Search

Food contact materials (FCMs) can contain hazardous chemicals that may have the potential to migrate into food and pose a health hazard for humans. Previous studies have mainly focused on plastic materials, while data on packaging materials made from paper and cardboard are limited. We used a panel of cell-based bioassays to investigate the presence and impact of bioactive chemicals on human relevant endpoints like oxidative stress, genotoxicity, inflammation, xenobiotic metabolism and endocrine system effects in extracts made from paper and cardboard. In total, 23 methanol extracts of commonly used paper and cardboard available on the Swedish market were extracted as a whole product using methanol to retrieve polar substances, and tested at concentrations 0.3–10 mg/mL and 0.2–6 mg/mL. At the highest concentration bioactivities were observed in a high proportion of the samples: oxidative stress (52%), genotoxicity (100%), xenobiotic metabolism (74%), antiandrogenic- (52%) and antioestrogenic receptor (39%). Packages of potential concern included cake/pastry boxes/mats, boxes for infant formula/skimmed milk, pizza boxes, pizza slice trays and bag of cookies. It should be noted that the extraction for packages like cake/pastry boxes can be considered exaggerated, as the exposure usually is shorter. It can be hypothesised that the observed responses may be explained by inks, coatings, contaminants and/or naturally occurring compounds within the material. To summarise, an effect-based approach enables hazard identification of chemicals within FCMs, which is a valuable tool for ensuring safe use of FCMs. [ABSTRACT FROM AUTHOR]

This paper intends to give an impression of new technologies and processes that are in development for application to achieve decarbonization, and about which less or no experience on associated hazards exists in the process industry. More or less an exception is hydrogen technology because its hazards are relatively known and there is industry experience in handling it safely, but problems will arise when it is produced, stored, and distributed on a large scale. So, when its use spreads to communities and it becomes as common as natural gas now, measures to control the risks will be needed. And even with hydrogen, surprise findings have been shown lately, e.g., its BLEVE behavior when in a liquified form stored in a vessel heated externally. Substitutes for hydrogen are not without hazard concern either. The paper will further consider the hazards of energy storage in batteries and the problems to get those hazards under control. Relatively much attention will be paid to the electrification of the process industry. Many new processes are being researched, which given green energy, will be beneficial to reduce greenhouse gases and enhance sustainability, but of which hazards are rather unknown. Therefore, as last chapter the developments with respect to the concept of hazard identification and scenario definition will be considered in quite detail. Improvements in that respect are also being possible due to the digitization of the industry and the availability of data and considering the entire life cycle, all facilitated by the data model standard ISO 15926 with the scope of integration of life-cycle data for process plants including oil and gas production facilities. Conclusion is that the new technologies and processes entail new process and personal hazards, and that much effort is going into renewal but safety analyses are scarce. Right in a period of process renewal, attention should be focused on possibilities to implement inherently safer design. [ABSTRACT FROM AUTHOR]

For mining engineering and geological engineering, the deformation and fracture of coal and rock are the essential causes of dynamic disasters. In this paper, the loading experimental system was established on gas-bearing coal, to study the internal relationship between the spatial distribution of EP and the development process of damaging localization on coal mass. The results indicated the temporal response of EP signal could reflect the stress state and damage degree of gas-bearing coal, showing the precursor feather when coal mass failed. Particularly, when the stress dropped suddenly, the EP signal has a sudden mutation, and the acoustic emission (AE) signal suffered the pulsed increase, while the crack grew and expanded rapidly. Furthermore, when local severe damage occurs inside the coal mass, there was abnormal EP spatial distribution with high-value or dense contours in these zones, where simultaneously AE rupture events frequently occurred, and cracks expanded and gathered. The characteristics of EP spatial distribution can reveal the development process of coal mass damaging localization. Meanwhile, the mentioned zones with abnormal EP distribution above are hazard sources inducing coal mass’s instability and failure. The study results provide the foundational research work of fine forecasting on coal and gas outburst disaster hazard. [ABSTRACT FROM AUTHOR]

