Identification Of Potential Hazards Research Articles

Structure plane interpretation of rockfall and early identification of potential hazards based on UAV photogrammetry

Structure plane interpretation of rockfall and early identification of potential hazards based on UAV photogrammetry

Identification of Potential Hazards in Hazardous Waste Disposal Using Job Safety Analysis (JSA) At Infineon Technologies Batam

Infineon is a manufacturing company that in the production process produces a lot of hazardous waste. This study aims to identify potential hazards and risks using the Job Safety Analysis (JSA) method that exist in each work sequence, as well as determine risk criteria, provide risk assessment and risk control. The stages of data processing start from sequencing work steps, identifying hazards and risks, assessing the risk of potential hazards and determining proposals for controlling potential hazards. The results of this study found that the potential hazards that can cause injuries and work accidents in hazardous waste management are mostly related to chemical spillage and manual handling. There are 10 jobs that have a risk value of 6 and 2 jobs that have a risk value of 4. Improving work safety can be done by educating especially to waste operators and equipping PPE cabinets so that they are easily accessible.

Identification of Potential Hazards in Occupational Safety and Health Among Rice Milling Workers at UD. Lestari

Occupational health and safety (OHS) is crucial for safeguarding workers' well-being and preventing workplace accidents and diseases. This study explores OHS hazards at UD Lestari, an informal sector rice milling operation in Semarang City, Indonesia. The research employed a descriptive qualitative approach, conducting interviews, observation, and measurements from April to May 2024. The aim of this study was to identify various OHS hazards present in UD. Lestari's rice milling operations. This research found that all respondents experienced respiratory problems (100%) and 3 people (50%) experienced hearing problems, attributed to inadequate use of Personal Protective Equipment (PPE) and smoking habits. Dust levels inside the production area exceeded permissible limits (8.04 mg/m3), posing risks of respiratory diseases. Similarly, noise levels surpassed recommended thresholds (93.26 dB), increasing the likelihood of hearing loss. This study contributes valuable insights into enhancing workplace safety and underscores the importance of ongoing efforts to safeguard worker health in informal sector industries. Future research should explore additional factors influencing OHS outcomes to further enhance workplace safety practices and employee well-being.

Hazard Identification and Safety Education on The Clothing Convection Industry Business in Semarang

The clothing convection industry is one of the most popular businesses, with many growing businesses in Indonesia. In this industry, there are potential hazards that may occur either from work environment factors, the use of tools or machines, or from workers. Research objective to be achieved is to identify potential hazards in the clothing convection industry X and Y. This research used descriptive research, and the sample was two workers at the clothing convection industry X and four workers at the clothing convection industry Y for the data. The sample selection used random sampling. The data analysis technique used a narrative analysis. To minimize the number of work accidents or prevent accidents in the workplace, the identification of potential hazards is carried out through hazard analysis methods; one method is HAZOPS (Hazard Operability Studies). Based on the results of identification from workers and observation using HAZOPS method to minimize potential danger that can occur in each production with safety education using video to convey information easily for workers. Education on the use of PPE is also provided so that workers have safety knowledge and awareness at work. X and Y convection have various potential dangers in the clothing convection industry. Therefore, immediate action and attention from management are needed to minimize work accidents.

Study on Early Identification of Rainfall-Induced Accumulation Landslide Hazards in the Three Gorges Reservoir Area

