Case Study Of Risk Assessment Research Articles

Comprehensive groundwater risk assessment case study: arid northern Jordan agricultural areas

Comprehensive groundwater risk assessment case study: arid northern Jordan agricultural areas

Comprehensive groundwater risk assessment case study: arid northern Jordan agricultural areas

In the case of Jordan, the paper demonstrates that intensive land use in arid areas imposes tremendous pressure on groundwater. The comprehensive investigations of the contamination loads, the pote...

항공기 가스터빈 엔진 위험도 평가 사례 연구: 아크 바인딩에 의한 CT7 엔진 1단계 터빈 블레이드 피로 균열

항공기 가스터빈 엔진 위험도 평가 사례 연구: 아크 바인딩에 의한 CT7 엔진 1단계 터빈 블레이드 피로 균열

Chemical Impacts of Potential CO2 and Brine Leakage on Groundwater Quality with Quantitative Risk Assessment: A Case Study of the Farnsworth Unit

Potential leakage of reservoir fluids is considered a key risk factor for geologic CO2 sequestration (GCS), with concerns of their chemical impacts on the quality of overlying underground sources of drinking water (USDWs). Effective risk assessment provides useful information to guide GCS activities for protecting USDWs. In this study, we present a quantified risk assessment case study of an active commercial-scale CO2-enhanced oil recovery (CO2-EOR) and sequestration field, the Farnsworth Unit (FWU). Specific objectives of this study include: (1) to quantify potential risks of CO2 and brine leakage to the overlying USDW quality with response surface methodology (RSM); and (2) to identify water chemistry indicators for early detection criteria. Results suggest that trace metals (e.g., arsenic and selenium) are less likely to become a risk due to their adsorption onto clay minerals; no-impact thresholds based on site monitoring data could be a preferable reference for early groundwater quality evaluation; and pH is suggested as an indicator for early detection of a leakage. This study may provide quantitative insight for monitoring strategies on GCS sites to enhance the safety of long-term CO2 sequestration.

An interval type-2 fuzzy reasoning model for digital transformation project risk assessment

This study presents a new risk assessment model by combining interval type-2 fuzzy best-worst method (IT2F-BWM) and perceptual reasoning for risk evaluation of digital transformation projects. Digital transformations are technology-driven change processes that transform many businesses. Digital transformations are risky and difficult undertakings so that the decision-makers should be supported with appropriate risk assessment tools. The proposed model is a step towards this direction by providing decision-makers with a practical and applicable risk assessment tool that computes with words through a transparent and interpretable reasoning mechanism. In the proposed model, the relative importance of risk factors (RFs) is derived by using IT2F-BWM. Then, IT2F rule-based model is developed by considering risk factors along with the likelihood and severity of risks. The risk magnitudes of digital transformation projects are evaluated via perceptual reasoning. Both the input and output of the reasoning model are IT2F numbers, and the resulting risk magnitudes are decoded into words such as critical, major, and minor so as to ease interpretation. A real-life digital transformation risk assessment case study is conducted in order to demonstrate the applicability of the proposed model.

Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA

Occupational safety issues encountered in the worksite environment are the issues that companies should consider in improving their operations with a view to human health and environmental awareness. Many methods with different rationales have been existed in the literature to prioritize hazards according to their risk levels and to mitigate their consequences. In this study, a new model is developed for occupational risk assessment by merging two well-known multi-criteria decision-making methods named best and worst method (BWM) and multi attribute ideal real comparative analysis (MAIRCA) under fuzzy environment. The proposed model differentiates from other similar models by three aspects. First, it considers severity of a hazard and its associated risk from the human and environmental riskiness perspectives. Secondly, it applies fuzzy BWM (F-BWM) to calculate the relative importance of three risk factors named as “probability, frequency and severity” of traditional Fine–Kinney method. Thirdly, it applies fuzzy MAIRCA (F-MAIRCA) to rank hazards according to their risk level using importance values obtained by F-BWM. To show applicability of the approach, a case study of risk assessment in a marble factory is fulfilled. Additionally, a number of validation studies including benchmarking analysis with fuzzy VIKOR and fuzzy TOPSIS methods; a sensitivity analysis by varying importance weights of risk factors are carried out to highlight the solidity of the proposed approach.

