Power and industry are responsible for around two-thirds of carbon emissions and half of energy demand, and yet we are frequently kept in the dark about how the facilities that make up these sectors operate. For instance, verified country-level data from the International Energy Agency (IEA) is delayed by up to three years - and outside the EU and US, data is often untimely, unreliable or publicly unavailable.

These data gaps prevent decision-makers from making informed decisions that would help ensure an orderly and timely transition to a low-carbon economy.

Fortunately, this could change dramatically thanks to a revolution happening in space. Every part of earth is now photographed in high-resolution every day. Moreover, satellite providers are offering numerous different sensor types, such as Copernicus’s Sentinel-5 Precursor, which was launched in 2017 and measures sulphuric dioxide, nitrogen dioxide, carbon monoxide, formaldehyde, ozone and methane. This imagery offers a potentially powerful response to those governments and asset owners who are unwilling or unable to disclose timely and accurate data.

To help take advantage of this opportunity, the Carbon Tracker Initiative developed an innovative methodology to explore the extent to which satellite imagery and data science could be used to estimate the utilisation of coal-fired power plants.

Understanding plant utilisation is essential for an economic analysis of power generation assets. It is required to understand economic viability and relative competitiveness, which helps investors, policymakers and civil society develop plant retirement schedules and forecast asset-stranding. The current lack of transparency therefore has the potential to stifle the phase-out of coal-fired generation. We know that to meet the temperature goal set out in the Paris Agreement, one coal plant will need to close every day until 2040. Greater transparency will improve decision-makers’ ability to focus on the key questions: which plants, and when?

While there are barriers to understanding power and industrial facilities from space, satellite imagery coupled with data science will not only improve transparency in these industries, it could potentially upend existing information flows. For example, the accuracy of our model for predicting the utilisation of EU and US coal plants was 92% and 91%, respectively.

We applied our satellite imagery methodology and integrated the plant utilisation results into our climate scenario analysis for coal power in China. This analysis showed that 40% of coal plants in China could be loss-making in 2018.

Satellite imagery can give an accurate picture of coal plant performance when operators can't, or won't
Satellite imagery can give an accurate picture of coal plant performance when operators can't, or won't
Image: Carbon Tracker

To meet the temperature goal in the Paris Agreement in a timely and orderly manner, the timeliness and granularity of data from fossil-fuel assets needs to be dramatically improved. To date, satellite imagery has been largely overlooked in the power and industry sectors. This looks set to change as high-resolution daily coverage of satellite imagery becomes the new normal. This situation will give decision-makers access to data flows that were previously unimaginable.

The report, Nowhere to hide: Using satellite imagery to estimate the utilisation of fossil fuel power plants, is available here