Identification of NO hotspots from oversampled TROPOMI NO column based on image segmentation method.

Satellite-based measures of NO have become increasingly available for resolving the limitation on insufficient spatial and temporal coverage of ground-level monitoring networks. Oversampled NO column density can obtain more detailed features of NO column with a spatial resolution as high as 2 km × 2 km, while it is still challenging to identify hotspots of NO pollution plume in city-scale due to background interference. In this study, we proposed a method for detecting the NO hotspot grids from oversampled satellite NO column based on the image segmentation method, and identifying major source types using Term frequency-inverse document frequency (TF-IDF). A fractal model was used to evaluate and eliminate the background portion of the NO column and an adaptive threshold method was adopted to identify the region of interest (ROI) of local hotspot NO column. Hot-grid index, counting the frequency of NO hotspot ROI in each grid, was conducted to identify the hotspot grids. TF-IDF was used to semantically analyze the major source types of NO hotspot grids. Taking Central and Eastern China as the studied domain, the hotspot grids of NO and the relevant major source types were identified based on the proposed method. The major non-road mobile sources (such as Beijing Capital International Airport), industrial areas (such as Caofeidian Industrial Park) and urban areas were clearly distinguished. The power plant, Coke and Iron and Steel were identified as major source types in the whole year in the corresponding NO hotspot grids. Notably, the identification of hotspot grids indicated a higher probability of a local high-intensity NO pollution plume rather than a quantitative NO emission; the key source types were the semantic keywords in hotspot grids, which does not mean there were no other exiting emission sources. This proposed method has strong implications on rapidly identifying the NO hotspot grids based on oversampled TROPOMI NO column and the list of industrial enterprises.