A Next-Generation Risk Assessment Case Study for Coumarin in Cosmetic Products.

Next-Generation Risk Assessment is defined as an exposure-led, hypothesis-driven risk assessment approach that integrates new approach methodologies (NAMs) to assure safety without the use of animal testing. These principles were applied to a hypothetical safety assessment of 0.1% coumarin in face cream and body lotion. For the purpose of evaluating the use of NAMs, existing animal and human data on coumarin were excluded. Internal concentrations (plasma Cmax) were estimated using a physiologically based kinetic model for dermally applied coumarin. Systemic toxicity was assessed using a battery of in vitro NAMs to identify points of departure (PoDs) for a variety of biological effects such as receptor-mediated and immunomodulatory effects (Eurofins SafetyScreen44 and BioMap Diversity 8 Panel, respectively), and general bioactivity (ToxCast data, an in vitro cell stress panel and high-throughput transcriptomics). In addition, in silico alerts for genotoxicity were followed up with the ToxTracker tool. The PoDs from the in vitro assays were plotted against the calculated in vivo exposure to calculate a margin of safety with associated uncertainty. The predicted Cmax values for face cream and body lotion were lower than all PoDs with margin of safety higher than 100. Furthermore, coumarin was not genotoxic, did not bind to any of the 44 receptors tested and did not show any immunomodulatory effects at consumer-relevant exposures. In conclusion, this case study demonstrated the value of integrating exposure science, computational modeling and in vitro bioactivity data, to reach a safety decision without animal data.

A structured analysis of risk to important wildlife elements in three Australian Wildlife Conservancy sanctuaries

SummaryWhere data and information are lacking, structured expert risk assessments can provide a powerful tool to progress natural resource planning. In many situations, practitioners make informal assessments of risk within small groups that typically constitute employees. In this study, we report on three small (in terms of experts) structured expert‐based risk assessment case studies conducted by expert employees of a not‐for‐profit organisation (Australian Wildlife Conservancy) to demonstrate the utility of the approach. The case studies were carried out for three wildlife sanctuaries managed by AWC: Faure Island, Karakamia and Paruna. The likelihood that a set of direct risk factors would cause management failure for sets of important wildlife elements in the three sanctuaries was elicited from the small group of ecological experts. The analysis was couched in terms of a management aim to not lose species from each wildlife element over the management period of 25 years with current management. The experts believed, in particular, that increasing temperature and decreasing water availability associated with climate change were likely to impact significantly upon the vegetation elements and water‐reliant fauna associated with the sanctuaries. Some vegetation elements were also thought likely to be at risk of over‐grazing, unsuitable fire regimes and, in some cases, disease. In addition to predation by exotic predators at one sanctuary, the experts identified additional direct risk factors for various fauna elements associated with expected changes to the vegetation elements, including reduction in food availability, nesting habitat, and generally important life media. From the risk analyses, a preliminary conceptual model was developed to underpin monitoring and to indicate areas for possible management intervention and research. The case studies demonstrate that even in a small workplace team, structured risk assessments can be efficiently accomplished and can provide expedient and transparent information that effectively captures and aggregates the views of the experts.

Shelter-in-place risk assessment for high-pressure natural gas wells with hydrogen sulphide and its application in emergency management

This paper provides a risk assessment method of sheltering in-place for high-pressure natural gas wells with hydrogen sulphide. In this paper, the shelter-in-place risk is estimated by integrating the health consequences of an individual taking one kind of emergency response to the emergency orders of sheltering in place from the emergency decision makers and the probability of the corresponding emergency response action. The probability of the corresponding emergency response action in the proposed method is estimated through the accident probability analysis and the probability analysis of taking a certain response action. The health consequence estimation is based on air exchange rate test of the shelter buildings as well as accident consequence calculation. The evaluation of shelter-in-place risks based on “as low as reasonably practicable (ALARP)” guidelines was employed to provide suggestions for emergency management under both normal conditions and off normal conditions. A case study of risk assessment of sheltering in the local residential houses in Xuanhan County of Sichuan Province, China was taken as an example to illustrate the proposed risk assessment process of shelter-in-place and its application in the decision-making process for emergency management.