The environmental perception system is the foundation of unmanned driving systems and also the fundamental guarantee of the safety and intelligence of unmanned vehicles. The obstacle hazard identification technology is the core of the environment perception system, and it is also the basic condition for the autonomous driving of unmanned vehicles. In view of the complexity of obstacle danger identification, this research paper designs an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm for hazard recognition of obstacles in unmanned scenes through a systematic approach. First, it highlights the significance of morphological component analysis in identifying non-smooth regions within images where obstacles are likely to be present. Second, it introduces a novel approach for core point definition by identifying an optimal MinDensity value based on the curvature of the density distribution curve. Third, it addresses variations in density sequences through smoothing and normalization. Finally, it constructs an improved DBSCAN Algorithm for hazard recognition of obstacles in unmanned scenes. It addresses limitations in the traditional DBSCAN by refining the core point definition using an adaptive density threshold. It identifies the "elbow point" in density distribution, enhancing its ability to distinguish density states. Additionally, it incorporates density curve smoothing, normalization, and a merger step for handling stationary objects. The results show that it has high accuracy (95.6%), precision (96.3%), recall (94.5%), and F-Score (95.4%), as well as increased consistency (92.5%) and dependability (93.2%). It also has fast real-time data processing, lasting only 0.12 s, making it an excellent choice for obstacle detection and unmanned hazard avoidance. [ABSTRACT FROM AUTHOR]

Endocrine disrupting chemicals or carcinogens have been known for decades for their endocrine signal disruption. Endocrine disrupting chemicals are a serious concern and they have been included in the top priority toxicants and persistent organic pollutants. Therefore, researchers have been working for a long time to understand their mechanisms of interaction in different human organs. Several reports are available about the carcinogen potential of these chemicals. The presented review is an endeavor to understand the hazard identification associated with endocrine disrupting carcinogens in relation to the human body. The paper discusses the major endocrine disrupting carcinogens and their potency for carcinogenesis. It discusses human exposure, route of entry, carcinogenicity and mechanisms. In addition, the paper discusses the research gaps and bottlenecks associated with the research. Moreover, it discusses the limitations associated with the analytical techniques for detection of endocrine disrupting carcinogens. [Display omitted] • Types of endocrine disrupting chemicals (EDCs) related to cancer were analyzed. • EDCs associated cancers and their mechanisms were discussed. • Human exposure to EDCs was explored. • Assessment of EDCs carcinogenicity was performed. • Research gaps and future studies were suggested. [ABSTRACT FROM AUTHOR]

The setting of concentrations for testing substances in ecotoxicological studies is often based on fractions of the concentrations that cause 50% mortality (LC50 or LD50) rather than environmentally relevant levels. This practice can result in exposures to animals at test concentrations that are magnitudes of order greater than those experienced in the environment. Often, such unrealistically high concentrations may cause non-specific biochemical or morphologic changes that primarily reflect the near-lethal health condition of the animal subjects, as opposed to effects characteristic of the particular test compound. Meanwhile, it is recognized that for many chemicals, the toxicologic mode of action (MOA) responsible for lethality may differ entirely from the MOAs that cause various sublethal effects. One argument for employing excessively high exposure concentrations in sublethal studies is to ensure the generation of positive toxicological effects, which can then be used to establish safety thresholds; however, it is possible that the pressure to produce exposure-related effects may also contribute to false positive outcomes. The purpose of this paper is to explore issues involving some current usages of acute LC50 data in ecotoxicology testing, and to propose an alternative strategy for performing this type of research moving forward. Toward those ends, a brief literature survey was conducted to gain an appreciation of methods that are currently being used to set test concentrations for sublethal definitive studies. [ABSTRACT FROM AUTHOR]

Renewable energy attracts increasing attention from both industry and academia under the context of carbon neutrality. For wind and solar energy, the strong dependence on natural processes results in the imbalance between energy production and real demands. Energy storage technologies, e.g., Compressed Air Energy Storage (CAES), are promising solutions to increase the renewable energy penetration. However, the CAES system is a multi-component structure with multiple energy forms involved in the process subject to high temperature and high-pressure working conditions. The CAES system is a complex process flowsheet consisting of charging and discharging process. The process should be optimized to achieve the best thermodynamic and economic performance. Under the optimal design conditions, it might lead to severe consequences once a failure occurs, e.g., harm to humans, the environment, and assets. Limited attention and scarce available information have been paid to the CAES system risk management yet. Hence, this paper applies the System-Theoretic Process Analysis (STPA), which is a top-down method based on system theory, to identify the CAES system safety hazards. The results are expected to provide a preliminary guideline for practitioners regarding the safety and reliability of the CAES system. As a result, a more reliable CAES system can contribute to a more flexible energy system with more efficient and economic utilization of fluctuating renewable energy. [ABSTRACT FROM AUTHOR]

