scholarly journals Probabilistic Risk Assessment of Livestock Snow Disasters in the Qinghai-Tibetan Plateau

2018 ◽  
Author(s):  
Tao Ye ◽  
Weihang Liu ◽  
Peijun Shi ◽  
Yijia Li ◽  
Jidong Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
High Risk ◽  
Tibetan Plateau ◽  
Return Period ◽  
Probabilistic Risk Assessment ◽  
Assessment Model ◽  
Future Climate Change ◽  
Tibet Autonomous Region ◽  
Probabilistic Risk

Abstract. Understanding risk using a quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment model for livestock snow disasters in the Qinghai-Tibetan Plateau (QTP) region and derives risk assessment results based on historical climate conditions (1980–2015) and present-day prevention capacity. In the model a hazard module was developed to identify/simulate individual snow disaster events based on boosted regression trees. Together with a fitted quantitative vulnerability function, and exposure derived from vegetation type and grassland carrying capacity, risk metrics based on livestock mortality and mortality rate were estimated. In our results, high risk regions include the Nyainqêntanglha Range, Tanggula Range, Bayankhar Mountains and the region between the Kailas Range and neighboring Himalayas. In these regions, annual livestock mortality rates were estimated as > 2 % and mortality was estimated as > 2 sheep unit/km2 at a return period of 1/20 a. Prefectures identified with extremely high risk included Yushu in Qinghai Province and Naqu, Shigatse, Linzhi, and Nagri in the Tibet Autonomous Region. In these prefectures, a snow disaster event with return period of 1/20 a or higher can easily claim a total loss of more than 200 000 sheep units. Our results provide a quantitative reference for preparedness and insurance solutions in reducing mortality risk. The methodology developed here can be further adapted to future climate change risk analyses and provide important information for planning climate change adaption in the QTP region.

scholarly journals Event-based probabilistic risk assessment of livestock snow disasters in the Qinghai–Tibetan Plateau

2019 ◽  
Vol 19 (3) ◽  
pp. 697-713
Author(s):  
Tao Ye ◽  
Weihang Liu ◽  
Jidong Wu ◽  
Yijia Li ◽  
Peijun Shi ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
High Risk ◽  
Tibetan Plateau ◽  
Return Period ◽  
Probabilistic Risk Assessment ◽  
Future Climate Change ◽  
Tibet Autonomous Region ◽  
Event Based ◽  
Probabilistic Risk

Abstract. Understanding risk using quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment (PRA) model for livestock snow disasters in the Qinghai–Tibetan Plateau (QTP) region and derives risk assessment results based on historical climate conditions (1980–2015) and present-day prevention capacity. In the model, a hazard module was developed to identify and simulate individual snow disaster events based on boosted regression trees. By combining a fitted quantitative vulnerability function and exposure derived from vegetation type and grassland carrying capacity, we estimated risk metrics based on livestock mortality and mortality rate. In our results, high-risk regions include the Nyainqêntanglha Range, Tanggula Range, Bayankhar Mountains and the region between the Kailas Range and the neighbouring Himalayas. In these regions, annual livestock mortality rates were estimated as >2 % and mortality was estimated as >2 sheep unit km−1 at a return period of 20 years. Prefectures identified with extremely high risk include Guoluo in Qinghai Province and Naqu, and Shigatse in the Tibet Autonomous Region. In these prefectures, a snow disaster event with a return period of 20 years or higher can easily claim total losses of more than 500 000 sheep units. Our event-based PRA results provide a quantitative reference for preparedness and insurance solutions in reducing mortality risk. The methodology developed here can be further adapted to future climate change risk analyses and provide important information for planning climate change adaption in the QTP region.

