Detection and emission estimates of NOx sources over China North Plain using OMI observations
We designed a fast procedure to detect the nitrogen oxides (NO x) sources in the China
North Plain and to estimate their NO x emissions through a two-dimensional Gaussian fitting
method applied to averaged Ozone Monitoring Instrument (OMI) observations of nitrogen
dioxide (NO2) column concentration. The Northern China Plain is a region that has one of
the highest densities of anthropogenic NO x sources in the world and therefore the sources
are difficult to distinguish. With our procedure we still found 94 individual NO x emission …
North Plain and to estimate their NO x emissions through a two-dimensional Gaussian fitting
method applied to averaged Ozone Monitoring Instrument (OMI) observations of nitrogen
dioxide (NO2) column concentration. The Northern China Plain is a region that has one of
the highest densities of anthropogenic NO x sources in the world and therefore the sources
are difficult to distinguish. With our procedure we still found 94 individual NO x emission …
Abstract
We designed a fast procedure to detect the nitrogen oxides (NOx) sources in the China North Plain and to estimate their NOx emissions through a two-dimensional Gaussian fitting method applied to averaged Ozone Monitoring Instrument (OMI) observations of nitrogen dioxide (NO2) column concentration. The Northern China Plain is a region that has one of the highest densities of anthropogenic NOx sources in the world and therefore the sources are difficult to distinguish. With our procedure we still found 94 individual NOx emission sources. Of these sources Tangshan city has the strongest NOx emission rate (92 Gg N year–1), while the weakest that we are still able to detect is Zhangjiakou city, with a NOx emission rate of 0.4 Gg N year–1. Using the fitting results, we reconstruct the NO2 column concentration distribution map, which matches the OMI observations with an R2 = 0.85 and a slope of 0.78. The derived NOx emission rates for cities and provinces level show good agreement with former studies.
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