Sucralose, a sugar substitute first approved for use in 1991, is a non-caloric sweetener regulated globally as a food additive. Based on numerous experimental animal studies (dating to the 1980s) and human epidemiology studies, international health agencies have determined that sucralose is safe when consumed as intended. A single lifetime rodent carcinogenicity bioassay conducted by the Ramazzini Institute (RI) reported that mice fed diets containing sucralose develop hematopoietic neoplasia, but controversy continues regarding the validity and relevance of these data for predicting health effects in humans. The present paper addresses the controversy by providing the perspective of experienced pathologists on sucralose-related animal toxicity and carcinogenicity data generally, and the RI carcinogenicity bioassay findings specifically, using results from publicly available papers and international regulatory authority decisions. In the authors' view, flaws in the design, methodology, data evaluation, and reporting of the RI carcinogenicity bioassay for sucralose diminish the value of the data as evidence that this agent represents a carcinogenic hazard to humans. This limitation will remain until the RI bioassay is repeated under Good Laboratory Practices and the design, data, and accuracy of the pathology diagnoses and interpretations are reviewed by qualified pathologists with experience in evaluating potential chemically-induced carcinogenic hazards. [ABSTRACT FROM AUTHOR]

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection. [ABSTRACT FROM AUTHOR]

The use of robotics and automation (RA) within construction operations to combat stagnant productivity, high rates of injuries and fatalities, and a declining workforce is increasing. However, utilizing RA for construction operations creates human-robot interactions (HRIs) that can lead to the emergence of novel hazards or exacerbate existing safety risk levels. These hazards, if ignored, could worsen worker safety performance. This paper presents a study intended to identify critical HRI safety risks and develop a pre-task planning protocol for the assessment of safety risks associated with the use of RA. To achieve this goal, the authors utilized a sequential multi-phase approach relying on information obtained from a literature review, a 3-round Delphi process consisting of a panel of experts from industry and academia, and interviews with safety experts. Forty hazards associated with RA and 20 potential strategies for the mitigation of HRI safety risks were identified and evaluated. This information was used to develop a safety risk assessment tool that yields an overall risk rating of using RA. This study contributes to knowledge and practice by identifying and quantifying critical safety risks associated with HRI and developing a tool to assess and mitigate unique HRI safety risks. Utilizing insights developed in this study could improve construction worker safety and health and aid the industry's increasing push towards a smart and safe workforce. [ABSTRACT FROM AUTHOR]

Large-scale irrigation area reconstruction and expansion projects involve the repair, reconstruction and new construction of sluices, channels, inverted siphons, aqueducts and other structures. In order to ensure the quality of the project and avoid the occurrence of safety accidents, it is necessary to explore, prevent and control the hazards that may lead to building quality defects and safety accidents during the construction period. Using the work breakdown structure method and the analytic hierarchy process, the paper took the sluice engineering construction as an example and established the hazard identification and risk assessment model during the sluice engineering construction period. It had been successfully used in the identification and risk assessment of hazard sources during the construction period of the sluice project of the second phase of Zhaokou Yellow River diversion irrigation area. The research results show that the construction operation risks and building material risks have the greatest impact on the overall safety of the project and the two types of hazard sources that need to be focused on prevention and control during the project construction period. [ABSTRACT FROM AUTHOR]

