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4.
Philos Trans A Math Phys Eng Sci ; 376(2121)2018 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-29712793

RESUMO

Extreme weather causes substantial adverse socio-economic impacts by damaging and disrupting the infrastructure services that underpin modern society. Globally, $2.5tn a year is spent on infrastructure which is typically designed to last decades, over which period projected changes in the climate will modify infrastructure performance. A systems approach has been developed to assess risks across all infrastructure sectors to guide national policy making and adaptation investment. The method analyses diverse evidence of climate risks and adaptation actions, to assess the urgency and extent of adaptation required. Application to the UK shows that despite recent adaptation efforts, risks to infrastructure outweigh opportunities. Flooding is the greatest risk to all infrastructure sectors: even if the Paris Agreement to limit global warming to 2°C is achieved, the number of users reliant on electricity infrastructure at risk of flooding would double, while a 4°C rise could triple UK flood damage. Other risks are significant, for example 5% and 20% of river catchments would be unable to meet water demand with 2°C and 4°C global warming respectively. Increased interdependence between infrastructure systems, especially from energy and information and communication technology (ICT), are amplifying risks, but adaptation action is limited by lack of clear responsibilities. A programme to build national capability is urgently required to improve infrastructure risk assessment.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'.

5.
Sci Rep ; 12(1): 16221, 2022 09 28.
Artigo em Inglês | MEDLINE | ID: mdl-36171329

RESUMO

Cost-effective on-demand computing resources can help to process the increasing number of large, diverse datasets generated from smart internet-enabled technology, such as sensors, CCTV cameras, and mobile devices, with high temporal resolution. Category 1 emergency services (Ambulance, Fire and Rescue, and Police) can benefit from access to (near) real-time traffic- and weather data to coordinate multiple services, such as reassessing a route on the transport network affected by flooding or road incidents. However, there is a tendency not to utilise available smart city data sources, due to the heterogeneous data landscape, lack of real-time information, and communication inefficiencies. Using a systems engineering approach, we identify the current challenges faced by stakeholders involved in incident response and formulate future requirements for an improved system. Based on these initial findings, we develop a use case using Microsoft Azure cloud computing technology for analytical functionalities that can better support stakeholders in their response to an incident. Our prototype allows stakeholders to view available resources, send automatic updates and integrate location-based real-time weather and traffic data. We anticipate our study will provide a foundation for the future design of a data ontology for multi-agency incident response in smart cities of the future.


Assuntos
Ambulâncias , Serviços Médicos de Emergência , Cidades , Computação em Nuvem , Inundações
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