Probabilistic Risk Assessment Research Articles

Probabilistic scenario-based assessment of national food security risks with application to Egypt and Ethiopia

Abstract This study presents a novel approach to assessing food security risks at the national level, employing a probabilistic scenario-based framework that integrates both Shared Socio-economic Pathways and Representative Concentration Pathways. This innovative method allows each scenario, encompassing socio-economic, and climate factors, to be treated as a model capable of generating diverse trajectories. This approach offers a more dynamic understanding of food security risks under varying future conditions. The paper details the methodologies employed, showcasing their applicability through a focused analysis of food security challenges in Egypt and Ethiopia, and underscores the importance of considering a spectrum of socio-economic and climatic factors in national food security assessments.

Time-dependent probabilistic tsunami risk assessment: application to Tofino, British Columbia, Canada, subjected to Cascadia subduction earthquakes

A new time-dependent probabilistic tsunami risk model is developed to facilitate the long-term risk management strategies for coastal communities. The model incorporates the time-dependency of earthquake occurrence and considers numerous heterogeneous slip distributions via a stochastic source modeling approach. Tidal level effects are examined by considering different baseline sea levels. The model is applied to Tofino, British Columbia, Canada within the Cascadia subduction zone. High-resolution topography and high-quality exposure data are utilized to accurately evaluate tsunami damage and economic loss to buildings. The results are tsunami loss curves accounting for different elapsed times since the last major event. The evolutionary aspects of Tofino’s time-dependent tsunami risk profiles show that the current tsunami risk is lower than the tsunami risk based on the conventional time-independent Poisson occurrence model. In contrast, the future tsunami risk in 2100 will exceed the time-independent tsunami risk estimate.

Probabilistic risk assessment of dietary exposure to lead in residents of Guangzhou, China

Lead and its compounds can have cumulative harmful effects on the nervous, cardiovascular, and other systems, and especially affect the brain development of children. We collected 4918 samples from 15 food categories in 11 districts of Guangzhou, China, from 2017 to 2022, to investigate the extent of lead contamination in commercial foods and assess the health risk from dietary lead intake of the residents. Lead was measured in the samples using inductively coupled plasma mass spectrometry. Dietary exposure to lead was calculated based on the food consumption survey of Guangzhou residents in 2011, and the health risk of the population was evaluated using the margin of exposure (MOE) method. Lead was detected in 76.5% of the overall samples, with an average lead content of 29.4 µg kg−1. The highest lead level was found in bivalves. The mean daily dietary lead intakes were as follows: 0.44, 0.34, 0.25, and 0.28 µg kg−1 body weight (bw) day−1 for groups aged 3–6, 7–17, 18–59, and ≥ 60 years, respectively. Rice and rice products, leafy vegetables, and wheat flour and wheat products were identified as the primary sources of dietary lead exposure, accounting for 73.1%. The MOE values demonstrated the following tendency: younger age groups had lower MOEs, and 95% confidence ranges for the groups aged 3–6 and 7–17 began at 0.6 and 0.7, respectively, indicating the potential health risk of children, while those for other age groups were all above 1.0. Continued efforts are needed to reduce dietary lead exposure in Guangzhou.

Optimal energy storage system selection for future cost-effective green hydrogen production: Integrating techno-economic, risk-based decision making, and cost projections

This study conducts technical, economic, and safety analysis of a green hydrogen production system consisting of a 1000 kWp photovoltaic cell, 3 options of energy storage namely lead carbon (PbC), lithium-ion (Li-ion), and repurposed lithium-ion (2nd Life Li-ion) battery, and an electrolyzer. Firstly, the system is optimized to maximum hydrogen production by adjusting equipment capacity and capacity factors, informed by a 1-h resolution solar energy generation profile. This optimization yields insights into the system's yearly operational dynamics. Techno-economic analysis was conducted to estimate the levelized cost of hydrogen (LCOH) from 2020 to 2050, additionally, uncertainty analysis using Monte-Carlo simulation to estimate the range of uncertainty in LCOH projection from 2020 to 2050 was performed. Furthermore, a quantitative risk analysis, utilizing the process route index metric, evaluates the risk of battery explosions. Finally, this study employs multi-criteria decision-making to choose the best energy storage technology to produce green hydrogen from economic and safety factors. The result indicates that in 2020, the PbC battery emerged as the most cost-effective option. However, over time, both lithium batteries became the cheapest option with almost similar trends. In terms of explosion hazard, the analysis shows that the PbC battery is a safer option for stationary energy storage. When both aspects are considered, the preferred battery option is almost certainly PbC over the years, but in extreme cases where the decision-maker places significant emphasis on economic factors both Li-ion options may become preferable.

