Literature DB >> 32290028

Centrality metric for the vulnerability of urban networks to toxic releases.

Sofia Fellini1, Pietro Salizzoni2, Luca Ridolfi3.   

Abstract

The dispersion of airborne pollutants in the urban atmosphere is a complex, canopy-driven process. The intricate structure of the city, the high number of potential sources, and the large spatial domain make it difficult to predict dispersion patterns, to simulate a great number of scenarios, and to identify the high-impact emission areas. Here we show that these complex transport dynamics can be efficiently characterized by adopting a complex network approach. The urban canopy layer is represented as a complex network. Street canyons and their intersections shape the spatial structure of the network. The direction and the transport capacity of the flow in the streets define the direction and the weight of the links. Within this perspective, pollutant contamination from a source is modeled as a spreading process on a network, and the most dangerous areas in a city are identified as the best spreading nodes. To this aim, we derive a centrality metric tailored to mass transport in flow networks. By means of the proposed approach, vulnerability maps of cities are rapidly depicted, revealing the nontrivial relation between urban topology, transport capacity of the street canyons, and forcing of the external wind. The network formalism provides promising insight in the comprehensive analysis of the fragility of cities to air pollution.

Year:  2020        PMID: 32290028     DOI: 10.1103/PhysRevE.101.032312

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  2 in total

1.  Vulnerability of cities to toxic airborne releases is written in their topology.

Authors:  Sofia Fellini; Pietro Salizzoni; Luca Ridolfi
Journal:  Sci Rep       Date:  2021-11-29       Impact factor: 4.379

2.  Spatiotemporal evolution of NO2 diffusion in Beijing in response to COVID-19 lockdown using complex network.

Authors:  Zhe Zhang; Hong-Di He; Jin-Ming Yang; Hong-Wei Wang; Yu Xue; Zhong-Ren Peng
Journal:  Chemosphere       Date:  2022-01-15       Impact factor: 7.086

  2 in total

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