How can forecasting changes in electronic waste inform circular-economy planning?

In brief:

Project:
“Forecasting electronic waste flows for effective circular economy planning”

Focus:
Application of industrial-ecology theory to electronic waste

Type of research:
Predictive modelling

Lead researcher:
Dr. Callie Babbitt, Associate Professor, Department of Sustainability, Golisano Institute for Sustainability, Rochester Institute of Technology

Quick look:

• Product innovation far outpaces policies for managing electronic waste (e-waste): The makeup of consumer electronics—materials and technologies—entering the e-waste stream becomes more complex each year. Yet most policies for handling this waste in the U.S. lag far behind the pace of the market, leaving processors to recycle, repair, or refurbish products that are no longer in production and for which there is little demand.
• Limited economic scope: Most e-waste management strategies tend to focus on recovering high-value materials, like gold, that are increasingly diluted in the waste stream as products become more lightweight. This represents a missed opportunity for creating new economic value and sustainably diverting e-waste through circular-economy (CE) interventions.
• A shortening innovation curve for popular electronics: VCRs first entered the market in 1977 and grew in sales until 2000. DVD players, introduced in 1997, reached peak sales volume in less than half that time (nine years). GIS’s Dr. Callie Babbitt and a research team analyzed market adoption trends like these to chart the quickening pace at which consumer electronics emerge, peak, and, eventually, decline from use entirely.

The research:

Most well-known consumer electronic products share a similar life story: They each enter the market, change consumer expectations, and make older, well-known products obsolete. Over time, however, emerging technologies mature and become commonplace until they too are displaced by yet another innovation. Dr. Babbitt and her colleagues at GIS, in noticing this pattern, saw an opportunity for improving how policies addressing e-waste are developed.

In 2018, Dr. Babbitt worked with Dr. Roger Chen, a former assistant professor at GIS, and Shahana Althaf, a recent graduate of GIS’s doctoral program, to build a forecasting model for anticipating trends within the consumer electronics market with respect to waste management and material recovery. The tool was designed to help both U.S. states and companies plan for advancing CE objectives, such as green product design, reuse markets, and material-recovery technologies. It would also support efforts to engage businesses and other stakeholders in resource-conservation activities. More fundamentally, the forecasting model would give CE planners in both the public and private sectors a practical means for moving from a rear- to a forward-facing strategy in order to best direct resources to achieve sustainable results.

The GIS team began their research by reviewing and validating existing modeling methodologies to find a basic framework on which to build their own. They found that a material flow analysis (MFA) model best suited their goal. MFA is widely used by scientists to predict waste generation. Most often it is applied retrospectively, but Dr. Babbitt and her colleagues aimed to apply it proactively. However, few MFA models have been used to forecast the adoption of new technologies, a critical objective of the project.

Data is scarce when it comes to events that have yet to happen. To account for this, the researchers integrated an "S-shaped" logistics curve into the MFA model, a modeling technique originally developed by ecologists to analyze biological population growth. It has since been applied to other contexts, and is especially useful to industrial ecology, a key focus of Dr. Babbitt’s research. In place of a biological species, the researchers analyzed the growth and decline of over 15 different electronic products that have entered the market between 1962 and 2009. These included CRT (cathode-ray tube) monitors, desktop computers, printers, LED (light-emitting diode) monitors, LCD (liquid-crystal display) televisions, and laptops. An underlying logistics curve was established for these products using annual historical sales data. This was incorporated into the overall MFA model.

In the final stage of the study, the researchers applied the predictive model to forecast the adoption cycles for four case-study products representing new and emerging technologies (determined at the time of the study): fitness trackers, smart thermostats, drones, and OLED (organic light-emitting diode) TVs. The results showed that logistics forecasting can be used to predict flows of both older products with abundant historical data and emerging products with little adoption data in order to inform effective CE strategies.

Study results:

Mass-based e-waste policies fall short

The forecasting model could help government agencies to understand how shifts in consumer electronics impact e-waste flows. As products become smaller and lighter, recovery targets based solely on tonnage may miss opportunities for identifying CE pathways for electronics at the end of their useful lives. A broader approach may also reveal new kinds of eco-toxicity associated with emerging technologies that may not necessarily be tied to high-volume materials.

Anticipating future e-waste can create opportunities for urban mining

Cobalt, once common in laptop batteries, is used less and less in newer, lightweight battery technologies. The study forecasted that, by 2021, the projected flow of cobalt waste from discarded laptops will exceed its demand by about 100 metric tons. Foreseeing trends like this can help urban miners plan ahead to realize closed-loop solutions for rare-earth metals like cobalt. 

Forecasting tomorrow’s e-waste can practically support CE planning today

Applied to televisions, the model predicted how CRT TVs will disappear from e-waste streams as subsequent screen technologies age. By 2030, more than half of the nearly 400,000 metrics tons of televisions projected to be discarded in 2030 will be OLED screens. Little is presently known about either the environmental impacts of OLED materials or the potential for their reuse, but citing this trend could motivate efforts to find sustainable, circular pathways for them.

The model can be used to allocate resources within a CE

The study’s case-study methodology can easily be applied to other similar products using only a limited amount of data. Doing so will allow planners in the public and private sectors to cultivate circular pathways for valuable industrial components, like lithium-ion batteries, or for new materials with unknown reuse applications or environmental impacts, like carbon-based films in OLED screens.

Manufacturers can use the model to project their e-waste flows

Companies do not typically have the modeling capability to predict future waste flows, limiting their ability to set appropriate targets or plan for the management of end-of-life electronics. This model gives manufacturers agency within a CE by giving them the ability to project e-waste flows over a near-term time horizon.

Looking ahead:

Dr. Babbitt’s wider work is concerned with applications of industrial-ecology theory. She has designed a number of studies addressing consumer electronics, and currently is focusing her research on food waste and plastic packaging. Industrial ecology is a framework that looks to natural ecosystems to find a new way of thinking about how resources, like materials and energy, and waste are processed within an industrial economy.

See the full study ›

See all work by Dr. Babbitt ›