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

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.

Emission Observatory – Pilot for Africa

Climate change, driven by increasing atmospheric concentrations of anthropogenic greenhouse gases (GHGs), is one of the greatest threats of our time. Space-based observations offer new opportunities for improving the completeness and transparency of emission reports as they provide objective observations over areas where other information is inaccurate or not available.

Over the past decade, satellite-based measurements of greenhouse gases have transformed the estimation of emission rates from anthropogenic hotspots. New satellite observations of emission plumes from point sources have created opportunities to use simpler and more computationally efficient methods for estimating emissions. International accords like the 2015 Paris Agreement have played a major role in driving research in this area. Many space agencies, organizations, and private companies are now developing new GHG satellite missions and constellations to observe plumes and support future monitoring of GHG emissions.

To obtain emission estimates from atmospheric concentrations, mathematical inverse modeling methods are needed. The Finnish Meteorological Institute is dedicated to developing new methods for data-driven emission estimation that do not require complex atmospheric modeling. In particular, the team has developed several new plume inversion techniques for various recent satellite missions. As part of user engagement activities, the team has piloted a new service for the African continent, where ground-based information has traditionally been less available.

The Emission Observatory – Pilot for Africa platform is an interactive map service for monitoring anthropogenic GHG and air pollution hotspots in Africa using satellite observations and state-of-the-art emission estimation methods. Specific focus areas include cities and megacities, the mining sector (particularly critical minerals needed for the green transition), energy production (e.g., power plants in South Africa’s Highveld region), and the oil and gas industry (especially regarding fugitive methane emissions and gas flaring). The service is set to inform decision makers, environmental authorities, citizens and industry about emission sources and their spatio-temporal variability, specifically over the African continent. The information provided through the platform are tailored to the users’ needs and feedback. The platform is based on publicly available observations from the EU’s Copernicus Sentinel fleet and NASA’s Earth observation program. 

User and stakeholders of the Emission Observatory – Pilot for Africa service can engage and participate in the service implementation through a co-design process.

If you are interested in and would like to benefit from this service and methods, please contact us: emissionobservatory@fmi.fi

Link to the service: https://www.emissionobservatory.org

Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods

Highlights

  • NO2 to NOx scaling factors calculated from the MicroHH large-eddy simulations.
  • Optimal scaling factors depend on the emission inversion method.
  • Scaling factors applied to derive NOx emissions from S5P/TROPOMI NO2 observations.
  • Optimal scaling factors are substantially higher than the values previously used.

We have a new paper in Atmospheric Pollution Research!

In this paper, we propose improved nitrogen dioxide (NO2) to nitrogen oxide (NOx) scaling factors for several data-driven methods that are used for the estimation of NOx power plant emissions from satellite observations of NO2. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO2 satellite observations over the Matimba/Medupi power stations in South Africa.

In this new paper, we show that due to the non-linear chemistry the optimal NO2 to NOx scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO2 observations. The results highlight the challenge in appropriately accounting for the conversion from NO2 to NOx when estimating point source emissions from satellite NO2 observations.

Reference

Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Diego Santaren, Sandro Meier, Maarten C. Krol, Bart J.H. van Stratum, Iolanda Ialongo, Frédéric Chevallier, Johanna Tamminen, Dominik Brunner, Grégoire Broquet,: Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: a case study of Matimba/Medupi power stations in South Africa, Atmospheric Pollution Research, Volume 15, Issue 7, https://doi.org/10.1016/j.apr.2024.102171, 2024.

Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine

Satellite observations show significantly reduced air pollution levels over the major Ukrainian cities, power plants and industrial areas.

Since February 2022, the full-scale war in Ukraine has been strongly affecting society and economy in Ukraine. Satellite observations provide crucial information to objectively monitor and assess the impacts of the war. A new paper published today on Scientific Reports utilizes satellite observations of air pollutants and other relevant parameters from multiple platforms to assess the impacts of the ongoing war on the Ukrainian society. Satellite observations show that the concentrations of nitrogen dioxide (NO₂), which is emitted through fossil fuel combustion processes, declined in 2022 over the major Ukrainian cities, power plants and industrial areas by 15–46%.

