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Fecal Sludge To Energy in a Prototype
Supercritical Water Oxidation Reactor
Marc A. DESHUSSESDepartment of Civil and Environmental Engineering
Duke University, Durham, North Carolina
Open defecation… = everyday business
for about 1,100,000,000 people
2.4 billion people do not have access to
“improved” sanitation
© Bill & Melinda Gates Foundation | 4
Source: WSP analysis, using BMGF funded research
Illegally
dumped
Not effectively
treated
Effectively
treated
Drainage systems Receiving waters
9% 9% 9%1%
Leakage
Unsafely emptied
Safely emptied
Left to overflow
or abandoned
69%1%
Residential environment
79%On-site
facility
20%WC to
sewer
1%Open defecation
Untreated sludge ends in the environment (Dhaka, Bangladesh)
“INSTITUTIONAL” OPEN DEFECATION
2%
98%of fecal sludge
unsafely disposed
2%of fecal sludge
safely disposed
WSH STRATEGY
AND PRIORITIES
Confined Animal Feeding Operations (CAFOs)
= as much waste as a small town
Issues: organics and nitrogen
management, methane and odor
emissions, antibiotic resistant
bacteria, very low cost margins
• 8600 hogs
• 1400 m3 manure/week
• 17 tons COD/week
• 1.6 tons N/week
• 0.6 tons P/week8600 m3
anaerobic digester
Feces: 70-520 g/(p day) ~ 80% moisture
• Fats (5-25%)
• Carbohydrates (10-30 %)
• Nitrogenous materials (2-3%)
• Minerals (5-8%)
• Bacteria and bacterial debris (10-30%)
Where all pathogens and most of the energy is
~80 gdry , 107 g COD, ~2 g N, 1.6 MJ / (p day)
Content of Fecal Waste
Urine: 0.6 – 1.1 L/(p day)
•Organic salts (38%)
•Urea (36%)
•Organic compounds (13%)
•Ammonium salts (13%)
Contains most of the nitrogen ~7 gN/(p day)
and P ~1gP/(p d)
~440 W h/(p d)
This is a 87 kWh
dump!!!
Our Vision: Omni Processor for Fecal Waste
Sanitation for the urban poor using supercritical water
oxidation (SCWO)
Pit Latrine Collection & Transport Businesses
Supercritical treatment facility, 20 ft. container for ~1000 people
(~450-530 kWh/d)
In supercritical water, organics are rapidly
oxidized (in seconds) resulting in heat, and CO2
Benefits
o Very fast reaction (sec.)
o High conversion
to CO2 + clean water
o No SOx, NOx or odor
o No need to dry waste
o Can co-treat haz. wastes
Technical risks
o Corrosion
o Salts deposition/plugging
Pilot unit at Duke
- Heat and energy recovery
- Metallurgy and corrosion
- Process control
- Slurry pumping
System Characteristics
Basic characteristics
• 100-150 kg dry/day
• 1-2 m3/day
• Assume feed ~7-15% solids
• Reactor ID: 19 mm
• Reactor length: 4.0 m
• Heat exchanger length: 39 m
• Reynolds #: 30,000 – 60,000
• Residence time in reaction
section = 2.5 to 4.5 seconds!
Anti corrosion and plugging
measures
• High Re number, slight down
slope
• Minimize transition zones
• Reactor and part of heat
exchanger in Inconel 625
• Tandem HEPS
• Periodic maintenance
Other
• Startup with isopropyl alcohol (IPA)
but any other liquid fuel will work
• Air is used as oxidant
Pilot unit construction
Process Flow Diagram
Fecal sludge
(+co-fuel)
Air
(Furnace)
ReactorGas-liquid-solid separators
CO2, N2, O2
Clean water out
Water loop
Solids
Air-water mixture
0
10
20
30
40
Heat to 400 C
supercritical
Heat of
combusion
Po
wer
(k
W)
50 kgwet/h, 10% solids basis
Air-water preheat
Pilot unit construction
Fecal
Simulant
(lab only)
High solids-content (16%)
secondary sludge
Ash content: 24%
HHV: 15 MJ/kgdry
SCWO Feedstocks Processed
Isopropanol
(IPA)
Starter and
model fuel Dried chicken manure
HHV: 12 MJ/kgdry
Used as surrogates for
human fecal waste
(8-15% solids)Dog feces
HHV: 15.7 MJ/kgdry
Test run with 1.3% isopropanol
Typical IPA run: 99.9% removal
System Characterization with IPA
Effect of n: Stoichiometric factor of O2
84
86
88
90
92
94
96
98
100
102
0.0 0.5 1.0 1.5 2.0 2.5
Re
mo
val (
%)
O2 Stoichiometric factor (-)
COD Removal
IPA Removal
System Characterization with IPA
Calorific
content of
feed
increases
Secondary Sludge Treatment
Feed
EffluentEffluent
After settlingFeed
Biosolids as
received
(14 MJ/kg dry)
Slurry feed:
4.3% biosolids
9% IPA
Secondary Sludge Treatment
• IPA run - 3.2
MJ/kg
• Sludge run –
2.4 MJ/kg from
IPA + 0.8 MJ/kg
from sludge
