Statistical predictability of wintertime PM2.5 concentrations over East Asia using simple linear regression
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jeong, Jaein I. | - |
dc.contributor.author | Park, Rokjin J. | - |
dc.contributor.author | Yeh, Sang-Wook | - |
dc.contributor.author | Roh, Joon-Woo | - |
dc.date.accessioned | 2021-06-22T04:43:21Z | - |
dc.date.available | 2021-06-22T04:43:21Z | - |
dc.date.created | 2021-05-10 | - |
dc.date.issued | 2021-07 | - |
dc.identifier.issn | 0048-9697 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/612 | - |
dc.description.abstract | The interannual meteorological variability plays an important role in wintertime air quality in East Asia. In particular, monsoons and the El Niño Southern Oscillation (ENSO) are known as important mechanisms for determining wintertime PM2.5 concentrations. In addition, Arctic Oscillation, North Atlantic Oscillation, and Pacific Decadal Oscillation are also known to affect meteorological conditions and thus PM2.5 concentrations in East Asia. Here, we used a global 3-D chemical transport model (GEOS-Chem) with assimilated meteorological fields to investigate the long-term (1980–2014) relationship between 16 different climate indices and wintertime PM2.5 concentrations in this region. We show that wintertime PM2.5 concentrations in Northeast Asia (33–41°N, 118–141°E) are highly correlated with ENSO indices and the Siberian high-pressure system. Furthermore, we develop a simple linear regression (SLR) model for the prediction of wintertime PM2.5 concentrations. Despite the use of a single predictor, the SLR model shows good performance with r > 0.72 in reproducing targeted PM2.5 concentrations. The hit and false alarm rates are 77% and 11%, respectively, indicating the high predictive accuracy of the model. In particular, the model shows excellent performance for capturing the abnormal variability of wintertime PM2.5 concentrations in Northeast Asia. © 2021 Elsevier B.V. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Elsevier BV | - |
dc.title | Statistical predictability of wintertime PM2.5 concentrations over East Asia using simple linear regression | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Yeh, Sang-Wook | - |
dc.identifier.doi | 10.1016/j.scitotenv.2021.146059 | - |
dc.identifier.scopusid | 2-s2.0-85102058206 | - |
dc.identifier.wosid | 000647608000010 | - |
dc.identifier.bibliographicCitation | Science of the Total Environment, v.776, pp.1 - 9 | - |
dc.relation.isPartOf | Science of the Total Environment | - |
dc.citation.title | Science of the Total Environment | - |
dc.citation.volume | 776 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 9 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.subject.keywordPlus | Air quality | - |
dc.subject.keywordPlus | Atmospheric movements | - |
dc.subject.keywordPlus | Atmospheric pressure | - |
dc.subject.keywordPlus | Atmospheric thermodynamics | - |
dc.subject.keywordPlus | Climate models | - |
dc.subject.keywordPlus | Climatology | - |
dc.subject.keywordPlus | Climate index | - |
dc.subject.keywordPlus | East Asia | - |
dc.subject.keywordPlus | El Nino southern oscillation | - |
dc.subject.keywordPlus | Interannual | - |
dc.subject.keywordPlus | Linear regression modelling | - |
dc.subject.keywordPlus | Northeast Asia | - |
dc.subject.keywordPlus | Performance | - |
dc.subject.keywordPlus | PM$-2.5$ | - |
dc.subject.keywordPlus | Simple linear regression | - |
dc.subject.keywordPlus | Winter monsoon | - |
dc.subject.keywordPlus | Linear regression | - |
dc.subject.keywordPlus | air quality | - |
dc.subject.keywordPlus | annual variation | - |
dc.subject.keywordPlus | concentration (composition) | - |
dc.subject.keywordPlus | El Nino-Southern Oscillation | - |
dc.subject.keywordPlus | long-term change | - |
dc.subject.keywordPlus | monsoon | - |
dc.subject.keywordPlus | particulate matter | - |
dc.subject.keywordPlus | prediction | - |
dc.subject.keywordPlus | regression analysis | - |
dc.subject.keywordPlus | three-dimensional modeling | - |
dc.subject.keywordPlus | winter | - |
dc.subject.keywordPlus | article | - |
dc.subject.keywordPlus | Asia | - |
dc.subject.keywordPlus | El Nino | - |
dc.subject.keywordPlus | linear regression analysis | - |
dc.subject.keywordPlus | particulate matter 2.5 | - |
dc.subject.keywordPlus | prediction | - |
dc.subject.keywordPlus | winter | - |
dc.subject.keywordPlus | Far East | - |
dc.subject.keywordAuthor | Climate indices | - |
dc.subject.keywordAuthor | East Asia | - |
dc.subject.keywordAuthor | PM2.5 | - |
dc.subject.keywordAuthor | Simple linear regression | - |
dc.subject.keywordAuthor | Winter monsoon | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0048969721011268?via%3Dihub | - |
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