Residential Methodology

Scope Boundary

Residential 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
  • “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

Master Surplus Equation:
( Tons Purchased from Grocery Stores + Tons Obtained Elsewhere )
x Surplus Rate
——————————————————————————————————
= Tons Residential Surplus

In ReFED’s data model, the following calculations are repeated for every state, year, and food type before any aggregation is done.

Table 17. Calculations Performed to Quantify U.S. Residential Surplus Food

DATA ITEM

DATA SOURCE OR CALCULATION

EXAMPLE

US Dollars Purchased from Grocery Stores

Nielsen Point-of-Sale (POS) Data[38]

$43,334,294 worth of Tomatoes purchased from grocery stores in Arkansas in 2021

Tons Purchased fron Grocery Stores

Nielsen Point-of-Sale (POS) Data[38]

9,971 tons Tomatoes purchased from grocery stores in Arkansas in 2021

Retail Price per Lb

= US Dollars Purchased from Grocery Stores / Tons Purchased from Grocery Stores / 2,000 lbs per ton

See U.S. Grocery Retail Dollar-to-Weight Conversion Factors Report[40] for more information on the price per lb data.
= $43,334,294 worth of Tomatoes purchased / 9,971 tons Tomatoes purchased / 2,000 lbs per ton
= $2.17 per lb

% of Food Obtained from Grocery Stores

USDA NHANES Survey[51]

90.80% of Tomatoes obtained from grocery stores (as opposed to restaurants, farmers markets, food banks, gas stations, home gardens, etc.)

Tons Obtained Elsewhere

= Tons Purchased from Grocery Stores * (100% - % of Food Obtained from Grocery Stores) / % of Food Obtained from Grocery Stores

= 9,971 tons purchased from grocery * (100% - 90.80%) / 90.80%
= 1,010 tons Tomatoes obtained elsewhere

Surplus Rate

National Household Food Waste Tracking Survey [39]

= 21.87% of Tomatoes brought home are wasted

Tons Surplus

= ( Tons Purchased from Grocery Stores + Tons Obtained Elsewhere) * Surplus Rate

= (9,971 tons purchased from grocery + 1,010 tons obtained elsewhere ) * 21.87%
= 2,401 tons Tomatoes surplus

US Dollars Surplus

= Tons Surplus * Retail Price per Lb * 2,000 lbs per ton

= 2,401 tons Tomatoes surplus * $2.17 per lb
= $10,436,232 surplus

Cause Calculations

Master Cause Equation:
Tons Surplus due to Cause = Tons Surplus * % Loss due to Cause
Table 18. Calculations Performed to Quantify the Causes of U.S. Residential Surplus Food

DATA ITEM

DATA SOURCE OR CALCULATION

EXAMPLE

% Surplus due to Cause

NRDC Home Kitchen Diaries[35]

Example data breakdown of home food waste causes for produce (See Appendix X for other food types):

Considered inedible: 16.20%
Cooking issues: 0.26%
Date label concerns: 0.85%
Didn’t taste good: 2.49%
Didn’t want leftovers: 2.06%
Inedible parts: 46.42%
Left out too long: 3.72%
Other: 3.79%
Spoiled: 22.85%
Too little save: 1.37%
————————————————
Total: 100%

Tons Surplus due to Cause

= Tons Surplus * % Surplus due to Cause

Tons due to Considered inedible:
= 2,401 tons Tomatoes surplus * 16.20%
= 388 tons

Tons due to Cooking issues:
= 2,401 tons Tomatoes surplus * 0.26%
= 6 tons

Tons due to Date label concerns:
= 2,401 tons Tomatoes surplus * 0.85%
= 20 tons

Tons due to Didn’t taste good:
= 2,401 tons Tomatoes surplus * 2.49%
= 59 tons

Tons due to Didn’t want leftovers:
= 2,401 tons Tomatoes surplus * 2.06%
= 49 tons

Tons due to Inedible parts:
= 2,401 tons Tomatoes surplus * 46.42%
= 1,114 tons

Tons due to Left out too long:
= 2,401 tons Tomatoes surplus * 3.72%
= 89 tons

Tons due to Other:
= 2,401 tons Tomatoes surplus * 3.79%
= 91 tons

Tons due to Spoiled:
= 2,401 tons Tomatoes surplus * 22.85%
= 548 tons

Tons due to Too little to save:
= 2,401 tons Tomatoes surplus * 1.37%
= 32 tons

US Dollars Surplus due to Cause

= US Dollars Surplus * % Surplus due to Cause

US Dollars due to Considered inedible:
= $10,436,232 Tomatoes surplus * 16.20%
= $1,690,431

