Metal Removal Capabilities of Passive Bioreactor Systems: Effects of Organic Matter and Microbial Population Dynamics

Principal Investigator:Linda Figueroa, Associate Professor of Environmental Science & Engineering1

Project TeamDianne Ahmann1 Miranda Logan1

George Aiken4 Marie-Helene Robustelli1David Blowes3 Jason Seyler1

Kenneth Carlson2 �Paolo Hemsi2Nancy DuTeau2 Sriram Ananthanarayan2

Donald Macalady1

Kenneth Reardon2

Charles Shackleford2

Thomas Wildeman1

Sandra Woods2

1Colorado School of Mines2Colorado State University3University of Waterloo4USGS, Boulder

Rocky Mountain Regional Hazardous Substance Research CenterProject 3

Motivation & Need

! All states in Region 8 have environmental problems associated with historic and current mining operations

Issues associated with environmental impacts include:

! Cost effective technologies to clean up mine waste sites

! Less costly and more rational clean–up strategies

WaybrantWaybrant, , BlowesBlowes and and Ptacek Ptacek 19981998

Passive barrierPassive barrier

Research goals & objectives

Goal

The overall goal of this project is to evaluate the effect of organic matter characteristic on microbial population distributions and metal concentration in passive reactive zones and develop modeling tools for design and analysis.

Objectives

1. To evaluate the physical, chemical and biological compositionof the components used to create the permeable reactive zones.2. To determine the effect of the organic substrate characteristics on effluent metal concentration.3. To determine the effect of the substrate and time on variations in microbial population.4. To evaluate the use of mathematical models to relate metal removal and transport to various system parameters.

Approach

Approach

Limitations of previous research have included:

Focus on initial metal removal rates rather than on performance longevity

Limited examination of only sulfate-reducing bacteria

Lack of systematic design protocol (e.g., substrate selection and residence time)

No modeling tool to facilitate design and analysis

Tasks

Tasks that we have initiated are:

Characterization of chemical, physical and biological characteristics of substrate material.

Correlation of substrate characteristics to sustainable activity of sulfate reduction coupled with metals removal in mini-column experiments.

Investigation of the microbial community structure using activity and molecular methods. Target organism are sulfate reducers and non-sulfate-reducing microbial groups, such as cellulolytic bacteria,fermenters, syntrophs, and methanogens

Development of a specific mathematical model that captures the most important aspects of the processes and a numerical implementation of this mathematical model. This implemented model is expected to be added as a new “package” to an existing transport model. Finally, this numerical model will be tested for different conditions, including porous media

Substrate characterization

91.00.180.5826.0Column mixture

1000.0020.0246.0Wood shavings

----Sand

----Limestone

33.30.540.5519.3Inoculum

64.40.3 – 0.6*1.1523.7Dairy manure

99.00.5 – 0.8* 3.1743.0Alfalfa

VS / TS

(%)

Total P

(%)

Total N

(%)

Total org. C

(%)

Component

Sorption experiments

Experimental plan:The study focused on zinc and its sorption by five substrates : one inorganic (limestone) and four organic (wood shavings, brew waste, walnut hulls, and manure).

For each substrate, samples, run in duplicate, are prepared with a known quantity of material and a known ZnSO4 concentration. The volume of ZnSO4 added in each sample is 100 ml. A blank with 100 ml of DI water and a known quantity of substrate is also prepared. All samples are agitated for 24 hours at room temperature. They are then centrifuged, filtered, and acidified before ICP analysis.

Sorption experiments

Theory:The data were fit to a linear

approximation of the Langmuirmodel defined by :

q = K0* ce

Where :q = sorbed quantity

(mg of metal per g of substrate)

K1 = Langmuir adsorption constant

Q = maximum number of sorption site

K0 = K1 * Q (L/g)

Sorption experiment results

Manure sorption

y = 0.9054xR2 = 0.687

0123456789

10

0 2 4 6 8 10 12

Ce (mg/L)

q (m

g/g)

Sorption experiments

Comparative zinc sorption capacities of:Wood shavings, Walnut hulls & Brew waste

y = 0.025x

R2 = 0.9788

y = 0.0111x

R2 = 0.8531

y = 0.1661x

R2 = 0.8206

0

0.1

0.2

0.3

0.4

0.5

0.6

0 5 10 15 20 25 30

Ce (mg/L)

q (m

g/g)

wood shavings walnut hulls brew waste

Column team

Pilot column experiments

Pilot Column Material:

(based on dry weight) 20 % dairy manure 15 % walnut wood shavings10 % alfalfa

5 % wetland inoculum 45 % silica sand (#8 mesh) 5 % limestone

Pilot Column Specifications:Volume = 589 cm3

Mixed material per columns = 520 gramsDry weight per column = 185 gramsFlow rate = 220 ml/dayEstimated hydraulic residence time = 3 days

