On the Effectiveness of Emergency Reduction Measures for Ultrafine Dust Concentration in Seoul, Korea
DOI:
https://doi.org/10.47611/jsrhs.v13i2.6760Keywords:
Ultrafine dust, regression analysis, emergency reduction measures, effecivenessAbstract
Since 2018, emergency reduction measures (ERMs) have been implemented by the Seoul Metropolitan Government to address air quality in Seoul, Republic of Korea. ERMs are activated when the concentration of ultrafine dust, particulate matter (PM) with an aerodynamic diameter of less than 2.5μm (PM 2.5), exceeds a certain level. In this study, using the daily time series data from 1 January 2018 to 31 June 2023, the effectiveness of ERMs is empirically analyzed by specifying multiple regression models in which PM 2.5 is explained not only by the days of ERMs but also by many other important factors. The empirical analysis shows that (i) PM 2.5 is influenced by its own past values up to three days; (ii) PM 2.5 is negatively influenced by both rainfall and wind speed, but positively related to temperature, humidity and yellow dust. The effect of PM 2.5 from the neighborhood (Dailan, China) is significantly positive; (iii) the effect of vehicle traffic volume and coal thermal power generation on PM 2.5 is not statistically significant; (iv) the effect of ERMs is not very strong when many important control variables are included in the regression equation. In conclusion, the ERMs do not play an effective role in reducing PM 2.5 over the whole period. However, it can be seen that the effectiveness of the ERMs has been increasing in recent years.
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Kim, M. (2019). The Effects of Transboundary Air Pollution from China on Ambient Air Quality in
South Korea. Heliyon, 5(12). https://doi.org/10.1016/j.heliyon.2019.e02953
Kim, J., Choi, D., Koo, Y., Lee, J., & Park, H. (2016). Analysis of Domestic and Foreign Contributions using DDM in CMAQ during Particulate Matter Episode Period of February 2014 in Seoul. Journal of Korean Society for Atmospheric Environment, 32(1), 82-99. http://dx.doi.org/10.5572/KOSAE.2016.32.1.082
Kim, K. & Kim, O. (2019). Analyzing Transboundary Particulate Matters of Korea and China Using Time-series Analyses. Journal of the Association of Korean Geographers, 8(1), 33-46. https://doi.org/10.25202/JAKG.8.1.3
Kim, H., Zhang, Q., & Heo, J. (2018). Influence of intense secondary aerosol formation and long-range transport on
aerosol chemistry and properties in the Seoul metropolitan area during spring time: Results from KORUS-AQ.
Atmospheric Chemistry and Physics, 18(10), 7149–7168. https://doi.org/10.5194/acp-18-7149-2018
Lee, S., Kang, B., Yeon, I., Choi, J., Park, H., Park, S., Lee, H., & Cho, B. (2012). Analysis of PM 2.5 Case Study Burden at Chungju City. Journal of Korean Society for Atmospheric Environment, 28(5), 595-615. http://dx.doi.org/10.5572/KOSAE.2012.28.5.595
National Institute of Environmental Research. (2019). Guidelines for installation and operation of air pollution measuring network. Korea Environment Corporation. https://keco.or.kr
Newey, N. & West, K. (1987). A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix. Econometrica, 55(3), 703-708. https://doi.org/10.2307/1913610
Oh, H. R., Ho, C. H., Koo, Y. S., Baek, K. G., Yun, H. Y., Hur, S. K., Choi, D. R., Jhun, J. G., & Shim, J. S. (2020).
Impact of Chinese air pollutants on a record-breaking PMs episode in the Republic of Korea for 11–15 January
Atmospheric Environment, 223, 117262. https://doi.org/10.1016/j.atmosenv.2020.117262
Oh, J., Shin, H., Shin, Y. & Jeong, H. (2017). Forecasting the Particulate Matter in Seoul using a Univariate Time Series Approach. Journal of The Korean Data Analysis Society, 19(5), 2457-2468. https://doi.org/10.37727/jkdas.2017.19.5.2457
Park, S. & Shin, H. (2017). Analysis of the Factors Influencing PM2.5 in Korea: Focusing on Seasonal Factors. Environmental Policy, 25(1), 227-248. https://dx.doi.org/10.15301/jepa.2017.25.1.227
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