T = 586 ± 4.9 °CT = 577 ± 12.2 °CT = 475 ± 17.5 °CT = 462 ± 7.3 °CT = 219 ± 0.8 °CT = 204 ± 8.0 °C
T after reaction
Secondary Sludge Treatment Summary
Removal (%)
99.97
98.12
98.60
Influent Effluent
Analysis (9.6% IPA) Steady State
COD (mg/L) 183667 50
IPA
Removal (%)
99.97
Influent Effluent
Analysis (3% sludge + 9% IPA) Steady State
COD (mg/L) 214000 70
Total N (mg/L) 10875 200
NH3 (mg/L) 443 17.6
NO3-(mg/L) 183 15.9
NO2-(mg/L) 14.9 0.4
PO4-3
(mg/L) 4930 67.9
pH 6.8 7.02
Conductivity (?S/cm) 2560 659
Sludge +IPA
Dog Feces Treatment Slurry feed pre-processing:
14% solids (15.7 MJ/kg dry)
Effluent
Feed10% solids
+ 4% IPA
Fresh Dog Feces Treatment Summary
Removal (%)
99.97-99.85
95.32-91.70
99.91-99.56
Influent Effluent
Analysis (10% sludge + 4% IPA) Steady State
COD (mg/L) 192276 65-280
Total N (mg/L) 4704 220-420
NH3 (mg/L) 627.2 185-325
NO3-(mg/L) 98 0.3-0.8
NO2-(mg/L) 22.54 0.04-0.54
PO4-3
(mg/L) 14543.2 13.4-63.9
pH 5.95 -
Conductivity (µS/cm) 4500 -
Dog poop +IPA
Treatment of Micro PollutantsExperimental Approach
• Spiked trace contaminants during a run
• Used high concentrations of Triclosan, Acetaminophen, and
Ibuprofen
• Run with spiked IPA first, then spiked dog feces and IPA
Results
• Ibuprofen and acetaminophen (10 mg/L each) – not analyzed yet
• Triclosan:
Relevant concentration: 0.5 – 1 µg/L
Concentration spiked: 100 µg/L
Concentration in effluent (IPA treatment): ND at < 0.1 µg/L
Concentration in effluent (dog feces + IPA treatment ): < 0.1 µg/L
Removal > 99.99%
Modeling Studies• Develop a conceptual model of the process (with reaction
kinetics, mass and energy balances)
• Use model to:
– Conduct data analysis
– Explore process sensitivity
– Process optimization and design
• Methods: Aspen Plus
– Peng-Robinson equation of state
– Plug flow kinetic reactor (Rplug)
– Heat exchangers sizing using the Exchanger Design and
Rating (EDR) tool
2𝐶3𝐻8𝑂 + 9𝑂2 → 8𝐻2𝑂 + 6𝐶𝑂2𝐶3𝐻8𝑂 + 3𝑂2 → 4𝐻2𝑂 + 3𝐶𝑂2𝐶𝑂 + 𝑂2 → 2𝐶𝑂2
𝑟𝑖= 𝑘𝑒 Τ−𝐸𝑎 𝑅𝑇𝐶𝐼𝑃𝐴𝐶𝑂2
Reactions (IPA)
Modeling the Heat Exchangers
Exp. Model
U (W/m2-K) 196-205 367
Q (kW) 47-49 51
LMTD (K) 114 65
Shell side
Tube side
Exp. Model
U (W/m2-K) 90-124 89
Q (kw) 3.6-4.9 4.1
LMTD 33 39
Modeling the Heat Exchangers
Shell side
Tube side
Adding Heat Losses to the System
Model vs. Experiments
We are currently using the model
to optimize process design and
operation using a factorial
approach
Motor
Size (kW)
Duty
Cycle
Actual
Power (kW)
Motor
Size (kW)
Duty
Cycle
Actual
Power (kW)
Furnace 15 5% 0.75 Furnace 15 90% 13.5
Air Compressor 11.2 80% 9.0 Air Compressor 11.2 80% 9.0
Water Pump 3.7 50% 1.9 Water Pump 3.7 50% 1.9
Biomass Pump 11 15% 1.7 Biomass Pump 11 15% 1.7
PC Pump 0.56 60% 0.34 PC Pump 0.56 60% 0.34
PLC and Sensors 1 100% 1 PLC and Sensors 1 100% 1
Steam Generation -4 100% -4 Net Electric Power Draw (kW): 27.3
Gaseous Expansion -0.1 100% -0.1 Gasoline Equilivance* (gal/day): 49
Net Electric Power Draw (kW): 10.4
Gasoline Equilivance* (gal/day): 18
Current and Projected Energy Balance
Currently not
autothermal:
But we have 17
kW heat loss in
final cooling and
~10 kW heat
losses around
the reactor
Optimized design:
• Turn of furnace (autothermal)
• Recover energy from gas expansion (3-6 kW)
Expected draw ~6-10 kW
Produce 5-10 kW as heat
Some Lessons LearnedDesign
• Pumping slurries at low flow and high pressure is a challenge
• Compression fittings in temperature zones
above 350 °C = high failure rate
Operation
• Capillary depressurization system is difficult to control during
start up and shut down but
work well otherwise
• Foam in the HEPS can affect
level sensor reading
Modeling
• Losses play a crucial role,
requires some tricks in Aspen
Concluding Remarks: Why I am Optimistic…
• SCWO achieves both waste treatment and pathogen
control extremely fast. We can even co-treat
hazardous wastes and produce clean water, without
odor, SOx, or NOx emissions…
• Selling “high value added” by products can be a driver
Sell a 10 L shower 5-10 cents
= $1.7-3.4 per kWh!
• But many challenges remain…
AcknowledgmentsGates Foundation and USDA
for fundingDeshusses lab
[email protected] http://sanitation.pratt.duke.edu/