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Background/Objectives: This research aims to increase public interest about particulate matter (PM) exposure using Google Trends (GT) to determine the correlation between the actual concentration value of PM and public perception. Methods/Statistical analysis: We collected open public data on average concentrations of PM10 and PM2.5, weather/climate, real-time web search volume on PM, PM-related consumer goods, and health-related information for 70 days from January 1 to March 11, 2019 for Seoul. Statistical analysis on correlation was carried out on this data. Findings: PM10 was correlated with real-time web search, air cleaner, and filter-mask (or dust mask), while PM2.5 was correlated with temperature, humidity, real-time web search, air cleaner, and filter-mask. We found that when the concentrations of PM10 and PM2.5 were high, the search volumes for PM10 and PM2.5 increased, and the rate of purchase of air cleaners and filter-masks increased. This indicated a correlation between increased concentrations of PM10 and PM2.5 and respiratory diseases. In particular, when PM2.5 concentration was higher than PM10, it was found to be more sensitive to PM-related information. Improvements/Applications: To minimize the adverse effects of PM on public health, we need to have objective information related to PM and public attention and participation.
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