Midwest Grain Shipment Optimization

Case Study: Midwest Grain Shipment Optimization

Scenario A regional grain cooperative in Iowa ships harvested corn from rural elevators near Des Moines to a rail transload facility in Chicago for onward export. The project involved selecting between two intermodal options: (1) dedicated diesel-powered line-haul trucks (short-haul leg only), and (2) a hybrid truck-rail corridor using Class I rail for the majority of the journey. Constraints included strict delivery windows (±4 hours), limited terminal dwell time (<6 hrs), and a corporate net-zero roadmap requiring verified emissions tracking per ton-mile.

Given Data

• Distance: 520 miles (Des Moines → Chicago)
• Payload: 24.5 tons (standard grain trailer load)
• Fuel consumption: 0.062 gallons/mile (for optimized Class 8 tractor with aerodynamic trailer)
• Emission factor: 22.4 g CO₂e/gallon (EPA 2023 diesel baseline)

Calculation The tool computes carbon emissions per ton-mile as:

Carbon Emissions per Ton-Mile = (Fuel Consumption × Emission Factor) ÷ Payload

Substituting values:

• Fuel Consumption × Emission Factor = 0.062 gal/mi × 22.4 g CO₂e/gal = 1.3888 g CO₂e/mi
• Convert to kg: 1.3888 g/mi = 0.0013888 kg/mi
• Divide by payload: 0.0013888 kg/mi ÷ 24.5 tons = 0.0567 kg CO₂e/ton-mile

Rounded to two decimal places per tool specification: 0.06 kg CO₂e/ton-mile

Result and Decision This value (0.06) was benchmarked against the rail-heavy alternative (calculated separately at 0.021 kg CO₂e/ton-mile). Although the truck-only option met schedule requirements, its emissions intensity was nearly 3× higher. The cooperative opted for the intermodal rail solution — contracting with BNSF for priority block train service — despite a $12/ton cost premium. They also implemented real-time telematics to validate fuel use and onboarded the calculator into their quarterly sustainability reporting.

Lesson Even modest payload increases (e.g., from 20 to 24.5 tons) meaningfully reduce emissions intensity — but only if vehicle utilization is maximized without compromising safety or axle weight limits. Load optimization must be paired with modal shift analysis to avoid false efficiency gains.