Foodservice Methodology
Scope Boundary
This diagram communicates the scope boundary as aligned with the Food Loss and Waste Accounting and Reporting Standard[17]. Note that ReFED’s analysis also includes food sent to donations, although donations are not considered a destination within the Standard.
- NOTES
“Food Donation” has been added as a Destination
“Biomaterial Processing is referred to as “Industrial Uses” in our model
“Co/anaerobic digestion” is referred to as “Anaerobic digestion” in our model
“Controlled Combustion” is referred to as “Incineration” in our model
“Refuse/discards” is referred to as “Dumping” in our model
Calculations
Surplus Food Calculations
In ReFED’s data model, the following calculations are repeated for every state, year, and foodservice segment before any aggregation is done.
DATA ITEM |
DATA SOURCE OR CALCULATION |
EXAMPLE |
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|---|---|---|---|
SUPPLIER PURCHASES AND CUSTOMER SALES |
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% National Purchases from Suppliers |
Technomic Ignite Platform[43] |
$__foodservice_example_national_supplier_purchases__ U.S. __foodservice_example_sub_sector_category__ location purchases from suppliers and distributors |
|
% National US Dollars Sold |
Technomic Ignite Platform[43] |
$__foodservice_example_national_dollars_sold__ U.S. __foodservice_example_sub_sector_category__ location sales |
|
State % Share of Supplier Purchases |
= # State Locations for Top 500 Restaurants[43] / # US Locations for Top 500 Restaurants[43] |
__foodservice_example_percent_of_locations__% of U.S. __foodservice_example_sub_sector_category__ locations in __foodservice_example_state__ for Top 500 Restaurants |
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% In-scope Igredients |
ReFED Calculation
See Appendix O for more information
|
ReFED estimates the following breakdown for menu ingredients:
__foodservice_example_in_scope_ingredients__%
|
|
US Dollars State Supplier Purchases |
= National Purchases from Suppliers * State % Share of Supplier Purchases * % In-scope Ingredients |
$__foodservice_example_national_supplier_purchases__ U.S. __foodservice_example_sub_sector_category__ location purchases * __foodservice_example_percent_of_locations__% __foodservice_example_state__ market share * __foodservice_example_in_scope_ingredients__% in-scope
= $__TODO_foodservice_example_state_supplier_purchases__ estimated __foodservice_example_sub_sector_category__ location purchases in __foodservice_example_state__
|
|
US Dollars Sold |
= National Purchases from Suppliers * State % Share of Supplier Purchases * % In-scope Ingredients |
$__foodservice_example_national_dollars_sold__ U.S. __foodservice_example_sub_sector_category__ location sales * __foodservice_example_percent_of_locations__% __foodservice_example_state__ market share * __foodservice_example_in_scope_ingredients__% in-scope
= $__foodservice_example_us_dollars_sold__ estimated __foodservice_example_sub_sector_category__ location sales in __foodservice_example_state__
|
|
Wholesale Price per Lb |
ReFED Calculation
See Appendix O for more information
|
ReFED estimates that the average wholesale price of food for __foodservice_example_sub_sector_category__ locations in __foodservice_example_year__ was $__TODO_foodservice_example_wholesale_price__ per lb. |
|
State Tons Supplier Purchases |
= US Dollars State Supplier Purchases / Wholesale Price per Lb / 2,000 Lbs per ton |
= $__TODO_foodservice_example_state_supplier_purchases__ state supplier purchases / $__TODO_foodservice_example_wholesale_price__ per lb / 2,000 lbs per ton
= __foodservice_example_tons_supply__ tons of food purchased from suppliers for __foodservice_example_sub_sector_category__ locations in __foodservice_example_state__
|
|
Pre-Consumer Surplus Rate |
LeanPath[30] |
__foodservice_example_leanpath_surplus_rate__% of food spend not utilized by kitchens |
|
Tons Sold |
= State Tons Supplier Purchases * ( 100% - Pre-Consumer Surplus Rate ) |
= __foodservice_example_tons_supply__ tons of food purchased from suppliers * (100% - __foodservice_example_leanpath_surplus_rate__% )
= __foodservice_example_tons_sold__ tons sold to customers at __foodservice_example_sub_sector_category__ locations in __foodservice_example_state__
|
|
PRE-CONSUMER FOOD SURPLUS |
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Tons Pre-Consumer Surplus |
= State Tons Supplier Purchases * Pre-Consumer Surplus Rate |
= __foodservice_example_tons_supply__ tons food purchased from suppliers * __foodservice_example_leanpath_surplus_rate__% surplus rate
= __foodservice_example_tons_preconsumer_surplus__ tons pre-consumer surplus at __foodservice_example_sub_sector_category__ locations in __foodservice_example_state__
|
|
% of Pre-Consumer Surplus that is Overproduction |
LeanPath[30] |
__foodservice_example_percent_preconsumer_overproduction__% of pre-consumer surplus for the __foodservice_example_sub_sector__ sector is due to overproduction. |
|
Tons Overproduction |
= Tons Pre-Consumer Surplus * % of Pre-Consumer Surplus that is Overproduction |
= __foodservice_example_tons_preconsumer_surplus__ tons pre-consumer surplus * __foodservice_example_percent_preconsumer_overproduction__% overproduction
= __TODO_foodservice_example_tons_preconsumer_overproduction__ tons Overproduction
|
|
Retail Price per Lb |
= US Dollars Sold / Tons Sold / 2,000 lbs per ton |
= $__foodservice_example_us_dollars_sold__ sold / __foodservice_example_tons_sold__ tons sold / 2,000 lbs per ton
= $__TODO_foodservice_example_retail_price__ retail value per lb sold
|
|
US Dollars Overproduction |
= Tons Overproduction * Retail Price per Lb
Note: Overproduction is valued at retail rather than wholesale price, because it is ready to sell to a customer.