Korean Perspective for Integrated Deterministic-Probabilistic Safety Assessment and its Synergetic Strategy with Conventional Methods

The PSA (Probabilistic Safety Assessment) is presented as a method of comprehensively evaluating the types of accidents that can occur at nuclear power plants. One of the key components to obtain technical success was the introduction of event tree analysis, and its strength and weakness has been reviewed and enhanced with the term, for instance, Integrated Deterministic-Probabilistic Safety Assessment (IDPSA) since 1980s. However, the technical and policy maturity of IDPSA appears to have room for improvement: the terminologies need to be arranged internationally, and there are no official standards or guidelines for the method itself. Due to a misperception of IDPSA, there are even concerns that appropriate contribution in risk assessment cannot be made. For this reason, surveys and focus group interviews, sharing development experiences, and the direction of regulation and R&D on IDPSA were conducted targeting PSA experts in Korea. In order to support such process, authors have structured an overview of the development history and technical features of IDPSA. Finally, we will explore the ways to achieve synergy between the deterministic safety analysis and PSA, which may the origin of motivation how to deal with dynamic variability more properly such that an undue risk can be minimized.

Sustainability risk assessment in manufacturing: A Life Cycle Assessment-based Failure Mode and Effects Analysis approach

This study introduces a methodology integrating Life Cycle Assessment (LCA) with Failure Mode and Effects Analysis (FMEA) to identify and assess environmental sustainability risks in manufacturing processes in alignment with the Corporate Sustainability Reporting Directive (CSRD) and European Sustainability Reporting Standards (ESRS). In contrast to existing top-down approaches at sector and company level, this methodology specifically addresses the challenge of transitory sustainability risks in manufacturing, driven by rapid changes in regulatory frameworks and market expectations, by providing a robust and adaptable framework for comprehensive, bottom-up risk assessment directly on the manufacturing shop floor. Through a detailed literature review, the paper identifies gaps in current risk assessment methods and proposes a novel approach that enhances traditional FMEA by incorporating LCA results, thereby facilitating a comprehensive, quantitative analysis of sustainability risks. The practical application of this methodology is demonstrated through a case study, underscoring its effectiveness in real-world settings and potential for broader applications in sustainable manufacturing. The results presented in the paper also include quantitative sustainability performance benchmarks for the EU28 industrial sector, offering a strategic tool for manufacturers to improve sustainability practices, align operations with environmental standards, and mitigate transitory sustainability risks. This research contributes to the sustainable evolution of manufacturing, providing a methodological foundation for understanding and managing sustainability risks.

Multiple pathway exposure risks and driving factors of heavy metals in soil-crop system in a Pb/Zn smelting city, China

Heavy metals (HMs) in soil near metal smelting areas have attracted great interest due to their crucial threat to agricultural product safety and human health. We investigated HMs in agricultural soils and crops (wheat and maize) in a Pb/Zn smelting city, central China; analysed the exposure risk of HMs through multiple pathways in a soil-crop system through Monte Carlo simulations; and identified the key driving factors using random forest (RF) model. The results showed that most soil HMs exceeded their background level. Cd had the highest exceeding rate compared with the screening values and the highest exceeding rate (40%, in wheat) compared with the food safety limit. Additionally, Cd had the highest bioaccumulation capacity in both maize and wheat. In identifying the key driving factors of soil HMs, RF had a satisfactory prediction performance for As, Cd, and Pb, with corresponding R2 values of 0.47, 0.51, and 0.60, respectively, with the dominant factors being distance to the Pb/Zn smelter, coal washery, and road area, respectively. However, Cr and Hg exhibited lower R2 values which may be due to their limited influence from the selected anthropogenic, traffic, and industrial variables. Probabilistic health risk assessments through Monte Carlo simulations revealed that the non-carcinogenic risk was around the risk limit (HI=1), while the carcinogenic risk for both children and adults exceeded the risk limit (TCR=1E-04), and adults had higher carcinogenic risk than children, which was due to a longer duration of exposure and higher ingestion rate of crop grains in adults. Cd had the highest carcinogenic risk and the highest probability of exceeding the limiting risk. Briefly, levels of Cd in both soil and crops should be controlled, especially for the source of smelting emissions. The results of this study could be treated as valuable references for policymakers to formulate control strategies for soil HM pollution in agricultural areas near Pb/Zn smelting activities.

