SLIDE 1
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Objective
Revision of dynamical interaction of plant and soil in the process of airborne tritium transfer.
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Porting the tritium dynamical model into soil moisture block of - - PowerPoint PPT Presentation
Porting the tritium dynamical model into soil moisture block of - - PowerPoint PPT Presentation
Porting the tritium dynamical model into soil moisture block of Canadian Land Surface scheme (CLASS) Environmental Technologies Branch, Nuclear Sciences Division, CRL, AECL VY Korolevych January 25, 2011, EMRAS II, WG7 Mtg., Vienna
SLIDE 2
SLIDE 3
Issue
Predictions of plant tritium in ETMOD deviate from
- bservations in a long run (beyond ~72 hrs); soil tritium
predictions of ETMOD is in error all the time. Enhancement of modelling of tritium in soil is implied by new Canadian regulations
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SLIDE 4
CNSC: Current regulations
- 7,000 Bq/L is the current drinking water guideline in
Canada
- Where dose 7,000 Bq/L come from?
- Radiation protection basis of the drinking water
guideline is from ICRP
- Effective dose limit for public is 1 mSv/y
- Single exposure risk (1 mSv/y for one year) is
estimated to be 7.3 x 10-5 (ICRP, 1991)
- Lifetime exposure risk (1 mSv/y for 70 years) is
estimated to be 5 x 10-3 (ICRP,1991)
- Guideline for tritium in drinking water is 0.1 mSv/y of
dose through consumption of drinking water (WHO)
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SLIDE 5
Guideline (GL)
- GL = RDL/(DCF x Q)
- = (1 x 10-4 Sv/y)/(730 L/y x 1.8 x 10-11 Sv/Bq)
- = 7,610 Bq/L
- RDL = reference dose level, equal to 0.1 mSv/year
- DCF = dose conversion factor for ingestion by
adults (Sv/Bq)
- Q = annual ingested volume of drinking water
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SLIDE 6
Variation of the Final Criteria
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Country Final value
Guideline calculation 7,610 Bq/L WHO Russia Canada 10,000 Bq/L 7,700 Bq/L 7,000 Bq/L
SLIDE 7
Variation in Reference Dose Level
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Country RDL Drinking water guideline
Australia 1 mSv/year 76,103 Bq/L Finland 0.5 mSv/year 30,000 Bq/L Unite State* 0.04 mSv/year 740 Bq/L Canada 0.1 mSv/year 7,000 Bq/L
* US doesn't adapt ICRP
SLIDE 8
CNSC: Tritium Study and new regulations
- 100 Bq/L suggested new guideline (2010)
- The decision of the European Parliament was cited wrt
indicator of parametric value at 100 Bq/L on 13 May 1998
- Most EU members use the 100 Bq/L guideline for
tritium only as a screening value
- The risk at a lifetime exposure of 0.1 mSv/y is 6 x10-4
(Health Canada, 1995)
- Health Canada protocol for drinking water standard:
lifetime risk is from 1 x 10-5 to 1 x 10-6
- “Essentially negligible” lifetime cancer risk of about 5 x
10-6
- 100 Bq/L is reasonably practical and a planned action
by early 2011
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SLIDE 9
AECL Modelling capabilities
- Present capabilities focussed at tritium atm. dispersion, deposition,
transfer in plants and re-emission back to atmosphere:
- ADDAM-IST (CAN CSA N288.2)
- Various codes for Atmospheric Dispersion and Deposition
- IMPACT (CAN CSA N288.1)
- ETMOD-2
- UFOTRI
- Primitive off-line TT model
- CLASS 3.7
- CLASS+CTEM v1.1
- Under development:
- CLASS+CTEM+TT (Stage 2: Soil module)
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SLIDE 10
ETMOD-2 overview
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SLIDE 11
ETMOD-2 overview
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Grid (1):
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ETMOD-2 overview
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Grid (2):
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ETMOD-2 (continued)
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SLIDE 14
ETMOD-2 (continued)
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Transport in soil (cont):
SLIDE 15
ETMOD-2 (continued)
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Transport in soil (cont): HT: HT0:
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ETMOD-2 (continued)
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HTO transfer to/from vegetation:
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ETMOD-2 (continued)
- Dry Matter Production
- Gross photosynthesis rates are calculated using the CO2 consumption model (Weir et al. 1984, Sellers
1985, Mitchell et al. 1991, Pinder et al. 1988) and depend on air temperature, the resistance to CO2 uptake by the plant and the photosynthetically active radiation reaching the plant, which in turn depends on leaf area index. The production rate of dry matter is based on net photosynthesis taking into account both growth and maintenance respiration. Plant dry mass is updated using the dry matter produced in the time
- step. The wet vegetation mass is then calculated from the dry mass and the fractional water content,
which is assumed to remain constant as the plant grows.
