Data methodology
How the numbers are calculated.
Zerra presents government-published data as clearly as possible. Where we make calculations — like CO₂ avoided — this page explains the method, the assumptions, and the limitations.
01
Data sources
Zerra draws from three primary sources. All are authoritative, publicly available, and accessed programmatically — not manually refreshed from static files.
Clean Energy Regulator — Small-scale Installation Postcode Data
Monthly postcode-level counts of approved small-scale renewable energy installations — solar PV, batteries, wind, hydro, and heat pumps. Accessed via the CER API. Only includes installations that have had their STC application approved; pending applications are excluded.
Monthly
OpenElectricity — Grid Emissions Intensity
7-day rolling average grid emissions intensity by NEM region (NSW1, QLD1, VIC1, SA1, TAS1) and WEM (Western Australia). Accessed via the OpenElectricity API. Used for real-time CO₂ calculations on postcode pages. Falls back to AEMO/CER 2024 annual averages when the live API is unavailable.
Live
CER Quarterly Carbon Market Report (Q3 2025)
Published quarterly by the Clean Energy Regulator. Used for market-level totals — ACCU issuances, LGC volumes, and carbon project counts shown on the Market Pulse page. These figures are updated quarterly, not live.
Quarterly
02
How CO₂ savings are calculated
Each postcode page shows an estimated annual CO₂ avoided by all solar systems in that postcode combined. This is a community total, not a per-household figure.
The calculation uses the following formula:
CO₂ avoided (tonnes/yr) =
Installations × Average system size (kW) × Capacity factor × Hours per year × Grid intensity (kg CO₂/kWh) ÷ 1,000
The cars-off-the-road equivalent uses 2.1 tonnes CO₂/year per average Australian passenger vehicle, based on the Australian Government's National Greenhouse Accounts methodology.
The homes-powered equivalent uses 5 tonnes CO₂/year per average Australian household electricity consumption.
03
Grid emissions intensity by state
Grid intensity is how much CO₂ is emitted per unit of electricity generated, expressed in grams per kilowatt-hour (gCO₂/kWh). It varies significantly by state depending on the fuel mix of generators on the grid.
Zerra uses a 7-day rolling average from OpenElectricity where available. When the live API is unavailable, the following annual average fallback values are used (AEMO/CER 2024):
| State / Territory |
Grid zone |
Fallback intensity |
| New South Wales / ACT | NSW1 | 790 gCO₂/kWh |
| Victoria | VIC1 | 980 gCO₂/kWh |
| Queensland | QLD1 | 810 gCO₂/kWh |
| South Australia | SA1 | 370 gCO₂/kWh |
| Western Australia | WEM | 630 gCO₂/kWh |
| Tasmania | TAS1 | 170 gCO₂/kWh |
| Northern Territory | N/A (not on NEM) | 640 gCO₂/kWh |
South Australia's low intensity reflects its high renewable penetration. Victoria's high intensity reflects its reliance on brown coal. As each state's grid mix changes over time, the live OpenElectricity values will reflect those changes — the fallback values are updated annually.
04
Data freshness
Different data on Zerra is updated at different cadences:
Grid emissions intensity
Updated live via the OpenElectricity API on each page load. The live widget on postcode pages reflects current grid conditions. The baked-in static text uses a 7-day average from the most recent build.
Live
Postcode installation counts
Rebuilt monthly from the CER postcode dataset. The date shown on each postcode page reflects the date of the last build run. Pages are regenerated automatically each month via a scheduled GitHub Actions workflow.
Monthly
05
Limitations & caveats
The CO₂ figures on Zerra are directional estimates — useful for understanding relative impact and community-level trends, but not certified audit figures. The following limitations apply:
12-month registration window. Under the Renewable Energy (Electricity) Act 2000, installers have up to 12 months after installation to create STCs. This means recent installation figures in the CER dataset are always a floor — they will continue to rise as late claims are processed. The numbers you see are the minimum, not the final count.
Average system size. The 9 kW figure is a national median. Actual system sizes vary by postcode, year of installation, and household type. Older installations tend to be smaller (3–5 kW); recent installations tend to be larger (10–13 kW). This introduces an estimation error that is larger for postcodes with predominantly older or newer stock.
Capacity factor. The 15.5% capacity factor is a national annual average. It varies by latitude (more solar hours in QLD than TAS), local shading, panel orientation, and system degradation over time. Postcodes in high-sunshine areas will generate more than this factor implies; dense urban postcodes may generate less.
Grid intensity variation. The 7-day rolling average smooths out daily and seasonal variation. A solar system generates most during the day when grid intensity is typically lower (other solar is also generating). Using a 24-hour average slightly overstates the CO₂ avoided, since the displacement happens during lower-intensity daytime hours.
Community total, not per household. The CO₂ figure represents the estimated combined output of all solar systems in a postcode — not what any individual household avoids. Divide by the number of installations for a rough per-system estimate.
06
Questions or corrections
If you find a data error, a calculation that doesn't match what you'd expect, or a postcode with incorrect suburb names, the best way to flag it is via the FAQ page or directly through the Clean Energy Regulator's own data portal.
Zerra is built on open government data. Every number on this site can be verified against the CER postcode dataset and the OpenElectricity API. That's the point.