|
= __TODO_foodservice_example_tons_preconsumer_overproduction__ tons overproduction * $__TODO_foodservice_example_retail_price__ retail value per lb sold * 2,000 lbs per ton
= $__TODO_foodservice_example_dollars_preconsumer_overproduction__ overproduction
|
|
Tons Pre-Consumer Surplus (excluding Overproduction) |
= Tons Pre-Consumer Surplus - Tons Overproduction |
= __foodservice_example_tons_preconsumer_surplus__ tons Pre-Consumer Surplus - __TODO_foodservice_example_tons_preconsumer_overproduction__ tons Overproduction
= __foodservice_example_tons_preconsumer_surplus_excluding_overproduction__ tons Pre-Consumer Surplus (excluding Overproduction) at __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
|
US Dollars Pre-Consumer Surplus by Food Type (excluding Overproduction) |
= Sum for all Food Categories[Tons Pre-Consumer Surplus (excluding overproduction) * % Food Type * Wholesale Price per Lb] * 2,000 lbs per ton |
Note: Values Vary by Food Type
= Sum for all Food Types[ (X tons Pre-Consumer Surplus * Y% Food Type * $Z Wholesale Price per lb) * 2,000 lbs per ton ]
= $__foodservice_example_dollars_preconsumer_surplus__
|
|
CATERING OVERPRODUCTION |
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Breakdown of Sales by Customer Distribution Channel |
Technomic Ignite Platform[43] |
For __foodservice_example_sub_sector_category__ locations in __foodservice_example_year__:
Take-out: __foodservice_example_percent_takeout__%
Onsite Dining: __foodservice_example_percent_onsite__%
Catering: __foodservice_example_percent_catering__%
——————-
Total: 100%
|
|
% Catering Overproduction |
ReFED Expert Interviews
See Appendix Q for more information
|
Experts estimate that __foodservice_example_percent_catering_overproduction_rate__% of food is typically left unserved at breakfast or lunch catering events. |
|
Tons Catering Sold |
= Tons Sold * % Catering |
= __foodservice_example_tons_sold__ tons sold * __foodservice_example_percent_catering__% of sales is catering
= __foodservice_example_tons_catering_sold__
|
|
Tons Catering Overproduction |
= Tons Catering Sold * % Catering Overproduction
Note: All Catering Overproduction was listed as “Prepared Foods” in the Food Waste Monitor.
|
= __foodservice_example_tons_sold__ tons sold * __foodservice_example_percent_catering__% of sales is catering * __foodservice_example_percent_catering_overproduction_rate__% food left unserved at events
= __foodservice_example_tons_catering_overproduction__ tons catering overproduction from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
|
US Dollars Catering Overproduction |
= US Dollars Sold * % Catering * % Catering Overproduction |
= $__foodservice_example_us_dollars_sold__ sold * __foodservice_example_percent_catering__% of sales is catering * __foodservice_example_percent_catering_overproduction_rate__% food left unserved at events
= $271,718,460 catering overproduction from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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PLATE WASTE |
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Average Menu Retail $ per Lb |
= US Dollars Sold / Tons Sold / 2,000 lbs per ton |
= $__foodservice_example_national_dollars_sold__ / __foodservice_example_tons_supply__ tons / 2,000 lbs per ton
= $__TODO_foodservice_example_average_menu_price_per_lb__/lb
|
|
Plate Waste Rate |
Plate Waste Studies[__citation_platewaste_Roe__],[__citation_platewaste_Massow__],[__citation_platewaste_PSU__],[__citation_platewaste_Folger__],[__citation_platewaste_Smith__]
See Appendix P for plate waste rates used for each type of foodservice.
|
In the plate waste study relevant to __foodservice_example_sub_sector__ locations, __foodservice_example_platewaste_rate__% of food served became plate waste
|
|
Tons Onsite Food Served |
= Tons Sold * % Onsite Dining |
= __foodservice_example_tons_sold__ * __foodservice_example_percent_onsite__%
= __foodservice_example_tons_onsite_food_served__ tons served at __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
|
US Dollars Onsite Food Served |
= Tons Onsite Food Served * Average Menu Retail $ per Lb * 2,000 lbs per ton |
= __foodservice_example_tons_onsite_food_served__ tons served * $__TODO_foodservice_example_average_menu_price_per_lb__/lb * 2,000 lbs per ton
= $__foodservice_example_dollars_onsite_food_served__ served at __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
|
Tons Catering Served |
= Tons Catering Sold - Tons Catering Overproduction |
= __foodservice_example_tons_onsite_food_served__ - __foodservice_example_tons_catering_overproduction__ tons catering overproduction
= __foodservice_example_tons_catering_served__ tons catering served from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
|
US Dollars Catering Served |
= Tons Catering Served * Average Menu Retail $ per Lb * 2,000 lbs per ton |
= __foodservice_example_tons_catering_served__ tons catering served * $__TODO_foodservice_example_average_menu_price_per_lb__/lb * 2,000 lbs per ton
= $__foodservice_example_dollars_catering_served__ catering served from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
|
Tons Onsite Plate Waste |
= Tons Onsite Food Served * Plate Waste Rate |
= __foodservice_example_tons_onsite_food_served__ * __foodservice_example_platewaste_rate__% food served becomes plate waste
= __foodservice_example_tons_onsite_platewaste__ tons onsite plate waste from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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Tons Catering Plate Waste |
= Tons Catering Served * Plate Waste Rate |
= __foodservice_example_tons_catering_served__ tons catering served * __foodservice_example_platewaste_rate__% food served becomes plate waste
= __foodservice_example_tons_catering_platewaste__ tons catering plate waste from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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US Dollars Catering Plate Waste |
= US Dollars Sold * % Onsite Dining * Plate Waste Rate |
= $__foodservice_example_us_dollars_sold__ sold * __foodservice_example_percent_onsite__% of sales is onsite dining * __foodservice_example_platewaste_rate__% food served becomes plate waste
= $__foodservice_example_dollars_onsite_platewaste__ onsite plate waste from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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US Dollars Catering Plate Waste |
= US Dollars Catering Served * Plate Waste Rate |
= $__foodservice_example_dollars_catering_served__ catering served * __foodservice_example_platewaste_rate__% food served becomes plate waste
= $__foodservice_example_dollars_catering_platewaste__ catering plate waste from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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Total Tons Plate Waste |
= Tons Onsite Plate Waste + Tons Catering Plate Waste
Note: All Plate Waste was listed as “Prepared Foods” in the Food Waste Monitor.