- OBT Formation
- The dry matter produced at a given time is assumed to have a T/H ratio equal to 0.6 times the T/H ratio in
the plant water that takes part in the photosynthesis at that time. OBT concentrations following exposure decrease due to dilution with new uncontaminated dry matter. ETMOD does not account for the slow conversion of OBT to HTO in plants due to metabolic processes. OBT concentrations calculated in this way are assumed to apply to all dry matter in the plant. The rate of OBT concentration (COBT(t), Bq/L) accumulation follows the biomass growth:
d(MCOBT)/dt = IDp dM/dt CHTO, IDp – isotopic discrimination factor, and M(t) is a
dry matter water equivalent of biomass (combustible water, kg/m2).
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SLIDE 18
ETMOD-2 Face Validity Tests
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SLIDE 19
ETMOD-2 Tests (continued)
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SLIDE 20
ETMOD-2 Tests (continued)
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- where
Cpw is the HTO concentration per unit mass of plant water (Bq kg-1),
- Vex is an exchange velocity (m s-1),
- Mw is the mass of plant water per unit ground surface area (kg m-2),
- Ca is the HTO concentration in air (Bq m-3),
- is the ratio of the vapour pressure of HTO to H2O (0.91), and
- h is the saturation humidity at leaf temperature (assumed equal to air temperature)
- (kg m-3).
- Exchange velocities calculated by ETMOD fluctuate according to the current meteorological
conditions, with most values lying between 2 x 10-3 and 8 x 10-3 m/s
- ETMOD overpredicts in the initial period and underpredicts after 3
days (72 hrs)
Soybean Scenario Report:
SLIDE 21
New Development Stage 2: Soil module of CLASS+CTEM+TT
Stage 2 of Tritium Transfer implementation in CTEM+CLASS: Porting the tritium dynamical model into soil moisture block of Canadian Land Surface scheme (CLASS) Validation of the modelling system against surface flux measurements and meteorological observations at Perch Lake tower at CRL and at experimental garden plots in the Perch Lake tower vicinity. On going work: Analysis of gaps in available inputs and assembly of datasets to run the model at different sites:
- Point flux measurements
- Gridded inputs
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SLIDE 22
CLASS
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(D.L. Verseghy et al. Atmosphere-Ocean, V38, N1, 2000 Special Issue, 269 p.)
(Can. Land Surface Scheme)
SLIDE 23
Components of CLASS
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Energy Fluxes Radiation Fluxes CO2 Fluxes Water Fluxes
SLIDE 24
- Can. Terrestrial Ecosystem Model
(CTEM), V. Arora’2007 )
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Carbon assimilation, allocation and dissimilation (5 pools)
SLIDE 25
CTEM+CLASS
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Source: CTEM manual v1.1
SLIDE 26
Tritium Transfer in CTEM+CLASS framework
AECL - OFFICIAL USE ONLY / À USAGE EXCLUSIF - EACL
26
HTOSOL1 HTOSOL2 HTOSOL3 OBTRT2 OBTRT1 OBTSTEM OBTRT3 OBTLEAF HTOATM HTOLF
SLIDE 27
Tritium Transfer in CTEM
27
Leaf compartment TFWT:
ML = (CL + A -RgL-RmL -DL)/(0.45 0.19)
Stem compartment HTO activity : Roots: HTO activity CHTO,R = CHTO,sr1 OBT activity: MsCOBT,R (t+t) = Idmwe[COBT,leaf AR -
- COBT,R (t)(RgR+RmR-DR)]
Root zone (HTO activity in soil layer 1):
MSR1CHTO,sr1 = Idmwefr1COBT,root(RgR+RmR +DR) - CHTO,sr1 (Ebs + a12 ) - a21 CHTO,sr2, …
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Ms CHTO,s (t+t) = I1[(Astem - RgL- RmL -DL) CHTO,leaf - (Rgs-Rms –Ds) CHTO,s (t)].
