How wrong is your Scope 2 number?
Most Australian commercial Scope 2 reports rely on an annual-average grid factor from DCCEEW. It’s the legally defensible default. It’s also, depending on when you operate, meaningfully wrong.
Below is an end-to-end worked example for an illustrative Australian commercial site. The intensity and consumption figures are representative — not a specific historical day — but the arithmetic is the same arithmetic gridIQ performs on actual meter data against actual half-hourly carbon intensity.
The illustrative site
An 8.6 MWh/day facility in New South Wales. Operations start at 06:00 and wind down after 22:00. Overnight load is minimal. 250 operating days per year. Annual consumption: 2,150 MWh.
Method 1 — location-based
Use a single annual-average grid intensity factor. For this worked example we use 0.68 tCO₂/MWh, which sits in the range of recent DCCEEW NSW factors (use the factor current at the time of your reporting period in practice).
This is the number that lands in most sustainability reports today. It’s fast to calculate and easy to defend. It’s also blind to when the site actually consumed.
Method 2 — time-matched market-based
Break the day into windows, match each window to the grid’s actual carbon intensity while consumption happened, then re-aggregate. A representative day for this site looks like:
| Window | MWh | Intensity (tCO₂/MWh) | Emissions (tCO₂) | Note |
|---|---|---|---|---|
| 00:00–06:00 | 0.5 | 0.72 | 0.36 | Overnight baseload — coal-heavy |
| 06:00–10:00 | 1.8 | 0.55 | 0.99 | Morning ramp — solar rising |
| 10:00–14:00 | 2.4 | 0.32 | 0.77 | Solar peak — renewables dominant |
| 14:00–18:00 | 2.0 | 0.48 | 0.96 | Solar fade, gas ramp |
| 18:00–22:00 | 1.3 | 0.71 | 0.92 | Evening peak — coal and gas |
| 22:00–24:00 | 0.6 | 0.70 | 0.42 | Late evening — coal baseload |
| Day total | 8.6 | 0.514 (wtd) | 4.42 |
Weighted daily intensity is 0.514 tCO₂/MWh — lower than the annual average because the site runs heavily during solar hours and barely operates overnight when the grid is coal-dominant.
The delta
For this illustrative daytime-weighted load, time-matching cuts reported emissions by roughly 24%. Flip the consumption profile to overnight-heavy and the delta flips too — time-matched emissions can come in higher than the location-based figure when load sits on coal baseload while the sun is down.
Which number is right?
Both are legitimate under GHG Protocol. The location-based figure is the baseline all entities must report. The market-based figure — including time-matched — is where the credible claim of actual grid impact lives. Under Australia’s emerging ASRS regime, assurance teams will increasingly expect both.
The trap is reporting only the location-based figure when your operations are genuinely greener than the annual average. You under-claim your emissions performance. The opposite trap — reporting only market-based when your load sits on overnight coal — is exactly the greenwashing ASRS is designed to prevent. Report both. Let the audit trail show the work.
How gridIQ does this automatically
Feed gridIQ your half-hourly meter data. It matches each interval to the grid carbon intensity calculated from the actual generation mix at that moment, stamps the DCCEEW factor version current during your reporting period, and returns both methods side by side with a full audit trail. Re-run the same period next year and you get the same numbers — the factor vintage stays locked to when you reported, not silently re-baselined as DCCEEW publishes updates.
Illustrative worked example. Intensity values and the location-based factor are representative of Australian NEM conditions but do not reflect a specific historical day or a specific customer. Use the DCCEEW factor current to your reporting period for defensible disclosure.