Such reductions reflect the decrease in population and corresponding emissions from the transport and commercial or residential sectors as well as the decline in industrial production, especially from the metallurgic and chemical industry, which led to a reduction in power demand and corresponding electricity production from power plants. Carbon dioxide (CO₂) observations also indicate reductions in fossil fuel combustion, especially in eastern Ukraine, where the largest emission sources are located.

Difference of the March-August mean tropospheric NO2 columns between 2022 and 2021 based on S5P/TROPOMI observations. Blue colors indicate reductions observed in 2022. Black dots correspond to the major cities, industrial areas and power plants.

“During peaceful times, reductions in nitrogen dioxide concentrations as those observed here would be considered as a welcome improvement of air quality and human health. In this case, the observed changes tell a different story about the extent of the disruption caused by the war on the Ukrainian society and economy. Also, the reductions in fossil fuel consumption in Ukraine might have been partly offset by an increase elsewhere”, explains senior researcher at the Finnish Meteorological Institute Iolanda Ialongo, who led the work.

Exceptional fire patterns near the front line
Satellite imagery and fire detections indicate an anomalous distribution of fires along the front line, which are attributable to shelling or other war-related fires, rather than the typical homogeneously distributed fires related to crop harvesting. Satellite imagery data also show drastic changes over the city of Mariupol, which was attacked during the first three months of the war.

The signal from the hot smokes from the metallurgic industrial facilities in the city disappears from the satellite imagery after March 2022, which suggest an interruption of industrial activities, and, correspondingly, NO₂ levels decreased.

The results are based on the NO₂ retrievals from the European TROPOMI (TROPOspheric Monitoring Instrument), onboard the Sentinel 5 Precursor satellite, and the CO₂ observations from the NASA’s OCO-2 satellite. Also satellite imagery from the Sentinel 2 satellite was analyzed as well as fire detectionsfrom the Visible Infrared Imaging Radiometer Suite (VIIRS).

The research was carried on at the Finnish Meteorological Institute together with colleagues from the University of Lviv (Ukraine) and USRA (USA). The Finnish part of the research was supported by the Ministry for Foreign Affairs of Finland via theInterinstitutional Development Cooperation Instrument (ICI), UHMC-FMI Meteorology project and the Research Council of Finland.

Reference: Ialongo, I., Bun, R., Hakkarainen, J. et al. Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine. Sci Rep13, 14954 (2023). https://doi.org/10.1038/s41598-023-42118-w

Building a Bridge: Estimating Carbon Dioxide Emissions Using Satellites

A team of researchers estimated the carbon dioxide (CO2) emissions from coal-fired power plants and other major anthropogenic point sources in the South African Highveld region using space-based data. The results indicate that the CO2 emissions can be obtained also in challenging cases where the plumes from multiple sources overlap.

The article analyses the emissions of six power stations (Kendal, Kriel, Matla, Majuba, Tutuka and Grootvlei) and the largest single emitter of greenhouse gas in the world, Secunda CTL synthetic fuel plant. The annual CO₂ emissions of the Secunda CTL exceed the emissions of several European countries, including Finland, Norway, and Portugal. 

Overall, the space-based emission estimates are in good agreement with the emission inventories. Thus, satellite observations can be used for CO2 emission estimation and are particularly useful when no other information is available.

Orbiting Carbon Observatory-3 mission operates on the International Space Station (ISS). To support the quantification and monitoring of anthropogenic CO₂ emissions, OCO-3 incorporates a new key capability that provides observations in Snapshot Area Maps (SAMs), providing contiguous images over regions as large as 80 km by 80 km in two minutes. Altogether the article analyzes six OCO-3 SAMs jointly with Sentinel-5P/TROPOMI nitrogen dioxide (NO2) columns.

Sentinel-5P/TROPOMI NO₂ and OCO-3 XCO₂ SAM observations on 21 January 2022.

The new article is a continuation of the previous work where the authors studied the emissions and NOx-to-CO₂ emission ratio of the isolated Matimba power station. The article extends the method to challenging cases where CO₂ plumes from multiple sources overlap.