. Ms (t+t) = . Ms (t) +Ms (0.45 0.19)-1(Cs +Astem-Rgs-Rms -Ds)
OBT activity:
Ms COBT,s(t+t) = Idmwe[(COBT,leafAstem - COBT,s (t)(Rgs-Rms -Ds)]
SLIDE 28
Tritium Transfer in CTEM
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MHTO,s = I1[(Astem - RgL- RmL
- DL) CHTO,leaf -
- (Rgs-Rms –Ds) CHTO,s].....
Leaf compartment
ML = I1 (CL + A -
- RgL- RmL -DL)
Exported:
Astem, Aroots,DL COBT=CHTO,leaf
Stem compartment : Roots:
MR = Ist (CR + + Aroots -RgR -RmR)
HTO Released into soil layer 1:
fr1 MRCOBT,R = fr1Ist (AR + +RgR+RmR)COBT,R
Updates in mass of 5 compartments results in OBT and HTO translocation
SLIDE 29
Tritium Transfer in CLASS (CTEM+CLASS)
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Soil HTO :
dMw,s1CHTO,s1 /dt = = - (EfR1 + Ebs +- EI12)CHTO,s1 + PHTO PHTO is total activity in infiltrating precip
V
ex = gc(t)Vmax
Vmax – measured
Catm is the HTO concentration in the atmospheric moisture (Bq/L), Catm is the weighted time-average of atmospheric HTO concentration (Bq/L), Cleaf is the HTO concentration in the plant water in leaf (Bq/L), M is the whole plant dry matter water equivalent (d.m.w.e. kg/m2), Mleaf is the mass of a leaf part of the plant per surface area, fresh water equivalent (f.w.e., kg/m2), Vex is exchange velocity in units converted to atmospheric water flux similar to that of ET (mm/s), Csoil is the HTO concentration in the soil moisture (Bq/L), E denotes ET (mm/s) and w is the water density; IDp =0.8 Iij is the infiltration rate as per vertical HTO concentration gradient (mm/s)
atmHTO uptake: HTO diffusion
dMw,s1CHTO,,s2/dt = I12CHTO,s1- (EfR2+I23)CHTO,s2
SLIDE 30
Tritium Transfer in CLASS (CTEM+CLASS)
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Soil HTO :
dMw,s1CHTO,s1 /dt = = - (EfR1 + Ebs +- EI12)CHTO,s1 + PHTO PHTO is total activity in infiltrating precip
V
ex = gc(t)Vmax
Vmax – measured
Catm is the HTO concentration in the atmospheric moisture (Bq/L), Catm is the weighted time-average of atmospheric HTO concentration (Bq/L), Cleaf is the HTO concentration in the plant water in leaf (Bq/L), M is the whole plant dry matter water equivalent (d.m.w.e. kg/m2), Mleaf is the mass of a leaf part of the plant per surface area, fresh water equivalent (f.w.e., kg/m2), Vex is exchange velocity in units converted to atmospheric water flux similar to that of ET (mm/s), Csoil is the HTO concentration in the soil moisture (Bq/L), E denotes ET (mm/s) and w is the water density; IDp =0.8 Iij is the infiltration rate as per vertical HTO concentration gradient (mm/s)
atmHTO uptake: HTO diffusion
dMw,s1CHTO,,s2/dt = I12CHTO,s1- (EfR2+I23)CHTO,s2
COBT(t), is the of OBT concentration (Bq/L) IDp – isotopic discrimination factor Mleaf,cw(t) is a dry matter water equivalent of biomass (combustible water, kg/m2) A – photosynthesis rate (kg/m2/s)
Mleaf,cwdCOBT,L/dt = Mleaf,cw
- 1A(IDp CHTO,L -
COBT,L)
OBT in leaf compartment:
SLIDE 31
Verification of tritium translocation in CTEM+CLASS (on-going)
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SLIDE 32
Pilot test: inputs variability
- The micrometeorological complexity of CRL site is
typically translated into high variability of surface fluxes and wind conditions and presents a certain challenge
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SLIDE 33
Pilot test: inputs variability
- The micrometeorological complexity of CRL site is
typically translated into high variability of surface fluxes and wind conditions and presents a certain challenge
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SLIDE 34
