An official website of the United States government
Abstract The United States Food Loss and Waste Reduction Goal seeks to reduce national food waste by 50%, down to 74 kg per capita, by 2030. Here we investigate state policies’ alignment with the federal goal across four policy categories. We develop a policy scoring matrix and apply it to wasted food solutions listed in the non-profit ReFED’s database to derive ranges of food waste diversion potential and projected generation across states. On the basis of state policies alone, no state can meet the federal target. We estimated a diversion potential of 5–14 kg per capita and a food waste generation of 149 kg per capita nationally in 2022, equivalent to the 2016 baseline. Without additional intervention at the state and federal level promoting a shift from food waste recycling towards prevention, rescue and repurposing, food generation in the United States will probably remain high.
more »
« less
Food waste, date labels, and risk preferences: An experimental exploration
Abstract This study provides theoretical and experimental evidence that consumers adjust their premeditated food waste by date labels and their risk and loss preferences. The “Use by” date label leads to more premeditated food waste than “Best by” for deli meat and spaghetti sauce. However, changing date labels may not lower premeditated food waste relative to no label at all. Greater loss aversion correlates with higher premeditated food waste regardless of date labels and products. For participants with high loss aversion, they have higher premediated waste with no statistical difference in response for “Best by” and “Use by” labels. These results highlight the heterogeneous response to date labels.
more »
« less
- Award ID(s):
- 2115405
- PAR ID:
- 10600494
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Applied Economic Perspectives and Policy
- Volume:
- 47
- Issue:
- 3
- ISSN:
- 2040-5790
- Format(s):
- Medium: X Size: p. 1029-1057
- Size(s):
- p. 1029-1057
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Systems‐level approaches are required for addressing the world's major challenges at the food–energy–water nexus. Taking on complex issues, such as rising food insecurity, malnutrition, and food waste, concomitant with unprecedented levels of stress on environmental systems, will necessitate that future scholars and decision makers be prepared through transdisciplinary student training. However, in higher education, students tend to be siloed within their discipline. In this study, we present a case for the development of transdisciplinary graduate student training based on an inter‐institutional and fully remote group of graduate students who assembled during the COVID‐19 pandemic to address the issue of food waste. We use our wide‐ranging disciplinary backgrounds, high‐performance transdisciplinary team training, and stakeholder feedback to develop and conduct a weeklong social media campaign to share educational resources for reducing household food waste. This work offers valuable lessons learned through the student's lens to those seeking to create or improve future transdisciplinary training methods for tackling food waste and other global grand challenges. Key insights from this process include the importance of accountability and open communication when conducting collaborative teamwork, the utility of various mobile and online tools for effectively facilitating remote group work, and the vital role of transdisciplinarity in devising creative solutions.more » « less
-
Abstract Reducing food loss and waste can improve the efficiency of food supply chains and provide food security. Here we estimate mass flow as well as food loss and waste along the US food supply chain for 10 commodity groups and nine management pathways to provide a baseline for designing efficient strategies to reduce, recycle, and recover food loss and waste. We estimate a total food loss and waste of 335.4 million metric tonnes from the U.S. food supply chain in 2016. Water evaporation (19%), recycling (55%), and landfill, incineration, or wastewater treatment (23%) accounted for most of the loss and waste. The consumption stage accounted for 57% of the food loss and waste disposed of through landfill, incineration, or wastewater treatment. Manufacturing was the largest contributor to food loss and waste (61%) but had a high recycling rate. High demand, perishable products accounted for 67% of food waste. We suggest that funding for infrastructure and incentives for earlier food donation can promote efficiency and sustainability of the supply chain, promote FLW collection and recycling along the U.S. FSC, and improve consumer education in order to move towards a circular economy.more » « less
-
In this paper, we answer the question of when inserting label noise (less informative labels) can instead return us more accurate and fair models. We are primarily inspired by three observations: 1) In contrast to reducing label noise rates, increasing the noise rates is easy to implement; 2) Increasing a certain class of instances' label noise to balance the noise rates (increasing-to-balancing) results in an easier learning problem; 3) Increasing-to-balancing improves fairness guarantees against label bias. In this paper, we first quantify the trade-offs introduced by increasing a certain group of instances' label noise rate w.r.t. the loss of label informativeness and the lowered learning difficulties. We analytically demonstrate when such an increase is beneficial, in terms of either improved generalization power or the fairness guarantees. Then we present a method to insert label noise properly for the task of learning with noisy labels, either without or with a fairness constraint. The primary technical challenge we face is due to the fact that we would not know which data instances are suffering from higher noise, and we would not have the ground truth labels to verify any possible hypothesis. We propose a detection method that informs us which group of labels might suffer from higher noise without using ground truth labels. We formally establish the effectiveness of the proposed solution and demonstrate it with extensive experiments.more » « less
-
PurposeFreezing extends the shelf life of food. Home freezing of fresh foods and the purchase of frozen foods have been advocated as approaches to reduce food waste in US households. This paper discusses how commonly US households apply these practices, quantifies frozen food waste and relates these practices to food waste. Design/methodology/approachWe add questions to the summer 2022 wave of the US Household Food Waste Tracking Survey. The novel survey data provide important baseline information and household behaviours, such as food waste, home freezing of fresh food and the purchase of frozen foods. We analyse the association among these behaviours from more than 1,000 US households. FindingsWe find that US household wastes about 26 g per person per week of food that was once frozen, which is about 6% of all household food waste. The finding indicates that a small portion of food waste in US households comes from frozen food. Vegetables and meats are the most commonly discarded frozen foods. Among the frozen items reported as discarded, about 30% were purchased as frozen rather than purchased fresh and then frozen at home by the consumer and about 30% more were reported as discarded from the refrigerator rather than directly from the freezer. The findings are important for informing strategies to reduce household food waste. Research limitations/implicationsWhile the data provide important baseline information and correlate the use of freezing with lower waste levels, more work is needed to understand if interventions encouraging frozen food purchase or home freezing would reduce household food waste. Originality/valueWe provide unique, detailed information about the quantity of frozen food waste in US households and the relationships between consumer food waste and the practices of frozen food purchasing and home freezing.more » « less