The early identification of potential hazards is crucial for landslide early warning and prevention and is a key focus and challenging issue in landslide disaster research. The challenges of traditional investigation and identification methods include identifying potential hazards of landslides triggered by heavy rainfall and mapping areas susceptible to landslides based on rainfall conditions. This article focuses on the problem of early identification of rainfall-induced accumulation landslide hazards and an early identification method is proposed, which is “first identifying the accumulation that is prone to landslides and then determining the associated rainfall conditions”. This method is based on identifying the distribution and thickness of accumulation, analyzing the rainfall conditions that trigger landslides with varying characteristics, and establishing rainfall thresholds for landslides with different accumulation characteristics, ultimately aiming to achieve early identification of accumulation landslide hazards. In this study, we focus on the Zigui section of the Three Gorges Reservoir as study the area, and eight main factors that influence the distribution and thickness of accumulation are extracted from multi-source data, then the relative thickness information extraction model of accumulation is established by using the BP neural network method. The accumulation distribution and relative thickness map of the study area are generated, and the study area is divided into rocky area (less than 1 m), thin (1 to 5 m), medium (5 to 10 m), and thick area (thicker than 10 m) according to accumulation thickness. Rainfall is a significant trigger for landslide hazards. It increases the weight of the sliding mass and decreases the shear strength of soil and rock layers, thus contributing to landslide events. Data on 101 rainfall-induced accumulation landslides in the Three Gorges Reservoir area and rainfall data for the 10 days prior to each landslide event were collected. The critical rainfall thresholds corresponding to a 90% probability of landslide occurrence with different characteristics were determined using the I-D threshold curve method. Prediction maps of accumulation landslide hazards under various rainfall conditions were generated by analyzing the rainfall threshold for landslides in the Three Gorges Reservoir area, serving as a basis for early identification of rainfall-induced accumulation landslides in the region. The research provides a method for the early identification of landslides caused by heavy rainfall, delineating landslide hazards under different rainfall conditions, and providing a basis for scientific responses, work arrangements, and disaster prevention and mitigation of landslides caused by heavy rainfall.

INTEGRATING ADVANCED TECHNOLOGIES FOR ENHANCED HSE MANAGEMENT IN THE FMCG SECTOR

The Fast-Moving Consumer Goods (FMCG) sector operates in a dynamic environment, facing numerous challenges in maintaining Health, Safety, and Environment (HSE) standards while meeting the demands of a rapidly evolving market. To address these challenges, integrating advanced technologies has emerged as a strategic approach for enhancing HSE management practices within the FMCG sector. This review explores the integration of various advanced technologies and their impact on improving HSE management in the FMCG industry. The utilization of technologies such as Internet of Things (IoT), Artificial Intelligence (AI), and Big Data Analytics has revolutionized HSE management practices in the FMCG sector. IoT sensors embedded in production machinery and equipment enable real-time monitoring of environmental conditions, equipment performance, and worker safety. AI-driven predictive analytics algorithms analyze vast amounts of data to identify potential safety hazards, predict equipment failures, and optimize HSE protocols. Furthermore, the adoption of wearable devices equipped with biometric sensors provides continuous health monitoring for employees, ensuring early detection of fatigue, stress, or other health-related issues. Virtual Reality (VR) and Augmented Reality (AR) technologies are utilized for immersive HSE training simulations, enabling employees to practice safety procedures in realistic virtual environments, thus enhancing their preparedness for real-life scenarios. Moreover, the integration of drone technology facilitates remote monitoring of vast operational areas, enabling quick identification of potential hazards and swift response to emergencies. Additionally, blockchain technology ensures the transparency and traceability of HSE data across the supply chain, enhancing accountability and compliance with regulatory standards. The integration of advanced technologies holds significant promise for enhancing HSE management practices in the FMCG sector, fostering a safer and more sustainable operational environment while addressing the evolving challenges of the industry.
 Keywords: HSE, Management, FMCG, Technologies, Technology, Review, Innovation.

Hazard Identification and Risk Assessment for Dismantling of Phosphoric Acid Tank Using 100-Ton Crane & Scaffolding in a Chemical Industry

The dismantling of industrial equipment or machinery, especially within the chemical sector, poses unique challenges that require an in-depth assessment of potential hazards and risks. This study provides a comprehensive analysis of the Hazard Identification and Risk Assessment (HIRA) conducted for the dismantling procedure of a phosphoric acid tank in a chemical industry setting, using a 100-ton crane and scaffolding. The (Hazard Identification and Risk Assessment) HIRA approach involves an extensive evaluation of various aspects involving the systematic identification of potential hazards, followed by a detailed evaluation of the risk involved. The risk assessment will be performed using quantitative methodology to estimate the likelihood and severity of identified hazards. Subsequently, potential mitigation methods are put forth to deal with the risks that have been identified with regard to each specific hazard. Key hazards in this activity include mechanical failures, environmental issues, human errors, and exposure to chemicals. The findings of this study contribute valuable insights to the field of industrial safety, by providing a framework for conducting Hazard Identification and Risk Assessment (HIRA), particularly adapted to the dismantling of chemical storage tanks using heavy machinery and scaffolding. This study aims to enhance the overall safety culture in the chemical industry by promoting proactive risk management during complex dismantling activities. Keywords: Hazard, Risk, Hazard identification, Risk assessment, Phosphoric Acid Tank dismantling.

