Key Takeaways
- Global e-waste generation reached 53.6 million metric tons in 2019.
- E-waste from large equipment accounted for 44.4% of total global e-waste in 2019.
- Small equipment generated 29.7 million tons of e-waste globally in 2019.
- Only 17.4% of global e-waste was formally recycled in 2019.
- Europe recycled 42.5% of its e-waste in 2019.
- US electronics recycling rate was 15% in 2018.
- Improper disposal releases 0.4 million tons of heavy metals yearly.
- E-waste contributes 70% of toxic waste in landfills.
- Annual e-waste pollution equals 1.5 million tons of CO2.
- Global e-waste value of materials $57 billion in 2019.
- Recovered metals from e-waste worth $10 billion yearly.
- Gold in e-waste valued at $15 billion annually.
- WEEE Directive covers 12 categories of e-waste.
- Basel Convention regulates transboundary e-waste movement.
- US has 25 state e-waste laws.
Electronic recycling is vital as global e-waste grows rapidly while formal recycling rates remain low.
E-waste Generation
E-waste Generation Interpretation
Economic Value
Economic Value Interpretation
Environmental Impact
Environmental Impact Interpretation
Policies and Initiatives
Policies and Initiatives Interpretation
Recycling Rates
Recycling Rates Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Aisha Okonkwo. (2026, February 13). Electronic Recycling Statistics. Gitnux. https://gitnux.org/electronic-recycling-statistics
Aisha Okonkwo. "Electronic Recycling Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/electronic-recycling-statistics.
Aisha Okonkwo. 2026. "Electronic Recycling Statistics." Gitnux. https://gitnux.org/electronic-recycling-statistics.
Sources & References
- Reference 1EWASTEMONITORewastemonitor.infoVisit source
- Reference 2EPAepa.govVisit source
- Reference 3UNITARunitar.orgVisit source
- Reference 4ECec.europa.euVisit source
- Reference 5CALRECYCLEcalrecycle.ca.govVisit source
- Reference 6GSMAgsma.comVisit source
- Reference 7DCCEEWdcceew.gov.auVisit source
- Reference 8GOVgov.ukVisit source
- Reference 9ENVenv.go.jpVisit source
- Reference 10KECOkeco.or.krVisit source
- Reference 11CANADAcanada.caVisit source
- Reference 12MEEmee.gov.cnVisit source
- Reference 13CPCBcpcb.nic.inVisit source
- Reference 14WHOwho.intVisit source
- Reference 15PLASTICPOLLUTIONCOALITIONplasticpollutioncoalition.orgVisit source
- Reference 16BASELbasel.intVisit source
- Reference 17UNEPunep.orgVisit source
- Reference 18STATISTAstatista.comVisit source
- Reference 19IEAiea.orgVisit source
- Reference 20MARKETSANDMARKETSmarketsandmarkets.comVisit source
- Reference 21OECDoecd.orgVisit source
- Reference 22STEP-INITIATIVEstep-initiative.orgVisit source
- Reference 23SERNsern.orgVisit source
- Reference 24DECdec.ny.govVisit source