Pilot test: inputs variability
- The micrometeorological complexity of CRL site is
typically translated into high variability of surface fluxes and wind conditions and presents a certain challenge
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SLIDE 35
Pilot test: inputs variability
- The micrometeorological complexity of CRL site is
typically translated into high variability of surface fluxes and wind conditions and presents a certain challenge
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Some averaging in time definitely removes any ambiguity.
SLIDE 36
Pilot test: inputs variability
- The micrometeorological complexity of CRL site is
typically translated into high variability of surface fluxes and wind conditions and presents a certain challenge
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Some averaging in time definitely removes any ambiguity. Alternatively – spatial averaging could be deployed based on Taylor hypothesis of frozen turbulence. Data from neighbouring meteostations becomes critical.
SLIDE 37
Gap-filling in Inputs: Available observations
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SLIDE 38
Gridded Inputs
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- CRU (Tyndall
Centre dataset) Monthly observations interpolated to 0.5deg. Grid
- GR-2 1.85deg
(NCAR),
- ETA-32 (NCAR)
SLIDE 39
Quality of available gridded and point data
- Available meteorological drivers
- Issues related to data quality
- Assimilation of scarce and intermittent observation
data
- Off-line tests
- On-line tests of distributed system (gridded data
sources)
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SLIDE 40
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Specific Humidity
- 2%
- 1%
- 1%
0% 1% 1% 2% 2% 3% 3% 4% 4%
Regular Spatial Interpolation
- f hourly observations (SI):
Specific Humidity
- 50%
- 40%
- 30%
- 20%
- 10%
0% 10% 20% 30%
0.5x0.5deg gridded observations (CRU):
Lon- 128.58
- 125.77
- 122.67
- 120.73
- 117.63
- 114.1
- 111.45
- 110.72
- 106.68
- 104.2
- 101.1
- 97.87
- 91.62
- 86.95
- 82.47
- 80.8
- 79.93
- 79.3
- 77.53
- 73.75
- 71.38
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.37
- 58.55
- 55.6
degrees logitude
L- n
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 9
- 9
- 8
- 8
- 8
- 7
- 7
- 7
- 7
- 7
- 6
- 6
- 6
- 6
- 6
- 6
- 5
- 5
degrees logitude
Precipitation
- 40%
- 30%
- 20%
- 10%
0% 10% 20% 30% 40% 50%
SW radiation
- 8%
- 6%
- 4%
- 2%
0% 2% 4% 6% 8% 10% 12%
Wind speed
- 6%
- 4%
- 2%
0% 2% 4% 6% 8% 10%
SI forcing anomalies
L- n
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 9
- 9
- 8
- 8
- 8
- 7
- 7
- 7
- 7
- 7
- 6
- 6
- 6
- 6
- 6
- 6
- 5
- 5
degrees logitude
Precipitation
- 20%
0% 20% 40% 60% 80% 100% 120% 140% 160% 180% 200%
SW radiation
- 50%
- 40%
- 30%
- 20%
- 10%
0% 10% 20% 30%
Temperature
- 9
- 8
- 7
- 6
- 5
- 4
- 3
- 2
- 1
1 2
CRU forcing anomalies
L- n
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 9
- 9
- 8
- 8
- 8
- 7
- 7
- 7
- 7
- 7
- 6
- 6
- 6
- 6
- 6
- 6
- 5
- 5
degrees logitude
Quality of available gridded and point data (ad hoc and gridded obs interpolation)
SLIDE 41
Precipitation anomaly: NARR vs. CRU
- 600
- 400
- 200
- n
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 9
- 9
- 9
- 8
- 8
- 8
- 7
- 7
- 7
- 7
- 6
- 6
- 6
- 6
- 6
- 6
- 5
- 5
degrees longitude mm/year
NARR Precip anomaly CRU Precip anomaly
- 600
- 400
- 200
200 400 600 / / /
GR2_Precip anomaly NARR Precip anomaly
- Sfc. meteo forcing comparison:
Precipitation anomaly in NARR (vs.GR2)