US Dollars due to Cooking issues:
= $10,436,232 Tomatoes surplus * 0.26%
= $26,679

US Dollars due to Date label concerns:
= $10,436,232 Tomatoes surplus * 0.85%
= $88,947

US Dollars due to Didn’t taste good:
= $10,436,232 Tomatoes surplus * 2.49%
= $259,667

US Dollars due to Didn’t want leftovers:
= $10,436,232 Tomatoes surplus * 2.06%
= $214,499

US Dollars due to Inedible parts:
= $10,436,232 Tomatoes surplus * 46.42%
= $4,844,180

US Dollars due to Left out too long:
= $10,436,232 Tomatoes surplus * 3.72%
= $388,571

US Dollars due to Other:
= $10,436,232 Tomatoes surplus * 3.79%
= $395,741

US Dollars due to Spoiled:
= $10,436,232 Tomatoes surplus * 22.85%
= $2,384,197

US Dollars due to Too little to save:
= $10,436,232 Tomatoes surplus * 1.37%
= $143,315

Destination Calculations

Master Destination Equation:
Tons Surplus sent to Destination = Tons Surplus * % Sent to Destination
Table 19. Calculations Performed to Quantify the Destinations of U.S. Residential Surplus Food

DATA ITEM

DATA SOURCE OR CALCULATION

EXAMPLE

Destination Breakdown of Residential Surplus

NRDC Home Kitchen Diaries [35]

According to the NRDC Home Kitchen Diaries, this was the destination breakdown of residential surplus for Produce (See Appendix Y for other food types):

Animal feed: 0.45%
Compost: __residential_example_percent_composting__%
Sewer: 1.30%
Trash: 52.32%
————————————————
Total: 100%
% of Trash that is landfill vs incineration in Arkansas
(BioCycle/Columbia University Survey)[8] (See Appendix Z)
% of Trash that is landfill = 100.00%
% of Trash that is incineration = 0.00%
Breaking “Trash” into Landfill vs Incineration:

% landfill = % Trash * % of Trash that is landfill

% incineration = % Trash * % of Trash that is incineration

% landfill:
= 52.32% * 100.00%
= __residential_example_landfill_rate__

% incineration:
= 52.32% * 0.00%
= __residential_example_incineration_rate__

Tons Animal Feed

= Tons Surplus * % Animal Feed

= 2,401 tons Tomatoes surplus * 0.45% animal feed
= 10 tons Tomatoes sent to animal feed

Tons composting

= Tons Surplus * % composting

= 2,401 tons Tomatoes surplus * __residential_example_percent_composting__% composting
= __residential_example_tons_composting__ tons Tomatoes composting

Tons Sewer

= Tons Surplus * % Sewer

= 2,401 tons Tomatoes surplus * 1.30% disposed down the drain
= 31 tons Tomatoes disposed via sewer

Tons landfill

= Tons Surplus * % landfill

= 2,401 tons Tomatoes surplus * 100.00% landfill
= __residential_example_tons_landfill__ tons Tomatoes landfill

Tons incineration

= Tons Surplus * % incineration

= 2,401 tons Tomatoes surplus * 0.00% incineration
= __residential_example_tons_incineration__ tons Tomatoes incineration

US Dollars Animal Feed

= US Dollars Surplus * % Animal Feed

= $10,436,232 Tomatoes surplus * 0.45% animal feed
= $46,702 Tomatoes sent to animal feed

US Dollars composting

= US Dollars Surplus * % composting

= $10,436,232 Tomatoes surplus * __residential_example_percent_composting__% composting
= $__residential_example_us_dollars_composting__ Tomatoes composting

US Dollars Sewer

= US Dollars Surplus * % Sewer

= $10,436,232 Tomatoes surplus * 1.30% disposed down the drain
= $135,360 Tomatoes disposed via sewer

US Dollars landfill

= US Dollars Surplus * % landfill

= $10,436,232 Tomatoes surplus * 100.00% landfill
= $__residential_example_us_dollars_landfill__ Tomatoes landfill

US Dollars incineration

= US Dollars Surplus * % incineration

= $10,436,232 Tomatoes surplus * 0.00% incineration
= $__residential_example_us_dollars_incineration__ Tomatoes incineration

Data Sources and Limitations

Retail Value and Tons Purchased at Grocery Stores

Raw data and documentation:
This is confidential data from Nielsen and cannot be shared.

