Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring

Abstract. Quantifying facility-level methane emission rates using satellites with fine spatial resolution has recently gained significant attention. However, the prevailing quantification algorithms usually require the methane column plume from a solitary point source as input. Such approaches are challenged with overlapping plumes from multiple point sources. To address these challenges, we propose a separation approach based on a heuristic optimization and the multi-source Gaussian plume model to separate the overlapping plumes. Subsequently, the integrated mass enhancement (IME) model is applied to accurately quantify emission rates. To validate the proposed method, observation system simulation experiments (OSSEs) of various scenarios are performed. The result shows that plume overlapping exacerbates the quantifying error of the IME method when applied without such a separation approach, where the quantification mean absolute percentage error (MAPE) increased from 0.15 to 0.83, and it is affected by factors such as source intervals, wind direction, and interference emission rates. By contrast, the application of the proposed separation method together with the IME quantification approach mitigates this interference, reducing the quantification MAPE from 0.83 to 0.38. Moreover, the proposed method also outperforms the direct use of multi-source Gaussian plume fitting for the quantification, with a MAPE of 0.45. Our separation method separates overlapping plumes from multiple sources into distinct, single-source observations, enabling the IME algorithm – a high-precision quantification approach for fine-spatial-resolution plume images – to handle multi-source scenarios effectively. This method can help future spaceborne carbon inventory activities for spatially clustering carbon-emitting facilities.