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1981-1990, Reanalysis: ET anomaly
- 300
- 200
- 100
100 200 300 400
Lon
- 131.82
- 127.37
- 124.9
- 122.58
- 120.45
- 117.43
- 114.02
- 111.22
- 108.48
- 105.55
- 103
- 99.95
- 94.98
- 90.72
- 85.93
- 82.47
- 80.8
- 79.85
- 77.78
- 74.28
- 72.27
- 69.55
- 68.2
- 66.25
- 64.68
- 63.27
- 60.23
- 57.4
- 52.78
degrees longitude mm/year
GR2 ET anomaly NARR ET anomaly
Comparison of gridded products with point observations
- Major difference is in Winds
- The second largest difference
between obs and GR2 datasets is in Precipitation field.
- The third difference in datasets
is in slightly overestimated Specific Humidity in GR2.
- The 4-th difference in datasets is
in overestimated LW radiation in GR2 and NARR (as well as Underestimated SW radiation in GR2) at whole Spring season affecting snow-melt timing
Quality of available gridded and point data
ET anomaly: GR2 vs. CRU
- 250
- 200
- 150
- 100
- 50
50 100 150 200
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 125 129 133 137 141 145degrees longitude mm/year CRU_ET anomaly1 GR2 ET anomaly
SLIDE 42
Quality of available gridded and point data (Reanalysis Drivers)
1981-1990 Reanalysis: SW radiation anomaly
10 20 30 40 50 60 70
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
degrees longitude W/m2
gr2 narr 1981-1990 Reanalysis: LW radiation anomaly
- 60
- 50
- 40
- 30
- 20
- 10
10 20 30 40
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
degrees longitude W/m2
gr2 narr
- Sfc. meteo forcing comparison:
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1981-1990 Reanalysis: Wind anomaly
- 6
- 4
- 2
2 4 6 8
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
degrees longitude m/s
gr2 narr
1981-1990 Reanalysis: Pressure anomaly
- 14
- 12
- 10
- 8
- 6
- 4
- 2
2 4 6
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
degrees longitude kPa
gr2 narr
- Sfc. meteo forcing comparison:
1981-1990 Reanalysis: Specific Humidity anomaly
- 30%
- 20%
- 10%
0% 10% 20% 30%
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
narr_anom/obs (%) gr2_anom/obs (%)
- Sfc. meteo forcing comparison:
1981-1990 Reanalysis: Precipitation anomaly
- 1000
- 800
- 600
- 400
- 200
200 400 600
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
degrees longitude mm/year
gr2 narr 1981-1990 Reanalysis: 2m_Temperature anomaly
- 8
- 6
- 4
- 2
2 4 6
Lon- 131.82
- 127.37
- 124.9
- 122.67
- 122.07
- 118.88
- 115.67
- 113.9
- 111.22
- 110.28
- 106.68
- 104.67
- 102.47
- 98.27
- 94.37
- 90.72
- 86.95
- 82.57
- 81.15
- 80.65
- 79.63
- 77.78
- 75.72
- 73.42
- 71
- 68.42
- 66.82
- 66.08
- 64.68
- 63.28
- 60.23
- 57.4
degrees longitude deg C
gr2 narr
SLIDE 43
Quality of available gridded and point data (impact on prognostic w ater)
a)
SI_ET_anomaly_%
- 20%
- 10%
degrees longitude from -145W to 55W (shown are corresponding station IDs)
CRL Point Lepreau PNGS
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b)
CRU_ET_ANOMALY_%
- 20%
- 10%
degrees longitude from -145W to 55W (shown are corresponding station IDs)
75%CRL Point Lepreau PNGS
c)
GR2_ET_anomaly _%
- 20%
- 10%
CRL Point Lepreau PNGS
SLIDE 44
Gridded parameterization of LSS (1)
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SLIDE 45
Gridded parameterization of LSS (2): LAI dynamics
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SLIDE 46
Fig.1 CRL Acid Rain Site (ARS) dedicated to atmospheric uptake of tritium using tarp-covered clean soil Fig.2 CRL Perch Lake Site dedicated to re-emission of tritium.
