S43A-2470: On the uncertainties of seismic parameters: a Bayesian framework for their estimation using Brune's model

The estimation of seismic parameters from ground-motion records is subject to many uncertainties, such as: (i) parameterization, modeling procedures and underlying hypotheses, (ii) approximated input parameters, (iii) instrumental errors on records and their impact in data post-processing, (iv) procedures to estimate model’s parameters. However these uncertainties are rarely treated and propagated to the final results. For example, on one side, density of rocks, velocity model, geometrical spreading, radiation pattern are just some of the common parameters needed to estimate the main seismic parameters of an earthquake and are generally used as average values. On the other side, uncertainties derived from the acquisition system and processing of the data are often neglected. Nevertheless, in many cases these uncertainties may be particularly important, as for example in the analysis of historical earthquakes, where both instrumental response and treatment of analog records intrinsically imply non negligible sources of uncertainty. Here, we present a new Bayesian procedure to estimate seismic parameters that allows: (i) to obtain a robust estimation of the Brune’s model parameters (Brune 1970, 1971) and relatives uncertainties, (ii) to account for the uncertainty related to the Earth model, and (iii) to propagate such uncertainties on the estimation of seismological parameters (seismic moment, moment magnitude, radius of the circular source zone and static stress drop). It is important to highlight that this study does not want to discuss the validity or the physical significance of the Brune’s model, but it is focused on the details of how to fit it on a dataset in order to evaluate the seismological parameters, accounting and properly propagating a rather large range of uncertainties. These capabilities of the proposed procedure are finally demonstrated through an illustrative application analyzing seismic records from historical events

The ARGO Project: assessing NA-TECH risks on offshore oil platforms

Abstract Analysis of natural and anthRopoGenic risks on Offshore platforms (ARGO) is a 3-years project, funded by the Italian Ministry of Economic Development. The project, coordinated by AMRA, a permanent Research Centre for the development of innovative technologies applied to environmental problems, aims at providing technical-support for the analysis of natural and anthropogenic risks on offshore oil-platforms. ARGO has developed methodologies for the probabilistic analysis of industrial accidents triggered by natural events (NA-TECH) on offshore platforms. The final analysis of the ARGO Project suggest a constant monitoring of exploitation activity, fluids re-injection and storage using high technology networks

Cross-cutting principles for planetary health education

Since the 2015 launch of the Rockefeller Foundation Lancet Commission on planetary health,1 an enormous groundswell of interest in planetary health education has emerged across many disciplines, institutions, and geographical regions. Advancing these global efforts in planetary health education will equip the next generation of scholars to address crucial questions in this emerging field and support the development of a community of practice. To provide a foundation for the growing interest and efforts in this field, the Planetary Health Alliance has facilitated the first attempt to create a set of principles for planetary health education that intersect education at all levels, across all scales, and in all regions of the world—ie, a set of cross-cutting principles

Global economic burden of unmet surgical need for appendicitis

Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

Analysis of eruptive and seismic sequences to improve the short-and long-term eruption forecasting

Forecasting the time, location, nature, and scale of volcanic eruptions is one of the most urgent aspects of modern applied volcanology. The reliability of probabilistic forecasting procedures is strongly related to the reliability of the input information provided, implying objective criteria for interpreting the historical and monitoring data. For this reason both, detailed analysis of past data and more basic research into the processes of volcanism, are fundamental tasks of a continuous information-gain process; in this way the precursor events of eruptions can be better interpreted in terms of their physical meanings with correlated uncertainties. This should lead to better predictions of the nature of eruptive events. In this work we have studied different problems associated with the long- and short-term eruption forecasting assessment. First, we discuss different approaches for the analysis of the eruptive history of a volcano, most of them generally applied for long-term eruption forecasting purposes; furthermore, we present a model based on the characteristics of a Brownian passage-time process to describe recurrent eruptive activity, and apply it for long-term, time-dependent, eruption forecasting (Chapter 1). Conversely, in an effort to define further monitoring parameters as input data for short-term eruption forecasting in probabilistic models (as for example, the Bayesian Event Tree for eruption forecasting -BET_EF-), we analyze some characteristics of typical seismic activity recorded in active volcanoes; in particular, we use some methodologies that may be applied to analyze long-period (LP) events (Chapter 2) and volcano-tectonic (VT) seismic swarms (Chapter 3); our analysis in general are oriented toward the tracking of phenomena that can provide information about magmatic processes. Finally, we discuss some possible ways to integrate the results presented in Chapters 1 (for long-term EF), 2 and 3 (for short-term EF) in the BET_EF model (Chapter 4)