|
= __foodservice_example_tons_onsite_platewaste__ tons onsite plate waste + __foodservice_example_tons_catering_platewaste__ tons catering plate waste
= __TODO_foodservice_example_tons_total_platewaste__ tons total plate waste from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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Total US Dollars Plate Waste |
= US Dollars Onsite Plate Waste + US Dollars Catering Plate Waste |
= $__foodservice_example_dollars_onsite_platewaste__ onsite plate waste + $__foodservice_example_dollars_catering_platewaste__ catering plate waste
= $__TODO_foodservice_example_dollars_total_platewaste__ total plate waste from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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TOTAL FOOD SURPLUS |
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Tons Food Surplus |
= Tons Overproduction + Tons Pre-Consumer Surplus (excluding Overproduction) + Tons Plate Waste (including Onsite Dining and Catering) + Tons Catering Overproduction |
= __TODO_foodservice_example_tons_preconsumer_overproduction__ tons Overproduction + __foodservice_example_tons_preconsumer_surplus_excluding_overproduction__ tons not sold + __TODO_foodservice_example_tons_total_platewaste__ tons total plate waste + __foodservice_example_tons_catering_overproduction__ tons catering overproduction
= __foodservice_example_tons_surplus__ tons food surplus from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
|
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US Dollars Food Surplus |
= US Dollars Overproduction + US Dollars Pre-Consumer Surplus (excluding Overproduction) + US Dollars Plate Waste (including Onsite Dining and Catering) + US Dollars Catering Overproduction |
= $__TODO_foodservice_example_dollars_preconsumer_overproduction__ overproduction + $__foodservice_example_dollars_preconsumer_surplus__ pre-consumer surplus (excluding overproduction) + $__TODO_foodservice_example_dollars_total_platewaste__ total plate waste + $__foodservice_example_us_dollars_catering_overproduction__ catering overproduction
= $__foodservice_example_dollars_surplus__ food surplus from __foodservice_example_sub_sector__ locations in __foodservice_example_state__
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Cause Calculations
DATA ITEM |
DATA SOURCE OR CALCULATION |
EXAMPLE |
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|---|---|---|---|
PRE-CONSUMER SURPLUS CAUSES |
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Tons Overproduction |
See calculation above for Tons Overproduction |
= __TODO_foodservice_example_tons_total_overproduction__ tons Overproduction |
|
US Dollars Overproduction |
See calculation above for US Dollars Overproduction |
= $__TODO_foodservice_example_dollars_total_overproduction__ Overproduction |
|
% Surplus due to Cause (excluding Overproduction) |
Leanpath[30]
See Appendix R for causes by segment as well as proxies segments used when data was not available for a particular segment.
|
Pre-consumer food surplus causes (not including Overproduction) for the __foodservice_example_leanpath_segment__ segment in __foodservice_example_year__ (used as a proxy for most restaurants). :
Breads & Bakery:
Cooking issues: __foodservice_example_cause_breads_cookingissues__%
Date Label Concerns: __foodservice_example_cause_breads_datelabels__%
Equipment issues: __foodservice_example_cause_breads_eqptissues__%
Food Safety: __foodservice_example_cause_breads_safety__%
Handling errors: __foodservice_example_cause_breads_handling__%
Other: __foodservice_example_cause_breads_other__%
Spoiled: __foodservice_example_cause_breads_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_breads_trim__%
————————————————-
Total: 100%
Dairy & Eggs:
Cooking issues: __foodservice_example_cause_dairy_cookingissues__%
Date Label Concerns: __foodservice_example_cause_dairy_datelabels__%
Equipment issues: __foodservice_example_cause_dairy_eqptissues__%
Food Safety: __foodservice_example_cause_dairy_safety__%
Handling errors: __foodservice_example_cause_dairy_handling__%
Other: __foodservice_example_cause_dairy_other__%
Spoiled: __foodservice_example_cause_dairy_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_dairy_trim__%
————————————————-
Total: 100%
Dry Goods:
Cooking issues: __foodservice_example_cause_drygoods_cookingissues__%
Date Label Concerns: __foodservice_example_cause_drygoods_datelabels__%
Equipment issues: __foodservice_example_cause_drygoods_eqptissues__%
Food Safety: __foodservice_example_cause_drygoods_safety__%
Handling errors: __foodservice_example_cause_drygoods_handling__%
Other: __foodservice_example_cause_drygoods_other__%
Spoiled: __foodservice_example_cause_drygoods_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_drygoods_trim__%
————————————————-
Total: 100%
Fresh Meat & Seafood:
Cooking issues: __foodservice_example_cause_meat_cookingissues__%
Date Label Concerns: __foodservice_example_cause_meat_datelabels__%
Equipment issues: __foodservice_example_cause_meat_eqptissues__%
Food Safety: __foodservice_example_cause_meat_safety__%
Handling errors: __foodservice_example_cause_meat_handling__%
Other: __foodservice_example_cause_meat_other__%
Spoiled: __foodservice_example_cause_meat_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_meat_trim__%
————————————————-
Total: 100%
Frozen:
Cooking issues: __foodservice_example_cause_frozen_cookingissues__%
Date Label Concerns: __foodservice_example_cause_frozen_datelabels__%
Equipment issues: __foodservice_example_cause_frozen_eqptissues__%
Food Safety: __foodservice_example_cause_frozen_safety__%
Handling errors: __foodservice_example_cause_frozen_handling__%
Other: __foodservice_example_cause_frozen_other__%
Spoiled: __foodservice_example_cause_frozen_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_frozen_trim__%
————————————————-
Total: 100%
Prepared Foods:
Cooking issues: __foodservice_example_cause_prepared_cookingissues__%
Date Label Concerns: __foodservice_example_cause_prepared_datelabels__%
Equipment issues: __foodservice_example_cause_prepared_eqptissues__%
Food Safety: __foodservice_example_cause_prepared_safety__%
Handling errors: __foodservice_example_cause_prepared_handling__%
Other: __foodservice_example_cause_prepared_other__%
Spoiled: __foodservice_example_cause_prepared_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_prepared_trim__%
————————————————-
Total: 100%
Produce:
Cooking issues: __foodservice_example_cause_produce_cookingissues__%
Date Label Concerns: __foodservice_example_cause_produce_datelabels__%
