
5.68000
5.70000
6.37000
7.28000
2.50000
7.18000
7.95000
7.08000
MISSING
7.50000
7.37000
8.00000
7.17000
7.17000
8.50000
7 BOURS3
0.750000
0.750000
0.500000
1.00000
1.00000
3.50000
3.42000
3.50000
3.50000
3.42000
3.17000
0.300000
1.25000
0.00000
1.34000
0.00000
1.58000
0.330000
MISSING
MISSING
3.25000
2.75000
2.75000
2.58000
9 BOURS4
3.00000
2.90000
MISSING
6.45000
MISSING
7.33000
8.22000
7.33000
7.33000
7.16000
7.33000
5.35000
3.25000
MISSING
6.45000
6.45000
4.87000
4.87000
MISSING
MISSING
6.22000
MISSING
MISSING
5.87000
                                                                                        157
-------
                                                           Section Appendix C
                                                           October 15, 1985   '
                                                           Page 22 of 22
                                                        634
                                     Table 22
ABSTAT 3.00
BLUEBERRY STUDY, TIELD DATA
PILE: 8303-HT
                                                                                     REV* »
COMKAMDt PRINT DATA
MISSING VALOE TREATMENT: INCLUDE
VARIABLES S
CASE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
1 SUBJECT
2.00000
3.00000
4.00000
5.00000
6.00000
7.00000
8.00000
9.00000
10.0000
11.0000
12.0000
17.0000
26.0000
1.00000
14.0000
15.0000
16.0000
18.0000
19.0000
20.0000
21.0000
22.0000
23.0000
25.0000
2 GROUP
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
1.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
2.00000
4 TIBLDKG1
41.9501
19.0476
46.7120
32.1996
42.6304
91.8368
32.3129
66.6667
94.7846
21.5420
32.3129
17.6871
45.5782
22.6757
36.0544
61.6780
55.3288
77.3243
45.5782
52.1542
91.8368
45.3515
38.5488
47.8458
6 YIELDKG2
46.2585
17.9138 •
43.7642
14.5125
47.1655
98.6395
43.5374
68.7075
84.1270
21.7687
43.5374
29.0250
59.4105
18.1406
31.9728
58.0499
29.0250
MISSING
46.2585
54.8753
102.494
36.2812
36.2812
49.4331
8 YIELDKG3
2.49433
1.36054
0.00000
MISSING
MISSING
58.5034
MISSING
56.6893
54.4218
MISSING
MISSING
MISSING
MISSING
0.00000
MISSING
0.00000
0.00000
MISSING
2.49433
4.30839
60.7710
MISSING
MISSING
16.7801
10 TIELDKG4
24.7166
13.1519
MISSING
46.7120
MISSING
99.7733
68.0272
75.7370
95.0114
29.4785
58.9570
MISSING
22.6757
MISSING
40.1361
53.7415
MISSING
MISSING
26.9841
31.9728
108.617
MISSING
MISSING
MISSING
                                                                               158
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                                            635
        APPENDIX D



     CONSENT FORMS AND



INSTRUCTIONS FOR PARTICIPANTS
                                              159
-------
UNIVERSITY OF CALIFORNIA
                                                               636
BERKELEY • DAVIS • IRVINE • UM ANGELES • RIVERSIDE • SAN DIECO • «AN FRANCISCO  ij
                                                SANTA BARBARA • SANTA CRUZ
 COLLEGE OF ENGINEERING
 SANITARY ENGINEERING
  RESEARCH LABORATORY
                                    RICHMOND FIELD STATION, BLOC. 112
                                    47TH * HOFFMAN BLVD.
                                    RICHMOND, CALIFORNIA 04804
                                    415-231-9400
                   STUDY OF PESTICIDE EXPOSURE AMONG
                           BERRY HARVESTERS
       CONSENT TO ACT AS SUBJECT FOR RESEARCH AND INVESTIGATION
 Subject's Name.
                                           .Date.
 2.
The Pesticide Hazard Assessment Project at the  University of
California wishes to study the amount of dust and pesticides in
your workplace.  We want to measure your level of exposure to
pesticide residues and to evaluate  its health  hazard.  If you
agree to  participate, we  will  ask you  to  wear  some sample col-
lectors during your workday.  We  will provide you with:

     (1)   gauze patches  taped to  an arms and legs like small
          bandages,
     (2)   a T-shirt with patches  attached,
     (3)   cotton work gloves, and,  perhaps
     (4)   a pump worn on your belt with a dust collector on your
          shoulder.

This study also calls for the collection of  all  of each person's
urine for a maximum  of  four days.  If you choose to participate
in the study, you will  be provided with containers and be given
thorough instructions for their use.

After your work, we will collect these samples  and  take them
back to  our laboratory for analysis.  We  will then evaluate
these measurements as they  might affect your health,  or that of
your co-workers.  Therefore, we  ask  for your cooperation.  Your
participation in this study is purely voluntary.  It will have
no effect on your employment status here this  summer.   We would
like to  sample for  nearly  the whole workday,  but you can end
your participation at any time.

I understand that  the study  in  which I  am participating
involves:
      b.
     The wearing of patches that act as collectors of dust and
     pesticides as  they fall on roe while  I work.

     The possibility  of wearing a small portable air sampling
     device while working during the  study period.
      c.   The collection of urine samples  for  up  to  4 days.
                                                                       160
 Rev. 22 Jun 83
-------
                                                                637
Page 2                                                 Consent Form


3.   I hereby authorize 	»  or other such
     qualified assistants,  as  may be  selected by Dr.	,
     to collect urine, patch and air samples.

4.   The procedures and  investigation in which I  am participating
     have been explained  to me by	.

5.   I understand that the urine, patch and air sampling procedures
     may involve some  annoyance or inconvenience.

6.   I understand that Dr.	and/or such
     qualified assistants as may  be  selected by him will  answer any
     questions I may have at any  time concerning the study.  I under-
     stand that I may withdraw from the study at  any time.  I also
     understand that if I do withdraw, it will in  no way  jeopardize
     my employment.

7.   I understand that no. unusual or extraordinary  pesticide applica-
     tions have been made for  the purposes of this  study.

8.   I understand that  I  will be paid a bonus of  $20.00  for the
     completion of urine  sampling over a maximum of four days.

9.   I understand that my name will not be used in any  context or in
     any way connected with the use of results from any of the col-
     lection procedures.
                                         Subject's Signature
                                    Parent or Guardian's Signature
                                               Witness
                                                                    161
Rev.  22 Jun  83
-------
UNIVERSITY OF CALIFORNIA
BERKELEY • DAVIS • IB VINE • LOS ANGELES • RIVERSIDE • SAN DIECO • (AN FRANCISCO
                         638
                                                       SANTA BARBARA • SANTA CBfZ
COLLEGE OF ENGINEERING
SANITARY ENGINEERING
 RESEARCH LABORATORY
RICHMOND FIELD STATION. BLDC. 112
47TH fc HOFFMAN BLVD.
RICHMOND. CALIFORNIA 04804
415-S31-MOO
                                  GRODP A
             INSTRUCTIONS FOR PARTICIPANTS IN UNIVERSITY STUDY
          You have  volunteered to participate in an important field
     study  in which we  are trying  to investigate  the absorption
     of pesticides through the skin of persons working in fields which
     have been sprayed with pesticides. As  fruit pickers,  you may  have
     been exposed to very small  quantities of pesticides which may
     remain on leaves and fruit from a  previous spray to control
     insects or plant  diseases.
          In order to measure concentration of pesticides on the  skin,
     Group A, to which you belong, will be fitted with cotton gloves
     for hand exposure and cotton patches  for  exposure to the rest  of
     the body. Both Group A and Group  B (the other  participants) will
     be collecting their urine throughout the study.
          The study in which you  are participating will commence  on
     Sunday night and will be completed at the end of  the work day  on
     Friday  of  that  week.  It  is important  that you follow these
     instructions and that you try to complete ALL SIX DAYS of the
     study.  If you  must drop  out of  the study  for one  reason  or
                                                                     16;
-------
                                                               639
another, please  notify your foreman or any  of  the University
people who will  be working with you during this week. But, we
urge you to try to work with your fellow participants and tough
it outl
     Bere then are the simple instructions which  we  will ask you
to follow. Again,  if you  have  any questions or run  into any
trouble, please  contact your  foreman or any of  the University
people right away.

                   Sunday Night  and Monday
     At  the end  of this briefing you  will receive 2  plastic
containers. One is a bottle with black markings (Night Bottle)
and the other is a collapsible container marked "Specimen Storage
Container"  (Overflow Container).  We will now demonstrate how to
assemble  this container.
     On Sunday night before you  go to bed and on  Monday morning
as you wash up,  we want you to  collect aJLL of your urine into
your black-marked Night Bottle. If your Night Bottle ever becomes
full, deposit all excess urine  into your  Overflow Container.
Please store the containers  when used  in a cool  place (for
example,  in your  refrigerator). Bring your Night Bottle  into the
field on  Monday morning  and give  it to the  University person in
charge of specimen collecting.  (If you  had  to use the  overflow
container, bring that with you into the  field.)
     We will issue you a pair of white cotton gloves which may
decrease  your dermal pesticide exposure. When the gloves become
too dirty or wet, please go to the Control Station (a University
                                                                  163
-------
vehicle) but d_e na£ try. t£ re.mojte_ yfiiir slaves. We will  remove
your gloves and issue you another,  new  pair.
                            Tuesday
    »Before you go into the field to pick berries on Tuesday, go
                                                        •
to the Control Station and you will be issued gloves, just like
on  Monday, and you will  be outfitted with cotton  patches on
different  parts of your body. You will keep the patches  on all
day since  they will not become too soiled. If, however, a patch
should  come loose, please  notify  your  foreman or  University
personnel. We'll be there  to help youl If the gloves  become too
dirty or wet,  please notify us,  and  we  shall issue  a new pair of
gloves to you. Do  not try to remove the gloves yourself!  During
your lunch hour, let us remove your  gloves,  and we shall issue
you a new set of gloves when  you return to work  after lunch.
     At the end of your work day, return to the Control Station,
and we  shall  remove your  gloves and patches  for the  day  Just
before you go home, we shall give you  a new  Night Bottle and a
new  Overflow  Bottle to take home. Please collect ALL OF  YOUR
URINE into  these bottles, storing them in a  cool place, just like
before.  When you return to  work  on Wednesday morning,  bring  both
of these bottles with you and hand them to the  personnel  at the
Control  Station.

                 Wednesday.  Thursday, £ Friday

     On  Wednesday morning, before you enter the field,  please
give your Night and Overflow  bottles, which  you  have brought with
you from home,  to  the University person on  duty. Again,  you  will
                                                                  164
-------
                                                                 64!
be issued gloves and patches just like on Tuesday. In addition,
on each  of  these  three days  you  will be  handed a new white
plastic  bottle  (your Day Bottle)  which  will  be  marked with  your
name and number.   We want you to collect all of your urine  into
this bottle  during the time that you  are in  the field.    Next to
the toilet  facilities, we have provided several ice chests in
which we want you to store your Day Bottle while not in use.
     Gloves will  be changed by us at the lunch break,  and new
gloves will be issued to  you if needed,  just like before. On
                                              i
Thursday and Friday you will only be issued gloves  and not patches.
     At  the  end of  the work day on Wednesday and Thursday, we
will issue you a new Night Bottle  and  a new Overflow Bottle in
which we want you  to collect all of your urine  until you return
to the field in the morning with  the bottles,  just  like before.
     On  Friday, the experiment will be over at the end of the
work day.  At that time you give  your  last  Day Bottle to us.
IF YOU HAVE ANY QUESTIONS,  PLEASE ASK ANY OF  THE UNIVERSITY
PERSONNEL,  AND THEY  SHALL GLADLY ANSWER ANY AND ALL OF YOUR
QUESTIONS.
    Thank  you  very much for agreeing  to participate in this
important study which is significant  for the health  of all
agricultural field  workers in Oregon and  across the country.
         State University of Oregon,  Corvallis
         University  of California,  Berkeley
                                                                  165
-------
UNIVERSITY OF CALIFORNIA, BERKELEY
BERKELEY • DAVIS • IRVINE • LOS ANGELES • RIVERSIDE • SAN DIEGO • SAN FRANCISCO
SANTTABY ENGINEERING AND ENVIRONMENTAL
    HEALTH RESEARCH LABORATORY
      COLLEGE OF ENGINEERING
      SCHOOL OF PUBLIC HEALTH
                                                                       642
                                                           SANTA BARBARA • SANTA CRUZ
                                           MAILING ADDRESS:
                                           UNIVERSITY OF CALIFORNIA
                                           RICHMOND FIELD STATION, BLDC. Ill
                                           1301 S. 4Mi STREET
                                           RICHMOND, CALIFORNIA M804-4WB
                                           (415) B1-M49


                                           24 October 1985
 Dr.  Geraldine Fristrom
 PSSP Laboratory  Coordinator
 EAB/HED/OPP   (TS-769-C)
 United States Environmental Protection Agency
 401  M Street, SW
                                                   RE:  CR-810691-02-0
Washington, D.C.   20460

Dear Gerrie:

      Attached is  a corrected  page  five for Appendix C  of the

final report we  just handed you.  While working over some  of the

files that had gone into the  production of  the report,  I  discov-

ered that this one table had  the incorrect  Sample ID;  so,  I have

corrected it in  all copies but  yours.

      I hope your trip to West Coast  is considered successful.   I

presume that you have things  at Davis all squared away, and that

both you  and Jim are happy.

                                Sincerely
 Encl.
                                                                          166
-------
                                                643
An Assessment of Exposure  of Okra Harvesters
  to Carbaryl
        Research performed  by

        Texas Tech University
        San Benito, TX  78586

        February 28, 1986
-------
                                                                             644
In behalf of the  Texas  PHAP the undersigned have reviewed and approved the
report draft entitled "An Assessment of Exposure of Okra Harvesters to
Carbaryl ."
             Qual i ty  Assurance Of ficer                    Date
                                                         Date
                                    ii
-------
                                                                           645
==============================================================================
                             TABLE OF CONTENTS
                             ===================
Section                                                                 Page

ABSTRACT 	   1 v

INTRODUCTION	    1

BACKGROUND 	    6

fCTHODS AND PROCEDURES	    8

RESULTS	   13

INTERPRETATION AND ANALYSIS  	   17

FIGURES	   20

TABLES	   21

ACKNOWLE DGEMENTS	   25

LITERATURE CITED 	   26
================================5=============================================
                                  111
-------
     Abstract.   Human exposure to residues  of carbaryl (1-Naphthyl N-           646
methylcarbamate) was assessed in  a  study  group of Individuals re-entering
a 10 acre field of okra  immediately after an aerial application of a wettable
powder formulation.  Deposition of carbaryl was examined on artificial
substrates,  elevated panels,  as well  as on  foliage  and soil.  Residues of
carbaryl  appeared to be  uniformly distributed over  the foliage canopy.  The
mean concentration detected on panels (6.04 _+ 3.35 ug/cm2) elevated within the
canopy was not significantly  different than the mean concentration detected in
leaves (9.37  +_ 5.24 ug/cm2).  Concentrations detected  in  leaf samples collected
near the canopy were not signficantly different than concentrations detected
in leaf samples obtained from below the canopy.  The lowest mean concentration
was detected in soil (0.408 +_ 0.297 ug/cm2).  The  transfer of residues to the
workers was  assessed through the examination of residue concentrations on
sampling devices, 100 cm2 gauze patches,  located on outside and inside sleeves
and the chest pockets of cotton chambray  shirts worn  by  the  subjects.
Significantly greater concentrations  of carbaryl were detected on outside
sleeves  (8.61 ^2.59 ug/cm2) than on chest patches (3.06_+1.38 ug/cm2).
Concentrations of carbaryl  detected on  outside sleeves were  not signficantly
different than  concentrations  detected on  inside  sleeves  (5.53 +_ 3.35 ug/cm2).
Residues of carbaryl appeared to  accumulate on outside arm patches and
penetrate the cotton chambray shirt.  Urine samples analyzed  for  the
metabolite  of  carbaryl, 1-napthol, indicated  dermal absorption of carbtry"!
(0.037 +_ 0.005  ug/mg creatinine/ml).  Immediate health effects from this
level of exposure appeared remote.  The burden on  metabolic  and excretory
processes from  such  an exposure for an extended period might require  further
investigation.
                                    iv
-------
                                                                          647
           AN  ASSESSMENT  OF  EXPOSURE OF OKRA HARVESTERS TO CARBARYL

                                 INTRODUCTION

     Occupational  exposure to  carbaryl has been extensively reviewed by the
National Institute of Occupational  Safety and  Health (NIOSH, 1976) and the
World Health Organization (WHO,  1982).   NIOSH (1976) estimated  that 10,000
workers in the U.S.  may be exposed  to carbaryl every year including
agricultural  crop workers, fanners, plant  nursery workers and  spray pilots.
A case study (NIOSH,  1976) of  agricultural workers exposed  to carbaryl in the
Soviet Union (Yakim. 1967) indicated  no change in physiological functions
before or after work, although whole blood cholinesterase activity was
depressed 11-22% in individuals involved in loading to  a  high of  30% in aerial
signalers.  Airborne  concentrations of carbaryl were contrasted among the
loading site (2 mg/M3) and the concentrations  (4  mg/M3) detected  in the fields
where signalers were exposed and within  the aerial  applicators  cabin  (7
mg/M3).  Concentrations detected in the cabin  of  aircraft used  to spray
carbaryl exceeded threshold  limits  (5 mg/M3) most recently  utilized by the
American Conference  of Governmental Industrial Hyglenists  (ACGIH, 1984).
Although concentrations appeared to exceed threshold limits within the aerial
applicators workspace, the origin of  the residues and  the extent  of exposure
to the pilots was  not  given (NIOSH, 1976).
-------
                                                                          648
     In another assessment of risk to workers occupationally  exposed to
carbaryl, Comer et al.  (1975) determined that workers involved 1n mixing and
bagging dust formulations of carbaryl were subjected to  greater  risk of dermal
exposure than field workers.  Spraymen working in fruit orchards were exposed
to 59.0 mg/hr compared  to 73.9 mg/hr  for factory workers.  Urine samples
obtained from factory workers contained an average  of 8.9 ppm and a high of 65
ppm of the principal metabolite of carbaryl, 1-naphthol.  Accepting these
values and those reported by Best and Murray (1962) as representative of
possible daily exposures to carbaryl, a  70 Kg worker may be expected to be
exposed to concentrations well  above the acceptable daily intake (ADI)  of  0.01
rag/Kg set by the Food and Agricultural  Organization of  the United Nations
(FAO)  and the World Health Organization (Kuhr and Dorough,  1976).  Although
exposure of workers to carbaryl  would be expected to be greater  than the
general population (Kuhr and Dorough,  1976),  the work related studies reported
by NIOSH (1976) did not indicate serious health effects  related  to enhanced
exposure.
     Maitlen et al. (1982) observed that nearly  100% of  the exposure to
aerial applicators occurred through the hands as a result of manual adjustment
of spray nozzles.  A similar route of exposure was  observed for  workers
involved in ground application.   Individuals involved in  handgun application
received more uniform  exposure.  Applicators received considerably less
exposure than individuals Involved in mixer-loader  operations.
     By considering many of the facets of pesticide application to fruit
orchards, Maitlen. et  al. (1982)  were able to estimate  the  extent of exposure
to farm  workers.  Aerial flaggers or signalers had  the highest hourly dfc.-mal
-------
                                                                              649
exposure (HDE).  Residues were more evenly distributed over the body compared
to mixer-loaders, aerial  applicators, or  tree thinners.  Flaggers received
greatest exposure on the  face, while workers performing the other duties
received greatest exposure  through the hands.
     Transfer of dislodgable  residues of carbaryl onto the hands of workers
Involved in thinning leaves from the trees (thinners)  was  also  compared with
the loss of residues from  the leaves (Maitlen et al., 1982).  Loss of residues
from the leaves followed first order kinetics with a  loss of 87% of the
residue in the first 8 days.  The remainder of the residue was lost more
slowly.  Maitlen et  al. (1982)  obtained  a significant correlation  (r * 0.99)
between leaf residue (ug/cm2j and hourly dermal  exposure on the hands of
thinners.   The  pharmacokinetlc disposition of the insecticide was not
observed.
     Dermal exposure to carbaryl  by strawberry harvesters was  studied by Zweig
et al.  (1984).  They  determined that, on this crop at least, dermal exposure
1s mainly on the hands and forearms and, to  a much  lesser degree, on the lower
legs.  They also observed higher  exposure levels in the morning than in the
afternoon and that younger and/or lighter weight subjects exhibited lower
exposures.
     Best and Murray (1962) contrasted the exposure of carbaryl-manufacturing
plant workers with corresponding  blood samples for the determination of
cholinesterase activity and urine specimens  for  the detection  of the primary
metabolite of carbaryl, 1-naphthol  (NIOSH,  1976).  The NIOSH document  (NiOSH,
1976) which reported the results  of Best and Murray (1962)  suggested that,  th
cholinesterase data were based on an Insensitive method and were not
-------
                                                                           650
representative of exposure as Indicated by the concentrations of 1-naphthol
detected in urine.   An  average  of 354 ug/1 of 1-naphthol was detected in urine
collected after completion of the work day during 3.5 months of  activity,
e.g., production, bagging  and shipping of carbaryl.  After cessation of
activity, urine concentrations of 1-naphthol  decreased  to 108 ug/1.  Upon
resumption of work  urine concentrations of 1-naphthol  rebounded  to a high of
10 mg/1  in M% of the 138 urine specimens.   Best and Murray (1962)  reported a
range of air concentrations of carbaryl between  1.23 and 40 mg/M3  for the
study period.  Although the air concentration exceeded threshold limit values
(5 mg/M3) and urine concentrations  of 1-naphthol  indicated  exposure, the
employees studied did not demonstrate clinical evidence of  intoxication
(NIOSH,  1976).
     Carbaryl (1-naphthyl  N-methylcarbamate)  is a widely used monomethyl
carbamate insecticide with reasonably well  understood acute  toxicological
properties (NIOSH,  1976 and Kuhr and Dorough,  1976).  Exposure to  the many
formulations of carbaryl may be detected through  examination of  serum or red
blood cell (RBC) cholinesterase (ChE) activity and  metabolites of  carbaryl in
blood or urine.   Associations between  dermal  exposure and biological activity
may be  useful  in the preparation of worker protection  standards (NIOSH,  1976).
Because of the rapidity of hydrolysis of  carbaryl,  depression of ChE activity
may not  be sensitive enough to measure exposure (NIOSH, 1976).   Detection of
concentrations of metabolites in urine may prove more quantitative.
     This study was designed to estimate exposure of okra harvesters to
dislodgable residues of carbaryl (SevinM 50-W)  following  an aerial
application at the maximum labeled  rate (4 Ibs/acre).   Exposure  was to be
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                                                                             651
assessed by making comparisons of concentrations of  carbaryl metabolites
detected In urine of  workers  to concentrations of residues of  carbaryl found
In dermal exposure  patches and the associated substrates, okra leaves  and  soil.
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                                                                         652
                                 BACKGROUND

     Okra is an  Important  fresh market and processing market crop grown in
Texas primarily on 400 to  800 acres  of  the  Lower Rio Grande  Valley  (LRGV)
(Sikes et a!.,  1980).  At maturity, okra grown in South Texas reaches a height
of one to two meters.  The leaves are relatively large and the foliage is
heavy.  The  pods mature rapidly, requiring a daily harvest to maintain uniform
sizes.  Harvesting  is done early in  the morning to allow  for easy manipulation
of the pods at maximum freshness.
     Harvesters may be expected to  contact  residues  of carbaryl when handling
the pods through the lush  foliage.  Continuous exposure to carbaryl  may be
expected as the harvest continues.   Okra is picked over a period of many days
according to sizing requirements of  the grower.  Applications of carbaryl may
be repeated in accordance  with insect  pest  pressures.  Additionally, workers
may  influence their own exposure through the clothing they  wear (barriers),
through personal behavior (eating habits, smoking), and the speed with which
they work.  Harvesters are usually  paid by  the amount of  okra  picked.
     Both youth, 17 years  of age and younger, and adult farmworkers are
engaged in the harvest of  okra.  In  addition, children of migrant farmworkers
frequently enter the fields with their parents (Spear,  1982).  Youths  involved
in the harvest of okra may be  expected to come into  contact  with  pesticide
residues at the same level as adults.   Munn et al. (1985) observed  that youths
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                                                                          653
may experience a higher absorbed dose  because of lower body weights.  This
study was originally designed to examine the exposure of youth and adult
farmworkers to carbaryl while harvesting okra.  The aim of the study was to
estimate the level  of  exposure between youths and adults.
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                                                                        654
                            METHODS  AND PROCEDURES

     A ten acre  field near Monte Alto In Willacy County of the Lower Rio
Grande Valley (LRGV) of Texas was chosen as the sample site.  Deposition of
carbaryl was examined on elevated panels,  soil, and  okra  leaves.  The elevated
panels consisted of three 100 cm2 gauze patches distributed  over a
0.093 m2 (1 ft2) surface elevated at the height of the canopy (171 cm).  Nine
panels were placed within 40 inch wide rows and aligned  in a north south
direction from the west edge of the  field.  Each panel was separated by
25 rows  (24.6 m).   A companion set of nine panels was placed 61.8 m (200 ft.)
from  the  east border and 61.8 m from the first set.   The  panels aligned in the
north-south plane along rows were transected at the middle of the  field by
another  set of 10 panels aligned in  the east-west  plane.
      Sevin 50-W (EPA Reg. No. 264-315)  was aerially  applied  at  the rate of 4
Ibs. per  acre on 20 October 1983.  The  applicator sprayed in swaths from east
to west beginning at the north end traveling south.   The  applicator made 14
passes with two final passes across  each north and south  end.  The time of
application was 1400 hours and the wind velocity was 10-12 miles per hour from
the  southeast.  The temperature at  1300 was 86°  F.   The soil  was
dry although a percent moisture reading was not taken.
     Sample collection started 30 minutes  after  application  and continued  *or
three hours.  A single gauze patch was randomly selected from each of the  13
                                      8
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                                                                        655
panels for extraction.  The remaining  patches were stored  frozen.  The patch
selected for extraction was  placed  In  an  Erlenmeyer  flask  with  150 ml methanol.
The solution and  patch were agitated on a Burrell wrist action shaker for 15
minutes.  The extracts from  three replications were combined and dried with
sodium sulfate.   The dried extract was concentrated with a Buchi Rotovapor
R110 evaporator and reduced  to  5  ml  on a  nitrogen Meyer N-EVAP analytical
                                                     \
evaporator.
     Leaf samples were collected from  plants along assigned rows 1n the north-
south direction.  The  samples (5  cm2) were taken from exposed
leaves at the top of the canopy (n  = 100) and from covered leaves under the
canopy (n = 100).  The leaf punches were dropped from the punch Into 120 cc
plastic urine specimen containers and  transported on dry Ice to the
laboratory.   Ten  leaf punches were drawn from each of the 100 samples
collected In the field.   The  leaf punches (n = 10) from each of the sampling
sites (n * 9)  were  examined  for dlslogable residues  of carbaryl according to
the method  of Gunther  et al. (1974).
     The ten leaf punches (50 cm2)  were placed in 120 cc urine specimen
cups for extraction.  The sample  was extracted with 75 ml deionized water and
50 ul of (0.5%) Witconol NP-100 surfactant at maximum agitation for 15 minutes
on a laboratory shaker.   The  sample was extracted three  times.  The extracts
were collected 1n a 1000 ml  separatory funnel.   The  volume was adjusted  to 600
ml with a 2% solution  of  sodium sulfate in water.  The sodium sulfate acted as
a clearing agent to prevent  formation  of  an  emulsion upon  extraction.  The
600 ml solution  was extracted three times with 150 ml methylene chloride.  Yhe
-------
                                                                        656
extract was pooled and  dried with  sodium sulfate.  The dried sample was
concentrated to 0.5 ml  and the  volume adjusted  to  5.0 ml with methanol.
     Deposition of carbaryl on  soil was examined on 400  cm2 soil  pans  (n * 4)
containing 100 grams of soil  at a depth of 0.5 cm.  The pans were placed in a
row flush with the soil near  the center of the  field.  Soil from the pans was
transferred to quart size zip-lock(R) bags and  stored frozen until prepared
for analysis.   The  soil (10 g)  was extracted three  times  with 50 ml  methanol
with vigorous agitation of a Burrell  wrist action shaker for 15 minutes.  The
pooled extract (150 ml) was filtered  through Whatman  #1  filter  paper.  The
filtrate was concentrated in a Buchi  Rotovapor  R110 evaporator  and reduced to
5.0 ml  on a nitrogen Meyer N-EYAP analytical evaporator.
     The sample extracts were analyzed by  reverse  phase  high performance
liquid chromatography (HPLC) at  280 nm with a Spectra-Physics liquid
chromatograph equipped with a Model  SP8440 variable wavelength  detector, a
SP8700 solvent delivery system,  and a SP8750 organizer with a 7125RV Rheodyne
syn'nge sample injector with a  10 ul  sample  loop (Cramer et al.,
1982).   Samples were separated on an  All tech C18 (250 mm x 4 mm  i.d.)  column.
The mobil phase was  50% acetonitrile and  50% water at a  1  ml/mi n flow  rate.
The peaks were integrated  and computations quantified by a Hewlett Packard
HP9826 desk top micro-computer  utilizing  the 4400 Series Nelson Analytical
Software Program for Chromatography.
     A mean concentration of 0.10 _+ 0.03 ug/cm2 was recovered from panel
patches (n«3)  fortified with carbaryl (0.10 ug/cm2).  Seventy percent  of the
fortified concentration (1.3 ug/cm2)  Of carbaryl  was  recovered  from  leaves.
Much higher recovery (143%) was obtained  from soil  fortified at 1.0 ug/y.
                                     10
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                                                                            657
     Preharvest  urine specimens were obtained from 5 male and 3 female
farmworkers.  These  subjects did not enter the field.  Farmworker
participation was cancelled because of Inclement weather.  The study design
was amended to utilize urine samples  obtained from three of the four male
members of the study team before entry Into the field and after collection of
substrate samples.   These study team  workers became  the  test subjects.  The
harvesters originally recruited as test subjects became the control
population.  The test subjects were equipped with 4x4 gauze sample patches
(100 cm2) on the inside and  outside sleeves and on the right and left chest
pockets of cotton chambray work shirts.   The gauze patches were analyzed for
residues of carbaryl according  to  the method described for  panel  patches.
Urine samples were  examined for the metabolite of carbaryl,  1-naphthol,
according to the method of Shafik  et  al.  (1971).  The minimum detection limits
for this method were established  by Shafik et al. (1971) at 0.02 ppm.  A
recovery of 77.0 percent was obtained for a single quality control sample
fortified at  20.0 ng/ml.
     Urine (1.0  ml)  was added  to 3.0 ml 4N HC1 in 15  ml  culture tubes and
heated at 32°C for one  hour.  The hydrolyzed sample was allowed to cool to
room temperature and then extracted twice with 5.0 ml methylene chloride.  The
combined extracts were adjusted to 10.0 ml with methylene chloride and dried
with sodium  sulfate.  The extract  was transferred  to another 15 ml  cultura
tube.  The sodium sulfate was rinsed twice with methylene chloride and the
rinsate was added to the combined extract.  The  residue was exchanged from
methylene chloride  Into  acetone and slowly reduced In volume (0.5  ml).  Tiie
residue in acetone was derivatized in the presence of potassium carbonate and
                                     11
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                                                                            658
a 1.0 percent solution (100 ul) of alpha-Bromo-2,3,4,5,6-pentafluorotoluene
(PFB).   The  50 ml  culture  tube  was  tightly capped and heated at 100°c for
one hour.  The tubes were  allowed to cool and adjusted in volume with benzene
extracted redistilled  water to  5.0  ml.  The sample was extracted twice with
5.0  ml  hexane.  The combined  extracts of hexane (10.0  ml)  were  dried with
sodium  sulfate and then reduced in volume to 1.0 ml.  The  sample  (1.0 ml) was
applied to a hexane conditioned silica  gel column (9mm  i.d., 300m long).  The
1-napthyl chloracetate derivative  was  recovered with  the 60% benzene/hexane
extract (Shafiket al., 1971).
     Analysis of 1-napthol was  performed on  a  dual column  Tracor MT220 gas
chromatograph equipped with a [^H]  detector.  The instrument parameters were:
column  temperature, 2000c; inlet temperature,  225°C;  detector  temperature,
205°C; nitrogen  flow,  40 ml/min;  5.0% OV210  and 1.5%  0V17/1.95% OV210 columns.
     Descriptive statistics were obtained  for  each data set according to the
Univariate procedure,  Statistical  Analysis System (SAS, 1979).  The
distribution of  sample values was evaluated  prior to  performing a statistical
test of significance.  The  differences between means were  tested for
significance at the 5 percent  level according  to  Student's t-test.  Three
dimensional  plots and  charts  were  obtained through SAS  (1981).
                                     12
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                                                                           659
                                  RESULTS

     The deposition  of carbaryl was examined on elevated panels, soil, and
okra leaves.   A test of  trend  based on Kendalls tau (Conover,  1980) revealed a
near uniform  deposition  of residues on elevated panels  placed  along the north-
south plane  in two  rows 60 meters (tau * -0.0833, n *  9, P < 0.754) and 120
meters  (tau  » -0.2500, n * 9, P <0.348) from the west edge of the field
(Fig. 1).  The deposition of  residues  detected  on  panels  1n  the  north-south
plane was compared  to deposition on panels  1n  the east-west plane  (F1g. 1).
Residue  concentrations on panels  were found to be Independent (tau = -0.4000,
n « 10,  P < 0.09) of the distance from the north  edge of  the field.   The
mean residue concentration on panels  arranged  In  east-west plane (6.70 _+4.68
ug/cm2)  was found to be  not  significantly  different  (t = 0.2381,  P  < 0.50, 26
d.f.) than the mean  concentration (7.49 +_ 4.82  ug/cm2)  obtained  for  the  north-
south direction.
     Deposition on panels  was compared to deposition on  leaves  (Table 1).
Because  leaf  samples were collected along rows in  a north-south  plane, residue
concentrations on leaves were compared with residue concentrations  on panels
In the same direction.   The  mean residue  concentration on  leaves (9.37 +_ 5.24
ug/cm2)  near ## top Of  tne  canopy (n « 5) was f0un(j to ^  not significantly
different (t * -1.5062,  P < 0.20, d.f. • 13) than the mean concentration (6.04
+_ 3.35 ug/cm2) found In  panel patches (n s  9) along similar  rows  60  meters
                                     13
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                                                                          660
from the west edge of the field (Table 1).  Mean concentrations of panel
patches along rows 60 meters and 120 meters from  the west edge  of the field
were not significantly  different  (t =  -1.2975,  P  <  0.40,  d.f. = 18).
The deposition of carbaryl  on panel  patches and leaves near the top of the
canopy appeared to be uniform.
     The ranks of residue concentrations  on bottom leaves  below the canopy
(Table 1) were found  to  be  not significantly  different  (T  « 34.5,  n = 6,
m  =  3,  P < 0.122) than the ranks of the concentrations on  top leaves according
to the Mann-Whitney test for two  Independent samples (Conover,  1980).  This
test was chosen because of the size of the unbalanced data sets.  A paired
comparison of leaf samples from plants along  similar rows  (Table 1) was not
significant (t = 1.6609, d.f.  *  2, P  < 0.40) at the  5% level.
     Although residue concentrations on leaves below the canopy did not appear
to be significantly different than concentrations  on leaves near the top of
the canopy, the study design  did not permit the evaluation of the distribution
of residues through the canopy.  The lowest mean  concentration  of carbaryl
residues was  detected in soil samples  (10 g)  collected  from  526.5 cm2 pans
(n = 4) placed flush  with the soil  surface approximately  100 meters from the
north edge of the field  and 80 to  100 meters  from  the west edge of the  field
(Table 2).   However,  because  of  the location  of the  soil samplers, a
statistical comparision of residue concentrations between substrates,  panels,
leaves and soil, could not be made.
     Transfer of residues of carbaryl  to  workers  was assessed through the
examination of residue concentrations  on  sampling  devices  (100  cm2 gauze
patches) located on the outside  and inside sleeves and  on the chest pocket* of
                                     14
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                                                                              661
cotton chambray work shirts worn by members of the sampling team.  These
workers were engaged In sample  collection and not the harvest of okra.
Although their activities  In  some respects mimIced those of the okra
harvester, these subjects may be regarded as not-occupationally exposed.  The
four participants were adult males (age > 17 years).
     The paired differences In residue concentrations  between outside and
Inside sleeve patches (Table 3)  were  found  to  be not significantly different
(t = 1.900, d.f. -  3, P  <  0.20).  A similar result (t = 1.993, d.f. - 3, P <
0.20) was observed  for  paired comparisons of inside sleeve  patches and chest
patches (Table 3).   Outside sleeve  patches,  however, appeared  to accumulate
greater (t » 7.893,  d.f. * 3,  P < 0.005) concentrations of carbaryl than chest
patches.   The workers appeared  to accumulate greater residues  on the arms than
on the chest.   In addition, the  accumulated  residues on the  sleeves appeared
to penetrate the cotton  chambray material.
     The  transference and  possible dermal absorption of carbaryl  by  workers
exposed to dislodgable  residues  of carbaryl was monitored by examining
concentrations  of 1-naphthol  in  urine.  Urine samples were  provided by the
three study team participants before and  after entering the field to collect
substrate samples (Table 4).  A urine specimen was not obtained from subject
12.   The eight farmworkers scheduled  to participate 1n the  study provided
preharvest urine samples.   These samples  served as controls (Table 4).
     1-Naphthol  was detected In urine samples  from the three participants of
the study team after the collection of substrate  samples  (Table 4).   The
concentration  of 1-naphtol was 0.087  _+0.021 ug/ml.  When adjusted to the
urinary creatlnlne concentration,  the normalized mean concentration was
                                     15
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                                                                           662
0.037 +_ 0.005 ug/mg/ml.  The participants  1n the study team  appeared  to
accumulate and absorb residue concentrations of carbaryl  while collecting the
substrate sampling  devices.
                                    16
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                                                                          663
                         INTERPRETATION AND ANALYSIS

     The aerial  application  of  a  wettable  powder formulation (Sevln 50-W) of
the N-methyl  carbamate Insecticide carbaryl (1-napthyl N-methyl carbamate) on
a 10 acre plot of okra was found  to  be uniform over artificial sampling
devices, elevated panels (Fig.  1), and the foliage canopy (Table 1).   Human
subjects entering the field  to  collect environmental  samples  appeared to
accumulate residues on sampling devices located on the. outside sleeves and
inside sleeves and on the chest of the cotton chambray shirts worn by the
workers (Table 3).   The  concentrations of carbaryl detected on outside sleeve
patches were significantly greater  than  the concentrations  detected on chest
patches.  The motion of  arms during  work operations may explain the difference
between concentrations  on outside sleeve patches and  patches on the  chest.
The accumulated residue concentrations on outside sleeve patches were found to
be not significantly different  than  the concentration detected on inside
sleeve patches.   Residues of carbaryl apppeared  to pass through the sleeve of
the chambray work shirt.  The protective value  of the shirt was considered
suspect.  Indeed,  the metabolite  of  carbaryl, 1-naphthol, was detected 1,i the
urine of the three  test subjects (Table  4) after three hours  of exposure  in
the field.  1-Naphthol  was not  detected  in urine collected  prior  to entry  to
the field. In addition,  1-naphthol was not detected in urine of any of  the
                                     17
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                                                                     664
members of the control group (Table  4).  The test subjects appeared to have
dermally absorbed some residues.
     Carbaryl  has been observed (Feldmann and Maibach, 1974) to be rapidly
absorbed upon  dermal  contact.  The rate of absorption appears to be similar
over different body regions (Maibach et al., 1971).  The concentrations of
1-naphthol in  urine of the test workers (Table  4)  was well below the urinary
output (8.1 ug/ml)  from  ingestion of a controlled concentration of carbaryl
(Knaak  et al.,  1968).  Knaak et al.  (1968)  observed that concentrations
dermal ly  absorbed  or  transferred  did not  represent an acute  health threat.
Similar assessments of possible risk to the occupational ly exposed have been
offered by Maitlen et al. (1982); Gold, et al.  (1982); and Leavitt et al.
(1982).  However, the long term effects of repeated  exposure to these
concentrations are less well known  (Comer et al.,  1975).  The burdens on
metabolic and excretory systems after repeated  exposure to subacute
concentrations of carbaryl may require further study (Knaak  et al.,  1968;
Ruhr and  Oorough,  1976).
     The metabolism of carbaryl  1s complex (Kuhr  and Dorough, 1976, and Menzie
1969, 1974,  1978, and 1980).  The hydroxylated  metabolites (4-hydroxy-l-
napthyl N-methylcarbamate, 5-hydroxy-l-naphthyl N-methyl-carbamate,  1-naphthyl
N-hydroxy methylcarbamate and 5, 6-dihydro-5, 6-dihydroxy-l-naphthyl N-methyl-
carbamate) may appear in the urine of mammals  as  glucuronide and sulfate
conjugates (Kuhr and Dorough,  1976).  Hydroxylation by NADPH dependent
microsomal enzymes predominates over hydrolysis to 1-naphthol in most
vertebrate species.  Because of the  predominance  of  the conjugated
hydroxylated  metabolites in urine,  determination of exposure based on  1-
                                     18
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                                                                     665
naphthol  may represent  an  underestimation of actual exposure.   We  advocate the
examination of blood and urine for total  metabolites of carbaryl with values
normalized to creatinine clearance.  The units  would then  be expressive of
both hepatic and nephritic function.
                                    19
-------
                                                      9.99
                                              II! I
                                              • • •
                                           rl I
                             _
       20      60      100      140
Distance  (meters) from  west edge of field
F!g. 1.  Distribution of carbaryl  residue concentrations (ug/cm )
detected In 100 cm  gauze patches  from panels arranged in an east-
west plant- in a north-south plane.
                                                                         CT\
                                                                         cr-.
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                                                                            667
    Table  1.  Deposition of aerially-applied carbaryl as Sev1n(R)  50-W on
             panels and okra leaves  along rows In the north-south plane.