CRL Experiments in 2009-2010 (1)
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SLIDE 47
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- Behavior of HT, HTO and OBT in soil and soil porewater
- The ratio of exchangeable and non-exchangeable OBT in vegetables
(COG – on-going)
Experiments at CRL in 2010-2011 (2)
Fig.3 Darlington Site
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SITE DATE TIME TOTAL TIME OBS 1 15/09/200 9 13:03:52 4 1 15/09/200 9 13:07:59 4 1 15/09/200 9 13:14:27 4 1 15/09/200 9 18:30:53 4 1 15/09/200 9 18:36:48 4 1 15/09/200 9 18:42:50 4 1 16/09/200 9 6:18:21 4 1 16/09/200 9 6:26:49 4 1 16/09/200 9 6:32:49 4 2 15/09/200 9 12:56:49 4 2 15/09/200 9 13:10:12 4 2 15/09/200 9 13:16:30 4 2 15/09/200 9 18:26:38 4
Soil CO2 : TAIR TLEAF CO2 FLOW RH EAIR
Experiments at CRL in 2009-2010 (4)
date time potatoes uncovered tomatoes uncovered potatoes covered tomatoes covered storage leaves stems fruit soil leaves stems fruit soil leaves stems fruit soil leaves stems fruit soil 19-Aug-09 14:00 X X X X X X X X X X X X X X X Bldg 560 freezer 19-Aug-09 19:00 X X X X X X X X X X X X Bldg 560 freezer 20-Aug-09 5:30 X X X X X X X X X X X X Bldg 560 freezer 15-Sep-09 13:00 X X X X X X X X X X X X X X X X Bldg 513A freezer 15-Sep-09 18:00 X X X X X X X X X X X X Bldg 513A freezer 16-Sep-09 6:00 X X X X X X X X X X X X X X X X Bldg 513A freezer 05-Oct-09 13:00 X X X X X X X X X X X X X X X X Bldg 513A freezer 05-Oct-09 18:30 X X X X X X X X X X X X X X X X Bldg 513A freezer 06-Oct-09 6:30 X X X X X X X X X X X X X X X X Bldg 513A freezer
Tritium samples: HTO measured in all of them, OBT – in all leaves and fruits and in a subsample of stems and soil
Ambient parameters:
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Experiments at CRL in 2009-2010 (5)
plume
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In September all significant precipitation events except the last one coincided with plume over
- ARS. The last event is
translated in clean soil in the immediate subsurface layer, while the deep (>20sm) layer contains washout from September plumes
Experiments at CRL in 2009-2010 (6)
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Summary
Accurate process-based model is needed as a background for scientifically sound new robust regulatory model Carbon-based consideration of HTO requires more
- n water-use efficiency and night time
Complete local meteorology is critical for LSS (should be more robust wrt gridded inputs of winds and radiation) Ongoing experiments require more attention wrt ambient drivers
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