Equipment issues: __foodservice_example_cause_produce_eqptissues__%
Food Safety: __foodservice_example_cause_produce_safety__%
Handling errors: __foodservice_example_cause_produce_handling__%
Other: __foodservice_example_cause_produce_other__%
Spoiled: __foodservice_example_cause_produce_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_produce_trim__%
————————————————-
Total: 100%
Ready-to-Drink Beverages:
Cooking issues: __foodservice_example_cause_bev_cookingissues__%
Date Label Concerns: __foodservice_example_cause_bev_datelabels__%
Equipment issues: __foodservice_example_cause_bev_eqptissues__%
Food Safety: __foodservice_example_cause_bev_safety__%
Handling errors: __foodservice_example_cause_bev_handling__%
Other: __foodservice_example_cause_bev_other__%
Spoiled: __foodservice_example_cause_bev_spoiled__%
Trimmings & Byproducts: __foodservice_example_cause_bev_trim__%
————————————————-
Total: 100%
|
|
Tons Pre-Consumer Surplus due to Cause (excluding Overproduction) |
= Tons Pre-Consumer Surplus by Food Type * % Pre-Consumer Surplus due to Cause |
Tons due to Cooking Issues:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_cookingissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_cookingissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_cookingissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_cookingissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_cookingissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_cookingissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_cookingissues__%
= __foodservice_example_tons_cookingissues__ tons
Tons due to Date Label Concerns:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_datelabels__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_datelabels__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_datelabels__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_datelabels__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_datelabels__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_datelabels__%
= __foodservice_example_tons_datelabels__ tons
Tons due to Equipment Issues:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_eqptissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_eqptissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_eqptissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_eqptissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_eqptissues__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_eqptissues__%
= __foodservice_example_tons_eqptissues__ tons
Tons due to Handling Errors:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_handling__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_handling__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_handling__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_handling__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_handling__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_handling__%
= __foodservice_example_tons_handling__ tons
Tons due to Other:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_other__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_other__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_other__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_other__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_other__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_other__%
= __foodservice_example_tons_other__ tons
Tons due to Spoiled:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_spoiled__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_spoiled__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_spoiled__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_spoiled__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_spoiled__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_spoiled__%
= __foodservice_example_tons_spoiled__ tons
Tons due to Trimmings & Byproducts:
= __foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ tons surplus Breads & Bakery * __foodservice_example_cause_breads_trim__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_dairy__ tons surplus Dairy & Eggs * __foodservice_example_cause_dairy_trim__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_drygoods__ tons surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_meat__ tons surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_trim__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_frozen__ tons surplus Frozen * __foodservice_example_cause_frozen_trim__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_produce__ tons surplus Produce * __foodservice_example_cause_produce_trim__% + __foodservice_example_tons_preconsumersurplus_excl_overproduction_bev__ tons surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_trim__%
= __foodservice_example_tons_trim__ tons
|
|
US Dollars Pre-Consumer Surplus due to Cause (excluding Overproduction) |
= US Dollars Pre-Consumer Surplus by Food Type * % Pre-Consumer Surplus due to Cause |
US Dollars due to Cooking Issues:
= $__foodservice_example_tons_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_cookingissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_cookingissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_cookingissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_cookingissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_cookingissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_cookingissues__%
= $__foodservice_example_dollars_cookingissues__
US Dollars due to Date Label Concerns:
= $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_datelabels__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_datelabels__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_datelabels__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_datelabels__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_datelabels__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_datelabels__%
= $__foodservice_example_dollars_datelabels__
US Dollars due to Equipment Issues:
= $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_eqptissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_eqptissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_eqptissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_eqptissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_eqptissues__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_eqptissues__%
= $__foodservice_example_dollars_eqptissues__
US Dollars due to Handling Errors:
