reactive transport in columns (oxired 2)
TRANSCRIPT
Reactive Transport Modeling – Column Tests –
OXIRED II
Jana Nicolai, Harald Kalka – Mar 2011Umwelt- und Ingenieurtechnik GmbH Dresden
Project financed by:
Hydraulics1
Ion Exchange2
Redox Reactions4
Mineral Phases3
increasing complexity
Geometry & Hydraulics1
Experimental Data (TU Berlin)
Porosity
Dispersion
CEC
dried at 200°C
dried at 200°C
500 to 600 °C
Col 3
Col 4
Col 5
yes
yes
no
sediment
Fe coated sand
hydraulics
no
yes
yes
µ biology
naturalCol 2 yes no
Col 1 provisional test
inflo
w Q
Fe-coated
sand
35 cm
Q = 1.0 mL / min
porosity: = 0.35
dispersion: αL = 0.003 m
Column Setup (35 cells)
pure sand
Bromide breakthrough
35 cm
Column Setup (35 cells)
pure sand
Col 1Col 2Col 3
Col 4
Col 5
Fe-coatedsand
mono-layer
anaerob.zone
aerob.zone
0
5
10
15
20
25
30
35
40
45
5 6 7 8 9 10 11time [days]
Bro
mid
e [m
g/L]
pure ADV
DISP = 0.3 cm DISP = 0.6 cm
DISP = 1.2 cm
Longitudinal Dispersion
Note: There is no numerical dispersion (blue curve).
Bromide
Col 3
Ion Exchange2
without Ion Exchange
Li
Br
Hydraulics (Retardation of Li)
Li
Br
with Ion Exchange
Col 2
scre
en sh
ots
of T
RN
Q = 1.3 mL/min
Fe-coated / dried sediment 200°C
Fe-coated / 500 to 600 °C
Br Li
Br
Br
Li
Li
Li
Col 3
Col 4
Col 5
retarded ?adsorbed ?
Li
CTOT = 5 meq/L
dried sediment 200°C
Q = 1.0 mL/min
Q = 1.1 mL/min
CTOT = 20 meq/L
Col 1 Col 2 Col 3 Col 4 Col 5
flow Q mL / min provi-sional
1.3 1.3 1.0 1.1
time T days 14 11 19 13
sediment natural natural 200 °C 200 °C 550 °C
CTOT meq / L 20 20 20 20 5
µ biology yes yes yes yes (no)
Fe coated sand no no no yes yes
shrinks due to 550 °C
Column Parameters
other0%
NaX2%
KX1%
HX0%
MgX212%
CaX285%
HXKXNaXCaX2
MgX2other
Ion Exchange
time [days]
Mg [mg/L]
Ca [mg/L]
K [mg/L]
CEC = 20 mmol/L
Cation Exchange
H+ + X- = HX log K = 1.0 K+ + X- = KX log K = 0.7
Na+ + X- = NaX log K = 0.0 Li+ + X- = LiX log K = -0.08
Ca+2 + 2X- = CaX2 log K = 0.8 Mg+2 + 2X- = MgX2 log K = 0.6 NH4
+ + X- = NH4X log K = 0.6 Fe+2 + 2X- = FeX2 log K = 0.44 Al+3 + 3X- = AlX3 log K = 0.36
Carbam+ + X- = CarbamX log K = 0.0
new species added
Pharmaceutically Active CompoundsChemicalFormula Structure Molar
Weight
Primidone C12H14N2O2 218.25
Carbamazepine(CBZ) C15H12N2O 236.26
Sulfamethoxazole(SMX) C10H11N3O3S 253.28
0
1
2
3
4
5
6
7
8
9
10
11
10 11 12 13 14 15 16 17 18 19time [days]
Car
bam
azep
ine
[µg/
L] experiment
model without IX model with IX
retardation
Carbamazepine
degradation due to ozonation
Retardation of CBZC
ol 4
PhACsBromide [mg/L]
CBZ [mg/L]
SMX [mg/L]
Primidone [mg/L]
Bromide [mg/L]
CBZ [mg/L]
SMX [mg/L]
Primidone [mg/L]
time [days] time [days]
Col 4 Col 5
Mod
el R
esul
ts
Mineral Phases3
Mineral Phases
gypsum CaSO4H2O
ferrihydrite Fe(OH)3
aluminum hydroxide Al(OH)3
amorphous SiO2 SiO2
calcite CaCO3
as equilibrium phases (based on log K values)
as kinetic reaction
Lake Tegel water: SI > 0
Calcite Kinetics
Column 3
0SIformm101rrate
0
SIdiss
s/mM103r 8diss
Ca [mg/L] DIC [mg/L]
mM5m0 ?