«==*===========33=========================3======»============================

                         Carbaryl  Concentration (ug/cm2)
fHctanrp fpnn
V 1 9 t»wll\*w • I \MU
north edge of
field (m)
34
37
52
56
71
75
90
94
109
112
127
131
146
150
165
169
184
192
===============

60m

3.57

6.38

10.58

2.98

3.20

8.47

7.33

10.26
1.57

======
Panels8/ Leaves
120m Top Bottom
9.96

2.00
13.17
10.03
11.30
17.72
13.60
17.72

8.33
4.59 1.72
3.94

7.80
12.49 4.59
2.91
1.07 0.73
========== =B= ========================== 33 =========cc=";==e
    a/  Distance of panels in rows 60 and 120 meters  from west edge of me
    ~   field.
                                    21
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                                                                           668
Table 2.  Comparison of the deposition of carbaryl on  panels,  okra (top and
bottom  of canopy) and soil.
Substrate
Panel si/
Leaves!/
Leaves£/
Soil!/

Lowest
Value
2.00
1.07
0.73
0.129
Carbaryl
Highest
Value
14.63
13.60
4.59
0.754
Concentration (ug/on2)
Mean
6.70
9.37
2.34
0.468
Standard
Deviation
4.68
5.24
2.00
0.297
Coefficient
of Variation
0.70
0.56
0.85
0.63
!/ Line of panels (n = 10) 100 meters  from the  north  edge  of  the field 2).
-/ Leaf punches (n = 6) collected from okra  leaves at the  top of the  canopy.
£/ Leaf punches (n = 3) collected from okra leaves  below the  canopy.
-I Soil samples (lOg) collected  from soil pans (526.5 cm2) located 80  and 100
   meters from the west edge of  the field and  101.25 meters from the north
   edge of the field.
                                     22
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                                                                           669
    Table 3.  Accumulation of dlslodgable  residues of carbaryl as Sevin(R)
             50-VI on body patches.   The means and standard deviations  for
             each sampling device are provided.

====33»===33==««====3====3=33=3=«=======»=====================================
                       Carbaryl concentration (ug/on2)
HUlKCr
Number
9
10
11
12

Outside Sleeve
9.99
8.18
5.16
11.10
8.61 + 2.59
Inside Sleeve
5.41
2.87
3.55
10.30
5.53 + 3.35
Chest Patch
4.28
2.19
1.58
4.20
3.06 + 1.38
                                    23
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                                                                     670
 Table 4.  Concentrations of the urinary metabolite 1-naphthol  detected
          in urine samples provided by eight control  and  3  test  subjects.
          Urine  samples were obtained from the test subjects,  members
          of the research team, before and after collection of substrate
          samples.
Worker
Identifier
Hour of
Sample
Collection
1-Naphthol
Concentration
(ug/ml)
Creatinine
Concentration
(mg/ml )
Normalized
Concentration
1-Napthol (ug/mg/ml )
                  Control Group - Did Not Enter Field
1
2
3
4
5
6
7
8
1956
1956
1955
1958
1958
1955
1958
1956
NO
ND
ND
ND
ND
ND
ND
ND
2.46
1.86
2.80
1.92
1.30
2.41
3.45
1.66
-
-
-
-
-
.
-
-
                  Test Group - Prior to Entering Field

 9          1430            ND              1.88
10          1430            ND              2.79
11          1430            ND              1.63
                     Test Group - Three Hour Exposure

 9          1919            0.08            2.26              0.035
10          1800            0.11            2.32              0.043
11          1810            0.07            2.03              0.034
                                   24
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                                                                       671
                             ACKNOWLEDGEMENTS

     A number of persons contributed materially to the work described above,
In either the planning of  the project,  doing field work, analyzing samples, or
preparation of the report.  These are:  R. L. Carey,  V. F. Cox,  C. C.  Oary,
M. A. Garcia,  M. E. Garcia, R. L. Garcia,  A. Guillen, Jr.,  K. J. Huxford,
N. J. Magouirk,  A.  Martinez,  T. R.  Mol lhagen, and   A. G. Navarro.
                                   25
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                                                                           672
                              LITERATURE CITED

American Conference of  Government  Industrial Hygienists.  1984.  Documentation
     of the threshold limit values for chemical substances In the environment.
     ACGIH, Inc., Cincinnati, OH.  504pp.

Best, E.  M.,  Jr. and B.  L.  Murray.   1962.  Observations on workers exposed to
     sevin insecticide—a preliminary report.   J. Occ. Med. 4:507-517.

Comer, S. W., D. C. Staiff, J. F. Armstrong, and H. R.  Wolfe.  1975.
     Exposure of workers  to  carbaryl.   Bull.  Environ.  Contam. Toxicol.
     13(4):385-391.

Conover, W. J. 1980. Practical nonparametric statistics, 2 ed.  John  Wiley and
     Sons, NY.  493 pp.

Cramer, P. H., A.  D. Drinkwlne, J. E. Going, and  A. E. Carey.  1982.
     Determination of carbofuran and its metabolites by high-performance
     liquid chromatography using on-line trace enrichment.   J. Chromatog.
     235:489-500.

Pel dman,  R. J. and H.  I. Maibach.   1974.  Percutaneous  penetration of some
     pesticides and herbicides 1n  man.   Toxicol.  Appl. Pharm.  28:126-132.
                                     26
-------
Gold,  R. £., J. R. C. Leavltt, T. Holes law,  and  0. Tuby.   1982.  Exposure of
    urban applicators to carbaryl.  Arch. Envlronm. Contain. Toxicol. 11:
                                                                               67:
    63-67.
Gunther, F. A., J. H. Barkley, and W. E. Westlake.  1974.  Worker environment
     research.  II.  Sampling and processing  techniques for determining
     dislodgable  pesticide  residues on leaf  surfaces.  Bull. Environ. Contain.
     Toxlcol.  12(6).-641-644.

Knaak, J. B., M. J. Tallant, W. J. Bart ley, and L. J. Sullivan.  1968.  The
     metabolism of carbaryl  In the rat, guinea pig, and man.  J. Agrlc. Food
     Chem. 16:465-470.

Kuhr, R.  J. and H.  W. Do rough.  1976.   Carbamate Insecticides: chemistry,
     biochemistry and toxicology.  CRC  Press,  Inc.,  Cleveland,  OH.   301 pp.

Leavltt, J. R. C., R. E. Gold,  T. Holcslaw, and D. Tupy.  1982.  Exposure of
     professional  pesticide  applicators  to carbaryl.   Arch. Environ. Contam.
     Toxlcol.  11:57-62.

Maibach, H. I., R.  J. Fel dman, T. H. M11 by, and W. F. Serat.  1971.  Regional
     variation  In percutaneous penetration In  man.   Arch. Environ.  Health
     23:208-211.
                                    27
-------
Maitlen, J. C., C. R. Sell. L. M. McDorough, and S. N. Fertig.   1982.
     Workers in the agricultural  environment:  Dermal  exposure to carbaryl.    0/4
     Pp. 83-103 jn^ Pesticide  residues and exposure, J. R.  Plimmer, ed.  ACS.
     Symposium Series No. 182,  American Chemical Society.  Washington, D.C.
     213 pp.

Menzie, C.  M.  1969.   Metabolism of pesticides.   U.S  Department of the
     Interior Fish and Wildlife Service, Special  Scientific Report - Wildlife
     No. 127,  Washington, D.C.   487  pp.

Menzie, C.  M.  1974.   Metabolism of pesticides,  Update  I.  U.S. Department of
     the Interior Fish and Wildlife  Service, Special  Scientific  Report -
     Wildlife  No. 184, Washington, D.C.  486 pp.

Menzie, C.  M.  1978.   Metabolism of pesticides,  Update  II.  U.S.  Department of
     the Interior Fish and Wildlife  Service, Special  Scientific  Report -
     Wildlife  No. 212, Washington, D.C.  381 pp.

Menzie, C.  M.  1980.   Metabolism of pesticides, Update III.   U.S.  Department
     of the Interior Fish and Wildlife  Service, Special Scientific Report -
     Wildlife No. 232, Washington, O.C.  709 pp.

Munn, S.,  T. J. Keefe, and E. P. Savage.   1985.  A comparative study  of
     pesticide exposures in adults and  youth migrant  field workers.   Arch.
     Environ. Health  40(4):215-220.
                                     28
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National  Institute for Occupational  Safety and Health.  1976.   Criteria for a
                                                                            675
     recommended standard:  Occupational  exposure  to carbaryl.  DHEW (NIOSH)
     Publ. No. 77-107.   192 pp.
SAS. 1979.   SAS user's guide.  1979 edition.  SAS Institute, Inc., Gary. NC.
     494 pp.

SAS. 1981.   SAS/Graph user's guide.  1981 edition!  SAS  Institute.  Inc..
     Gary,  NC.  126 pp.

Shaflk, M.  T., H.  C. Sullivan, and H. F. Enos. 1971.  A method for the
     determination of 1-naphtol  In urine.  Bull. Environm. Contam. Toxlcol.
     6(1):  34-39.

S1kes, V. R., D. McCraw, T. Longbrake. S. Cother, and B. Peavy.  1980.  Keys
     to profitable okra  production for food and seed.  Texas Agricultural
     Extension Service,  Keys to  Profitable Production Series, No. L-1805.   4
     pp.  (unnumbered).

Spear, R. C.  1982.  Farm  worker exposure to pesticides residues: reflections
     on differential risk.  Pages 67-76  In V. R. Hunt, M. K. Smith, D. Worth,
     Eds.,  Banbury Report  II, Environmental Factors in Human Growth and
     Development,  V.R. Hunt, M.  K. Smith, D. Worth, Eds., Cold Spring harbor
     Laboratory.
                                     29
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World Health Organization.  1982.   Recommended health-based  limits  In
     occupational  exposure  to  pesticides.  Technical Report Series No. 667.   6/6
     WHO,  Geneva.   110 pp.

Yakim, V.  S.  1967.  [The maximum permissible concentration of sevin In  the
     air of the work zone]  Gig. Sanlt.  32:29-32.

Zwelg,  G., R. Gao, J. M.  Witt,  W. Popendorf,  and K. Bogen.  1984.  Dermal
     exposure to  carbaryl  by strawberry harvesters.  J. Agrlc. Food Chem.
     32(6): 1232-1236.
                                    30
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                                                      677
An Assessment of Exposure  of Cucumber
  Harvesters to Azinphos-Methyl
        Research performed by

        Texas Tech University
        San Benito, TX  78586

        March 31, 1986
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                                                                      678
In behalf of  the Texas PHAP the undersigned  has  reviewed and approved the
report draft  entitled "An Assessment of  Exposure of Cucumber Harvesters to
Azinphosmethyl  In  South Texas."
                                                        Date
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                              TABLE  OF  CONTENTS
S3sa——S—SSSSSSSSSSSSSSS=SSSSSSS=SSB==S=Sas=SS5=SSSSS3SSS=XS3S=SSS=a=S=SSSSS=SS
Section                                                                   Page
ABSTRACT 	    1v
INTRODUCTION 	     1
METHODS 	     6
     Deposition 	     6
     G1 oves 	     9
     A1r Samples 	    10
     Gauze Patches 	    10
     Urine	    11
ANALYTICAL PROCEDURES 	    12
     Patches	    12
     Soil 	    12
     Fol 1 age	    13
     Gloves 	    13
     Air Samplers 	    13
     Urine	    13
     Instrumentation 	    14
     Recoverles 	    15
     Analytical Standards 	    16
RESULTS	    18
INTERPRETATION AND ANALYSIS 	    25
FIGURES	    27
TABLES	    39
ACKNOWLEDGEMENTS	    60
LITERATURE CITED 	    61
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                                                                         680
                                   ABSTRACT

     Occupational  exposure of youth (age <_ 17 years) and adult (age > 17
years) farmworkers to residues of azinphosmethyl  was assessed in a cohort of
individuals harvesting cucumbers from a field in the Lower Rio Grande Valley
(LRGV) of South Texas treated with Guthion 2L by  aerial  application at the
rate of 2 pints per acre.   Guthion appeared  to be uniformly  distributed over
the field as indicated by the concentrations of azinphosmethyl detected on
gauze patches (103.2  cm2)  arranged on  panels (929 cm2) placed within the
field.  The median concentration  on panel  patches was (0.57  ug/cm2).  The mean
concentration was 0.73 +_ ug/cm2.  The decline or  loss  of dislodgable residues
of azinphosmethyl from foliage was rapid  reaching nondetectable  levels within
two days after application.  The half life of azinphosmethyl  on  soil from a
nearby field was estimated to be  2.54 days.   Harvesters  entered  the field 2
days after application of Guthion 2L. The harvesters  accumulated
significantly greater concentrations of  azinphosmethyl on right hand gloves
(0.92  +_ 0.54 ug/cm2)  than  on outside shirt patches  (0.03 ug/cm2)-   Farmworkers
harvesting cucumbers  may  be expected to contact residues of  azinphosmethyl
more  readily on their hands  rather than their forearms.   Residue
concentrations did not appear to  penetrate  protective clothing.
Concentrations of dialkyl  phosphorous metabolites (DMP and DMTP) of
azinphosmethyl were  not detected  in the urine provided by the workers within a
24 hr period after 3.5 hours of exposure.  The 2  day reentry interval  appeared
to diminish the potential  for exposure to azinphosmethyl.
                                  iv
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                                                                             681
       EXPOSURE OF  CUCUMBER HARVESTERS TO AZINPHOSMETHYL IN SOUTH TEXAS

                                 INTRODUCTION

     In an Interagency Agreement, dated  March 17,  1980,  officials of the U.S.
Department of Labor and the U.S. Environmental Protection Agency pledged their
respective organizations to a  program  of "mutual cooperation In the design and
conduct of studies  to obtain data on the effects of pesticides on youths
employed 1n agriculture."  A comprehensive collection of activities were
proposed as tools for examining the present state of knowledge of pesticide
effects upon children.  One area of Investigation was assigned primarily to
the national  Pesticide Hazard  Assessment Projects  (NPHAP), the conduction or
operation of a series of pesticide exposure  studies of both adult and juvenile
farmworkers.  These studies were  Intended  to  provide an assessment of the
exposure of harvesters to one  or  more of the pesticides  used  to protect  these
crops from damage by pests or diseases.
     The migrant streams of the western United States are comprised mainly of
Spanish-speaking peoples. Because of  the  predominantly  Hispanic  culture,
the Lower  Rio Grande Valley (LRGV) of  south  Texas  1s home  to  one  of
the largest migrant farmworker populations 1n the United States.  During the
period September through May of most years,  the region provides Intermittent
work harvesting a wide  variety of fruits and vegetables.  In  the  Spring, as
the local harvests near completion, the  workers will gradually depart to
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                                                                           682
follow harvests of many of the same crops at progressively more northern
latitudes.   Workers of the LRGV  are the chief component of the central migrant
stream that works the Great Plains and the Midwest.  However, many will travel
directly to Florida or California to work the coastal streams northward.
     Because pesticides are applied to virtually all crops grown in the LRGV,
residues of the pesticides may  represent a  health hazard to field workers
either through prolonged dermal contact with leaves and fruit or through
inhalation or Ingestion of dislodgable residues.  The kinds of adverse effects
that can result from such  exposures range from skin or eye irritation to acute
intoxication.
     The commodities grown  in this four-county  region are annually treated
with perhaps as much as five million pounds of pesticide products, or 25 to 35
percent of all the pesticides used In Texas.  Hidalgo County alone, probably
the most intensively farmed county 1n the state, may receive as much as the
other three Valley counties combined.  Cotton and grains account for possibly
the greatest portion of this usage, but they need little human contact during
growth or harvest.  On the other hand, citrus, many vegetables, and some
specialty crops do require hand  labor and also require considerable pesticide
usage, occasionaly during harvest.
     The climate of the Lower Rio Grande Valley (LRGV) has been classified as
humid desert.  Mid-day relative  humidities  average 61 percent at Brownsville
and decline to about 45-50 percent in Starr County to the west, while mean
annual rainfall ranges from 27  to 19  inches In  the same direction (U.S.
Weather Service, Brownsville,  pers. comm.).   Summer temperatures frequently
exceed 100° F.  This climate could influence the formation of oxons from
organophosphate insecticides.  Oxons are frequently noted as having some
importance in poisoning incidents  involving harvesters in arid parts  in
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California (Maddy and Edmlston,  1982).  The combination of both high
temperature and high humidity has been observed to promote degradation
(Eto,  1979).  Most farmworkers In the region are employed In the Fall and
Spring.   During this  period humidity remains  relatively high and temperatures
are much lower.  The  rate of  degradation of certain pesticides may be
subsequently lower than during the summer.
     Texas growers will annually plant 7,000-10,000 acres of cucumbers.  Over
half of this acreage  will be In the LRGV.  Typically two harvests are made 1n
the LRGV.  April  through  June and  September through November.  The crop Is
picked by hand.  Since  cucumbers do not mature uniformly, several pickings of
the same field may be spaced  a week or  more apart.  Frequently mounting Insect
pressure and changes  1n market conditions may justify one or more Insecticide
applications during the harvest period.
     The array of pesticides  recommended for use  on cucumbers  up to, and
during,  harvest (Texas Agr.  Ext. Serv., 1980)  Include  several  that may
represent a considerable  risk to  the occupational ly exposed (Federal Working
Group on Pest Management, 1974).  The  level of exposure may be dependent on
the capacity to transfer pesticide residues from  leaf  or fruit surfaces to a
harvester.  Cucumbers may represent a low-risk potential because of the low
growth habit a property which restricts activities from the breathing zone and
exposure to the torso and upper legs and arms.  However, hands alone may
account for perhaps the largest part of the residues accumulated  by  workers .
The harvesting of cucumbers does require handling of considerable  foliage.   In
addition the picking  of cucumbers In early morning when leaves are  covered
with dew may  facilitate both the transfer and uptake of pesticide residues.
     The transfer of  dlslodgable  residues of  the  Insecticide azinphosmethyl
during the harvest of cucumbers was studied  to assess  the  potential  hazard of
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exposure to organophosphorous Insecticides.  Deposition of a formulation of
azlnphosmethyl, Guthlon 2L, was examined  In conjunction with estimates of
transfer of residues to harvesters.  Measurements of residues on articles of
clothing worn by harvesters together with concentrations of metabolites of
azlnphosmethyl detected In urine of workers may  be useful in assessing the
potential  risk of exposure to farm workers harvesting  cucumbers.
     The organophosphorous Insecticide  azlnphosmethyl  (o,o-d1methyl s-[4-
oxo-1,2,3-benzotriazin-3  (4H)-yl) methyl]  phosphorodlthloate) has been offered
by Mobay Chemical Corporation (Agricultural Chemicals  Division, Kansas City,
Mo.)  under three  formulations (Mobay,  1982) Guthion 2S, Guthion 2L, and
Guthion 50% WP (PVA) for  control of spotted and  striped cucumber beetle and
western-striped cucumber beetle on cucumbers.  The label recommends (Mobay,
1982) complete foliar coverage  with sufficient water at the rate of 2 pints of
Guthion 2S and 2L per acre and 1 pound Guthion 50%  WP (PVA) per acre.  The
labels restrict the  use of these formulations of azinphosmethyl to no more
than 3 applications per season. Azlnphosmethyl  shall  not be applied within 1
day  of  harvest.
     Azinphosmethyl is a member of the phosphorodithioate class of
organophosphorous insecticides (O'Brien,  1967 and Eto,  1979).   Azlnphosmethyl
is soluble 1n most organic solvents but only   slightly soluble in water, 29
ppm at  25° C (Eto,  1979).  The  unformulated compound is subject to hydrolysis
at high temperatures (> 200° C) where  it  decomposes  to form a gas (Eto, 1979
and Mobay, 1979).  Hydrolysis may  be accelerated under aqueous conditions with
Increased temperature and pH (Menzle,  1978).  The half life of Azinphosmethyl
varied from 5 days under aqueous conditions  (40° C)  to 484  days under dry
conditions at 60 c (Menzie,  1978).  These  values may be contrasted against the
much shorter half life (10.4  hours) reported by  Eto  (1979) with azinphos-
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                                                                              685
methyl prepared in ethanol (70°  C, pH 6.0).  The formulated products remain



more stable (Menzie, 1980).  The half life of formulations of azinphosmethyl



on the foliage of different crops may be variable (Menzie, 1980).   The half




life of azinphosmethyl on apple trees was 2.6 to 6.3 days (Free et al.,



1976).



     The large objective of this work was to estimate the risk of exposure



to cucumber harvesters to azinphosmethyl applied to the crop in south Texas.




There were also several lesser objectives: (1) to measure the degradation of



azinphosmethyl on leaves and soil between the time of application and the



time of harvest; (2) to measure the transfer of residues from the crop and



soil to the workers during harvest; and  (3) to measure the absorbtion of



azinphosmethyl by the harvesters.
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                                                                         686
                                  METHODS
     Guthlon 2L,  a restricted use product of Mobay Chemical Corporation
bearing the EPA Registration Number 3125-102 (22.2%  azlnphosmethyl,  59.8%
aromatic petroleum distillates and 18.0%  Inert  Ingredients) was ground applied
along east-west rows with a boom and tractor assembly at 2 pints  per acre to a
9.79 acre plot  of cucumbers and squash at 1205  hours on April 7,  1983.  The
plot was unequally divided between squash  (3.10 acres) and cucumbers (6.69
acres). The boom covered  18 rows.  The nozzle  diameter and conditions of the
spray rig were not recorded.   Wind velocity at  1700  hours  was  10  to 12 miles
per hour (mph)  from the northeast.
     Deposition.   Deposition of azlnphosmethyl  was examined  on  two panels
placed within rows near the middle of the cucumber subplot, approximately 95
meters from the  east and west edges of the  field and 71.1  and  99.6 meters from
the south edge of the field (F1g.  1).   Additional deposltlonal  data was
obtained from  panels (n =3) placed  within rows  of the squash subplot,
approximately  92.5 meters from the east and west edge of the field and 4.06,
36.6 and 69.1 from the  north edge  of the  field  to the  border of the cucumber
subplot (F1g.  1).  The  panels were  12 x 12  cardboard squares (929 cm2) covered
with  aluminum  foil.  The foil  was cleaned with acetone before  the attachment
of  three 4  ply 4 x 4 Inch (103.2 cm2) surgical  gauze patches.   The  patches
were  arranged  1n a trigonal pattern with two patches  In the corners and  one
patch  midway from the  opposite corners.
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     Deposition and loss of residues  of azinphosmethyl were  examined on soil
and on leaf samples taken  from arbitrarily  selected cucumber and squash
plants.  Soil  pans  were placed flush  with the soil  surface along rows in close
proximity to panels In the cucumber subplot.   The  soil (100  g) was spread
evenly over the bottoms of a series (n = 10) of 9 x 9 inch (522.6 cm2)
aluminum cooking pans  aligned in groups of five along rows  (Fig. 1).  The soil
in the Interior of the field was Willacy fine sandy loam.  The soil along the
north and south edges of the  field  was  saline  Racombes sandy clay loam.  In
the squash  subplot, soil pans (n *  10) were placed  along  rows  in parallel
lines  of five (Fig. 1) in close proximity  with panels  and  at  three additional
locations 32.5,  75.2 and 103.6 meters  from  the north  edge of the field, equal
distance from the  east and west  edges. The soil  used in  the pans near the
north  edge  of the  squash section was Racombes sandy clay  loam.  The moisture
content of  the soil was not recorded.
     Soil samples  were collected from the pans immediately after application
(1205  hours April 7, 1983) and at hourly  intervals  over  a seven day period.
The soil was collected  in  resealable quart sized Zip-LockR plastic  storage
bags and transported to the laboratory on dry ice.  The samples were stored
frozen until  analysis.
     Leaf samples  (n « 100) were collected from cucumber plants across rows
within a 28 row  section.  Samples were obtained from plants  within  three  28
row  sections at different  times  over the seven day period.   In a similar
fashion, leaf samples (n * 100)  were collected from squash  plants  across
sections (n » 4) of 16 rows.  The leaf samples were obtained with  a
Birkestrand punch  (2.5  cm diameter).  The  leaf punches were  dropped from  the
punch  into  120 cc  plastic urine specimen containers and  transported on dry ice
to the laboratory and stored frozen until analysis.
-------
     Information to be gained from the study on the deposition and loss of  588
azinphosmethyl from panels, soil, and foliage was  to be compared with  a
companion study designed to assess exposure of  cucumber harvesters  to
azinphosmethyl.  Guthion  2L was  aerially  applied  to a  20  acre  field of
cucumbers at  the rate of 1.0 pint per acre  at 0930 on  2 May  1983.   The
aircraft was equipped to  cover 20 rows of cucumbers flying at 105 mph  with the
spray delivered through 8006 nozzles  at 35-40 psi.  The application along
north-south rows was completed at 1000 hours.  The temperature at 0930 was
800p.  The wind velocity  was 8-10 mph gusting to 22 mph from the southeast.
     Deposition of  azinphosmethyl was measured  on  panels  placed along rows in
a south-north plane (Fig.  2).  The panels were  designed identically to  the
previous study.   Panel  patches were collected in resealable pint sized Zip-
LockR storage bags  immediately after application.  The samples were
transported on dry  ice to the laboratory  and stored frozen  until analysis.
     Deposition and loss  of residues of azinphosmethyl  were estimated from
soil samples and leaf  punch samples.  Soil  pans similar to those described
earlier were  placed along rows within a section of 16  rows (Fig. 2).   Soil
samples were collected as previously  described  from the pans at various times
over a 4 day period.   The  soil was a  Willacy fine  sandy loam.  The  field had
been irrigated on 28 April  1983.   Moisture  content was not measured.
     Leaf samples  (n = 100) were obtained with a Birkestrand punch (2.5 cm
diameter) across rows within a  section of 16 rows  in accordance with the
method previously described.  Leaf punches  were collected from 8 sections
(Fig. 2) immediately  after  application and  Sections 2,  4, 6, and 8 at  various
times on subsequent days.
     Exposure of farmworkers to  residues  of azinphosmethyl while harvesting
cucumbers was assessed by measuring concentrations of  azinphosmethyl on
                                      8
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sampling devices worn by the harvesters.   In  addition,  the  absorption of         689
residues of azlnphosmethyl  was estimated  from measurements of the
concentrations of dialkyl phosphorous metabolites in urine  samples provided by
the harvesters before, during, and after  harvest.
     The workers arrived at the field at  0630.  After an  explanation of the
work proposed, the volunteers proceeded through a series  of study stations
where they signed consent forms and were  briefly interviewed.  The cohort
consisted of 6 females and 22 males (Tables 1 and  2).   Average age of the
females was 39.3 +_ 18.0 years (Table 1).   The youngest  female  was  17 years;
the oldest 61  years.   A 28  year old subject,  worker number 42, (Table 1) was 4
months pregnant.  This individual  weighed 68 Kg.  The average  weight of the
females was 63  +_ 12  Kg.  The average height was 1.58 +_ 0.06 meters.  The
average age of the males was 41.5 _+ 18.8  years (Table 2).   The average height
of the males was  1.68 _+0.06  meters.  The average weight  of  the males was
64^ 11.2 Kg.
     The workers entered the field at 0800.  While  they were harvesting, a
somewhat longer Interview (15-20 minutes) of  each worker  was undertaken to
obtain their work history as well as their perception of  their own health and
medical history (Appendix).   During the Interview,  notes  were  taken on
clothing worn and Individual picking practices (Tables  3 and 4).  Harvest
activities were completed by 1145 hours;  harvesters were  not in the field
longer than four hours.   The  number of buckets  of cucumbers picked by each
worker was obtained  from the labor contractor  (Tables  1  and 2).
     Gloves.   To estimate the amount of contact with pesticide residues
through the hands,  16 subjects were recruited  to wear a pair of lightweight
100% cotton twill work gloves with knit wristlets and seamless palms (Sears
catalog number 51 K 25915).   The average  surface area of  the gloves (minus the
-------
knit wristlet) was 85.2 in? _* 1.29 (549.7 cm2, n = 3).  After the  exposure
period, the gloves were sealed  In plastic bags and placed on dry  1ce.  The
samples were catalogued and stored frozen until analysis was started.
     Air Samples.   Seven of the  subjects were fitted with  DuPont P-4000
Personal Air Sampling Pumps equipped with an air sampling cartridges to assess
the potential for inhalation  of  airborne residues.  The pumps were clipped to
military web belts with the pump positioned  to ride at the waist at the small
of the back  (Fig.  3).   This location caused very little Interference with
worker movement.  The pumps were set to draw 1 liter/minute.  Calibration was
done just prior to sampling and  immediately upon returning from the field.
The time that the  workers wore the pumps was documented in two ways.  First,
each pump had a device to  report running time.  Second, these values were
compared with the notes on the times the pumps were checked out and checked
1n.
     The pumps were connected to the  cartridges  through a 90 cm length of 1/4
inch (inside diameter) x 1/16 inch (thickness)  Tygon  tubing.  The  tubing was
adapted to the 4 mm cartridge nipple with  a 4 cm length of 1/4  inch (outside
diameter x 1/8 inch (inside diameter) polypropylene tubing.   The  tubing from
the pump passed between an arm and the torso and cartridge was clipped to the
shirt collar (Fig. 3).
     The Bond Elute C18 Bonded Phase Cartridges were obtained from AnalytiChem
International, Harbor City, CA.  The 30 cc  syringe cylinder  was packed with
approximately  1.5  g of Sepralyte Octadecyl C18.  Cartridges exposed 1n the
field were sealed  inside a plastic  bag and transported on dry ice to the
laboratory.  The samples were stored frozen until analysis.
     Gauze Patches.   To assess the potential for pesticide contact and
absorption through the arms,  gauze exposure patches  with  surface  area
                                     10
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                                                                         691
103.2 cm?  per patch were  placed on 25 subjects, one on each forearm
outside the shirt, and one on each forearm Inside the shirt.  Workers
performed their normal work activity for 3.5  hours.
     Urine.  Study subjects were required to contribute urine specimens to
measure the concentration of pesticide metabolites which might result from
exposure while  harvesting cucumbers.  Specimens were obtained from each
subject.  Samples were collected  before  the subject started to work.
Additional samples were collected throughout the day.   Subjects were also
asked to provide a sample of their  first void  of the following morning.  Urine
samples were collected in standard plastic, four-ounce urine specimen
containers, and were placed directly on  dry ice for Immediate  transport to the
laboratory.  The samples  were cataloged  and kept  frozen  until  analysis.
                                     11
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                                                                         692
                            ANALYTICAL PROCEDURES
     Patches.   Gauze  patches from panels and clothing worn by the workers were
extracted in the same fashion.   Panel patches were extracted individually
(103.2cm2).  Rjght and left forearm  patches (206.4 cm2) were extracted
together.   The  patches were extracted three times in a 500 ml  Erlenmeyer flask
containing 75 ml methanol using a Burrel 1  wrist-action shaker at setting six.
The three extracts were combined, filtered through Whatman  No.l paper on a
Buchner funnel, dried with anhydrous sodium sulfate,  and  concentrated to 5 ml
on a Buchi Rotavapor  R110.  Final volume adjustment was made as needed prior
to analysis by high performance liquid  chromatography (HPLC) for  panel patches
and gas chromatograph (GC)  for  clothing patches.
     Soil.  Soil samples (10.0  g) were extracted three times in acetone with a
Burrel 1 wrist-action shaker on  setting  six.  The three extracts were combined,
dried with sodium sulfate, filtered through Whatman  No.l paper on a Buchner
funnel, and concentrated to 5 ml using  a Buchi  Rotavapor  R110.  Adjustments
were made to  the volume  prior  to analysis by HPLC.  This method was preferred
over the  method outlined in Sections 11,  A and 11,  B of the EPA  Manual  (U.S.
E.P.A., 1980).   Hexane was found to be a less desirable solvent for extraction
of these  soils than acetone.  A flocculent was  formed in  the presence of
hexane lessening the surface area exposed  to  the solvent.   Substitution  of
acetone for hexane  eliminated the formulation  of the  flocculent and resulted
in a 10 percent improvement in  recovery of azinphosmethyl.
                                     12
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  Foliage.   Leaf  punch  samples  (n = 10) with a combined surface area of of
50.0 cm2 were extracted according to  the method of Gunther et al.  (1974) for
the measurement of dlslodgable  residues.  The samples were extracted three
times for 15 minutes 1n the presence  of 75 ml  distilled water containing a
1:50 dilution  of  the  surfactant, Wltconol NP-100, on a Kraft shaker-1n-the-
round (Model  S-500) at  maximum speed.
     The three extracts were collected and  tranferred  to  a  1.0 L separatory
funnel and  extracted  three times with 150 ml methylene chloride.  A solution
of saturated sodium sulfate In water  was used  to  break up any emulsion that
formed.  The hexane was dried with anhydrous sodium sulfate and than
concentrated with a  Buchl Rotavapor R110 to 5 ml.  Final  evaporation to
0.5 ml was  done on a  Meyer N-Evap.  This volume  was  adjusted  to 5  ml  with
methanol.  Additional  volume adjustments were made  prior to  analysis by HPLC.
     Gloves.  The  gloves were cut into  1  to 2 cm2  pieces (the knit wristlets
were  not tested) and  placed in a 1.0  1  Erlenmeyer  flask and extracted three
times with methanol on a Burrell  wrist-action  shaker at setting eight.  The
pieces were tranferred to a Buchner funnel  and washed.  The extracts were
combined, filtered, and concentrated  to 5 ml with  a Buchl  Rotavapor R110.  The
volume was adjusted  as needed for analysis  by HPLC.
     Air Samplers. Extraction  of the residues from the entrapment medium of
the Bond Elute CIS cartridges  was accomplished by eluting  150 ml of acetone
through the cartridge at approximately  5 ml/m1n.  This solution was dried with
anhydrous sodium sulfate and evaporated to  1  ml  with a Buchl  Rotovapor R110.
The extract was analyzed by GC.
     Urine.  Each  specimen  was  prepared for analysis of dialkyl phosphorous
metabolites according to  a  modified method  of  the  procedures  described by Reid
and Watts (1981), Takade et al. (1979), and Daughton et al. (1979).  A
                                     13
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                                                                            694
1.0  ml  aliquot  of  the  urine  sample  was  diluted  to 20 ml with acetonitrlle in a
micro impinger tube.   Approximately 200 mg Nad was added to the azeotrope
mixture and was evaporated at 90-95° c  to near dryness.  The concentrate was
derivatized for 30 minutes at  90-95° C in the presence of 20 ml of a 5.55 mM
solution of 3-benzyl-l-p-toyltriazene prepared  in chloroform.  The derivatized
sample was evaporated to 1.0 ml  using a one  ball Snyder column.  The
concentrated sample was diluted with 15 ml of a 104 salt solution (0.57 g
NaCl/ml 12N HC1).  The diluted sample was extracted three times with 6.0 ml
ethyl ether.  The  organic layer was retained and dehydrated with anhydrous
Na?S04 and evaporated  to 0.1 ml.  The concentrate was adjusted to 1.0 with
acetone and prepared for GC analysis.
     The concentration of creatinine in the urine samples was measured
according to the method of Patel  and  George  (1981).   An aliquout of urine
(0.50 ml)  was diluted  with distilled deionized  water  to  12.5 ml.  The diluted
urine (0.10 ml) was thoroughly mixed with 0.20 ml acetonitrile.  The mixture
was  centrifuged at 1,000 RPM for 5  minutes to sediment particulate matter.
The supernatant was prepared for analysis by HPLC.
     Instrumentation.   Azinphosmethyl in  samples extracted from leaves, panel
patches . soil  and gloves was  detected  by reverse phase HPLC at 280 nm on a
Spectra-physics high pressure  liquid chromatograph equipped with a SP8700
solvent delivery system and  a  SP8440 variable wavelength detector.  The column
was  a  uBondapack  CIS  (Alltech  Associates,  Deerfield,  IL).  The flow rate of
the  mobil phase (45* acetoni trile,  55*  H2°^  was 1-° ml/mln.
     A Tracer 222 gas  chromtograph  was  used to assay  samples (air cartridges
and  shirt  patches) for azinphosmethyl.   Instrument parameters were as
follows:  detector, FPD in  phosphorus mode @ 256 nm;  column,
4* SE30/6* OV210 coated with Gas Chrom  Q, 80/100 mesh; column temperature,
                                     14
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200QC; detector temperature,  1900C;  carrier gasses, nitrogen @ 60 ml/min,£95
hydrogen @ 50 ml/min, and air @ 100 ml/mln.
     Alkyl phosphate concentrations were detected In urine by gas-liquid
chromatography (GC) with a Tracer 222 gas chromatograph equipped with a flame
photometric  detector (FPD).  The Instrument was operated  In the  phosphorus
mode (256 nm).  A 10% DC 200 column was used to separate  the four alkyl
phosphates  (DMP,  DEP, DMTP and DETP) at a  flow rate of 50 cc N2/m^n arxj a
column temperature of 198°C 1socrat1c.
     Creatinine was separated  by  HPLC  on a prepacked uBondapack  C}g column
with an average particle size  of  10 u  (Alltech Associates,  Deerfield, IL).
The flow rate of the mobile phase (25% acetonitrile and 75% methanol plus 1 ml
NH4OH) through the column was  1.5 cc/m1n from a Spectra Physics  SP 8700
solvent delivery system.  Creatinine was detected with a UV/VIS SP 8440
detector set at 254 nm.
     All detectors  were  Interfaced  with a Nelson Model 4400 Chroma tography
Data System.  Data  were reduced and stored on  diskettes.
     Recoveries.  Recovery of concentrates  of azlnphosmethyl from fortified
quality control  samples  of the environmental  substrates  (soil and  leaves) and
the sampling devices (gauze  patches and gloves) was examined to estimate  the
accuracy and precision of the  analytical methods.  Accuracy of the data was
understood  to relate to  the  relative error of  the mean of  a series of test
results to  the expected  result, as given by the percent recovery  (Anon,  1968;
McFarren et al.,  1970; Kirchmer,  1983).  The precision of the method was  given
by the percentage of the coefficient of variation (C.  V.) or the relative
standard deviation  (RSD),  as an index  of dispersion of a series of test
results.
     A series (n »  8) of  10  g soil  samples were fortified  with  100 ug of
                                     15
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azinphosmethyl.   The  mean recovery of the 8 samples was  9.64 +_ 0.37  ug/g
(96.4%) with an  RSD of  3.80%.  Recovery of azinphosmethyl (1.10 +_ 0.07 ug/cm2)
In gauze  patches (n = 9) was 113.6 percent  of  the  expected  fortification  level
(100 ug).  The recoveries were clustered about the mean  (RSD = 6.86%).  The
recovery  of  azinphosmethyl  (0.165 _+ 0.012  ug/cm2)  from gloves (n  « 6)  was 90.7
percent of the expected  fortification level (100 ug) and  well within control
(RSD » 7.42%),  less than 2 standard deviations of  the  mean.   The  recovery of
azinphosmethyl  (1.66^0.23 ug/cm2) from leaves (n = 14)  fortified with 100 ug
was more variable (RSD  • 13.9%) but within control.  The  percent  recovery  was
83.2 perecent.
     Recovery of dialkyl  phosphorous metabolites was examined In urine samples
fortified with dimethyl phosphate (DMP), dimethylthiophosphate (DMTP),
di ethyl phosphate (DEP)  and  diethylthiophosphate (DETP).   The minimum detection
limit (MDL)  for DMP was set at 0.10 ug/ml  with 0.087 +_ 0.01  ug/ml (RSD =
9.95%)  recovered  or 87.7  percent  of  the expected.  Detection of  the companion
dimethyl  phosphorous  metabolite, DMTP,  was more variable.  The MDL  was set at
0.10 ug/ml  from  observed  recovery levels of  0.099^0.042  ug/ml  (RSD  = 42.8%).
Recovery of the  diethyl  phosphorous  metabolite, DETP, was quite variable.  The
MDL was  set at  0.10 ug/ml  although the recovery (0.14+^0.06 ug/ml) was more
than expected (RSD =43.8%).  The minimum detection  limits for the  DEP  were
set at 0.25 ug/ml with a recovery of 95.6 ug/ml (RSD = 12.5).
     Concentrations of  the  dialkyl phosphorous metabolites  were normalized to
concentrations  of urinary creatinine.  Recovery of creatinine was examined in
urine  samples (n = 8) fortified  with 0.50 mg/ml.  The recovery of creatinine
(0.54  +_ 0.05) was 109 percent of  the expected with an RSD  of 8.93 percent.
     Analytical  Standards.  The  standards used in the recovery studies were
acquired from the U.  S.  Environmental Protection  Agency, Pesticides and
                                     16
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Industrial  Chemicals Repository (MD-8),  Research  Triangle  Park,  NC.  The     "     
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                                                                              698
                                  RESULTS