S43A-2470: On the uncertainties of seismic parameters: a Bayesian framework for their estimation using Brune's model

The estimation of seismic parameters from ground-motion records is subject to many uncertainties, such as: (i) parameterization, modeling procedures and underlying hypotheses, (ii) approximated input parameters, (iii) instrumental errors on records and their impact in data post-processing, (iv) procedures to estimate model’s parameters. However these uncertainties are rarely treated and propagated to the final results. For example, on one side, density of rocks, velocity model, geometrical spreading, radiation pattern are just some of the common parameters needed to estimate the main seismic parameters of an earthquake and are generally used as average values. On the other side, uncertainties derived from the acquisition system and processing of the data are often neglected. Nevertheless, in many cases these uncertainties may be particularly important, as for example in the analysis of historical earthquakes, where both instrumental response and treatment of analog records intrinsically imply non negligible sources of uncertainty. Here, we present a new Bayesian procedure to estimate seismic parameters that allows: (i) to obtain a robust estimation of the Brune’s model parameters (Brune 1970, 1971) and relatives uncertainties, (ii) to account for the uncertainty related to the Earth model, and (iii) to propagate such uncertainties on the estimation of seismological parameters (seismic moment, moment magnitude, radius of the circular source zone and static stress drop). It is important to highlight that this study does not want to discuss the validity or the physical significance of the Brune’s model, but it is focused on the details of how to fit it on a dataset in order to evaluate the seismological parameters, accounting and properly propagating a rather large range of uncertainties. These capabilities of the proposed procedure are finally demonstrated through an illustrative application analyzing seismic records from historical events.UnpublishedSan Francisco, USA.3.1. Fisica dei terremotiope

A probabilistic tool for multi-hazard risk analysis using a bow-tie approach: application to environmental risk assessments for geo-resource development projects

In this paper, we present a methodology and a computational tool for performing environmental risk assessments for geo-resource development projects. The main scope is to implement a quantitative model for performing highly specialised multi-hazard risk assessments in which risk pathway scenarios are structured using a bow-tie approach, which implies the integrated analysis of fault trees and event trees. Such a model needs to be defined in the interface between a natural/built/social environment and a geo-resource development activity perturbing it. The methodology presented in this paper is suitable for performing dynamic environmental risk assessments using state-of-the-art knowledge and is characterised by: (1) the bow-tie structure coupled with a wide range of probabilistic models flexible enough to consider different typologies of phenomena; (2) the Bayesian implementation for data assimilation; (3) the handling and propagation of modelling uncertainties; and (4) the possibility of integrating data derived form integrated assessment modelling. Beyond the stochastic models usually considered for reliability analyses, we discuss the integration of physical reliability models particularly relevant for considering the effects of external hazards and/or the interactions between industrial activities and the response of the environment in which such activities are performed. The performance of the proposed methodology is illustrated using a case study focused on the assessment of groundwater pollution scenarios associated with the management of flowback fluids after hydraulically fracturing a geologic formation. The results of the multi-hazard risk assessment are summarised using a risk matrix in which the quantitative assessments (likelihood and consequences) of the different risk pathway scenarios considered in the analysis can be compared. Finally, we introduce an open-access, web-based, service called MERGER, which constitutes a functional tool able to quantitatively evaluate risk scenarios using a bow-tie approach.The work presented in this paper has been performed in the framework of the EU H2020 SHEER (Shale gas exploration and exploitation induced Risks) Project, Grant No. 640896. The implementation of the MERGER system in the IS-EPOS platform is performed in the framework of the EU H2020 EPOS-IP (European Plate Observing System) project, Grant No. 676564. AMRA (AG, RR, PG) received support from the Italian Ministry of Economic Development (MISE - DGRME) by co-financing the research activities in the framework of the cooperation agreement n. 23671 (06/08/2014). Activities from Polish partners (JK) in EPOS-IP are co-financed by Polish research funds associated with the EPOS-IP project, Grant No. 3503/H2020/15/2016/2.Published385-4106V. Pericolosità vulcanica e contributi alla stima del rischioJCR Journa

Multi-hazard risk pathway scenarios associated with unconventional gas development: Identification and challenges for their assessment

In this paper we summarize a number of risk pathway scenarios that are often claimed in literature as of priority for risk analyses in unconventional gas development. The resulting scenarios are structured in diagrams representing causal relationships between events. We argue that science is called to fill gaps regarding the main processes characterizing the involved events and defining the conditions under which their occurrence may be enhanced or inhibited. In this way, these scenarios can be more objectively parameterized, making their quantitative assessment a more feasible task and opening the way for the formulation of appropriate risk mitigation strategies