Evolving spiking neural networks methods for classification problem: a case study in flood events risk assessment

<p>Analysing environmental events such as predicting the risk of flood is considered as a challenging task due to the dynamic behaviour of the data. One way to correctly predict the risk of such events is by gathering as much of related historical data and analyse the correlation between the features which contribute to the event occurrences. Inspired by the brain working mechanism, the spiking neural networks have proven the capability of revealing a significant association between different variables spike behaviour during an event. Personalised modelling, on the other hand, allows a personal model to be created for a specific data model and experiment. Therefore, a personalised modelling method incorporating spiking neural network is used to create a personalised model for assessing a real-world flood case study in Kuala Krai, Kelantan based on historical data of 2012-2016 provided by Malaysian Meteorological Department. The result shows that the method produces the highest accuracy among the selected compared algorithms.</p>

A pulsed-dose study evaluating chronic toxicity of chlorothalonil to fish: A case study for environmental risk assessment.

Chlorothalonil is a fungicide which is highly toxic to aquatic organisms. However, in natural aquatic environments, it is very rapidly degraded, with a half‐life typically in hours, reducing exposure of aquatic organisms and the potential for effects. In standard regulatory studies looking at the chronic toxicity of chlorothalonil to fathead minnow, the most sensitive endpoint was fecundity. A standard fish full–life cycle study, where chlorothalonil concentrations were maintained constant throughout, resulted in a no‐observed‐effect concentration (NOEC) of 1.4 µg/L. Comparing peak modeled exposure concentrations to this NOEC can result in the chronic risk to fish being considered unacceptable. The present study investigated the effect on fecundity in fathead minnow using a fish short‐term reproduction assay. Five different exposure profiles were employed with time‐varying concentrations based on realistic worst‐case modeled environmental exposure profiles, multiplied by an assessment factor of 10, which resulted in maximum measured concentrations up to 15.5 µg/L. There were no effects on fecundity from any of the exposure profiles tested. Therefore, based on these more realistic exposure profiles, the chronic risk to fish could be considered acceptable if these exposures were deemed to be representative of the worst case. Environ Toxicol Chem 2019;38:1549–1559. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Site selection for floating offshore wind turbines in Japanese coasts by quantitative risk assessment

Floating offshore wind turbines (FOWTs) are now at the stage of demonstration experiments in Japan. They have a specific risk of “drift”, which is negligible for bottom-fixed offshore wind turbines. Taking account of the risk of drift, it is necessary to consider the spatial relations between a FOWT and surrounding sea-lanes, coastal facilities, and ecosystem, in addition to the profitability and stakes in fishing industry, when selecting an appropriate site for installing the FOWT. In this paper, the authors propose the method of site selection for installing a FOWT by quantitative risk assessment, taking account of the spatial relations between the FOWT and surrounding sea-lanes, coastal facilities and ecosystem. Based on the calculation results in the case study of the quantitative risk assessment, the following procedure is recommended: first, extract the area where the risks related to the sea-lane are small enough, and second, select the position within the extracted area with the smallest risk of collision with coastal facilities or ecosystem in case of drift of the FOWT by quantitative evaluation of the risk distribution under the environmental conditions in the area. The proposed procedure is commonly applicable in most areas of Japanese coast.