     Deposition of Guthion 2L was examined by detecting  residues of
azinphosmethyl  in a  single  patch  on  panels  (n = 5) placed within  rows  of the
squash and cucumber subplots in field one (Fig. 1).  Additional  depositional
data was obtained from a  companion study  of the examination of azinphosmethyl
residues on patches of 21 panels placed within rows of a second cucumber field
(Fig. 2).  The first field was treated with Guthion 2L by ground application
at 1205 hours on 7 April  1983.  The second f iel d was  treated wi th Guthion 2L
by aerial application at 0930 hours on 2 May 1983.   Comparisons of the
differences in deposition on  the sampling devices  between aerial and  ground
application were not attempted because of the differences in  the size and
location of the fields and  the unbalanced nature of the  designs.  The fields
were  treated Independently.
     Patches taken from the  apex of the trigonal pattern of  three patches were
used to estimate deposition.  Concentrations detected  1n  the  apex patches were
compared with patches from a selected corner.  A paired  comparison of the
differences in concentration between apex patches and  corner  patches  was found
to be not significant (t = - 0.8848, d.f. = 9, P <  0.40).  The deposition of
Guthion 2L on the three gauze  patches set in a trigonal  pattern on  the  panels
was  regarded as uniform.
     Because of the  location of  the  panels  (Fig. 1) and  the  size of the data
sets in the squash (n  = 3) and cucumber (n = 2)  subplots,  the deposition over
field one could not be estimated.  The mean concentrations of azinphosmethyl
                                     18
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                                                                              699
1n panel  patches from the squash subplot (0.30 +_ 0.10 ug/cm2) were found to
be not significantly different (t = - 0.2637, d.f.  = 3, P = < 0.50) than the
mean concentration (0.17  +_ 0.03 ug/cm2) obtained for the cucumber subplot
(Table 5).   The  concentrations of azinphosmethyl along the mldline of field
one were regarded as uniform.
     The larger sample size (n « 21) and design of the second field (F1g. 4)
allowed for an estimation of deposition  of  Guthion 2L after aerial
application.  The median  concentration of azinphos methyl detected in panel
patches was 0.57 ug/cm2.   The  mean concentration  was 0.73 +_ 0.44 ug/cm2.  The
incomplete  rows  and  column  design (Table 6) was partitioned into  subsets for
treatment according to a  two-factor analysis of variance without replication
(Sokal and Rohlf, 1969).   Missing values  for subset  1  (Table 7) were estimated
by iteration according to the  protocol  of Snedecor and Cochran (1976) for two
missing values.  The variance  among columns in the south to north direction
were  not  significantly different  (F2,e * 2-665°.  p  < °-10)-  The  differences
between rows  were also not significantly different (F^ g  r 0.1633, P < 0.25).
Adjustments in the estimation of the  error  and treatments sums of squares and
mean  squares with associated degrees of freedom were made according to  the
protocol of Snedecor and Cochran (1976)  for missing  values.  The one-way
analysis of variance with the columns as classes revealed no significant
difference  (F? in =  0.4219, P < 0.25)  among columns.   A similar treatment of
inside rows and  columns  in  subset 2  (Table 8) revealed  no significant
differences among columns (Fif3 s 0.0028,  P <  0.25) or between rows
*F3,3 = 0-1518,  P <  0.25).  The aerial application of Guthion 2L  appeared to
be uniformly distributed over the panels in field 2.
     Deposition and  loss of residues of azinphosmethyl  were examined in soil
samples and foliage  from both  fields  at various  times after the  application  of
                                     19
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Guthlon 2L.   Residue concentrations  in  soil  within strips of the squash
subplot in field one (Table 9) declined  in  accordance  with a first order rate
of decay (Fig.  5).   The half-life for the loss of azinphosmethyl  from soil
in strip 1  was estimated to be 2.85 days (Fig. 6)  from the slope of the
equation

     1.  Log (ug/g) = - 0.1056 days  + 1.1153
         r = - 0.9429, r2 • 0.8890,  n = 8,  P < 0.001.  6 d.f.

with 88.9 percent of the variablity attributed to the linear regression.  A
similar result (t 1/2 = 2.02 days) was obtained  for soil  from strip 3  (Fig. 7)
according to equation 2 with 95.6 percent of

     2.  Log (ug/g) = - 0.1490 days + 1.1614
         r = - 0.9827, r2 = 0.9557,  n = 7.  P < 0.001, 5 d.f.

the variability accounted for by the regression.  The half-life for the loss
of azinphosmethyl  from soils in strip 4 (Fig.  8)  was  slightly  longer (3.60
days).

     3.  Log (ug/g) = - 0.0835 days + 1.0236
         r = - 0.9430. r2 « 0.8893, r * 8,  P < 0.001, 6 d.f.

     The loss of residues of azinphosmethyl from  soil  in strips 2 and  3
(Table 10)  of the cucumber subplot (Fig.  1)  appeared  to  follow  a first order
decay  curve  (Fig. 9).  The half-life (1.78  days) of azinphosmethyl in  soil
from strip 2 (Fig. 10)  was estimated from the equation
                                      20
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                                                                           701
     4.   Log (ug/cm2)  ~  -  0.1692 days + 1.2894
         r - - 0.6434. r2  « Q.4140, n * 7, P < 0.20, 5 d.f.

with 41.4 percent of the variability attributable to ttie regression.   The
correlation coefficient  (r » - 0.6434) was  not  significant (t  «  -  1.8795,
P < 0.20, 5 d.f.).  The  half-life must be viewed with caution.
     The half-life  (2.66 days) obtained for strip 3  (F1g.  11) was more
consistent with the half-life estimates obtained for the squash subplot than
for strip 2.  The correlation coefficient (r «  - 0.9872) was significant
(t = -  15.1925, P < 0.001,  6 d.f.)  with 97.5 percent  of the variability
accounted for by the  regression equation

     5.  Log (ug/g) = -  0.1130 days +  0.9598
         r = - 0.9872, r2  = 0.9747, n  = 8.  P <  0.001, 6 d.f.

     A common  slope  (b  »  - 0.1185) was obtained by the analysis of covariance
of  the  slopes  of  the five regression equations (Snedecor and Cochran,  1967).
The slopes of the regression  equations were found  to be not significantly
different (F4>28  =  0.8743,  P  < 0.25).   The common half-life of azinphosmethyl
in soil from the 5  strips  of the  squash and cucumber subplots was  2.54 days.
     Estimates of the half-life  of residues of  azinphosmethyl  in soil from
strips (16 rows) within  the second field (Fig.  2)  could not be obtained.
Samples were taken from soil pans at widely divergent  sites within the strips
and at different times and dates  (Table 11).  The  study design did not permit
the statistical analysis of the data.  The median  concentration  for  the
samples (n = 12) was  2.03  ug/g.
                                     21
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                                                                              /
     Unlike the gradual  decline of residue concentrations on soils, residue
concentrations detected  on both squash  leaves  (Table 12) and cucumber leaves
(Table 13) 1n field one  declined  rapidly.  Half-life estimates of the loss of
azinphosmethyl from squash and cucumber leaves were not determined.  First
samples were obtained approximately 2 hours  after completion of  the ground
application of Guthion 21.  Reentry regulations did not permit sampling
immediately after  application (Ref  ).   The concentrations of azinphosmethyl
detected in leaf punch samples (n  = 2) obtained from strips within the squash
subplot (k = 4),  approximately 2  hours  after the  application of  Guthion 2L,
were  found  to  be not  significantly different  ^3,4 * 2.3661, P  < 0.25).   The
mean  concentration observed for the combined samples from the 4 strips  (N * 8)
was 1.47 +_ 0.27 ug/cm2.
     Initial leaf punch  samples from  the cucumber subplot were taken
approximately  4  hours after application (Table 13).  Because of  the
differences in sampling times, a comparison  of mean  concentrations of
azinphosmethyl in leaf punch  samples  from the  squash and cucumber subplots
was not attempted.  The concentrations  of azinphosmethyl  detected in leaf
punch samples (n *  2)  from the three sections within the cucumber subplot were
found to  be  not  significantly  different (F2>3 = 1.977,  p  <  Q.25).  The mean
concentration of azinphosmethyl (3.54 +_ 2.17 ug/cm2) detected in leaf punch
samples from cucumber leaves sampled approximately 4 hrs  after application was
observed  to be greater than the mean concentration (1.47  +_ 0.27  ug/cm2)
observed for leaf punch  samples from  squash  leaves obtained 2 hours after the
application.
     Leaf punch  samples from strips  (n =  8) in  the  second  cucumber field
sampled on 2 May 1983 were obtained immediately after aerial  application.  The
research  team  wore protective  clothing to obtain the samples.  The
                                     22
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                                                                            703
concentrations of azinphosmethyl  detected  in  leaf  punch  samples  (n = 100) over
the sampling period 2 May 1983 to 6 May 1983  (Table  14) appeared to decline 1n
accordance with a first order decay curve (Fig.  12).  Because of the
unbalanced nature of the  design (Table 14), an estimate  of the half-life of
azinphosmethyl on cucumber leaves  was not  determined.
     Exposure of cucumber harvesters to residues of Guthlon 2L was  examined by
measuring concentrations  of azinphosmethyl  on sampling devices worn by the
workers and by detecting concentrations of the dialkyl phosphorous  metabolites
dimethyl phosphate (DMP) and dlmethylthlophosphate  (DMTP) In urine samples
provided by the workers.   The harvesters entered field 2 (F1g. 2) two days
after the aerial application of Guthlon 2L and were  monitored for three and
one half hours for the  accumulation of residues of azinphosmethyl on sampling
devices, air sampling  cartridges  (n = 7),  gloves  (n  = 16), and gauze patches
worn on the outside (n «  25)  and  Inside forearm sleeves of their work shirts.
Azinphosmethyl was not detected 1n any  of  the air  sampling cartridges
(Table 15).  The workers  did  not  appear  to contact airborne  residues.
However,  the  efficiency  of the  air sampling  devices was  not established.
A more detailed study 1s  required to assess respiratory  exposure.
     Concentrations of azinphosmethyl were detected  in gauze  patches
(206.4 cm2) located on the outside (P = 0.60) and  inside (P = 0.24)
forearm sleeves of workshlrts worn by some of the workers (Table 15).
Azinphosmethyl was not detected in 40 percent of the outside  patch samples
(1 - P = 0.40) and 76 percent of  the Inside patch samples (1 -  P = 0.76).
Concentrations detected in outside patches were  found to  be  significantly
greater (T » 3.241,  P < 0.001) than  Inside  patches according  to  the Wilcoxon
signed ranks test for matched pairs (Conover, 1980).  This test  was  preferred
over the paired t-test because of the number  of zero values.  The median
                                     23
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concentration observed for outside  patches was 0.03 ug/cm2; the mean value
0.011 ^ 0.020 ug/cm2.
     Concentrations of azlnphosmethyl  detected  in right hand  gloves  (0.93 _+
0.46  ug/cm2)  were found to be not significantly  different  (t  » 0.0082, d.f.  =
15, P < 0.001) than concentrations  detected  in left hand gloves (0.92 +_ 0.54
ug/cm2)  according to the  t-test on  paired samples  (Table 15).   The harvesters
did not  appear to demonstrate handedness while harvesting.   The mean
concentration observed for right  hand gloves (0.92 +_ 0.54 ug/cm2) was found
to be significantly greater (t =  9.805, d.f. =39,  P  < 0.001) than the
mean concentration obtained for outside arm patches (0.011 +_
0.20 ug/cm2).  Exposure of harvesters to residues of  azinphosmethyl
appeared to occur through predominately contact with the hands.
     The dialkyl  phosphorous metabolite DMTP was  detected in morning voids of
one female harvester (Table 16) and one male harvester (Table 17) on the
second day following harvest of cucumbers  in field two.  Dialkyl phosphorous
metabolites were not detected in  the urine  of any other subjects.  The
harvesters did not appear to absorb residues of azinphosmethyl  after three and
one half hours of work harvesting cucumbers.  Concentrations of DMTP, however,
did appear in the urine of two subjects 24  hours  after  entering  the  field.
Excretion of detectable levels of DMP and DMTP may have  occurred  later.
Clinical surveilance of exposure  to  organophosphorous insecticides by the
determination of dialkyl  phosphorous metabolites in urine may require a more
extended period of monitoring.
                                     24
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                                                                              705
                         INTERPRETATION AND ANALYSIS

     Farmworkers entering a field (F1g. 2)  located In the Lower Rio Grande
Valley (LGRV)  of South  Texas to harvest cucumbers two days after an aerial
application of Guthion 2L accumulated residues of azinphosmethyl on gloves
(Table 15) and outside  shirt patches  (Table  15) but did not appear to absorb
residues after  three hours and 30 minutes  of  harvesting (Tables 16 and  17).
The deposition of azinphosmethyl  on artificial substrates, panels, within the
field appeared  to be uniform (Fig.  4).   Loss of residues of azinphosmethyl
from leaves appeared to rapid (Fig.  12).  The  half-life of azinphosmethyl on
soil from  an  ajoining field was estimated  to  be 2.54 days.  A substantial loss
of residues on  leaves and soil  may be expected prior  to reentry.
     The harvesters did accumulate residues on gloves at much higher
concentrations than on arm patches.   This observation appeared to  be
consistent with the  results of  Wolfe et al. (1966) and Davis et al.  (1983)
where hand exposures might range from  20 to 50 percent of the total  exposure.
Davis et  al.  (1983) cautioned,  however, that residue  levels obtained from the
use of absorbent gloves might represent an  over estimation of potential  dermal
exposure.  Accepting the values obtained for gloves  as  exaggerated estimates
of exposure, the upper limit of dermal  exposure of  azinphosmethyl  on  the
hands may be  extrapolated to be 0.31 ug/Kg/hr  using  the estimates  of  body
surface area  given by  Hansen et al. (1978)  for the hands (0.082 m2) of a 70 Kg
individual exposed  for 3.5 hours.
     The concentrations detected In outside shirt  patches  (Table 15) was
considered negligible.   In  addition,  residues  of azinphosmethyl  did not  appear
                                     25
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                                                                            706




to penetrate the shirt as indicated by the significantly lower



concentrations detected in inside shirt patches (Table 15).  A similar



result was observed by Hansen et al. (1978) for tractor drivers and sprayers



wearing similar clothing but exposed to much higher concentrations of



azinphosmethyl for longer periods.  Indeed, Hansen et al. (1978) projected



from their findings that normal work clothing may be adequate to protect



workers exposed to azinphosmethyl in an orchard spray program.  Davis et al.



(1983) concluded that workers thinning apples may experience little acute or



semiacute (subacute) toxic hazard when exposed to residues of azinphosmethyl



beyond the 24 hour reentry limit.  The dislodgable residues of



azinphosmethyl detected on apple leaves by Davis et al. (1983) were far in



excess (1.9 + 0.2 ug/cm2) of the concentrations detected in cucumber leaves



(Tables 12 and 13) two days after the aerial application of Guthion 2L at



the rate of 1 pint per acre (210 g/acre) may be expected to contact 0.31



ug/kg/hr through the hands while harvesting for 3.5 hours without clinical



signs or symptoms or the appearance of metabolites of azinphosmethyl in the



urine within 2 days of exposure.  Youths (age < 17 yrs) may be expected to



contact similar levels as adults  (age 2 17) but may experience greater risk



of acute intoxication because of lower weights (Munn et al., 1985).
                                    26
-------
                                                        707
            North edge
            —170 m	
     E
     o
     CO
 0)
 "5
 o
     E
    10
    cvi
—  —  —  —   —u
Squash   "         4 \\
—  —  _••  —   —\)
Cucumber
                                   16  rows
28 rows
                    •185  m
Fig. 1.  Schematic representation of the cucumber and
squash subplots and the arrangement of soil pans •
and panels • within strips in  field one.  The field
was treated with Guthion 2L by  ground application on
7 April  1983.
                   27
-------
NJ
OO
                11       57      103     149     195
           Distance (meters)  from west edge of  field
            Fig. 2.  Schematic representation of cucumber field two and the arrangement
            of soil pans • and panels •  along rows within strips aligned in a south-
            north plane. The field was treated with Guthi on 2L by aerial application
            on 2 May 1983-
                                                                                                CD
                                                                                                CO
-------
                                                                 709
                                      Subject Number
             /         Arm Patches         /
        Leg Patches                Cotton Gloves
Fig.  3>  Positions of sampling devices (air pumps, body patches
and gloves) worn by workers  harvesting cucumbers treated with a
formulation (Guthion 2L)  of  azinphosmethyl.
                        29
-------
UJ
o
                                    1.63
      14VW      »,.,.  mia
              ifa    I
       «•       l     •     i
                              f       f       f

                             103    149    19
    11     57     103    149    195

Distance (meters) from west edge of field



 Fig. 4.  Deposition of Guthion 2L detected as azinphosmethyl in gauze patches on
 panels tn the second cucumber field,
-------
                                                                    711

^
O)
"o>
D
_ ^
>
0)
E
(0
o

QL
C
*N
03

20.0
18.0

16.0
14.0

12.0
10.0
8.0

6.0

4.0

2.0

—

3
_
.
3 1

3
1
4
-
4 3 1
4 4
"


1 I I 1 1 I I
1.0    2.0    3.0    4.0    5.0

             Days
                                                         6.0
Fig.  5.  Decline or  loss of residue concentrations of azinphosmethyl
from  soil contained  within pans  in strips 1,3,  and k of the  squash
subplot  in field one.  Numbers represent strips.
                           31
-------
                                                              712


'5
O)

jz

H%\
I %>%N
N^^ '
^v%
""\


—

i i i i iii
              1.0    2.0   3.0    4.0   5.0   6.0

                   Days after  application
Fig. 6.  Semi logarithmic display of  residue concentrations of
azinphosmethyl detected in soil obtained from pans in  strip 1 of
the squash subplot in field one.
                          32
-------
    18.0
    16.0
    14.0
    12.0
di  10.0

0>   8.0
—   6.0
-------
   14.0

   12.0

O) 10.0

    8.0
 O)
 3
 5*
JC

 0
 E
 CO
 o

 Q.
 C
"N
 CO
     6.0



     4.0
    2.0
                                                          714
           0   1.0   2.0   3.0     4.0   5.0    6.0

                    Days after application
 Fig.  8.  Semilogarithmic display of residue concentrations of
 azinphosmethy1 detected in soil obtained from pans in strip A of
 the squash subplot in field one.
                          34
-------
                                                                  715



^^
D)
O)
3
•5,
0
E
(0
o
a
•~
CO



1 1.0

10.0

9.0

8.0
7.0
6.0
5.0

4.0
3.0

2.0

1.0


2

3


3 2
3
2
2
2
3
23
3 2
3
_
3
-
I 1 I I I I 1
             0     1.0    2.0    3.0    4.0    5.0    6.0

                                Days
Fig.  3.  Decline or  loss of residue concentrations of azinphosmethyl
from  soil contained  within pans  in strips 2 and  3 of the cucumber
subplot  in field one.  Numbers represent strips.
                          35
-------
                                                            716


O)
^^%
0)
D

—
.n
**
o>
E
CO
O
JC
Q.
c
*N
CO



14.0
12.0
10.0

8.0

6.0

4.0




2.0





-N

\
:
\
N
x *
x%
\ •
X

xx
\
vv
vx
s
1)11 111
          0    1.0   2.0    3.0    4.0   5.0    6.0

                   Days  after application
Fig.  10.  Semilogarithmic display of residue concentrations of
azinphosmethyl detected in soil obtained from pans  in strip 2 of
the cucumber subplot.
                        36
-------
 O)

 O)
 D
 0
 E
 CO
 O

 D.
^C
*N
 co
14.0
12.0

10.0

 8.0


 6.0



 4.0
 2.0
                                                             717


               1.0   2.0   3.0     4.0   5.0    6.0

                    Days after application
 Ffg.  11.  Semilogarithmic display of residue concentrations of
 azinphosmethyl detected in soil obtained from pans in strip 3 of
 the cucumber  subplot.
                         37
-------
                                                                 717
    1.4  .
~  1.2
CM
 0
    0.8  J
    0.6  .
     0.4
 N
     0.2 .
        0 .
s

1

7
                                                     2

                                                     4
                                                      68
                        1.0
                     2.0          3.0
                       Days
4.0
      Fig. 12.   Decline or  loss of residue concentrations of azinphosmethyl
      on  leaf punch samples taken from cucumber plants within strips of the
      second cucumber field.  Numbers refer to strips.
                               38
-------
                                                                            718
Table  1.  Cohort of six human female subjects exposed to dlslodgable
residues of a liquid formulation (Guthlon 2L)  of azinphosmethyl while
harvesting  cucumbers on a 21  acre field In the Lower R1o Grande Valley of
Texas.   A dash  (-) Indicates a missing value.   Values  In  parentheses are
heights In  Inches or weight In pounds.  The buckets used  during harvest are
plastic and have a five gallon capacity.   The  mean value  Is  accompanied by the
standard deviation.
Worker
Number
3
18
30
42
48
49
Physical Characteristics
Age
61
17
61
28
37
32
He1ght(m)
1.55 (61)
-
1.65 (65)
-
1.60 (63)
1.52 (60)
Welght(kg)
49 (108)
51 (112)
64 (142)
68 (150)
80 (177)
65 (145)
Buckets
Harvested
21
20
21
13
18
13
Mean
39.3 + 18
1.58 + 0.06
63 + 12
                                                                  17.7 + 3.8
                                     39
-------
                                                                          719
Table 2.   Cohort of 22 human male  subjects exposed to disiodgable residues of
a liquid formulation  (Guthion 2L) of azinphosmethyl while harvesting
cucumbers on a 21 acre field in the Lower Rio  Grande  Valley of Texas.  A dash
(-)  indicates  a missing value.  Values in parentheses are heights in inches or
weight in pounds.   The buckets  used  during harvest are plastic and have a five
gallon capacity.   The mean value  is accompanied  by the  standard  deviation.
Worker
Number Age
1 38
26 42
31 24
33 53
34 47
35 38
36 19
37 22
38 39
39 36
43 34
45 28
46 52
47 25
50 70
51 85
52 61
53 65
54 34
55 65
Physical Characteristics
Height(m)
1.65 (65)
1.83 (72)
1.68 (66)
1.68 (66)
1.70 (67)
1.70 (67)
1.62 (64)
1.62 (64)
1.75 (69)
1.70 (67)
1.68 (66)
1.75 (69)
1.57 (62)
1.70 (67)
1.60 (63)
-
1.70 (67)
1.65 (65)
1.62 (64)
1.65 (65)
Weight(kg)
70 (155)
96 (212)
60 (132)
77 (169)
57 (125)
82 (180)
52 (115)
64 (142)
60 (132)
54 (120)
54 (119)
72 (158)
54 (119)
53 (116)
68 (150)
66 (145)
65 (144)
73 (160)
54 (119)
67 (148)
Buckets
Harvested
20
-
21
18
26
13
17
16
18
13
33
20
-
13
18
14
11
20
25
.
                                     40
-------
Table 2.  (Cont.)                                                             7 9f)
SS=SS3SSSSSSSSSSSSSB3SS=SSS5SSSBSSBSSSSCSS=SSSSSaSSSS=SS3SBSS=SS=S=SS:SSSSS==SSS
                                 Physical Characteristics
Hurncr
Number
56
57
Age
17
19
Height(m)
1.68 (66)
1.62 (64)
Weight(kg)
54 (118)
55 (122)
DUkKCi.3
Harvested
19
21
      Mean         41.518.8   1.68+ 0.06     6411.2         18.7 +5.3
                                     41
-------
                                                                         721
Table 3.  Description of apparel  worn by  six  female  subjects exposed to
dislodgable residues of a liquid formulation (Guthion  2L) of azinphosmethyl
while harvesting cucumbers on a 21 acre field in the Lower Rio Grande Valley
of Texas.   Abbrebiations or keys used In  the  table are as follows:  under
Footwear,  BT = Boots, SH * Street Shoes,  SX » Stockings Only, TN = Tennis
Shoes; Trouser Type, 1 = Other, 2 » Jeans; Shirt, 1 =  Study, 2 = Non Study;
Gl oves, 1  = Gl oved, 2 • Ungl oved; Headwear,  1 = Cap, 2 =  Hat, 3 = Bare, 4 =
Handkerchief;  Air Sampler,  1 * Yes, 2 * No.
                              Articles of Clothing
   Worker               Trouser                                     Air
   Number    Footwear     Type      Shirt     Gloves     Headwear   Sampler


     3         TN          1         1          1          4          2

    18         SX          1         1          1          1          2

    30         TN          1         1          1          2          2

    42         TG          1         2          2          3          2

    48         TN          1         2          1          1          1

    49         SH          1         2          1          1          2
                                    42
-------
                                                                             722
Table 4.  Description of apparel worn by 22 male subjects exposed to
dislodgable  residues of a liquid formulation  (Guthion 2L) of azinphosmethyl
while harvesting cucumbers on a 21 acre field in the Lower Rio Grande Valley
of Texas.  Abbrebiattons or keys used in the table are as follows:   under
Footwear,  BT » Boots, SH = Street Shoes, SX * Stockings Only, TN «  Tennis
Shoes; Trouser Type, 1 = Other, 2 « Jeans; Shirt, 1 = Study, 2 » Non Study;
Gl oves, 1  «  Gl oved,  2 * Ungl oved; Headwear,  1 * Cap, 2 » Hat, 3 * Bare, 4 =
Handkerchief;  Air  Sampler,  1 « Yes, 2 * No.
Worker
Number
1
26
31
33
34
35
36
37
38
39
43
45
46
47
50
51
52
53

Footwear
SH
BT
TN
SH
SH
SH
BT
BT
BT
BT
BT
BT
SH
SH
BT
BT
BT
SH
Articles of Clothing
Trouser
Type
1
1
2
1
1
1
1
2
2
2
1
1
1
1
1
1
1
1
Shirt
1
1
1
1
1
1
2
1
1
1
2
1
2
2
1
2
2
1
Gl oves
1
2
1
2
1
1
1
1
2
2
1
1
2
2
1
1
1
2
Headwear
1
1
1
2
1
1
3
1
1
3
1
1
3
1
1
1
1
2
E8SSSSSSSSSS
A1r
Sampler
2
2
2
1
2
2
2
2
1
1
2
2
2
2
2
2
2
2
                                    43
-------
Table 4.  (Cont.)                                                       723
==================================================================:
Articles of Clothing
Worker
Number
54
55
56
57
Footwear
BT
BT
BT
BT
Trouser
Type
1
1
1
1
Shirt
1
2
2
1
Gl oves
2
2
2
1
He ad wear
1
1
3
1
Air
Sampler
2
1
1
1
                                 44
-------
                                                                          724
Table 5.   Concentrations of azlnphosmethyl (ug/cm2) detected In gauze patches
          (103.2 cm2) from panels placed within strips of the  squash and
          cucumber subplots 1n field one (F1g.  ) after ground application of
          Guthlon  2L at 1205  hours on  7  April  1983.

3============================================================================5
       Panel  Location                          Subplot
Strips
2
3
1
3
4
Squash

-
0.27
0.21
0.41
Cucumber
0.19
0.15
_
.
—
                                  0.30 +  0.10          0.17 + 0.13
===================================================================
                                     45
-------
                                                                             725
Table 6.  Concentrations of azinphosmethyl  (ug/cm2)  detected  in  panel patches
          from sampling sites along south  to north and west to east
          coordinates in the second cucumber field following  an  aerial
          application of Guthion 21 at 0930 hours on 2 May 1983.

===========*====================================================»=============
Distance from         Distance (meters)  from south edge  of field
west edge of      	
field               23         61          114         152        198   Total


     11            0.18                   1.75                    0.41   2.34

     34                       0.40                    0.33              0.73

     57            0.95                   0.84                    1.63   3.42

     80                       0.31                    0.50              0.81

    103            1.26                   1.19                    0.85   3.30

    126                       1.08                    0.77              1.85

    149            0.25                   0.37                    MVa    0.62

    171                       0.52                    0.57              1.09

    195            0.68                   0.50                    MVa    1.18



Total              3.32       2.31        4.65        2.17        2.89   15.34

==============================================================================



a Missing value
                                     46
-------
                                                                         726
Table 7.   Subset  1, values and coordinates for estimation  of  homogeneity of
          deposition (ug/cm2)  of azlnphosmethyl  by two factor analysis of
          variance  without  replication.

33SSS33SS3SSS333S3S3SS33S3333SSS=3SS33=3S=S333S=S3SS333333SS3333333S33S33=3:
Distance  from         Distance (meters) from South Edge of Field
web u my
Field
11
57
103
149
195
Total
=======3
e ui
<
0
0
1
0
0
3
23
.18
.95
.26
.25
.68
.32
3333533
1
1
0
1
0
0
4
3=333353=3=33333
14
.75
.84
.19
.37
.50
.65
19
0.
1.
0.
0.
0.
3.
8
41
63
85
25a
54a
68
Total
2.34
3.42
3.30
0.87
1.72
11.65
a  Values  obtained by Iteration
                                    47
-------
                                                                         727
Table 8.   Subset 2, values and coordinates for estimation  of  homogeneity
          deposition  (ug/cm2) of azinphosmethyl  by two factor analysis of
          variance  without replication.
Distance from
wcS u CO ye QT
field
34
80
126
171
Distance (meters)
61
0.40
0.31
1.08
0.52
=====ss ===============—=
from south edge of field
152
0.33
0.50
0.77
0.57

Total
0.73
0.81
1.85
1.09
Total                        2.31                    2.17               4.48
                                     48
-------
                                                                             728
Table 9.   Deposition and loss of residues of  azinphosmethyl from soil
          contained in aluminum cooking pans  (522.6 cm2) aligned in
          parallel lines of five pans within  strips (16 rows) of the
          squash  subplot in field one (Fig.  1).
3S333S33SBB333B333SSS33E33333333S3S3S3333S333SS3S
Strip 1 Strip 3
Day
post
applic.
0
0.14
0.93
1.88
2.88
3.97
4.88
5.89
Strip 4
Azinphosmethyl Day Azinphosmethyl Day
concentration post concentration post
(ug/g) applic. (ug/g) applic.
11.8
12.4
13.1
6.47
8.80
5.83
3.69
3.22
0
0.15
0.98
1.93
2.92
4.02
4.90

17.2
12.7
10.6
6.57
5.66
3.19
3.10

0
0.16
1.00
1.96
2.94
4.05
4.92
5.92
Azinphosmethyl
concentration
(ug/g)
12.0
12.0
7.30
5.76
6.15
4.62
4.77
3.42
                                    49
-------
                                                                          729
Table 10.   Deposition and loss of residues of azinphosmethyl  from soil
           contained in aluminum cooking pans (522.6 cm?)  aligned in
           parallel lines of five pans within strips (28 rows)  of the
           cucumber subplot in field one (Fig. 1).

3S33333S33S333S33333S33SSSBSS3S3S3333S333333333S333333333S3S3333SS33333BBBBB3S
               Strip  2
Strip 3
Day
post
application
0
0.16
1.02
1.98
2.97
4.14
4.96

Azinphosmethyl
concentration
(ug/g)
10.6
6.12
8.29
6.25
4.24
5.47
3.30

Day
post
application
0
0.17
1.02
2.01
3.01
4.16
4.97
5.88
Azinphosmethyl
concentration
(ug/g)
9.82
8.24
7.43
4.68
4.15
3.59
2.55
1.84
                                     50
-------
                                                                     730


Table 11.   Concentrations  of azlnphosmethyl detected In soil samples (10 g)
           taken from soil (100 g) contained In aluminum cooking pans
           (522.6 cm2) placed within sections of 16 rows aligned 1n a
           south to  north  direction (Fig.  2).

==============================================================================
 Sample Collection          Location of Sample
Date
May 1983
2
2
2
2
3
3
3
4
4
4
5
5
Time
(hrs)
1000
1000
1000
1000
1115
1128
1118
0915
1055
1035
0835
0915

Section
3
5
5
7
5
7
5
3
5
7
3
5
D1 stance
West Edge
57
103
103
149
103
149
103
57
103
149
57
103
From (m)
South Edge
23
23
134
23
114
114
114
114
114
197
197
197
Azinphosmethyl
Pf\ n/* An far* A ^ ^n n
i/uriucn tra t lu n
(ug/g)
4.60
3.28
3.62
1.73
0.92
1.92
2.37
3.48
1.65
0.69
0.77
2.14
                                                        Median = 2.03 ug/g
                                                  :===============:
                                     51
-------
                                                                             731
Table 12.  Concentrations of azinphosmethyl  detected on  leaf  punch  samples
           (n = 100) obtained from strips (16  rows) within  the  squash
           subplot (Fig. 1) at various times throughout  the sampling period
           7 April 1983 to 13 April  1983.

