Consider two identical plants consuming the same total electricity. The first draws it all from the grid. The second draws half and generates the rest on diesel.
The first reports a clean Scope 2 figure and almost nothing in Scope 1. The second reports half that Scope 2, plus a substantial Scope 1 figure at a completely different emission factor — and, because diesel generation is considerably more carbon-intensive per unit of electricity than most grid supply, a higher total.
Those are not small differences. For a plant running significant generation, the split determines both the size of the footprint and where it sits in the disclosure. And a platform that assumes continuous grid supply will never ask the question — it will take your kilowatt-hours, apply a grid factor, and report a number that is internally consistent and wrong.
This is the clearest single example of why factor sets and data models built for other markets fail here. The arithmetic is not harder. The question is different.
A group running six plants and a dozen depots does not have a harder measurement problem than one running a single site. It has a harder collection problem: twenty separate sets of readings arriving at twenty different levels of reliability, on a monthly cycle, from people whose primary job is production.
Central spreadsheets fail at this reliably. The failure is not technical — it is that the sustainability lead becomes the single point through which every figure must pass, and they cannot chase twenty sites and also do the analysis.
Structured intake moves entry to the site and leaves the centre reviewing status. That is the difference between a cycle that closes and one that runs three months late every year.
Cement, iron and steel, aluminium and fertilisers are on the CBAM list. If you export any of them into the EU, your buyer has a declaration obligation and will pass a data request to you — typically well before any Nigerian mandate reaches you.
What they need is emissions embedded per tonne of product from a specific installation, which requires production volumes alongside energy and process data and a documented allocation across grades and outputs. Start capturing production volumes in the same system as the energy data and the allocation becomes arithmetic rather than a project.
For a total it is workable. For anything useful it is not: site-level fuel hides which unit is inefficient, makes maintenance decisions invisible, and gives you nothing to act on. Per-generator metering is a modest cost and it is where the operational savings come from.
Fuel into a captive plant you own and operate is Scope 1, and the electricity it produces is not purchased so it never enters Scope 2. If you export surplus power to a third party there are allocation questions — take advice, and document the treatment.
Yes, and for manufacturers it is usually the more useful figure. Absolute emissions rise with production; intensity shows whether you are actually getting more efficient. It is also what CBAM effectively asks for, so you are building it anyway.
It distorts intensity in both directions, and you should say so. Disclosing utilisation alongside intensity lets a reader separate an efficiency improvement from a demand change — and stops you claiming credit for a downturn.
A summary of a regulation is not the regulation. These are the primary documents this page is based on.
Four questions, and you get the year you first file, the framework, and what to collect first.
Plain-language explainers of the FRC and SEC rules, ISSB S1 & S2, and what each asks you to disclose.
What a consultant-led reporting cycle costs against an annual licence, in Naira.