POTENTIAL HAZARDS AND RISK FACTORS OF THE WORK ENVIRONMENT IN THE FOUNDRY INDUSTRY X

Background: Workers have a risk of work accidents and Occupational Diseases (PAK) caused by the work process, behavior at work, and the work environment. Identification of potential hazards and risk assessment is the first step to find hazards in the workplace and then carry out control measures to create a safe and healthy workplace.
 Objective: Knowing potential hazards, environmental risk values, and physical working conditions in the Metal Casting Industry of X.
 Method: The method used in this study is a descriptive survey. The number of samples in this study were 36 workers. Data collection techniques are carried out through observation activities using sheetsJob Safety Analysis (JSA) and risk assessment sheets, interviews using interview guides, and measurements of physical working conditions usingenvironment meter. The data analysis carried out is descriptive analysis which provides an overview of potential hazards and environmental risk values.
 Results: Overall there are 54 potential hazards in the production process at CV Dwi Jaya Logam which consist of a wet mold making process, there are 12 potential hazards, dry mold making CO method2 there are 10 potential hazards, metal smelting has 20 potential hazards, pouring molten metal into the mold has 6 potential hazards, and disassembling the mold has 6 potential hazards. There are 28 potential hazards in the production process at CV Mulya Jaya consisting of grinding there are 6 potential hazards, cutting iron using a saw machine there are 2 potential hazards, drilling there are 6 potential hazards, turning there are 4 potential hazards, making holes using machinesscrap there are 3 potential hazards, the formation of workpieces using machinesmilling there are 2 potential hazards, welding has 3 potential hazards, and product painting has 2 potential hazards. Overall, the physical working environment conditions in the form of temperature and lighting at CV Dwi Jaya Logam and CV Mulya Jaya did not meet the requirements, while the results of noise measurements at the two locations met the requirements.
 Conclusion: Potential hazards found in the metal casting industry CV Dwi Jaya Logam, namely 54 potential hazards which are divided into 2 levels of risklow, 10 levels of riskmoderate, 30 levels of risk high, and 12 levels of riskextreme. CV Mulya Jaya Metal casting industry identified 28 potential hazards divided into 4 risk levelslow, 4 levels of riskmoderate, 12 levels of risk high, and 8 levels of riskextreme. These potential hazards come from the physical work environment (temperature, lighting, and noise) and the production process at each work step. The results of measurements of the physical working environment in the form of temperature do not meet the requirements according to the Regulation of the Minister of Manpower of the Republic of Indonesia No. 5 of 2018, the average lighting measurement results are also . do not meet the requirements according to Regulation of the Minister of Health No. 70 of 2016, and the average noise measurement results meet the requirements according to the Indonesian Minister of Manpower Regulation No. 5 of 2018.

Analysis Of Work Accident Risk In Plywood Production Units Using Job Safety Analysis Method At Pt Intracawood Manufacturing Tarakan City

Background: The plywood industry cannot be separated from work accidents, so efforts are needed to reduce the number of work accidents by carrying out work accident control programs, namely by implementing risk management. Therefore, this study aims to analyze the risk of work accidents in the plywood production unit using the Job Safety Analysis method. Methods: This research is a Mixed Methods research with the research method used is the Sequential Explanatory Design method. Quantitative sampling was carried out by means of probability sampling with 175 respondents and qualitative sampling by taking 5 informants. The research instruments used interview sheets, Job Safety Analysis Worksheets and AS/NZS 4360:2004 as well as questionnaires and observation sheets. Quantitative data analysis using the Semi-Quantitative analysis method using the Job Safety Analysis Worksheet, qualitative data analysis using content analysis with source and method triangulation. Results: The results of the study found that the hazards in the plywood production process included the work environment, the smell of glue and putty paint, the dangers of working tools such as machines. Based on the identification of potential hazards, a risk analysis is carried out on the rotary work unit, there are 2 work steps with a substantial risk level and 6 work steps with a priority 3 risk level. 1 work step with a risk level of the Priority 3 category and 3 work steps with an Acceptable category risk level. Conclusion: There are several work accidents that are caused by the workers themselves and the work environment. so that control recommendations are given such as making SOPs, providing PPE, conducting training for each work step and providing signs or installing safety signs in places that might cause accidents.

