The research, led by Valentina Pusateri of the Technical University of Denmark together with Mikołaj Owsianiak, Marja Rinne, Stig I. Olsen, Michael Z. Hauschild, and Sami Kara, tackles a stubborn blind spot in environmental accounting. Life cycle assessment, the standard tool for measuring the environmental footprint of products, has long struggled with how to treat metal resources. Recent methodological advances have shifted the focus from simple resource depletion toward resource dissipation: the idea that a metal becomes a genuine loss when it flows into a sink from which future users cannot realistically recover it. But existing methods typically treat all unrecovered metals as equally dissipated, ignoring the crucial fact that some stocks are far easier to tap than others, and that accessibility shifts as technologies mature and ore grades decline.

The Danish-Australian team proposed an elegantly simple criterion built on comparative profitability. A metal in a given anthropogenic stock is classified as dissipated when the net present value of extracting it from that stock is lower than the net present value of extracting the same metal from the reference stock, which the researchers defined as the upper continental crust, the most plentiful and dominant source of metals. In other words, if mining companies can always make more profit pulling copper out of the ground than out of a landfill, the landfilled copper is effectively inaccessible, no matter how concentrated it is. The authors were careful to stress that this does not mean the metal cannot physically be extracted; it means that in a global economy with a plentiful alternative source, the stock will not become the dominant supply, and its metal functions remain out of reach for the system as a whole.

To operationalize this dissipation quotient, the team assembled an unusually comprehensive economic dataset. They screened more than 500 publications and reports, ultimately extracting capital and operating expenditure data from 45 studies covering extraction of gold, copper, and iron from mine tailings, landfills, and hoarded stock such as end-of-life electronics. All costs were harmonized to 2024 euros using GDP deflators and exchange rates, and allocated per kilogram of extracted metal. Because revenues from metals are set on global exchange markets regardless of origin, the comparison reduces to a battle of costs: whichever source delivers metal more cheaply wins, and the loser is classified as dissipated.

The numbers reveal stark differences between the three metals. Extracting copper from anthropogenic stocks costs between roughly 6 and 670 euros per kilogram, while gold extraction runs between 28,000 and 44,000 euros per kilogram, a gap of about three orders of magnitude driven by the vastly different concentrations of the metals in waste streams. Iron sits at the bottom of the range, from about 0.07 to 120 euros per kilogram. Hoarded stock, meaning discarded phones, computers, and circuit boards, proved the most expensive source overall, despite its high metal concentrations, because collecting and dismantling small, complex devices is costly. Landfills showed the lowest average extraction costs for copper and iron, while tailings generally emerged as the most accessible stock type across the analysis.

The crucial twist comes from the reference side of the equation. Ore grades have fallen steadily since large-scale mining began, and the researchers projected this decline forward using an exponential decline model calibrated on historical data, cross-checked with a power regression approach. Copper ore grades have historically declined by about 1.72 percent per year, gold by about 1.05 percent, and iron by 0.61 percent. Because energy for mining and processing is the dominant cost driver and rises steeply as grades fall, the cost of primary extraction is expected to climb. At a 25-year horizon, the projected grade decline raises reference extraction costs by less than 10 percent. But by 300 years, the present value of costs is expected to increase by roughly 20 percent for gold, 200 percent for copper, and a striking 330 percent for iron relative to today.

Running the dissipation criterion across three time horizons of 25, 100, and 300 years produced a nuanced and somewhat counterintuitive picture. Accessibility generally increases with time, as primary mining becomes more expensive and the economic gap narrows. Gold consistently emerged as the most accessible metal, classified as non-dissipated in hoarded electronic waste, which aligns with the fact that gold recovery is already the main economic driver of e-waste recycling. Iron in tailings also performed relatively well. By contrast, hoarded iron, drawn from electronic waste where iron is merely a structural contaminant rather than a recovery target, was classified as dissipated across the entire range of uncertainty at every time horizon, with cost differences reaching minus 311 euros per kilogram at 300 years. Most other metal-stock combinations remained, on average, dissipated even at 300 years, though the uncertainty ranges were wide enough that many straddled the boundary.

The team then asked whether technological learning could flip these classifications. Using the classic Wright’s law framework, which links cost reduction to growth in cumulative output, they calculated the learning rates that emerging extraction technologies would need to break even with primary mining. For most combinations the required learning rates ranged from about 40 to 80 percent per doubling of output, far above the 15 to 25 percent considered realistic for emerging technologies, making a reclassification unlikely. Tailings were the notable exception. Copper recovery from tailings would need learning rates of only 25 to 40 percent, gold less than 20 percent, values well within reach as technologies mature. This finding dovetails with real-world developments, as copper is already being extracted from old mine tailings that were once written off as inaccessible.

The authors are candid about the limitations. Data availability was uneven, with no cost data at all for gold in landfills, and abandoned or dispersed technosphere stocks had to be excluded entirely. The assumption that anthropogenic metal concentrations stay constant over time may not hold if these stocks become active supply sources, and the assumption that metals recovered from waste fetch the same market price as virgin metal may fail where purity is lower. Yet sensitivity analysis suggested that the classifications are more sensitive to technology maturity and learning than to plausible shifts in reference ore grades. Recognizing this irreducible uncertainty, the researchers recommend a careful vocabulary shift: stocks meeting the criterion should be labeled potentially dissipative, and those clearing it potentially non-dissipative, rather than treated as certainties.

The implications reach well beyond academic methodology. Current footprinting approaches, including influential methods that assume everything not recycled within a given timeframe is dissipated, may systematically overestimate resource use impacts by ignoring the metal-, stock-, and time-specific nature of accessibility. The dissipation curves and breakthrough times generated by this framework could feed directly into next-generation life cycle impact assessment metrics, replacing crude recycling-rate proxies with economically grounded estimates of when, and whether, the metals we bury today will serve future generations. In a world where maximum technical circularity is estimated at only 30 to 40 percent and primary extraction will dominate for decades, knowing which of our discarded riches are truly lost, and which are merely waiting for the economics to turn, is a question whose answer is finally taking quantitative shape.

Subject of Research: Economic dissipation of copper, gold, and iron in anthropogenic stocks for resource footprinting

Article Title: Determining the dissipation of copper, gold, and iron resources in anthropogenic stocks based on extraction economics

Article References: Pusateri, V., Owsianiak, M., Rinne, M., Olsen, S. I., Hauschild, M. Z., & Kara, S. (2026). Determining the dissipation of copper, gold, and iron resources in anthropogenic stocks based on extraction economics. Journal of Industrial Ecology, 30(4), 1743-1759. https://doi.org/10.1007/s44498-026-00118-9

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00118-9

Keywords: anthropogenic stocks, resource dissipation, life cycle assessment, circular economy, mine tailings, landfill mining, urban mining, ore grade decline, extraction economics, metal recycling, resource footprinting, technosphere