Air pollution levels are highly correlated with temperature or humidity, so we investigated the relationship between PM10 and the spatial synoptic classification (SSC) scheme on daily mortality, according to age group and season. Daily death data for 2000–2014 from Seoul, Korea, were acquired, and time-series analysis was applied with respect to season and to each of seven distinct SSC types: dry moderate (DM); dry polar (DP); dry tropical (DT); moist moderate (MM); moist polar (MP); moist tropical (MT); and transition (T). Modification effects were estimated for daily, non-accidental, cardiovascular, and respiratory mortality between PM10 and SSC types. The following SSC-type-specific increased mortalities were observed, by cause of death: non-accidental mortality: DT (1.86%) and MT (1.86%); cardiovascular mortality: DT (2.83%) and MM (3.00%); respiratory mortality: MT (3.78%). Based on simplified weather types, increased PM10 effects in non-accidental mortality rates were observed in dry (1.54%) and moist (2.32%) conditions among those aged 40–59 years and were detected regardless of conditions in other age groups: 60–74 (1.11%), 75–84 (1.55%), and 85+ (1.75%). The effects of particulate air pollution, by SSC, suggest the applicability of SSC to the comparison and understanding of acute effects of daily mortality based on weather type.
Particulate Matter Mortality Rates and Their Modification by Spatial Synoptic Classification
