📥 Input Data

Each calculation relies solely on the information entered by the seller when publishing a listing:

Field	Role
Listing title	Identifies waste type → selects CO₂ and health factor
Weight (lb)	Primary variable for all calculations
City	Geolocation of impact

🌱 Section 1 — CO₂ Impact

Principle

Recycling one tonne of metal, paper or plastic avoids the CO₂ emissions that would have been produced by virgin raw material extraction or by informal landfilling and burning of the waste.

Formula

Example : 24 lb of copper → 0.011 t × 3.5 = 0.0385 t CO₂ avoided (38.5 kg)

Waste type detection

The plugin analyzes the listing title and compares it against a keyword list (French + English). The first recognized keyword determines the factor applied. If no keyword matches, a conservative factor of 1.0 t CO₂/t is used.

Main CO₂ factors (source: ADEME Base Carbone)

Material	t CO₂ avoided / tonne recycled	Justification
Aluminum	9,5	Avoids Hall-Héroult electrolysis
Cuivre / Copper	3,5	Avoids pyrometallurgy
Bronze	3,2	Copper/tin alloy
Laiton / Brass	3,0	Copper/zinc alloy
Inox / Stainless steel	2,5	Avoids virgin nickel addition
Fer / Acier / Steel	1,8	Avoids blast furnace
E-waste / Electronics	4,0	High precious metal density
Lithium battery	5,0	Lithium, cobalt, nickel extraction
Papier / Paper	0,9	Avoids deforestation + methane
Plastique PET / PET Plastic	1,5	Avoids naphtha cracking
Default (unrecognized)	1,0	Conservative value

Displayed equivalents

• Trees/year : CO₂ (t) × 45 — 1 mature tree absorbs ~22 kg CO₂/year (FAO)
• Car km avoided : CO₂ (t) × 6 000 — average car ~120g CO₂/km (ADEME)

🔬 Section 2 — Pollutant Exposure Risk Reduction Indicators

Scientific context

Informal recycling is one of the main sources of heavy metal exposure in collection areas. These indicators estimate the quantity of pollutants diverted from informal recycling (cable burning, battery dismantling, e-waste processing) toward controlled formal channels. They represent an estimated exposure risk reduction — not causal clinical impact attribution.

The 4 estimated diversion indicators

🔴 Lead diverted — estimate (kg)

Source: Pure Earth (2016), WHO Lead Exposure Report (2021) — factor 0.5 kg/t (conservative).
Risk context: lead is associated with neurodevelopmental effects in children — WHO states there is no safe exposure threshold.

☁️ PM2.5 diverted — estimate (kg)

Source: EPA AP-42 (2022) — burning one tonne of cables generates ~15 kg of PM2.5 under field conditions.
Risk context: PM2.5 is associated with respiratory disease — proxy for exposure risk reduction.

⚠️ Cadmium diverted — estimate (g)

Source: Pure Earth Toxic Sites Database (2020), UNEP (2018) — 200g cadmium/tonne of e-waste.
Risk context: cadmium is associated with kidney damage — proxy for exposure risk reduction.

🧠 Mercury diverted — estimate (g)

Source: UNEP Minamata Convention (2018) — 50g mercury/tonne of electronic equipment.
Risk context: mercury is a neurotoxin — proxy for exposure risk reduction even at low doses.

Exposure Risk Reduction Index (ERRI)

📚 Official Sources

⚠️ Limitations & Validation Status

These indicators are conservative estimates based on global emission factors (WHO, Pure Earth, EPA, UNEP). They represent an estimated pollutant exposure risk reduction — they do not constitute causal clinical impact attribution and have not been peer-reviewed.

Transitional measurement system: FerayPro Tracer starts with conservative global coefficients as a baseline, and evolves toward locally validated models through field data collected in Morocco and the DRC (Phase 2). Phase 2 results will include statistical confidence intervals.

FerayPro Tracer — Open Source MIT — View live dashboard →