Overview of Impact Calculator
In 2016, ReFED launched its landmark Roadmap to Reduce U.S. Food Waste by 20%. That initial report became a touchstone for those in the food waste space, but there was a growing need for more – and more granular — data about the issue to fill in knowledge gaps and move the food system from awareness about the issue to insight-driven action. The newly developed ReFED Insights Engine is the next generation of data, insights, and guidance on U.S. food waste. This online data and solutions hub for food loss and waste is designed to provide anyone interested in food waste reduction with the information and insights they need to take meaningful action. Informed decision making is needed to achieve national and international goals of reducing food waste by 50 percent by 2030.
- Current ReFED Insights Engine tools include:
Food Waste Monitor: Centralized, trusted repository of information built with data from more than 50 public and proprietary datasets that shows how much food is being wasted in the U.S., why it’s happening, and where it goes.
Impact Calculator: Quantifies the impact of wasted food on the climate, natural resources, and recoverable meals.
Solutions Database: Provides a stakeholder-specific, comprehensive analysis of 40+ food waste reduction solutions based on impact goals, along with detailed fact sheets on each.
Solution Provider Directory: Connects users with a vetted list of 700+ nonprofit and for-profit organizations ready to help implement food waste reduction solutions.
The Impact Calculator quantifies greenhouse gas emissions reduction, water savings, and donated meal recovery potential of different food surplus management scenarios in the U.S. by sector and food type. Before creating this tool, the ReFED team sought feedback from its network of industry professionals from businesses, capital providers, government, nonprofits, and academia. The Impact Calculator was designed to incorporate this feedback and fill key needs and data gaps not covered by existing tools in the market. The following thematic areas summarize the rationale for developing this tool and its features:
- New and More Granular Information
Additional destinations: In the U.S., the most commonly used tool for evaluating the greenhouse gas impact of various food surplus management scenarios has been the EPA WARM tool. Currently the EPA WARM tool only includes four surplus food destinations (composting, anaerobic digestion, landfill, and prevention; Prevention is referred to as source reduction in WARM.). The Impact Calculator was designed to analyze twelve destinations of surplus food including the EPA WARM destinations as well as donations, animal feed, industrial uses, not harvested, land application, incineration, sewer, and dumping.
Sector-specific GHG data: Due to the lack of readily available data, food waste experts have long employed the practice of using the same GHG factor to quantify the impact of wasting a particular food type, regardless of where in the supply chain the surplus food happens. The reality is that impact factors vary greatly depending on where in the supply chain the surplus happens because greenhouse gas emissions accrue from stage to stage. If a strawberry is wasted on a farm, for example, the footprint shouldn’t include emissions that haven’t happened yet (e.g. transportation of the strawberry to a grocery store, refrigeration at the grocery store, transportation to a consumer’s home, etc.). The Impact Calculator is the first tool to make this data and analysis readily available on a sector-specific basis by using sector-specific GHG factors developed by Quantis (See Appendix A).
More food types: Again, due to the lack of readily available data, prior tools did not include data for all food types and was particularly lacking for prepared food items in foodservice and complex foods that you might find in the dry goods or frozen aisles of a grocery store (e.g., canned soup, frozen meals). The Impact Calculator was designed to cover all food types and includes nine comprehensive categories: Breads & Bakery, Dairy & Eggs, Dry Goods, Fresh Meat & Seafood, Frozen, Prepared Foods, Produce, Ready-to-drink Beverages, and “Standard Mix”. The “Standard Mix” option was created for cases when the exact food type makeup is unknown, which was one of the most highly requested features for the Impact Calculator. Many times a person using the tool might not know exactly what food types were wasted (e.g., they might only know the weight of food in a compost bin). The Standard Mix factors were developed to represent the typical food type makeup of surplus food in each sector in the U.S. using the waste characterization output of ReFED’s Food Waste Monitor[__citation_ReFED_Insights_Engine__], rather than using a flat average of impact factors for multiple food types as prior tools have done (e.g. flat average of breads, meat, etc.).
- Interactivity and Automation
User-friendly online format: Before the Impact Calculator, similar tools existed in Excel-based formats or more technical Life Cycle Assessment (LCA) software formats. Stakeholders described spending hours learning how to use these prior tools and expressed the need to be able to quickly input information and view results without this time-intensive learning curve. The Impact Calculator allows users to input information and view results in seconds.
Quick updates and rapid feedback loop: A custom, automated web application allows the data behind the Impact Calculator to be quickly updated as new information becomes available. This reduces the time required to update the tool to hours instead of months or years.
Open source data: Raw data and documentation is now made publicly available as much as legally possible. Confidential data is only used in cases where it yielded significant advantages over publicly available data.
- Adaptable Framework
Methodology can be expanded to other countries if needed: Because the past Roadmap served as inspiration for many other food waste initiatives at the international level, this platform was intentionally designed to be expanded to other countries using geographically specific data.