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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2020-81
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-81
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  15 Apr 2020

15 Apr 2020

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A revised version of this preprint is currently under review for the journal AMT.

The quantification of NOx and SO2 point source emission flux errors of mobile DOAS on the basis of the Gaussian dispersion model: A simulation study

Yeyuan Huang1,2, Ang Li1, Thomas Wagner4, Yang Wang4, Zhaokun Hu1, Pinhua Xie1,2,3, Jin Xu1, Hongmei Ren1,2, Xiaoyi Fang5, and Bing Dang6 Yeyuan Huang et al.
  • 1Key Lab. of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, 230031, China
  • 2University of Science and Technology of China, Hefei, 230027, China
  • 3CAS Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361000, China
  • 4Max Planck Institute for Chemistry, Mainz, Germany
  • 5Chinese Academy of Meteorological Science, Beijing, 100081, China
  • 6Beijing Municipal Climate Center, Beijing, 100089, China

Abstract. Mobile differential optical absorption spectroscopy (mobile DOAS) has become an important tool for the quantification of emission sources, including point sources (e.g., individual power plants) and area emitters (e.g., entire cities). In this study, we focused on the error budget of mobile DOAS measurements from point sources, and we also offered recommendations for the optimum settings of such measurements. First we established a Gaussian plume model from which the NOx and SO2 distribution from the point source was determined. In a second step the simulated distributions are converted into vertical column densities of NOx and SO2 according to the mobile DOAS measurement technique. With assumed parameters, we then drove the forward model in order to simulate the emissions, after which we performed the analysis. Following this analysis, we conclude that: (1) Larger sampling resolution clearly results in larger flux error. The proper resolution we suggest is between 5 m and 50 m. Even larger resolutions may also be viable, but > 100 m is not recommended. (2) Error effects vary with measurement distance from the source. We found that undetectable flux (measured VCDs are under the detection limit) is the main error source when measuring far from the source, for both NOx and SO2. When measuring close to the source, low sampling frequency results in large flux error. (3) The wind field primarily affects 2 aspects of the flux measurement error. When measuring far from the source, dispersion results in more undetectable flux, which is the main error source. When measuring close to the source, wind field uncertainty becomes the main error source of SO2 flux, but not of NOx. We suggested that the proper wind speed for mobile DOAS measurements is between 1 m/s and 4 m/s. (4) The study of NOx atmospheric chemistry reactions indicated that a [NOx]/[NO2] ratio correction has to be applied when measuring very close to the emission source. But even when such a correction is applied, the remaining errors can be significant. To minimize the [NOx]/[NO2] ratio correction error, we recommended 0.05 NO2 maximum reaction rate as the accepted NOx steady-state thus to determine the proper starting measurement distance. (5) The error of the spectral retrieval is not a main emission flux error source and its error budget varies with the measuring distance. (6) Increasing the number of measurements can lower the flux error that results from wind field uncertainty and retrieval error. This directly indicates that SO2 flux error could be lowered if the measurements are repeated when not too far from the emission source. With regard to NOx, more measurement times can only work effectively when not very close or too far from the source. (7) Also the effects of the temporal and spatial sampling are investigated. When the sampling resolution is prescribed, the integration depends on the driving speed and the corresponding flux error is mainly determined by the undetectable flux. When the car speed is prescribed, the integration time is determined by the sampling resolution for measuring near the source, while undetectable flux predominates when far away. (8) As a general recommendation, our study suggests that emission rates < 30 g/s for NOx and < 50 g/s for SO2 are not recommended for mobile DOAS measurements. The source height affects the undetectable flux, but has little influences on the total error. Based on the model simulations our study indicates that mobile DOAS measurements are very well suited tool to quantify point source emissions. The results of our sensitivity studies are important to make optimum use of such measurements.

Yeyuan Huang et al.

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Yeyuan Huang et al.

Yeyuan Huang et al.

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Short summary
Mobile DOAS has become an important tool for the quantification of emission sources. In this study, we focused on the error budget of mobile DOAS measurements from point sources based on the model simulations, and we also offered recommendations for the optimum settings of such measurements. From the results, we also discovered a missing error source(undetectable flux) and clarified the [NOx]/[NO2] ratio correction effect of flux measurement.
Mobile DOAS has become an important tool for the quantification of emission sources. In this...
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