Preprints
https://doi.org/10.5194/egusphere-2024-1173
https://doi.org/10.5194/egusphere-2024-1173
22 Aug 2024
 | 22 Aug 2024
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Gridded surface O3, NOx, and CO abundances for model metrics from the South Korean ground station network

Calum Patrick Wilson and Michael John Prather

Abstract. We present gridded surface air quality datasets over South Korea for three key species – ozone (O3), carbon monoxide (CO), and nitrogen oxides (NOx) during the timeframe of the Korea–US Air Quality (KORUS–AQ) mission (May–June 2016). The tenth degree hourly averaged abundances are constructed from the 300+ air quality network sites using inverse distance weighting with simple declustering. Cross–comparing the interpolated fields against the site data that was used to create them reveals high prediction skill for O3 (80 %) throughout South Korea, and moderate skill (60 %) for CO and NOx on average in densely observed regions after individual mean bias corrections. The gridded O3 and CO interpolations predict the NASA DC–8 observations in the planetary boundary layer (PBL) with high skill (80 %) in the Seoul Metropolitan Area (SMA) after subtracting the mean bias. DC–8 NOx observations were much less predictable on account of consistently negative vertical gradients within the PBL. Our gridded products capture the mean and variability of O3 throughout South Korea, and of CO and surface NOx in most site–dense urban centres (SMA, Cheongju, Gwangju, Daegu, Changwon, and Busan).

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Calum Patrick Wilson and Michael John Prather

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1173', Anonymous Referee #1, 13 Oct 2024 reply
    • AC1: 'Reply on RC1', Calum Wilson, 21 Oct 2024 reply
Calum Patrick Wilson and Michael John Prather
Calum Patrick Wilson and Michael John Prather

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Short summary
We evaluated how well we can infer air pollutant levels (ozone, carbon monoxide, and nitrogen oxides) between air quality stations throughout South Korea, finding good representation in most densely measured cities in spite of intense small-scale emission hotspots. Comparing observed air quality with gridded model output is desirable, and so we created gridded datasets over South Korea using air quality station measurements, which agreed with airborne measurements around Seoul.