Dynamic complex network analysis of PM2.5 concentrations in the UK, using hierarchical directed graphs (V1.0.0)

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dc.contributor.authorBroomandi, Parya
dc.contributor.authorGeng, Xueyu
dc.contributor.authorGuo, Weisi
dc.contributor.authorPagani, Alessio
dc.contributor.authorTopping, David
dc.contributor.authorKim, Jong Ryeol
dc.date.accessioned2021-03-11T14:39:43Z
dc.date.available2021-03-11T14:39:43Z
dc.date.issued2021-02-18
dc.description.abstractThe risk of a broad range of respiratory and heart diseases can be increased by widespread exposure to fine atmospheric particles on account of their capability to have a deep penetration into the blood streams and lung. Globally, studies conducted epidemiologically in Europe and elsewhere provided the evidence base indicating the major role of PM2.5 leading to more than four million deaths annually. Conventional approaches to simulate atmospheric transportation of particles having high dimensionality from both transport and chemical reaction process make exhaustive causal inference difficult. Alternative model reduction methods were adopted, specifically a data-driven directed graph representation, to deduce causal directionality and spatial embeddedness. An undirected correlation and a directed Granger causality network were established through utilizing PM2.5 concentrations in 14 United Kingdom cities for one year. To demonstrate both reduced-order cases, the United Kingdom was split up into two southern and northern connected city communities, with notable spatial embedding in summer and spring. It continued to reach stability to disturbances through the network trophic coherence parameter and by which winter was construed as the most considerable vulnerability. Thanks to our novel graph reduced modeling, we could represent high-dimensional knowledge in a causal inference and stability framework.en_UK
dc.identifier.citationBroomandi P, Geng X, Guo W, et al., (2021) Dynamic complex network analysis of PM2.5 concentrations in the UK, using hierarchical directed graphs (V1.0.0). Sustainability, Volume 13, Issue 4, February 2021, Article number 2201en_UK
dc.identifier.issn1937-0695
dc.identifier.urihttps://doi.org/10.3390/su13042201
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16467
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectatmospheric pollutionen_UK
dc.subjectcausalityen_UK
dc.subjectstabilityen_UK
dc.subjectcomplex networken_UK
dc.subjectPM2.5en_UK
dc.titleDynamic complex network analysis of PM2.5 concentrations in the UK, using hierarchical directed graphs (V1.0.0)en_UK
dc.typeArticleen_UK

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