= $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_handling__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_handling__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_handling__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_handling__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_handling__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_handling__%
= $__foodservice_example_dollars_handling__
US Dollars due to Other:
= $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_other__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_other__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_other__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_other__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_other__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_other__%
= $__foodservice_example_dollars_other__
US Dollars due to Spoiled:
= $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_spoiled__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_spoiled__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_spoiled__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_spoiled__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_spoiled__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_spoiled__%
= $__foodservice_example_dollars_spoiled__
US Dollars due to Trimmings & Byproducts:
= $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_breads__ surplus Breads & Bakery * __foodservice_example_cause_breads_trim__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_dairy__ surplus Dairy & Eggs * __foodservice_example_cause_dairy_trim__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_drygoods__ surplus Dry Goods * __foodservice_example_cause_breads_drygoods__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_meat__ surplus Fresh Meat & Seafood * __foodservice_example_cause_meat_trim__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_frozen__ surplus Frozen * __foodservice_example_cause_frozen_trim__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_produce__ surplus Produce * __foodservice_example_cause_produce_trim__% + $__foodservice_example_dollars_preconsumersurplus_excl_overproduction_bev__ surplus Ready-to-drink Beverages * __foodservice_example_cause_bev_trim__%
= $__foodservice_example_dollars_trim__
|
|
PLATE WASTE AND CATERING OVERPRODUCTION |
|||
Tons Plate Waste |
See calculation above for Tons Plate Waste |
= __TODO_foodservice_example_tons_total_platewaste__ tons plate waste |
|
US Dollars Plate Waste |
See calculation above for US Dollars Plate Waste |
= $__TODO_foodservice_example_dollars_total_platewaste__ plate waste |
|
Tons Catering Overproduction |
See calculation above for Tons Catering Overproduction |
= __foodservice_example_tons_catering_oveproduction__ tons catering overproduction |
|
US Dollars Catering Overproduction |
See calculation above for US Dollars Catering Overproduction |
= $__foodservice_example_dollars_catering_oveproduction__ catering overproduction |
|
Destination Calculations
DATA ITEM |
DATA SOURCE OR CALCULATION |
EXAMPLE |
|---|---|---|
Destination Breakdown of PreConsumer Food Surplus |
Food Waste Reduction Alliance (FWRA) Survey[14]
Note: ReFED used Leanpath[30] data rather than FWRA survey data to quantify the breakdown of preconsumer surplus for states that have organic waste recycling laws (California, Connecticut, Massachusetts, Oregon, Vermont, Washington). See Appendix S (LINK!) for more information.
|
Donated: __foodservice_example_preconsumer_pct_donated__%
Animal feed: __foodservice_example_preconsumer_pct_animalfeed__%
Anaerobic Digestion: __foodservice_example_preconsumer_pct_ad__%
Compost: __foodservice_example_preconsumer_pct_composted__%
Land Application: __foodservice_example_preconsumer_pct_landapp__%
Sewer: __foodservice_example_preconsumer_pct_sewer__%
Dumping: __foodservice_example_preconsumer_pct_dumping__%
Trash: __foodservice_example_preconsumer_pct_trash__%
————————————————
Total: 100%
Note: ReFED excluded industrial uses (biomaterials/processing) data from the FWRA surveys, because most of this is spent cooking oil rather than preconsumer surplus.
|
% of Trash that is Landfilled vs Incinerated in __foodservice_example_state__ (Biocycle/Columbia University Survey[8]) (See Appendix Z) |
% of Trash that is Landfilled = __TODO_foodservice_example_pct_trash_landfilled__%
% of Trash that is Incinerated = __TODO_foodservice_example_pct_trash_incinerated__%
|
|
Breaking “Trash” into Landfill vs Incineration:
% Landfilled = % Trash * % of Trash that is Landfilled
% Incinerated = % Trash * % of Trash that is Incinerated
|
% Landfilled:
= __foodservice_example_preconsumer_pct_trash__% * __TODO_foodservice_example_pct_trash_landfilled__%
= __TODO_foodservice_example_pct_preconsumer_landfilled__%
% Incinerated:
= __foodservice_example_preconsumer_pct_trash__% * __TODO_foodservice_example_pct_trash_incinerated__%
= __TODO_foodservice_example_pct_preconsumer_incinerated__%
|
|
Destination Breakdown of Plate Waste |
ReFED assumed that plate waste was sent to “Trash” in all states, except states that have organic waste recycling laws. For those states, Leanpath[30] plate waste destinations data was used instead. See Appendix T for more information. |
Assumed 100% Trash for plate waste in __foodservice_example_state__ |
% of Trash that is Landfilled vs Incinerated in __foodservice_example_state__ (Biocycle/Columbia University Survey[8]) (See Appendix Z) |
% of Trash that is Landfilled = __TODO_foodservice_example_pct_trash_landfilled__%
% of Trash that is Incinerated = __TODO_foodservice_example_pct_trash_incinerated__%
|
|
Breaking “Trash” into Landfill vs Incineration:
% Landfilled = % Trash * % of Trash that is Landfilled
% Incinerated = % Trash * % of Trash that is Incinerated
|
% Landfilled = 100% * __TODO_foodservice_example_pct_trash_landfilled__% = __TODO_foodservice_example_pct_platewaste_landfilled__%
% Incinerated = 0% * __TODO_foodservice_example_pct_trash_incinerated__% = __TODO_foodservice_example_pct_platewaste_incinerated__%
|
|
Destination Breakdown of Catering Overproduction |
ReFED assumed that catering overproduction was sent to “Trash” in all states, except states that have organic waste recycling laws. For those states, Leanpath[30] plate waste destinations data was used instead. See Appendix U for more information. |
Donated: __foodservice_example_catering_pct_donated__%
Animal feed: __foodservice_example_catering_pct_animalfeed__%
Anaerobic Digestion: __foodservice_example_catering_pct_ad__%
Compost: __foodservice_example_catering_pct_composted__%
Industrial uses: __foodservice_example_catering_pct_industrial__%
Land Application: __foodservice_example_catering_pct_landapp__%
Sewer: __foodservice_example_catering_pct_sewer__%
