🎓 Lesson 8 D5

Real-World Project Walkthrough

Carbon footprinting a mining supply chain means adding up all the greenhouse gas emissions—from digging ore to delivering metal—to see how much climate impact the whole process creates.

🎯 Learning Objectives

  • Calculate Scope 1, 2, and upstream Scope 3 emissions for a blast-to-haul operation using activity data and emission factors
  • Analyze trade-offs between blast optimization (e.g., finer fragmentation) and downstream transport/processing emissions
  • Apply GHG Protocol boundaries to define system scope for a mine-to-port supply chain
  • Explain how explosive selection (ANFO vs. emulsion) affects total cradle-to-gate CO₂e intensity
  • Design a simplified carbon footprint dashboard for a mid-sized open-pit operation

📖 Why This Matters

Every tonne of copper or iron ore moved involves diesel trucks, electricity-powered crushers, and manufactured explosives—each emitting CO₂, CH₄, and N₂O. With global net-zero mandates accelerating (e.g., EU CBAM, SEC climate disclosure rules), mining companies now face investor pressure, regulatory reporting, and contract requirements tied to verified carbon footprints. Ignoring supply chain emissions risks stranded assets, lost tenders, and reputational damage—while accurate footprinting unlocks efficiency gains: optimizing blast design can reduce haul cycles by 12–18%, cutting both fuel use and costs.

📘 Core Principles

Carbon footprinting in mining hinges on three pillars: (1) System boundary definition—distinguishing operational control (Scope 1 & 2) from value-chain responsibility (Scope 3); (2) Activity-based accounting—converting physical flows (litres of diesel, kg of ANFO, kWh of grid power) into CO₂e using standardized emission factors; and (3) Tiered data quality—prioritizing primary plant data (Tier 1) over regional averages (Tier 3) per GHG Protocol guidance. Crucially, blasting is a high-leverage intervention point: improved fragmentation reduces secondary crushing energy and haul truck cycles, shifting emissions from Scope 1 (diesel) to Scope 2 (grid electricity)—with net reductions possible only if grid decarbonization is factored in.

📐 Total Cradle-to-Gate Emissions (Blast-to-Stockpile)

This formula aggregates emissions across key blasting-adjacent supply chain nodes using activity data and emission factors. It supports comparative analysis of blast designs (e.g., tighter spacing vs. higher burden) on total carbon intensity per tonne of milled ore.

💡 Worked Example

Problem: A copper mine blasts 50,000 t of ore per month. Diesel haul trucks consume 185,000 L/month (EF = 2.68 kg CO₂e/L). Explosives used: 22,000 kg ANFO (EF = 3.2 kg CO₂e/kg, including ammonium nitrate production & transport). Grid power for crushing: 1.2 GWh/month (local grid EF = 0.42 kg CO₂e/kWh). Calculate total monthly CO₂e.
1. Step 1: Hauling emissions = 185,000 L × 2.68 kg CO₂e/L = 495,800 kg CO₂e
2. Step 2: Explosives emissions = 22,000 kg × 3.2 kg CO₂e/kg = 70,400 kg CO₂e
3. Step 3: Crushing emissions = 1,200,000 kWh × 0.42 kg CO₂e/kWh = 504,000 kg CO₂e
4. Step 4: Sum = 495,800 + 70,400 + 504,000 = 1,070,200 kg CO₂e = 1,070 t CO₂e/month
Answer: The result is 1,070 t CO₂e/month, or 21.4 kg CO₂e per tonne of blasted ore—within the typical range of 15–35 kg CO₂e/t for mid-tier open-pit operations using fossil grid power.

🏗️ Real-World Application

At BHP’s Escondida Mine (Chile), engineers integrated carbon footprinting into blast design optimization in 2022. By reducing burden from 5.2 m to 4.6 m and increasing hole density, they achieved 18% better fragmentation (D₈₀ reduced from 85 cm to 69 cm), cutting average haul cycles per tonne by 15%. Coupled with fleet telematics and a 20% shift to blended ANFO-emulsion (lower NOₓ and embodied carbon), the change reduced cradle-to-crusher emissions by 9.3 kg CO₂e/t — validated via third-party ISO 14064-3 verification. The project paid back in <18 months via diesel savings alone.

📋 Case Connection

📋 Cost Optimization in Supply Chain Carbon Footprinting

Maintaining quality while reducing costs

📚 References