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What you’ll build in this exercise:
  • Create a comprehensive test dataset representing one month of Mangrove Biochar operations
  • Run the full calculation pipeline and validate every batch output
  • Verify all ledger balances reconcile
  • Document and fix any integration issues discovered during testing
This is the most comprehensive exercise in the course. You’ll load a full month of realistic test data, run the complete pipeline, and systematically validate every output. Think of this as a dress rehearsal for production. Prerequisites: Complete Lesson 5.1, Lesson 5.2, and Lesson 5.3. Your project should have all event types, models, batch partitioning, and LCA calculations from Modules 1-4.

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Part 1: Design (30 min)

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1. Define test scenarios

Plan your test dataset to cover all three scenario types:

Happy Path

Normal operations:
  • 4 typical deliveries (2-6 t)
  • 5 feedstock receipts
  • 3 lab analyses
  • Standard moisture (10-20%)
  • Typical H:C ratio (0.2-0.5)

Edge Cases

Boundary values:
  • 1 high-moisture receipt (50%)
  • 1 high H:C ratio analysis (0.75)
  • 1 very small delivery (0.5 t)
  • 1 zero-distance transport

Error Cases

Invalid data:
  • Missing a required datapoint
  • Event outside accounting period
  • Duplicate tracking IDs

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2. Calculate expected outputs

Before running the pipeline, calculate the expected output for every batch in a spreadsheet. Include:
  • Gross carbon for each delivery
  • Proportional emission allocation (by mass)
  • Direct transport emissions per delivery
  • Net carbon per batch
  • Ledger totals and balances

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3. Identify potential failure points

List what might go wrong:
  • Slug mismatches between new event types and model nodes
  • Date range issues with edge case events
  • Allocation denominators including edge case batches
  • Missing aggregation for energy consumption events

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Part 2: Build in Mangrove (1.5 hrs)

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Step 1: Create the January 2024 test dataset

Create the following events using Add Data or Bulk Import : 5 Feedstock Receipt events: 3 Lab Analysis events: 4 Biochar Delivery events: 1 Energy Consumption event (January):
  • Electricity: 12,000 kWh
  • Propane: 600 gallons
  • Period: Jan 1 – Jan 31
4 Transportation events:
Use bulk importfor faster data entry when creating many events. Prepare a CSV with all required columns matching your event type slugs.

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Step 2: Run the full pipeline

  1. Go to Production Accounting and generate batches for January 2024.
  2. Resolve any validation messages. These indicate missing or problematic data.
  3. Submit to generate batches.
If you see validation errors, don’t skip them. They’re the first sign of integration issues. Check the pitfalls from Lesson 5.3 to diagnose the root cause.

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Step 3: Validate batch outputs

For each of the 4 delivery batches, compare the pipeline output against your expected values:
1

Check gross carbon

Does the gross tCO2e for each batch match your spreadsheet? If not, check the production model nodes (dry mass → carbon → CO2 conversion).
2

Check emission allocation

Are electricity and propane emissions allocated proportionally by mass? Do the allocations across all batches sum to the total period emissions?
3

Check transport emissions

Is DEL-003’s transport emission zero (on-site delivery)? Are other deliveries’ transport emissions correct?
4

Check net carbon

Does net = gross - (allocated electricity + allocated propane + transport) for each batch?
5

Check edge case batches

DEL-004 (0.5 t): Is the net carbon very small or potentially negative? If negative, flag this. The methodology may require a minimum batch size or different handling.

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Step 4: Verify ledger reconciliation

Check each ledger’s balance:
If a ledger balance goes negative, it means you’re claiming more output than input at that stage. That’s a mass balance violation that must be resolved before reporting.

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Step 5: Document and fix issues

For every issue found:
  1. Describe the symptom: what output was wrong?
  2. Identify the root cause: which pitfall from Lesson 5.3?
  3. Apply the fix: update the configuration
  4. Re-run and verify: confirm the fix resolves the issue

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Success criteria

You have completed the Module 5 exercise when:
  • Test dataset created: 17 events across 5 event types covering happy path and edge cases
  • Pipeline executed: Generate Batches runs for January 2024 without unresolved validation errors
  • 4 batches generated: one per delivery, with correct gross and net carbon values
  • Batch outputs match: all values within 1% of your pre-calculated expected outputs
  • Emissions correctly allocated: proportional allocations sum to period totals, direct allocations are batch-specific
  • Ledger balances reconcile: no negative balances, inputs ≥ outputs at each stage
  • Edge cases handled: high moisture, high H:C, small delivery, and zero-distance transport produce correct results
  • Issues documented: any problems found during testing are documented with root cause and fix

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What’s next

Your Mangrove Biochar project now passes comprehensive testing. In Module 6: Advanced Patterns & Production you’ll learn best practices for model design, advanced techniques, and how to prepare your project for production deployment.