Dumping: __foodservice_example_catering_pct_dumping__%
Trash: __foodservice_example_catering_pct_trash__%
————————————————
Total: 100%
|
% of Trash that is Landfilled vs Incinerated in __foodservice_example_state__ (Biocycle/Columbia University Survey[8]) (See Appendix Z) |
% of Trash that is Landfilled = __TODO_foodservice_example_pct_trash_landfilled__%
% of Trash that is Incinerated = __TODO_foodservice_example_pct_trash_incinerated__%
|
|
Breaking “Trash” into Landfill vs Incineration:
% Landfilled = % Trash * % of Trash that is Landfilled
% Incinerated = % Trash * % of Trash that is Incinerated
|
% Landfilled = __foodservice_example_catering_pct_trash__% * __TODO_foodservice_example_pct_trash_landfilled__% = __TODO_foodservice_example_pct_catering_landfilled__%
% Incinerated = __foodservice_example_catering_pct_trash__% * __TODO_foodservice_example_pct_trash_incinerated__% = __TODO_foodservice_example_pct_catering_incinerated__%
|
|
Tons Donated |
= Tons Pre-Consumer Surplus (incl or exlc overproduction??) * % Donations for Pre-Consumer Surplus + Total Tons Plate Waste * % Donations for Plate Waste + Tons Catering Overproduction * % Donations for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_donated__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_donated__%
= __foodservice_example_tons_donated__ tons
|
Tons Animal Feed |
= Tons Pre-Consumer Surplus * % Animal Feed for Pre-Consumer Surplus + Total Tons Plate Waste * % Animal Feed for Plate Waste + Tons Catering Overproduction * % Animal Feed for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_animalfeed__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_animalfeed__%
= __foodservice_example_tons_animalfeed__ tons
|
Tons Industrial uses |
= Tons Pre-Consumer Surplus * % Industrial uses for Pre-Consumer Surplus + Total Tons Plate Waste * % Industrial uses for Plate Waste + Tons Catering Overproduction * % Industrial uses for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_industrial__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_industrial__%
= __foodservice_example_tons_industrial__ tons
|
Tons Anaerobic Digestion |
= Tons Pre-Consumer Surplus * % Anaerobic Digestion for Pre-Consumer Surplus + Total Tons Plate Waste * % Anaerobic Digestion for Plate Waste + Tons Catering Overproduction * % Anaerobic Digestion for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_ad__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_ad__%
= __foodservice_example_tons_ad__ tons
|
Tons Composted |
= Tons Pre-Consumer Surplus * % Composted for Pre-Consumer Surplus + Total Tons Plate Waste * % Composted for Plate Waste + Tons Catering Overproduction * % Composted for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_composted__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_composted__%
= __foodservice_example_tons_composted__ tons
|
Tons Land Application |
= Tons Pre-Consumer Surplus * % Land Application for Pre-Consumer Surplus + Total Tons Plate Waste * % Land Application for Plate Waste + Tons Catering Overproduction * % Land Application for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_landapp__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_landapp__%
= __foodservice_example_tons_landapp__ tons
|
Tons Sewer |
= Tons Pre-Consumer Surplus * % Sewer for Pre-Consumer Surplus + Total Tons Plate Waste * % Sewer for Plate Waste + Tons Catering Overproduction * % Sewer for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_sewer__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_sewer__%
= __foodservice_example_tons_sewer__ tons
|
Tons Dumping |
= Tons Pre-Consumer Surplus * % Dumping for Pre-Consumer Surplus + Total Tons Plate Waste * % Dumping for Plate Waste + Tons Catering Overproduction * % Dumping for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __foodservice_example_preconsumer_pct_dumping__% + __TODO_foodservice_example_tons_total_platewaste__ tons * 0% + __foodservice_example_tons_catering_oveproduction__ tons * __foodservice_example_catering_pct_dumping__%
= __foodservice_example_tons_dumping__ tons
|
Tons Landfilled |
= Tons Pre-Consumer Surplus * % Landfilled for Pre-Consumer Surplus + Total Tons Plate Waste * % Landfilled for Plate Waste + Tons Catering Overproduction * % Landfilled for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __TODO_foodservice_example_pct_preconsumer_landfilled__% + __TODO_foodservice_example_tons_total_platewaste__ tons * __TODO_foodservice_example_pct_platewaste_landfilled__% + __foodservice_example_tons_catering_oveproduction__ tons * __TODO_foodservice_example_pct_catering_landfilled__%
= __foodservice_example_tons_landfilled__ tons
|
Tons Incineration |
= Tons Pre-Consumer Surplus * % Incineration for Pre-Consumer Surplus + Total Tons Plate Waste * % Incineration for Plate Waste + Tons Catering Overproduction * % Incineration for Catering Overproduction |
= __foodservice_example_tons_preconsumersurplus__ tons * __TODO_foodservice_example_pct_preconsumer_incinerated__% + __TODO_foodservice_example_tons_total_platewaste__ tons * __TODO_foodservice_example_pct_platewaste_incinerated__% + __foodservice_example_tons_catering_oveproduction__ tons * __TODO_foodservice_example_pct_catering_incinerated__%
= __foodservice_example_tons_incinerated__ tons
|
US Dollars Donated |
= US Dollars Pre-Consumer Surplus * % Donations for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Donations for Plate Waste + US Dollars Catering Overproduction * % Donations for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_donated__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_donated__%
= $__foodservice_example_dollars_donated__
|
US Dollars Animal Feed |
= US Dollars Pre-Consumer Surplus * % Animal Feed for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Animal Feed for Plate Waste + US Dollars Catering Overproduction * % Animal Feed for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_animalfeed__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_animalfeed__%
= $__foodservice_example_dollars_animalfeed__
|
US Dollars Industrial uses |
= US Dollars Pre-Consumer Surplus * % Industrial uses for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Industrial uses for Plate Waste + US Dollars Catering Overproduction * % Industrial uses for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_industrial__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_industrial__%
= $__foodservice_example_dollars_industrial__
|
US Dollars Anaerobic Digestion |
