Converting Farm Waste to Energy A Primer of Anaerobic Digestion of

Dairy Waste

S.J. Grimberg

Dept. Civil Environmental Eng.Clarkson University, Potsdam, NY

U.S. Energy Consumption by SourceUS Primary Energy Consumption

To get 1000 MW electrical:Method Investment needed Photovoltaic 100 km2 @ 10% efficiency (40 sq. miles)

Windmills 6,660 wind turbines @ 150 kW (20 m blades)666 wind turbines @ 1.5 MW (40 m blades)

Biogas 7,143,000 cows 60,000,000 pigs800,000,000 chickens

Bioalcohol 6,200 km2 of sugar beets (2,400 sq. miles) 7,400 km2 of potatoes (2,800 sq. miles) 16,100 km2 of corn (6,200 sq. miles) 272,000 km2 of wheat (104,00 sq. miles)

Bio-oil 24,000 km2 of rapeseed (9,000 sq. miles)

Biomass 30,000 km2 of wood (12,000 sq. miles)U. Mich.-Schwank

Source:Gottfried Besenbruch, General Atomics

Anaerobic Digestion of Manure• Biologically converts organic matter to

biogas– 55-68% CH4, 32-45% CO2, trace H2S – Biogas can be used as a fuel source for

engine generator sets or boilers. • Manure management

– Dairy manure produced in the U.S.: • Approx. 1x109 tons/year• Approx 4 million cows on farms with at

least 300 cows– Translates to 1.5x108 tons

manure /year– This could produce > 400 MW of

electric power– Odor reductions and nutrients– Reduction in fecal coliforms and

pathogens

U.S. Farm Digesters• Mostly single farm digesters

– Simple structures, often lack reliability– Poor treatment efficiency; i.e. high capital cost

http://www.biogas.psu.edu/othertypesmod.htmlhttp://www.nyserda.org/programs/Environment/ag&indwastemgt.asp

Anaerobic Digestion Process Schematic

Gas

Organic Composites

MS AA

HAc, HPr, HBu, HVa, NH3, CO2, LCFA

Acetate H2 CO2

CH4

CO2

CH4

H2

H2O

Liquid

Ac-, Pr-, Bu-, Va-, NH4+, HCO3

-, LCFA-

HCO3-

Gas

GasMicrobes

NH3 NH4+

Lipids Carb. Proteins Inerts

Dec

ayG

rowt

h

Physiochemical Processes

Bio

chem

ical

Pro

cess

es

Dairy Manure Characteristics

Parameter Mean ± standard deviation Total COD (mg/L) 92,736 ± 33,846 %TS 8.78 ± 1.78 %VS 6.18 ± 1.55 pH 7.6 Total VFA (mg/L) 14,251 ± 4,809 Acetate (mg/L) 7,817 ± 3,219 Propionate (mg/L) 3,336 ± 1,102 Isobutyrate(mg/L) 686 ± 145 Butyrate (mg/L) 1,043 ± 421 Isovalerate (mg/L) 658 ± 70 Valerate (mg/L) 708 ± 89

Microgy MicgogyMicgogy

Plug Flow Digester Example

AA Dairy has been meticulous in obtaining data for more than 6 years

• biogas production (total & per cow)• biogas composition (CO2 measurements)• oil consumption (daily)• electricity generated on the farm• electricity sold to the grid• difference between generated & sold is

electricity used on the farm

Odor Issues Defined by VFAs

0

5000

10000

15000

20000

25000

12-May 1-Jun 21-Jun 11-Jul 31-Jul 20-Aug

Con

cent

ratio

n (m

g/L)

Influent

Date

Acetic55%

Propionic23%

Isobutyric5%

Butyric7%

Isovaleric5%

Valeric5%

VFA distribution-

Acetic63%Propionic

37%

Effluent

Influent

Effluent

•VFA reduced in Digester•Stinkier Larger VFA molecules not found in effluent

-500

0

500

1000

1500

2000

2500

6/8/98 12/25/98 7/13/99 1/29/00 8/16/00 3/4/01 9/20/01 4/8/02 10/25/02 5/13/03

Net sold to the grid

Electricity generated and net electricity sold to the grid at AA Dairy per day (1998-2003)

Produced on Farm

-50 point moving average

kWhr

/day

Difference = Energy Used on the Farm

Date

Sheland Farms

Downtime Cost (lost revenue)Farm Load Supply Percentages (as installed)

-10

10

30

50

70

90

110

130

1 21 41 61 81 101 121 141 161Operating Time (Days)

Perc

ent O

f Loa

d (%

)

• By using remote smart grid protocols and monitoring, the uptime could be improved for an additional $12k per year over current operations.