Pilot Column Influent:

Dinero Tunnel mine drainage, Leadville, CO

Contains 36.6 mg/L Mn, 9.8 mg/L Zn,and 125 mg/L SO4, pH 5.96

Iron

0

10

20

30

0 10 20 30Days

mg/

L ABC

Zinc

0

5

10

0 10 20 30Days

mg/

L ABC

Influent

Manganese

0

15

30

45

0 10 20 30Days

mg/

L

ABC

Sulfur

0

50

100

150

0 10 20 30Days

mg/

L ABC

Pilot Column ResultsPilot Column Results

Microbial Framework

CH4

NOM(cellulose, lignin,

etc.)

Monomers(glucose, etc.)

Fatty Acids

(lactate)

H2 Methanogens

FermentersSyntrophs

Sulfate-reducers

SO42-

H2SMe2+

MeS(s)

AcetateCO2

Oligomers(cellobiose,

etc.)

Hydrolysis

Hydrolysis

Pilot column experiments

Total Sulfur - Pilot Column 110 mM Acetate Pulse

0

50

100

150

200

250

300

8 9 10 11 12 13 14 15 16 17 18

Days

mg/

L

Total Sulfur - Pilot Column 25 mM Acetate Pulse

0

50

100

150

200

250

300

8 9 10 11 12 13 14 15 16 17 18

Days

mg/

L

Total Sulfur - Pilot Column 31 mM Acetate Pulse

0

50

100

150

200

250

300

8 9 10 11 12 13 14 15 16 17 18

Days

mg/

L

One day acetate pulse into One day acetate pulse into pilot columnspilot columns

Mini column experimentscommunity interactions

Mini-Column Material:(based on dry weight) 30 % walnut wood shavings 10 % brewery waste 5 % dairy manure5 % wetland inoculum 5 % limestone (#10 mesh)45 % silica sand (#8 mesh)

Mini-Column Specifications:Volume = 40 cm3

Mixed material per column = 19 gramsDry weight per column = 17 gramsFlow rate = 24 ml/dayEstimated hydraulic residence time = 1 day

Mini-Column Influent:Simulated mine drainage mixture comprised of 50mg/L Fe, Mn, and Zn, and 1400 mg/L SO4, pH 6.0Influent sparged with nitrogen to minimize oxidation of Fe

Mini column experimentscommunity interactions

Effluent S5 mM Lactate Pulse

0

100

200

300

400

500

600

700

0 5 10 15 20 25 30 35 40 45Days

Con

cent

ratio

n (m

g/L)

78

pulsestart mine water

influent = 475 mg/L

Mini column experimentssubstrate comparisons

MethodsSubstrates used: Walnut Hulls, Corn Cobs, Brewery Waste, Walnut Wood ShavingsColumns contain individual substrates and are run in duplicate. Simulated mine water comprised of: 50mg/l of Fe, Mn, Zn, and 1400 mg/l SO4

The flow rate through the columns was 24ml/day

Hydraulic residence time approximately 1.0 daysMetals and Total Sulfur were measured on an ICP To prevent volatilization of sulfide gas the effluent was maintained at a pH of 9.0

Influent was sparged with nitrogen to minimize oxidation/precipitation of Iron

Column Description5 grams of each substrate (dry wt basis)

5 % of an inoculum/manure combination mixed in with substrate 5 grams of limestone #10 mesh# 8 mesh sand filling the remaining volume