====a=======3=========s==s===s==========================s=====a===============
                  Strip 1         Strip 2         Strip  3        Strip 4
damp i i ng
Date
(April 1983)
7
7
8
8
9
9
10
10
11
11
12
12
13
13
Time
(hrs)
1415
1422
1040
1058
0930
0945
0925
1050
1135
1155
0930
0940
0945
1000
ug/cm2
1.65
1.22
ND
0.65
0.63
1.49
ND
0.97
ND
ND
ND
ND
ND
ND
Time
(hrs)
1430
1445
1115
1127
1003
1016
1050
1005
1215
1230
1030
1010
1007
1030
ug/cm2
1.46
1.67
1.65
0.41
ND
0.71
0.97
ND
ND
0.54
ND
ND
ND
ND
Time
(hrs)
1500
1510
1145
1200
1040
1055
1025
1040
1245
1300




ug/on2
1.14
1.17
2.74
ND
ND
0.57
0.60
0.76
ND
ND




Time
(hrs)
1520
1530
1215
1232
1120
1130
1100
1115
1320
1325




ug/cm2
1.91
1.52
ND
ND
0.82
0.87
0.51
ND
ND
ND




                                     52
-------
                                                                           732
Table 13.   Concentrations of azinphosmethyl  detected on  leaf punch samples
           (n  « 100) obtained from strips (28 rows) within the cucumber
           subplot  (F1g. 1) at various times throughout  the sampling period
           7 April  1983 to 12 April 1983.
Camnl 1 nn
OQIII^J 1 1 Iiy
Date
(April 1983)
7
7
8
8
9
9
10
10
11
11
12
12
:ssszs=aiss=Bsssass3s=assss=B:
Strip 1 Str

Time Time
(hrs) ug/cm2 (hrs)
1550 2.24 1620
1600 0.93 1640
1305
1322
1200
1215
1150
1205
1535
1600
1120
1135
:======s=x:
IP 2

ug/cm2
4.64
3.00
0.08
ND
ND
1.36
0.14
0.59
0.08
0.67
NO
ND
:==c=====:
Str

Time
(hrs)
1647
1657
1355
1415
1230
1250
1235
1255
1500
1525


:===========
ip 3

2
ug/cm
3.22
7.22
0.05
0.06
0.11
1.20
0.58
ND
0.55
0.84


                                    53
-------
                                                                          733
Table 14.  Concentrations of azlnphosmethyl (ug/cm2)  detected on leaf punch
           samples (n = 100) obtained from cucumber plants within  strips (n
           8)  of the second field (Fig. 2) sampled from 2 May 1983 to 6 May
           1983.
 Sampling             Day                     Strips  1n Field
uaie
(May 1983)
2
3
4
4
4
5
5
5
5
6
6
6
6
lime
(hrs)
1000
1000
1035
1150
1210
0914
0940
1000
1030
0825
0900
0933
1005
application 1 2 3
0.42 0.39 1.47
1.00
2.01 0.47
2.06
2.09
2.96 0.33
2.97
3.00
3.01
3.93 0.05
3.96
3.97
4.00
45678
0.49 1.39 0.30
0.72

0.66
0.05

0.26
0.09
0.09

0.01
0.05
0.04
 :=====================================================================zr======
                                     54
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     Table  15.  Concentrations of azinphosmethyl detected in sampling devices
worn by farmworkers harvesting cucumbers  in Field Two  (Fig. 2).  Harvesters
entered the field 2 days after an aerial  application of Guthion 2L on 2
May 1983.   Exposure was monitored for 3 hours and 30 minutes (0800 to 1130
hours).
                                                                               734
Worker
Ident i f ication
Number
1
3
18
26
30
31
33
34
35
36
37
38
39
42
43
45
46
47
Air Shirt Patches
(ug/m3 ) Outside
0.006
ND
0.009
ND
ND
ND
ND 0.021
ND
0.003
0.023
0.011
ND ND
ND 0.033
0.006
ND

ND ND
ND ND
(ug/cm2 )
Inside
0.001
ND
ND
ND
ND
ND
ND
ND
ND
0.002
0.008
ND
ND
ND
ND



Gloves
Right
0.63
0.95
0.68

0.57
1.06

0.83
0.43
1.11
0.65



2.07
0.92


(ug/cm2
Left
0.70
1.05
0.85

0.40
1.14

2.15
0.23
1.02
0.42



1.86
0.71


(Cont.)
                                         55
-------
Table 15.   (Cent.)
                                                                      735
3=============================================================3=======S===S==r
Worker
Shirt Patches (ug/cm2)    Gloves (ug/on2)
luentir ica tiun
Number
48
49
50
51
52
53
54
55
56
57
Samplers (ug/m3) Outside
ND 0.001
0.067

0.028
0.006
0.005
0.062
ND 0.002
ND ND
ND
Inside
0.004
ND

ND
ND
0.001
0.003
ND
ND

Right
0.66
0.45
1.70

0.69




1.44
==============
Left
0.70
0.30
1.40

0.67




1.21
=======
                                   56
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                                                                               736
Table 16.  Urinary metabolites of organophosphorous Insecticides  detected in
urine collected from six female agricultural  workers harvesting cucumbers
treated with a liquid formulation of azinphos methyl, Guthion 2L,  at the rate
of one pint acre (0.25 IDS azinphosmethyl per acre).  Abbreviations for
urinary metabolites are as follows: DMP = Dimethyl phosphate, DMTP »
Dimethylthiophosphate.  Samples with missing values are indicated by a
dash (-).  ND - Not detected
                 Day  of       Time of   Urinary Metabolites (ug/ml )
Worker   Void     Void         Void     ...........................  Creatinine
Number  Number  Collection  Collection        DMP        DMTP           (mg/ml )


   3       1       1         0745            ND         ND           0.15
           2       1         0905            ND         ND           0.08
           3       1         1130            ND         ND           0.60
           4       2         0800            ND         ND           0.31

  18       1       1         0800            ND         ND           0.09
           2       1         1135             -

  30       1       1         0735            ND         ND           1.59
           2       1         1135            ND         ND           3.94
           3       2         0800            ND        0.23           1.18

  42       1       1         0830            ND         ND           0.54
           2       1         1130            ND         ND           0.91

  48       1       1         0750            ND         ND           0.78
           2       1         1135            ND         ND           0.83
           3       2         0800            ND         ND           2.02

  49       1       1         0745            ND         ND           1.32
           2       1         0925            ND         ND           1.06
           3       2         0800            ND         ND           0.60
                                     57
-------
                                                                            737
Table 17.   Urinary  metabolites of organophosphorous Insecticides detected  In
urine collected from  22  male  agricultural workers harvesting cucumbers treated
with a liquid formulation  of  azlnphosmethyl, Guthlon 2L, at the rate of one
pint per acre (0.25 Ibs. azlnphosmethyl per acre).  Abbreviations for
urinary metabolites are  as follows: DMP = Dimethyl phosphate, DMTP =
Dimethylthiophosphate.   Samples  with missing values are Indicated by a
dash (-).  NO = Not detected
Worker
Number
1


26


31

33


34


35


36


37


38


39

Void
Number
1
2
3
1
2
3
1
2
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
Day of
Void
Collection
1
1
2
1
1
2
1
1
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
2
1
1
Time of Urinary Metabolites (ug/ml
Void -- 	
Collection
0755
1135
0800
0740
1140
0800
0940
1135
0755
1130
0800
0750
1125
0800
0750
1135
0800
0900
1135
0800
0750
1135
0800
0750
0905
0800
0755
1140
DMP
ND
ND
-
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
-
ND
ND
ND
ND
ND
DMTP
ND
ND
-
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
0.10
ND
ND
-
ND
ND
ND
ND
ND
)
- Creatinine
(mg/ml )
0.21
1.03
-
0.89
1.14
1.18
1.67
2.44
1.07
2.42
2.86
3.28
3.48
0.50
2.90
2.82
0.98
1.68
0.92
1.81
0.63
1.51
-
0.60
0.46
0.60
1.12
1.44
                                     58
-------
Table  17. (Cont.)
                                        738
                Day of       Time of
Urinary Metabolites (ug/ml)
nor*er
Number
43


45


46


47
50


51

52

53


54



55


56


57


VUIU
Number
1
2
3
1
2
3
1
2
3
1
1
2
3
1
2
1
2
1
2
3
1
2
3
4
1
2
3
1
2
3
1
2
3
VUIU
Collection
1
1
2
1
1
2
1
1
2
1
1
1
2
1
2
1
1
1
1
2
1
1
1
2
1
1
2
1
1
2
1
1
2
Collection
0800
1135
0800
0800
1120
0800
0755
1145
0800
1130
0750
1130
0800
1130
0800
0755
1130
0755
1130
0800
0755
0900
1125
0800
0755
1145
0800
0800
1140
0800
0800
1140
0800
DMP
NO
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
DMTP
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
(mg/ml )
0.46
1.25
1.29
0.88
0.28
1.74
0.28
0.83
0.76
2.85
1.71
1.24
2.32
0.32
1.13
0.67
1.95
0.79
1.98
0.83
0.99
3.81
4.21
2.11
0.94
0.65
0.88
0.65
2.11
0.74
0.66
0.92
1.13

                                   59
-------
                                                                       739
                              ACKNOWLEDGEMENTS

     A number of persons contributed materially to the work described above,
In either the planning of the project, doing fleldwork, analyzing samples,
testing the data, or  preparation of the report.  These are:  R.  L. Carey, V.
F. Cox, C.  C. Dary, M. A. Garcia, M. E. Garcia, R. L.  Garcia,  A. Guillen, Jr.,
K. J. Huxford, N. J. Magoulrk, A. Martinez, T. R. Mollhagen, A.  G. Navarro, J.
Spielberg, J.  H. Stamper, J. L. Tamez, and J. L. Val dez.
                                    60
-------
                                                                             740
                               LITERATURE CITED

Anonymous.   1968.   Spectrometry nomenclature;  Guide  for measures of precision
     and accuracy.   Anal.  Chem 40(14):2271.

Conover, W.  J.   1980.   Practical  nonparametrlc statistics,  2 ed.  John Wiley &
     Sons,  New York.

Daughton, C. G., A.  M.  Cook,  and  M.  Alexander.  1979.  Gas  chromatographlc
     determination of  phosphorus-containing  pesticide metabolites via
     benzyl a tion.   Anal. Chem. 51:1941-1953.

Davis, J. E., E.  R. Stevens and D.  C.  Staiff.   1983.  Potential exposure  of
     apple  thlnners to azinphosmethyl  and comparison of two methods for
     assessment of hand exposure.  Bull.  Environ.  Contam.  Toxlcol. 31:
     631-638.

Eto, M.  1979.   Organophosphorus pesticides:  Organic and  biological
     chemistry.  CRC Press, Inc., Boca Raton,  FL.

Federal Working Group  on Pest Management.   1974.  Occupational  exposure  to
     pesticides.   Report to the Federal Working Group on  Pest  Management  from
     the Task Group on Occupational  Exposure to  Pesticides. 155 pp.
                                     61
-------
                                                                             741
Gunther, F.  A.,  J.  H. Barkley, and W.E. Westlake.  1974.  Worker Environment
     Research.   II.   Sampling  and Processing Techniques for Determining
     Dislodgable Pesticide Residues on Leaf Surfaces.  Bull.  Env.  Cont.  Tox.
     12(6):641-644.

Hansen, J. D., B. A.  Schneider,  B.  M.  Olive, and J.  J.  Bates.   1978.
     Personnel  safety and foliage residue in an orchard spray  program using
     azlnphosmethyl and captan.  Arch. Environm. Contam.  Toxicol.  7:63-71.

Kirchmer, C. J.  1983.  Quality  control  in water analyses.  Environ. Sci.
     Technol. 17(4):174A-181A.

McFarren, E. F., R. J. Lishka, and  J.  H.  Parker.  Criterion for judging
     acceptability of analytical methods.  Anal. Chem.  42(3):358-365.

Maddy, K. T., and S.  C. Ediminston.   1982.  Pesticide safety  program of  the
     California Department of Food  and Agriculture based  upon measurements of
     potential  workplace exposure  and  the elimination of  excess exposures.
     J. R. Plimmmer, ed.  ACS Symposium Series No. 182, American Chemical
     Society, Washinton, D. C.

Menzie, C. M.  1978.   Metabolism of pesticides, Update II.  U.S. Department of
     the Interior F1sh and Wildlife Service,  Special Scientific Report-
     Wildlife No. 212, Washington,  D.  C.
                                     62
-------
                                                                          '     742
Menzie,  C.  M.   1980.  Metabolism of pestlcieds, Update III.  U.S. Department
     of  the Interior  Fish  and Wildlife Service, Special Scientific Report-
     Wildlife  No.  232, Washinton, D. C.

Mobay Chemical  Company, Agricultural Chemicals Division.  1979.  Material
     Safety Data  Sheet:  Guthlon Insecticide.  Kansas City, MO.

Mobay Chemical  Company,  Agricultural  Chemicals  Division.  1982.  Material
     Safety Data  Sheet: Guthlon  Insecticide.  Kansas City, MO.  4 pp.

Munn, S., Lt.  J.  Keefe, and  E. P. Savage.  1985.  A comparative study of
     pesticide  exposures In  adults and youth migrant field workers.  Arch.
     Environ.  Health  40(4):215-220.

O'Brien, R. D.   1967. Mode  of action of insecticides.  Ann. Rev. Entomol. 11:
     369-402.

Patel, C. P.,  and R.  C. George.  1981.  Liquid chromatographic determination
     of creatinine in serum  and  urine.  Anal. Chem. 53:734-735.

Free, D. J., K. P. Butler, E. R. Kintal 1, and D. K. R. Stewart.  1976.
     Persistence  of foliar residues of dimethoate and  azinphosmethyl and
     their toxidty to  the apple maggot.  J. Econ. Entomol. 69(4):  473-478.

Reid, S. J., and R. R.  Watts.   1981.  A method for the determination of
     dialkyl phosphate residues in urine.   J.  Anal.  Tox.  5:126-132.
                                     63
-------
Sokal, R. R. and F. J. Rohlf.  1969.   Biometry.  W.  H.  Freeman  and  Company,   743
     San Francisco, CA.  776 pp.

Snedecor, G. W. and W. G. Cochran.  1976.   Statistical  Methods.  6th Edition.
     The Iowa State University Press, IA,  U.S.A. 593 pp.

Takade, D. Y., J. M. Reynolds, and J. H. Nelson.  1979.   l-(4-n1trobenzyl)-3-
     (4-tolyl) triazene as a derivatizing  reagent for  the analysis of  urinary
     dialkyl phosphate metabolites of organophosphorus pesticides  by gas
     chromatography.  J. Agric. Food  Chem. 27(4):746-753.

Texas Agricultural Extension Service.  1980.   Texas guide for  controlling
     insects on commercial vegetable  crops.  Publ.  No.  B-1305.  28pp.

U.S. Environmental Protection Agency.  1980.   Manual of analytical  methods  for
     the analysis of pesticides in humans  and  environmental  samples.   Health
     Effects Research  Laboratory, Research Triangle Park, NC.   Publ. No. EPA-
     600/8-80-038.

Wolfe, H. R., J. F. Armstrong and W.  F.  Durham.   1966.  Pesticide  exposure
     from concentrate spraying.  Arch. Environ.  Health 13:340-344.
                                     64
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                                                   744
An Assessment of Exposure of  Tomato
  Harvesters to Chlorothalonil
        Research performed by

        Texas Tech University
        San Benito, TX  78586

        November 26, 1985
-------
                                                                         745
In behalf of  the Texas PHAP the undersigned have  reviewed  and  approved the
report draft  entitled "An Assessment of Exposure  of Tomato Harvesters to
Chlorothalonll."
             Quality Assurancef fleerDate
           •2
                  reject  Dir&ctor                         Date
                           J
                                      ii
-------
                                                                        748
                                 INTRODUCTION

     Assessment of exposure  of farmworkers  to pesticide residues and the
Implied risk of adverse health effects associated with exposure has received
considerable attention from federal  regulatory  agencies (Relnert and Severn,
1985).  Farmworker exposure  to pesticide  residues as a result of reentry Into
fields to harvest fruits and vegetables has been observed at varyng levels for
the past 25 years (N1gg and  Stamper,  1982).  The prediction of dermal exposure
and prevention of injury has been of central Interest to regulatory agencies
and Industry (Honeycutt et al.,  1985).  Although the knowledge about reentry
exposure  has advanced with respect to the adult farmworker, a good deal of
information must be gathered to evaluate the extent of pesticide exposure to
youth, 17 years of age and younger,  and the potential adverse health effects
of exposure.
     Children of migrant farmworkers frequently enter the  fields as
harvesters or as dependents  (Spear,  1982).  Youths  participating In the
harvest may contact residues at the same rate as adults, but experience a
higher absorbed dose because of lower body weights (Munn et al.,  1985).  A
comparative study of pesticide exposure to  youth and adult migrant farmworkers
may be designed to compare relative  contact with residues between  adults and
youths.  The value of such a study Is dependent on  the detectability of the
pesticide on environmental substrates and sampling  devices worn by the workers
and the harvest activities required  for the crop.   This study examined contact
with residues on sampling devices:  gloves,  arm  patches and leg  patches worn  by
-------
farmworkers, youths and adults, harvesting tomatoes at two locations In the   "'
Lower Rio Grande  Valley of Texas on two separate dates  -  17  May 1982 and
4 June 1982.
-------
                             TABLE OF CONTENTS
746
8X3XS33B33388B3SS3388S333S8S33S333333333XS3SS33XB38SBS33333333SS3333SS33SSSSS3
Section                                                                  Page
ABSTRACT 	   1v
INTRODUCTION 	    1
BACKGROUND 	    3
METHODS	    7
     Study Sites 	    7
     Crop and Pesticide Application 	    8
     Weather 	    8
     Human Subjects 	    8
     Gloves, Towels, and Patches 	   10
     Analytical Methods 	   10
     Quality Assurance 	'	   11
RESULTS	   15
INTERPRETATION AND ANALYSIS 	   19
DISCUSSION AND CONCLUSIONS 	   21
FIGURES	   23
TABLES	   31
ACKNOWLEDGEMENTS 	   44
LITERATURE CITED 	   45
APPENDICES	   46
     A.  Methods
     B.  Worker Interviews
•33333333X33833333333333333333333333333B333=333333B333333333SB333333333=3=3338
                                     iii
-------
                                                                        747
                                   ABSTRACT

     Contact with residues of the fungicide chlorothalonll was examined  In
youth (age £ 17 years) and adult (age >  17 years) farmworkers during the
harvest of tomatoes at two Independent sites on 17  May 1982 (n  • 25) and
4 June 1982 (n « 40).   The accumulation  of  residues  on sampling devices,
gloves and arm and leg patches,  worn by  the harvesters was  measured to assess
areas of contact.  The protective value  of  the  gloves  was estimated from
paired comparisons of concentrations detected In gloves and  1n  towels used to
wash  the  hands.  Both age classes,  youths and adults,  accumulated residues on
the sampling devices at similar concentration levels.    Gloves  appeared to
act as a protective barrier limiting  further penetration of residues  to  the
hands.  Hand contact with residues  could not, however, be explained by the
performance of the harvesters.  Contact  with residues on arm and leg patches
did not correlate with worker height or  weight.  The  farmworkers at the  first
site, harvested  17 May  1982,  5  days after application of BravoM, contacted
16.2 +_ 5.1 ng/Kg/hr"l on arm  and leg patches.  The farmworkers  harvesting
tomatoes  at the  second site  on  4 June 1982, 9 days  after application  of
BravoW contacted significantly less  residue,  10.3 ^ 5.7  ng/Kg/hr'1.  These
results Indicated that youths employed  1n the harvest of  tomatoes may be
expected  to contact residues of the fungicide chlorothalonll at equal rates as
adults.
                                       iv
-------
                                                                            750
                                 BACKGROUND

     Tomatoes are grown 1n Texas as fresh market and processing crops  with an
annual  combined value of $10 million (Parsons et al., 1977).  The greatest
commercial production of tomatoes  1n Texas occurs 1n the Lower R1o Grande
Valley  with  39.3 percent of the total  acreage (4,200 acres).   Hidalgo County,
where the study site was located,  accounted  for 72.7 percent of the three
county area  (1,650 acres)  and  28.5 percent  of  the total (T.D.A.,  1982).
     Tomatoes are grown 1n  the  Lower Rio Grande Valley  over 90 to 120 day
periods during two seasons,  from December to May and again from September to
November (Parsons, et al.,  1977).  The  temperatures during  the two growing
seasons range from 800p to 85°F during the day and 60°F to 70°F In the  evening.
Harvest commences for green-wrap tomatoes when full  size 1s achieved and the
tomatoes are void of pink color.  Vine-ripened  tomatoes are picked when the
stem changes from green to  pink.  Both  harvests observed for this report were
of green tomatoes only.
     Harvesters pick according  to  the  size of the tomato,  entering the  field
as many as three times In accordance with grading practices of the grower.
Labor associated with picking Is sometimes divided between family members,
with women and  children picking the fruit, and  the men  carrying the loaded 5-
gallon buckets  through the  rank foliage to the receiving crates.   Because  of
this division of labor,  women and  children may come  Into contact  with
dlslodgeable residues of pesticides more readily than men.  Harvest of
tomatoes requires close contact with  foliage.  Harvesters  must stand  knee  deep
-------
751
In foliage while separating leaves In order to pick.   Exposure  to  dislodge able
residues of a pesticide may occur on the lower legs and from the elbows  to the
hands.
     The Texas Department of Agriculture (Parsons  et al.,  1977) recommends
repeated application of herbicides, Insecticides and  fungicides to tomatoes
throughout the growing season.  Parsons et al. (1977) did  not 11st
chlorothalonll (BravoM) among the recommended fungicides.   BravoW-6F, a
flowable formulation of chlorothalonll, was listed by Johnson and Amador
(1975) for control  of early blight, late blight, anthracnose, and  gray spot
leaf, as well as botrytls gray mold on tomatoes.   Application of  Bravo(R)-6F was
recommended when disease threatens at the  rate of  1-1/2  to 2  pints per acre
for control of early blight and late blight with higher rates (2-3 pints/acre)
required for control of anthracnose,  gray  leaf spot,  and botrytls  gray mold.
Treatments were recommended every 7  to 10  days until  harvest.
     ChlorothalonH, 2,4,5,6-tetrachloro1sophthalon1trfle,  1s a broad spectrum
fungicide registered under the trade  names Clortoslp, Daconll 2787,  Exotherm,
Termll and Bravo (Farm Chemicals Handbook, 1985).   Chlorothalonll  has a  low
vapor pressure (<0.01 Q  4(X>c)  and  water solubility (0.6 ppm)  and may be
expected to remain on the leaf surface to provide residual protection  (Merck,
1976; Thomson,  1985; and  Plmentel,  1981).  The label for BravoM  500
contains the signal word WARNING,  while the labels for Clortoslp and Exotherm
are marked  CAUTION  (Farm Chemicals Handbook,  1985).  Both Bravo(R) W-75  and
DaconllW W-75 are labeled DANGER.   In all  cases,  protective clothing 1s
recommended when mixing,  loading  or applying chlorothalonll. Chlorothalonll
has been found to cause  dermatitis and eye Irritation (Farm  Chemicals
Handbook, 1985 and  Hallenbeck and Cunningham-Burns,  1985).  The acute  oral
LD50 for male and female rats was reported 1n Farm Chemicals Handbook
-------
(1985) as 10 g/Kg.  The dermal toxlclty to albino rabbits was 10  g/Kg.  The     752
funglcldal  activity  of chlorothalonll has  been attributed to the  Inactlvatlon
of tMol  enzymes (Plmentel,  1981).  Chlorothalonll has been observed
(Pimentel,  1981)  to  bind to thlol groups of enzymes of the glycolytlc pathway,
6»9«» glyceraldehyde-3-phosphate dehydrogenase.   This  action  may be common to
higher organisms and of considerable  Importance  when  assessing  risk to non-
target organisms.
     The persistence of chlorothalonll  on  food crops  (FAD, 1979; Hlramatsu and
Furutanl, 1979;  Kosekl et al.(  1980;  Soma  et  a!., 1980; and Looney and
Cochrane, 1981)  and  soil  (Anon,  1979a,b and Soma et al.,  1980)  suggests the
possibility of transfer of residues from  foliage to non  target  animals.
Residues of chlorothalonll  have been  detected on summer wheat (0.78 mg/Kg) 21
days after application and on winter barley (<0.01 mg/Kg) 47 days after
application (FAD, 1979).  A temporary maximum residue limit of  0.2 mg/Kg was
recommended by the FAO (1979) on these commodities when chlorothalonll was
used at the rate of  1 to 3 Kg Al/ha over  a six week period following
application.   Similarly, wet table powder  formulations of  chlorothalonll were
found by Hlramatsu and Furutanl (1979)  to  persist on  cucumbers  1n accordance
with the growth  rate  of the vegetable.  Other vegetables  and fruit  Including
tomatoes were found by Kosekl  et al. (1980)  to contain residues from 0.001 to
1.35 ppm.   Soma  et al. (1980) observed  chlorothalonll  residues  In tomatoes up
to 0.32 ppm.   These  levels exceeded residue concentrations on many other
vegetables but were dwarfed by extremely  high levels (11.4 ppm) of
chlorothalonll In soil taken from  the  same tomato  field (Soma  et al., 1980).
Chlorothalonll Is apparently used 1n large quantity  In Japan for the control
of Phytophthera  Infestans on tomatoes  (Anon,  1979a).   Disappearance of 50
percent of the residues 1n soil were  observed to take 3  to 5 weeks with 80
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percent disappearance In 10 weeks (Anon,  1979a).   Residues  appeared  to  rema1r753
on the soil surface (Anon,  1979a).  Residues on tomatoes  after standard
application rates remained above threshold values  of  1.0 ppm  (Anon, 1979b).
     Although application rates may differ substantially  between Japan  and the
United States, the persistence of chlorothalonll  on vegetables requires an
Investigation of the potential  transfer of residues  from  foliage to  harvesters
picking tomatoes.  This study was an attempt to estimate the potential  for
contact and accumulation of dlslodgeable  residues of chlorothalonll  on
sampling devices worn by farmworkers harvesting tomatoes.  The aim of the
study was to determine If underage  farmworkers, ages 17 years and younger,
contacted higher levels of residues than  adults.
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                                                                          754
                                  METHODS

     Study  Sites.  Field one was a 22-acre field within the limits of the city
of Mission, Hidalgo  County* Texas.  The field had two distinct sections,
separated by a  tree  row.  The northern-most section was an 8-acre square,
while the southern-nrost was a 12-acre rectangle.  A public thoroughfare
provided the northern border  of  the field, and there were some dwellings
across the  street.  Occupied homes were located at the northwest and northeast
corners of the field.  Tilled ground  and citrus orchards bordered the rest of
the f 1 el d.
     The soil of the entire field was classified  as  Hidalgo-Urban land
complex.  Soils of the  Hidalgo series are deep,  moderately permeable with a
sandy clay loam surface layer (Jacobs,  1981).  Irrigation of the field was
along north-south trending furrows.
     Field two was a 63-acre field In the R1o Grande River flood plain.
It lies 4 Km northwest of  the city of Hidalgo and 11 Km south-southwest  of
McAllen, Hidalgo County, Texas.  The  field Is Irregularly-shaped and  Is
bordered on the west and south by resacas (oxbows),  on  the  north  by a levee,
and on the east by a road. There  were no dwellings adjacent to the field.
     The soils at field two are  deep, moderately well drained, somewhat
permeable, silt loams  and sllty clay  loams of the Rio Grande and Matamoros
series (Jacobs, 1981).   At Its closest point, the field lies 0.6 Km from the
Rio Grande River, at Its farthest point,  2.1  Km.   Irrigation of  the field was
along east-west trending furrows.
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                                                                         -    75!
     Crop and Pesticide Application.  Both fields were planted with the Flora-
Dade 908  variety of tomato,  1n  72 inch rows.  By the time of harvest, the
vines had spread to form a dense ground cover 12 to  26  Inches  deep.
     BravoW  500 and Pydrin^ were applied by aircraft to field one on 12
May 1982 and the same chemicals were applied to field two  on 26  May  1982.  In
both cases the application rates  were one 1.5 pints  (AI) of  Bravo^ 500 and
5.3 oz (AI)  PydrinW per acre.
     The time between application and harvest for field one  was  five days and
for field two was nine  days.   Leaf samples were collected from each field for
each respective period.  These  samples  were  to  be analyzed to establish the
rate and degree of degradation of the  pesticides before harvesters entered the
fields.  However, these  samples decomposed  in storage before the
chlorothalonil methods could be perfected and validated.  Thus an Important
part of the study was missing.
     Weather.  The weather conditions on the day of  harvest  (17  May  1982) at
field one were: no wind; overcast skies with light,  intermittent drizzle; high
temperature was 800 F,  low  750 F.  Weather conditions at  field two on the date
of harvest (4 June 1982):  no wind and  clear  skies; high temperature  was  91° F,
minimum was 760 p.  In  neither case was there precipitation  between  the  date
of application and the  date of harvest.
     Human  Subjects.  The populations  studied consisted of crews  of  harvesters
selected  solely by the  labor contractors.  The workers  did not have  advanced
notice  of the study.  The cohort In field one (17  May 1982)  consisted of 25
farmworkers.  The cohort In field two  (4 June 1982)  consisted  of 40
farmworkers.   In both cases the study participants numbered about half  the
harvesters actually working In the field.  No attempt was  made to determine
the reasons some workers  declined to participate.  However,  the  notion  of
                                      8
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being an experimental  animal  was clearly  troublesome  to a few persons, while    756
others"did not want to be encumbered by any of the sampling devices.  Although
volunteers were remunerated for their cooperation,  to preclude any suggestion
of human experimentation, no attempt was  made to alter  the  level of
participation by any worker.
     The workers arrived at the fields in the period 1630 to 0715  hours.
                i
After an explanation of the work proposed,  the volunteers proceeded through a
series of study stations where they: (1)  signed  consent forms; (2) were
briefly interviewed; (3) were weighed;  and  (4) were equipped with gloves and
dermal patches.  Workers were provided with the array of  sampling  devices on a
voluntary basis.  For easy Identification,  a  group  of participants were
provided with long sleeved, twill work shirts bearing numbers on the front
and back.
     The workers entered the fields over the period 0730 hours  to  0815  hours.
While each worker was harvesting, a somewhat longer interview (15-20 minutes)
was undertaken  to obtain their work history as well as  their perception of
their own health and medical  history.   During  the Interview, notes were taken
on Individual picking practices (Appendix B).   Harvest activities were
completed for the first monitoring by 1431  hours and  by  1320 hours for the
second monitoring.  No  harvester was in the field longer than seven hours.
The number of buckets of tomatoes picked  by each worker was  obtained from the
labor contractor for possible correlation with  residues detected  In  the
substrates tested.
     Both harvests reported upon were  of the  first picking of the field.
Receiving crates were placed  around the border of the fields and most  of the
workers  started Initially  harvesting the crop  In the vicinity of the crates.
Periodically throughout the day, a collection  of 10-20 workers was gathered to
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pick 1n front of a tractor pulling a disc harrow.   This  newly cultivated      ' 0|
ground provided a new path for the placement of additional receiving crates,
thereby shortening the distance required to carry  loaded buckets.   When  a
bucket was dumped Into the receiving crate, the worker received a token  which
was later redeemed for pay.
     Gloves, Towels, and Patches.  The transfer of residues  of chlorothalonll
to workers harvesting tomatoes was examined by measuring the accumulation  of
residues on sampling devices worn by the workers.   Hand contact with.residues
of chlorothalonll was estimated from an examination of residue concentrations
In gloves and hand wash  towels.  The gloves were lightweight 100% cotton
twill work gloves with knit wristlets and seamless palms (Sears catalog  number
51K25915).   The glove surface area minus the knit wristlet was  549.7 cm2.
Exposure through the gloves was estimated from residues  collected  on  towels
used to clean both hands.  The towels (84% cotton, 16% polyester, 890.3  cm2,
Leshner of St.  Marys, Ohio 45885) were Immersed In solvent (50:50 ethanol  and
water) and then used to wipe  the hands clean.
     To assess the potential  for accumulation of residues on the arms and  legs
of workers, gauze patches  (103.2 cm2)  were placed  at  near equal  distances  from
the ankle on the outside legs and on the Inner aspect of forearms equal
distance from  the wrist (Fig. 1).   Following 3.5 hours of continuous exposure,
the gloves, patches and soiled hand  wash  towels were  sealed In plastic bags
and placed on dry 1ce for transport to the laboratory.   All  samples were
stored frozen  until  analysis.
     Analytical Methods.  The sampling devices were  analyzed according to the
methods outlined 1n Appendix A.  The gloves  and hand  wash towels were cut Into
approximately  6.45 cm2 pieces and extracted three times  In 200 ml methanol for
15 minutes on a Burrell wrist-action shaker.  The  extracts were passed through
                                     10
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                                                                               75b
glass wool  to obtain a combined sample.  Sodium sulfate was  added  to the
sample to absorb excess water.  The sample and five rinses were transferred to
a round bottom flask and reduced to near dryness  on a Buchl  Rotavapor  R110.
The sample was reconstituted with  10.0 ml hexane and concentrated  to 1.0 ml
with a gentle stream of  nitrogen  using a Meyer N-Evap.  Following  extraction,
the sample was passed through  2.0 g silica gel column deactivated  with 400 ul
benzene extracted water.  Fraction one (100% hexane)  was used  to elute the
sample.  Fraction two (1% benzene/992 hexane) was discarded.   Fractions three
(20% benzene/80% hexane) and four (60% benzene/40% hexane) were collected and
combined to  obtain  the  final extract  for GC analysis.
     The arm and leg patches (103.2 cm2) were extracted three times with 150
ml  methanol  In a 500 ml Erlenmeyer flask on a Burrell wrist-action shaker set
at 6.  The  extracts  were collected  and dried with sodium  sulfate and
evaporated to 5.0 ml.  The concentrate was adjusted to 10.0  ml  and prepared
for analysis by GC.
     Samples were analyzed  for residues of chlorothalonll  with a Tracor 220
gas chromatograph by electron  capture (3H) with  two column confirmation (4.0%
SE30/3.0%  OV210 and 1.5% OV17/1.95%  OV210).  The  carrier gas (N2) flow was 72
cc/m1n (Isocratlc)  with an oven temperature of 200°C.  Chlorothalonll
(BravoCO)  code 1640 was used as  the reference standard.   The  standard was
obtained from the U.S. EPA Pesticides and Industrial  Chemicals Repository,
U.S.  EPA  Environmental  Research Center,  Research  Triangle Park, NC 27711.  The
standard was prepared 1n methanol  as  99.7% chlorothalonll.
     Quality Assurance.  Measurement of chlorothalonll residues on the
sampling devices worn by farmworkers harvesting  tomatoes  was complicated by
the large concentrations detected.  Extracts of the samples  required
considerable dilution to obtain resolvable  peaks.  Residue concentrations  In
                                     11
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sample extracts were more readily detectable than companion  check samples
fortified at much lower concentrations.  Minimum detection limits were          7:
                                                                               ' s
established for each substrate from the check samples.  Concentrations
detected In gloves fortified with 0.27  ng/cm2 Were much greater than expected
(Table 1) because of conflicting  underlying  peaks observed with each column
(Fig.  2).   Conflicting peaks  were detected 1n blanks prepared with  each check
sample (Fig. 2).   Dilution of blanks and check samples  to conform with peak
detection of test samples resulted In more stable baselines. However,
conflicting peaks detected In check samples  (0.91 ng/cm2) on both columns made
Interpretation difficult (Fig. 3).  An  Increase  In  the fortification level
(18.2  ng/cm2)  produced easily  resolvable peaks for  chlorothalonll on  both
columns  (Fig. 4).  A series  of check  samples prepared  to evaluate the quality
of analysis revealed substantial  Improvement 1n recovery  (109.3%) of
chlorothalonll (18.2 ng/cm2)  on the SE30-OV210 column  and 79.1  percent
recovery on the confirmatory OY17-OV210 column (Table  2).  The  mean
concentration of  chlorothalonll  (19.9 _+ 1.5  ng/cm2) detected  1n this series of
check samples on the SE30-OV210 column  were  used to set control  limits
(C.V.»7.57%).   Check  samples  prepared for each series of test samples were
within control limits (Fig.  5).  Control limits  were exceeded for duplicate
analysis on the OV17-OV210 column (F1g. 6).  Minimum detection  limits were
established for chlorothalonll  residues on gloves with the SE30-OV210 column
at 18.2 ng/cm2.
     Determination  of control  limits for detection of  chlorothalonll In
hand wash  towels was  Initiated at 0.56 ng/cm2 (Table 3).  A  mean concentration
of 0.60 JK 0.20 ng/cm2 was recovered In  the check samples with a recovery of
107.2  percent of  expected (0.56 ng/cm2).  Recovery  of  chlorothalonll  was quite
variable  (C.V.  «  33.9%),  however,  necessitating  reexamlnatlon of control limits
                                     12
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at higher fortification levels.
     Check samples fortified with 11.2 rig/cm? were less variable (C.V.  »
20.6%),  although recovery was 81.1 percent of the expected.  The mean recovery
was 9.11 i 1.88 ng/cm2.  Control limits were  set with this series of check
samples.  Check  samples within  each  sequence  of test samples were found to be
within control limits  (Fig. 7).  The mean recovery of chlorothalonll In hand
wash towels was 10.6 j* 1.4  ng/cm2 or 94.4  percent of  the expected
(11.2 ng/cm2).  Check samples within the  sequences were less variable
(C.V. • 13.0%) than the control  check samples (C.V. • 20.6%).
     Quality control samples for gauze patches worn on the shirt sleeves and
trouser legs of  harvesters  were  analyzed on two dates,  shortly  after sample
collection on 1  December 1983,  and  much later with stored  samples on 22
October 1985.  A control  series  of check  samples was  not prepared prior to the
analysis of samples tested on 1 December  1983.  Recovery of a  single check
sample  fortified with  96.9 ng/cm2 was 96.0 ng/cm2 or 99.1  percent.   Additional
check samples (n •  3)  fortified with 48.4 ng/cm? yielded  55.5  ± 9.1 ng/cm2, a
recovery of 114.7  percent.  The  samples  appeared to be within  the control
limits (C.V. - 16.5%) established for hand wash towels.
     Recovery of chlorothalonll  1n  gauze patches analyzed  on 22 October 1985
was a  good deal less (70.0%)  than the 1  December 1983 analyses.  A control
series of jcheck samples (n « 3) fortified- with 96.9 ng/cm2 yielded  a mean
recovery of 67.8 ^6.5  ng/cm2.   Although  some degree  of accuracy may have been
lost between dates of analysis as Indicated by the different rates of
recovery, a measure of precision was gained  In the later  analysis of the
control series as  Indicated by  the Improvement In  the coefficient of variation
                                     13
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(9.631).  The check sample prepared with the test sample sequence was      ' "'
reflective of that level  of precision  (Fig. 8).
                                     14
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                                                                             762
                                  RESULTS
                                •