Nielsen data represents over 85% coverage of grocery retail sales in the U.S. Each year top U.S. grocery retailers report item level point-of-sale sales data to Nielsen[38], including information about each item such as the grocery chain where it was sold, the brand name of the product, the food classification (department, category, subcategory), the weight of food and packaging, and many other attributes. ReFED used this data to quantify the retail value and weight of food sold by grocery retailers in the U.S. by year, state, and food type. For more information about the weight data, see the U.S. Grocery Retail Dollar-to-Weight Conversion Factors report[40].

Nielsen provided point-of-sale data for the years 2016-2019. In order to estimate values for the missing years 2010-2015 each subcategory was extrapolated using category-level average year-over-year linear growth rates for both sales value and sales weight. Due to the high granularity of the categories, there were some cases where the growth rates were either extremely high or extremely low. To avoid unrealistic growth estimations over time within these outlier categories, department-level growth rates were used instead if a category had a growth rate ±15%. These outlier categories represent 0.5% of total sales.

The accuracy of these estimates is limited to the accuracy of the Nielsen sales and weight data. The weight data for UPC items comes directly from up-to-date product packaging images. For non-UPC items sold in eaches, Nielsen estimates weight using a weight conversion factor (e.g., the average weight of a lemon). For other non-UPC items, Nielsen is reliant on the retailer transaction data to provide the item sale weight units (e.g., lbs of apples sold).

A limitation of using this dataset to quantify residential grocery store purchases is that a small portion of grocery store sales is actually to commercial or non-residential customers (e.g., local restaurants, local food banks, etc.). Future iterations of this work should quantify the percentage of grocery store sales that is attributed to these non-residential customers by food type so that grocery sales can be discounted to only include residential sales. In the meantime, the resulting residential surplus estimates may be slightly overestimated.

Food Obtained from Grocery Stores vs Elsewhere

Every two years the National Health And Nutrition Examination Survey (NHANES)[51] is conducted as a partnership between the U.S. Department of Health and Human Services (DHHS) and the U.S. Department of Agriculture (USDA) to provide information on the health and nutritional status of people in the United States. In one portion of the study, participants are asked questions about their food intake over a two day period (e.g., food type and weight consumed, whether the food was obtained from a grocery store or restaurant, etc.). ReFED used this data to quantify the portion of each food type obtained from grocery stores versus other sources (e.g., restaurants, food pantries, convenience stores). See Appendix V as well as the raw data and documentation link above for details. The calculations were performed for each state, although the survey results are only available at the national level. Because food preferences and consumption patterns vary geographically, state-level data is needed in the future for better estimates.

Residential Food Surplus Rates

As of 2023, ReFED is now estimating residential waste using research produced by a collaborative effort between the Ohio State Food Waste Collaborative and the Multiscale RECIPES Sustainable Regional Systems Research Network[39], led by Professor Brian Roe. Since 2021, surveys of household food waste habits have been conducted three times a year, in which weekly per capita waste in grams is estimated for 24 foods.

To calculate the loss rate, weekly per capita waste is scaled to total tons of residential waste. This annual waste is then scaled to account for inedible waste and by respondent underreporting. The loss rate is then calculated by dividing total annual waste in tons by total sales in tons, which is derived from Nielsen IQ sales data.

Since the survey data begins in 2021, 2016-2019 estimates are backfilled by multiplying 2023 surplus rates by total sales for each year. We assume that pre-COVID consumer waste behavior is similar to that of 2023, which appears to be a return to pre-pandemic “normalcy”. This “return” is evident in the overall increase in per capita sales and a major return to dining out, in spite of record high food prices. For 2020, we calculated waste rates based on survey results from a single wave, conducted in February 2021.

We validated the household waste estimates by cross-referencing them with an in-house systematic review of waste characterization studies, which analyzed residential waste generation data collected from more than 20 states over the past 20 years to set a rough baseline for household waste in landfills.

This new methodology allows us to produce a more accurate estimate, and importantly, to measure change over time in both absolute and relative consumer waste.