The applicability of similar emission estimation approaches for future satellite missions such as the Copernicus Carbon Dioxide Monitoring mission CO2M are discussed. CO2M is Copernicus Sentinel Expansion missions and will focus on carbon dioxide released into the atmosphere specifically through human activity.

The research was carried on at Finnish Meteorological Institute together with colleagues from USRA, Colorado State University and Caltech/JPL. The Finnish part of the research was supported by European Space Agency (DACES), Academy of Finland (CitySpot, CoE inverse and ACCC) and EU-H2020 CoCO2.

The full publication by Hakkarainen and co-authors can be found at the following link: https://doi.org/10.1088/1748-9326/acb837

TanSat Successfully Detects Human-Caused CO2 for the First Time

Launched in 2016, TanSat is China’s first global carbon dioxide monitoring satellite. Tan is the Chinese pronunciation of carbon. While TanSat has been providing researchers with data for several years, new algorithms were recently added to the TanSat instruments that greatly improved TanSat’s measurement precision.

The research team conducted their study by looking at two sets of measurements collected over two cities. The scientists used TanSat carbon dioxide data captured in May 2018 near Tangshan, China, and in March 2018 near Tokyo, Japan. They compared the TanSat data to nitrogen dioxide measurements captured by the TROPOspheric Monitoring Instrument onboard the Copernicus Sentinel-5 Precursor satellite on the same dates over the same cities.

“We analyzed TanSat data in synergy with European Copernicus Sentinel-5 Precursor TROPOMI nitrogen dioxide observations to help the detection of anthropogenic plumes and to analyze the carbon dioxide-to-nitrogen dioxide ratio,” said Dongxu Yang, from the Institute of Atmospheric Physics, Chinese Academy of Sciences.

The left panel illustrates TROPOMI NO2 observations overlapped by TanSat XCO2 observation near Tangshan (China) on 6 May 2018. ERA5 wind fields are shown as arrows. The XCO2 background is calculated as a median, north of the white dashed line. The right panels (top and bottom) show the XCO2 and NO2 observations (respectively) along the TanSat track. The black dots indicate the running mean. Orange colors indicate the XCO2 converted from NO2 tropospheric columns via a linear fit.

Their two case studies show TanSat carbon dioxide measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns like that of the TROPOspheric Monitoring Instrument’s nitrogen dioxide observations. In addition, the carbon dioxide-to-nitrogen dioxide ratio in Tangshan, China, and Tokyo, Japan, align with the emission inventories.

“This is an important step in TanSat data analysis. The next step is to infer emissions and to prepare for the TanSat-2 constellation including the joint analysis of CO2 and NO2 plumes,” said Janne Hakkarainen, from the Finnish Meteorological Institute.

Looking ahead, the team has plans to expand this research. “The TanSat is our first attempt on global carbon monitoring. The next generation of China’s Global Carbon Dioxide Monitoring Satellite mission, TanSat-2, is now in the design phase,” said Yi Liu, from the Institute of Atmospheric Physics, Chinese Academy of Sciences.

According to Liu, TanSat-2’s target measurements will focus on cities with an 800-1000 kilometer (500-620 mile) wide swath to record the gradient of carbon dioxide from city central to rural areas using an imaging process and a 500-meter (1600-foot) footprint size to improve the emission estimation accuracy. TanSat-2 will be a constellation of satellites distributed into at least two orbits in the morning and afternoon to cover a city or a point source twice a day.

“Our goal is to use satellite measurements to improve our knowledge of the carbon cycle and to further analyze and constraint the carbon dioxide sources and sinks and their uncertainties,” said Liu.

Reference: “Detection of Anthropogenic CO2 Emission Signatures with TanSat CO2 and with Copernicus Sentinel-5 Precursor (S5P) NO2 Measurements: First Results” by Dongxu Yang, Janne Hakkarainen, Yi Liu, Iolanda Ialongo, Zhaonan Cai and Johanna Tamminen, 25 October 2022, Advances in Atmospheric Sciences. https://doi.org/10.1007/s00376-022-2237-5

Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method

Since the Paris Agreement was adopted in 2015, the role of space-based observations for monitoring anthropogenic greenhouse gas (GHG) emissions has increased. To meet the requirements for monitoring carbon dioxide (CO2) emissions, the European Copernicus programme is preparing a dedicated CO2 Monitoring (CO2M) satellite constellation that will provide CO2 and nitrogen dioxide (NO2) observations at 4 km2 resolution along a 250 km wide swath.