     The  transfer of residues of chlorothalonll to farm workers harvesting
tomatoes was estimated from the  concentration  of chlorothalonll accumulated In
sampling devices worn by the workers over the study periods In fields one and
two.  Comparisons between fields were not made because of differences 1n the
Individuals and their  work habits  between cohorts.  Because of the lack of
environmental data, e.g., residue concentrations on leaves and fruit, an
effort was made to test the differences between the concentration of
chlorothalonll  In paired  samples trapped  In the sampling devices worn by the
workers.  Although  direct Inferences about transfer from environmental
substrates to the workers could  not  be  made, between sample differences 1n
accumulation of chlorothalonll  may provide an Indication  of anatomical areas
of comparative contact with residues during harvest.  Areas of contact, as
reflected by the accumulation of chlorothalonll  on the sampling  devices, may
vary between youths (£ 17 years) engaged In  the  harvest of tomatoes  and their
adult counterparts (>  17 years).   A  special  effort was made to Identify
physical features which might be responsible for differences  In contact with
residues between youths  and adults.
     Of the 25 Individuals engaged In the harvest of tomatoes In field one,
three of the farmworkers were youths,  17 years  and younger (Table 4).  The
average age of  the cohort was 29.7 _+ 9.9 years,  the median age 28 years.   Six
members  of  the cohort were females.  The three youths  were males.  The average
height and  weight  of  the youths was 64.7 +_ 3.5  Inches and 121 ± 13  pounds.
                                     15
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The average height of the entire cohort plus the youths was 65.7 ± 4.2 Inches
with a median height of 65 Inches.   The  average  weight was 151 ± 26 pounds.  ' 63
The median weight was 147 pounds.
     The three youths, worker numbers 5, 6, and  7, were grouped with five
adults to measure the accumulation  of chlorothalonll  residues  on gauze patches
worn on  the shirt sleeves and trouser legs of the harvesters (Table 5).  The
concentrations of chlorothalonll  detected In  arm patches (1.30 +_ 0.80 ng/cm2)
were found to be not significantly different (t * -2.102, 7 d.f., P < 0.05)
from the concentration found In leg patches (2.41 +_ 0.84 ng/cm2) according
to the t-test on paired observations (Snedecor and  Cochran,  1976).  Contact
with residues of chlorothalonll  during harvest did  not appear  to differ
between anatomical areas.  In agreement  with  that observation, residue
concentrations detected In arm patches worn by youths  were not significantly
different (t « 14,  n « 3,  P < 0.20) from adults.  A similar result was obtained
for leg patches (t » 13,  n » 3, P <  0.20).  The Mann-Whitney test for
Independent samples was used because of the size (n = 3, m » 5,  N  = 8) of the
unbalanced data sets  (Conover,  1980).
     Youths appeared to come Into contact with residues of chlorothalonll at
the same level as adults, as Indicated by the  arm and leg  patch  data.
Unfortunately, such a comparison could not be  made  with respect  to  the
accumulation of residues  on  gloves  and handwash  towels; only adults were
Included In this cohort (Table 6).  Comparisons were made, however, among
sampling devices.  A paired t-test  of concentrations  detected  In  right hand
gloves and hand wash towels  (Table 6) revealed a significantly greater (t •
3.706, d.f. • 12, P < 0.005) level of residues  1n gloves.   The gloves appeared
to trap the residues and  not allow penetration to the hands.   Any  further
Interpretation of the protective quality of the gloves could not be made,
                                     16
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however, because of the lack of a companion cohort of ungloved Individuals.
Hand contact,  as  Indicated  by  the mean concentration  of  chlorothalonll  detected
In gloves (3.36 _+ 3.11 ug/cm2), was not significantly different from  perceived
contact  with arm patches  (t  « 1.813, d.f. « 18, P < 0.10) and leg patches
(t - 0.835, d.f.  -  18, P < 0.50).
     Results from the second field, studied on 4 June 1982,  were  not
Inconsistent with the first.   The sample  group was larger, composed of  24
males and  16  females  ages  10  to  70 years (Table 7).   The average  age  of the
males was  30.9 +_ 17.9 years, the  females  35.3  ± 18.2 years.  The median  age  of
the entire cohort was 31 years,  the average 32.9 +_ 18.3 years.  The study
group was represented by 13 youths  (_<  17 years) and 26  adults (> 17 years).
The age of one female subject was not  recorded.  The median height of the
youths was 63 Inches  with  the average  height  of 59.1 ± 8.4 Inches.  The
average weight of the youths was 111.1 ± 32.3  pounds.  The median weight was
110 pounds.  These physical factors may be compared to those for the  adults.
The median and average height of the adult farmworkers  were 64 Inches and 61.2
± 11.9 Inches  respectively.  The  median weight was 158 pounds  and the average
weight 164 ± 30 pounds.
     A subset of workers composed of  5 youths and 7 adults was selected to
examine  the accumulation of chlorothalonll  residues on arm and leg patches
(Table 8).   Unlike  the results obtained for the previous field,  the
concentrations of chlorothalonll  detected In leg patches were  found to be
significantly greater (t  - 3.526, d.f. - 12,  P < 0.005) than the
concentrations detected In arm patches.  The concentrations in leg patches
worn by  the youths were  found to be  not  significantly different (t « 26, n «
5, m » 7, P < 0.20)  from the adults  according to the  Mann-Whitney test  for
                                     17
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Independent samplss.  A similar result was obtai                       = 24.5,
n • 5, m • 7, P < 0.20).
                                                                         i
     Hand contact with residues was examined with a second  subset of
harvesters (Table 9).  The accumulation of residues in gloves was compared to
the concentration of chlorothalonil  found  in  hand  wash  towels.  The
concentrations In gloves  were found to be  significantly greater (t  * 3.679,
d.f. • 15.  P < 0.005) than the  concentrations detected  in hand wash towels.
As observed in the previous  study  of field one, gloves  appeared to accumulate
the residues with significantly lower concentrations reaching the hands.  The
concentrations detected In gloves  were not significantly  different (t = 23, n
» 5, ra « 9, P  < 0.05) between youths and adults.  A similar result was
obtained for hand wash towels (t • 29.5,  n = 5, m = 9,  P  <  0.20).  The age of
one female worker was  not recorded and, as a result,  residue  values were not
included In the analysis.  Unlike  the results obtained  in the study of field
one, hand contact with residues of chlorothalonil  were  significantly greater
than contact on  forearms (t =  3.510, d.f.  = 25, P < 0.005) and the lower legs
(t - 3.159, d.f.  = 2.5. P < 0.005).
                                     18
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                                                                         766
                        INTERPRETATION AND ANALYSIS

     Farmworker contact with chlorothalonil residues while harvesting tomatoes
appeared to be greater  through the hands than coincident contact on the
forearms or lower legs.  Youths  (_< 17 years) and adults appeared to contact
residues at similar levels.  As a result, an examination of physical factors
which might be used to separate  youths  from adults,  e.g., height and weight,
was rendered academic.
     Contact with residues might, however,  be expected to Increase with an
Increase in the size or performance of the harvester.   Performance may be
dependent on experience and  health.  In order to examine relationships
between size and performance, rank correlations (Conover, 1980)  were performed
on paired values  of height and weight against residue concentrations detected
in arm and leg patches.  Correlations based on  ranks were performed because of
the narrow spread and uncertainty about the distribution of the Independent
variables, height and weight.
     Height and residue concentrations  detected in arm patches from field one
(Table 10) were  found to be  mutually Independent (tau «  0.2381,  n  «  7,
P < 0.452).   The  absence of  trend was also observed for correlations on weight
                                                                         t
and residues  in arm  patches (tau » -0.1071, n  « 8, P < 0.356), height and '
residues  In leg patches (tau « -0.2381, n « 7, P < 0.454) and weight and   '
residues  In leg patches (tau * -0.0714, n « 8, P <0.403).  The lack of
correlation between the physical parameters, height and weight, and  residues
in arm patches and leg  patches in the first field was observed again  for the
                                     19
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second field (Table 11).  The lack of correlation suggests the presence of
unknown factors which might contribute to the prediction of causality.
Further predictions of causality by multl-regression or factor analysis were
deferred for more  carefully controlled studies.
     The accumulation of chlorothalonll residues In gloves was examined in
relation to the performance of the harvesters as expressed  In the amount of
tomatoes harvested (Tables 10 and  11).  Greater hand contact with the
vegetables and foliage was expected to Increase  the concentrations of residues
1n the gloves worn by the harvesters.  Correlations on ranks on the amount
harvested and residue levels detected in gloves for fields one (tau  = -0.4762,
 n » 7, P < 0.134) and two (tau - -0.0727, n » 11, P <  0.378) were  found
however to be dlsconcordant and Independent.  Hand contact with residues did
not appear to be dependent on performance.
                                     20
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                                                                      768
                         DISCUSSION AND CONCLUSIONS

     Youths employed In the harvest of tomatoes were found  to contact similar
concentration levels of  the fungicide chlorothalonll as adult harvesters.
Although meaningful extrapolations about total body exposure could  not  be
made, the youths In field one accumulated 69.6 _+ 23.7 ng/Kg based on the
summation of the concentrations detected In arm and leg patches.  The ranked
values,  normalized  to  the  Individual  weights  (ng/Kg),  were not  significantly
different from the adults (t * 17, n » 3, m » 5, P < 0.20). A  similar result
t « 33, n » 5, m » 7, P < 0.20) was observed for normalized val ues  for youths
and adults  from field  two.   The youths accumulated 38.54,+ 24.7 ng/Kg during
harvest 1n  the second  field.
     As pooled samples,  farmworkers  from field one contacted 16.2 ± 5.1
ng/Kg hr'1 on arm patches and leg patches while harvesting tomatoes treated
with chlorothalonll  5  days  prior to reentry.   Farmworkers In field  two
(treated 9  days prior  to  reentry) contacted 10.3 +_ 5.7  ng/Kg hr*1 after a
similar exposure period  of 3.5 hours.  The mean concentration  for field one
was found to be significantly greater (t * 2.3489, d.f.  « 18, P < 0.01) than
the mean concentration for field two.  The relevance of such a comparison Is
questionable; environmental  data, useful for a more direct comparison of
decline 1n  residues between fields, was  not taken.  In support of this
supposition,  significantly  greater concentrations were detected In  gloves
taken from field two  (t *  2.3483, d.f.  -25,  P < 0.025) compared to field one.
Clearly the conflict between greater  residue  levels In patches (between
                                     21
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fields one and two) and that observed In gloves (between fields) reflects on
farmworker activities rather than differences 1n residue levels between       -,,
reentry Intervals for the fields.
     The health Implications of  such exposure to chlorothalonll 1n both
youths and adults Is unclear.  Chlorothalonll has been observed to cause
dermatitis In the occupational ly exposed (Hallenbeck and Cunningham-Burns,
1985 and Horluchl et al.t  1980).  The mechanism of action may be related to
the action of chlorothalonll on thlol enzymes (Plmentel, 1981) and the
structural similarity of chlorothalonll  to hexachlorobenzene and this
compound's porphyrigenie activity (Hayes, 1982).   Repeated  exposure might
Influence Iron distribution and the appearance of porphyri a.  Chronic exposure
to chlorothalonll may be Identified with the appearance of urinary
coproporphyrfn.
     Future studies may be  designed to Investigate the  subacute and chronic
effects of chlorothalonll  on agricultural  workers.  Environmental  samples
should be taken throughout  the study period, from time  of application to the
completion of the harvest.   Dermal  exposure may be estimated from the
accumulation of  residues on sampling devices worn  by  the workers.  Absorption
of chlorothalonll may be examined  In biliary excretions (Chin  et  al., 1980 and
Chin et al., 1981) and compared to the appearance of  porphyrins in urine after
exposure.
                                      22
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                                                        770
                                 Subject Number
      Leg Patches
Cotton Gloves
Fig. 1.  Positions of sampling devices (body patches
and gloves) worn by workers harvesting tomatoes treated
with a formulation (Bravo(R'500) of chlorothalonil.
                    23
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K)
                  1.5%OV17
                1.95%OV210
                    minutes


            4.0%SE30
           3.0%OV210
              minutes
                        CM
                        0>
                         •
                        IO
o
o
•
CM
                           i •. v _'«„' r -.-	
   B

B
           Fig.  2.  Chromatographic display of the detection of chlorothalonil in
           fortified (0.27 ng/cm2) check samples (A) and blanks (B)  of glove extracts
           by two column confirmation (1.5% OV17/1.95% OV210 and 4.0% SE30/3.0% OV210)
           with electron capture {3H} (Carrier gas (No) flow rate 57 cc/min at 200°C
           isocratic).  Peak retention time is indicated for chlorothalonil.
-------
                1.5%OV17
                                 0
                   minutes
                        in
                        o
                        cd
o
o
CM"
                    4.0%SE30
                   3.0%OV210
                      minutes
         M
         CM

         CO

O
O
oi
NJ
Ul
1 1
i
1
1 ll

1
1
1
]Z
J

t



IA
i
1
i
; !•


*
, : !! ! ;


I j

1


[





j!


|
It
1
1 .1
1 
-------
                    1.5%OV17
                   1.95%OV210
                       minutes
to
cr>
                       L_*	I	L..
                          CM
                          00

                          in
                        —^-^\n^
j—j—j—i—i
     O
     O
     CM'
                4.0%SE30
                3.0%OV210
                  minutes
                                       B
                                    B
               Fig. 4.  Chromatographic display of the detection of chlorothalonil
               in fortified (18.2 ng/cm2)  check samples (A) and blanks (B) of glove
               extracts by two column confirmation (1.57» OV17/1.95% OV210 and
               4.0% SE30/3.07, OV210) with  electron capture (3H) (Carrier gas (N2)
               flow rate 57 cc/min at 200°C isocratic).  Peak retention time is
               indicated for chlorothalonil.
-------
                                                        774
+3
+2
+ 1
0
-1
-2
-3
•
w - ^
5
2 *
1

3
-
25.5
23.9
22.3
20.7
19.1
17.5
15.9
Fig. 5. Column SE30-OV210.   Normal probability  plot
of glove samples (x - 20.7  + 1.6 ng/cnr)  fortified
with 18.2 ng/cm2 chlorothalonil.  Numbers represent
individual samples.  Dashed line represents  expected
recovery of fortified concentrations (18.2 ng/cm2).
                      27
-------
                                                       775'
+3
+2
+ 1
0

-1

-2
-3
-
1
2
4
5
3
. „
-
21.1
18.1
15.1
12.1

9.1

6.1
3.1
Fig. 6.  Column OV17-OV210.  Normal probability plot
of"glove samples (x - 12.1 + 3.0 ng/cm2) fortified
with 18.2 ng/cm2 chlorothalonil.   Numbers represent
individual samples.  Dashed line represents expected
recovery of fortified concentrations (18.2 ng/cm2).
                       28
-------
                                                        776
+3
+2
+ 1

-1
-2
-3

— —
3
1 2
4
_ —
-
14.8
13.4
12.0
1^^ ^^
0.6
9.2
7.8
6.4
Fig. 7.  NormaImprobability plot of hand wash
towel samples (x = 10.6 + 1.4 ng/cm^)  fortified
with 11.2 ng/cm^ chlorotEalonil.  Numbers represent
individual samples.  Dashed line represents expected
recovery of fortified concentrations (11.2 ng/cm2).
                       29
-------
                                                      777
+5
+4
+3
+2
+ 1

0
-1
-2
-
-
— —
_ _

r 2
3
1
-
100.3
93.8
87.3
80.8
74.3

67.8
61.3
54.8
Fig. 8.  Normal probability plot of patch samples
(x - 67.8 + 6.5 ng/cm2)  fortified with 96.9 ng/cm2
chlorothalonil.  Numbers represent individual samples.
Dashed line represents expected recovery of fortified
concentrations (96.9 ng/cm2).
                       30
-------
                                                                          778
Table 1.  Detection of chlorothalonll  by  two  column confirmation analysis  1n
          glove check  samples fortified with 0.27 ng/cmz.
                                Chlorothalonll (ng/cm2)!/
Sample              4% SE30/3*  OV210         1.5% OV17/1.95Z OV210
Q.
Q.
0.
Q.
Q.
C.
C.
C.
C.
C.
#1
*2
13
*4
#5
0
4
0
2
2
.50
.33
.01
.91
.71
(0.
(0.
(0.
(4.
(4.
58)
02)
18)
65)
02)
0
6
0
3
3
.66
.14
.27
.90
.49
(-)
(5.
(0.
(6.
(5.

64)
09)
05)
46)
I/ Values enclosed are from blanks prepared with each check sample.
                                     31
-------
                                                                       779
Table 2.  Detection of chlorothalonll  by  two  column  confirmation analysis In
          glove  check  samples  fortified  with 18.2 ng/cm?.
                                Chlorothalonll (ng/cm2)
Sample              4% SE30/3* OV210         1.5* OV17/1.95X OV210
Q. C. #1
Q. C. 12
Q. C. #3
Q.C. mean + S.D.
C.V.
Percent recovery
19.1
18.9
21.6
19.9 + 1.5
0.0757
109.3 %
14.9
13.6
14.6
14.4 + 0.7
0.0474
79.1 %
                                     32
-------
Table 3.  Detection  of chlorothalonll  In hand wash towel  check  samples fortified
         with 0.56 ng/on2 on a 4% SE30/32 OV210 column.


Sample                           Chlorothalonll  (ng/cm2)
Q. C. II                                    0.72

Q. C. 12                                    0.37

Q. C. 13                                    0.72
Q.C. mean + S.D.                            0.60 + 0.20
C.V.                                        0.339"
Percent recovery                          107.2 %
                                     33
-------
                                                                           781
Table 4.   Physical  characteristics of human subjects Involved In the harvest
          of tomatoes In field one (17  May 1982)  treated with chlorothalonll.
          Performance of the  harvesters Is Indicated by amount harvested
          (buckets).
Worker
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

Sex
F
F
F
F
M
M
M
M
M
M
M
M
M
M
M
M
M
M
F
M
Physical
Characteristics

Age Height (in) Weight (ib)
25
39
34
42
15
15
16
34
24
29
35
21
25
52
44
25
42
32
25
29
57
62
67
62
61
65
68
65
70
64
65
63
65
68
70
69
66
71
63
—
146
126
181
136
109
119
135
169
140
146
169
122
146
166
202
191
156
160
111
183
Amount
Harvested
.
-
-
-
-
31
39
-
40
-
-
49
65
47
-
-
-
29
40
36
                                     34
-------
Table 4,  continued.         .                                        n
                                                                         782
                       Physical Characteristics
Worker                                                           Amount
Number        "Sex     A~geHeight (In)     Weight lib)        Harvested

  21            M     27        75              160                  29
  22            M     20                        149                  39
  23            M     21        70              187                  50
  24            F     43        58              119
  25            M     28        67              147
                                     35
-------
                                                                        783
Table 5.  Chlorothalonll residue concentrations on patches worn by human
          subjects  while harvesting tomatoes 1n field one (17  May  1982).
Worker
Number
5
6
7
8
14
16
17
22
Physical Characteristics
Sex
M
H
M
M
M
M
H
M
Age Height (1n)
15
15
16
34
52
25
42
20
61
65
68
65
68
69
66
—
Chlorothalonll (ug/cm2ja/
Amount
Weight (Ib) Arm Patch
109
119
135
169
166
191
156
149
1.90
0.83
1.06
0.57
3.00
1.14
0.69
1.21
Leg Patch Harvested
2.84
2.75
1.85
2.10
0.74
3.18
3.33
2.47
«
31
39
-
47
-
-
39
£/ Patches for Worker Numbers 5-8  were analyzed on 6 December  1983.
   Patches for Worker Numbers 14-22 were analyzed on 22 October 1985.
                                     36
-------
                                                                        784
Table 6.  Chlorothalonll residue concentrations found on gloves and hand wash
         towels  from human subjects harvesting tomatoes In field one
         (17 May 1982).
Worker
Number
4
9
13
15
17
18
19
20
21
23
24
25
Physical
Sex
F
M
M
M
M
M
F
M
M
M
F
M
Age
42
24
25
44
42
32
25
29
27
21
43
28
Characteristics
Height
(1n)
62
70
65
70
66
71
63
-
75
70
58
67
Weight
(lb)
136
140
146
202
156
160
111
183
160
187
119
147
Chlorothalonll (ug/cm2)^
Right Glove
0.92
1.66
2.02
1.54
4.60
4.52
2.43
11.69
6.27
0.65
1.71
2.28
Hand Wash Towel
0.01
0.03
0.09
0.02
0.02
0.01
0.02
0.02
0.04
0.02
0.00
0.01
Amount
Harvested
.
40
65
-
-
29
40
36
29
50
-
•
- Gloves and hand wash towels were analyzed on 11-17 October 1985.
                                     37
-------
                                                                  785
Table 7.  Physical characteristics  of human subjects Involved In  the harvest
         of  tomatoes  In field two (4 June 1982) treated with chlorothalom'l.
Worker
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

Sex
M
M
M
M
M
M .
M
F
M
M
M
M
F
F
F
F
F
F
F
F
Physical
Character!
Age Height (In)
17
13
12
10
19
19
19
49
17
17
15
17
12
16
15
10
16
-
58
52
68
58
57
48
68
68
65
60
63
68
65
68
48
65
65
48
48
-
60
65
sties
Weight (Ib)
154
85
80
82
140
151
139
159
128
125
131
139
71
110
171
80
90
160
143
153
Amount
Harvested
-
•»
15
-
21
53
60
-
20
-
38
39
10
-
3
13
16
40
19
16
                                    38
-------
Table 7, continued,
                                                              786
Worker
Number
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Sex
F
F
F
F
F
F
F
M
M
M
M
M
M
M
M
M
M
M
M
M
Physical
Characteristics

Age Height (In) Weight (ib)
40
60
50
41
52
23
36
33
22
29
56
60
58
31
34
48
56
32
38
70
61
62
58
60
62
61
61
59
61
64
68
66
63
-
64
:65
\66
^67
.66
65
210
170
129
165
195
157
125
150
264
136
205
150
175
173
185
170
150
165
136
175
Amount
Harvested
20
•»
-
33
23
23
30
«•
20
28
29
39
33
56
46
46
-
30
-
20
                                 39
-------
                                                                     787
Table 8.  Chlorothalonll  residue  concentrations on patches worn by human
          subjects while harvesting tomatoes  In  second field (4 June 1982).
Worker
Number
2
3
10
14
15
19
21
32
35
36
38
39
Physical Characteristics
Sex
M
M
M
F
F
F
F
M
M
M
M
M
Age Height (In) Weight I
13
12
17
16
15
58
40
60
34
48
32
38
58
57
68
65
65
60
61
66
64
65
67
66
85
80
125
110
171
143
210
150
185
170
165
136
Ch1orothalon41 (ug/on2)!/
Amount
lib) Arm Patch
0.56
1.15
0.41
0.25
0.09
1.29
0.92
0.67
0.65
0.51
0.56
0.24
Leg Patch
1.06
1.73
1.22
0.95
1.36
2.21
1.94
3.23
0.76
1.54
0.22
2.51
Harvested
—
15
-
•-
3
19
20
39
46
46
30
"
!/ Patches were analyzed  on  19-21 September 1983.
                                     40
-------
                                                                         788
Table 9.  Chlorothalonll residue concentrations  found on gloves and hand wash
          towels  used as sampling devices by human subjects while harvesting
          tomatoes  In second field (4 June 1982).
Worker
Number
1
4
7
11
12
16
18
23
24
25
26
28
30
33
34
Physical
Sex
M
M
M
M
M
F
F
F
F
F
F
M
M
M
M
Age
17
10
19
15
17
10
-
50
41
52
23
33
29
58
31
Characteristics
Height
(In)
68
48
65
65
68
48
-
58
60
62
61
59
64
63
-
weight
(Ib)
154
82
139
131
139
80
160
129
165
195
157
150
136
175
173
Chlorothalonll (ug/cm2^
Right Glove
0.14
0.12
1.57
15.60
0.12
7.71
10.42
10.50
0.82
18.14
11.38
13.53
27.58
9.04
28.63
Hand wash low el 1
4.96
0.26
2.64
0.00
0.04
0.02
2.83
1.32
0.23
1.08
0.04
0.52
0.01
1.68
2.73
Amount
Harvested
-
-
60
38
39
13
40
-
33
23
23
-
28
33
56
*/ Gloves and hand wash towels were analyzed on 18-28 October 1985.
                                     41
-------
                                                                         789

Table 10.  Rank correlations  (Kendalls-Tau) of paired values of the physical
           characteristics  of the farmworkers and the amount of tomatoes
           harvested (buckets) against the concentrations of chlorothalonll
           detected In sampling  devices  (gloves, arm patches and leg patches)
           worn by harvesters working In field one.
                        S3S333S333333333333333333SS333333333333333333333333X38
   Physical
Characteristic
Correlation coefficients  (P  under H0 " 0)
 chlorothalonll  concentration  (ug/on2)
             Sampling  device
Height
Weight
Amount
Harvested
Gl oves Arm
0.2381
-0.1071
-0.4762 (P < 0.13)
Patches
(P <
(P <

0.
0.

45)
36)

Leg F
-0.2381
-0.0714

'atches
(P
(P

< 0.
< 0.

45)
40)

                                     42
-------
                                                                       790

Table 11.   Rank correlations  (Kendalls-Tau) of paired values of the physical
           characteristics of  the farmworkers and the amount of tomatoes  .
           harvested (buckets) against the concentrations of chlorothalonil
           detected  1n sampling devices (gloves, arm patches and leg patches)
           worn by harvesters  working 1n field two.
   Physical
Characteristic
                 Correlation coefficients  (P under H0 " 0)
                  chlorothalonll  concentration (ug/on2)
                              Sampling  device.
Height
Weight
Amount
Harvested
Gloves Arm
-0.4091
-0.0151
-0.0727 (P < 0.38)
Patches
(P
(P

< 0.07)
< 0.47)

L££
-0.0606
0.0151

Patches
(P
(P

< 0.
< 0.

39)
53)

                                     43
-------
                                                                  791
                             ACKNOWLEDGEMENTS
     A number of persons contributed materially to the work described above,
1n either the planning of the project, doing field work,  analyzing samples,
testing the data, or  preparation of the report.  These are:  N. Cano, Jr.,
M. A. Qarda,  M. E. Garcia, R. L. Garcia, K. J. Huxford,  A.  Igleslas, Jr.,
N. J. Magoulrk, A. Martinez, J. J. Mollhagen,  A. G. Navarro, and J. L. Valdez.
                                    44
-------
                                                                       792
                              LITERATURE CITED

Anonymous.   1979a.   Investigation of  pesticide residues In soil.  Anna. Rep.
     Hiroshima Pref. Agrlc.  Exp. Stn.  1978:24.

Anonymous.  1979b.   Investigation of the confirmation of the safety of
     pesticide residues.   Annu.  Rep.  Hiroshima Pref.  Agrlc.  Exp.  Stn.   1978:24.

Chin, B. H., R. 0. Hell man, R. T. Bachand, G. Chernenko and J. Barrow man.
     1980.   Absorption and biliary  excretion of Chlorothalonll and Its
     metabolites In the rat.  Toxlcol. Lett. 5(Sp 1):150.

Chin, B. H., J. B. McGloln,  N. L. Spangler,  and R. D. Hellman.  1981.
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     endotracheal, and dermal administration of l4C-chlorothalon1l.   Bull.
     Environ. Contain. Toxlcol. 26(1):258-261.

Conover, H. J.  1980.  Practical  nonparametric statistics, 2ed. John Wiley &
     Sons,  NY.  493 pp.

Farm Chemicals Handbook.  1985.  Chlorothalonll.   Melster Publishing Co., OH.
     519 pp.
                                     45
-------
Food and Agriculture Organization.   1979.  Chlorothalonll.  FAO Plant  Prod. 70?
     Prot. Paper 15 (Suppl):79-83.

Hallenbeck,  VI. H.  and K. M. Cunningham-Burns.  1985.  Pesticides and Human
     Health.  Springer-Verlag,  NY.   166 pp.

Hayes,  W. J..  Jr.  1982.   Pesticides Studied in Man.   Williams  & W1lk1ns,
     Baltimore/London.  672 pp.

Hlramatsu,  R. and F. Furutanl.   1979.  Persistence of sprayed captan and
     chlorothalonll on cucumber  grown In  greenhouse.  Effect of fruit growth
     on reduction of concentration  of pesticide  residue.  Yamaguch1-ken Nogyo
     31:23-28.

Honeycutt, R. C., G. Zwelg, N. N. Ragsdale.   1985.  Dermal Exposure Related to
     Pesticide Use.  American Chemical  Society,  Washington,  DC.  529 pp.

Horfuchl, N., S. Ando, and Y. Kambe.  1980.   Dermatitis  due  to  pesticides  for
     agricultural use.  Jpn. J. Dermatol. 90(3):277.

Jacobs, J..  L.  1981.  Soil  survey  of Hidalgo County, Texas.   United States
     Dept.  of Agriculture,  Soil  Conservation Service 1n  cooperation with  the
     Texas  Agricultural Experiment Station.   171 pp.

Johnson,  J. D. and J. M. Am ado r.   1975.  Texas guide for reducing vegetable
     disease  losses.  Texas Agricultural  Extension Service, the Texas  A & M
     University System.  Publ. No. MP-902.  15 pp.
                                     46
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                                                                        794
Kosekl, M.  Y. Shlmamura, T. Makl, Y. Tamura, and Y.  Naol.   1980.  Residues of
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     and  fruits.  Annu. Rep. Tokyo Metrop. Res.  Lab.  Public Health 31(1):
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Looney,  N.  E. and  W. P. Cochrane.  1981.   Relative effectiveness of, and
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Merck Index.  1976.  Ninth Ed.  Merck 4 Co., Inc., Rahway, NJ. 1313 pp +
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Munn, S., T. J. Keefe,  E. P. Savage.  1985.  A comparative study of pesticide
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Nlgg, H.  N. and  J.  H. Stamper.  1982.  Regional  considerations In worker
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     Exposure.   American Chemical Society, Washington, DC.  213 pp.

Parsons, J., R. Roberts, S. Cotner, T. Longbrake, P. Thompson, and VI.  Peavy.
     1977.   Keys  to profitable  tomato production In South and West Texas.
     Texas Agricultural  Extension Service, The Texas A 4 M University System.
     Publ.  No. L-1045.  Unnumbered  pp.
                                     47
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Pimentel, D., Ed.   1981.  CRC Handbook of Pest Management in  Agriculture   795
                                      •
     Vol. III.  CRC Press,  Inc., FL.  656 pp.

Reinert, J. C. and D. J. Severn.   1985.  Dermal  exposure to pesticides: the
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     Investigation of  the residue of chlorothalonil in crops  and soils.  Part
     2.  Jpn. J. Public Health 27(10):643.

Spear, R. C.   1982.  Farm worker exposure to pesticide residues:  reflections
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     Publications, CA.  181 pp.
                                     48
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                                                                   796
                                Appendix A

                                 Methods
Al  Extraction of gloves, hand wash towels and  patches for chlorothalonll.
A2  Gas chromatographlc conditions for detection  of chlorothalonll.
                                     49'
-------
     Extraction of  Gloves, Hand Wash Towels and Patches for Chlorothalonil    797!

1.   Cut sample Into  approximately 1 Inch square pieces.
2.   Place into 1000  (or 500) ml flasks.
3.   Extract three times with methanol: first with 200 mis for 20 minutes,
     second and third time with 150 mis for 15 minutes using a Burrell wrist-
     action shaker.
4.   Decant through glass wool in funnel into second 1000 ml Erlenmeyer flask.
     On last extraction be sure and wring sample  out thoroughly and rinse
     glassware well.
5.   Dry with Na2$04  to  absorb any moisture.
6.   Transfer to round bottom flask and evaporate just to dry ness.
7.   Bring up to approximately 5-10 mis with hexane.
8.   Evaporate with nitrogen  to 1 ml.
9.   Pass samples through columns, using 2 g of deactivated silica and the
     following fractions:
     Fraction I    100% hexane - use this to elute  sample.
     Fraction II   1% benzene-hexane - discard.
     Fraction III  20%  benzene-hexane - collect together with Fraction IV
     Fraction IV   60%  benzene-hexane.
     Collect III and  IV  and bring down to  desired level and give to
     chromatographer  to  be  Injected.
                                     Al
                                        50
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        Gas  Chromatographlc Conditions for Detection of Chlorothalonll OTHK
                                                                           798
               Column  I
Instrument - Tracor 220 gas chromatograph
Column - 4%  SE30/3Z OV210
Flow rate 72 cc/mln.,  2000 Q.
Detector - Electron capture (3H)
Imput attenuation 103
Output attenuation 32
Bucking range 6
Detector flow control
     02  85  ml/ml n.
     H  100  ml/n1n.

