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Area

Climate & GHG accounting

Emissions accounting Scope 1–3 Provenance Geospatial Machine learning

Greenhouse-gas inventories, plant-level emissions analysis, Scope 1–3 readiness — most of my applied climate work sits here, turning messy, scattered emissions data into numbers someone can trace and defend. Two things recur across it — plant-level and facility-level emissions analysis on the research side, and audit-ready greenhouse-gas inventories on the practice side. In both, the discipline is the same: pin every factor and every derived value to its source, and keep the difference between a measurement and an estimate visible. I work senior-led, on the keys myself.

Method

The method here

The capabilities I lean on most in this area: data integration and ETL across inconsistent sources; geospatial analysis and spatial joins for facility-level questions; data science, including machine-learning gap-fill where records are incomplete; and a provenance-and-verification discipline so every factor traces back to its source. Where a value is model-derived rather than measured, I keep that distinction on the record — it matters to anyone reusing or assuring the number.

Where this area leads

If you're heading toward mandatory disclosure or third-party assurance, the compliance lane is the direct route. Tell me the filing you're preparing for and where your inventory stands.