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The surface-mining worker fatalities are unacceptably high as compared to other private industries in United States such as construction, manufacturing, agriculture, forestry, fishing and hunting. Although many studies about generating a safe work environment and developing safety training through intervention modules have tried to reduce the number of worker fatalities by utilizing an administrative approach to the development of safety controls, a rigorous study about understanding craftworkers' perceptions of a safe work environment is lacking. This study particularly investigated quarry workers' safety behaviors regarding work hazards by adapting findings from construction safety research because construction and mining industries have similarities in work hazards and environment. Despite their similarities, the work fatality rate in the mining industry is greater than in the construction industry (BLS, 2018). To gain a greater understanding of how quarry workers identify and interpret work hazards and employ strategies to prevent accidents, this study explored quarry workers' perceptions of work hazards (i.e., hazard identification, severity interpretation) and their preventive strategies to develop a safer working environment at the workplace. To accomplish this, a single descriptive case study was conducted with multiple sources of data such as interviews with photo elicitation, field notes, site photographs, and precursory meeting with safety managers. These sources of data were used to investigate quarry workers' identification and interpretation skills and utilization of preventive strategies. This study will contribute to improve safety of workers by incorporating workers' perceptions of work hazards and by exploring their experience to the development of safety training. / Master of Science / The surface-mining industry is one of the private industries with a high fatality rate in the United States. To reduce the number of accidents and help workers to perform safely in the workplace, previous studies have investigated different strategies to promote workers’ safety performance. These strategies include safety interventions such as safety training and safety inspections. However, a lack of study exists to understand workers’ behaviors and perceptions regarding safety and work hazards. To better explore workers’ behaviors and perceptions, this study adapted findings from construction safety research. Because the number of surface-mining safety research is relatively small and the work environment and types of work hazards in both the surface-mining and construction industries share similarities, the findings in construction safety research can be used to promote a safer workplace for surface-mine workers. By adapting findings in construction safety research, this study further investigated workers’ perceptions of work hazards, which is operationalized in two approaches: hazard identification and severity interpretation. This study also examines workers’ execution of strategies to prevent accidents. These observations were gathered through the utilization of a case study of quarry, which gave a guideline to the researcher to collect data from multiple sources (e.g., precursory meeting with safety managers, field notes, photographs, interviews) and analyze the findings by primarily using participants’ responses in the interviews with photo elicitation. This study will contribute to improve a safer workplace in the surface mining industry by incorporating workers’ perceptions and experience and by emphasizing workers’ involvement in tandem with company commitment to develop safety training.

Hazards and risks are currently identified in generic risk silos using top-down tools and methods which are incorporated into whole system risk management frameworks such as enterprise risk management. The current methods of identification and documentation are linear in approach and presentation. However, the world is multi-dimensional requiring a method of identification which responds to complex non-linear relationships. A method is required to identify cross- disciplinary hazards and formulate a register method to evidence the identified hazards. This study uses expert elicitation, web, survey and case studies to develop a method for cross-disciplinary hazard identification by application of the dimensions of generic, interface, causation and accumulation. The results of the study found many of the tools and methods used for hazard and risk identification such as hazard and operability studies took a top down approach commencing with a known failure and establishing cause and effect. The starting position of a known failure or event precludes identification of new types of failure or events and perpetuates a linear approach to hazard identification. Additionally the linear design of a risk register does not facilitate the presentation of multidimensional hazards. The current methods do not accommodate multiple lifecycles and components within cross discipline relationships. The method was applied to three case studies. The first case study had an existing risk register of 50 risks, post method application an additional 531 hazards were identified; case study (2) a register of 49 hazards and post method application additional hazards of 261; case study (3) an initial register of 45 hazards and an additional 384 hazards after method application. The impact of the method application highlights inconsistencies in the initial risk register and provides a tool which will aid the identification understanding and communication of hazards. Additionally it documents previously unidentified cross-disciplinary hazards and provides a proactive register method for identification and documentation by application of the dimensions of interface, causation and accumulation.

