Food Waste Diversion from Landfills: A Cost–Benefit Analysis of Existing Technological Solutions Based on Greenhouse Gas Emissions
Abstract
:1. Introduction
2. Materials and Methods
2.1. Scenario 1: Waste Pick Up and Landfill Disposal
2.2. Scenario 2: Waste Pick Up and Centralized Composting
2.3. Scenario 3: Dehydrator and Centralized Composting
2.4. Scenario 4: On-Site ADLO, Poor BOD Reduction Performance
2.5. Scenario 5: On-Site ADLO, BOD Reduction as Per Literature Case Study
2.6. Scenario 6: In-Sink Waste Disposal, No BOD Reduction
2.7. Assumptions and Calculation Parameter Setting
3. Results
3.1. Techno-Economic Comparison of the Six Scenarios
3.2. Environmental Benefit Assessment
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Parameter | Setting/Value | Reference | Comments |
---|---|---|---|
BioStar accelerator medium (USD week−1) | 1.9 | [17] | Calculated from accelerator chip use (per kg of food waste) for ORCA machine in US case study. |
Enzyme formulation (USD week−1) | 1.2. | [17] | Calculated from enzyme use (per kg of food waste) for ORCA machine in US case study. |
Electricity cost (USD kWh−1) | 0.19 | [41] | Using average annual electricity bills of AUD 6000 for SMEs using 20,000 kWh (single rate) per annum in Victoria. Offers as of April 2018, GST inclusive. |
EX-30 machine electricity usage (kWh day−1) | 3.2 | [30] | |
EX-30 machine water usage (L day−1) | 278 | [30] | |
EX-30 water usage (kL day−1) | 0.278 | [30] | |
EX-30 water usage (kL week−1) | 1.67 | [30] | calculated assuming 6-day working week. |
EX-30 weekly energy usage (kWh week−1) | 19.2 | [30] | calculated assuming 6-day working week. |
EX-30 water usage (kL week−1) | 1.67 | [30] | calculated assuming 6-day working week. |
Water usage charge (USD kL−1) | 2.16 | [22] | |
Sewerage disposal charge (USD kL−1) | 1.37 | [22] | |
Trade waste usage volume charge (USD kL−1) | 0.65 | [22] | |
Trade waste usage BOD charge (USD kg−1 BOD) | 0.80 | [22] | |
Trade waste usage Total Kjendhal N charge (USD kg−1 N) | 1.53 | [22] | |
Trade waste usage SS charge (USD kg−1 SS) | 0.43 | [22] | |
Trade waste usage Inorganic TDS charge (USD kg−1 TDS) | 0.02 | [22] | |
Weight of food generated (kg week−1) | 180 | Assuming Ex-30 machine is operated at full capacity of 30 kg d−1 for 6 days a week. | |
Density of food (g L−1) | 500 | [8] | |
General food waste disposal costs (USD week−1) | 11.5 | [42] | For a 240 L bin. |
Organics food waste disposal cost (USD week−1) | 29.8 | [43] | For a 240 L bin. |
Volume of waste generated (L week−1) | 360 | Assuming food waste density of 500 g L−1. | |
Moisture content of food waste (%) | 75% | [44] | |
In-sink disposal water usage (kL week−1) | 2.4 | [31,45] | Using 4 L capita−1 day−1, assuming 3 meals capita−1 d−1, and 100 g food waste per meal and 1800 meals week−1. |
Insinkerator energy usage (Watts) | 370.0 | [46] | |
Insinkerator energy usage (KWh kg−1 food waste) | 0.037 | Assuming 3 h d−1 operation, 6 day week, 180 kg week−1 food waste. | |
Centralized composting electricity consumption (kWh tonne−1 food waste) | 300 | [34] | |
Dehydrator energy requirement (kWh kg−1 food waste) | 0.7 | [12] | |
COD of food waste (g COD kg−1 food waste) | 350 | [18] |
Parameter | Setting/Value | Reference | Comments |