Applying Probabilistic Risk Assessment to Safety Risk Analysis in Aviation

2016 ◽  
pp. 321-343
Author(s):  
Poornima Balakrishna ◽  
Sherry Smith Borener ◽  
Ian Crook ◽  
Alan Durston ◽  
Mindy J. Robinson
Keyword(s):  
Risk Assessment ◽  
Probabilistic Risk Assessment ◽  
Hazard Identification ◽  
Assessment Model ◽  
Subject Matter Experts ◽  
Technological Changes ◽  
National Airspace System ◽  
Assessment Techniques ◽  
Structured Approach ◽  
Probabilistic Risk

When making policy, procedural, or technological changes to a complex system that has safety implications, a key question decision makers must answer is: What are the risks to the users of the system that will result from making these changes to the system? This chapter illustrates a method to explore different facets of this question using mathematical modeling and probabilistic risk assessment techniques, with the objective of assessing the safety impact of changes to the National Airspace System that follow from the Federal Aviation Administration's next generation air traffic modernization program. The authors describe the development of an Integrated Safety Assessment Model as a structured approach to evaluating current and emerging risks in National Airspace System operations. This process addresses the previously stated risk question by combining fault tree and event sequence diagram modeling techniques, hazard identification and analysis methods, opinions from subject matter experts, and concepts from business intelligence.

A Probabilistic Risk Assessment Model for Birds Exposed to Granular Pesticides

2007 ◽  
Vol preprint (2009) ◽  
pp. 1
Author(s):  
Dwayne Robert James Moore ◽  
David Fischer ◽  
Scott Teed ◽  
Sara Rodney
Keyword(s):  
Risk Assessment ◽  
Probabilistic Risk Assessment ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Probabilistic Risk

Use of Thermodynamics, Engineering Economics and Probabilistic Risk Assessment in Evaluating Climate Change Decisions

2009 ◽  
Author(s):  
Milton Meckler ◽  
Amip J. Shah
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Thermal Performance ◽  
Distribution System ◽  
Probabilistic Risk Assessment ◽  
System Level ◽  
Electrical Grid ◽  
Engineering Economics ◽  
Infrastructural Support ◽  
Probabilistic Risk

Climate change is often considered in terms of its macroscale implications. For example, many governments and non-governmental organizations are engaged in the development of policy frameworks that could influence different societal actions and behavioral scenarios. But such macroscale policy decisions may also significantly impact the localized design of products and services in different business ecosystems. Unfortunately, products and services are generally designed only taking into account local influences. An approach that ties macroscale frameworks to localized product- or system-level design metrics is lacking. For example, the cost of upgrading the entire U.S. electrical system has been estimated to be on the order of $200 billion, and recent U.S. policy discussions in the area outline options such as “smart” grid upgrades, distributed and/or on-site renewable energy systems including solar and wind energy, infrastructural support for plug-in of electric and hybrid vehicles etc. But most existing electricity generation and thermal performance models of power generating stations or cogeneration plants fail to provide any indication of the environmental impacts associated with distributing electricity from generator to point-of-use. It is thus not intuitive how the direction of localized plant or system design should be altered given the different macro-level initiatives. This paper attempts to fill this gap by exploring a methodology that combines engineering economics, probabilistic risk assessment, and thermodynamic (2nd Law) analysis to evaluate different policy choices. Specifically, a framework that could allow quick estimation of the comparative consumption, operational power requirements, relative thermal performance and environmental footprint associated with different proposals on upgrading the grid is developed. The approach is demonstrated in the context of a representative segment of a hypothetical electrical grid distribution system located between two electric power generating stations (EPGS) facing overload as additional customer demands are projected to be integrated with renewable sources in the near-term future.

scholarly journals A probabilistic risk assessment for the vulnerability of the European carbon cycle to weather extremes: the ecosystem perspective

2015 ◽  
Vol 12 (6) ◽  
pp. 1813-1831 ◽  
Author(s):  
S. Rolinski ◽  
A. Rammig ◽  
A. Walz ◽  
W. von Bloh ◽  
M. van Oijen ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Time Series ◽  
Weather Conditions ◽  
Probabilistic Risk Assessment ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Data Set ◽  
Weather Events ◽  
Probabilistic Risk

Abstract. Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour. We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981–2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case. At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model-based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.

scholarly journals A probabilistic risk assessment for the vulnerability of the European carbon cycle to extreme events: the ecosystem perspective

2014 ◽  
Vol 11 (6) ◽  
pp. 10167-10202
Author(s):  
S. Rolinski ◽  
A. Rammig ◽  
A. Walz ◽  
K. Thonicke ◽  
W. von Bloh ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Time Series ◽  
Meteorological Condition ◽  
Terrestrial Ecosystems ◽  
Probabilistic Risk Assessment ◽  
Meteorological Conditions ◽  
Border Region ◽  
Index Value ◽  
Probabilistic Risk