Dynamic human error risk assessment of group decision-making in extreme cooperative scenario

For groups in extreme environments, their reliability requirements in complex operational systems are high due to isolation from society, physical constraints for extended periods of time, and exposure to significant hazards. This study attempts to solve the problem of dynamic quantitative risk analysis of decision-making process for extreme group during complex cooperative scenarios. Based on an extended IDA team cognitive model, typical failure modes and performance quantification mechanisms of team communication were analyzed. The performance curve was utilized to distinctively model the cognitive behaviors of operators within the team, driving the cognitive transmission paths of group decision-making in a hybrid event tree. Error calibration of human error due to time uncertainty was conducted. The steps and techniques for dynamic risk analysis of decision-making of extreme groups under complex, dynamic, and ambiguous scenarios were summarized. The proposed method was validated through simulation in a typical powered diving task of manned submarine.

Seismic Resilience in Critical Infrastructures: A Power Station Preparedness Case Study

The role of critical infrastructures in maintaining the functioning of the economy and society and ensuring national security, particularly their durability in delivering essential services during crises, including natural disasters such as earthquakes, is critical. This work introduces an analytical methodology to quantify potential earthquake damage to power stations and evaluate the cost-effectiveness of measures to enhance their seismic resistance. By employing fragility curves and probabilistic risk analyses, this approach provides a structured framework for the comprehensive assessment of risks and the identification of economically practical mitigation strategies. A detailed examination of strategies to protect critical power station components against seismic activity is presented, revealing that a minor investment relative to the overall project budget for earthquake-proofing measures is economically effective. This investment, representing a marginal fraction of 0.5% of the total project expenditure significantly reduces the seismic risk of power station failure by 36%. Reinforcing essential elements, including switching stations, water treatment facilities, and water tanks, is emphasized to ensure their continued operation during and after an earthquake. This research highlights the critical significance of integrating risk assessment with benefit-to-cost analysis in strategic decision-making processes, supporting the prioritization of investments in infrastructure enhancements. These enhancements promise substantial reductions of risks at minimal costs, thus protecting essential services against the impacts of natural disasters. This research contributes to state-of-the-art research in critical infrastructures resilience.

Quantitative Risk Analysis for Construction Projects Considering Risks Correlations and Fuzzy Logic

Construction projects have a high level of uncertainty because of several risk factors. Risks may affect projects in many ways resulting in time delays or cost overruns. Thus, the evaluation of uncertainty is required to get a reliable schedule. This research proposes a method for project scheduling considering risks. Expert judgment is used to identify and analyze risks. Potential risks are identified through Failure Mode Effect Analysis (FMEA). Risks impact is evaluated through fuzzy logic and Monte Carlo Simulation (MCS). The simulation considered the relationship between risks, and risks and activities.

Analyzing heavy metal contamination for one of the high-rate consumption fruits in Iran: A probabilistic health risk assessment

Good health and well-being is one of the sustainable development goals (SDGs) that can be achieved through fruit consumption. This study measured cucumber (Cucumis sativus L.) heavy metal concentrations. Inductively coupled plasma-mass spectrometry (ICP-OES) was used to analyze the samples for heavy metal content. The uncertainty and sensitivity analyses of carcinogenic and non-carcinogenic heavy metal intake via cucumber (Cucumis sativus L.) consumption were assessed by Monte Carlo simulation. The mean ± SD levels of Cu, Pb, Zn, Cd, and As were determined to be 157.87 ± 128.54, 33.81 ± 6.27, 288.46 ± 114.59, 35.22 ± 18.67, and 33.6 ± 18.1 μg/kg, respectively. The 95th percentile of HI related to heavy metal intake via cucumber (Cucumis sativus L.) among children and adults were 2.64 and 1.75, respectively. Also, the 95th percentile of ELCR related to heavy metal were 8.26E-4 and 4.14E-3 among children and adults, respectively. The 95th percentile of LTCR of As among adults and As, Cd, and Pb among children were in the WHO target range (1E-04 to 1E-06) so reducing the concentration of them can help to reduce overall LTCR. When HQ and LTCR are below the cut limits, reducing heavy metals in high-consumption meals is a good way to lower them. In general, due to the wide consumption of various fruits, such as cucumber (Cucumis sativus L.), the concentration of environmental pollutants in their edible tissues should be monitored regularly, and the concentration of pollutants in these tissues should be minimized by proper planning.