A common characteristic of all chemical allergens, both respiratory and skin allergens, is the ability to form stable associations with proteins; the resulting hapten-protein complex being sufficient to provoke an immune response. There is evidence to suggest that selective binding of chemicals with proteins or peptides may impact on the quality of immune response that will develop. In the investigations described here, we have taken a reductionist approach to protein reactivity and evaluated the binding characteristics of 20 of the most commonly reported chemical respiratory allergens towards defined peptides with a single reactive amino acid of interest. The hypothesis is that it is possible to identify and characterize different forms of chemical allergens as a function of preferential peptide binding.Utilizing the standardized reaction conditions of a direct peptide reactivity assay (DPRA), the reactivity of respiratory allergens for cysteine and lysine peptides was evaluated. Activity in the DPRA is reported as the percent depletion of peptide following 24 h incubation. An important and intriguing observation was that, when compared with skin sensitizers, chemical respiratory allergens exhibited a preferential reactivity for lysine. This preference was characterized quantitatively as a ratio of the mean depletion of lysine compared with cysteine (Lys:Cys ratio). The Lys:Cys ratio was observed to be robust and reproducible over time.A limitation of many in chemico methods for hazard identification is the lack of a metabolic component that allows for the identification of pro-haptens. In order to address this limitation, reported here is the use of the peroxidase peptide reactivity assay (PPRA), which utilizes a horseradish peroxidase/hydrogen peroxide (HRP/P) enzymatic system as a proxy for oxidative metabolism. Additionally, reactivity in the PPRA is characterized after a 24 h reaction time utilizing a concentration-response model (thus, permitting consideration of dose-response relationships defined as an EC15 value). Unexpectedly, the preferences for lysine observed with chemical respiratory allergens in the DPRA were lost or blunted in PPRA. The EC15 values demonstrated that relative reactivity between chemical respiratory allergens varied by up to 4 orders of magnitude. The identification of quantitative differences in reactivity could prove useful as a guide to evaluate potency in the future, should reliable metrics become available.To characterize the selectivity of binding by chemical respiratory allergens, the DPRA was modified to allow for the evaluation of reactivity to histidine, tyrosine and arginine. Confirming our previous observations, each of the respiratory sensitizers was observed to react to both lysine and cysteine, with in most instances, a preference for the former. Reactive promiscuity was a function of the other peptides with histidine being the most reactive followed by arginine and tyrosine. To model more complex reactive conditions, a novel modification was made to the DPRA to allow competition for lysine and cysteine to be assessed in a single reaction mixture. The results of these competitive reactivity experiments identified a range of binding patterns to lysine and cysteine that in some cases resulted in different binding being expressed.At present, there are no methods available to reliably identify potential chemical respiratory allergens. The work presented here has demonstrated that respiratory allergens can be identified as potential sensitizers based on their ability to react with lysine and cysteine. More importantly, the balance of reactivity to these two peptides can provide a means of discriminating between respiratory and skin sensitizers.

Autonomous Unmanned Aerial Vehicles (UAVs) in agriculture are increasingly in demand to reduce cost, labour and increase effectiveness and quality in farming. However, it is necessary to improve reliability for this technology to perform its full potential without harming humans, animals or the environment. The reliability increases by identifying the hazards and mitigating them. Therefore the risks are identified, analyzed and mitigated using analysis tools. Two different methods are used to analyze and reduce hazards, and each method utilizes various analysis tools. In addition, redundancy and preventive action are proposed to eliminate or minimize the danger. This thesis identifies risks by studying and reviewing a generic use-case from the AFarCloud project and compares the two hazard analysis methods to determine which method provides the most reliable result.

<p>The U.S. construction sector ranks second in fatal occupational injuries in 2021 among other sectors. Although many research efforts have been conducted for decades to improve safety at construction jobsites, fatal occupational injuries did not reduce to the desired level. Specifically, previous studies argued that still more than 70% of hazards often remained unrecognized by construction workers even after receiving safety training. In addition to the enforced safety regulations, the Organizational Safety and Health Administrator (OSHA) has mandated safety training for construction workers to train them regarding potential hazards and risks at jobsites while mainly focusing on a general overview of the hazards and preventive measures.</p> <p>However, in the last decade, it was extensively argued that workers’ low performance in hazard identification may not only be related to their hazard knowledge and more related to the cognitive processing of information to identify and perceive the cues in a construction environment to remain situationally aware (i.e., cognitive failures). Therefore, there is a critical need to identify a new approach for customizing training construction workers to address the lack of knowledge and cognitive failures that workers may experience. Thus, this thesis aimed to develop multi-modal personalized safety training to reduce human errors and construction workers' unsafe behaviors by improving their hazard identification abilities.</p> <p>To do so, workers’ hazard identification skills were assessed through subjective and objective non-invasive psychophysiological metrics (e.g., visual attention, emotional responses) in an immersive 360° virtual environment and customized training for them. The effectiveness of the developed personalized training was tested and validated, and the findings indicate considerable improvements in subjects’ hazard identification performance after receiving this customized training.</p> <p>This thesis contributed to the body of knowledge and practice by proposing an advanced personalized safety training framework that automatically translates workers' subjective test results and objective psychophysiological responses into customized training recommendations. The outcomes lay the necessary foundations for building tailored training regimens to improve construction worker safety using comprehensive cognitive analysis and effective intervention strategies. The developed personalized safety training will not only improve workers' hazard identification performance but will also save construction companies time delays and cost overruns by eliminating the need for a repetitive retraining of the workforce.</p>

