Multisensor and Multimodel Monitoring and Investigation of a Wintertime Air Pollution Event Ahead of a Cold Front Over Eastern China

Given the limitations in pollutant measurements (e.g., coverage, observation errors) and air quality model uncertainties (e.g., with parameterizations and emissions), a multisensor and multimodel approach offers additional benefits compared to a single-instrument and deterministic approach for monitoring, investigating, and predicting air pollution events. In this study, we use multisensors (including the spaceborne MODIS, OCO-2, AIRS, and OMPS instruments as well as surface instruments) and multimodels (including WRF-Chem and WRF-CO2) to investigate a severe air pollution event on December 9, 2016 over eastern China. During this episode, a strong cold front moved southward. At the leading edge of the front, WRF-CO2 simulates an enhanced XCO2 belt while WRF-Chem simulates a belt of high PM2.5 concentration. The XCO2 and PM2.5 belts are generally colocated, due to coemission of CO2 and pollutants (or their precursors). Satellite observations including MODIS AOD, OCO-2 XCO2, OMPS NO2, AIRS CO, and surface data confirm the simulated pollution and XCO2 belts. Later on, the front became distorted due to terrain blocking and mountain channel flows. Both observations and simulations show that the channel winds between Mountains Dabie and Huang transport the haze plume into Jiangxi province, enhancing pollution in the region. It is concluded that the multisensor (including space-based and ground-based instruments) and multimodel (e.g., WRF-CO2, WRF-Chem) approach can be used to collectively monitor and investigate air pollution events, given that emissions of the involved species have generally similar spatial distributions.

Automated summary

In this study, a multisensor and multimodel approach was used to investigate a severe air pollution event in eastern China on December 9, 2016. The study found that the multisensor and multimodel approach can be effectively used to collectively monitor and investigate air pollution events.