---|---|---|---|
COD (g COD Kg−1 wet food waste) | 196 | [19] | Wet weight reduction of 44% in 1 day. Assumption that %COD reduction is the same as the %weight reduction. |
BOD (g BOD kg−1 wet food waste) | 98 | Using BOD:COD ratio of two in undigested food in Kim et al. 2015. | |
N (g N kg−1 wet food waste) | 4.1 | [47] | Assuming a COD:TotalN ratio of 48 for undigested food. |
SS (g SS kg−1 food waste) | 154 | [18] | Assuming ~56% solubilization and a food waste, moisture content of 75%. |
Inorganic TDS (g TDS kg−1 food waste) | 3.76 | [17] | Calculated from salinity of ORCA machine digestate, added water volume, and food load. |
Parameter | Setting/Value | Reference | Comments |
---|---|---|---|
BOD (g BOD kg−1 wet food waste) | 8.3 | [17] | Calculated from ORCA digestate BOD, added water volume and food load. |
N (g N kg−1 wet food waste) | 0.33 | Assuming similar N reduction and BOD reduction to BOD reduction. | |
SS (g SS kg−1 food waste) | 93.2 | [17] | Calculated from ORCA digestate TSS, added water volume and food load. |
Inorganic TDS (g TDS kg−1 food waste) | 3.76 | [17] | Calculated from salinity of ORCA machine digestate, added water volume, and food load. |
Parameter | Setting/Value | Reference | Comments |
---|---|---|---|
COD of food waste (g COD kg−1 wet food waste) | 350 | [18] | |
BOD (g BOD kg−1 wet food waste) | 175 | Using BOD:COD ratio of two in undigested food in Kim et al. 2015. | |
N (g N kg−1 wet food waste) | 7 | [47] | Assuming a COD:Total N ratio of 48 for undigested food. |
SS (g SS kg−1 food waste) | 250 | Assuming grinding reduces total solids to suspended solids. | |
Estimated inorganic TDS, Scenarios 3 and 4 (g TDS kg−1 food waste) | 3.76 | [17] | Calculated from salinity of ORCA machine digestate, added water volume, and food load. |
Water usage (L capita−1 day−1) | 4 | [31] | |
Customer food waste production (kg meal−1 day−1) | 0.1 | [47] |
Parameter | Setting/Value | Reference/Comments |
---|---|---|
Density of food waste (kg L−1) | 0.5 | [48] |
Truck fuel consumption (L km−1) | 0.345 | [49] |
Energy content of truck diesel fuel (MJ L−1) | 38.6 | [50] |
Truck CO2 emissions (kgCO2e (km−1 tonnes−1 of food) | 0.2 | [33] |
Distance to transfer station (km) | 15 | Estimate |
Distance between transfer station and landfill (km) | 15 | Estimate |
Moisture content of food (%) | 75% | [51] |
Garbage truck maximum weight load (Tonnes) | 24 | [52] |
CO2 equivalents from methane release (kgCO2e tonne−1 of food) | 2965 | [33] |
Anaerobic digester recoverable energy (kWh tonne−1 of waste) | 400 | [52] |
WWTP energy benchmark (kWh kg−1 COD removed) | 2.8 | [35] |
COD of food waste (g COD Kg−1 of food waste) | 350 | [18] |
Indirect CO2 equivalents from use of electricity in Victoria, Australia (kg CO2e kWh−1) | 1.08 | [53] |
Scenario | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | |||||||
In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | |
On site and/or Road Energy Use and output (kWh kg−1 food waste) | 0.0046 (a) | 0 | 0.3 | 0 | 0.70 | 0 | 0.11 | 0 | 0.11 | 0 | 0.04 | 0 |
Sewer+WWTP Energy use and output (kWh kg−1 food waste) | - | - | - | - | - | - | 0.55 (d) | 0.25 (c) | 0.05 (d) | 0.02 (c) | 0.98 (d) | 0.45 (c) |
Water (L kg−1 food waste) | - | - | - | - | - | - | 9.3 | 9.3 | 9.3 | 9.3 | 13.3 | 13.3 |
