Preprints
https://doi.org/10.5194/acp-2021-474
https://doi.org/10.5194/acp-2021-474

  14 Jun 2021

14 Jun 2021

Review status: this preprint is currently under review for the journal ACP.

A New Inverse Modeling Approach for Emission Sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei Region

Xinghong Cheng1, Zilong Hao2, Zengliang Zang2, Zhiquan Liu3, Xiangde Xu1, Yuelin Liu4, Yiwen Hu5, and Xiaodan Ma5 Xinghong Cheng et al.
  • 1State Key Lab of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 2Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, China
  • 3National Center for Atmospheric Research, Boulder, CO, USA
  • 4College of Architecture and Environment, Sichuan University, Chengdu 610065, China
  • 5Nanjing University of Information Science and Technology, Nanjing 210044, China

Abstract. We develop a new inversion method which is suitable for linear and nonlinear emission sources (ES) modeling, based on the three-dimensional decoupled direct (DDM-3D) sensitivity analysis module in the Community Multiscale Air Quality (CMAQ) model and the three-dimensional variational (3DVAR) data assimilation technique. We established the explicit observation operator matrix between the ES and receptor concentrations, and the background error covariance (BEC) matrix of the ES which can reflect the impacts of uncertainties of the ES on assimilation. Then we constructed the inversion model of the ES by combining the sensitivity analysis with 3DVAR techniques. We performed the simulation experiment using the inversion model for a heavy haze case study in the Beijing-Tianjin-Hebei (BTH) region during December 27–30, 2016. Results show that the spatial distribution of sensitivities of SO2 and NOX ES to their concentrations, as well as the BEC matrix of ES, are reasonable. Using the posteriori inversed ES, underestimations of SO2 and NO2 during the heavy haze period are remarkably improved, especially for NO2. Spatial distributions of SO2 and NO2 concentrations simulated by the constrained ES were more accurate compared with the priori ES in the BTH region. The temporal variations in regionally averaged SO2, NO2, and O3 modelled concentrations using the posteriori inversed ES are consistent with in-situ observations at 45 stations over the BTH region, and simulation errors decrease significantly. These results are of great significance for: studies on the formation mechanism of heavy haze; reducing uncertainties of ES and its dynamic updating; providing accurate “virtual” emission inventories for air-quality forecasts and decision-making services for optimization control of air pollution.

Xinghong Cheng et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-474', Anonymous Referee #1, 28 Jun 2021
  • RC2: 'Comment on acp-2021-474', Anonymous Referee #2, 07 Jul 2021

Xinghong Cheng et al.

Xinghong Cheng et al.

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Short summary
We develop a new inversion method of emission sources based on the sensitivity analysis and three-dimension variational technique. The novel explicit observation operator matrix between emission sources and receptor’s concentrations is established. Then this method is applied to a typical heavy haze episode in North China, and spatiotemporal variations of SO2, NO2, and O3 concentrations simulated using the posterior emission sources are compared with results by the priori inventory.
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