Quantifying instantaneous nitrogen oxides emissions from power plants based on space observations.

Area of Science:

• Atmospheric Science
• Environmental Monitoring
• Remote Sensing

Background:

• Thermal power plants are major sources of nitrogen oxides (NOx) emissions, affecting air quality and health.
• Satellite observations offer global coverage for emission quantification, but traditional methods have limitations.
• Previous studies integrating long temporal data introduced errors in annual emission estimates for individual power plants.

Purpose of the Study:

• To introduce a novel method for quantifying instantaneous NOx emissions from power plants using single satellite overpass data.
• To reduce annual emission estimation errors by accounting for temporal variability in emissions and diffusion conditions.
• To compare the performance of the Exponentially-Modified Gaussian (EMG) model with the Gaussian Plume Model (GPM) for instantaneous emission estimation.

Main Methods:

• Utilized single overpass observations from the Tropospheric Monitoring Instrument (TROPOMI) on Sentinel-5 Precursor.
• Applied the Exponentially-Modified Gaussian (EMG) plume model for instantaneous emission rate quantification.
• Quantified instantaneous NOx emission rates for six U.S. power plants.

Main Results:

• The EMG model provided more accurate instantaneous emission estimates compared to the GPM.
• The novel method demonstrated a 63.7% improvement in annual emission estimations at the individual power plant level.
• Accurate quantification of instantaneous emission rates was achieved by addressing temporal variability.

Conclusions:

• Satellite-based instantaneous NOx emission quantification is feasible and significantly improves accuracy over traditional methods.
• The EMG model offers a superior approach for estimating power plant emissions from satellite data.
• This research provides more granular data for understanding power plant emission behavior and improving air quality management.