Redox Reactions4
-5,0
-2,5
0,0
2,5
5,0
7,5
10,0
12,5
15,0
0 2 4 6 8 10 12 14 16 18 20
Time in days
pE
-300
-150
0
150
300
450
600
750
900E
h in mV
Col 2Col 3Col 4Col 5
Experimental Fact (Redox Potential)
microbial activity (Col 2 to 4)
no activity (Col 5)
Microbe
e-Do
nor
e-Ac
cept
or
Ox Ox + e-
Red + e- Red
e- Energy (ATP)
+
Electron Transfer
oxidation (loss of e-)
reduction (gain of e-)
0 10 20-20 -10
0 10 20-20 -10
O2 reduction
denitrification
MnO2 → Mn+2
Fe(3) oxide → Fe+2
SO4-2 reduction
CH4 fermentation
reductions
oxidation of Corg
Sulfide → SO4-2
Fe+2 oxidation
nitrification
Mn+2 oxidationoxidations
pe
half-reactions relevant in Col 2, Col 3, and Col 4
Biodegradation of Organic Matter
Degradation of Organic Matter (CH2O)
CH2O + H2O = CO2 + 4H+ + 4e- oxidation: C(0) C(IV)
O2 + 4H+ + 4e- = 2H2O reduction: O(-II) O(0)
NO3- + 2H+ + 2e- = NO2
- + H2O reduction: N(V) N(III)NO2
- + 8H+ + 6e- = NH4+ + H2O reduction: N(III) N(-III)
SO4-2 + 10H+ + 8e- = H2S + 4H2O reduction: S(VI) S(-II)
electron donors
electron acceptors
less important
Sequential Reduction of Nitrate
no measured data
NO3- NO2
- NOx N2 PON DON NH4+
GW / columns: closed systembioreactor: open system
CH2O Degradation – Enzyme Kinetics
From simple to complex:
1st order kinetics
Michaelis-Menten
Michaelis-Menten e Acceptors
Michaelis-Menten e Acceptors Population Dynamics
d[P]/dt
[S] KS
vmax
½ vmax
PEESSE k
k
k
]S[K]S[v
dt]P[d
S
max
]E[kv 0max
]ES[]E[]E[ 0
kkkKS
steady state
+
+
E
S
ES E
P
Michaelis-Menten Kinetics
Two Principal Approaches
Enzyme Kinetics Population DynamicsMichaelis, Menten 1913 Monod 1942
dynamical variable: substrate [S] biomass or cell density B
deduced from well-defined assumptions about the catalytic mechanism empirical equation
]S[K]S[v
dt]S[d
Smax
]E[kv Tmax
]S[K]S[
Smax
B)(dtdB
]S[K]S[v
dt]S[d
S
max
Mixed-Order Kinetics
]S[Kv
dt]S[d
S
max
maxvdt
]S[d
1st order
zero order
S << KS
S >> KS
S0 = 80 mMKS = 8 mMμeff = 410-7 M/s
Michaelis-Menten
used model parameters
Combination of both Approaches
Number of Enzymes and Biomass amount are correlated.
BY
Ek maxT
)t(BY
)t(dt
]S[d
)t(B)t(dtdB
]S[K]S[)t(
Smax
Yield
ODE System
Applied Model (with e Acceptors)
electron flow
max2S
20
2
B)t(B
]OCH[K]OCH[
dt]OCH[d
maxmax
eff BY
)t(f)t( accepteff0
)t(NOa)t(NOa)t(Oaf)t(f 2231200accept
A non-linear system.
Ther
mod
ynam
ics
Enzyme Kinetics
+
E
H
EH
+
E
2S ESS
+
E
S ESG
+
G
]S[IK]S[v
1S
max
11 K
]H[1I
2S
max
I]S[K]S[v
22 K
]S[1I
3S
max
I1
]S[K]S[v
33 K
]G[1I
competitive inhibition
self-inhibition(HALDANE)
non-competitive inhibition
What About Inhibition ?
B
t Lag Exp Stationary Death
Individual Cell(Cell Growth)
Populations of Cells
Increase in Cellular Mass
and Size
Increase in Total Number of Cells
Difficult to Measure
Bacterial Growth
strain a
enzyme A
enzyme B
strain b
strain cXA ≠ Xa
Population vs. Enzyme Density
pH & pe
time [days]
time [days] time [days]
Col 2 Col 2
Col 3 Col 3
Col 4 Col 4
Col 5
Col 5
pH pe
pH pe
pH pe
pH
pe
Redo
x Dy
nam
ics
time [days]
Redox Dynamic
0,00
0,02
0,04
0,06
0,08
0,10
0,12
0,14
0,16
0 1 2 3 4 5 6 7 8time [days]
Oxygen [mM]
Nitrate [mM]
Nitrite [mM]
Ammonium [mM]
Col 3mass
balance
time [days]
Redox Zonation inside Col 3
0,00
0,02
0,04
0,06
0,08
0,10
0,12
0,14
0,16
0,18
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35
Nitrate [mM]
Nitrite [mM]
Ammonium [mM]
Oxygen [mM]initial state
0,00
0,02
0,04
0,06
0,08
0,10
0,12
0,14
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35
after 20 hours
0,00
0,02
0,04
0,06
0,08
0,10
0,12
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35
after 45 hours
0,00
0,02
0,04
0,06
0,08
0,10
0,12
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35
distance inside the column [m]
Nitrate [mM]
Nitrite [mM]
Ammonium [mM]
Oxygen [mM]
after 70 hours
Conclusions5
Conclusion 1
“simple” sand-filled columns
surprisingly complex redox dynamics
Most things are unseen in raw data.
Conclusion 2
Intro
model
A sound combination of
experimentQC
(always) reveal details about a system that you didn’t think of beforehand.
data
Conclusion 3
IntroOnce a model is calibrated by real datascenarios can be simulated:
variation of flow velocity
natural sediments w/o µbiology and/or technical sandlarger columns (upscaling)
column systems (and reactors)