Interesting Possibility: Co-generation w/ Food Wastes

–Benefits to farmerBenefits to farmer» Increased biogas productionIncreased biogas production» Improved gas quality (reduced Improved gas quality (reduced

concentrations of Hconcentrations of H22SS»““Tipping fees” can be substantialTipping fees” can be substantial

–Benefit for Food Waste Generators»Potential Savings for disposal

Need for improvement

• NY State incentives:– Limited to farmers only– Treatment of no more than 25% non farm waste

• Farm digester design largely empirical.– Cannot predict mixed waste performance

• A system model may significantly improve operation and design process.

ADM1: Modeling Anaerobic Digestion

• For any organic material (COD basis)• Potential to simulate mixed substrates

• Continuous flow stirred tank reactor (CSTR)

• Plug flow reactors can be simulated using reactors in series.

• Includes:• 26 mass balances• 19 biochemical kinetic processes• 3 gas liquid transfer kinetic processes

• Requires numerous stoichiometric and kinetic constants

• Readily available data however:• Waste COD• Total VFA• Biogas composition

Approach• Develop a simplified input data set using the laboratory

data (Page et al, 2008)• Develop and validate model parameter set using

laboratory and full scale steady state data using trial and error approach (Page et al, 2008).– With good results for primary parameters but could not predict

reaction intermediates• Develop parameter set to simulate pilot digester

operated at non-steady state using detailed measurements and optimization routines

Pilot plant

Time [days]

0 20 40 60 80 100

Effl

uent

CO

D [g

/L]

0

20

40

60

80

100

Measurements Prediction (Page et al. 2008) Prediction this study

COD Removal

Average Influent COD: 92.7±43.0 g/LAverage Effluent COD: 45.5±16.2 g/L

Biogas Results

Time [days]

0 20 40 60 80 100

Bio

gas

Flow

[m3 /d

]

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Measurements Prediction (Page et al. 2008) Prediction this study

Time [days]

0 20 40 60 80 100

Met

hane

Con

tent

[%]

0

20

40

60

80

100

Measurements Prediction (Page et al. 2008) Prediction this study

Average CH4 content: 57%

Volatile Fatty Acids

Time [days]

20 30 40 50 60 70 80 90

Ace

tate

Con

cent

ratio

n [g

/L]

0

2

4

10

15

20

Measurements Prediction (Page et al.2008) Prediction this study

Time [days]

0 20 40 60 80 100

Pro

prio

nate

Con

cent

ratio

n [g

/L]

0.001

0.01

0.1

1

10

Measurements Prediction (Page et al. 2008) Prediction this study

Conclusions • Anaerobic digestion of farm waste represents a good

opportunity for farmers to generate revenues and reduce energy needs

• Mixing dairy wastes with other wastes improves process economics

• Models needed that can handle mixed waste to optimize design• Calibration of the wastewater model provided encouraging

results. concentration, and ammonia.

Acknowledgements• Students:

– David Page, O’Brian and Gere, Syracuse, NY– Ben Durfee, Stearns and Wheler, LLC– Shawn Jones, SUNY Canton, summer research student Clarkson University– Ying Zhang, Yunghui Deng, MS students Clarkson University– Mark Venczel, Rajiv Narula, PhD students, Clarkson University– Noelle du Juvigny, Institut Polytechnique LaSalle Beauvais, France– Alex Maxwell, summer research student Clarkson University

• Drs. Powers, Pillay, Welsh and Thatcher

• North Harbor Dairy• Drs. Christian Rosen, Darko Vrecko and Ulf Jeppsson (all Lund University) for providing the

Matlab ADM1 code.

• Funding Sources: USDA, DOE, New York Ag and Markets, NYSERDA

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