Probabilistic safety and reliability studies toward licensing and deploying HTGR technology in the Polish chemical industry

The pivotal aspects of the Probabilistic Safety Assessment (PSA) and reliability studies for the foreseen HTGR-based nuclear-chemical (Nuc-Chem) facilities are discussed. The traditional PSA methodology has been extended to include the mutual dependence of nuclear and chemical systems of the hybrid Nuc-Chem installations, where HTGR serves as a heat source for various chemical processes. The Dynamic Bayesian Network (DBN) approach has been utilized for modeling time sequences of failures, including interactions between nuclear and non-nuclear systems, as well as external hazards. The Global Variance Method (GVM), based on the Sobol indices, has been proposed for uncertainty and sensitivity studies concerning numerous sources of variability in a consistent manner. The paper presents the outcomes and achievements from research oriented toward licensing and deploying High Temperature Gas-cooled Reactors (HTGR) within the Polish chemical industry. The general framework developed in this work for PSA of the hybrid Nuc-Chem facilities can be applied to support the licensing process and safe operation of the Polish chemical plants to be equipped with HTGRs.

A Chronic Aquatic Hazard Assessment for the Perfume Raw Material Octahydro-tetramethyl-naphthalenyl-ethanone.

Octahydro-tetramethyl-naphthalenyl-ethanone (OTNE) is a high-production volume fragrance material used in various down-the-drain consumer products. To assess aquatic risk, the Research Institute for Fragrance Materials (RIFM) uses a tiered data-driven framework to determine a risk characterization ratio, where the ratio of the predicted-environmental concentration to the predicted-no-effect concentration (PNEC) of <1 indicates an acceptable level of risk. Owing to its high production volume and the conservative nature of the RIFM framework, RIFM identified the need to utilize a species sensitivity distribution (SSD) approach to reduce the PNEC uncertainty for OTNE. Adding to the existing Daphnia magna, Danio rerio, and Desmodesmus subspicatus chronic studies, eight new chronic toxicity studies were conducted on the following species: Navicula pelliculosa, Chironomus riparius, Lemna gibba, Ceriodaphnia dubia, Hyalella azteca, Pimephales promelas, Anabaena flos-aquae, and Daphnia pulex. All toxicity data were summarized as chronic 10% effect concentration estimates using the most sensitive biological response. Daphnia magna was the most sensitive (0.032 mg/L), and D. subspicatus was the least sensitive (>2.6 mg/L, the OTNE solubility limit). The 5th percentile hazardous concentration (HC5) derived from the cumulative probability distribution of the chronic toxicity values for the 11 species was determined to be 0.0498 mg/L (95% confidence interval 0.0097-0.1159 mg/L). A series of "leave-one-out" and "add-one-in" simulations indicated the SSD was stable and robust. Add-one-in simulations determined that the probability of finding a species sensitive enough to lower the HC5 two- or threefold was 1/504 and 1/15,300, respectively. Given the high statistical confidence in this robust SSD, an additional application factor protection is likely not necessary. Nevertheless, to further ensure the protection of the environment, an application factor of 2 to the HC5, resulting in a PNEC of 0.0249 mg/L, is recommended. When combined with environmental exposure information, the overall hazard assessment is suitable for a probabilistic environmental risk assessment. Environ Toxicol Chem 2024;00:1-12. © 2024 SETAC.

Risk of rabies reintroduction into the European Union as a result of the Russo-Ukrainian war: A quantitative disease risk analysis.

The importation of rabid animals poses a continual threat to rabies freedom in the European Union (EU). Following the Russian invasion of Ukraine in 2022, the European Commission eased the rules on companion animal importations for Ukrainian refugees through derogations to the EU Pet Travel Scheme (EU PETS). As Ukraine remains endemic for canine rabies, this paper aimed to quantitatively assess whether the change in regulations affected the risk of rabies introduction to the EU. Transmission pathways for both EU PETS and derogations to this scheme were considered, as well as the scenarios of 100% compliance and reduced compliance within both schemes. Stochastic modelling was performed via a Monte Carlo simulation to calculate the median and 95% confidence intervals of the annual risk of rabies entry and the years between rabies entries into the EU. Following 100% compliance, the derogation scheme posed a significantly lower risk at a value of 3.63 × 10-3 (CI 95% 1.18 × 10-3-9.34 × 10-3) rabies entries per year in comparison to EU PETS where the risk was 4.25 × 10-2 (CI 95% 1.44 × 10-2-9.81 × 10-2). Despite a significantly lower risk as compared to EU PETS under 100% compliance, the derogation scheme was more sensitive to a reduction in compliance which resulted in a 74-fold increase in risk. Given this, even under reduced compliance, the annual risk remained lower under the derogation scheme, although this was not statistically significant. The findings of this study suggest that a 4-month period of quarantine, as modelled for the derogation scenario, could reduce the annual risk of rabies entry. This scheme may present a viable solution for the management of companion animal influxes in future crises.

