Transcript RODOS CUSTOMISATION - International Atomic Energy Agency

FDMH (RODOS) and more
Romanian contribution
IFIN-HH
Customization of RODOS and tritium module
(1998-2000)
ADM
Atmospheric Dispersion Module
Hydrological
Module
FDMT
FDMA
FDMF
FDMH
Terrestrial
Food Chain
Module
Aquatic
Food Chain
Module
Forest
Food Chain
and Dose
Module
Tritium
Food Chain
and Dose
Module
Terrestrial
Dose
Module
Aquatic
Dose
Module
Dose Combination Module
Countermeasure Subsystem CSY
Requirement: compatible with FDMT
(non tritium food chain model terrestrial)
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•
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Main crops, growth dynamics, Leaf area development, production
Animal products, animal diet and forage
human diets
irrigation
Plants and animals considered
ALL PLANTS IN Central Europe but FRUIT VEG. = TOMATO
FRUITS ( APPLE)- preliminary; BERRIES - preliminary
SUNFLOWER; GRAPES- preliminary; RICE- preliminary
ALL ANIMALS IN Central Europe
SHEEP MILK- preliminary
LAMB, PORK, CHIKEN based on few experimental data and
hydrogen metabolism
SHEEP based on unpublished experimental data and hydrogen
metabolism
Egg chicken very preliminary
FDMH - INPUT & OUTPUT DATA
• DYNAMIC
METEOROLOCICAL
DATA
• VIP_ NET RADIATION
• WEATHER PROGNOZE
• FDMT-NUCLIDE INDEP.
• SITE SPECIFIC CLIMATIC
DATA
• PHYSIOLOGICAL PLANT
PARAMETERS
• HTO&OBT ANIMAL
TRANSFER
PARAMETERS
Up to now, simple soil model
simple long term model
• INHALATION AND
INGESTION DOSE , AS
FOR DCM
• Fine time grid , HTO and
OBT concentration in
GRASS, most
contaminated location
• Ingestion time grid, HTO
and OBT concentration in
plants and animal products
for all locations
• NO
COUNTERMEASURES
FLOWCHART
Main program
Site and plants
Meteorologic files
DIAGNOZE
Actual yields ,
leaf area index
Photosynthesis
ACTUAL
Uptake of HTO
Conversion to OBT
in accident time
PROGNOZE
Evolution of HTO
Evolution of OBT
3 day prognoze
Doze and
Countermeasures
LONG TERM
Box model
Slow rate
Evolution until harvest
Long Term
prediction
countermeasures
Uptake, release and conversion of HTO in plants
• Resistance approach for uptake and loss
• Canopy resistance determined from gross photosynthesis and CO2 gradient [
NOT JARVIS APPROACH}
• Conversion from HTO to OBT driven by dry matter production rate
• Plant physiological parameters determined using crop growth model and
experimental dynamic data on LAI, leaves mass, storage organ mass, total
aboveground mass at the field scale
• more consistent parameters , NOT a collection of laboratory data
• Same set of parameters for canopy resistance and conversion to OBT
• NO need of leaf to canopy scaling
• Easy control with plant growth
• Easy to apply in various pedoclimatic conditions
• Easy to expand to other plants
• Care on sun set and sun rise
• Care on OBT formation in night (some calibration)
Correlating 3H and 14C
• Photosynthesis, driver for
- 14C uptake and conversion to organic
- - uptake of HTO in plant water (canopy resistance)
- -HTO to OBT conversion
- WOFOST crop growth model
Water cycle
Respiration
Distribution of dry matter to plant parts
Plant development stage
Basic plant processes
Potato- photosynthetic rate (canopy- favorable
temperature and age)
50
30
20
10
450
400
350
300
250
200
150
100
R
PA
5
0 6
4
3
2
50
1
LAI
0
Temperature and plant development stage, PAR and LAI
ASSIM RATE
40
Plant growth, experimental data and model
2500
exp. data
rom. param
E.C. param
8000
leaf exp.
leaf model
steam exp.
steam model
fruit exp.
