Catalog of NO_x emissions from point sources as derived from the divergence of the NO₂ flux for TROPOMI

Abstract

Abstract. We present version 1.0 of a global catalog of NOx emissions from point sources, derived from TROPOspheric Monitoring Instrument (TROPOMI) measurements of tropospheric NO2 for 2018–2019. The identification of sources and quantification of emissions are based on the divergence (spatial derivative) of the mean horizontal flux, which is highly sensitive for point sources like power plant exhaust stacks. The catalog lists 451 locations which could be clearly identified as NOx point sources by a fully automated algorithm, while ambiguous cases as well as area sources such as megacities are skipped. A total of 242 of these point sources could be automatically matched to power plants. Other NOx point sources listed in the catalog are metal smelters, cement plants, or industrial areas. The four largest localized NOx emitters are all coal combustion plants in South Africa. About 1/4 of all detected point sources are located in the Indian subcontinent and are mostly associated with power plants. The catalog is incomplete, mainly due to persisting gaps in the TROPOMI NO2 product at some coastlines, inaccurate or complex wind fields in coastal and mountainous regions, and high noise in the divergence maps for high background pollution. The derived emissions are generally too low, lacking a factor of about 2 up to 8 for extreme cases. This strong low bias results from combination of different effects, most of all a strong underestimation of near-surface NO2 in TROPOMI NO2 columns. Still, the catalog has high potential for checking and improving emission inventories, as it provides accurate and independent up-to-date information on the location of sources of NOx and thus also CO2. The catalog of NOx emissions from point sources is freely available at https://doi.org/10.26050/WDCC/Quant_NOx_TROPOMI (Beirle et al., 2020).

An improved understanding of NOx emissions in South Asian megacities using TROPOMI NO2 retrievals

“…By taking the divergence of the NO 2 fluxes, even higher resolution identification of point sources was made possible [18,19]. Emissions estimates in Germany were found to be in good agreement with the European Pollutant Release and Transfer Register [18] and worldwide hotspots were in agreement with the Global Power Plant Database [19].…”

“…In the original method [18,19], two-dimensional Gaussian functions were mapped onto the largest hotspots in sequence, removing the Gaussian from the divergence map each time a new source was estimated. In this study, a GMM was used to estimate emissions from multiple hotspots in the flux divergence fields simultaneously.…”

“…Uncertainty analyses were performed by varying the key parameters in the method. In a revised catalog of NO x point sources [19], removed the sink term when estimating the emissions. This is effectively like setting the lifetime to infinity.…”

“…Table 1 shows the emissions, length scale and eccentricity of the Gaussian estimates and compares them with the corresponding emissions from the REAS and EDGAR inventories, as well as with the total power of the plants in the WRI inventory and with the previous TROPOMI estimates [19]. The type of each hotspot was determined by inspection of the surroundings using Google maps.…”

“…This has made it possible to estimate urban emissions more accurately, for example over the Canadian Oil Sands [14], in Paris [15], in North America [16], and in South Korea [17]. By taking the divergence of the NO 2 fluxes, even higher resolution identification of point sources was made possible [18,19]. Emissions estimates in Germany were found to be in good agreement with the European Pollutant Release and Transfer Register [18] and worldwide hotspots were in agreement with the Global Power Plant Database [19].…”