CO2 equivalents generated (b) (kgCO2e kg−1 food waste) | - | 3.0 | - | 0.32 | - | 0.76 | - | 0.70 | - | 0.17 | 1.1 |
Appendix B. Sample Calculations
Appendix B.1. Cost Calculations
Appendix B.1.1. Scenario 1: Landfill Base Case)
Appendix B.1.1.1. Required Bin Volume (L week−1)
Appendix B.1.1.2. Disposal Cost (USD week−1)
Appendix B.1.2. Scenario 5: ADLO with Performance and per US Case Study
Total Cost (USD week−1)
- (1)
- BioStar accelerator Cost (USD week−1)
- (2)
- Enzyme Cost (USD week−1)
- (3)
- Electricity Cost (USD week−1)
- (4)
- Water Cost (USD week−1)
- (5)
- Trade Waste Costs
- Trade Waste Volume Cost (USD week−1)
- Trade Waste BOD Cost (USD week−1)
- Trade Waste N Cost (USD week−1)
- Trade waste SS Cost (USD week−1)
- Trade waste TDS cost (USD week−1)
Appendix B.2. Energy, Water and CO2 Equivalents Estimates
Appendix B.2.1. Scenario 1: Landfill Base Case
Appendix B.2.1.1. Energy Required (kWh kg−1 Food Waste)
Appendix B.2.1.2. CO2e Generated (kg CO2e kg−1 Food Waste)
Appendix B.2.2. Scenario 5: ADLO with Performance and per US Case Study
Net CO2e
- (1)
- Total CO2e generated (kgCO2e kg−1)
- CO2e generated from COD at WWTP (kgCO2e kg−1 food waste)= Energy required for treatment at WWTP on COD basis (kWh kg−1 food waste) × indirect (scope 2) CO2e from use of electricity (kg CO2e kWh−1)
- CO2e generated from electricity used by ADLO machine (kg CO2e kg−1 food waste)
- CO2e generated from electricity used to pump the digestate to the WWTP (kWh L−1)
- (2)
- CO2e Saving due to Electricity Generation from Food Waste Methane at WWTP (kg CO2e kg−1 Food Waste)
Appendix B.2.3. Scenario 6
Water Usage (L kg−1 Food Waste)
- (1)
- Water usage per meal (L meal−1)
- (2)
- Restaurant meal frequency (meals d−1)
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Parameter | Acceptance Criteria Limit | Scenario 4 | Scenario 5 (Orca Digestate [17]) |
---|---|---|---|
pH | 6–10 | 5.1 (a) | 4.2 |
SS (mg L−1) | 10,000 | 97,000 | 67,000 |
Nitrogen (mg L−1 TNK) | 500 | 3333 | 286 (b) |
BOD (mg L−1) | 4000 | 70,000 | 6000 |
Scenario | Approximate Equipment Cost (USD) | Simple Payback Period (yr) | |
---|---|---|---|
Base Case: Landfill (Scenario 1) | Base Case: Centralized Composting (Scenario 2) | ||
3: (dehyd.+compost) | 20,000 | np * | 18 |
4: (ADLO worst case) | 7500 | np | np |
5: (ADLO best case) | 7500 | 48 | 4 |
6: (in-sink disposal) | 1200 | np | np |
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Sanciolo, P.; Rivera, E.; Navaratna, D.; Duke, M.C. Food Waste Diversion from Landfills: A Cost–Benefit Analysis of Existing Technological Solutions Based on Greenhouse Gas Emissions. Sustainability 2022, 14, 6753. https://doi.org/10.3390/su14116753
Sanciolo P, Rivera E, Navaratna D, Duke MC. Food Waste Diversion from Landfills: A Cost–Benefit Analysis of Existing Technological Solutions Based on Greenhouse Gas Emissions. Sustainability. 2022; 14(11):6753. https://doi.org/10.3390/su14116753
Chicago/Turabian StyleSanciolo, Peter, Eduardo Rivera, Dimuth Navaratna, and Mikel C. Duke. 2022. "Food Waste Diversion from Landfills: A Cost–Benefit Analysis of Existing Technological Solutions Based on Greenhouse Gas Emissions" Sustainability 14, no. 11: 6753. https://doi.org/10.3390/su14116753