Abstract. Extreme meteorological events are most likely to occur more often with climate change, leading to a further acceleration of climate change through potentially devastating effects on terrestrial ecosystems. But not all extreme meteorological events lead to extreme ecosystem response. Unlike most current studies, we therefore focus on pre-defined hazardous ecosystem behaviour and the identification of coinciding meteorological conditions, instead of expected ecosystem damage for a pre-defined meteorological event. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and meteorological conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are, thus, estimated on the basis of observed hazardous ecosystem behaviour. We first adapt this generic approach to extreme responses of terrestrial ecosystems to drought and high temperatures, with defining the hazard as a negative net biome productivity over a 12 months period. Further, we show an instructive application for two selected sites using data for 1981–2010; and then apply the method on pan-European scale addressing the 1981–2010 period and future projections for 2071–2100, both based on numerical modelling results (LPJmL for ecosystem behaviour; REMO-SRES A1B for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI index to describe the meteorological condition. They also provide examples for their interpretation in case of vulnerability to drought for Spain with the expected value of the SPEI being 0.4 lower for hazardous than for non-hazardous ecosystem behaviour, and of non-vulnerability for Northern Germany, where the expected drought index value for hazard observations relates to wetter conditions than for the non-hazard observations. The pan-European assessment shows that significant results could be obtained for large areas within Europe. For 2071–2100 they indicate a shift towards vulnerability to drought, mainly in the central and north-eastern parts of Europe, where negative net biome productivity was not used to be associated with drought. In Southern parts of Europe, considerable vulnerability and risk to drought have been identified already under current conditions; in future, the difference in SPEI between hazardous and non-hazardous ecosystem behaviour as well as the frequency of hazardous ecosystem behaviour will increase further. Vulnerability decreased only for the border region between Ukraine, Russia and Belarus, where a change in ecosystem types occurred with less vulnerable plant species in the future. These first model-based applications indicate the conceptional advantages of the proposed method by focusing on the identification of critical meteorological conditions for which we observe hazardous ecosystem behaviour in the analysed dataset. Application of the method to empirical time series would be an important next step to test the methods.

scholarly journals A Socio-Technical, Probabilistic Risk Assessment Model for Surgical Site Infections in Ambulatory Surgery Centers

2014 ◽  
Vol 35 (S3) ◽  
pp. S133-S141 ◽  
Author(s):  
Ebru K. Bish ◽  
Hadi El-Amine ◽  
Laura A. Steighner ◽  
Anthony D. Slonim
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Ambulatory Surgery ◽  
Surgical Site Infections ◽  
Probabilistic Risk Assessment ◽  
Assessment Model ◽  
Antibiotic Administration ◽  
Ambulatory Care Setting ◽  
Skin Preparation ◽  
Probabilistic Risk

Background.To understand how structural and process elements may affect the risk for surgical site infections (SSIs) in the ambulatory surgery center (ASC) environment, the researchers employed a tool known as socio-technical probabilistic risk assessment (ST-PRA). ST-PRA is particularly helpful for estimating risks in outcomes that are very rare, such as the risk of SSI in ASCs.Objective.Study objectives were to (1) identify the risk factors associated with SSIs resulting from procedures performed at ASCs and (2) design an intervention to mitigate the likelihood of SSIs for the most common risk factors that were identified by the ST-PRA for a particular surgical procedure.Methods.ST-PRA was used to study the SSI risk in the ASC setting. Both quantitative and qualitative data sources were utilized, and sensitivity analysis was performed to ensure the robustness of the results.Results.The event entitled “fail to protect the patient effectively” accounted for 51.9% of SSIs in the ambulatory care setting. Critical components of this event included several failure risk points related to skin preparation, antibiotic administration, staff training, proper response to glove punctures during surgery, and adherence to surgical preparation rules related to the wearing of jewelry, watches, and artificial nails. Assuming a 75% reduction in noncompliance on any combination of 2 of these 5 components, the risk for an SSI decreased from 0.0044 to between 0.0027 and 0.0035.Conclusion.An intervention that targeted the 5 major components of the major risk point was proposed, and its implications were discussed.

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