Evolutionary model and risk analysis of ship collision accidents based on complex networks and DEMATEL

To manage and control ship collision risk, this paper aims to develop a quantitative risk analysis approach based on complex networks and Decision-making Trial and Evaluation Laboratory (DEMATEL), to study the evolution of ship collision accidents. Firstly, through the search, selection and analysis of accident investigation reports of ship collisions in the world, 46 Risk Influential Factors (RIFs) were identified, and a network model for the evolution of ship collision was established. Secondly, a risk analysis of the evolution model for ship collision accidents was conducted by utilizing the topology characteristics of the complex network theory. Thirdly, a robustness analysis was used to identify 10 key RIFs involved in ship collisions from a global network perspective, and the grey relation analysis technique was employed to verify the key RIFs. Finally, the DEMATEL method was utilized to identify 11 key RIFs from a perspective of causality, and corresponding risk control measures were proposed to mitigate those key RIFs. The research results provide theoretical support for identifying the key RIFs and controlling the risk transmission of ship collision, and have practical significance for preventing the occurrence of ship collision accidents and ensuring the safe navigation of ships.

Validation of EPG/SAG Rev. 4 of the Kuosheng Nuclear Power Plant Using the MAAP5 Code

The Boiling Water Reactor Owner’s Group released Emergency Procedure Guidelines and Severe Accident Guidelines Revision 4 (EPG/SAG Rev. 4) in 2018. The major improvement to EPG/SAG Rev. 4 was Contingency 1 (Alternate Level/ Pressure Control). Contingency 1 coordinates the reactor pressure vessel (RPV) water level and RPV pressure control action to prolong the availability of steam-driven injections and optimize the transfer to motor-driven systems. In this study, the effectiveness of the EPG/SAG Rev. 4 Contingency 1 strategy was compared with those of EPG/SAG Revision 2 Contingency 1 and Specific Major Incident Guidelines (SMI) using the Modular Accident Analysis Program, Version 5 (MAAP5). SMI was developed by the Taiwan Power Company to mitigate a Fukushima-like accident. The surrogate plant that analyzed is the Kuosheng Nuclear Power Plant (NPP). The Kuosheng NPP is BWR-6 Mark-III containment. MAAP5 is an integral severe accident analysis program that simulates the responses of a light water reactor power plant during a severe accident. This program has been used extensively for probabilistic risk assessments and for verification and validation of mitigation actions specified in severe accident management guidelines. The simulation scenarios were extended loss of alternative-current power and loss of ultimate heat sink. The low-capacity, motor-driven portable pump was the only available system for RPV injection in the first hour of the accident. In this time period, the RPV water level and pressure were controlled by reactor core isolation cooling and safety relief valves. After this study, the strategy of EPG/SAG Rev. 4 Contingency 1 was successfully validated, and the effectiveness of minimum pre-depressurization RPV water level and the low-capacity, motor-driven portable pump were also demonstrated in this study.

Elemental composition of toxic and essential elements in rice-based baby foods from the United States and other countries: A probabilistic risk analysis

Consumption of rice-based foods provides essential nutrients required for infants and toddlers’ growth. However, they could contain toxic and excess essential elements that may affect human health. The study aims to determine the composition of rice-based baby foods in the USA and outside and conduct a multiple-life stages probabilistic exposure and risk assessment of toxic and essential elements in children. Elemental concentrations were measured using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) in thirty-three rice-based baby foods. This includes 2 infant formulas, 11 rice baby cereals, and 20 rice snacks produced primarily in the United States, China, and other countries. A probabilistic risk assessment was conducted to assess risks of adverse health effects. Results showed that infant formula had higher median concentrations of selenium (Se), copper (Cu), zinc (Zn), sodium (Na), magnesium (Mg), calcium (Ca), and potassium (K) compared to rice baby cereal and rice snacks. On the contrary, rice snacks had the highest median concentration of Arsenic (As) (127 μg/kg) while rice baby cereals showed the highest median concentration of Cd (7 μg/kg). A higher lifetime estimated daily intake was observed for samples manufactured in the USA compared to those from China and other countries. Hazard quotient (HQ < 1) values were suggestive of minimal adverse health effects. However, lifetime carcinogenic risk analysis based on total As indicated an unacceptable cancer risk (>1E-04). These findings show a need for ongoing monitoring of rice-based foods consumed by infants and toddlers as supplementary and substitutes for breast milk or weaning food options. This can be useful in risk reduction and mitigation of early life exposure to improve health outcomes.

