scholarly journals Toward a cross-border early-warning system for Central Asia

2015 ◽  
Vol 58 (1) ◽  
Author(s):  
Jacek Stankiewicz ◽  
Dino Bindi ◽  
Adrien Oth ◽  
Stefano Parolai
Keyword(s):  
Central Asia ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Large Scale ◽  
Damage Control ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Successful Implementation ◽  
Cross Border

<p>Rapidly expanding urban areas in Central Asia are increasingly vulnerable to seismic risk; but at present, no earthquake early warning (EEW) systems exist in the region despite their successful implementation in other earthquake-prone areas. Such systems aim to provide short (seconds to tens of seconds) warnings of impending disaster, enabling the first risk mitigation and damage control steps to be taken. This study presents the feasibility of a large scale cross-border regional system for Central Asian countries. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. Installation of such systems within 3 years aims to both reducing the endemic lack of strong motion data in Central Asia that is limiting the possibility of improving seismic hazard assessment, and at providing the first regional earthquake early warning system in the area.</p>

A cross-border regional earthquake early warning system: PRESTo@CE3RN

2016 ◽  
Vol 86 (S2) ◽  
pp. 431-440 ◽  
Author(s):  
Damiano Pesaresi ◽  
Matteo Picozzi ◽  
Mladen Živčić ◽  
Wolfgang Lenhardt ◽  
Marco Mucciarelli ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System ◽  
Cross Border ◽  
Regional Earthquake

An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache
Keyword(s):  
Air Pollution ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Urban Air Pollution ◽  
Warning System ◽  
Air Pollutant ◽  
Pollution Level ◽  
Urban Air ◽  
Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

scholarly journals Feasibility study of earthquake early warning in Tehran, Iran

2021 ◽  
Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Disaster Mitigation ◽  
Lead Times ◽  
Worst Case ◽  
Earthquake Parameters ◽  
Earthquake Early Warning System ◽  
Earthquake Scenarios

AbstractIn this study, we examine the scientific feasibility of an Earthquake Early Warning System in Tehran, Iran, by the integration of the Tehran Disaster Mitigation and Management Organization (TDMMO) accelerometric network and the PRobabilistic and Evolutionary early warning SysTem (PRESTo). To evaluate the performance of the TDMMO-PRESTo system in providing the reliable estimations of earthquake parameters and the available lead-times for The Metropolis of Tehran, two different approaches were analyzed in this work. The first approach was assessed by applying the PRESTo algorithms on waveforms from 11 moderate instrumental earthquakes that occurred in the vicinity of Tehran during the period 2009–2020. Moreover, we conducted a simulation analysis using synthetic waveforms of 10 large historical earthquakes that occurred in the vicinity of Tehran. We demonstrated that the six worst-case earthquake scenarios can be considered for The Metropolis of Tehran, which are mostly related to the historical and instrumental events that occurred in the southern, eastern, and western parts of Tehran. Our results indicate that the TDMMO-PRESTo system could provide reliable and sufficient lead-times of about 1 to 15s and maximum lead-times of about 20s for civil protection purposes in The Metropolis of Tehran.

The First Stage of an Earthquake Early Warning System in South Korea

2017 ◽  
Vol 88 (6) ◽  
pp. 1491-1498 ◽  
Author(s):  
Dong‐Hoon Sheen ◽  
Jung‐Ho Park ◽  
Heon‐Cheol Chi ◽  
Eui‐Hong Hwang ◽  
In‐Seub Lim ◽  
...  
Keyword(s):  
South Korea ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Earthquake Early Warning System

Robust, an Earthquake Early Warning System in the Lower Rhine Embayment, Germany

2021 ◽  
Author(s):  
Bita Najdahmadi ◽  
Marco Pilz ◽  
Dino Bindi ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Adrien Oth ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Optimization Approach ◽  
Ground Acceleration ◽  
Earthquake Early Warning System ◽  
Scenario Earthquakes ◽  
Lower Rhine Embayment ◽  
Lower Rhine

&lt;p&gt;The Lower Rhine Embayment in western Germany is one of the most important areas of earthquake recurrence north of the Alps, facing a moderate level of seismic hazard in the European context but a significant level of risk due to a large number of important&amp;#160;industrial infrastructures. In this context, the project ROBUST aims at designing a user-oriented hybrid earthquake early warning and rapid response system where regional seismic monitoring is combined with smart, on-site sensors, resulting in the implementation of decentralized early warning procedures.&lt;br&gt;&lt;br&gt;One of the research areas of this project deals with finding an optimal regional seismic network arrangement. With the optimally compacted network, strong ground movements can be detected quickly and reliably. In this work simulated scenario earthquakes in the area are used with an optimization approach in order to densify the existing sparse network through the installation of additional decentralized measuring stations. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. By minimizing the cost function, a comparison of the best earthquake early warning system designs is performed and the potential usefulness of existing stations in the region is considered as&amp;#160;will be presented in the meeting.&lt;/p&gt;

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