인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Springtime PM<sub>10</sub> concentrations in South Korea pose a critical threat to public health and socioeconomic stability, which can be intensified by Asian Dust and anthropogenic emissions. While previous studies have examined wintertime atmospheric patterns affecting PM 10 concentrations, the physical mechanisms linked to land atmosphere interactions during spring remain largely unexplored. This study investigated the dominant synoptic patterns and the associated land and atmospheric processes, regulating inter-annual variability of spring PM<sub>10</sub> concentrations (2003 2024) using data from the European Centre for Medium-Range Weather Forecasts Reanalysis v.5 (ERA5) and Copernicus Atmosphere Monitoring Service (CAMS). The results revealed that high spring PM<sub>10</sub> concentrations in Korea were significantly associated with anticyclonic anomalies over the Amur River basin in far eastern Russia. The anticyclonic pattern induced the weakening of prevailing westerlies by easterly wind anomalies over the Korean Peninsula, promoting atmospheric stagnation and suppressing pollutant dispersion. The anomalous anticyclonic pattern was statistically and physically linked to snow cover reduction in the Amur River basin. The decreased surface albedo with reducing snow cover enhanced solar radiation absorption and thus greater heat transfer to the atmosphere through sensible and latent heat fluxes. Consequently, the increased atmospheric heating could lead to thermal expansion of the lower to middle troposphere thereby raising geopotential height and inducing the anticyclonic anomaly. By incorporating the atmospheric processes linked to land surface conditions, this research advances the understanding of climate and air quality interactions and offers a robust scientific foundation for developing early warning systems and evidence-based adaptation policies for springtime air quality management.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-151-26-02-096798484