= US Dollars Pre-Consumer Surplus * % Anaerobic Digestion for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Anaerobic Digestion for Plate Waste + US Dollars Catering Overproduction * % Anaerobic Digestion for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_ad__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_ad__%
= $__foodservice_example_dollars_ad__
|
US Dollars Composted |
= US Dollars Pre-Consumer Surplus * % Composted for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Composted for Plate Waste + US Dollars Catering Overproduction * % Composted for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_composted__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_composted__%
= $__foodservice_example_dollars_composted__
|
US Dollars Land Application |
= US Dollars Pre-Consumer Surplus * % Land Application for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Land Application for Plate Waste + US Dollars Catering Overproduction * % Land Application for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_landapp__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_landapp__%
= $__foodservice_example_dollars_landapp__
|
US Dollars Sewer |
= US Dollars Pre-Consumer Surplus * % Sewer for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Sewer for Plate Waste + US Dollars Catering Overproduction * % Sewer for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_sewer__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_sewer__%
= $__foodservice_example_dollars_sewer__
|
US Dollars Dumping |
= US Dollars Pre-Consumer Surplus * % Dumping for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Dumping for Plate Waste + US Dollars Catering Overproduction * % Dumping for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __foodservice_example_preconsumer_pct_dumping__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __foodservice_example_catering_pct_dumping__%
= $__foodservice_example_dollars_dumping__
|
US Dollars Landfilled |
= US Dollars Pre-Consumer Surplus * % Landfilled for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Landfilled for Plate Waste + US Dollars Catering Overproduction * % Landfilled for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __TODO_foodservice_example_pct_preconsumer_landfilled__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 100% + $__foodservice_example_dollars_catering_oveproduction__ * __TODO_foodservice_example_pct_catering_landfilled__%
= $__foodservice_example_dollars_landfilled__
|
US Dollars Incineration |
= US Dollars Pre-Consumer Surplus * % Incineration for Pre-Consumer Surplus + Total US Dollars Plate Waste * % Incineration for Plate Waste + US Dollars Catering Overproduction * % Incineration for Catering Overproduction |
= $__foodservice_example_dollars_preconsumersurplus__ * __TODO_foodservice_example_pct_preconsumer_incinerated__% + $__TODO_foodservice_example_dollars_total_platewaste__ * 0% + $__foodservice_example_dollars_catering_oveproduction__ * __TODO_foodservice_example_pct_catering_incinerated__%
= $__foodservice_example_dollars_incinerated__
|
Data Sources and Limitations
National Foodservice Purchases and Sales
State Restaurant Locations and Employee Counts for Non-Restaurant Segments
Raw data and documentation:
Restaurant Locations: This contains confidential data from Technomic and cannot be shared.
Employee Counts for Non-Restaurant: https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Foodservice_EmployeeCounts.xlsx
For limited service restaurants, full service restaurants, and bars & taverns, ReFED allocated national sales down to the state level using the Technomic state-level locations data for the Top 500 restaurants[43]. A limitation of this approach is that sales is not always proportional to the number of locations.
Wholesale Price per Lb
Pre-Consumer Surplus Rates
Leanpath is a technology company that helps foodservice companies track, weigh and analyze the amount of food that is wasted in commercial kitchens. Leanpath customers indicate the reason the food was not used, where it will be sent (e.g., composting, landfill, etc.), and the food type of the disposed food when using Leanpath’s software system. Based on the data in their system across multiple clients, Leanpath estimates that on average 4.2% of food purchases are not utilized in commercial foodservice kitchens[30].
Food Type Breakdown
Distribution Channels (Dine in vs Takeout vs Catering)
Plate Waste Rates
Catering Overproduction Rates
Pre-Consumer Surplus Causes
Pre-Consumer Surplus Destinations
For most states, ReFED used data from the 2016 Food Waste Reduction Alliance (FWRA) survey[14] of restaurants in which 28 restaurant companies responded (11.8% of U.S. market share based on sales) to estimate the destination breakdown of pre-consumer surplus. Data on industrial uses (or biomaterials/processing) was excluded because most of this is spent cooking oil rather than pre-consumer surplus. Since this data indicated that 94% of pre-consumer surplus is landfilled, which is not the case in states that have organics recycling laws, ReFED instead used data from Leanpath[30] to estimate the pre-consumer surplus destinations for these states (California, Connecticut, Massachusetts, Oregon, Vermont, and Washington). ReFED did not use the Leanpath data for other states to avoid selection bias as Leanpath clients may be more likely to compost food scraps than the average foodservice business.
Plate Waste Destinations
Raw data and documentation: - https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Foodservice_CateringPlateWasteDestinations.xlsx - https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Foodservice_OnsitePlateWasteDestinations.xlsx
ReFED assumed that plate waste was sent to “Trash” in all states, except states that have organics recycling laws. For these states (California, Connecticut, Massachusetts, Oregon, Vermont, and Washington), Leanpath plate waste destinations data was used instead[30]. ReFED did not use the Leanpath data for other states to avoid selection bias as Leanpath clients may be more likely to compost food scraps than the average foodservice business.
Catering Overproduction Destinations
ReFED assumed that catering overproduction was sent to “Trash” in all states, except states that have organic waste recycling laws. For states with organics recycling laws (California, Connecticut, Massachusetts, Oregon, Vermont, and Washington), Leanpath catering overproduction destinations data was used instead[30]. ReFED did not use the Leanpath data for other states to avoid selection bias as Leanpath clients may be more likely to compost food scraps than the average foodservice business.