Traffic Transformer: Transformer-based framework for temporal traffic accident prediction

<abstract><p>Reliable prediction of traffic accidents is crucial for the identification of potential hazards in advance, formulation of effective preventative measures, and reduction of accident incidence. Existing neural network-based models generally suffer from a limited field of perception and poor long-term dependency capturing abilities, which severely restrict their performance. To address the inherent shortcomings of current traffic prediction models, we propose the Traffic Transformer for multidimensional, multi-step traffic accident prediction. Initially, raw datasets chronicling sporadic traffic accidents are transformed into multivariate, regularly sampled sequences that are amenable to sequential modeling through a temporal discretization process. Subsequently, Traffic Transformer captures and learns the hidden relationships between any elements of the input sequence, constructing accurate prediction for multiple forthcoming intervals of traffic accidents. Our proposed Traffic Transformer employs the sophisticated multi-head attention mechanism in lieu of the widely used recurrent architecture. This significant shift enhances the model's ability to capture long-range dependencies within time series data. Moreover, it facilitates a more flexible and comprehensive learning of diverse hidden patterns within the sequences. It also offers the versatility of convenient extension and transference to other diverse time series forecasting tasks, demonstrating robust potential for further development in this field. Extensive comparative experiments conducted on a real-world dataset from Qatar demonstrate that our proposed Traffic Transformer model significantly outperforms existing mainstream time series forecasting models across all evaluation metrics and forecast horizons. Notably, its Mean Absolute Percentage Error reaches a minimal value of only 4.43%, which is substantially lower than the error rates observed in other models. This remarkable performance underscores the Traffic Transformer's state-of-the-art level of in predictive accuracy.</p></abstract>

Identification of Potential Hazards Associated with South Korean Prawns and Monitoring Results Targeting Fishing Bait.

This study detected two potential pathogens, Vibro parahaemolyticus, which causes acute hepatopancreatic necrosis disease (AHPND), and white spot syndrome virus (WSSV), in fishing bait in South Korea. However, their infectious nature was not confirmed, possibly due to the degradation caused by freezing/thawing or prolonged storage under frozen conditions. While infectivity was not confirmed in this study, there is still a significant risk of exposure to these aquatic products. Furthermore, fishing bait and feed should be handled with caution as they are directly exposed to water, increasing the risk of disease transmission. In Australia, cases of WSSV infection caused by imported shrimp intended for human consumption have occurred, highlighting the need for preventive measures. While freezing/thawing is a method for inactivating pathogens, there are still regulatory and realistic issues to be addressed.

Identification Of Potential Hazards In Palm Oil Companies In The Sterilizer Section Using The HIRARC Method

Identification Of Potential Hazards In Palm Oil Companies In The Sterilizer Section Using The HIRARC Method

Using machine learning and satellite data from multiple sources to analyze mining, water management, and preservation of cultural heritage