Incineration of waste is increasing in the EU. However, in the incineration process, both fly and bottom ash materials are generated as waste that requires further action. A common goal throughout Europe is to find ways to utilize ash materials in an environmentally and economically efficient manner in accordance with the current legislation. This legislation is the Waste Framework Directive (WFD) which lists essential properties (H-criteria) to classify waste, as hazardous or not. Of these criteria, ecotoxicity (H-14) should be classified based on the wastes’ inherent hazardous properties. The WFD further states that this classification should be based on the Community legislation on chemicals (the CLP Regulation). Today, there are no harmonized quantitative criteria for the H-14 classification in the WFD, but there is a proposal from the EU on a computing model that summarizes all the measured elements classified as ecotoxic in the solid material. However, there may be a poor relationship between the theoretical ecotoxicity, based on analysed individual elements, and their actual contribution to the measured total toxicity. Therefore, to reduce the risk of incorrectly assessing the hazard potential, the overall aim of this doctoral Thesis was to develop a scientifically well-founded basis for the choice of leaching methodology and ecotoxicity testing for the H-14 classification of ash materials in Europe. In Paper I, different ash materials were classified, two leaching methods were compared and the sensitivity as well as the usefulness of a selected number of aquatic ecotoxicity tests were evaluated. Paper III and IV studied different leaching conditions, relevant for both hazard classification and risk evaluation of ash. Moreover, all four papers investigated potentially causative ecotoxic elements in the ash leachates. The results from this Thesis show that elements not classified as ecotoxic in the chemical legislation have a significant influence on the overall toxicity of the complex ash materials and will be considered if using the approach with ecotoxicity tests on ash leachates, but not if using the computing model. In addition, the approach of comparing chemically analysed elements in the solid ash with literature toxicity data for the same elements systematically over-estimates the hazard potential. This emphasizes the importance of using leaching tests in combination with ecotoxicity tests for the ecotoxicity classification of ash materials, at least if the aim is to fully understand the inherent hazard potential of the ash. To conclude, the recommendation for H-14 classification of ash is that leachates should be prepared using the leaching test and conditions evaluated in Paper III and that the generated leachates should be tested in a battery of test organisms representing a wide range of biological variation and different routes of exposure. This classification proposal has support in the CLP Regulation and contributes to harmonizing the waste and chemical legislation. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.</p>

This thesis investigates the proposition that use must be made of quantitative information to control the reporting of hazard scenarios in automatically generated HAZOP reports. HAZOP is a successful and widely accepted technique for identification of process hazards. However, it requires an expensive commitment of time and personnel near the end of a project. Use of a HAZOP emulation tool before conventional HAZOP could speed up the examination of routine hazards, or identify deficiencies I in the design of a plant. Qualitative models of process equipment can efficiently model fault propagation in chemical plants. However, purely qualitative models lack the representational power to model many constraints in real plants, resulting in indiscriminate reporting of failure scenarios. In the AutoHAZID computer program, qualitative reasoning is used to emulate HAZOP. Signed-directed graph (SDG) models of equipment are used to build a graph model of the plant. This graph is searched to find links between faults and consequences, which are reported as hazardous scenarios associated with process variable deviations. However, factors not represented in the SDG, such as the fluids in the plant, often affect the feasibility of scenarios. Support for the qualitative model system, in the form of quantitative judgements to assess the feasibility of certain hazards, was investigated and is reported here. This thesis also describes the novel "Fluid Modelling System" (FMS) which now provides this quantitative support mechanism in AutoHAZID. The FMS allows the attachment of conditions to SDG arcs. Fault paths are validated by testing the conditions along their arcs. Infeasible scenarios are removed. In the FMS, numerical limits on process variable deviations have been used to assess the sufficiency of a given fault to cause any linked consequence. In a number of case studies, use of the FMS in AutoHAZID has improved the focus of the automatically generated HAZOP results. This thesis describes qualitative model-based methods for identifying process hazards by computer, in particular AutoHAZID. It identifies a range of problems where the purely qualitative approach is inadequate and demonstrates how such problems can be tackled by selective use of quantitative information about the plant or the fluids in it. The conclusion is that quantitative knowledge is' required to support the qualitative reasoning in hazard identification by computer.

This master`s thesis deals with a hazard analysis of selected machinery according to an actual legislative documents in Slovakia, which were taken over from Europien Union directives. The thesis is focused on exploring legislation related to the safety of toolroom workshop in the Czech Republic and Germany. Because of that was done the recherché of harmonized standards in these countries. Subsequently is made the identification of hazards under recherched standards and assessment of control system based on the performance level of the system. In the end are all obtained data evaluated and the precautionary measures are suggested. With taking care of economic factors are finally proposed the possibilities of the elimination of risks.

The Priority Risk Index is increasingly used as a methodology for quantifying jurisdictional risk for hazard mitigation planning purposes, and it can evolve to meet specific community needs. The index incorporates probability, impact, spatial extent, warning time, and duration when assessing each hazard, but it does not explicitly integrate a vulnerability and consequence analysis into its final scoring. To address this gap, a new index was developed- the Enhanced Priority Risk Index (EPRI). The new index adds a sixth category, vulnerability, calculated from a vulnerability and consequence analysis of the impacts on seven sectors identified in Standard 4.1.2 of the Emergency Management Accreditation Program (EMAP). To obtain a vulnerability score, impacts are ranked by sector from low (1) to very high (4), then a weighting factor is applied to each sector. The vulnerability score is added to the EPRI and provides risk levels based on the number of exploitable weaknesses and countermeasures identified within a specific jurisdiction. The vulnerability score and resulting EPRI are scalable and can be applied across jurisdictions, providing a transferable methodology that improves the hazard identification and risk assessment process and provides an approach for meeting EMAP accreditation standards.