Particulate Matter Mortality Rates and Their Modification by Spatial Synoptic Classification

Abstract

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.

Short-Term Associations of Fine Particulate Matter and Synoptic Weather Types with Cardiovascular Mortality: An Ecological Time-Series Study in Shanghai, China

“…In European countries, the relationship between air pollutants and cardiovascular mortality has been found to be overall positive and of higher magnitude at high air temperatures [42]. In Asia, a study in Korea also found similar modification effects [43].…”

Gastrointestinal tissue as a “new” target of pollution exposure

“…The micrometric size of UFPs increases their ability to absorb toxins, microorganisms, and spores (pathobionts) on their surface and allows them to translocate through alveolar epithelial cells and enter the systemic circulatory system where they can cause damage to distal tissues and cells and where the presence of absorbed reactive substances can further stimulate immune cell reactivity. 14,15 In particular, PM exposure has been associated with general adverse health effects and the development/exacerbation of organic-specific disorders: for example, in lungs (decreased lung function, asthma and general worsening of respiratory problems), 10,16 in the heart (cardiac arrhythmia and heart attack), 9,17,18 in the skin (psoriasis, atopic dermatitis, acne) [19][20][21] and in the eyes (dry eyes, conjunctiva disorders). 22,23 Only relatively recently, the scientific community has been interested in investigating the harmful effects of PM on the gastrointestinal (GI) tract, linking the pollutant exposure to the triggering or exacerbation of inflammatory bowel disorders such as inflammatory bowel disease (IBD), Crohn's disease and colorectal cancer.…”

Real-Time Low-Cost Personal Monitoring for Exposure to PM2.5 among Asthmatic Children: Opportunities and Challenges

“…Their home locations, distributed around Seoul Metropolitan Area, are shown as a triangle in Figure 1. [24,25]. Recently, a number of monitoring efforts have been undertaken including a feasibility study to assess indoor PM exposure, but most of them focused on fixed IoT devices which failed to capture the concurrent air pollution and environmental monitoring data from their real-time locations [26,27].…”

“…In South Korea, most of the PM-related public health policies and clinical interventions remain based on outdoor environments monitored by the conventional station-based method due to the lack of efforts to promote a large-scale personalized monitoring [24,25]. Recently, a number of monitoring efforts have been undertaken including a feasibility study to assess indoor PM exposure, but most of them focused on fixed IoT devices which failed to capture the concurrent air pollution and environmental monitoring data from their real-time locations [26,27].…”