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Detecting the causality influence of individual meteorological factors on local PM(2.5) concentration in the Jing-Jin-Ji region

Due to complicated interactions in the atmospheric environment, quantifying the influence of individual meteorological factors on local PM(2.5) concentration remains challenging. The Beijing-Tianjin-Hebei (short for Jing-Jin-Ji) region is infamous for its serious air pollution. To improve regional a...

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Detalles Bibliográficos
Autores principales: Chen, Ziyue, Cai, Jun, Gao, Bingbo, Xu, Bing, Dai, Shuang, He, Bin, Xie, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5269577/
https://www.ncbi.nlm.nih.gov/pubmed/28128221
http://dx.doi.org/10.1038/srep40735
Descripción
Sumario:Due to complicated interactions in the atmospheric environment, quantifying the influence of individual meteorological factors on local PM(2.5) concentration remains challenging. The Beijing-Tianjin-Hebei (short for Jing-Jin-Ji) region is infamous for its serious air pollution. To improve regional air quality, characteristics and meteorological driving forces for PM(2.5) concentration should be better understood. This research examined seasonal variations of PM(2.5) concentration within the Jing-Jin-Ji region and extracted meteorological factors strongly correlated with local PM(2.5) concentration. Following this, a convergent cross mapping (CCM) method was employed to quantify the causality influence of individual meteorological factors on PM(2.5) concentration. The results proved that the CCM method was more likely to detect mirage correlations and reveal quantitative influences of individual meteorological factors on PM(2.5) concentration. For the Jing-Jin-Ji region, the higher PM(2.5) concentration, the stronger influences meteorological factors exert on PM(2.5) concentration. Furthermore, this research suggests that individual meteorological factors can influence local PM(2.5) concentration indirectly by interacting with other meteorological factors. Due to the significant influence of local meteorology on PM(2.5) concentration, more emphasis should be given on employing meteorological means for improving local air quality.