RM/RA CRAMM as the new quantitative method for risk management

Purpose – The aim of this paper is to introduce new risk management method based on quantitative approach. RM/RA CRAMM was designed by Slovak researchers as user-friendly method for Public institutions dealing with risk management, crisis planning, civil protection. It has a multipurpose use. Design/methodology/approach – Three-phase procedure is introduced, including risk identification, analysis and evaluation. The case-study of risk assessment as an example of the application is included. Findings – Quantitative methods in risk management are rare due to the complex of factors influencing the risks being assessed. Research limitations/implications – A complex Area/Location risk assessment needs number of exact values and estimations for proper risk identification. Team-work is very welcomed but not necessary. Practical implications – Practical value of the method is incredible due to its applicability on the wide range of the research fields related to the risk management. Originality/Value – The method introduced is an original product of Slovak team of researchers led by author of this paper. Keywords: RM/RA CRAMM, risk management, risk assessment, quantitative, single equation method, case study. Research type: case study. JEL classification: C20 – General.

The Safety Risk Event Avoidance Capability (SAREAC) Indicator

Current practice regarding risk assessment contemplates the severity and likelihood of risks and employs the use of matrices where these factors are classified and cross-referenced to evaluate risk levels. Depending on the adequacy and reliability of data, the likelihood is estimated with quantitative or qualitative methods; severity is estimated according to experience from past events. This standard technique for assessing risks has been negatively criticised regarding validity and reliability due to effects of cognitive biases and a deterministic view of the possible consequences of risks. Even more, because of the lack of standardisation in risk matrices, a benchmarking across systems and organisations is not feasible. Taking into account the limitations mentioned, as well as the fact that the classification of hazards/causal factors, risk event(s) and consequences always depend on the analyst's view, this study proposes the Safety Risk Avoidance Capability (SAREAC) metric for a defined system. This metric focus on the prevention of risk events and combines quantitative and qualitative parameters referred in the literature but not yet exploited. SAREAC consists of two parts: the influence of hazards and the remaining effects of hazards after implementing or designing controls. Each of the SAREAC parts is calculated through specific steps which they result in a normalized score that allows more reliable comparisons amongst systems or over time. Data from a published risk assessment case study were used to demonstrate the use of SAREAC.

Using multi-criteria risk ranking methodology to select case studies for a generic risk assessment framework for exotic disease incursion and spread through Europe

We present a novel approach of using the multi-criteria pathogen prioritisation methodology as a basis for selecting the most appropriate case studies for a generic risk assessment framework. The approach uses selective criteria to rank exotic animal health pathogens according to the likelihood of introduction and the impact of an outbreak if it occurred in the European Union (EU). Pathogens were evaluated based on their impact on production at the EU level and international trade. A subsequent analysis included criteria of relevance to quantitative risk assessment case study selection, such as the availability of data for parameterisation, the need for further research and the desire for the case studies to cover different routes of transmission. The framework demonstrated is flexible with the ability to adjust both the criteria and their weightings to the user’s requirements. A web based tool has been developed using the RStudio shiny apps software, to facilitate this.

Microplastics in freshwater river sediments in Shanghai, China: A case study of risk assessment in mega-cities.

Microplastics, which are plastic debris with a particle diameter of less than 5mm, have attracted growing attention in recent years. Its widespread distributions in a variety of habitats have urged scientists to understand deeper regarding their potential impact on the marine living resources. Most studies on microplastics hitherto are focused on the marine environment, and research on risk assessment methodology is still limited. To understand the distribution of microplastics in urban rivers, this study investigated river sediments in Shanghai, the largest urban area in China. Seven sites were sampled to ensure maximum coverage of the city's central districts, and a tidal flat was also included to compare with river samples. Density separation, microscopic inspection and μ-FT-IR analysis were conducted to analyze the characteristics of microplastics and the type of polymers. The average abundance of microplastics in six river sediment samples was 802 items per kilogram of dry weight. The abundance in rivers was one to two orders of magnitude higher than in the tidal flat. White microplastic spheres were most commonly distributed in river sediments. Seven types of microplastics were identified, of which polypropylene was the most prevailing polymers presented. The study then conducted risk assessment of microplastics in sediments based on the observed results, and proposed a framework of environmental risk assessment. After reviewing waste disposal related legislation and regulations in China, this study conclude that in situ data and legitimate estimations should be incorporated as part of the practice when developing environmental policies aiming to tackle microplastic pollution.