Evaluation of water inrush risk is becoming increasingly important as coal mining activities reach greater depths. Hazard identification, as well as hazard analysis, is the first step in accident prevention. However, there have not been any studies that focus on the hazard analysis system for mine water inrush. In this paper, hazard identification and its definitions are briefly summarized and a comprehensive review of methods for hazard identification and classification are conducted. To illustrate the hazard of coal mine water inrush, data on coal mine accidents (since 2001) are collected and hundreds water inrush accidents were analyzed in depth. Empirical, statistical analysis and case study method were used to conduct the research. By collecting a large number of mine water inrush cases, hazard identification and risk control measures for coal mine water inrush accidents were conducted. Hazard identification method based on fault tree analysis, as well as a method based on management oversight and risk tree (MORT) and energy release theory were put forward. The analysis results show that the historical information and experiences are critically important in hazard identification of mine water inrush. Hazard of mine water inrush is divided into dynamic root hazard and static root hazard which can be further categorized into static innate hazard and dynamic-triggered hazard. Strategies for risk control of mine water inrush are combined into three aspects: engineering controls, operation system controls, and human behavior controls. Finally, a case study of the Taoyuan coal mine was conducted to illustrate the proposed system, with limitations and future studies are discussed. The hazard identification and classification system can be broadly applied to coal mines and will improve risk control and prevention of mine water inrush accidents. [ABSTRACT FROM AUTHOR]

Crane-related accidents often occur due to failure in timely and accurate hazard identification. Virtual Reality (VR) technology facilitates immersive environments for improving hazard identification without real-world consequences. However, the impact of simulation fidelity on hazard identification performance, particularly for novice crane operators, remains underexplored. This paper examines how simulation fidelity and task complexity affect hazard identification performance among novice operators through a VR experiment with two fidelity and two complexity levels. Findings demonstrate high-fidelity (HF) scenarios significantly improve hazard identification success rate and speed for swing-over hazards but extend task completion times. Task complexity modulates simulation fidelity's impact on task completion, with significant differences between fidelity levels observed only under low complexity. These insights inform the design and calibration of simulation fidelity in VR platforms, potentially improving training efficacy and crane lifting safety for novice operators. • Explores the impact of simulation fidelity on novice crane operators' hazard identification. • Finds that high-fidelity boosts success rate but reduces speed in hazard identification. • Highlights accuracy-speed trade-off due to simulation fidelity changes. • Emphasises interaction fidelity for immersive, real-world-like experiences. • Guides on balancing simulation fidelity and cost-effectiveness in VR safety training. [ABSTRACT FROM AUTHOR]

Nanoplastics are associated with several risks to the ecology and toxicity to humans. Nanoplastics are synthetic polymers with dimensions ranging from 1 nm to 1 μm. They are directly released to the environment or secondarily derived from plastic disintegration in the environment. Nanoplastics are widely detected in environmental samples and the food chain; therefore, their potentially toxic effects have been widely explored. In the present review, an overview of another two potential sources of nanoplastics, exposure routes to illustrate hazard identification of nanoplastics, cell internalization, and effects on intracellular target organelles are presented. In addition, challenges on the study of nanoplastics and future research areas are summarized. This paper also summarizes some approaches to eliminate or minimize the levels of nanoplastics to ensure environmental safety and improve human health. [ABSTRACT FROM AUTHOR]

Power systems and their primary components, mostly the transmission and distribution of overhead lines, substations, and other power facilities, are distributed in space and are exposed to various atmospheric and meteorological conditions. These conditions carry a certain level of risk for reliable electrical power delivery. Various atmospheric hazards endanger the operation of power systems, where the most significant are thunderstorms, wildfire events, and floods which can cause various ranges of disturbances, faults, and damages to the power grid, or even negatively affect the quality of life. By utilizing a weather monitoring and early warning system, it is possible to ensure a faster reaction against different weather-caused fault detections and elimination, to ensure a faster and more adequate preparation for fighting extreme weather events, while maintaining overhead line protection and fault elimination. Moreso, it is possible to bypass overhead lines that have the highest risk of unfavorable meteorological events and hazards, and reroute the energy, thus providing electricity to endangered areas in times of need while minimizing blackouts, and consequently, improving the quality of human life. This paper will present an analysis of the various risks of atmospheric phenomena, in the meteorological and climate context, and discuss various power system components, the power system control, operations, planning, and power quality. A concept with the main functionalities and data sources needed for the establishment of an early warning weather hazard system will be proposed. The proposed solution can be used as a utility function in power system control to mitigate risks to the power system due to atmospheric influences and ongoing climate change. [ABSTRACT FROM AUTHOR]