               Column  2
Instrument - Tracor 220 gas chromatograph
Column - 1.5% OV17/1.951  OY210
Flow rate 55 cc/m1n.,  200° C.
Detector - Electron capture  (3H)
Input attenuation 103
Output attenuation 64
Bucking range 6
Detector flow control
     Q2 150  ml/mln.
     H  150  ml/mln.
                                 A2
                                            51
-------
                                            798
         APPENDIX B

Worker Interviews--!? May 1982
Worker Interviews-- 4 June 1982
                    52
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                                              799
An Assessment of Exposure  of Cucumber
  Harvesters to Methomyl
        Research performed by

        Texas Tech University
        San Benito, TX  78586

        February 28, 1986
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                                                                         800
In behalf of  the  Texas PHAP the undersigned  have  reviewed  and approved the
report draft  entitled "An Assessment of Exposure  of Cucumber Harvesters to
Methomyl."
             Quality Assurance" Of fleer
                                                         Date
                                       ii
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                                                                         801
                             TABLE OF CONTENTS






Section                                                               Page






ABSTRACT	   iv




INTRODUCTION	     1




METHODS AND MATERIALS 	     3




     Study Site 	     3




     Application	     4




     Weather 	     4




     Human Subjects 	     6




     Gloves and Patches 	     6




     Hand Washes 	     7




     Other Substrates 	     7




     Instrumentation 	     8




     Recoveries 	     8




     Analytical Standards 	     8




RESULTS AND DISCUSSION 	     9




FIGURE	    14




TABLES 	    15




ACKhOfl^EDGEMENTS 	    29




LITERATURE CITED 	    30




APPENDICES (Worker Interviews) 	    32




     A.  4 May 1982 	    32




     B.  19 May 1982 	   132
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                                                                       p,   802

     Transfer of dislodgable residues of methomyl (methyl  N-[(methyl
carbamoyl) oxy]  trloacetimidate) to sampling devices  worn  by  farm workers was
examined to estimate the  potential risk of exposure to a liquid formulation  of
LannateR during  the  harvest of cucumbers grown in the Lower Rio Grande
Valley of Texas  on two sampling dates 4 May 1982 and 19 May 1982.   The  highest
accumulation of methomyl residues were found on  gloves  on both study dates,  4
May 1982 (1.70_+0.97 ug/cm2) and 19 May 1982 (0.88^0.40 ug/cm2).  Residues
did not penetrate through the gloves as indicated by the reduced
concentrations detected  in hand wash towels (0.067 +_ 0.038 ug/cm2).   The
concentrations of residues on gloves and arm and leg patches  were compared
with the physical  characteristics of the workers which might influence  their
performance.  Residue concentrations detected on the sampling devices were
found to be independent  of the  amount  harvested  as well as the  age, sex,
height, and weight of the workers on both study  dates.
                                   IV
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harvesting cucumbers.  Although methomyl 1s quite unstable and degrades
rapidly,  build up of  methomyl after repeated  applications has been observed
(Kuhr and Do rough,  1977).  The residual-persistence  of methomyl  may be short
under certain environmental  conditions  (Kuhr  and Dorough, 1977) with an
expected half life  of 1 week.  The level of exposure to methomyl  may be
dependent on  the capacity  to transfer pesticide residues from leaf or fruit
surfaces to a harvester.  Cucumbers may represent a low-risk potential because
of the low growth habit a property which  restricts  activities from the
breathing zone and exposure  to the torso and  upper  legs and arms.  However,
hands alone may account for perhaps the largest part of  the residues
accumulated by workers.   The harvesting of cucumbers does require handling of
considerable  foliage.   In  addition, the picking of cucumbers In early morning
when leaves are covered  with dew may facilitate both the transfer and uptake
of pesticide  residues (Longbrake  et  al.,  1980).
     Measurement of residue concentrations transferred from the  foliage  to
workers while harvesting may reflect the residual persistence of methomyl
(Lannate^ L).  Lannate^ L 1s a water soluble liquid  formulation
of 24 percent methomyl (DuPont, 1977).   At the time of the  study,
Lannate(R)  L  was labeled for use on cucumbers (EPA Reg.  No. 352-370)
although the  Texas Agricultural  Extension  Service  (1980) did not recommend
any formulation of methomyl for control of insects  on cucumbers.  The
preharvest Interval following applications at the  rate of 2 to 4 pints per
acre is one day while higher application rates require a three  day  preharvest
Interval  (DuPont,  1977).
     The purpose of this study was to examine the  transfer of methomyl
residues from the foliage  to gauze patches located  on the arms and legs, and
gloves worn by juvenile (age < 17 years)  and  adult farmworkers.
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                                                                         803
                                INTRODUCTION

      Methomyl 1s a cholinesterase inhibiting insecticide with an oral  LD 50s
of 17.0 mg/kg for the male  rat and 24  for the female  rat (DuPont, 1980).   The
24 percent liquid formulation  has been observed to have an oral LD 50 of 130
in rats {DuPont,  1977) and  a dermal  LD 50  of 5,880 in rabbits  (DuPont, 1980;
A.C.G.I.H.,  1984).   Methomyl  does not appear  to  significantly  influence weight
gain or growth of male or female rats (Hayes,  1982).  Chronic feeding studies
involving  laying  hens did not  indicate any peripheral neurotoxic effect
(Hayes, 1982).  Methomyl  does  not  have a cumulative action (Wagner,  1983).
In addition,  methomyl does  not adversely effect reproduction or lactation
(Hayes, 1982) and teratogenic  and mutagenic  effects have not been observed
(Wagner, 1983).
     Toxicity of  methomyl  to man has been observed from  accidental poisoning
(Ecobichon and Joy,  1982 and Hayes,  1982) with few reported incidents  of
occupational  exposure (Wagner, 1983).   Hayes  (1982) reported 225 poisonings
resulting  from the use of dry  formulations of methomyl.  The continuation of
problems associated with inhalation of a powdered formulation have been  ruled
out following reformulation and marketing  of methomyl as a liquid concentrate
(Hayes, 1982).  Nevertheless,  reentry may represent considerable hazard  owing
to the extreme toxicity of methomyl (Hayes,  1982).   The  risk  of  exposure can
be reduced considerably by observing the reentry Interval.
     The potential  exposure of migrant workers to methomyl  may be estimatee
from the detection of residues of methomyl on sampling devices worn  by workers
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                                                                      804
                           ^THODS AND MATERIALS
     The chemical  name  of roethomyl  Is methyl N-[(methylcarbamoyl)oxy]
thioacetimidate; the  structural  formula  is depicted  below.  This substance
has a vapor pressure of 5 X 10'5 mm Hg  at 25° C (A.C.G.I.H.,  1984).
                                       o
                                       !l
                             CH,-C=N -O- C  NM  (11
                                 I
                                 S-CH.
                         methyl ft-|(m*thylcjrD*moylio>y :mio
-------
grower was made only to remain Informed of farm practices.
     The site was an Irrigated, single  20  acre  block of cucumbers.  The field
was Irregularly shaped,  measuring approximately 799 m on the north side; 1,010
m on the east; 653 m on the south; and 653 m on the west.  The topography was
essentially flat, with furrows running north-south.
     Application.  LannateW  L was  aerially applied at the rate of 2 pints
per acre on two dates, 3 May 1982 and 18 May 1982.  Both applications occurred
before observers could reach the  field,  thus  the exact times could not be
established.   But, in both Instances the application occurred before 1600
hours.  Reentry and harvest followed on consecutive dates after each
application.   There were no previous applications of any pesticides to this
crop.
     Weather.  The weather on the first date of application (3 May 1982) was a
morning low of 65° F and an afternoon high of 79* F.  Scattered thundershowers
were occurring  and  0.1 inch of precipitation fell  on  the  site in  the  morning.
On the following day the temperature ranged from 65* F  to  84* F.  There was no
precipitation at the site but scattered thundershowers  remained in the  area.
     The temperatures on the second  date of application ranged from 64*  F  to
85* F-  Rainfall amounting to 3.32 inches  had occurred  overnight.  There was
no precipitation on the  harvest date and tempertures ranged from  67*  F  to  90*
F-  Neither wind direction nor velocity were recorded  for  any of  the  dates.
     Human Subjects.  The population studied consisted  of a crew  of harvesters
selected solely by the labor contractor.  The workers  did  not have advanced
notice of the study.  The cohort on  the day following  the  first application (4
May 1982) consisted of  10  female and 23 males  (Tables  1,2).   The  cohort
following the second application (19 May 1982)  consisted of 9 females and 27
males (Tables 3,4).
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     Details  of the actual harvest of cucumbers may vary from region to          onx
                                                                               o06
region,  and often from grower to grower, but the most common practices In
South Texas are those observed  1n this study.  Individual workers are assigned
rows of vines to  facilitate crediting the vegetables picked to the approplate
worker.  A worker may chose  to pick one  or  two or sometimes more rows
depending upon their speed.  Each harvester 1s equipped with a 5 gallon
plastic pail  and  a  supply of burlap  bags.  The bags are either tied around the
waist or thrown ahead  as the harvest proceeds down the row.  Mature cucumbers
are placed  Into the plastic pail  until it 1s full.  The contents of the  pail
are then dumped  Into  a burlap  sack and  the  sack  Is left behind  to be later
picked by a loading crew with a truck.
     Depending upon market conditions,  the  crop  may be harvested three or more
times.  At  first  picking vines  do  not cover  the  ground.  Thus contact with
foliage, possibly bearing residues,  is confined  almost exclusively  to the
hands.  As the season progresses there Is more contact  between  the  foliage and
the feet,  ankles, and  forearms.  Although  the  growth habit of  the crop Is low
and would  appear  to pose minimal  risk,  the  leaves  are  very large and the
vegetable  lies on the  ground.   Thus  there is considerable  contact with the
foliage.
     The workers  arrived at the field at 0630.   After  an explanation of  the
work proposed, the  volunteers  proceeded through  a  series of study  stations
where they:  (1)  signed  consent  forms; (2) were briefly Interviewed; (3)  were
weighed; and  (4)  were  equipped  with gloves and dermal  patches.  For easy
identification,  all participants had numbered tags pinned to their clothing.
None of  the workers were provided  with  any  clothing or protective devices
beyond what they  brought to the field.
     On  the dates of study all  the workers had  entered  the  field at 0800.
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While they were harvesting, a somewhat longer Interview (15-20 minutes)  of   807
each worker was undertaken to obtain their work history as well as their
perception of their own health  and  medical history.  During the Interview,
notes were taken on Individual  picking practices  (Tables 1, 2).  On both dates
harvest activities  were completed by  1145; no harvesters were 1n the field
longer than four hours.  On the first harvest date the number of buckets of
cucumbers picked by each worker was obtained from the labor contractor for
possible correlation with residues  detected  in  the  several  substrates tested.
The contractor declined to provide the same information on the second harvest
date.
     Gloves and Patches.  Harvesters were equipped with sampling devices,
gloves and 103.2  cm2 gauze patches on both arms and legs  (Fig. 1).  Gauze
patches were placed at near equal distances  from  the  ankle on the outside legs
and on the inner aspect of the  forearms equal distance from the wrist.  Light
weight twill work  gloves of 100 per cent cotton (Sears catalog number 51 K
259151) were worn by workers  to measure the amount of contact with residues
through the hands.   The average surface area of the gloves minus the knit
wristlet was  549.7 cm2-
     Following a period of exposure, gloves  and patches were collected, sealed
in plastic bags, and placed on  dry  ice.  The gloves were cut  into 2 to 3 cm2
pieces (the knit wristlets were not tested)  and placed  in a 1.0 1 Erlenmeyer
flask and extracted three times with  350 ml  methanol  on a  Burrell wrist-action
shaker at setting 8.  The  pieces  were transferred to  a  Buchner funnel and
washed.  The extracts were combined,  filtered,  and concentrated  to 1.0 ml  with
a Buchi Rotavapor R110.  The concentrate was transferred  to  a 13  ml  centrifiige
tube and adjusted  to 10 ml.  The mixture was centrifuged at 1,000 RPM fcr 1
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                                                                             808
minute to obtain the final extract and prepared for high performance liquid



chromatography (HPLC).




     The right and left leg patches (206.4 cm2 ) were extracted together as




were the right and left forearm patches.  The patches were extracted three




times with 150 ml methanol in a 500 ml Erlenmeyer flask on a Burrell wrist-



action shaker on setting 6.  The extracts were collected and dried with



sodium sulfate and evaporated to 5.0 ml.  The concentrate was adjusted to




10.0 ml and prepared for analysis by HPLC.




     Hand Washes.  Exposure to the hands was estimated from residues




collected on hand towels used by the workers after they completed their




work.  The towels (84 % cotton, 16 % polyester, 890.3 cm2 , from Leshner, St.




Marys, CXI) were saturated with a 50:50 ethanol and water mixture then wrung




out just prior to use by the workers.  Each worker was given a single towel




and instructed to thoroughly wipe between the fingers and the fronts and




backs of the hands only as high as the wrist.  Once the washing was




completed, the worker dropped the hand towel directly into a resealable




plastic bag held open by a technician.  These bags were placed on dry ice




for transport to the laboratory, where they were kept frozen until analysis.




The procedure for extracting and testing for residues was the same as that




described for gloves and patches above.




     Other Substrates.  No samples of soil, urine, or deposition panels were




collected or used in this study.  Eight workers had been equipped with




personal air samplers on both study dates with the expectation that a




suitable method could be developed to extract methomyl from the entrapment




medium.   This could not be done.  Foliage samples were collected on both




dates just prior to the workers entering the fields.  However all  specimens
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                                                                            809
decomposed before testing could be initiated.

     Instrumentation.  Measurements of methomyl residues in the extracts

from the sampling devices were determined by HPLC according to the method of

Cramer et al. (1982).  Analysis was performed on a Waters HPLC equipped with

two Model 6000A solvent delivery systems and a Model 440 absorbance detector

set a 254 nm for the detection of methomyl.  The column utilized was a C-18

by Waters Associates.  Reverse phase was used with 25 % acetonitrile and 75

X water at a flow rate of 1 ml per minute.

     Recoveries.  Recovery of 100 ug methomyl in patches was 97.46 + 2.84 %

of expected concentrations.  The recoveries were well clustered about the

mean (CV = 2.92 %).  Methomyl recovered from gloves fortified with 1000 ng

of the compound averaged 1055 ± 203 (CV = 19.2).  The recovery of 200 ug of

methomyl fortified to wash towels averaged 54.9 + 9.4 % and was also

somewhat variable (CV = 17.0).

     Analytical Standards.  The analytical standards used for fortification

and comparison were obtained from the U.S. Environmental Protection Agency's

Health Effects Research Laboratory at Research Triangle Park, NC, 27711.

The standard used was methomyl, code number 4520, with a documented purity

of 99+ %.  The concentrated standard prepared for fortification purposes was

a 1 mg/ml concentration.  The working standard was at a 500 ng/ml

concentration.
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                                                                            810
                           RESULTS AND DISCUSSION
     The transfer of dislodgable residues of Lannate^  L  from the  foliage  to
workers harvesting cucumbers  was examined by measuring concentrations of
methomyl on sampling devices, gauze  patches on arms and legs and  gloves worn
by fanmworkers.  Concentrations of methomyl on right and  left hand gloves
were examined to determine If harvesters were  demonstrating right or left  hand
preferences.   Residue levels  might be expected  to be greater in right hand
gloves if workers were biased to use the right  hand while picking.  A paired
t-test of the difference between residue concentrations of methomyl detected
in right and  left hand gloves did not indicate  a significant difference
(t » 0.6367,  d.f. = 17, P > 0.50) between residue levels on the first
sampling (Table 5).   Similarly, on the second  sampling an hour later, no
significant difference (t = -0.0684, d.f.  « 13, P > 0.50)  was observed between
residue levels in right and left hand gloves  (Table 6).  The harvesters did
not appear to prefer either hand while  harvesting.  The gloves were regarded
as a single population and pooled to compare differences between residue
concentrations at each sampling period.
     The differences in  methomyl concentrations between sampling periods were
compared by worker.  The paired test revealed  a significant difference (t  -=
7.9125, d.f. » 21, P < 0.001)  in methomyl  concentrations between sampling
periods.   Significantly greater residues  of methomyl  (1.67 +_ 0.97  ug/cm*,  t« =
36) were found in the first sample  period.  The difference  observed  in residue
-------
concentrations In gloves between periods was attributed to loss  of methomyl         [
                                                                                81
from the foliage; the performance  of the  workers  did  not  change.                   '
     The concentrations of methomyl  detected In arm patches for the two
sampling periods (Tables  7,8) appeared to  reflect the difference observed for
gloves.   Greater  concentrations of methomyl were detected In arm patches  from
the first sampling period (0.54 ^ 0.35 ug/cm2> n = 15) compared to the
second (0.38  +_ 0.57 ug/cm2, n * 3).  However, the ranks of the unequal
samples were found to be not significantly different (T = 22, n = 3, m = 15,
P > 0.44) by  the  Mann-Whitney test for independent samples.  This result  was
challenged by a paired test  of  samples obtained from  workers  entering the
field on the  two  sampling periods.  The Wilcoxon signed ranks test of matched
pairs revealed no significant difference (T = 0.4286,  d  = 3,  P > 0.344)
between samples  from the two periods. Concentrations of methomyl on arm
patches  did not appear to  reflect  loss of  residues from foliage between
periods.  The residue levels on arm  patches appeared  to represent reduced
contact between  foliage and  arm patches.
     Mean residue concentrations in  arm patches (0.54 ± 0.35  ug/cm2,
n = 15)  and leg patches (0.40^0.38 ug/cm2, n = 12) collected  on the first
sampling  period  were found  to  be  significantly different (F « 30.485, d.f.
2,60, P  <  0.001) from gloves (1.67 +_ 0.97  ug/cm2).   Duncans  multiple  range
test revealed no significant difference between mean concentrations of
methomyl  residues  in arm (Table  7)  and  leg patches  (Table 9) at the  5.0% level
of confidence.   Exposure appeared to occur predominately through the hands.
     The protective value of the gloves was examined on  the  second date of
application  (19 May  1982).   As  observed  in the previous study (4 May  1982),
the mean concentration of methomyl  detected in right hand gloves (0.86 _* 0.48
ug/cm2, n = 22) was not significantly different (t = -0.2442, d.f. = 4!, ? *
                                     10
-------
 0.50) from left hand gloves (0.90 _+0.43 ug/cm2, d.f. = 21, P > 0.50).            o .
 However, the means of the pooled samples for both studies  were found to
be significantly different (t = 4.7183, d.f. = 77, P < 0.001).  The studies
were regarded  as  Independent.
     Inferences about the  protective value  of gloves were  gained from
comparisons of mean residues detected in gloves and concentrations found 1n
hand washes In study 2 (Table  10).  Using the surface area of  the gloves to produce
 similar units (ug/cm2), the pooled mean concentration of met homy 1 1n gloves
 (0.88+.0.40 ug/cm2, n = 43) was significantly greater (t = 8.5442, d.f. = 65,
 P < 0.001) than that recovered 1n hand  washes (0.067 +_ 0.038, n = 24).   Gl oves
appeared to afford protection  from accumulating residues of methomyl on the
hands.  Assigning protective value to the gloves did not appear to be
appropriate given the adjustment necessary to normalize units to  the size of
gloves.  Clearly,  however, the  predominant area of exposure appeared to occur
through the hands.  As in  the  first sample, concentrations in  the gloves were
significantly greater (F  = 14.279, d.f. = 2,67, P <  0.001)  than In  either arm
patches (0.24 +_ 0.22 ug/cm2,  n * 14) or leg patches (0.49 +; 0.41 ug/cm2, n «=
13 (Table  10).  However, in contrast to the  first sample,  the  Duncans multiple
range test revealed a  significant difference (P  < 0.05) between mean
concentrations in arm and  leg  patches.
     Concentrations  of methomyl detected in the sampling devices were examined
in relation to worker performance and physical  characteristics, such as height
and weight, to expose biases which might Influence  worker exposure.  The
performance of a  worker  was believed to be  dependent on sex,  age, height, and
weight.  The physical condition of the subjects, relative  to  habits which
might effect  health (Tables  1,2,3,4), may attenuate effects of sex, age,
height and  weight on performance.
                                     11
-------
     Although many of the same workers  were Involved in harvesting on both
dates, the worker groups were considered  Independent.  Ranks of  the age of       813
female workers (Table 1) were found  to  be not significantly different (t »
178.5, n  » 10, m = 23, P  > 0.369) from males (Table 2) according to the Mann-
Whitney test for Independent  samples.  The mean age of female workers was
43.3 _+ 12.8 years.  The mean age of male workers was 37.0^ 19.0 years.  The
lack of an age difference between males and females was attributed to the
composition of the work  unit  as a group of families.
     As might be expected  the ranks  of  heights of male workers (Table 2) were
significantly different  (t =  55, n = 8,  m = 22, P < 0.001) from  females
(Table 1).   However,  the ranks of weights of males  (Table 2) and females
(Table 1) were not significantly different (t = 149.5, n  « 10, m = 23,
P > 0.211).   The mean height  of males was 1.67 _+ 0.12 m while the  mean
height of females was 1.59 +_ 0.07 m.   The mean weight of females was 68.4
+_ 22.2 Kg.  The mean  weight  of males was 69.3 +_ 14.0 Kg.
     The  performance  of  the workers  In terms of cucumbers picked was  compared
to the physical  factors  of age, height, and weight.  Correlations  on ranks  of
amount harvested (Tables 1,2) and the physical  factors  for  females were  found
to be independent by age  (Tau - 0.3928, P > 0.10) and height (Tau - -0.0667, P
> 0.20).  The correlation on  weight was found to be more ambiguous (Tau  =
0.5357,  P >  0.05);  weight of  female  workers  appeared to  influence performance.
     The  correlations of amount harvested with the physical  factors for  males
were  found  to be  Independent for age (Tau  = 0.1324, P >  0.20), height (Tau  -
0.3167, P >  0.05), and weight (Tau = 0.3162, P  > 0.05).   The combined effects
of these  factors  was  not examined.
     Exposure of  harvesters to methomyl  residues on cucumber leaves was
examined in relation  to the  physical factors of  age, height, and  weight.
                                     12
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                                                                                814
Contact with cucumber foliage was  expected to depend on performance.  Rank
correlations were performed between residue  concentrations detected on gloves,
arm patches and leg patches and  amount harvested.  Residue concentrations on
gloves were found to be independent (Tau * 0.1304, P  > 0.62,  n » 12) of amount
harvested.   A similar result was obtained between concentrations found in arm
patches and amount harvested (Tau * 0.1970,  P > 0.50).  Concentrations
detected in gloves was  also found  to be  independent of amount harvested  (Tau =
0.2333,  P > 0.20, n = 9).   Clearly, the accumulation  of residues of methomyl
on these sampling devices  was not influenced by the  ability  to  harvest.
     Relationships sought  between the  physical  factors, age, height and
weight, and residue concentrations in  the various substrates were  found  to be
independent as  well.   The  correlations between  the concentrations of methomyl
detected in the sampling devices and the physical factors for the workers
involved in the first sampling period on day 1 (Table 11) and  day 2 (Table  12)
were uniformly independent. These results suggest that accumulation  of
residues of methomyl on the clothing  of farmworkers  is independent of physical
characteristics of the  workers  and their ability to  harvest  cucumbers.
                                     13
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                                                     815
                   Air Pump
                               Subject Number
                                           .J
Leg Patches
                              Cotton Gloves
Fig. 1.  Positions of sampling devices (air pumps,
body patches and gloves) worn by workers harvesting
cucumbers treated with a formulation (Lannate(R) L)
of methomyl.
                      14
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                                                                               816
Table 1.  Physical characteristics and health  habits of female workers
involved in harvesting cucumbers  treated with Lannate^  L on first  day (4 May
1982) after first application.
Physical Characteristics^ Health Habits
Worker
Number
1
3
5
7
8
9
11
21
32
33
Age
36
30
33
34
30
70
54
48
40
48
Height(m)
1.62 (64)
1.60 (63)
1.55 (61)
1.68 (66)
1.52 (60)
-
-
1.57 (62)
1.50 (59)
1.68 (66)
Weight(kg)
81 (179)
71 (156)
58 (128)
51 (113)
54 (118)
46 (102)
64 (140)
123 (270)
59 (129)
77 (169)
Smoker
Yes
No
Yes
No
Yes
No
Yes
No
No
No
Alcohol
Consumer
Yes
No
Yes
Yes
No
No
Yes
No
Yes
No
Under
Medication
No
No
No
No
No
No
No
Yes
No
No
Amount
Harvested
-
44
-
23
30
20
25
30
31
33
%  Height in meters  and weight in  kilograms.  Values enclosed are inches and
pounds respectively.
                                     15
-------
                                                                          817
Table 2.  Physical characteristics and health habits  of  male workers involved
in harvesting cucumbers treated  with Lannate^' L on first day (l\  May 1982)
after first application.
Physical Characteristics^3- Health Habits
Worker
Number
2
4
6
10
12
13
14
16
17
19
Age
41
51
18
64
39
25
58
25
65
57
Height(m)
1.83 (72)
1.70 (67)
1.72 (68)
-
1.65 (65)
1.65 (65)
1.65 (65)
1.70 (67)
1.60 (63)
1.75 (69)
Weight(kg)
94 (206)
82 (180)
61 (134)
67 (147)
70 (155)
61 (135)
70 (155)
64 (140)
69 (152)
57 (126)
Smoker
No
No
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Alcohol
Consumer
Wo
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
No
Under
Medication
Yes
No
No
No
No
No
No
No
No
Yes
Amount
Harvested
-
-
-
36
24
25
24
-
22
27
                                     16
-------
                                                                       818
Table 2 (Cent.).
Physical Characteristics^ Health Habits
Worker
Nunber
20
22
23
24
25
26
27
28
29
30
31
34
35
Age
13
15
52
15
35
71
62
47
46
15
14
33
23
Height(ra)
1.65 (65)
1.19 (47)
1.72 (68)
1.68 (66)
1.72 (68)
1.62 (64)
1.78 (70)
1.78 (70)
1.70 (67)
1.68 (66)
1.68 (66)
1.65 (65)
1.68 (66)
Weight(kg)
65 (144)
59 (130)
86 (190)
59 (130)
110 (242)
75 (165)
61 (134)
86 (189)
59 (130)
55 (122)
59 (130)
54 (120)
71 (156)
Smoker
Yes
Yes
No
No
No
No
Yes
Yes
Yes
No
No
Yes
Yes
Alcohol
Consuner
Yes
Yes
Yes
No
No
Yes
Yes
No
Yes
No
No
Yes
Yes
Under
Medication
No
No
No
No
No
No
No
No
No
No
No
No
No
Amount
Harvested
23
-
22
21
28
22
33
30
42
31
31
40
-
a/
u  Height in meters  and weight in kilograms.  Values enclosed are inches and

pounds respectively.
                                    17
-------
                                                                        819
Table 3. Physical characteristics and health habits  of  female workers involved
in harvesting cucumbers treated with Lannate^' L on second application
(19 May 1982).
Physical Characteristics^
Worker
Number
10
11
12
13
14
15
16
17
18
Age
60
34
20
54
53
34
50
36
40
Height(m)
1.52 (60)
1.70 (67)
1.57 (62)
1.52 (60)
1.52 (60)
1.60 (63)
-
1.65 (65)
1.57 (62)
Weight(kg)
50 (111)
60 (132)
54 (120)
66 (145)
95 (210)
48 (106)
76 (168)
62 (137)
59 (130)
Health Habits
Sinoker
No
No
Yes
Yes
No
Yes
No
No
No
Alcohol
Consumer
No
Yes
Yes
Yes
No
No
No
No
No
Under
Medication
No
No
Yes
No
No
No
No
No
No
31 Height in meters and weight in kilograms.   Values enclosed are inches and
pounds respectively.
                                     18
-------
                                                                          820
Table 4.  Physical characteristics and health habits of male workers involved
in harvesting cucumbers treated with Lannate^1"  L on second application
(19 May 1982).
Physical Characteristics^
Worker
Number Age
1
2
3
4
5
6
7
8
9
19
20
21
22
23
24
39
25
27
18
33
51
15
15
14
54
57
36
27
41
23
Height(m)
1.65 (65)
1.68 (66)
1.60 (63)
1.72 (68)
1.65 (65)
-
-
1.70 (67)
1.60 (63)
1.78 (70)
1.75 (69)
1.68 (66)
1.55 (61)
1.83 (72)
1.57 (62)
Weight(kg)
68 (150)
60 (132)
68 (150)
57 (126)
54 (120)
57 (125)
-
56 (124)
60 (131)
86 (190)
59 (129)
111 (244)
58 (127)
94 (207)
59 (130)
Health Habits
Alcohol
Smoker Consumer
Yes
No
Yes
Yes
Yes
Yes
-
No
No
No
Yes
No
Yes
-
Yes
Yes
No
Yes
Yes
Yes
Yes
-
No
No
No
No
No
Yes
-
Yes
Under .
Medication
No
Yes
No
No
No
No
-
No
No
Yes
Yes
No
No
-
No
                                    19
-------
                                                                821
Table 4 (Cont.).
Physical Character! stics^/
Worker
Number
25
26
27
28
29
30
31
32
33
34
35
36
Age
22
21
20
22
68
64
67
61
60
46
74
62
Height(ra)
1.60 (63)
1.62 (64)
-
1.70 (67)
-
1.72 (68)
1.72 (68)
1.65 (65)
1.78 (70)
1.70 (67)
1.62 (64)
1.78 (70)
Weight(kg)
63 (139)
81 (178)
69 (152)
74 (162)
74 (163)
69 (151)
70 (153)
71 (157)
73 (161)
61 (134)
68 (150)
60 (131)
Health Habits
Smoker
Yes
No
Yes
No
Yes
Yes
No
No
No
Yes
No
Yes
Alcohol
Consumer
Yes
No
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Under
Medication
No
Yes
No
No
Yes
No
No
No
No
No
No
No
2t Height in meters and weight in kilograms.  Values enclosed are inches and
pounds respectively.
                                    20
-------
                                                                          822
Table  5.  Methomyl residue concentrations on gloves worn by human subjects
while  harvesting cucumbers during the first  sampling period after first day
of application (4 May 1982).  F » Females, M = Males.  Values with -
are missing.

================================s=============================================
                                        Methomyl  (ug/on2)
Worker
Number
1
2
3
4
5
6
7
9
10
15
18
19
20
21
24
25
28
29
33

Sex
F
M
F
M
F
M
F
F
M
M
M
M
M
F
F
M
M
M
F

Left Glove
2.82
0.24
0.22
1.58
3.15
3.43
0.90
1.28
1.49
1.70
1.38
1.33
1.86
1.43
1.38
1.46
1.10
1.55
2.01
1.59 + 0.83
Right Glove
2.39
0.27
0.27
4.56
2.77
3.57
0.73
1.46
1.50
2.49
1.51
1.35
1.94
1.47
0.72
-
-
1.84
1.09
1.76 + 1.13
                                    21
-------
Table 6.   Methomyl  residue  concentrations on gloves worn by human subjects
while harvesting cucumbers  during the second sampling period after first day
of application (4 May 1982).  F = Females, M * Males.

==r=============================================r=============3=============s
                                         Methomyl (ug/on2)
Worker
Number
4
7
9
10
12
14
19
20
21
24
25
28
29
33
w£lSSSZS5Z3SZZSSSSS
Sex
M
F
F
M
M
M
M
M
F
M
M
M
M
F

Left Glove
0.00
0.00
0.01
0.10
1.44
1.10
0.05
0.04
0.12
0.00
0.04
0.00
0.00
0.05
0.21 + 0.46
Right Glove
0.00
0.00
0.00
0.12
1.49
1.10
0.04
0.09
0.13
0.07
0.00
0.03
0.00
0.02
0.22 + 0.46
                                    21A
-------
                                                                        824
Table 7.   Methomyl  residue concentrations on arm patches worn by human
subjects  while harvesting cucumbers during the  first  sampling period after
first day of application (4 May 1982).   F « Females,  M =  Males.

==============================================================3===============
                                              Methomyl (ug/cm^)
Worker
Number
8
13
14
16
17
22
23
26
27
30
31
32
34
35
Sex
F
M
M
M
M
M
M
M
M
M
M
F
M
M
Arm Patch
0.68
1.38
0.38
0.06
0.69
0.68
0.33
0.19
0.28
0.95
0.77
0.46
0.72
0.59
                                                0.58 + 0.34
                                     22
-------
                                                                           825
Table 8.   Methomyl residue  concentrations on patches worn by human subjects
while harvesting cucumbers  during the second sampling period after first day
of application (4 May 1982).  F = Females, M =  Males.

s=zrzas===3==s===============================================================r

                                         Methomyl (ug/on2)
             Worker
             Number        Sex        Arm Patch        Leg Patch
              13            M           1.04             0.00


              23            M           0.00             0.00


              30            M           0.04             0.00



==============================================================================


                                    0.36 + 0.59          0.00
                                    23
-------
                                                                          826
Table 9.  Me t ho my 1  residue concentrations on leg patches worn by human
subjects  while harvesting cucumbers during the first sampling period after
first day of application (4 May 1982).  F  « Females. M  « Males.

SSSSaS3S8ZSSSSSBSB=SSSSSSSSSSS3SS=SSSSaSSSSSS=SSSSSS3==BS=BS*SBSSSSS==SSSS
                                             Methomyl (ug/on2)
Worker
Number
8
11
14
17
22
23
26
27
30
31
34
35
Sex
F
F
M
M
M
M
M
M
M
M
M
M
Leg Patch
0.41
0.47
0.25
0.26
0.78
0.05
0.10
0.23
0.22
0.18
0.41
1.42
                                                0.40 + 0.38
                                    24
-------
                                                                         827


Table 10.   Methomyl  residue concentrations found on substrates  from human
subjects while harvesting  cucumbers  on  second  application (19 May 1982).
Value for hand wash  =  ug methomyl /glove surface area.  F * Females,  M = Males.
Values with - are missing.



                                Methomyl (ug/cnr)
Worker
Number
1
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Sex
M
M
M
M
M
M
M
M
F
F
F
F
F
F
F
F
Left Glove
0.24
-
0.26
-
0.57
0.20
-
1.05
-
1.64
0.95
-
0.59
0.98
1.10
_
Right Glove
0.28
-
0.28
-
0.63
0.09
-
1.20
-
1.15
0.61
-
0.71
0.97
0.94
_
Hand Wash Arm Patch
0.04
0.00 0.13
0.07
0.11
0.05
-
0.13 0.11
-
0.06 0.02
0.05
0.07
0.42
0.04
0.09
0.05
0.03
Leg Patch
-
0.26
-
0.06
-
-
0.10
-
1.21
-
-
0.59
-
-
-
0.08
                                    25
-------
Table 10.  Cont.
                                           828
Worker
Number
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Sex
F
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M

Left Glove
-
0.80
0.76
1.27
0.86
0.03
1.06
1.04
-
1.38
-
0.81
-
-
1.82
0.67
1.03
-
^
Methomyl
Right Glove
-
0.59
0.86
1.37
1.08
0.00
1.03
1.00
-
1.58
-
0.81
-
-
2.10
0.65
1.08
»
«
(ug/cnF)
Hand Wash Arm Patch
0.41
0.03
0.03
-
0.00
-
0.10
0.13
0.13 0.03
0.10
0.11 0.71
0.03
0.06 0.35
0.00
0.08
0.07
0.09
0.38
0.18

Leg Patch
0.76
-
-
-
-
-
-
-
0.43
-
0.95
-
1.12
0.02
-
-
-
0.22
0.53

              0.87+0.45
0.86+0.48   0.067+0.038  0.22+0.21   0.49+0.41
                                   26
-------
                                                                        829
Table 11.   Rank correlations  (Kendalls-Tau) of concentrations of methomyl
detected in sampling devices  collected from  farm workers during the first
sampling period first sample  day (4 May 1982).
s===s=========================================================================
                         Correlation coefficients  (P  under HQ = o)
  Substrate                        Methomyl  Concentration

                       Age                Height                Weight
  Left glove     -0.0812 (P< 0.65)     -0.2732  (P<  0.16)    0.0074  (P< 0.96)
  Right glove     0.3828 (P< 0.85)     -0.0790  (P<  0.71)    0.0383  (P< 0.84)
  Arm patch      -0.4000 (P< 0.07)     -0.1907  (P<  0.40)    -0.4122  (P< 0.06)
  Leg patch      -0.1679 (P< 0.45)     -0.3587  (P<  0.13)    -0.1985  (P< 0.37)
                          =================================================e==
                                     27
-------
                                                                  830
Table 12.   Rank correlations  (Kendalls-Tau) of concentrations  of  methomyl
detected in sampling  devices  collected from farm workers on the second date
(19 May 1983).

ma=========*================s=a==============================3=3=-============

                        Correlation coefficients (P under H0 * 0)
  Substrate                       Methomyl Concentration


                      Age                  Height                Weight
  Left glove     -0.1148  (P<  0.08)      -0.1585  (P< 0.38)     0.0286 (P< 0.86)

  Right glove    -0.0339  (P<  0.80)      -0.2340  (P< 0.20)     0.0190 (P< 0.90)

  Hand wash      -0.3303  (P<  0.02)      -0.0055  (P< 0.97)    -0.0582 (P< 0.68)

  Arm patch      -0.1326  (P<  0.51)      -0.0928  (P< 0.67)    -0.1677 (P< 0.43)

  Leg patch       0.0513  (P<  0.81)      -0.2518  (P< 0.24)     0.0129 (P< 0.95)

                                     28
-------
                                                                     831
                              ACKNOWLEDGEMENTS

     A number of persons contributed materially  to the work described above,
in either the planning of the project,  doing fieldwork, analyzing samples,
testing the data, or preparation of the report. These are:  V. F.  Cox, C. C.
Dary,  M. A. Garcia, M.  E. Garcia,  R. L. Garcia, A. Guillen,  Jr.,  K. J.
Huxford. N. J. Magouirk, A. Martinez, T. R. Mollhagen, A. G. Navarro, J. L.
Valdez.
                                    29
-------
                                                                     832
                              LITERATURE CITED
American Conference of Government Industrial Hygienists.  1984.  Documentation
    of the threshold limit values for chemical substances in the environment
    A.C.G.I.H.,  Inc.,  Cincinnati,  OH.  504  pp.

Bondy, M. K., R. H. Lebow, M. O'Malley,  T. Reilly.  1976.  Occupational
    health and  safety for agricultural  workers.  DHEW  (NIOSH) Publ. No. 77-
    150.   Washington,  D.C.

Cramer, P. H.,   A.  D. Drinkwine, J. E.  Going, and A.  E. Carey.  1982.
    Determination of carbofuran and its metabolites by high-performance liquid
    chromatography  using on-line trace  enrichment.  J. Chromatog.  235:489-500,

E. I.  Dupont de Nemours & Co.  1977.  Material safety data sheet for
    Lannate'^' L insecticide.  Biochemical Dept., Wilmington, DE.  3 pp.

E. I.  Dupont de Nemours & Co.  1980.  Me thorny 1 technical  data sheet.
    Biochemical Dept., Wilmington,  DE.   6 pp.

Ecobichon,  D. J. and  R.  M.  Joy.   1982.   Pesticides  and neurological diseases.
    CRC Press,  Inc.   Boca Raton, FL. 219 pp.
                                     30
-------
                                                                          833
Federal Working Group on Pest Management.   1974.  Occupational exposure to
    pesticides.  Report to the Federal Working Croup on Pest Management from
    the Task Group on Occupation Exposure  to  Pesticides.   155  pp.
Hayes, W. J.f  Jr.  1982.  Pesticides  studied in  man.   Williams & Wilkins,
    Baltimore/London.  455 pp.

KuhT| R. J.f  and H. W.  Dorough.   1977.   Carbamate insecticides:  chemistry,
    biochemistry and toxicology.  CRC Press,  Inc., Cleveland, OH.  301 pp.

Longbrake, TM R.  Roberts,  and S. Cotner.  1980.  Keys to fresh markert
    cucumber  production.   Texas  Agric.  Ext. Serv., Publ. No. L-1556.  4
    unnumbered  pp.

Texas Agricultural Extension Service.   1980.  Texas  guide  for controlling
    insects on commercial  vegetable  crops.  Publ. No.  B-1305.  28  pp.

Wagner, S. L.  1983.   Clinical  toxicology of acricultural chemicals.   Noyes
    Data Corporation,  Park Ridge,  NJ. 253 pp.

Zavaleta, A.  N.  1981.   Introduction - Mexican American health status:
    selected  topics from  the  borderlands.  Borderlands J. 4(1):  1-6.
                                      31
-------
                                                                         834
                                 Appendix C

                      Intralaboratory Quality Control

The tables and figures that follow in this section are  summaries  of the
recovery  of methomyl  from quality control  samples  for each substrate.
                                            32
-------
                                                  835
+ 3
+ 2
+ 1
0
-1
-2
-3

7 -


! 3 5 6 "
_ _
_
106.0
103.1
100.3
97.5
94.6
91.8
88.9
F^g. 1.   Normal probability  plot  of  patch  samples
(x = 97.46 + 2.84)  fortified with 100  UK methbmyl.
Numbers  represent individual samples.   Dashed line
represents expected recovery of fortified
concentrations (100 ug).
                            33
-------
                                                       836
+ 3
+ 2

+ 1

0
-1
-2
-3
.
.
4
1 "
1 5
2 6 89-
10
7
• «
1 664
1461

1258

1055
852
649
446
Fig.  2.  Normal probability plot  of  glove  samples
(x = 1055 + 203) fortified with 1000 ng  methomyl.
Numbers represent individual samples.  Dashed  line
represents expected recovery of fortified
concentrations (1000 ng)
                         34
-------
                                                      837
+ 5
+ 4
+ 3
+ 2
+ 1
  0
-1
-2
203.3
184.6
165.9
147.2
128.5
109.8
  91.1
  72.4
    Fie.  3.  Normal_probability plot  of hand wash
    towel samples  (x = 109.78 + 18.71) fortified with
    200 ug tnethomyl.  Numbers represent individual
    samples.  Dashed line represents  expected recovery
    of fortified concentrations (200  UR) .
                            35
-------
                                                                      838
Table Cl.  Recovery of methomyl in patches from quality control samples
fortified with 100 ug methomyl.
Sequence
1
2
3
4
5
6
7
Sample
Type
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Observed
Recovery (ug)
100.0
98.1
100.0
98.3
98.8
94.3
92.7
Percent
Recovery
100.0
98.1
100.0
98.3
98.8
94.3
92.7
                                      36
-------
                                                                      839

Table C2.  Chromatographic summary of Injection sequence for recovery  of
methomyl from gloves  fortified with 1000 ng methomyl.