ABSTRACT Remote sensing, particularly satellite-based, can play a valuable role in monitoring areas prone to geohazards. The high spatial and temporal coverage provided by satellite data can be used to reconstruct past events and continuously monitor sensitive areas for potential hazards. This paper presents a range of techniques and methods that were applied for in-depth analysis and utilization of Earth observation data, with a particular emphasis on: (1) detecting mining subsidence, where a novel approach is proposed by combining an improved U-Net model and Interferometry Synthetic Aperture Radar (InSAR) technology. The results showed that the Efficient Channel Attention (ECA) U-Net model performed better than the U-Net (baseline) model in terms of Mean Intersection over Union (MIoU) and Intersection over Union (IoU) indicators; (2) monitoring water conservancy and hydropower engineering. The Xiaolangdi multipurpose dam complex was monitored using Small BAsline Subsets (SBAS) InSAR method on Sentinel-1 time series data and four small regions with high deformation rates were identified on the slope of the reservoir bank on the north side. The dam body also showed obvious deformation with a velocity exceeding 60 mm/a; (3) the evaluation of the potential of InSAR results to integrate monitoring and warning systems for valuable heritage and architectural preservation. The overall outcome of these methods showed that the use of Artificial Intelligence (AI) techniques in combination with InSAR data leads to more efficient analysis and interpretation, resulting in improved accuracy and prompt identification of potential hazards; and (4) finally, this study also presents a method for detecting landslides in mountainous regions, using optical imagery. The new temporal landslide detection method is evaluated over a 7-year analysis period and unlike conventional bi-temporal change detection methods, this approach does not depend on any prior-knowledge and can potentially detect landslides over extended periods of time such as decades.

Identification of potential hazard of consumption of novel products to public health (systematic review)

Introduction. Declining volumes of meat production are associated, among other things, with fight against global warming. This unavoidably stimulates the scientific community to look for alternative sources of protein. However, novel foods can pose a potential health threat for consumers.
 The aim was to search for data on a potential threat for human health posed by consuming the most widely spread novel foods.
 Materials and methods. To achieve that, we accomplished a systematic review of relevant information sources using PRISMA recommendations on how to perform a systemic review of research articles. Overall, we analyzed more than two thousand sources to identify their relevance to the aim of this study; ultimately 64 sources were selected for analysis. 
 Results. Within this review, three groups of novel foods of animal origin were identified and considered. They were the most frequently mentioned in studies investigating potential health hazards for humans. We analyzed these potential hazards caused by consuming novel foods; it was established that attention should be paid to probable changes in biological values of protein in a novel food, undeclared or unintended chemicals in it, and hyper-reactivity of the human immune system. Besides, when insect or GM-animal proteins are used as food raw materials, a probability of pathogenic microorganisms in them should not be neglected. A distinctive feature of foods manufactured from GM-animals is estimation of a potential hazard associated with probable transfer of changed genes to the opportunistic gut microflora.
 Limitations. The study addressing potential health hazards posed by consumption of new foods considered only ‘new food products’ of animal origin.
 Conclusion. The systemic review of relevant information sources was aimed to identify potential health hazards posed by consumption of novel food of animal origin and allowed fulfilling hazard identification as the first stage in health risk assessment.

Determinants of knowledge associated with occupational hazards and perceived health problems among dye workers in Abeokuta, Nigeria.

Identification of potential hazards, their adverse health effects, and predisposing factors in the workplace are critical to improving safety. The objective of the study was to assess the knowledge of occupational hazards, the prevalence of perceived health problems and their predictors among textile dye workers in Abeokuta Nigeria who work in unsupervised settings. In this cross-sectional study, data were collected from 199 participants using a validated semi-structured interviewer-administered questionnaire. Multiple linear regression analysis was used to determine the predictors of knowledge while Pearson Chi-square was employed to test the association between perceived health problems, sociodemographics and work environment characteristics. The mean age of the respondents was 40 (SD=12) years with an average work experience of 19 years. The majority of respondents 139 (69.8%) had lower than average scores on knowledge of 25 questions on chemical hazards. There was no correlation between knowledge score and work experience (P=0.492) or age (P=0.462) but the knowledge was significantly associated with exposure score (P=0.004), gender (P=0.002) and adherence to instructions on chemicals usage (P=0.041) after adjusting for safe practice. The most frequent health problems among the dye workers were respiratory disorders (53.8%), allergies (51.8%), and skin disorders (24.1%). Airborne gaseous pollutants from the mixing of chemicals were associated with allergies (P=0.045), circulatory (P=0.02) and skin disorders (P=0.049) while air-borne textile fiber/dye particles could predict allergies (P=0.028). Findings revealed that exposure, gender and adherence to instruction labels on dye/chemical containers could determine knowledge of chemical hazards while physical work environment characteristics could determine health problems.

