Scientists Develop High-precision Methods to Monitor Global CO₂ Emissions from Power Plants

Coal-fired power plants remain one of the largest contributors to global CO₂ emissions. However, accurately measuring their emissions has long been a challenge due to outdated inventories and technological limitations of satellite-based methods. These challenges are especially pronounced in regions lacking modern emissions data or ground-based monitoring infrastructure.

A research team led by Professor SHI Yusheng from the Aerospace Information Research Institute, Chinese Academy of Sciences has developed a breakthrough solution to this problem. Using enhanced Gaussian plume model and data from NASA's Orbiting Carbon Observatory 3 satellite, the team has achieved high-precision CO₂ emission estimates from 14 large coal-fired power plants globally.

Key enhancements to the model include refined background CO₂ concentration estimation, more realistic simulation of plume rise behavior, and dynamic optimization of wind direction parameters.

The improvements significantly increased the accuracy of satellite-based CO₂ emission measurements. The updated model produced daily emission estimates ranging from 21.54 to 82.33 kilotonnes per day, with strong correlation coefficients (R values between 0.493 and 0.863), indicating reliable performance. Notably, optimizing wind direction and plume rises optimization were identified as key factors to the improved accuracy.

The verification by comparing with existing emission inventories shows that the results of this study have a high degree of consistency with the emission inventories in total but also revealed areas where existing databases underestimated actual emissions. For example, The Carbon Monitoring for Action (CARMA) database, developed by the Global Development Center, underestimated emissions from the Tuoketuo power plant in China, while the Global Coal Plant Tracker underestimated those from the James H Miller Jr plant in the United States. These discrepancies were largely due to outdated emission factors and statistical methods.

This study's findings establish a robust framework for dynamic, high-resolution monitoring of CO₂ emissions based on satellite data. While the current work focused on coal-fired power plants, the model is also applicable to other major s emissions from point sources, such as steel plants and oil/gas fields.

"This work demonstrates the powerful role satellite remote sensing technology can play in independently verifying emissions", said Professor Shi. "It not only supports more accurate regional carbon accounting but also helps identify abnormal emission events and evaluate the long-term effects of emission reduction measures."

The study was published in Journal of Cleaner Production.