3S33SS33S3338S3333333SS333SS=3333333=S33=833SS=S=3SS=33=3S33333=S333333=33SS=;B
                                                      Peak
               Sample!'    Observed       Peak       Retention     Percent
   Sequence     Type      Recovery {ng)    Area         Time        Recovery
0
1
2
3
4
5
6
7
8
9
10
Standard
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
1010
1205
1014
1003
1382
1194
1069
615
1076
1084
906
2273592
2710154
2280542
2256749
3107739
2686269
2403023
1382731
2418742
2438002
2036845
4.81
4.83
4.83
4.83
4.83
4.78
4.76
4.76
4.76
4.76
4.76
-
120.5
101.4
100.3
138.2
119.4
106.9
61.5
107.6
108.4
90.6
                            ================================================
     -'  Sequence for recovery of  1000  ng standard and quality control
         samples fortified with  1000  ng methomyl.
                                           37
-------
                                                                     840
Table  C3.  Recovery of methomyl in hand wash towels from  quality control
samples  fortified with 200 ug methomyl.
Sequence
1
2
3
4
Sample
Type
Q.C.
Q.C.
Q.C.
Q.C.
Observed
Recovery (ug)
90.7
133.0
99.4
116.0
Percent
Recovery
45.4
66.5
49.7
58.0
                                          38
-------
                                                              841
                            Appendix D
                             Methods

Dl  Extraction  of gauze patches for pesticides
02  Extraction  of gloves and hand wash towels  for pesticides
D3  High performance liquid chromatographic conditions  for
    detection of methomyl
                                      39
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                    Extraction of Gauze Patches

1.  Place one 4" X 4"  gauze  patch  In  a 500  ml  Erlenmeyer flask
    and add 150 ml s of methanol.
2.  Extract twice using a Burrell Wrist-Action Shaker set at #6.
3.  Collect to extracts and  dry  using Na2S04 and evaporate  to 5 mis.
4.  Take to chemist for the  addition  of  the internal standard.
                                    40
                                 Dl
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      Extraction of Gloves  and Hand  Wash  Towels  for Pesticides          843
1.  Cut gloves into approximately  1  inch  square  pieces.

2.  Place sample into 1000 ml  Erlenmeyer  flask and extract with
    methanol  (350 ml  portions) three times  on wrist-action
    shaker for 20, 15. and 15  minutes.

3.  Decant through glasswool  in funnel  into second 1000  ml Erlenmeyer
    flask.  Place sufficient  sodium  sulfate to absorb  any moisture in
    the extract.  Transfer to  round  bottom  evaporating flask.

4.  During second wrist-action extraction evaporate  samples  down  so
    second extraction will fit into  round bottom evaporating flask.

5.  Repeat for third extraction.

6.  Bring up to approximately  10 ml.

7.  Take to GC lab.
                                     41


                                D2
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         High Performance  Liquid  Chromatographic Conditions
                     for Detection  of Methomyl
Instrument -  Waters Liquid Chromatograph
Detector -  Model  440 at 254 nm
Column -  C18 Silica Gel - Waters
Mobil Phase •  25% Acetonitrile
               75% H20
Flow Rate -  1.0 ml/min
                                  42
                                 D3
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                                                 845
An Assessment of Exposure  of Turnip and
  Mustard Green Harvesters  to Phosdrin
        Research performed  by

        Texas Tech University
        San Benito, TX  78586

        April 1, 1986
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                                                                         846
In behalf of the  Texas  PHAP the undersigned has reviewed and approved the
report draft entitled "An Assessment of Exposure of Turnip Green  Harvesters to
Mevinphos."
                                                         Date
                                    11
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                              TABLE  OF CONTENTS                             °47
===-=ss==== = ====s= ===:s ============= === === ===== = = === === = = ========= = = ========= = =
Section                                                                   Page

ABSTRACT 	    1v
INTRODUCTION	     1
METHODS AND MATERIALS 	     7
     Study Site	     7
     Appl lea tion 	     8
     Weather 	     8
     Deposi tion 	     8
     Foliage 	     9
     Human Subj ects 	    10
     Gloves 	    11
     Gauze Patches 	    12
     Air Samples 	    12
     Analytical Methods 	    13
     Rec overi es	    13
RESULTS AND DISCUSSION	    16
FIGURES	    21
TABLES 	    32
ACKNOWLEDGEMENTS 	    50
LITERATURE CITED 	    51
APPENDICES	    55
     A.  Chromatographic Summaries
     B.  Additional Results
     C.  Analytical Methods
                                    111
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                                                                          848
      AN ASSESSMENT OF EXPOSURE OF  TURNIP  GREEN  HARVESTERS TO MEVINPHOS

                                   ABSTRACT
     Exposure of farmworkers to PhosdrinW 4EC  while harvesting turnips was
examined after an extended 10 day reentry  period in December of 1982.  Dermal
exposure was assessed through the measurement of residues of Phosdrin(R)
detected as cis-mevinphos on sampling devices, gloves, gauze  shirt patches,
and air sampling cartridges worn by the harvesters.   Residue levels  detected
in sampling devices were to be compared  to the concentrations of cis-mevinphos
detected in soil and  foliage throughout the 10 day period prior to reentry.
The half-life of PhosdrinW on  leaves and  soil  was estimated  to  be  0.53 to
1.10 days,  respectively.   Loss of Phosdrin(R) from soil  and leaves was
relatively rapid, reaching non-detectable  levels at the time  of reentry.   No
residues were detected in sampling devices worn by the workers.  This was
consistent with the loss of residues from  leaves and soil. Exposure of the
harvesters was negligible after the 10 day period as  indicated by the
detection of only trace levels of dimethyl phosphate (DMP) in  post  harvest
voids.  The absence of residues in  sampling devices associated with  workers
precluded any statistical comparison of  age or sex subsets of  workers.
                                    iv
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                                                               \           849
      AN ASSESSMENT  OF  EXPOSURE OF TURNIP GREEN HARVESTERS TO NEVINPHOS
                                INTRODUCTION

     A series of studies  on the effects of pesticides on youths employed In
agriculture was conducted by the National Pesticide Hazard Assessment Projects
with the cooperation of the U.S.  Environmental  Protection Agency  (EPA) and the
U.S. Department of Labor.  The studies were Intended to provide an assessment
of the exposure of  harvesters  to one  or more  pesticides used to protect crops
from damage by pests and  disease.  The accumulated data might be of value in
predicting  the level  of risk assumed  by adult and juvenile farmworkers while
harvesting  crops treated  with  the studied pesticides.
     The migrant streams of the western United  States are comprised mainly of
Spanish-speaking peoples.   Because of the predominantly Hispanic culture, the
Lower Rio Grande Valley (LRGV) of south Texas is home to one of the largest
migrant farmworker populations In the United  States.  During the period
September through May of most years,  the  region provides intermittent work
                            1
harvesting  a wide variety of fruits  and  vegetables.  In the Spring, as the
local  harvests near completion, the workers will  gradually depart to follow
harvests of many of the  same crops at progressively  more  northern latitudes.
Workers of the LRGV are the chief component of  the central migrant stream that
works the Great Plains and the  Midwest.  However,  many  migrant workers will
travel  directly to Florida  or California  to work  the coastal streams  northward.
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     The migrant worker may become exposed to pesticides throughout the year
                                                                               QCn
while engaged 1n agricultural activities.   The  effects on  health posed by
exposure to agricultural  chemicals is compounded by the health problems
associated with the migrant  hispanic population (Zavaleta, 1981 and
Bondy et al..  1976).  The health status of the migrant laborer might require
special attention when addressing occupational  exposure to pesticides.
Reentry Intervals may require accommodation to  the  health  considerations
associated with the migrant  worker population.  Because pesticides are applied
to virtually all  crops grown  in  the LRGV,  residues of the  pesticides may
represent a health hazard to  field workers either through  prolonged dermal
contact with leaves and fruit or through  Inhalation or  ingestion of
dislodgable residues.
     The commodities grown 3n this four-county region are  annually treated
with perhaps as much as  five  million  pounds of  pesticide products, or 25 to 35
percent of all the pesticides used in Texas.  Hidalgo County alone, probably
the most intensively farmed county in the  state, may receive as much as the
other three Valley counties combined.   Cotton and grains account for possibly
the greatest portion of this  usage.   However, these crops  require little
human contact during growth  or harvest.  On the other hand, citrus, many
vegetables, and some specialty crops  do require hand  labor and also require
considerable pesticide usage, occasionally during  harvest.
     The climate of the Lower Rio Grande Valley (LRGV)  has been classified as
                                                              3
humid desert.  Mid-day relative humidities average  61  percent at Brownsville
and decline to about 45-50  percent in Starr County to the west, while mean
annual rainfall ranges from  27  to 19 inches in the same direction (U.S
Weather Service, Brownsville, pers. comm.).   Summer temperatures frequently
exceed 100'F.  Ttiis climate could influence the formation  of oxons from
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organophosphate Insecticides.   Oxons are frequently noted as having some        Qr.
                                                                               OJl
Importance In poisoning incidents involving harvesters  in  arid parts in
California (Maddy and Edmiston, 1982).  The combination of both high
temperature and high humidity has been observed to promote degradation
(Eto,  1979).  Host farmworkers  in the  region are employed In the Fall  and
Spring.  During this period  humidity remains  relatively high and temperatures
are much lower.  The rate  of degradation of certain pesticides may be
subsequently lower than during the summer.
     Turnips are grown sparingly In the LRGV.  Turnips are a dual purpose crop
grown  for greens and vegetable roots (McCraw,  1979).  Planting should  be made
in the early spring or late fall.   Harvest is  usually performed  by hand,
before the weather gets hot.  The plants are low-growing with leaves attaining
heights of 14 to 16 Inches at harvest. Most workers harvest the crop on their
knees.  The  foliage  1s manually cut off at ground level.  After blemished
leaves are removed, bundles  of leaves  are  usually held against the chest and
tied together with string or light wire.   The  cutting,  sorting, and binding
procedures require a level of dexterity that prohibits most workkers from
wearing any kind of gloves, except on  the  coldest  of days.  This exposure plus
the extensive contact with foliage by the  chest and  forearms during binding
represent the greatest potential for the transfer and penetration of residues.
     Insect pressure on turnips may require treatment with malathion for
aphids, Sevln^ for flea  beetles,  a formulation of  Bacillus thuringiensis for
control of loopers and a pre-plant treatment of Diazinon(R) for control of
root maggots (McCraw,  1979).  Phosdrin^  was  not  listed by the  Texas
Agricultural  Extension Service (McCraw, 1979)  for control  of insect pests on
turnips.  However, commercial production of turnips may require treatment with
PhosdrinfR).
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     Phosdrin(R) 4EC 1s labeled for use on turnips grown as field or vegetable  «-
crops at the rate  of  1/4  to  1/2 pint per acre for control  of aphids  and  1/2 to
1 pint per acre for control  of cabbage worms, false chinch bugs,  leaf miners
(Diptera), grasshoppers, leaf hoppers and mites (Shell  Chemical
Company, 1982).  The harvest Interval  between last treatment and  reentry to
harvest Is 3 days  (Shell  Chemical  Company,  1982).
     PhosdrlnW 4EC  Is  an  emulslble liquid concentrate of 28.3*  mevlnphos
(Shell  Chemical Com pay.  1982)  consisting  of at least 60% of the alpha or cis
Isomeric form  (Hayes,  1982).  According  to  the nomenclature of Eto  (1979) the
cis-1somer Is beta mevlnphos and the  tran_s-i somer alpha mevlnphos.  The
geometry of  mevlnphos  previously  reported  by  Fukuto et al.  (1961) was viewed
by Eto (1979) as reversed.  The geometrical  isomers will be referred to as cis
or trans In this document.   The c1s-i somer  has  been  observed (Eto, 1979) to be
10-20 times more  Inhibitory to acetylcholinesterase (AChE) than the trans-
1 somer.  The cte-isomer Is  about  100 fold more  toxic  to Insects.
     Similar differences  in  activity between isomers can be addressed  to
degradation and metabolism of  mevinphos.  The half-life for alkaline
hydrolysis of cis-mevinphos  was reported  by Eto (1979) as  4.5 hours  (70° C,
pH 6.0).  The trans-isomer was more  rapidly hydrollzed  (3.7 hours, 70° C,
pH 6.0).  Hydrolysis of mevlnphos  in  aqueous solution appears to  be  pH
dependent (Hayes,  1982).  The half-life of hydrolysis of £ls-mevinphos and
trans-mevinphos at pH 11.0  (28° C) was 3.0  hours  and 1.8  hours, respectively.
Hydrolysis of trans-mevinphos  yields only dimethyl phosphate (Eto, 1979).
Two hydrolysis products may  be produced from ci_s-mevinphos, dimethylphosphate
and trans-phosdrln acid (Eto,  1979).   Under environmental  conditions,  light
energy (UV-1rrad1at1on) causes photo  isomerization of either Isomer  to a
mixture of 30 percent cis and  70  percent  trans  Isomers  (Eto, 1979).   Residues of
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Phosdrln(R)  (601 £l:s-mevinphos) on  foliage may be  expected  to  be  converted to
disproportionate concentrations of  trans-mevinphos.                           OjJ
     Metabolism of cls-mevinphos  occurs through  mlcrosomal  Induction In
mammalian hepatic systems to yield glutathlone sulfur conjugates (Eto,  1979)
and cis-desraethyl phosdrln (Morello et al.,  1968a).  The  trans-isomer Is
degraded by esterases at the vinyl  ester linkage (Hutson  et al.,  1972. Eto,
1979) to yield dimethyl phosphate (Morel lo et al.,  19685).   Mouse  liver
homogenates were able to degrade  trans-phosdrin  more rapidly than cis-phosdrin
(Morello et al.,  1968c).  The metabolites of both  Isomers are  excreted 1n
feces and urine (Casfda et al., 1958, Haley et al.,  1978).
     Mevlnphos Is an  organophosphorous compound of  high  oral  (3.7 - 6.1 mg/kg)
and dermal (4.5 mg/kg) mammalian  toxlclty (Merck Index, 1976).  The  Department
of Labor and EPA (Federal  Working Group on Pest Management, 1974) placed
mevlnphos In category I,  compounds with dermal LDso less  than  200 mg/kg.
Mevlnphos acts as an  Irreversible  Inhibitor of  red blood cell  (RBC)
chollnesterase (Hayes, 1982).   RBC  chollnesterase  activity  may be depressed
25% with 0.036 mg/kg/day  without  symptoms or reduction in plasma
cholinesterase activity (Hayes, 1982).  The primary symptom resulting from
exposure to mevlnphos was impairment in judgment  (Hayes, 1982).  Blurred
vision might be demonstrated as a consequence of contracted pupils (Hayes,
1982).   Symptoms, high fever and  abdominal  cramps, may be observed  up to 48
hours after contact (Hayes,  1982).  Numerous human poisoning cases  have been
reported which describe  the signs  of acute intoxication  (Abbadie et  al.,  1980,
Haley et al.,  1978,  and Hayes,  1982).  Mass poisoning of humans  from
consumption of greens contaminated with residues of mevlnphos  has been
reported (Murphy, 1975).
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     Because of the  small  difference  between oral  and  dermal  toxicity.
mevlnphos represents a compound of high risk to the occupatlonally exposed
(Federal  Working Group on Pest Management, 1974).   This study examined the
exposure of farmworkers harvesting turnips to a liquid formulation of
mevinphos, PhosdrinW 4EC.  The objective of the  study was to compare the
concentrations of residues of mevinphos on turnip foliage and soil  to the
accumulation of residues on  sampling  devices  worn  by farmworkers  while
harvesting.  The aim of the study was to relate the transfer of  residues from
soil and foliage to exposure of farmworkers  to Phosdrin'R' 4EC based on
concentrations of urinary metabolites.
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                                                                            855
                           METHODS AND MATERIALS
     The  two  Isomeric  forms of mevlnphos (2-carbomethoxy-l-methylvinyl
dimethyl  phosphate)  are  depicted below:
                          o
               H,C        C—OCHi              H,r        II
                  )c=c(                        ' <-<•'
         (CH,0),PO        II               (Cl!,0),l'o'      Xl--(K-H,
                                                )
                                                o         o
               cis-mevinphos                   trans-mevinphos
The NMR spectra melting point and stability of the isomers differ greatly
(Eto,  1979,  Hayes,  1982).  The melting point of cis-mevinphos is 210 c while
the melting point of the trans-isomer is  6.9° C (Hayes,  1982).   Phosdrin^
4EC, a restricted-use  product of  Shell Chemical Company bearing the EPA
Registration Number 201-289 (28.3% ci_s-mevi nphos,  18.8% related compounds,
47.9%  petroleum hydrocarbons and 5% inert ingredients),  was the formulation
studied.
     Study Site.  The  study site was  managed  by a  grower  that  raised a variety
of crops,  including citrus  and  several other  vegetables.  All the vegetables,
including  the  turnips,  were packed on the  farm.  An attempt was made to
minimize interference with ordinary growing practices.  Contact with the
grower was made only to remain  informed  of farm  practices.
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     The site was an irrigated, single 18 acre block of turnips.   The  field
measured approximately 110 m on the north side; 653 m on the east; 110 m on
the south; and 653 m on the west (Fig. 1).   The topography was  essentially
flat, with furrows running north-south.   The  soil is largely a  Willacy fine
sandy loam with a somewhat saline Racombes sandy clay loam portion on  the
eastern margin.
     Application.  No  previous  pesticide  use  history  for the site  was
obtained.  Phosdrin^ 4EC was  applied aerially at the  rate of  1/2 pint per
acre on  17 December 1982 (1500 hours).  The  aircraft was equipped  to cover a
20 row swath and deliver three  gallons  per acre of spray volume through 8000-6
nozzles  (at  35-40  psi).
     Weather.  The wind direction at the  time of application was not recorded.
The low  temperature for the day was 48"F  in  the morning and  the high
temperature of 75"F was reached shortly  after the time of application. The
prevailing weather for the next nine intervening  days  to harvest was
unremarkable.  High temperatures never exceeded 84 "F,  lows never  fell  below
50"F, nor was there any precipitation (Table 18).  However, on  the evening of
26 December a notherly cold front passed through the area, carried by  winds
gusting  to 20 mph.  These conditions remained through the date of harvest.
The cool temperature of the day of 47°F occurred as the workers were arriving
at the  field.  The high of 59"F was recorded in the afternoon,  about  four
hours after  harvesting had  ceased.
     Deposition.  Deposition of Phosdrin(R)  4EC was  measured on turnip
leaves and soil  after  application.   Soil  samples  were taken  from  five
locations within the  field (Fig. 1).   Soil  was scraped from  the surface  of
the field to a depth of 0.5 inches.   The  first samples (approximately  100 g  of
soil) were collected approximately  200 minutes after  the  application.
                                       8
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Subsequent samples were collected over an eight day period.  The samples



were placed in 120 cc polyethylene urine sample cups and put on dry ice for      857



transport to the laboratory.  On arrival at the laboratory, the samples were



catalogued and stored frozen for later analysis.



     A ten gram soil sample was placed in a narrow-mouthed Erlenmeyer flask



and extracted with acetone three times for 15 minutes with a Burrell wrist-



action shaker set on number six.  The three extracts were combined, dried



with sodium sulfate, filtered through Whatman No. 1 paper on a Buchner



funnel, and concentrated to 5 ml using a Buchi Rotovapor R110.  Adjustments



were made to the volume prior to analysis by QC.



     Foliage.  Deposition of mevinphos on foliage was measured by obtaining



20 leaf punches (100 cm2) from plants along selected rows (Fig. 2).  Samples



were collected prior to the entry of harvesters into the field.  Leaf



punches were obtained with a Birkstrand punch equipped to cut a 2.5 cm2



circle.  The punches were collected in resealable plastic bags and stored on



dry ice for transport to the laboratory.  On arrival, the samples were



catalogued and stored frozen until analysis.



     Samples were extracted using the method of Gunter et al.  (1974) for



measurement of dislodgable residues.  A 50 cm2 sample (10 punches x 2 sides



x 2.5 cm2) was placed in a 120 cc polyethylene urine specimen container to



which 3 drops of a 0.5 X dilution of Witconol NP-100 surfactant and 75 ml of



distilled water were added.  The samples were extracted three times for 15




minutes on a Burrell wrist action shaker set at speed six.  These extracts



were combined and transferred to a 1 liter separatory funnel and extracted




again three times with 400 ml hexane and 150 ml methylene chloride.  A



saturated 2 % solution of sodium sulfate in water was used to break up



emulsion.  Hexane was dried with anhydrous sodium sulfate and concentrated



                                     9
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with a Buchi Rotavapor R110 to 5 ml.  Final  evaporation  to  0.5 ml was done on  ocn
a Meyer N-Evap.   This volume  was  adjusted  to 5 ml with methanol.  Additional
volume adjustments were made prior to analysis by GC.
     Human Subjects.  The  transfer  of  residues on foliage and soil to workers
harvesting turnips was  studied on a population of hispanic  farmworkers.  These
workers were selected solely by the labor  contractor.  The  workers did not
have advanced notice of the study.   The  workers arrived  at  the  field at
approximately 0700.  After an explanation  of the work  proposed,  the volunteers
proceeded through a series of stations where they  signed consent forms,
received their numbered shirts, received their sampling  devices,  and
were briefly interviewed.  Owing to the disagreeable weather, all subjects
were wearing shoes, caps, jackets,  and long  pants,  in addition to the numbered
shirt provided.   The  sampling devices  worn was on a voluntary basis.  All
workers entered the field within  a  few minutes of 0800;  all workers completed
their harvest activities between 1045 and  1120.   The amount of work performed
was not obtained from the labor contractor.   Drinking water and  washing
facilities were provided but not utilized.
     Study subjects were also  required to  contribute urine  specimens  to  measure the
concentration of pesticide metabolites which might  result from  exposure  while
harvesting the crop.  Specimens were obtained from each subject. Portable
restrooms for both males and females were  provided. Samples were collected
before the subject started to work and as  they retired from the field.   They
were also asked to contribute their first  void the  following  morning.   Urine
samples were collected in  standard, plastic, four-ounce urine specimen
containers, and were placed directly on  dry  ice  for immediate transport to  the
laboratory.
                                      10
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                                                                        859
     The cohort consisted of 6 females and 11 males (Tables  1,2).  The average
age of the females was 20.5 _+ 12.0 years.   The youngest female was 11 years;
the oldest 40 years.  The ranks of the ages of the females were found to be
not s1gn1 flcantly different (T = 49.5, P > 0.20, n * 6, m = 11) from the males
according to  the Mann-Whitney test for two Independent samples (Conover,
1980).   The average age of the males  was  26.9 +_ 16.9 years.   The  youngest  male
was 8 years,  the oldest 55 years.  The closeness of age of the males  and
females was determined to be related  to the make up of the population as a
group of  families (Mollhagen et al.,  1985).  The uniformity of the age of the
population may be used to explain the lack of a significant  difference (T =
25, P > 0.20, n • 4. m  • 10) between the ranks of the weights of  the males and
the females.   The average weight of the females was 51.0 +_ 8.2 Kg; the average
weight  of the males was  62.6 _+ 27.2 Kg.   The transfer of residues may be
examined 1n relation  to the  pooled ages and weights of the workers with
effects partitioned by sex.
     Gloves.   Transfer of residues onto  the workers  was measured on sampling
devices (gloves,  arm patches  and air  samplers) worn by the workers (Fig.  3).
To estimate the amount of contact with pesticide residues through the hands,
9 subjects were recruited to wear a pair  of lightweight  100% cotton twill
work gloves with knit wristlets and seamless palms (Sears catalog number  51 K
25915).  The  average surface  area  of  three gloves (minus the  knit wristlet)
was  85.2  In2 ^ 1.29 (549.7 cm2).  After the exposure period,  the gloves were
sealed  in a plastic bag and  placed on dry ice.  The samples  were  catalogued
and stored 1n a freezer until analysis was started.
     The gloves were cut  Into 1  to 2  cm2  pieces (the knit wristlets were  not
tested) and placed in a 1.0  liter  Erlenmeyer  flask  and  extracted  three times
with methanol on a Burrell wrist-action shaker at setting 8,  The  pieces  were
                                     11
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                                                                        860
transferred to a Buchner funnel  and washed.  The extracts were combined,
filtered, and  concentrated  to  5  ml  with a Buchi  Rotavapor R110.  The volume
was adjusted as needed for analysis by GC.
     Gauze Patches.   To assess the  potential for pesticide contact and
absorption through the arms, gauze  exposure  patches  with surface  area  103.2
cm2 per patch were placed on 6 subjects, one on  each  forearm outside the
shirt (Fig.  3).  Workers  performed  their  normal  work activity  for 3.5  hours.
At the end of the day the patches were collected from the workers.  The
samples were  catalogued and stored in a freezer  until analysis.  Gauze patches
were extracted intact three times in a 500 ml  Erlenmeyer flask containing 75
ml methanol using a Burrell  wrist-action shaker  at setting 6.  The three
extracts were combined, filtered through Whatman No. 1 paper on a Buchner
funnel, dried with anhydrous sodium sulfate, and concentrated to 5 ml on a
Buchi Rotavapor R110.   Final  volume adjustment was made as needed prior to
analysis by GC.
     Air Samples.   Five of the subjects were fitted  with a DuPont P-4000
Personal Air Sampling Pump equipped with an  air  cartridge.  This was done to
assess the potential  for inhalation of airborne  residues.  In every case the
pumps were clipped to a military web belt and  the pump  positioned to ride at
the waist in  the  small of  the back  (Fig. 3).   This location caused very little
interference with worker movement.   The pumps  were set to draw 1  liter per
minute.  Calibration was done just  prior to  sampling  and  immediately upon
returning from the field.   The time  that the workers wore the pumps  was
documented in two ways.  First,  each pump had  a  device to report  running  time.
Second, these values  were compared  with the  notes on the times the pumps were
checked out and checked in.
                                     12
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                                                                            86 I
     The pumps were connected to the cartridges through  a 90 cm length of
quarter Inch (inside  diameter) tygon tubing.  The tubing was adapted to the 4
mm cartridge nipple.  The tubing from  the pump passed between an arm and the
torso and the cartridge was clipped to the  shirt collar. The trapping
cartridge was constructed of the barrel  section of  a 20  cc plastlpack
disposable syringe packed with 1.5  g Sepralyte  Octadecyl  C-18 100 urn silica
gel  and closed with  0.5 square  Inches of polyurethane.
     The exposed  cartridges were sealed  inside a  plastic bag and stored on dry
ice until transport to the laboratory  where they were catalogued and placed in
a freezer until  analysis.   Extraction of the residues from the entrapment
medium  was  accomplished by eluting 150 ml of acetone through the cartridge at
approximately 5 ml/min.  This solution was  dried with anhydrous sodium sulfate
and evaporated to 1 ml wi th a Buchi Roto vapor R110 and prepared for GC
analysis.
     Analytical  Methods.  Samples were analyzed for residues of mevinphos by
gas-liquid chromatography with a Tracor 222  gas chromatograph equipped with a
4.0% SE 30/6% 0V  210  column (flow rate  20 cc/min. 2000 c) and flame
photometric  detector (FPD) in  phosphorous mode.   Detection of mevinphos was
confirmed by two column analysis (10% DC 200, flow rate 50 cc/min, 165° c).
Mevinphos (PhosdrinCO) code 4640 as cj_s-mevinphos was used as the reference
standard.  The standard was obtained from the  U.S  EPA Pesticides  and
Industrial Chemicals Repository, U.S.  EPA Environmental  Research Center,
Research Triangle Park, NC 27711.   The standard was prepared in methanol as
100% cis-mevinphos.
     Recoveries.   Recovery of  added concentrations of mevinphos in the
substrates was examined to estimate precision, accuracy  and reproducibility of
methods of extraction and analysis.  The substrates were fortified with
                                     13
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                                                                           862
concentrations of mevinphos to reflect recovery of minimally detectable
levels.  A series  (n = 10) of 10 gram  soil samples were fortified with 150 ng
of mevinphos and compared to 150 ng/ml standards.   The mean recovery of the 10
samples  was  112.4 +_ 11.3 ng with  a  coefficient of variation of 10.0%.
Although recovery was less than expected (75%), observed  values were within
control.  Observed values were not  greater than two  standard deviations (Fig.
4).   The chromatographic summary  is provided  in Appendix A.
     Recovery of mevinphos from fortified (300 ng) gauze patches was improved
(86.7%) over  recovery  in soil  (75.0%).   The mean recovery of  10 samples was
260.2 +_ 30.2  ng with a coefficient of variation of 11.6%.   The improved
recovery of mevinphos from the patches was reflected in the more uniform
distribution of values  about  the  expected  line of recovery (Fig.  5).  This
level  of precision was attributed to the ease of extraction and the level  of
fortification (300 ng).   The chromatographic  summary is provided in
Appendix A.
     The mean  recovery of mevinphos from leaves fortified with 300 ng was
266.7^ 27.1  ng.  Values  were  well clustered  about the mean  (Fig. 6) as
indicated  by the coefficient  of variation  (10.1%).  The coefficient of
variation was consistent among substrates.  Greater percent recovery was
realized  for leaves  (89.0%) than  for soils  (75.0%)  or gauze patches (86.7%).
A summary of the chromatographic  sequence for leaves may be reviewed in
Appendix A.
     Recovery of fortified concentrations of cis-mevinphos  in  gloves was  99.0
percent  of expected (300 ng).   The mean recovery of cj[s-mevinphos was  297.0 +_
51.2 ng.  The  coefficient  of  variation (C.V.  = 17.2%) was greater than the
C.V. obtained for the  other substrates.   However,  individual sample values
                                      14
-------
                                                                             863
were within control (Fig. 7).  The chromatographic  summary is provided in
Appendix A.
     The average recovery of the  urinary metabolite of Phosdrin(R)
dimethyl phosphate (DMP) in urine samples fortified  with  0.25 ug/ml OMP was
0.22 +_ 0.02 ug/ml  or 88 percent.  Values were within control (Fig. 8)  with  a
coefficient of variation  of  8.93 percent.  The chroma tographic summary of the
injection sequence may be reviewed  in Appendix A.
                                     15
-------
                                                                       864
                            RESULTS AND DISCUSSION
     The disposition of  Phosdrin^ detected as cls-tnevlnphos was measured on
soil  and foliage.   Deposition was determined from soil and leaf samples
acquired immediately after application.  Decline or loss of residues was
estimated from samples  obtained over an extended period,  six days for leaves
and eight days for soil.
     Deposition of cis-mevinphos detected  in soil samples obtained from five
sites within the field was extremely variable (F1g.  1).  Concentrations ranged
from 44.0 ng/g at site 1 to non-detectable  or  zero levels at site 3.  Loss of
cis-mevinphos from soil  at site  1 was rapid over the eight day sampling period
(Table   ).  However, the decline in residue level did not follow a time
dependent trend.   The two-tailed  test  for trend using  Kendalls-tau  (Conover,
1980) was not significant (Hotel ling-Pabst T = 125, n = 8,  P > 0.20).  A
similar result, as expected, was obtained  for  site  3 (Hotelling-Pabst T = 135,
n  -  8,  P >  0.10).  The  greater value  for Hotelling-Pabst statistic  was
associated with  the number of zero ties (Table 4).   A lack of significant
trend (Hotelling-Pabst  T  =  113, n = 8,  P  > 0.20) was also observed  for site 5
(Table  5).
     Time dependent  trends were observed  for  sites  2  (Table  6) and  4 (Table
7). A highly  significant trend (Hotelling-Pabst T =  162,  n * 8,  P = 0.001) was
observed for  site 4.  The decline in residue concentrations  in soil  from site
2 appeared  to be time dependent (Hotelling-Pabst T = 147,  n = 8, P < 0.05).  A
plot of concentrations  of cis-mevinphos detected in soil from sites 2 and 4
                                     16
-------
against time (Fig.  9)  appeared  to  follow  first-order  kinetics.  The combined
samples revealed a significant time dependent trend (HotelHng-Pabst T  =  1205,
n = 16, P < 0.001).
     The data for each site were transformed (log scale)  to obtain estimates
of the half-life of Phosdrln^ residues  In  soil  over the interval 0.1 to 8
days post application.  A significant correlation (t = 3.582,  P  >  0.025) was
obtained between the log cjj-mevinphos concentration and  time (days)  for site
4 (Fig. 10).   A half-life of 1.01  days was  obtained from  the  slope of the
equation  (log (ng/g) = -0.2966 [log (ng/g) day ~1] + 1-51 days,  r =  -0.8483,
r2 = 0.7196).  The  mean residue level  was 0.653 +_ 0.723 ng/g with the mean
time of sampling 2.88 +_  2.07 days.
     Although the correlation was significant, the  half-life  and the linear
estimates of mean residue concentration and mean  time  were obtained  from an
equation with 28.04 percent of  the variability unaccounted for by the
regression.   Zweig et al. (1985) obtained  linear estimates and calculated half
life from equations with approximately 15.36  percent  of the variability
unaccounted for by the regression.  Estimates  of  half-life must be evaluated
according  to the variability in the regression.   The  correlation on  log cis-
mevinphos concentrations and time (days)  for site 2 was found  to be  not
significant (t * -1.196,  d1f.s  4,  P > 0.20).   Approximately  58.28 percent of
the variability  in  the equation log (ng/cm2) » -0.1095  [log (ng/cm2) days -1]
0.822 days,  r =  -0.6459,  r2 = 0.4172 was  unaccounted  for  by  the  regression.
A half-life could not  be  estimated with confidence  from the  equation.
     Deposition  and loss of Phosdrin(R) from foliage was  observed on the day
of application and  on  six subsequent days.  Leaf  punches  were  collected along
rows at different times over the six day period.  The  deposition of
           detected as ci_s-mevinphos  appeared to vary among rows (Fig. 2).
                                     17
-------
The lack of replicate  values  did not  allow  for  statistical evaluation of
                                                                             866
deposition among rows.  The highest concentration of ci^-mevinphos (0.37
ng/cm2) was detected in  leaf  punches  from row A, 19 meters from the west edge
of the field.  Except for a  slight rise in concentration (0.35 ng/cm2) jn ieaf
punches from row C, the deposition of Phosdrin^ appeared to decline from
west to east (Fig.  2).   A  test  of  trend  between residue  concentration and
distance from the west  edge of the field using Kendalls-tau  (Conover, 1980)
indicated a lack of trend (Hotel ling-Pabst T = 38, n =  5, P > 0.05).  The test
for trend was complicated by the  differences in the time of  sample collection
among  rows  (Table 8).   Leaf  punches  from row A were collected  206 minutes
after application while leaf punches  from  row  D were collected 20 minutes
later.  The time of sample collections may have contributed  to the
concentration differences among rows and represent a time dependent  loss of
residue.  However, the  test of trend  between residue concentrations  and  the
time  of sample collection was less ambiguous (HotelHng-Pabst T  = 36, n  =  5,  P
>  0.05) than the test for directional trend.
     The loss or decline of  residues  on  leaves  was  examined  more directly  by
row in relation  to  time of  sample collection.  Concentrations declined  rapidly
after  the  first day in  row A (Table 9).   A time dependent trend  was  not
indicated  (Hotelling-Pabst T -31, n  = 5,  P >  0.20).  Further analysis  for
trend  for  the additional 4 rows was  equally negative (Tables 10-13).  Although
residue levels declined rapidly to non-detectable levels, the detection of
concentrations greater  than  zero altered the apparent trend to zero  levels for
most rows.
     Treatment of  the data as  a single  population  revealed  a  significant trend
(HotelHng-Pabst T = 5265, n = 26, P < 0.001)  as evidence for a  decline of
mevinphos  concentrations.  A plot of positive values (Fig.  11) appeared to
                                      18
-------
                                                                             867
follow a first-order decay curve.  A test of trend for the positive values was
significant (Hotelling-Pabst T  = 288,  n  = 10,  P  <  0.02).   An estimate of the
rate of decline of phosdrin (kt «  1>33 ng/cm2  . day -1) was obtained from the
integral  of the first-order decay  curve  over the  period  of  positive values.
The half-life was estimated to be 0.53 days.   A  regression on the log
transformed data, although significant (t = -2.653, P  <  0.025), left only
46.81  percent of the variability  attributable  to the  equation  log (ng/cm2) = .
0.0831 [log (ng/cm2)  days'1] -  0.92 days.  An estimate of half-life based on
the regression was considered  inappropriate.
     Transfer of residues from soil  and foliage  to sampling devices, gloves,
arm patches, and air cartridges worn by workers  harvesting turnips was
examined to estimate the  level of exposure to PhosdMn^ 4EC.  Concentrations
of cis-mevinphos detected on the sampling devices  was compared  to  residues of
the metabolite dimethyl phosphate (DMP) detected  in urine  samples provided by
the workers during harvest.
     Farmworkers entered  the field 10 days after application and collection of
the last field samples.   Residue levels on  sampling devices were expected to
reflect the concentrations detected  in soil  and  foliage  on  the  final day of
field sampling.  Consistent with this  supposition, cis-mevinphos was not
detected in gloves, or air sample cartridges  (Tables 14,15).  The detection of
130 ng or 1.26  ng/cm2  In  arm  patches  worn by worker 20 (Table  15) was regarded
as a spurious anomaly.  The apparent  detection of  cis-mevinphos In  air
cartridges was ruled out by two column confirmation (see Appendix Bl).  Cis-
mevinphos detected by the SE 30/OY210 column could not be confirmed on DC-200.
Transfer of residues  to  sampling  devices appeared  to  reflect zero exposure in
accordance with the loss of residues from soil and foliage.
                                     19
-------
     The lack of transfer was substantiated by the detection of trace levels
of dimethyl phosphate (DMP) in urine samples of the  harvesters  (Tables  16,17).
These concentrations were lower than clinically important levels of DMP, 0.4
ppm in cases of moderate poisoning with mevinphos and 2.0 ppm in  a  more severe
case (Hayes,  1982).   The  formation of  DMP occurs  as  a result of esterase
activity on the p-o-v1nyl bond of trans-mevinphos (Eto,  1979,  Hut son et al.,
1972).   The cis-isomer may be degraded to cis-desmethyl  phosdrin and S-methyl
glutathione (Morello et  al.,  1968c, Beynon et al.,  1973).  Assessments  of
exposure to phosdrin based strictly on the measurement of  DMP in urine  may
underestimate the extent of exposure.   Moreover, DMP is  a  metabolite of a
variety of organophosphorous compounds (Eto, 1979).   Detection  of low levels
of DMP may be a consequence of Incidental exposure to organophosphorous
compounds  used outside the workplace.  The trace levels of DMP detected in  the
urine of the workers after harvest (Tables 16,17)  may have occurred from
incidental exposure  rather than from occupational exposure to phosdrin.
                                      20
-------
                          44.00
K>
8.67
                                         1.29
                                                  13.50
                     south edge  of  field
                            (110 m)
            Fig.  1.  Deposition of Phosdrin(R) 4EC detected as  cis-mevinphos  (ng/g)
            in soil samples collected from sites within a turnip  field following
            aerial application of Phosdrin(R) 4EC (0.5 pint per acre) on 17
            December 1982 at 1500 hours.
                                                                                      00
                                                                                      ON
-------
NJ

-------
                                                          871
                     Air Pump
                                Subject Number
Fig. 3.  Positions of sampling devices  (air  pumps,
body patches and gloves) worn by workers  harvesting
turnips treated with a formulation (PhosdrinW 4EC)
of mevinphos.
                      23
-------
                                                          872
+ 4
4- Q
T «3
+ 2