fruit model
2000
biomass kg_dm/ha
above ground biomass kg/ha
10000
6000
4000
2000
1500
1000
500
0
0
120
140
160
180
200
220
julian day
Sunflower, adaptation to
Romania
240
260
80
100
120
140
160
180
200
220
240
260
julian day
Wine grape, preliminary
280
HTO concentration in leaf water
Vexc
dC Vexc
 (Cair  0.91 sC )  (  s   )Cs
dt M w
Mw
Vexc=1/(Ra+Rb+Rc)
LAI
LAI
g c,w 
[
0
g min,w
1.6

al Ag
D
(C s  )(1  s )
D*
]dL 
g min,w
1.6
al
LAI 
 A dL
g
Rc=1/gc,w
0
D
(C s  )(  s )
D*
Canopy resistence
1.00E+04
fgri
fmai
fpot
fbet
fwba
1.00E+03
fsba
s/m
fwwh
1.00E+02
1.00E+01
0
10
20
30
time after 4 am, unit=0.5 h
40
50
60
Comparison between experimental and theoretical data for maximum stomata resistance
Plant type
Experimental
val.(s/m)
Theoretical val (s/m)
References
Wheat, vegetative
stage
41 – 52
56
Baldocchi, 1994
Wheat, anthesys
62 - 100
60
Baldocchi, 1994
Maize, vegetative
121 - 131
111
Baldocchi, 1994
Wheat
17 - 20
18
Choudhury, 1998
Potatoe
100 - 130
130
Vos, 1987
Alpha-alpha
100 - 120
110 – 130 (dep. VPD)
Saugier, 1991
Soya
66
70
Oliosa, 1996
Grass C3
74
74 – 120 (dep. VPD)
Knap, 1993
Grass C4
151
156 – 178 (dep. VPD)
Knap, 1993
partition fraction
Partition of newly formed dry mater
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Roots
leaves
stems
grain
0
0.5
1
1.5
2
Developm ent stage
Partition fraction of newly produced dry matter as a function
of development stage (0=emergence; 1= flowering; 2= full maturity)
Data are for maize cultivar F320 from South Romania
OBT formation- day, night
• POBT=FD*0.41*Pc* CHTO (Bq/h/m2)
• FD-fractionation (discrimination) ratio (formation of OBT/formation
of OBH)
• Pc -net assimilation rate of CO2 as kg CO2 per unit time and unit
surface of crop
• CHTO- Leaf HTO concentration
• The formation of OBT in the dark is only partly understood because
the plant physiological processes implied cannot be quantitatively
assessed.
• Possible processes:
- oxidative respiratory pathways;
- tricarboxilic acid cycle;
- isomerisation and hydrolytic splitting reactions
OBT production in night recycles previously day produced photosinthate
POBT=FD*0.41*K*[average prev day Pc]* CHTO
POBT=FD*0.41*K1*(LAI/LAIMAX) ]* CHTO
K1=(0.0012-0.0024)DT DT in hours
The new crop operational model test
with German data- no calibration
time
Rel. TWT at end
exposure %
TWT half time(1h after
end) min
REL OBT at
harvest %
EXP
Model
EXP
Model
EXP
DAWN
26-74
21-50
40-60
60-100
DAY
53-100
50-80
25-49
30-50
DUSK
20-26
12-18
230-660
200-600
NIGHT
18-19
8-15
?
>600
0.23
0.27
Exposure conditions
(globalrad,temp)
Model
0.29
90-170,11-26
0.34
400-800,26-36
0.34
26-38, 15-24
0.31
0,12-17
Improved FDMH, test with German wheat
Mod=German model
(16 days after anthesis)[ OBT night formation halved, improved canopy resistance model, unlimited fertilization]
Start time
(GMT)
Rel TWT at end
exposure %
TWT half
time(1h after
end) min
REL OBT at
harvest %
Exposure
conditions
(globalrad
(W/m2,temp-C)
4
21
98
0.29
70,12
5
29
68
0.3
200,12
9
45
35
0.36
800,20
10
43
32
0.36
900,21
14
33
48
0.34
700,22
18
16
220
0.37
70,19
19
10
230
0.36
3,18
23
3
390
0.36
0,14
Seasonal effect
4.0
3.5
ingestion dose a.u
3.0
adult
child
2.5
2.0
1.5
1.0
0.5
0.0
50
100
150
200
julian day
250
300
Diurnal effect on dose for tritium
RODTRIT-modest contribution
Main picture:
HTO concentration
in leafy vegetables
(night, rain 1mm/h)
Small Pictures
Time integrated air
concentration,
• Cs-137
HTO in leafy veg.
(day/night rel. dry)
Dose from ingestion
• day/night, dry
• night, rain
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FDMH- ACTUAL STATUS
• INTEGRATED, as a test case -2000
• GENERIC DATA BASE DONE 2000
• IN HOUSE TESTS FOR VARIOUS
ENVIRONMENTAL CONDITIONS <2006
• READY TO IMPLEMENT HTO IN ADM, still
waiting
• READY TO ACCESS WEATHER PROGNOZE
• TO BE COMPLETED FOR
COUTERMEASURES
• PROCESING FACTORS CLARIFIED
ON-GOING UPGRADES
• include a standalone atmospheric model (musemet) to be done
• sparce canopy theory for dry deposition (factor
2) done
• sun set, sun rise effect on canopy resistancedetails- improved canopy resistance-done
• New animal model- done ,to be implemented
• New soil model- in work
be done
• test and improve forest deposition (plume depletion) to be done
• review documentation to be done
• review programming style to be done
• to be done: when financing available
•
test and improve fruits and improve berries to
IAEA EMRAS & TRITIUM
I and II
Develop and test tritium dynamics into the
environment with focus on organic tritium
Offer internationally quality assurance for
radiological assessment tools
Unique occasion for Romanian Utility to
handle tritium risk
7/18/2015
Acknowledge the following contributors:
– Wolfgang Raskob- DE
– Phil Davis- CA
– Hiroshy Takeda-JP
– Nick Beresford- UK
– Masahiro Saito-JP
– Yves Belot-FR
– Neil Crout-UK
– Ring Peterson-USA
– Akhilesh Trivedi-CA
– Sarov team ( ARZAMASH-16) Russia
– Ruddy Helling- NE
IAEA, EC, Royal Society (UK) , STA (Jp), AECL (CA)
and (why not !) Romanian Ministry of Education and Research
(but until mid 2008)
7/18/2015