Abstract
Fine-scale nitrogen oxide (NOx) concentrations over South Korea are examined using surface observations, satellite data and high-resolution model simulations based on the latest emission inventory. While accurate information on NOx emissions in South Korea is crucial to understanding regional air quality in the region, consensus on the validation of NOx emissions is lacking. We investigate the spatial and temporal variation in fine-scale NOx emission sources over South Korea. Surface observations and newly available fine-scale satellite data (TROPOspheric Monitoring Instrument; TROPOMI; 3.5 × 7 km2) are compared with the community multiscale air quality (CMAQ) model based on the clean air policy support system (CAPSS) 2016 emission inventory. The results show that the TROPOMI NO2 column densities agree well with the CMAQ simulations based on CAPSS emissions (e.g., R = 0.96 for June 2018). The surface observations, satellite data and model are consistent in terms of their spatial distribution, the overestimation over the Seoul Metropolitan Area and major point sources; however, the model tends to underestimate the surface concentrations during the cold season.
Highlights
Introductionnitrogen oxide (NOx) emissions are released in the form of NO, but they react quickly and are transformed into NO2
Nitrogen oxides (NOx = NO + NO2 ) play an important role in tropospheric chemistry as well as in the formation of surface ozone and secondary aerosol formation for particulate matter
We evaluated the performance of the basic model to demonstrate the capability of the modeling system
Summary
NOx emissions are released in the form of NO, but they react quickly and are transformed into NO2. NO2 is a good indicator of NOx emissions, and using NO2 concentration as a proxy of NOx emissions has been accepted for practical purposes [1,2,3,4,5]. The observed concentration of surface NO2 concentration or vertically integrated column density has been used to estimate the amount of NOx emissions, especially in highly industrialized and urbanized areas such as East Asian cities. As providing accurate information on the intensity and location of emission sources is crucial to improving a chemical transport model, numerous studies have used observational data from surface and space-borne measurements to evaluate a model’s performance and update emission inventory information [6,7].
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