Simulated CO2M observations. Figure by Gerrit Kuhlmann, Empa.

In a new paper, we adapt the recently developed divergence method to derive both CO2 and nitrogen oxide (NOx) emissions of cities and power plants from a CO2M satellite constellation by using synthetic observations from the COSMO-GHG model. Due to its long lifetime, the large CO2 atmospheric background needs to be removed to highlight the anthropogenic enhancements before calculating the divergence. Since the CO2 noise levels are large compared to the anthropogenic enhancements, we apply different denoising methods and compare the effect on the CO2 emission estimates. The annual NOx and CO2 emissions estimated from the divergence maps using the peak fitting approach are in agreement with the expected values, although with larger uncertainties for CO2. We also consider the possibility to use co-emitted NOx emission estimates for quantifying the CO2emissions, by using source-specific NOx-to-CO2 emission ratios derived directly from satellite observations. In general, we find that the divergence method provides a promising tool for estimating CO2 emissions, alternative to typical methods based on inverse modeling or on the analysis of individual CO2 plumes.

Reference: Janne Hakkarainen, Iolanda Ialongo, Erik Koene, Monika E. Szeląg, Johanna Tamminen, Gerrit Kuhlmann, Dominik Brunner: Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset, Frontiers in Remote Sensingvol 3, 2022, doi:10.3389/frsen.2022.878731, Link

Carbon dioxide emission plumes from a large power station detected from space

Researchers at the Finnish Meteorological Institute developed a new methodology to derive source-specific NOₓ-to-CO₂ emission ratios using satellite observations. The method was applied to Matimba power station in South Africa. The results can be used to estimate carbon dioxide emissions.

Since the Paris agreement was adopted in 2015, the role of satellite observations in understanding anthropogenic CO2 emissions has become increasingly important. Currently, the NASA’s CO2 instrument Orbiting Carbon Observatory-2 (OCO-2), launched in 2014, provides CO2 observations with the best coverage and resolution. However, the observations are obtained on a narrow swath (less than 10 km), which does allow the detection of the cross-sections of the emission plumes, but not the plumes in their entirety. Satellite observations of co-emitted species, such as NO2, facilitate the detection of the CO2 emission plumes. The European Commission is currently planning a new CO2 monitoring mission CO2M via the Copernicus Programme, which will observe both CO2 and NO2 over a larger swath (over 250 km).

Estimating CO2 emissions from individual sources using satellite data can be challenging due to the large background levels, while it is easier for short-lived gases like NO2. In a recently published study, a new methodology to calculate source-specific NOₓ-to-CO₂ emission ratio from satellite observations is developed. This ratio provides information on how clean the employed technology is and can be used to convert NOₓ emission into CO2 emission. The method was tested for the Matimba power station in South Africa, which is an optimal case study as it is a large emission source with several satellite overpasses, and it is also well isolated from other sources.

OCO-2 and TROPOMI observations near Matimba power station (red triangle) in South Africa between May 2018 and November 2020. Image: Hakkarainen et al. 2021. CC BY 4.0.


The results are based on the CO2 observations from the NASA’s OCO-2 satellite and the NO2 retrievals from the European TROPOMI (TROPOspheric Monitoring Instrument), operating onboard the Sentinel 5 Precursor satellite since late 2017. During the 2018–2020 period, 14 collocations over Matimba enabled the simultaneous detection of the CO2 and NO2 plumes. The mean NOx-to-CO2 emission ratio was estimated as (2.6 ± 0.6) × 10⁻³ and the CO2 emission as 60 kton/day. The obtained CO₂ emission estimates are similar to those reported in existing inventories such as ODIAC.

The research was carried on in the DACES project, which focuses on detecting anthropogenic CO₂ emissions sources by exploiting the synergy between satellite-based observations of short-lived polluting gases (such as NO₂) and greenhouse gases.

The full publication by Hakkarainen and co-authors can be found at the following link: https://doi.org/10.1016/j.aeaoa.2021.100110