Usulan Pengendalian Risiko Keselamatan Dan Kesehatan Kerja Menggunakan Metode HIRARC di PT Buana Niaga Bersama

PT Buana Niaga Bersama Karawang is a manufacturing company that produces retreaded tires, this company uses mold machines and boiler machines. This study aims to analyze the application of safety and health from the beginning of the production process to finished goods, because this company has not fully implemented occupational safety and health, for example workers do not use safety shoes, carry raw materials manually. This research is a descriptive research that explains the application of occupational safety and health in the production area of PT Buana Niaga Bersama, the method used is HIRARC (Hazard Identification, Risk Assessment and Risk Control) with the first stage namely identifying potential hazards, then evaluating potential hazards and the last stage namely the control of potential hazards. The results of this study are based on the identification of potential hazards, there are 24 cases of potential hazards, with a risk assessment that there are as many as 62% or 15 cases of potential hazards with low risk (low risk), as many as 25% or 6 cases of potential hazards with moderate risk (medium risk). and as many as 13% or 3 cases of potential danger with severe risk (extreme risk). Suggestions for company owners are to provide personal protective equipment and establish standard operating procedures, while for workers, namely to work according to standard operating procedures and use personal protective equipment while working.

An Adaptive Identification Method for Potential Landslide Hazards Based on Multisource Data

The effectiveness of landslide disaster prevention depends largely on the quality of early identification of potential hazards, and how to comprehensively, deeply, and accurately identify such hazards has become a major difficulty in landslide disaster management. Existing deep learning methods for potential landslide hazard identification often use fixed-size window modeling and ignore the different window sizes required by landslides of different scales. To address this problem, we propose an adaptive identification method for potential landslide hazards based on multisource data. Taking Yongping County, China, as the study area, we create a multisource factor dataset based on the landslide disaster background in terms of topography, geology, human activities, hydrology, and vegetation as the sample for the identification model after processing. Moreover, we combine differential interferometric synthetic aperture radar (D-InSAR) and multitemporal InSAR (MT-InSAR) to process the surface deformation of the study area, and we measure the deformation richness based on the average of the pixel deformation difference within the current window of a pixel point in the image. Therefore, convolutional neural networks (CNNs) with different window sizes are adaptively selected. The results show that the precision of adaptive identification of potential landslide hazards in the study area is 85.30%, the recall is 83.03%, and the F1 score is 84.15%. The recognition rate for potential hazards reaches 80%, which is better than the fixed-window modeling result and proves the effectiveness of the proposed method. This method can help to improve intelligent identification systems for potential landslide hazards, and also contribute to the identification of other potential geological hazards, such as mudslides and collapses.

Identification of potential hazards and analysis of critical control points in cultured meat (in vitro meat) production

The development of food technologies at the present stage is aimed at expanding the range of food raw materials, including alternative food sources. One of such sources is meat derived from in vitro stem cells or cultured meat. The stages of in vitro meat production could be divided into four blocks: preparation of raw materials, cultivation of cells in a nutrient medium, forming the final product and preparing meat for sale to the consumer. The cultured meat production process must be accompanied by the improvement, implementation and maintenance of procedures based on HACCP principles. However, the developed and approved HACCP system for the cultured meat production hasn't been found in the scientific literature. Given the prospects for cultured meat production, the development HACCP system for this area is feasible. In this regard, it is advisable to identify critical control points in production and identify the potential hazards of cultured meat to consumers for subsequent risk assessment. The aim of the study was to identify potential health hazards and analyze key control points in cultured meat production. Material and methods. Previously conducted studies on in vitro meat cultivation technologies, as well as Russian regulatory and technical documentation were used as initial data on the production processes of cultured meat and the risk associated with its production. The method of studying and critical analyzing relevant scientific sources devoted to the safety of cultured meat was applied. In total, more than 120 sources were studied, from which 30 relevant ones were selected. Results. The potential hazards associated with the consumption of cultured meat are due to physical, chemical and biological factors. In addition, the occurrence of allergic reactions is identified as a danger factor. An imbalance of amino acids in the diet may occur as a result of the consumption of novel food in a significant proportion (>50% of meat consumption). Ten critical control points have been identified, each of which is characterized by the action of potential hazard factors of a different nature. It has been established that the number of critical control points is the same at all stages of production, except for the formation of the final product. The characteristics of hazard factors, as well as information about the critical control points of these factors' action, determine the possibility of assessing the potential hazard (and further risk assessment) and choosing measures to manage them, which meets the requirements of GOST R ISO 22000-2019. Conclusion. Each of the identified types of hazard is not specific to a particular stage of in vitro meat production and can effect negatively at several critical control points. When organizing control (monitoring) of the safety of new type food, one should be guided by the Technical Regulations of the Custom Union "On the Safety of Food Products", according to which the manufacturer of foods (including novel foods) must develop, implement and comply with procedures based on the HACCP. The use of HACCP is relevant under inappropriate risk for consumer health. To assess the risk level, exposure assessment (a key step in risk assessment) should be carried out for each type of hazard factor. For these purposes, it is necessary to identify the potential risk group and determine the scenarios of cultured meat's consumption.

