Simulation of Heavy Metal TrUse of Scale FacUse o Sca e acVariable Sorpt
Han Xiao1, Jürgen Böttc
1Institute of Soil Science, Leibniz Unive2Dept. of Environmental Sciences, Un
ransport in Unsaturated Soil: ctors to Quantify cto s to Qua t ytion Isotherms
cher1, and Jiří Šimůnek2
rsity of Hannover, Hannover, Germany
niversity of California, Riverside, USA
Spatial variability of heaSpatial variability of heaPrecipitationp
Water flow and
Object: Quantification of sorption
avy metal transportavy metal transport
solute transport
to quantify heavy metal transport
Footprint of scalingFootprint of scaling
Mill i il it f il t tMiller similarity for soil water reten
Tillotson & Nielsen functional norm
Boettcher scale factors for sorption
ti 1956ntion 1956
malization 1984
n 1997
increasing sorption intensity
Scaling rulesScaling rules
(Boettcher 199
Scaling of sorption isothScaling of sorption isoth
ReferencDer
Scale facDer
Der
Derpro
hermherm
ce sorption isothermrived from mixed soil samplesctorsrived from soil physicochemical
rived from mixed soil samples
rived from soil physicochemical perties
Scaling procedureScaling procedure
Di t liDirect scaling procedure
Calculated MeanCalculated Mean sorption isotherm
Calculated scale factors
I di t liIndirect scaling procedure
Sorption isotherm d i d f i d ilderived from mixed soil
samples
Scale factors transformed from soil properties using linear p p g
regression
Water flow and heavy mWater flow and heavy mmetal transportmetal transport Sampling locationSampling location
L i l d l d i l t iLuvisol developed in loess materiaGermany
source : Google
l i L th h Hl in Lathwehren, Hannover,
e Maps
Laboratory worksLaboratory works Soil properties & FreunSoil properties & Freun
pH CECeff Corg sand clay
‐ % % %‐ % % %
MeanTopsoil 6.9 96.8 1.18 3.8 11
MeanSubsoil 7.2 72.9 0.31 3.3 12
% % % % %
CV*Topsoil 2 40 10 9 1
Subsoil 2 42 17 13 2Subsoil 2 42 17 13 2
Coefficient of variationUnit of K is [µg1‐nLn/kg], unit of n is [‐]
dlich parametersdlich parametersK K K
y silt Feox Alox Mnox n(Cd)
n(Zn)
n(C
% []^ [] [% [] [] [
1 85 2617 581 356 14070.81
74980.51
241.
2 85 2621 603 228 22710.80
135090.49
121.
% % % % % % %
12 4 4 10 347
245
36
10 5 6 17 33 17 410 5 6 17 6 7 9
Direct scaling procedurDirect scaling procedur
Cd Zn
e topsoile topsoil
Cu
ndirect scaling procedundirect scaling procedu
Adj. R2 =0.513 Adj. R2 =0
pH Ox Fe pH Corg
Cd αin Zn
ure topsoilure topsoil
0.505 Adj. R2 =0.443
sand pH CEC Corg
αin Cu αin
Reference isotherm andReference isotherm andHeavy Horizon Sample Direct scaling proHeavy metal
Horizon Sample size
Direct scaling pro
R‐SI*
Cdtopsoil 50 13 S=1394C0.8
subsoil 50 16 S=2248C0.7
Zntopsoil 50 14 S=7482C0.5
subsoil 50 14 S=13638C0
Cutopsoil 50 5 S=245C1.33
subsoil 50 10 S=118C1.64
& coefficient of variation& coefficient of variationReference sorption isothermScale efficiencySorption isotherm derived from mixed sample
d Scale factorsd Scale factors
ocedure Indirect scaling procedureocedure Indirect scaling procedure
SE^Adj. R2 SImixed
#
%%80 85 10 0.513 S=1398C0.83
79 92 13 0.503 S=2229C0.77
51 88 11 0.505 S=8709C0.49
.49 75 7 0.248 S=15612C0.44
3 72 3 0.443 S=275C1.30
4 89 8 0.612 S=161C1.59
Modeling with HYDRUSModeling with HYDRUSInfiltration 250
SS0mm per year
Cμg/L
Tyr
Cd 100 500
Zn 8000 500
Cu 2000 100
Scenarios I with originaScenarios I with origina
Cd
Zn
0
Zn
0
Cu
0
l sorption equilibriuml sorption equilibrium
100 μg/L
8000 μg/L μg
2000 μg/L
Scenarios II with directScenarios II with direct
Cd
Zn
0
Zn
0
Cu
0
scaling procedurescaling procedure
100 μg/L
8000 μg/L μg
2000 μg/L
Scenarios III with indireScenarios III with indire
Cd
Zn
0
Zn
0
Cu
0
ect scaling procedureect scaling procedure
100 μg/L
8000 μg/L μg
2000 μg/L
ComparisonComparison
CdCdI
II
II
•Cu
•
ZnZn
I
Between different scenariosScenario I > Scenario II > Scenario Between different heavy metals
Zn(88%) > Cd (85%) > Cu(72%)
SummarySummary
h t l t t i b i lheavy metal transport is obviously
Direct scaling procedure: scale factvariability of heavy metal transporCu.Cu.
Indirect scaling procedure: predictIndirect scaling procedure: predict
i bl variable.
tors can describe the spatial t well for Zn, not so well for Cd and
ion accuracy must be improvedion accuracy must be improved.
Thanks for your attentioThanks for your attentioonon
Input α in HYDRUS 2Dput α USwith Cd direct scaling