• An extended STPA approach is proposed for safety analysis for human-system collaboration. • The human-related cognitive hazards are identified by incorporating a human cognitive model into STPA. • The operational contexts of unsafe control actions (UCAs) are systematically derived by using process model hierarchies. • Results reflect differences in humans' and technical hazards between the remote control mode and remote supervision mode of autonomous ships. • The result is beneficial for the development of future human-oriented and safe design of autonomous ships and their Shore Control Center (SCC). Shore control center (SCC) operators of maritime autonomous surface ships (MASS) may be allocated with complex responsibilities within different degrees of autonomy (DoA), from remote control to remote supervision, and the role of human in-the-loop is significant. In the current research on MASS, however, the safety of interactions between humans and systems are not sufficiently considered. Hence, this paper proposes a system-theoretic approach to safety analysis for human-system collaboration. The novelty of the approach is the definition of operational contexts of MASS and the integration of a human cognitive model into the system theoretic process analysis (STPA), called STPA-Cog. The method is demonstrated in two case studies of MASS: (i) remote control mode (RCM) and (ii) remote supervision mode (RSM), focusing on two types of navigational accidents (i.e., collision and grounding). The analysis results are derived by comparing the human-related and technical-related causal scenarios in RCM and in RSM. The findings can assist in human-oriented design and operational planning for SCC of MASS. Further, the proposed approach also has the potential to be used and extended to systemic safety analysis in other intelligent transportation systems. [ABSTRACT FROM AUTHOR]

• Wearable EEG-based hotspot approach supports ubiquitous construction hazard identification. • Similarities and discrepancies between VR and physical set-ups are revealed. • EEG classifiers developed in VR can be applied to a real-world setting. • Hotspot analysis allows for a spatial association between hazards and EEG signals. • Dual-layer approach enables the reduction of significant motion artifacts in EEG signals. Hazard identification on construction jobsites is one of the most critical components of construction safety management. To overcome the limitations in the current manual practice, researchers explored the correlation between hazard perception and changes in workers' electroencephalogram (EEG) signals collected from wearable sensors to identify and differentiate different types of hazards. However, most of such studies are based on experiments in a virtual reality (VR) environment. The unproven applicability of the VR-led results to the real jobsites and the potential discrepancies in results between the physical and virtual environments are the main barriers toward EEG-based ubiquitous hazard identification on the jobsites. To bridge the research gaps, this paper tests the feasibility of identifying construction hazards in physical and VR environments, and compares their results to identify discrepancies. Two experimental environments (physical and VR, respectively), each containing three hazards, were designed with the same configuration. Hazard identification task was performed in both experiments, data (e.g., EEG signals) was collected and preprocessed, and corresponding features were extracted. Hotspot analysis was conducted to infer the existence of hazards by assessing spatial associations. The results showed that both physical and VR settings were effective for hazard detection, while a better performance was observed in the VR setting. In addition, the potential of developing hazard zones as well as particular hazard locations and a gradual increase in subjects' perceived hazard level were revealed. The results highlight the opportunities of revealing potential construction hazards on the construction jobsite using wearable EEG. [ABSTRACT FROM AUTHOR]

The objective of this paper is to develop online risk models that can be updated as conditions change, using risk as one metric to control an autonomous ship in operation. This paper extends and integrates the System Theoretic Process Analysis (STPA) and Bayesian Belief Networks (BBN) with control systems for autonomous ships to enable supervisory risk control. The risk metric is used in a Supervisory Risk Controller (SRC) that considers both risk and operational costs when making decisions. This enables the control system to make better and more informed decisions than existing ship control systems. The novel control system is tested in a case study where the SRC can change: (i) which machinery system is active; (ii) which control mode to run the ship in; and (iii) which speed reference to follow. The SRC is able to choose the optimum machinery, control mode, and speed reference to maintain safe control of the ship over a route in changing conditions. • Method for developing a supervisory risk controller for autonomous surface ships. • Show how risk models can be used in ship control systems. • Supervisory controller for high-level control of autonomous surface ships. • Case study with supervisory risk control of autonomous surface ships. [ABSTRACT FROM AUTHOR]