Data Quality Evaluation
This quality assessment is meant to evaluate the quality of how each data source was used by ReFED to estimate food loss and waste. It is not meant to rate the quality of the study itself. A high quality study used by ReFED beyond the study’s intended purposes could result in a low data quality score. See Appendix AA for more information about the ReFED Data Quality Rubric.
Table 16. Data Quality Evaluation for Food Waste Monitor Foodservice Sector
DATA |
SOURCE |
DATA QUALITY SCORE |
||||||
|---|---|---|---|---|---|---|---|---|
CREDIBILITY |
UPDATE FREQUENCY |
COVERAGE |
FOOD TYPE |
GEOGRAPHY |
SCORE |
WEIGHT |
||
FOODSERVICE SURPLUS DATA |
||||||||
National Purchases from Suppliers |
Technomic Ignite Platform |
4 |
5 |
5 |
1 |
3 |
Medium 18/5 = 3.6 |
10% |
National US Dollars Sold |
Technomic Ignite Platform |
4 |
5 |
5 |
1 |
3 |
Medium 18/5 = 3.6 |
8% |
State Locations for Top 500 Restaurants |
Technomic Ignite Platform |
4 |
5 |
5 |
1 |
5 |
High 20/5 = 4.0 |
8% |
State Employee Counts for Non-Restaurant Segments |
U.S. Bureau of Labor Statistics Employee Levels |
5 |
5 |
5 |
1 |
5 |
High 21/5 = 4.2 |
8% |
Food Type Breakdown |
Technomic Ignite Platform Menu Data |
2 |
1 |
1 |
5 |
3 |
Low 12/5 = 2.4 |
8% |
Wholesale Price per Lb |
ReFED Calculations |
2 |
5 |
1 |
5 |
3 |
Medium 16/5 = 3.2 |
8% |
Pre-Consumer Surplus Rate |
Leanpath |
4 |
1 |
1 |
1 |
3 |
Low 10/5 = 2.0 |
3% |
Distribution Channels (Dine in vs Takeout vs Catering) |
Technomic Ignite Platform |
4 |
1 |
5 |
3 |
3 |
Medium 16/5 = 3.2 |
10% |
Plate Waste Rates |
Plate Waste Studies |
__foodservice_surplus_platewaste_rates_credibility__ |
__foodservice_surplus_platewaste_rates_update_frequency__ |
__foodservice_surplus_platewaste_rates_coverage__ |
__foodservice_surplus_platewaste_rates_food_type__ |
__foodservice_surplus_platewaste_rates_geography__ |
__foodservice_surplus_platewaste_rates_score_text__ |
__foodservice_surplus_platewaste_rates_weight_text__ |
% Catering Overproduction |
Expert Interviews |
1 |
1 |
1 |
2 |
1 |
Very Low 6/5 = 1.2 |
2% |
3.6 * 10% + 3.6 * 8% + 4.0 * 8% + 4.2 * 8% + 2.4 * 8% + 3.2 * 8% + 2.0 * 3% + 3.2 * 10% + 2.2 * 35% + 1.2 * 2% = 2.93 |
Low |
|||||||
FOODSERVICE CAUSES DATA |
||||||||
% Pre-Consumer Surplus due to Cause |
Leanpath |
4 |
5 |
1 |
5 |
3 |
Medium 18/5 = 3.6 |
6% |
Distribution Channels (Dine in vs Takeout vs Catering) |
Technomic Ignite Platform |
4 |
5 |
5 |
5 |
3 |
High 22/5 = 4.4 |
20% |
Plate Waste Rates |
Plate Waste Studies |
__foodservice_causes_platewaste_rates_credibility__ |
__foodservice_causes_platewaste_rates_update_frequency__ |
__foodservice_causes_platewaste_rates_coverage__ |
__foodservice_causes_platewaste_rates_food_type__ |
__foodservice_causes_platewaste_rates_geography__ |
__foodservice_causes_platewaste_rates_score_text__ |
__foodservice_causes_platewaste_rates_weight_text__ |
% Catering Overproduction |
Expert Interviews |
1 |
1 |
1 |
2 |
1 |
Very Low 6/5 = 1.2 |
4% |
3.6 * 6% + 4.4 * 20% + 2.0 * 70% + 1.2 * 4% = 2.54 |
Low |
|||||||
FOODSERVICE DESTINATIONS DATA |
||||||||
% Destination Breakdown for Pre-Consumer Surplus |
FWRA Surveys, Leanpath |
3 |
1 |
1 |
1 |
2 |
Very Low 8/5 = 1.6 |
15% |
% Destination Breakdown for Plate Waste |
Leanpath, ReFED Assumptions |
__foodservice_destinations_platewaste_destinations_credibility__ |
__foodservice_destinations_platewaste_destinations_update_frequency__ |
__foodservice_destinations_platewaste_destinations_coverage__ |
__foodservice_destinations_platewaste_destinations_food_type__ |
__foodservice_destinations_platewaste_destinations_geography__ |
__foodservice_destinations_platewaste_destinations_score_text__ |
__foodservice_destinations_platewaste_destinations_weight_text__ |
% Destination Breakdown for Catering Overproduction |
Leanpath, ReFED Assumptions |
4 |
5 |
1 |
5 |
2 |
Medium 17/5 = 3.4 |
10% |
% of Trash Landfilled vs Incinerated |
Biocycle/Columbia University Survey |
5 |
1 |
5 |
1 |
5 |
Medium 17/5 = 3.4 |
10% |
1.6 * 15% + 3.4 * 65% + 3.4 * 10% + 3.4 * 10% = 3.13 |
Medium |
|||||||