Development of world famine database for 1840–2019 and risk assessment of its occurrence and severity

Famine still exists in this world, hindering the achievement of Sustainable Development Goal 2: zero hunger. The history and the mechanisms of famine have been broadly studied; however, few studies have focused on quantitative and long-term analyses of the general characteristics of famine. This study analyzes the factors influencing famine and estimates its risks. We developed a historical famine database and estimated the probability and intensity of famine through regression analysis. Herein, we identified that less food production and underdevelopment are related to famine occurrence, and famine tends to be more intense in less urbanized and dryer areas. By extrapolating the regression with future scenarios, we revealed that famine would be less likely to happen in the future mainly due to GDP growth, although conflict would be the key factor of future famine risk. This study is one of the first steps in the quantitative analysis of long-term famine risk.

A new methodology for probabilistic flood displacement risk assessment: the case of Fiji and Vanuatu

This paper presents an enhanced probabilistic flood displacement risk assessment methodology. Several techniques have been proposed to estimate the number of people at risk of being displaced triggered due to climatic extremes. Among these methods, the probabilistic approach is promising for its quantitative nature and versatility at different scales. However, it has so far been limited to assessing loss of housing as the sole cause of displacement. The proposed methodology addresses this limitation by considering two additional elements beyond the traditional evaluation of housing loss: the likelihood of losing means of livelihood, directly included in the computation, and the likelihood of losing access to essential services, such as schools and health centers, provided as a factor to increase the propensity to displace. This new methodology is applied to assess flood disaster displacement risk in Fiji and Vanuatu, where climate change, coupled with the vulnerability of exposed assets, poses an existential threat to these Pacific islands, potentially leading to internal and cross-border population movements. Different climate scenarios were considered: current climate conditions (1979–2016 period), medium-term projected climate conditions (2016–2060), and long-term projected climate conditions (2061–2100). The average annual displacement increases in Fiji and Vanuatu by a factor of 3 and 4, respectively, in the projected long-term pessimistic climate scenario compared to current conditions. Depending on the country and climate change scenario, 20 to 40% of these displacements stem from loss of livelihoods as a dominant factor, highlighting the importance of considering this aspect in the vulnerability approach. The outcomes of these scenarios serve as the foundation for implementing displacement risk adaptation and management measures. This novel quantitative methodology holds significant potential for applications in larger domains and even globally.

Comprehensive identification and risk assessment of regulated and emerging mycotoxins in infant foods and related raw materials and risk management advice: A case study of an infant food company in China

This study evaluated muti-mycotoxins in 199 samples including processed infant foods and raw materials collected randomly from an infant food company and assessed their role in dietary exposure in infants and young children via probabilistic risk assessment. Approximately 79.6 % (74/93) of the processed infant foods and 65.1 % (69/106) of the raw materials were contaminated by mycotoxins, with a mean occurrence level of 3.66–321.8 µg/kg. Deoxynivalenol (DON) and tenuazonic acid (TeA) were the more prevalent mycotoxins detected, based on their higher frequencies and levels across samples. Co-occurrence of more than two mycotoxins was detected in 61.3 % (57/93) of the processed infant foods and 53.8 % (57/106) of the raw materials. Wheat flour and derived products (e.g., infant noodles and infant biscuits) were contaminated with higher contamination levels and a greater variety of mycotoxins than other samples (e.g., infant cereal and rice grains). The estimated daily exposure to OTA, DON, ZEN, and TEN was lower than the corresponding reference health-based guidance values, indicating acceptable health risks. However, the estimated dietary exposure to alternariol monomethyl ether (AME), alternariol (AOH), and tenuazonic acid (TeA) exceeded the corresponding thresholds of toxicological concern values, indicating potential dietary intake risks. Among the various samples, cereals and cereal-based infant foods emerged as the primary contributors to mycotoxin exposure. Further research is advised to address the uncertainties surrounding the toxicity associated with emerging Alternaria mycotoxins and to conduct cumulative risk assessments concerning multiple mycotoxin exposure in infants and young children.