Predicting burn severity for integration with post-fire debris-flow hazard assessment: a case study from the Upper Colorado River Basin, USA

Background Burn severity significantly increases the likelihood and volume of post-wildfire debris flows. Pre-fire severity predictions can expedite mitigation efforts because precipitation contributing to these hazards often occurs shortly after wildfires, leaving little time for post-fire planning and management. Aim The aim of this study was to predict burn severity using pre-fire conditions of individual wildfire events and estimate potential post-fire debris flow to unburned areas. Methods We used random forests to model dNBR from pre-fire weather, fuels, topography, and remotely sensed data. We validated our model predictions against post-fire observations and potential post-fire debris-flow hazard estimates. Key results Fuels, pre-fire weather, and topography were important predictors of burn severity, although predictor importance varied between fires. Post-fire debris-flow hazard rankings from predicted burn severity (pre-fire) were similar to hazard assessments based on observed burn severity (post-fire). Conclusion Predicted burn severity can serve as an input to post-fire debris-flow models before wildfires occur, antecedent to standard post-fire burn severity products. Assessing a larger set of fires under disparate conditions and landscapes will be needed to refine predictive models. Implications Burn severity models based on pre-fire conditions enable the prediction of fire effects and identification of potential hazards to prioritise response and mitigation.

The modification of methodological approaches for potential hazard identification of inadvertent chemicals in food

The existing methodological approaches for hazard identification and selection of priority hazard contaminants in foodstuff for further health risk assessment and legislation (in case of need) do not represent the reasons of inclusion inadvertent chemical substances in a number of priority for health risk assessment. The absence both of complex assessment and potential hazard categories of contaminants do not allow to assess the urgency of health risk assessment. Thus, it's advisable to expand the existing methodological approaches with the criteria of selection of hazard inadvertent chemical substances in food. The criteria allow for an integral assessment and further categorizing for health risk assessment and legislation. The aim of the research was to develop the methodological approaches to selection of priority inadvertent chemical substances in foodstuff for risk analysis and legislation based on the integral assessment Results. Material and methods. Various methods of chemical analysis were applied for detection of potentially hazard chemical substances in foodstuff. The further hazard identification and selection of priority chemical substances has been based on suggested criteria and categories that complete existing methodology. The approbation of methodological approaches to integral assessment and categorizing has been carried out on milk. Results and discussion. The potential hazard identification of inadvertent chemicals has been carried out using the complex of selection criteria. It was suggested to apply scores for calculation of integral score for further categorizing and selection of priority chemical substances (taking into account substances' toxicity class and possibility of migration during cooking or formation during technological process, and from packing, and from food raw materials). 5 hazard chemicals in milk (2-furanmethanol, thallium, mevinphos, sulfotep, mephospholane) were defined as priority category as the result of approbation. Conclusion. Integral assessment and categorizing of potential hazard of inadvertent chemicals in food applying basic and additional criteria taking into account natural content of the substances and their possibility of migration in food allow to assess the priority of health risk assessment and further hygienic legislation of the substances (in case if the risk level is inappropriate). During the approbation on the example of milk, 5 unintended substances that had potential hazard category I (high priority) were recommended for further risk assessment.