New Satellite-based Methods for Monitoring Emissions from Cities and Power Stations

Satellites have proven to be a powerful tool for monitoring individual emission sources from space. Recent research highlights the significant potential of satellite data to reveal previously unreported or underestimated emissions, especially in regions where official emission inventories are delayed or incomplete.

Tracking emissions from cities, power stations, and other major sources is critical for understanding and addressing climate change. In 2025, the Finnish Meteorological Institute (FMI) developed two new methods to estimate emissions using satellite observations.

Two New Satellite-Based Methods

1. Using Nitrogen Dioxide (NO₂) to Estimate CO₂ Emissions

The first method leverages satellite measurements of nitrogen dioxide (NO₂), a gas often emitted alongside carbon dioxide (CO₂), to improve CO₂ emission estimates. Using this technique, researchers found that emissions from the Matimba and Medupi power plants in South Africa were significantly underestimated in official inventories—likely because emissions from the newer Medupi plant are missing altogether. Similar gaps were found in the emissions data for cities like Baghdad, while inventories for cities in Western countries, such as Madrid and Las Vegas, were found to be more accurate.

2. LIME: Linear Integrated Mass Enhancement

The second method, called LIME (Linear Integrated Mass Enhancement), estimates emissions by analyzing how the mass of a gas plume increases linearly with distance from the source. This approach has been useful for example calculating methane emissions from industrial sites and gas leaks. It has already been applied to detect methane releases in Algeria and South Africa using two different satellite instruments.

Both methods contribute to the FMI’s Emission Observatory, an open-access web service that compiles emission data from individual sources such as cities and power plants—focusing especially on under-monitored regions like Africa.

The research was conducted in collaboration with leading international experts and supported by the Research Council of Finland.

Technical papers:

1.     Janne Hakkarainen, Iolanda Ialongo, Tomohiro Oda, and David Crisp: A robust method for calculating carbon dioxide emissions from cities and power stations using OCO‐2 and S5P/TROPOMI observations, Journal of Geophysical Research: Atmospheres, Volume 130, 2025,  https://doi.org/10.1029/2025JD043358.

2.     Janne Hakkarainen, Iolanda Ialongo, Daniel J. Varon, Gerrit Kuhlmann, and Maarten C. Krol: Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations, Remote Sensing of Environment, Volume 319, 2025, https://doi.org/10.1016/j.rse.2025.114623.

Uudet menetelmät tehostavat voimaloiden ja kaupunkien päästöseurantaa avaruudesta

Satelliitit ovat osoittautuneet toimivaksi tavaksi monitoroida yksittäisiä päästölähteitä avaruudesta käsin. Tuoreet tutkimukset havainnollistavat satelliittidatan merkittävää potentiaalia paljastaa puuttuvia päästölähteitä erityisesti siellä, missä päästöinventaariot ovat viivästyneitä tai epätäydellisiä.

Kaupunkien, voimaloiden ja muiden päästölähteiden seuranta on kriittistä ilmastonmuutoksen kannalta. Ilmatieteen laitoksella on kehitetty tänä vuonna kaksi uutta menetelmää päästölaskentaan satelliittihavainnoista.

Ensimmäinen menetelmistä perustuu toisen samanaikaisesti päästetyn kaasun eli typpidioksidin (NO₂) hyväksikäyttöön hiilidioksidipäästöjen arvioinnissa. Tätä menetelmää hyödyntäen tutkijat onnistuivat osoittamaan, että Etelä-Afrikassa sijaitsevien Matimba- ja Medupi-voimaloiden päästöt on inventaarioissa arvioitu alakanttiin luultavasti niin, että uuden Medupi-voiman päästöt puuttuvat päästöinventaarioista kokonaan. Myös muun muassa Irakin pääkaupunki Bagdadin päästötiedot ovat pahasti puutteellisia. Toisaalta taas länsimaissa sijaitsevien kaupunkien, kuten Madrid ja Las Vegas, päästöt ovat inventaarioissa oikein.

Toinen menetelmistä (LIME, Linear Integrated Mass Enhancement) perustuu siihen, että päästölähteestä leviävän kaasupilven massa kasvaa viivamuotoisesti etäisyyden kasvaessa. Menetelmää voidaan hyödyntää esimerkiksi metaanipäästöjen laskentaan kaasuvuodoista ja teollisuuslaitoksista. Sitä onkin sovellettu muun muassa metaanivuotojen arviointiin Algeriassa ja Etelä-Afrikassa kahta eri satelliittimittalaitetta käyttäen.

Avoin verkkopalvelu koostaa yksittäisten lähteiden päästöt

Molemmat tutkimukset liittyvät Ilmatieteen laitoksella kehitettyyn Emission Observatory -palveluun, jossa kaupunkien, voimaloiden ja muiden yksittäisten lähteiden päästöjä kartoitetaan erityisesti Afrikassa.

”Uudet menetelmät ovat tärkeitä nykyisille mittalaitteille, mutta niiden merkitys korostuu vielä tulevaisuudessa, kun uusia parempia satelliittihavaintoja tulee saataville,” molempia tutkimuksia vetänyt Ilmatieteen laitoksen erikoistutkija Janne Hakkarainen sanoo.