+ 1
0

-1

-2
-3
-4
- -
- -

~" 2 ~
1
5 6
-3
A 1O
4 89
7
^^ ^
X=112.4±11.3
Mevinphos
157.6
1A C O
4o.3
135.0

123.7
1 12.4

101.1

89.8
78.5
67.2
Fig. 4.  Normal probability plot of soil samples fortified
with 150 ng mevinphos.   Numbers represent individual samples
Dashed line represents expected recovery of fortified
concentrations (150 ng).
                         24
-------
                                                 873
+ 4
+ 3
+ 2
+ 1
1
0

-1
-2
-3
-4

.
6 -

-3
8
2 4
1 579
1
10 _
X = 260.2±30.2
Mevinphos
                                              381.0
                                              350.8
                                              320.6
                                              290.4
                                              260.2
                                              230.0
                                              199.8
                                              169.6
                                              139.4
Fig.  5.  Normal probability plot of  arm patch  samples
fortified with 300 ng mevinphos.  Numbers represent
individual samples.  Dashed line represents expected
recovery of fortified concentrations (300 ng).
                       25
-------
                                                      874
+ 4
+ 3
+ 2
+ -\
1
0

-1
-2
-3
-4
_
^ ^
10 _

^B
5 9
2 3 a
J 4 6 8
1
7
X = 266.7±27.1
Mevinphos
375.1
348.0
320.9
2Q Q Q
%J O . O
266.7

239.6
212.5
185.4
158.3
Fig. 6.  Normal probability plot of leaf punch  samples
fortified with 300 ng mevinphos.  Numbers represent
individual samples.  Dashed line represents  expected
recovery of fortified concentrations (300 ng).
                         26
-------
                                               875
+ 4
+ 3
+ 2
+ 1
o
^^
«f
— 1
-2
-3
-4

^^

1 6
	 9
4
5 7
23 8
_
X = 297.0±51.2
Mevinphos
                                          501.8
                                          450.6
                                          399.4
                                          348.2
                                          297.0
                                          245.8
                                          194.6
                                          143.4
                                            92.2
Fig. 7.  Normal probability plot of glove samples
fortified with 300 ng mevinphos.   Numbers represent
individual samples.  Dashed line represents expected
recovery of fortified concentrations (300 ng).
                    27
-------
                                                        876
+ 4
+ 3
+ 2

+ ••
1
0
-1
-2
-3

-4


«• ^K

5 7
V
— —
6
- 1 3
2
4 9 -
8 9
— _
— _
X = 0.224±0.02

DMP
0.304
0.284
0.264

OO >I A
.244
0.224
0.204
0.1S4
0. 1 64

0. 144

Fig. 8.  Normal probability plot of urine samples
fortified with 0.25 ug/ml dimethylphosphate (DMP).
Numbers represent individual samples.   Dashed line
represents expected recovery of fortified concentrations
(0'.25 ug/ml).
                       28
-------
             15.0
NJ

12.0
•"•N
0)
*%,
£? 9.0
»^x
CO
0 6.0
d
c
^
£^
0
4
_

2
4
2
2
4
2 4
4 2
4 4
2 2 2 4
I I I I I I I I
                       0     1.0    2.0   3.0    4.0    5.0   6.0    7.0

                                           Days

          Fig. 9.  Decline  or  loss of residues  of Phosdrin(R)  detected as cis-mevinphos
          in soil samples collected from sites  2 and 4 within  a  turnip field treated
          with an aerial application of Phosdrin(R) 4EC at the rate of 0.5 pint per
          acre (17 December 1982, 1500 hours).
-------
OJ
O

1





O)
*>,
O)
c
CO
0

Q.
C

^
0
E

CO
• •m
O





0

9

8
7
6

5

4

3




2





1




.0

.0

.0
.0
.0

.0

.0

.0




.0





.0


• \
\

\
~ \
»
\
\
\
\
\
\
* \
v •
~ \
• \
\
\
\
\
\


\
^
.
\ •
i j j i > it
0.1 1.0 2.0 3.0 4.0 5.0 6.0
                              Days  after  application
         Fig.  10.  Semilogarithmic  display of residue levels of cis-mevinphos
         detected in soil from site 4  to estimate rate of decline or loss  and
         the half-life of PhosdrinW  in soil after application of Phosdrin(R)  4EC
         at the rate of 0.5 pint per acre (17 December 1982, 1500 hours).
OO
-->j
00
-------
«•• s
N
^
"^
G)
*-s
CO
O
C
a
c
-------
Table 1.  Physical  characteristics  of  female             880
workers involved in harvesting  turnips after
application of Phosdrin^J  4EC.
                 Physical  Characteristics!/
Worker
Number
9
34
38
39
42
44
Age
31
14
11
14
13
40
Weight (Kg)
0»
50 (110)
40 (87)
-
55 (121)
59 (130)
£/ Weight in kilograms.  Values enclosed
   are pounds.
                     32
-------
                                                         8C
Table 2.  Physical  characteristics of male
workers Involved 1n harvesting  turnips after
application of Phosdrin^*'  4EC.
Worker
Number
2
5
14
19
20
31
32
47
50
52
55
Physical Characteristics!/
Age
53
36
16
13
12
8
10
55
35
24
34
Weight (Kg)
88 (193)
109 (240)
-
52 (114)
43 (94)
25 (55)
29 (63)
89 (196)
69 (152)
68 (149)
54 (118)
5  Weight in kilograms.  Values  enclosed
   are pounds.
                      33
-------
                                                               882
     Table 3.   Deposition and loss of mevinphos  detected  as cis-
mevinphos in soil collected from Site 1  (Fig.  1)  following aerial
application of Phosdrin(R) 4EC at 0.5 pint  per acre.
TIME POST /
Hours
3
35
74
117
152
191
230
269
APPLICATION
Days
0.13
1.45
3.08
4.88
6.33
7.96
9.58
11.21
ng/g
cis -mevinphos
44.00
0.00
3.77
2.25
0.62
0.00
0.00
1.17
                                   34
-------
                                                              883
     Table 4.   Deposition  and  loss of mevinphos detected as cis- •
mevinphos in soil  collected  from  Site 3  (Fig. 1) following aerial
application of Phosdrin(R) 4EC at 0.5 pint per acre.
TIME POST /
Hours
3
35
74
117
152
191
230
269
APPLICATION
Days
0.13
1.45
3.08
4.88
6.33
7.96
9.58
11.21
ng/g
cis-mevinphos
0.00
0.00
0.00
0.81
0.00
0.00
0.00
1.17
                                   35
-------
                                                          884
     Table 5.   Deposition and loss  of  mevinphos detected as cis-
mevinphos in soil collected from Site  5  (Fig.  1)  following aerial
application of Phosdrin(R)  4EC at 0.5  pint  per acre.
TIME POST t
Hours
3
35
74
117
152
191
230
269
APPLICATION
Days
0.13
1.45
3.08
4.88
6.33
7.96
9.58
11.21
ng/g
cis-mevinphos
1.29
17.10
3.65
0.00
0.27
1.87
0.38
1.86
                                   36
-------
                                                             885
     Table 6.   Deposition  and  loss  of mevinphos detected as cia-
mevinphos in soil  collected  from  Site 2  (Fig.  1) following aerial
application of Phosdrin(R) 4EC at 0.5 pint per acre.
TIME POST APPLICATION
Hours Days
3
35
74
117
152
191
230
269
0.13
1.45
3.08
4.88
6.33
7.96
9.58
11.21
ng/g
cis-mevinphos
8.67
5.95
3.33
4.46
0.00
0.51
0.00
2.82
                                   37
-------
                                                       886
     Table 7.   Deposition and loss  of  mevinphos detected as cis-
mevinphos in soil collected from Site  4  (Fig.  1) following aerial
application of Phosdrin(R)  4EC at 0.5  pint per acre.
TIME POST ;
Hours
3
35
74
117
152
191
230
269
APPLICATION
Days
0.13
1.45
3.08
4.88
6.33
7.96
9.58
11.21
ng/g
cis-mevinphos
13.50
7.71
2.71
3.74
3.37
1.11
0.95
0.00
                                   38
-------
                                                                         887

Table  8.   Concentrations of PhosdrinW detected as cis-mevinphos in leaf
punches collected  from rows on the first  day  of application.

s=====a====s===================================================================
Distance (m)
from west
Row edge of field
A 19
B 38
C 57
D 76
E 95
Time of
sample
collection
206
213
219
226
225
Mevinphos
concentration
( ng/cm2 )
0.37
0.23
0.35
0.16
0.13
=======
                                      39
-------
Table 9.  Deposition and loss of Phosdrin(R) detected as cis-mevinphos
(ng/cm2) on  leaf  punches collected  from row A (19 m from "welt edge of field)
following aerial  application of PhosdrinW 4EC (0.5  pints per  acre).

a==s=====x»=r=================================================================5

                  Post application time           Residue concentration
                Hours               Days          £|s-Mevinphos (ng/ai)2)
3
36
74
152
192
0.1
0.9
1.8
3.8
4.8
0.37
0.00
0.17
0.00
0.00
==============================================================================
                                     40
-------
                                                                    889
Table 10.   Deposition and  loss of  Phosdrin(R) detected  as  cis-mevinphos
(ng/cm^) on leaf punches collected  from row B (38  m from west edge of  field)
following aerial application of PhosdrinM  4EC (0.5 pints per acre).
                  Post application time           Residue concentration
Hours
4
37
75
117
192
Days
0.1
0.9
1.9
2.9
4.8
CJ£-Mev1nphos (ng/an.2)
0.23
0.24
0.16
0.00
0.00
                                    41
-------
                                                                      890
Table 11.   Deposition and loss of Phosdrin(R) detected as cis-mevinphos
(ng/cm2) on leaf punches collected from row C (57 m from WeTl edge of field)
following aerial application  of  Phosdrin
-------
                                                                         891
Table 12.   Deposition and loss of Phosdrin(R)  detected as ds-mevinphos
(ng/cm2) on leaf punches collected from row D  (76 m  from  west  edge of  field)
following aerial application of  PhosdrlnM 4EC  (0.5 pints per acre).
Post application  time
                                                 Residue concentration
Hours
4
37
76
117
192
sssssssssssssssaarasas:
Days
0.1
0.9
1.9
2.9
4.8
sss=s=====ss==s=a=====3:
£1s-Mev1nphos (ng/cm2)
0.16
0.00
0.00
0.00
0.10
= = r = = = = =====£ = r== === = - = ====::==r = s
                                   43
-------
                                                                      892

Table 13.  Deposition and loss of Phosdrin(R)  detected as cis-mevinphos
(ng/cm2) on leaf punches collected from  row E  (95 m  from West  edge of  field)
following aerial application of  PhosdrimR) 4EC  (0.5 pints per acre).
                  Post application time           Residue  concentration
Hours
4
37
76
117
153
192
Days
0.1
0.9
1.9
2.9
3.8
4.8
Cis-Mevinphos
0.13
0.00
0.00
0.00
0.00
0.00
(ng/on2)






 S3=3==3S==S============3S=============================S=3C==S==S==============
-------
                                                                     '      893
Table 14.   Residue concentrations of c_is_-mevinphos on sampling devices (arm
patches, gloves,  and air samplers) worn by female workers involved in
harvesting turnips after application of Phosdrin(R' 4EC.
                    •              Residue  Concentration

                                     Cis-Mevinphos (ng)

         Worker
         Number         Arm patch         Gloves         Air sampler


           9              0.00             0.00

          34              0.00

          38              0.00             0.00

          39              0.00

          42              0.00             0.00

          44              0.00              -              0.00
                                     45
-------
                                                                        894
Table 15.  Residue concentrations of ds-mev1nphos  on  sampling  devices (arm
patches, gloves,  and air samplers) worn by male workers Involved  In
harvesting turnips after application of Phosdr1n(R) 4EC.
                                  Residue Concentration

                                    C1s-Mev1nphos (ng)
Worker
Number
2
5
14
19
20
31
32
47
50
52
55
Arm patch
0.00
0.00
0.00
0.00
130.00
0.00
0.00
0.00
0.00
0.00
_
Gloves
0.00
0.00
0.00
-
-
-
0.00
0.00
0.00
-
_
A1r sampler
-
-
-
0.00
-
-
-
-
0.00
0.00
0.00
                                      46
-------
                                                                        895
Table 16.   Urinary metabolite, dimethyl phosphate (ug/ml) detected in urines
collected from six female workers while harvesting turnips treated with
PhosdrinlR) 4EC.  FMV  =  first morning void (0530-0700).
                         Day of         Time of
Worker      Void          Void           Void       Urinary Metabolite  (ug/ml)
Number      Number     Collection     Collection    Dimethyl phosphate  (DMP)


  91            1            1030               0.00
              2            2            FMV                0.01

 34           1            1            0800               0.00
              2            1            1100               0.02
              3            2            FMV                0.00

 38           1            1            0800               0.00
              2            2            FMV                0.00

 39           1            1            0800               0.01
              2            1            1100               0.01
              3            2            FMV                0.07

 42           1            1            0800               0.00
              2            1            1110               0.00

 44           1            1            0800               0.00
              2            1            1105               0.00
              3            2            FMV                0.01
                                     47
-------
                      896
Table 17. Urinary metabolite, dimethyl phosphate (ug/ml) detected in urines
collected from eleven male workers while harvesting turnips treated with
PhosdrinlR) 4EC. FMV = first morning void (0530-0700).
SSSSS5«*v_2SSSS5SSSSSSSS5S55SSSS3!SSSZSSS3
Day of
Worker Void Void
Number Number Collection
2


5

14

19

20

31


32

47

50

52

55

1
2
3
1
2
1
2
1
2
3
1
2
3
1
2
3
1
2
3
1
2
1
2
1
2
1
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
2
1
1
2
1
1
1
1
1
1
1
1
Time of
Void
Collection
0800
1100
FMV
0800
1045
0800
1100
0800
1045
FMV
0800
1045
FMV
0800
1100
FMV
0800
1105
FMV
0800
1100
0800
1105
0800
1100
0800
1120
Urinary Metabolite (ug/ml)
Dimethyl phosphate (DMP)
0.00
0.00
0.00
0.01
0.00
0.02
0.00
0.00
0.00
0.01
0.00
0.00
0.01
0.00
0.01
0.01
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
-
48
-------
                                                                         897
     Table 18.  Temperature extremes at the study site between the date of
application (17 December) of mevinphos and the date of harvest of turnip
greens (27 December).
        Day              Maximum              Minimum
  (December 1982)     Temperature (°F)     Temperature (°F)     Rainfall (in)
17 75
18 78
19 80
20 74
21 79
22 81
23 82
24 84
25 84
26 77
27 59
48
57
51
50
59
60
64
69
65
51
47
                                    49
-------
                                                                    898
                              ACKNOWLEDGEMENTS

     A number of persons contributed materially to the work described  above,
in either  the planning of the project, doing fieldwork, analyzing samples,
testing the  data, or  preparation of the report.  These are:  N. Cano,  Jr.,
M. A.  Garcia,  M. E. Garcia, R. L. Garcia,  K. J. Huxford, A.  Iglesias,  Jr.,
N. J. Magouirk, A. Martinez, and A. G. Navarro.
                                    50
-------
                                                                     899
                              LITERATURE CITED

Abbadie,  D., M. Colle, J. Battln.  1980.   Intoxication by organophosphorous
     Insecticides. A case  history of a 2 year old Infant. Pedlatrle 35(6):
     545-552.

Beynon,  K.  I., D. H.  Hutson,  and  A.  N.  Wright.  1973.  The  metabolism  and
     degradation  of vinyl phosphate insecticides in Residue Reviews.  SpMnger-
     Verlag, New York.

Bondy, M. K., R. H. Lebow, M. O'Malley, T. Reilly.  1976.  Occupational  health
     and safety for agricultural workers. DHEW  (NIOSH) Publ.  No.  77-150.
     Washington,  D.C.

Casida,  J. E., P. E. Gatterdam, J. B. Knaak,  R.  D. Lance, and R. P.
     Niedermeier.   1958.  Bovine metabolism of organophosphorous insecticides.
     Subacute feeding studies  with 0,0-dimethyl 1-carbomethoxy-l-propen-l-yl
     phosphate.  J. Agr. Food  Chem. 6:658-662.

Conover, W. J.  1980.  Practical nonparametric statistics,  2ed.  John Wiley 4
     Sons, New York.

Eto, M.  1979.  Organophosphorus pesticides: organic and biological  chemistry.
     CRC Press, Inc., Boca  Raton, FL.
                                     51
-------
                                                                            900
Federal  Working Group on Pest  Management.  1974.  Occupational exposure to
     pesticides.   Report to the Federal  Working Group on Pest Management from
     the Task  Group on Occupation Exposure to Pesticides.   155 pp.
Fukuto, T. R..  E. 0. Horning, R. L. Metcalf, and M. Y. Winston.  1961.  The
     configuration  of the alpha and beta isomers of methyl  3-
     (dimethoxyphosphinyloxy)crotonate  (Phosdrin(R)).   j. Org. Chem. 26:
     4620.

Gunther,  F. A., J. H. Barkley, and W. E.  Westlake.  1974.  Worker environment
     research.  II.  Sampling and processing  techniques  for determining
     dislodgable pesticide residues on leaf surfaces.  Bull. Env. Cont. Tox.
     12(6):641-644.

Haley, T. J., E. R.  Reichert, and H. W. Klemmer.  1978.  Acute human poisoning
     with parathion and mevinphos.   Fed.  Proc.  Fed. Am. Soc. Exp.  Blol.  37(3):
     247.

Hayes, W. J.,  Jr.  1982.   Pesticides studies in man.  Williams & Wilkins,
     Baltimore/London.  455 pp.

Hutson,  D. H.,  B. A. Pickering and C. Donninger.  1972.  Phosphoric acid
      triester-glutathione  alkyltransferase. A  mechanism for the
     detoxification of dimethyl phosphate trlesters.   Blochem.  J.  127:285-293.
                                     52
-------
                                                                   .     901
Maddy, K. T., and  S. C. Edminston.  1982.   Pesticide  safety program of the
     California Department of Food and Agriculture based upon measurements of
     potential  workplace exposure and the elimination of excess exposures.  lr±
     J.  R.  Plimmer, ed.,   ACS  Symposium Series,  No.  182., American Chemical
     Society, Washington, DC.

McCraw,  B.  D.   1979.   Easy gardening...turnips and mustards.  Texas
     Agricultural  Extension Service.   Publ.  No.  L-1589.  4  unnumbered pp.

Merck Index.  1976.  Ninth Ed.  Merck & Co., Inc., Rahway,  N.J.

Mollhagen, T.,  C. C. Dary, A.  Guillen, Jr.,  and  V. F. Cox.  1985.  An
     assessment of cucumber harvesters to methomyl.  Draft submitted to U.S.
     Environmental Protection  Agency, Washington, DC.

Morel lo, A., A.  Vardanis, and  E.  Y. Spencer.  1968a.   Comparative metabolism
     of two vinyl  phosphorothionate isomers  (Thiono  Phosdrin) by the mouse and
     the fly.  Biochem. Pharmacol. 17:1795-1802.

Morello, A., A.  Vardanis, and  E. Y. Spencer.   1968b.   The role of gl utathione
     in the detoxification of  some dimethyl  vinyl organophosphorus compounds.
     Abstracts  155th Meeting American Chemical Society,  San Francisco, April
     1-5, A-51.

Morello, A,, A.  Vardanis, and  E.  Y. Spencer.  1968c.   Mechanism  of
     detoxication  of some organophosphorous  compounds: The  role  of glutathione-
     dependent  demethylation.   Can. J.  Biochem.  46:885-892.
                                     53
-------
                                                                            902
Murphy, S.  D.   1975.  Pesticides 1n toxicology, the basic science of poisons.
     Macmlllan Publishing Co.,  Inc., New York. 768 pp.

Shell Chemical Company, Agricultural  Chemicals.   1982.   Label: Phosdrin(R)
     4EC Insecticide.   Houston, TX.

Zavaleta,  A. N.  1981.  Introduction -  Mexican American health status:
     selected  topics  from the borderlands.  Borderlands J.  4(l):l-6.

Zweig, G., R.  Gao, J. M. Witt,  W. J. Popendorf, and K. T. Bogen.  1985.
     Exposure  of strawberry harvesters to carbaryl  in  Dermal  Exposure Related
     to Pesticide  Use.   American Chemical Society, Washington, D.C.
                                     54
-------
                                                                          903
                                 Appendix A


                         Chromatographic Summaries

The tables  that follow  In this section are summaries  of the chroma tographic
sequence of injected standards for autocalibration and the companion quality
controls for each substrate.
                                           55
-------
                                                                            904
Table Al. Chromatographlc summary of Injection sequence  for recovery of
mevlnphos from soil  samples  (10 g) fortified with 150 ng cis-mevinphos.
ssss=s==s==
Sequence
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
================
Sample!/
Type
Standard
Blank
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
Observed
Recovery (nc
148.0
1.96
126.0
133.0
168.0
112.0
106.0
113.0
160.0
122.0
98.0
103.0
154.0
103.0
108.0
Peak
)) Area
222831
2913
187574
197564
249177
185420
175610
188086
265169
215895
172839
182116
272427
187228
196458
:==========:
Peak
Retention
Time
1.62
1.60
1.63
1.63
1.62
1.63
1.65
1.62
1.62
1.63
1.63
1.62
1.62
1.63
1.65
t===== =========
Percent
Recovery
-
-
84.0
88.7
-
74.7
70.7
75.3
-
81.3
65.3
68.7
-
68.7
72.0
     —'  Sequence for recovery  of  150 ng standard, blank,  and  quality control
         samples fortified with 150 ng autocalibration on  150  ng standard.
                                          56
-------
                                                                      904
Table A2.  Chromatographlc  summary of injection  sequence for recovery of
mevinphos from gauze patches (100 cm2)  fortified with 300 ng cis-mevinphos.
==================
                    :==============================s========================;
                                                        Peak
               Sample!/        Observed      Peak      Retention   Percent
   Sequence     Type         Recovery  (ng)   Area        Time      Recovery
1
2
3
4
5
6
7
8
9
10
11
Standard
Blank
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
-
0.0
245.0
258.0
288.0
262.0
250.0
319.0
250.0
276.0
250.0
255594
-
208645
219899
245055
223096
212809
220927
213310
235265
212699
1.73
-
1.78
1.78
1.78
1.77
1.73
1.75
1.77
1.73
1.75
-
-
81.7
86.0
96.0
87.3
83.3
106.0
83.3
92.0
83.3
     —'  Sequence for recovery of 300 ng  standard, blank, and quality control
         samples fortified with 300 ng cis-mevinphos.
                                          57
-------
                                                                         905
Table A3.  Chromatographlc summary of injection sequence for recovery of
mevinphos from gloves (549.7 cm2) fortified  with  300 ng  cis-mevinphos.
Sequence
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Samp lei/
Type
Standard
Autocal
Autocal
Straight Spike
Blank
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
Q.C.
Q.C.
Q.C.
Observed
Recovery (ng)
-
-
-
-
368.0
247.0
352.0
249.0
287.0
323.0
272.0
379.0
265.0
250.0
301.0
Peak
Area
91362
70943
557674
-
228144
152983
654864
181338
208885
704913
212902
297094
207533
588712
709293
Peak
Retention
Time
3.37
3.37
3.35
-
3.38
3.40
3.37
3.40
3.43
3.33
3.40
3.38
3.40
3.52
3.37
Percentb/
Recovery
-
-
-
-
122.7
82.3
-
83.0
95.7
-
90.7
126.3
88.3
83.3
100.3
     a/  Sequence for recovery  of 300 ng standard, blank,  straight  spike, and
         quality control  samples fortified with 300 ng cis-mevinphos.

     ]>/  Percent recovery based on straight spike (Peak area  « 557674) used as
         standard.
                                        58
-------
                                                                       906
Table A4. Chromatographic summary of injection sequence for recovery of
mevinphos from leaf samples (50 cm2)  fortified with 300 ng cvs-mevinphos.
Sample!/
Sequence Type
1
2
3
4
5
6
7
8
9
10
11
Standard
Autocal
Straight
Spike
Blank
Q.C.
Q.C.
Autocal
Autocal
Autocal
Q.C.
Q.C.
Observed Peak 1
Recovery (ng) Area
-
345.0
254.0
0.0
206.0
227.0
234.0
385.0
304.0
219.0
218.0
226029
260045
219837
-
178639
197462
202806
260336
263588
192606
191548
Percent^/
Recovery
Peak
Retention
Time Autocal Straight Spike
1.65
1.65
1.65
-
1.67 68.7
1.67 75.7
1.67
1.67
1.67
1.67 73.0
1.68 72.7
-
-
-
-
81.3
89.7
-
-
-
87.7
87.0
                                     59
-------
Table A4.   (Cont.)
907
Sample^-/ Observed Peak 1
Sequence Type Recovery (ng) Area
12
13
14
15
16
17
18
19
20
21
Q.C.
Autocal
Autocal
Q.C.
Autocal
Autocal
Q.C.
Q.C.
Q.C.
Q.C.
235.0
244.0
277.0
215.0
468.0
291.0
288.0
324.0
224.0
246.0
206826
213966
197218
189094
411575
398708
382601
430637
297404
327278
Percent^/
Recovery
Peak
Retention
Time Autocal Straight Spike
1.67 78.3 94.0
1.67
1.67
1.68 71.2 86.0
1.6b
1.65
1.65 96.0
1.67 108.0
1.63 74.7
1.65 82.0
     a./  Sequence for recovery of  300  ng standard, blank, straight  spike,
         and quality control  samples fortified with 300 ng cis-mevinphos.

     W  Percent recovery based on autocalibration and straight spike
         (Peak area = 219837) used as  standard.
                                       60
-------
                                                                      908
Table A5.  Chromatographic summary of  injection sequence for recovery of
dimethyl phosphate (DMP)  from urine samples fortified with 0.25  ug/ml DMP.
Sample3./ Observed Peak
Sequence Type Recovery (ug/ml ) Area
1
2
3
4
5
6
7
8
9
10
11
12
13
Standard
Autocal
Q.C.
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
Q.C.
Q.C.
Autocal
Q.C.
Q.C.
0.229
0.257
0.220
0.214
0.225
0.245
0.204
0.260
0.236
0.256
0.246
0.199
0.202
337433
346448
304654
296536
311605
339299
277315
352994
320959
335202
327867
260707
265265
Peak
Retention Percent
Time Recovery
2.53
2.53
2.53
2.53
2.53
2.52
2.53
2.53
2.53
2.53
2.52
2.53
2.53
-
-
88.0
85.6
90.0
-
81.6
104.0
94.4
102.4
-
79.6
80.8
     1(  Sequence for recovery of 0.25 ug/ml standard and quality  control
         samples fortified with 0.25 ug/ml autocalibration on 0.25 ug/ml
         standard.
                                            61
-------
                                                                           909

                                Appendix B


                             Additional Results

The tables that follow 1n this section  are additional  results which may be
useful  1n drawing conclusions about Information presented 1n the  text.
                                         62
-------
                                                                    910
Table Bl.  Confirmation of cis-mevinphos  in air cartridges by two column
method.

===r3=========================================================================

                                        Column Type
                         10%  OC200
SE 30/0V210
Peak
Area
Sample
2 27772
5 19042
6 18076
Autocal 398997
Autocal 410806
Peak
Retention
Time
3.68
3.72
3.70
3.52
3.52
Peak
Area
31193
70666
58128
135721
117235
Peak
Retention
Time
0.67
0.67
0.67
0.62
0.62
-------
                                                                          911
Table B2.  Residue concentrations  of cis-mevinphos on sampling devices (arm
patches and gloves) worn by agricultural workers Involved  in harvesting
turnips after application of Phosdrin(R) 4EC.  M * male; F = female.
                                  Residue Concentration

                                    Cis-Mevinphos (ng)
Worker
Number
1
3
4
6
7
8
10
11
12
13
16
17
18
22
23
Sex
M
F
M
M
M
M
M
M
M
M
M
M
M
M
M
Arm patch
0.00
0.00
0.00
0.00
-
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.72
0.00
G1 oves
-
-
-
-
0.00
-
-
-
-
-
-
-
-
-
_
                                           64
-------
                                                    912
Table B2  Cont.

Worker
Nunfcer
30
33
35
36
37
40
41
45
46
49
51
53
54
56
57


Sex
M
F
F
F
F
F
F
F
M
M
M
F
F
M
F
Residue Concentration
Cis-Mevinphos (ng)
Arm patch
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-
0.00
0.00
0.00
0.00
0.00
0.00
0.00


G1 oves
-
0.00
-
-
-
-
0.00
0.00
-
-
-
-
-
-
—
            ======================================
                              65
-------
                                                                             913
Table B3.  Urinary metabolite, dimethyl phosphate (ug/ml) detected in urines
collected from agricultural workers while harvesting turnips treated with
PhosdrinlR)  4EC.  FMV = first morning void (0530-0700); M = male; F = female.
Worker
Number
1

3

4


6

7

8
10

11

12

13

15

16


17


Sex
M

F

M


M

M

M
M

M

M

M

M

M


M


Void
Number
1
2
1
2
1
2
3
1
2
1
2
2
1
2
1
2
1
2
1
2
1
2
1
2
3
1
2
3
Day of Time of
Void Void Urinary Metabolite (ug/ml)
Collection Collection Dimethyl phosphate (DMP)
1
2
1
1
1
1
2
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
2
1
1
2
0800
FMV
0800
1100
0800
1045
FMV
0800
1100
0800
1105
1100
0800
1100
0800
1045
0800
1045
0800
1100
0800
1100
0800
1100
FMV
0800
1045
FMV
0.03
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.01
0.00
0.00
0.01
0.01
0.04
0.05
0.02
0.01
0.00
0.00
                                          66
-------
                                                   914
Table B3.  Cont.
Worker
Number
18


21

22


23


30


33

35
36

37

40


41

45

Sex
M


M

M


M


M


F

F
F

F

F


F

F .

Void
Number
1
2
3
2
3
1
2
3
1
2
3
1
2
3
1
2
2
1
2
1
2
1
2
3
1
2
1
2
Day of
Void
Collection
1
1
2
1
2
1
1
2
1
1
2
1
1
2
1
1
1
1
1
1
1
1
1
2
1
1
1
1
Time of
Void Urinary Metabolite (ug/ral)
Collection Dimethyl phosphate (DMP)
0800
1045
FMV
1100
FMV
0800
1105
FMV
0800
1100
FMV
0800
1045
FMV
0800
1100
1110
0800
1110
0800
1120
0800
1100
FMV
0800
1100
0800
1105
0.02
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.00
0.00
0.00
0.04
0.01
0.00
0.00
0.01
0.01
0.00
0.00
0.02
0.01
0.07
0.00
0.00
0.01
0.00
                                   67
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                                                           915
Table B3.  Cont.
Worker
Number Sex
46 M


49 M

51 M
53 F

54 F


56 M
57 F
Void
Number
1
2
3
1
2
1
1
2
1
2
3
1
1
Day of
Void
Collection
1
1
2
1
1
1
1
2
1
1
2
2
2
Time of
Void Urinary Metabolite (ug/ml )
Collection 01 methyl phosphate (DMP)
0800
1100
FMY
0800
1110
1110
0800
FMV
0800
1045
FMV
FMV
FMV
0.00
0.00
0.00
0.03
0.01
0.00
0.01
0.02
0.00
0.00
0.00
0.00
0.00
                                  68
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                                 Appendix C
                                  Methods
                                                                   916
Cl  Extraction of insecticides  from soil
C2  Extraction of plant  tissue  for dislodgable residues of pesticides
C3  Extraction of gauze  patches  for pesticides
C4  Extraction of bond elute  cartridges for insecticides
C5  Extraction of gloves for  pesticides
C6  Benzyl method for extraction of alky! phosphate metabolites of
    organophosphorous insecticides from urine
C7  Gas chromatographic  conditions for detection of cis-mevlnphos
                                        69
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                                                                          917
                     Extraction of Insecticides from Soil
1.   Weigh 10 g of  soil and place in a 250 ml Erlenmeyer flask.
2.   Extract twice  with 50 mis of acetone* 15 mln.
3.   Filter, extract  and evaporate to 5 mis.
4.   Check sample for OP's using FPO.
5.   Prepare a florisll column and pass sample through collecting the
    6 and 15% eluates; 6 and  15% ethyl ether in petroleum ether.
    Evaporate samples to 5 mis and take to chromatography lab.
    (Note) Step 5  only applies when extracting soil for organochlorines.
                                     ci           "'      70
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                                                                  918
        Extraction of Plant  Tissue  (Leaves)  for  Dislodgable Residues

1.  Take 50 cm2 or 10 large  leaf  punches and weigh them.
2.  Place the samples In 120 cc urine  specimen cups and add to each 3
    drops of surfactant (Witconol  NP-100 @ 0.5*  concentration) and 75 mis
    H20.
3.  Extract for 15 minutes using  the shaker  in the round set at the fastest
    speed possible.
4.  Pass the extract  to  a 1,000 ml (dilute sample extract volume to 500 mis
    with deionized H20)  separatory funnel and re-extract the sample
    as before for a second time.
5.  Collect both extracts in separatory  funnels  and adjust the volume to
    approximately 600 mis using  5%
6.  Extract the sample contained  in the  separatory  funnels  three times with
    150 mis of Di chl orome thane (Methylene  chloride).
7.  Collect both extracts and  dry with Na2S04  granules.
8.  Evaporate to 0.5 mis and adjust volume to  5.0 mis  using methanol .
9.  Take samples to chemist for the addition of  the Internal standard.
                                                     71
                                      C2
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                         Extraction  of  Gauze  Patches                          919

1.  Place one 4"  X 4"  gauze patch  in a  500 ml  Erlenmeyer flask  and add
    150 mis of methanol.
2.  Extract twice using a Burrell  Wrist-Action Shaker set at #6.
3.  Collect to extracts and dry using Na2S04  and  evaporate to 5 mis.
4,  Take to chemist for the addition of the internal  standard.
                                      C3
                                                    T*
                                                           72
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                                                                   920
                    Extraction of Bond  Elute Cartridges

                  for Organophosphates  and Organochlorine



1.  Pass  100 mis of acetone through the  cartridge at approximately
    5 mis a minute.
2.  Dry  with


3.  Evaporate  to  5 ml s and take to GC room.
                                     C4                 73
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                                                                        921


                     ALKYL PHOSPHATES by Benzyl Method

Preparation of Standards Jl Solutions:

     1.   Prepare an alkyl phosphate standard at the following concentrations:
         Prepare two standards  dally.
                    KDMP      .25 ug/ml
                    KDEP      .25 ug/ml
                    KDMTP     .50 ug/ml
                    KDETP     .50 ug/ml

     2.   Prepare 3-benzyl-l-p-toyltrlayene derivatlzlng reagent:
                    250 mg above In 200 mis chloroform
                    (must prepare this dally)

     3.   Prepare NaCl/HCl solution:   100 g NaCl
                                     175 ml 12 N HC1
         Bring up to 1  liter  with H2°

Procedure:

     1.   Place 1 ml  of  urine  sample In 30 ml micro implnger tube.

     2.   Bring up to 20 ml  mark with  CHjCN (acetonitrlle).  Add approximately
         200 mg NaCl (small spatula full).

     3.   Azeotrope at approximately 90-95° C, almost to dryness.  (Do not Dry)

     4.   Add  approximately 5  mis additional acetonitrlle and azeotrope to
         approximately  1 ml.

     5.   Den'vatize  with 20 mis benzyl derlvatlzing reagent and evaporate to 1
         ml, placing a  one ball snyder column on Implnger tube.

     6.   Let solution set for about 20 minutes.

     7.   Add 15 mis NaCl/HCl  solution.

     8.   Extract three  times  with 6.0 mis  ethyl ether.  Do this using glass
         stoppers and vortexlng each extraction for 2 minutes.
         HINT;  Easiest to remove organic  layer with 5 ml macropipet.

     9.   Dry with Na2S04'

    10.   Evaporate to 0.1 ml.

    11.   Adjust to 1 ml with  acetone.
         Note;  For standard, dilute to  100 mis in volumetric  flask.

     Reid, S. J. and Watts, R. R. (1981).  A method for the determination of
dialkyl  phosphate residues  In urine.  J. Analyt. Tox. 5,  126-132.

                                     ce             ;"      75
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                                                                            922
                     Extraction of Gloves  for Pesticides
1.  Cut gloves Into approximately 1 Inch square pieces.
2.  Place sample Into 1000 ml  Erlenmeyer flask and  extract with
    methanol (200 ml  portions) three times on wrist-action
    shaker for 20, 15, and 15  minutes.
3.  Decant through glasswool  in funnel  into second  1000 ml  Erlenmeyer flask.
    Place sufficient sodium sulfate to  absorb any moisture in  the
    extract.  Transfer to round bottom  evaporating  flask.
4.  During second wrist-action extraction  evaporate samples down  so
    second extraction will fit into round  bottom evaporating flask.
5.  Repeat for third extraction.
6.  Bring down to approximately 1 ml.
7.  Prepare columns necessary:
    Pack with glasswool at the tip about 1 cm high.
    Add approximately 5.5 grams sodium sulfate (one large glass  scoop full)
8.  Transfer sample from round bottom into column  and collect  in  50  ml  tube.
    Rinse four times with 5 ml increments of desired final solvent.
9.  Evaporate under nitrogen,  purge to  approximately 2 mis. Vortex and
    centrifuge sample.
10. Transfer to centrifuge tube.  Rinse 50 ml tube  twice  with  2 ml aliquots
    of solvent.  Add to transferred solvent.
11. Re-evaporate to desired volume.  Vortex and centrifuge.
12. Take to GC lab.
                                                              74
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                                                                   923
   Gas Chromatographlc Conditions for Detection of Cis-Mevinphos

              Column  1
Instrument - Tracer 222 gas chromatograph
Column - 4% SE30/6% OY210
Flow rate 20 cc/min.. 200° C.
Detector F.P.D.,  phosphorous mode
Input attenuation 103
Output attenuation 32
Bucking range 6
Detector flow control
     02 85 ml/min.
     H 100 ml/min.

              Column  2
Instrument - Tracor 222 gas chromatograph
Column - 10% DC 200
Flow rate 50 cc/min.. 165° C.
Detector F.P.D.,  phosphorous mode
Input attenuation 10
Output attenuation 64
Bucking range 6
Detector flow control
     02 150 ol/min.
     H  I50ml/m1n.
                                                     76
                                C7
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