Collaborative governance is increasingly advocated to address the ecological risk management issues that occur during urban agglomeration developing. However, how to form strong and effective collaboration is still a great challenge among multiple cities in urban agglomeration. By analysing the multiple ecological risk transmission pathways of the case of Pearl River Delta Urban Agglomeration (PRD) in China, this paper aims at deconstructing the complex structure and connection types in urban agglomeration, as well as exploring the inherent mechanism of ecological risk governance to achieve collaboration. Thus, a new Bayesian network model of ecological risk transmission is developed to visualize the key connection notes of risk transmission process. Testing the impacts of (1) number of collaborative cities, (2) spatial distance factor and (3) risk transmission links, we can find the optimal cooperative risk management strategy by reducing the probability of occurrence of key nodes and intervening on the critical path of the risk transmission process. The results show that (1) The current collab- orative governance plan in the PRD is mainly formulated by large cities driving small surrounding cities, which is not an optimal strategy. (2) The management effect of ecological risks in urban agglomerations is not necessarily positively correlated with the number of collaborative cities. There are multiple combinations methods under a certain number of collaborative cities and the effects of ecological risk collaborative governance are different. (3) Collaboration governance of urban agglomeration should be based on the overall planning of urban develop- ment, and comprehensively consider collaboration number, spatial distance and association between cities.

Research on collaborative management and optimization of ecological risks in urban agglomeration

Gonella F.;
2022-01-01

Abstract

Collaborative governance is increasingly advocated to address the ecological risk management issues that occur during urban agglomeration developing. However, how to form strong and effective collaboration is still a great challenge among multiple cities in urban agglomeration. By analysing the multiple ecological risk transmission pathways of the case of Pearl River Delta Urban Agglomeration (PRD) in China, this paper aims at deconstructing the complex structure and connection types in urban agglomeration, as well as exploring the inherent mechanism of ecological risk governance to achieve collaboration. Thus, a new Bayesian network model of ecological risk transmission is developed to visualize the key connection notes of risk transmission process. Testing the impacts of (1) number of collaborative cities, (2) spatial distance factor and (3) risk transmission links, we can find the optimal cooperative risk management strategy by reducing the probability of occurrence of key nodes and intervening on the critical path of the risk transmission process. The results show that (1) The current collab- orative governance plan in the PRD is mainly formulated by large cities driving small surrounding cities, which is not an optimal strategy. (2) The management effect of ecological risks in urban agglomerations is not necessarily positively correlated with the number of collaborative cities. There are multiple combinations methods under a certain number of collaborative cities and the effects of ecological risk collaborative governance are different. (3) Collaboration governance of urban agglomeration should be based on the overall planning of urban develop- ment, and comprehensively consider collaboration number, spatial distance and association between cities.
File in questo prodotto:
File Dimensione Formato  
JCLEPRO urban eco risk.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Accesso chiuso-personale
Dimensione 5.99 MB
Formato Adobe PDF
5.99 MB Adobe PDF   Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5014607
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 7
social impact