Mini column experimentssubstrate comparisons

Total Mn

0

10

20

30

40

50

60

70

80

90

0 5 10 15 20 25 30

H1H2C1C2B1B2W1W2

Mini column experimentssubstrate comparisons

Total Zn

0

1

2

3

4

5

6

7

8

9

0 5 10 15 20 25 30

H1H2C1C2B1B2W1W2

Microbial modeling

complex organicsXCÕ

soluble organics, SS1

acetic acid, SS2

carbon dioxide and methane, Sm

Hydrolysis

Acidogenesis

Methanogenesis

Sulfidogenesis

Level 1 schematicLevel 1 schematic

Microbial modeling

Level 1 model

1. Solubilization of cellulose to glucose via extracellular enzymes produced by fermenter

2. Fermentation of glucose to acetate

3. Growth of SRB on acetate

4. Growth of Methanogens on acetate

Microbial modeling

Hydrolysis

(n )(C6H10O5) + H2O = (n-1)(C6H10O5) + C6H12O6

Fermentation

C6H12O6 + 0.336 NH4+

=> 0.336 C5H7O2N + 1.007 H2 +2.158 C2H3O2– + 2.494 H+

Sulfate reduction

C2H3O2– +0.032NH4

+ +1.888 H+ + 0.92 SO42–

=> 0.032 C5H7O2N +1.36 H2O + 1.84 CO2 + 0.92 HS–

Methanogenesis

C2H3O2– +0.02 NH4

+ + 0.8896 H2O + 0.9 H+

=> 0.02 C5H7O2N + 0.9504 CH4 + 1.0096 CO2

Level 1 Level 1 stoichiometriesstoichiometries

Microbial modeling

fermentative growth µfSS1

Ksf +SS1

XB, f

fermenter decay bf XB, f

hydrolysis of cellulose kh

XC'XB, f

Kx,C + XC'XB, f

XB, f

SRB growth µsrSS2

Ksr +SS2

XB, sr

SRB decay bsrXB,sr

Methanogen growth µmSS2

Km +SS2

XB,m

Methanogen decay bmXm

Level 1 process modelsLevel 1 process models

Microbial modeling

ComponentsSS1 = glucoseXC' = cellulose available = function of d2, XC,XL)XL = lignind = nominal particle sizeXC = cellulose totalX B,f = fermenter biomassX B,sr = SRB biomassX B,m = methanogen biomassSS2 = acetateSm = methaneSalk = alkalinitySSO = sulfate

Parametersµf = maximum specific growth rate of fermentersbf = decay constant of fermentersKsf = half-saturation constant of fermenterskhc = hydrolysis rate of cellulosekhs = hydrolysis rate of particulate organicsKxf = hydrolysis saturation ratio for celluloseKcf = hydrolysis saturation ratio for particulate organicsµsr = maximum specific growth rate of SRBKsr = half-saturation constant of SRBbsr = decay constant for SRBµm = maximum specific growth rate of methanogensKm = half-saturation constant of methanogensbm = decay constant for methanogens

Level 1 components and parametersLevel 1 components and parameters

Microbial modelingLevel 2 schematicLevel 2 schematic

CH4

NOM(cellulose, lignin,

etc.)

Monomers(glucose, etc.)

Fatty Acids

(lactate)

H2 Methanogens

FermentersSyntrophs

Sulfate-reducers

SO42-

H2S Me2+

MeS(s)

AcetateCO2

Oligomers(cellobiose,

etc.)

Hydrolysis

Hydrolysis

Microbial modeling

Level 2 model1. Solubilization of cellulose to cellobiose via extracellular enzymes produced by fermenters

2. Solubilization of cellobiose to glucose via extracellular enzymes produced by fermenters

3. Fermentation of glucose to lactate

4. Fermentation of glucose to lactate and hydrogen

5. Fermentation of lactate to acetate

6. Fermentation of lactate to acetate and hydrogen

7. Growth of SRB on lactate

8. Growth of SRB on hydrogen

9. Growth of SRB on acetate

10. Growth of Methanogens on acetate

11. Growth of Methanogens on hydrogen

System Model

System Model

System Modeling Approach

! Development of unique numerical model of anaerobic biodegradation of organic substrates and microbially facilitated precipitation of metals

! Numerical simulations will be done using USGS MODFLOW2000 and MT3DMS

Ongoing and Future work

Ongoing and Future Work- Continue pulse experiments with more replicates, negative controls, larger pulse concentrations, more frequent sampling, and increased hydraulic residence times- Analyze samples on IC to determine sulfur speciation- Use results of slow-step characterization to further investigate relevant microbial activities

Modeling

-Continue calibration of existing flow models

- Develop stoichiometries and process equations for Level 2 microbial model

-Develop numerical model for microbial processes

Substrate characterization- Examine correlation between biodegradability and sulfate reducing activity relative to substrate components of soluble sugar and starch, protein, cellulose/hemicellulose, lignin

- Analyze the initial sulfate reduction potential of each substrate.

- Determine the longevity of each substrate.

- Measure the sorption characteristics of each substrate on all three metals of concern.

- Identify the most effective residence time for each substrate.

- Modify experimental set-up for gas collection, which will facilitate mass balance analysis and alleviate pressure buildup.

Ongoing and Future work

Ongoing and Future Work- Continue pulse experiments with more replicates, negative controls, larger pulse concentrations, more frequent sampling, and increased hydraulic residence times- Analyze samples on IC to determine sulfur speciation- Use results of slow-step characterization to further investigate relevant microbial activities

Microbial activity

-Continue pulse experiments with more replicates, negative controls, larger pulse concentrations, more frequent sampling, and increased hydraulicresidence times

-Analyze samples on IC to determine sulfur speciation

- Use results of slow-step characterization to further investigate relevant microbial activities

- Apply molecular tools in conjunction with activity measurements

SorptionFurther work is needed to establish the sorption capacity for

- other substrates,

- for the complete range of expected of metal concentrations

- for other metals