Dynamic Complex Network Analysis of PM2.5 Concentrations in the UK, Using Hierarchical Directed Graphs (V1.0.0)

The risk of a broad range respiratory and heart diseases can be increased by widespread exposure to fine atmospheric particles on account their capability have deep penetration into the blood streams lung. Globally, studies conducted epidemiologically in Europe elsewhere provided evidence base indicating major role PM2.5 leading more than four million deaths annually. Conventional approaches simulate transportation having high dimensionality from both transport chemical reaction process make exhaustive causal inference difficult. Alternative model reduction methods were adopted, specifically data-driven directed graph representation, deduce directionality spatial embeddedness. An undirected correlation Granger causality network established through utilizing concentrations 14 United Kingdom cities for one year. To demonstrate reduced-order cases, was split up two southern northern connected city communities, with notable embedding summer spring. It continued reach stability disturbances trophic coherence parameter which winter construed as most considerable vulnerability. Thanks our novel reduced modeling, we could represent high-dimensional knowledge framework.