{"id":37278,"date":"2025-08-11T23:07:16","date_gmt":"2025-08-11T21:07:16","guid":{"rendered":"https:\/\/www.co2news.sk\/?p=37278"},"modified":"2025-08-12T21:13:56","modified_gmt":"2025-08-12T19:13:56","slug":"how-satellites-reveal-emissions-from-belchatow-the-largest-coal-fired-power-plant-in-europe","status":"publish","type":"post","link":"https:\/\/www.co2news.sk\/en\/2025\/08\/11\/how-satellites-reveal-emissions-from-belchatow-the-largest-coal-fired-power-plant-in-europe\/","title":{"rendered":"How satellites reveal emissions from Be\u0142chat\u00f3w \u2014 Europe's largest coal-fired power plant"},"content":{"rendered":"

Be\u0142chat\u00f3w is often cited as the largest coal-fired (lignite) power plant in Europe and one of the world's largest sources of coal-fired electricity emissions. Its installed (achievable) capacity ranges from around 5,100 MW and the entire surrounding area is significantly tied to the mining and burning of local brown coal (lignite). (Global Energy Monitor<\/a><\/span>)<\/p>\n

Satellites and local CO\u2082 measurements: a new level of transparency<\/h5>\n

Traditional methods of monitoring emissions (fuel consumption, inventories, local measurements) remain the basis, but new studies show that satellite-based CO\u2082 measurements can complement this methodology even at a relatively local level. The research team published proof-of-principle that the Orbiting Carbon Observatory (OCO-2) and OCO-3 satellites can detect and quantify changes in columnar CO\u2082 concentrations associated with the operation of a large thermal power plant \u2014 specifically Be\u0142chat\u00f3w \u2014 during observations from 2017 to 2022. These satellite estimates showed trends consistent with hourly fluctuations in the plant\u2019s production data. (Frontiers<\/a>, NASA<\/a><\/span>)<\/p>\n

This means that, under suitable meteorological conditions, advanced analysis, and combination with ground-based measurements, operational fluctuations of large point sources of CO\u2082 can also be detected from satellite \u2014 adding an independent layer of verifiability to official inventories and legislative commitments.<\/p>\n

Why is Be\u0142chat\u00f3w significant right now?<\/h5>\n

Be\u0142chat\u00f3w burns mostly brown coal (lignite)<\/strong>, which has a higher CO\u2082 emission factor per unit of energy produced than most hard coals (bituminous). Standard emission factors show that different types of coal have different CO\u2082\/t of fuel unit and the resulting tonnes of CO\u2082 per MWh are generally higher for lignite. This makes the operation of such plants particularly carbon intensive. (eia.gov<\/a><\/span>)<\/p>\n

Moreover, according to plans and regional documents, the gradual decommissioning of the power plant is planned between 2030\u20132036 (depending on the schedule of the units); individual public analyses and reports indicate that the complete closure of operations is expected in 2036 at the latest. This raises questions about the fair transition of the region, energy security and the need for rapid deployment of replacement low-carbon capacities.<\/p>\n

Limits and opportunities of satellite monitoring<\/h5>\n

Satellite methods have limitations: cloud cover, resolution of the vertical structure of CO\u2082, wind effects, and the need for repeated data analysis. Therefore, they are most reliable when combined with ground-based measurements, meteorological flow models, and advanced algorithms (deep-learning or inverse models) that improve the ability to \u201cseparate\u201d the signal from a specific source from the background. Recent methodological work shows rapid progress in these techniques.<\/p>\n

Why does it matter?<\/h5>\n

The ability to track the emissions signatures of large power plants from satellite is a game-changer: it increases transparency, enables independent verification, and pushes for faster decarbonization. The Be\u0142chat\u00f3w case is a cautionary tale \u2014 large source, long operating time, and high carbon intensity \u2014 but also a laboratory testing tools that can lead us to more accurate and reliable real-world emissions measurements. JRi<\/strong><\/em><\/p>\n

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Sources and further reading (selected):<\/strong><\/p>\n