• A semi-automatic model is developed for hazard and accident cause identification. • We explore and analyze the semantic relationship between the hazards of marine accidents. • The importance of both hazards and accident causes is calculated and ranked. • We gain accident causes distribution in 40 different accident scenarios by using topic model. In the past decades, marine accidents brought the serious loss of life and property and environmental contamination. With the accumulation of marine accident data, especially accident investigation reports, compared with subjective reasoning based on expert experience, data-driven methods for analysis and accident prevention are more comprehensive and objective. This paper aims to develop a content-aware corpus-based model for the analysis of marine accidents to mine the accident semantic features. The general research framework is established to combine accident data, expert prior knowledge, and semi-automated natural language processing (NLP) technology. The NLP models are optimized, fused, and applied to the case study of ship collision accidents. The results show that the proposed model can accurately and quickly extract hazards, accident causes, and scenarios from the accident reports, and perform semantic analysis for the latent relationships between them to extend the accident causation theory. This study can provide a powerful and innovative analysis tool for marine accidents for maritime traffic safety management departments and relevant research institutions. [ABSTRACT FROM AUTHOR]

• A new occupational health and safety training method is proposed, especially for long-term health risks. • The training method is developed based on the integration of diminished quality of life (DQL) and virtual reality (VR). • The DQL-VR training improves the training quality in both hazard identification and risk perception. Safety training using Virtual Reality (VR) can be widely found in many industries. They are majorly focused on educating sequential operations, standard working procedures, and short-term safety risk assessment. Occupational health and safety (OHS) issues at the workplace contain both short-term safety incidents and long-term health issues. Comparing to short-term safety training, long-term health training is little discussed in the existing literature. One of the reasons is that the health issues are more complex than safety, as the biological outcomes may take time to develop, affected by multiple resources, and the injuries may be cumulative. The key contribution of the current paper is the development of a solid training method based on the integration of diminished quality of life (DQL) risk assessment and VR, namely DQL-VR. The use of DQL-VR would assist in delivering OHS knowledge to trainees with a special focus on chronic health components. The use of DQL increases the ability of trainees to determine long-term health hazards and perceive long-term health risks. The use of VR improves the learning efficacy and users' acceptance of the safety training. A pilot test is investigated to examine the efficacy of DQL-VR comparing with traditional safety training. The result shows that DQL-VR has great positive efforts in teaching hazard identification and risk perception, especially for long-term health aspects. The findings also indicate that the use of DQL-VR would benefit trainees' recall of knowledge. The development of DQL-VR also offers opportunities for trainees to foresee the hazards and experience the harmful consequences in a safe environment. [ABSTRACT FROM AUTHOR]

[Display omitted] • Approaches and models in Human Health Risk Assessment are comprehensively reviewed. • Method on the mechanisms of contaminant actions on human health hazards is needed. • Integration and update of existing toxicity databases are necessary. • Lack of health-based screening values is a barrier to biomonitoring. • The integration of fate and transport models and risk assessment systems is essential. Soil contamination is a serious global hazard as contaminants can migrate to the human body through the soil, water, air, and food, threatening human health. Human Health Risk Assessment (HHRA) is a commonly used method for estimating the magnitude and probability of adverse health effects in humans that may be exposed to contaminants in contaminated environmental media in the present or future. Such estimations have improved for decades with various risk assessment frameworks and well-established models. However, the existing literature does not provide a comprehensive overview of the methods and models of HHRA that are needed to grasp the current status of HHRA and future research directions. Thus, this paper aims to systematically review the HHRA approaches and models, particularly those related to contaminated sites from peer-reviewed literature and guidelines. The approaches and models focus on methods used in hazard identification, toxicity databases in dose–response assessment, approaches and fate and transport models in exposure assessment, risk characterization, and uncertainty characterization. The features and applicability of the most commonly used HHRA tools are also described. The future research trend for HHRA for contaminated sites is also forecasted. The transition from animal experiments to new methods in risk identification, the integration and update and sharing of existing toxicity databases, the integration of human biomonitoring into the risk assessment process, and the integration of migration and transformation models and risk assessment are the way forward for risk assessment in the future. This review provides readers with an overall understanding of HHRA and a grasp of its developmental direction. [ABSTRACT FROM AUTHOR]