Evaluation of the effects of particulate matter forecasting system on behavior patterns in Seoul, Korea

Abstract

Background and aim: The particulate matter (PM) forecasting system is one of the most prominent political options that can help to reduce the risk of PM. Its goal is to urge people to take avoidance behaviors for upcoming pollution by issuing warnings. In Korea, the national PM10 forecasting system was launched on February 6, 2014. We aimed to estimate the effectiveness of the PM forecasting system in relation to the number of visitors to the Children’s Grand Park in Seoul, Korea. Methods: We used regression discontinuity design to estimate the effectiveness of the policy from 2014 to 2019. Since the PM forecasting results were not available, the measured PM10 concentration of Seoul was used as a proxy for treatment variable. The cut-off point of the intervention was set to 80ug/m3, the starting point for a "Bad” rating, and the bandwidth was set to 10ug/m3. We further adjusted the daily mean temperature. Results: When the PM10 concentration exceeds 80ug/m3, the number of visitors to the park decreased by about 15,000. In addition, there was a negative relationship between PM10 concentration and the number of park visitors where pollution levels were over 80ug/m3. The results were statistically significant at the 10% significance level. Conclusions: Our result indicates that the PM10 forecasting system seems effective in Korea. According to previous studies in Korea, the risk of PM10 on various health outcomes decreased in recent years. The introduction of the forecasting system and increment in awareness of PM might be possible causes for that change in the PM10 risk.