Developing a framework for dynamic risk assessment using Bayesian networks and reliability data

Process Safety in the oil and gas industry is managed through a robust Process Safety Management (PSM) system that involves the assessment of the risks associated with a facility in all steps of its life cycle. Risk levels tend to fluctuate throughout the life cycle of many processes due to several time varying risk factors (performances of the safety barriers, equipment conditions, staff competence, incidents history, etc.). While current practices for quantitative risk assessments (e.g. Bow-tie analysis (BT), Layer of protection analysis (LOPA) etc.) have brought significant improvements in the management of major hazards, they are static in nature and do not fully take into account the dynamic nature of risk and how it improves risk-based decision making.In an attempt to continually enhance the risk management in process facilities, the oil and gas industry has put in very significant efforts over the last decade toward the development of process safety key performance indicators (KPI or parameters to be observed) to continuously measure or gauge the efficiency of safety management systems and reduce the risks of major incidents. This has increased the sources of information that are used to assess risks in real-time. The use of such KPIs has proved to be a major step forward in the improvement of process safety in major hazards facilities. Looking toward the future, there appears to be an opportunity to use the multiple KPIs measured at a process plant to assess the quantitative measure of risk levels at the facility on a time-variant basis.ExxonMobil Research Qatar (EMRQ) has partnered with the Mary Kay O'Connor Process Safety Center – Qatar (MKOPSC-Q) to develop a tool that monitors, in real time, the potential increases in risk levels as a result of pre-identified risk factors and process safety related data, using Bayesian Belief Networks (BN). The development of the tool involved two phases: 1) Development of a methodology that establishes the framework for the tool and 2) Development of the tool itself with the use of JAVA programming language. The overall tool is to be called PULSE, which stands for Process Unit Life Safety Evaluation.In this context, the paper presents a case study of the quantitative risk assessment of a process unit using BN. The different steps of the development of the BN are detailed, including: translation of a Bowtie into a skeletal BN, modification of the skeletal BN to incorporate reliability data, and insertion of equipment failure evidence into the BN for dynamic modeling. In addition, an overview of PULSE is presented. The outcomes of the dynamic modeling of the BN with real time insertion of evidence are discussed and recommendation for the framework for a dynamic risk assessment tool are made.

Quantifying pathogen risks associated with potable reuse: A risk assessment case study for Cryptosporidium

This study evaluated the reliability and equivalency of three different potable reuse paradigms: (1) surface water augmentation via de facto reuse with conventional wastewater treatment; (2) surface water augmentation via planned indirect potable reuse (IPR) with ultrafiltration, pre-ozone, biological activated carbon (BAC), and post-ozone; and (3) direct potable reuse (DPR) with ultrafiltration, ozone, BAC, and UV disinfection. A quantitative microbial risk assessment (QMRA) was performed to (1) quantify the risk of infection from Cryptosporidium oocysts; (2) compare the risks associated with different potable reuse systems under optimal and sub-optimal conditions; and (3) identify critical model/operational parameters based on sensitivity analyses. The annual risks of infection associated with the de facto and planned IPR systems were generally consistent with those of conventional drinking water systems [mean of (9.4 ± 0.3) × 10−5 to (4.5 ± 0.1) × 10−4], while DPR was clearly superior [mean of (6.1 ± 67) × 10−9 during sub-optimal operation]. Because the advanced treatment train in the planned IPR system was highly effective in reducing Cryptosporidium concentrations, the associated risks were generally dominated by the pathogen loading already present in the surface water. As a result, risks generally decreased with higher recycled water contributions (RWCs). Advanced treatment failures were generally inconsequential either due to the robustness of the advanced treatment train (i.e., DPR) or resiliency provided by the environmental buffer (i.e., planned IPR). Storage time in the environmental buffer was important for the de facto reuse system, and the model indicated a critical storage time of approximately 105 days. Storage times shorter than the critical value resulted in significant increases in risk. The conclusions from this study can be used to inform regulatory decision making and aid in the development of design or operational criteria for IPR and DPR systems.

