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Estimation of anthropogenic heat emission over South Korea using a statistical regression method

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Abstract

Anthropogenic heating by human activity is one of the key contributing factors in forming urban heat islands, thus inclusion of the heat source plays an important role in urban meteorological and environmental modeling. In this study, gridded anthropogenic heat flux (AHF) with high spatial (1-km) and temporal (1-hr) resolution is estimated for the whole South Korea region in year 2010 using a statistical regression method which derives based on similarity of anthropogenic air pollutant emissions and AHF in their emission inventories. The bottom-up anthropogenic pollutant emissions required for the regression method are produced using the intensive Korean air pollutants emission inventories. The calculated regression-based AHF compares well with the inventory-based AHF estimation for the Gyeong-In region, demonstrating that the statistical regression method can reasonably represent spatio-temporal variation of the AHF within the region. The estimated AHF shows that for major Korean cities (Seoul, Busan, Daegu, Gwangju, Daejeon, and Ulsan) the annual mean AHF range 10–50 Wm−2 on a grid scale and 20–30W m−2 on a city-scale. The winter AHF are larger by about 22% than that in summer, while the weekday AHF are larger by 4–5% than the weekend AHF in the major Korean cities. The gridded AHF data estimated in this study can be used in mesoscale meteorological and environmental modeling for the South Korea region.

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Authors and Affiliations

  1. Department of Atmospheric Science, Kongju National University, 182 Singwan-dong, Gongju-si, Chungnam, 314-701, Korea

    Sang-Hyun Lee

  2. Department of Environmental Engineering, Ajou University, Suwon, Korea

    Soon-Tae Kim

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  1. Sang-Hyun Lee
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  2. Soon-Tae Kim
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Correspondence to Sang-Hyun Lee.

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Lee, SH., Kim, ST. Estimation of anthropogenic heat emission over South Korea using a statistical regression method. Asia-Pacific J Atmos Sci 51, 157–166 (2015). https://doi.org/10.1007/s13143-015-0065-6

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  • DOI: https://doi.org/10.1007/s13143-015-0065-6

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