Nevertheless, calculating total annual waste required making several assumptions that introduce uncertainty. This includes:
  • Scaling estimates to account for respondent underreporting, a well-documented phenomenon

  • Scaling estimates to account for inedible parts

  • Accounting for elevated waste during holidays

  • Mapping food categories used in the surveys to ReFED’s food categories.

Previously, ReFED used the USDA Consumer-Level Food Loss Estimates [34] [53], which are the basis of the USDA ERS Loss-Adjusted Food Availability per Capita Dataset [5].

Residential Food Surplus Causes

Raw data and documentation: - https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Residential_CauseBreakdown_2010-2014.xlsx - https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Residential_CauseBreakdown_2015-2019.xlsx

As a part of a three-city study (New York, Nashville, Denver), Natural Resources Defense Council (NRDC) conducted an in-home study[35] where participants documented the weight and type of foods wasted over a two week period. Participants also documented the reason why they wasted the food and what they did with it (e.g., disposed of down the drain, trash, fed to animals, composting). ReFED used this data to quantify the causes of residential food waste by year, state, and food type.

There are a few limitations to using this data source for this purpose: (1) Although the study results were similar across the cities covered, rural areas were not covered. If variations in disposal habits vary in rural areas versus cities, these variations are not captured in the data. (2) Another limitation is that the two week timespan may not have been long enough to capture refrigerator cleanouts, which may have resulted in an underestimation of causes such as date label expiration and unwanted leftovers if study participants postponed their refrigerator cleanouts until the study was over. (3) Finally, because it was a one-time study, the data does not provide insight into consumer changes in disposal habits over time. Although this causal data is invaluable for understanding the major drivers of food waste in homes, more research is needed to address these data gaps.

Residential Food Surplus Destinations

ReFED also used the NRDC Home Kitchen Diaries[35] to quantify the destination breakdown of residential food surplus. The same strengths and weaknesses of the causal data listed above apply to the destinations component of the study as well. Additionally, it’s possible that the residential composting numbers may be higher than the U.S. average due to selection bias of the people that chose to participate in the study.

ReFED further broke down the NRDC “Trash” numbers into the portion that is landfill versus incineration in each state according to BioCycle’s 2010 “State of Garbage in America” survey[42], which was conducted in partnership with the Earth Engineering Center of Columbia University[8]. Because these surveys were discontinued in 2010 and no other state-level data sources exist, ReFED is reusing these estimates year over year to estimate the percentage of “trash” that is sent to incineration versus landfillnfacilities in each state.

Data Quality Evaluation

This rubric is designed to evaluate the quality of how each data source was utilized by ReFED to estimate food loss and waste. It is not meant to rate the quality of the study itself. See Appendix AA for more information about the ReFED Data Quality Rubric.

Table 20. Data Quality Evaluation for Food Waste Monitor Residential Sector

DATA

SOURCE

DATA QUALITY SCORE

CREDIBILITY

UPDATE FREQUENCY

COVERAGE

FOOD TYPE

GEOGRAPHY

SCORE

WEIGHT

RESIDENTIAL SURPLUS DATA

Retail Value Purchased at Grocery Stores

Nielsen Point-of-sale (POS) Data

4

5

5

5

5

High 24/5 = 4.8

17%

Tons Purchased at Grocery Stores

Nielsen Point-of-sale (POS) Data

4

5

5

5

5

High 24/5 = 4.8

17%

% of Food Obtained from Grocery Stores

USDA NHANES Survey

5

5

5

5

3

High 23/5 = 4.6

33%

Surplus Rate

National Household Food Waste Tracking Survey

4

5

5

4

3

High 21/5=4.2

33%

4.8 * 17% + 4.8 * 17% + 4.6 * 33% + 4.2 * 33% = 4.54

High

RESIDENTIAL CAUSES DATA

% Surplus Due to Cause

NRDC Home Kitchen Diaries

5

1

1

4

2

Low 13/5 = 2.6

100%

2.6 * 100% = 2.6

Low

RESIDENTIAL DESTINATIONS DATA

% Destination Breakdown

NRDC Home Kitchen Diaries

5

1

1

4

2

Low 13/5 = 2.6

95%

% of Trash landfill vs incineration

Biocycle/Columbia University Survey

5

1

5

1

5

Medium 17/5 = 3.4

5%

2.6 * 95% + 3.4 * 5% = 2.64

Low