Molemmat Ilmatieteen laitoksen vetämät tutkimukset ovat syntyneet kansainvälisessä yhteistyössä alan johtavien asiantuntijoiden kanssa. Tutkimusten rahoittamiseen on osallistunut Suomen Akatemia.

Tieteellisten artikkelien viitteet:

 Janne Hakkarainen, Iolanda Ialongo, Tomohiro Oda, and David Crisp: A robust method for calculating carbon dioxide emissions from cities and power stations using OCO‐2 and S5P/TROPOMI observations, Journal of Geophysical Research: Atmospheres, Volume 130, 2025,  https://doi.org/10.1029/2025JD043358.

Janne Hakkarainen, Iolanda Ialongo, Daniel J. Varon, Gerrit Kuhlmann, and Maarten C. Krol: Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations, Remote Sensing of Environment, Volume 319, 2025, https://doi.org/10.1016/j.rse.2025.114623.

Satellites reveal air pollution from the world’s largest copper mines

Satellite observations highlight nitrogen oxide emissions coupled with copper production 

 

Copper plays a crucial role in the global transition to a sustainable economy, serving as a key component in electric vehicles, solar panels, and wind turbines. However, copper mining also poses environmental and social challenges that must be addressed responsibly. Assessing the mining industry's performance and environmental impact is essential for tracking progress toward sustainable development.

 

A new study, published in Environmental Research Letters, utilizes satellite observations of nitrogen dioxide (NO₂) to estimate nitrogen oxide (NOx) emissions over 14 of the world’s largest open-pit copper mines. The monitored sites include major copper mines in the United States, Chile, Peru, Mexico, and Zambia. The emissions mostly originate from the diesel-powered mobile fleet operating over the mines. The highest emissions were observed at the Morenci copper mine in Arizona, USA. The study found that NOx emissions are rising at many sites, particularly in South America. In contrast, emissions in the Zambian mines appear to be declining, likely due to increased electrification of mining equipment. The emissions increase with increasing copper production and moved material volumes.

With growing pressure for the mining industry to align with environmental, social, and governance (ESG) principles, independent monitoring is crucial. “Currently, most sustainability reporting in the mining sector relies on self-disclosures by companies, which can be inconsistent and incomplete. Satellite observations provide an independent, timely, and transparent way to track emissions,” explains Dr. Iolanda Ialongo, senior researcher and lead author of the study.

Satellite observations can also detect sudden changes in mining operations, such as shifts in fossil fuel usage due to fleet electrification, thereby supporting emission reduction strategies. Satellite-based assessments are especially valuable in regions lacking other monitoring systems, offering actionable data for environmental authorities, non-governmental organizations, and local communities.

REFERENCE 
Ialongo I., Virta H., Hakkarainen J., Özcan C., Ranta M., and Zieleniewski S. (2025): Unveiling nitrogen oxide emissions from open-pit copper mines through satellite observations, Environ. Res. Lett. 20 034041 https://doi.org/10.1088/1748-9326/adb767

Linear Integrated Mass Enhancement

I’m pleased to share that our paper, “Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations,” has been published in Remote Sensing of Environment.

In this paper, we propose a new methodology for plume inversion emission estimation termed linear integrated mass enhancement (LIME). As the name implies, this approach is based on the integrated mass enhancement (IME) method and on the linear relationship between IME and the distance from the source. The proposed approach accounts for the information coming from different portions of the plume, and it can be seen as a “combination” of the cross-sectional flux (CSF) method and IME. The method offers a straightforward way to estimate the source strength by determining the slope of the linear fit.

We test the LIME approach with both real (OCO-3, S5P/TROPOMI, Sentinel-2) and simulated (MicroHH, SMARTCARB) satellite data. We apply the method to the simulated carbon dioxide (CO2) observations for the upcoming CO2M mission over the Matimba and Jänschwalde power stations with known source rates. We use the OCO-3 data to estimate the CO2 emissions originating from the Bełchatów power station in Poland (between 72 and 103 ktCO2/d). We also estimate the emissions from two methane (CH4) leaking sites in Algeria based on S5P/TROPOMI (77 and 47 tCH4/h for two days) and Sentinel-2 (7.7 tCH4/h) observations. Finally, we apply the LIME method to the Sentinel-2 retrievals from a controlled CH4 release in Arizona.

Across all case studies, the LIME emission estimates are in agreement with the expected values. The LIME estimates are also aligned with the state-of-the-art IME emission estimates, which are calculated as byproducts in the LIME emission estimation process.

Citation:

Janne Hakkarainen, Iolanda Ialongo, Daniel J. Varon, Gerrit Kuhlmann, and Maarten C. Krol: Linear Integrated Mass Enhancement: A method for estimating hotspot emission rates from space-based plume observations, Remote Sensing of Environment, Volume 319, 2025, https://doi.org/10.1016/j.rse.2025.114623.