RFID Technology for Deepwater Drilling and Completions Challenges

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 181012, “Leveraging RFID Technology for Deepwater Drilling and Completions Challenges,” by Euan Murdoch, SPE, Eddie Valverde, SPE, Rupa Sharma, Crystal Wreden, SPE, Alex Goodwin, and Jonathan Osei-Kuffour, Weatherford, and Kyle Kimmitt, Cornelis Loonstra, Babak Ghaempanah, and Deandre Reagins, Shell, prepared for the 2016 SPE Intelligent Energy International Conference and Exhibition, Aberdeen, 6–8 September. The paper has not been peer reviewed. Deepwater operators continually face technical and environmental challenges to drilling and completing wells safely and efficiently. To address these challenges, the industry has used radio-frequency-identification (RFID) technology to reduce risk, rig time, and nonproductive time and to perform operations that traditional tools cannot. This paper describes criteria for selecting RFID-enabled tools rather than traditional tools, integration of RFID tools with operations, and value-added features enabled by RFID. The complete paper also presents contingency, safety, and risk-assessment factors and case studies. RFID Background RFID is a method of communication using radio-frequency electromagnetic fields. Information is stored within RFID tags and is transferred to a reader when the two are close to each other. There are two types of tags: active tags, which contain their own energy source, and passive tags, which are energized by the reader as they pass by. A typical passive tag used in the tools described in this paper is shown in Fig. 1. This tag contains a transponder circuit and an antenna that receives signals from the reader. The transponder is programmed with a unique identification number and instructions for the reader. The reader contains a receiving antenna and a power source (Fig. 2) that generates an electromagnetic field. The field generated by the antenna powers the tag when it is within range and enables the tag to transmit the stored instructions. Because a passive RFID tag is powered by the reader antenna, it does not require batteries or an internal energy source, which makes the passive tags less costly and smaller than active tags. Receiving antennas can be programmed to respond only to specific tag identification numbers, and any tag passing by the receiver without these numbers will be ignored. Transferring RFID Technology to Deep Water RFID technology has been integrated into drilling and completions applications. One application of RFID technology is for drilling automation and drillpipe identification. RFID tags attached to drillpipe identify individual-joint dimensions, track inspection information, and allow inventory tracking. These tags can be used also to create an automatic pipe tally as drillpipe joints are run in hole past a reader located below the rotary. RFID technology has moved also into cementing. RFID-activated port collars have been designed recently for use in a drilling-with-liner application in the North Sea to cement a 9⅝-in. liner and eliminate the need to open the ports mechanically by means of a long inner string.

Aquarium molluscs as a case study in risk assessment of incidental freshwater fauna

Because biological invasions may cause loss of biodiversity, accurate predictions are necessary for implementing effective restrictions aimed at specific high-risk taxa. The majority of freshwater macroinvertebrate invaders are molluscs and crustaceans. The pet trade has been considered one of the main pathways for new introductions of such species. Risk assessment is usually focused on traded ornamental species whereas, despite their potential importance, incidental “hitchhiking” molluscs are usually given only minimal consideration. We surveyed the Czech Republic, which is one of the leading markets for aquarium species in the European Union (EU), and found 41 freshwater mollusc species (25 ornamental gastropods, 6 ornamental clams, and 10 “hitchhiking” gastropods) representing 13 families. We extrapolated data from the Czech Republic and, using Climatch v. 1.0, matched the climate in each species’ native range to the entire territory of the EU. We also assessed the risk associated with each species by FI-ISK. “Hitchhiking” gastropods were found to be significantly more hazardous and with higher potential to become established within the EU than were ornamental gastropods and bivalves. Many “hitchhikers” may be easily overlooked due to their small size and cryptic coloration or shape. Thus, they easily can be accidentally imported in association with aquarium plants. Therefore, we recommend here to disinfect imported ornamental plants to eradicate these unwanted faunal assemblages.