Hazard Characterization Research Articles

Specific effects on the thyroid relevant for performing a dietary cumulative risk assessment of pesticide residues: 2024 update.

EFSA updated its previous work on the establishment of specific effects that are considered relevant for grouping pesticide residues targeting the thyroid and for performing the retrospective assessment of dietary cumulative risk (CRA). The two specific effects already selected in 2019 leading to the two cumulative assessment groups (CAGs) 'hypothyroidism' and 'C-cell hypertrophy, hyperplasia and neoplasia' were reconfirmed. Compared to 2019, the list of indicators that can be used to identify these specific effects was refined to only include histopathological changes. In a second phase of the work, data will be extracted on indicators of the specific effects from the dossiers on active substances (a.s.) used as plant protection products. The criteria for including a.s. into CAGs were also updated, together with the hazard characterisation methodology and the lines of evidence for assessing CAG-membership probabilities. The tasks related to the data extraction and the establishment of the CAGs on hypothyroidism and on C-cell hypertrophy, hyperplasia and neoplasia are beyond the scope of this report. This part of the CRA process has been outsourced and will be the subject of a separate report.

Per- and Polyfluoroalkyl Substances: Impacts on Morphology, Behavior and Lipid Levels in Zebrafish Embryos.

The presence of per- and polyfluoroalkyl substances (PFASs) in aquatic environments is often persistent and widespread. Understanding the potential adverse effects from this group of chemicals on aquatic communities allows for better hazard characterization. This study examines impacts on zebrafish (Danio rerio) embryo physiology, behavior, and lipid levels from exposure to perfluorooctanoic acid (PFOA), perfluorohexane sulfonate (PFHxS), and heptadecafluorooctanesulfonic acid (PFOS). Embryos were exposed to lethal and sublethal levels of each chemical and monitored for alterations in physiological malformations, mortality, lipid levels, and behavior (only PFOA and PFHxS). The predicted 50% lethal concentrations for 120 hpf embryos were 528.6 ppm PFOA, 14.28 ppm PFHxS, and 2.14 ppm PFOS. Spine curvature and the inability of the 120 hpf embryos to maintain a dorsal-up orientation was significantly increased at 10.2 ppm PFHxS and 1.9 ppm PFOS exposure. All measured 120 hpf embryo behaviors were significantly altered starting at the lowest levels tested, 188 ppm PFOA and 6.4 ppm PFHxS. Lipid levels decreased at the highest PFAS levels tested (375 PFOA ppm, 14.4 PFHxS ppm, 2.42 ppm PFOS). In general, the PFAS chemicals, at the levels examined in this study, increased morphological deformities, embryo activity, and startle response time, as well as decreased lipid levels in 120 hpf zebrafish embryos.

Hazard and risk characterization of 56 structurally diverse PFAS using a targeted battery of broad coverage assays using six human cell types

Per- and poly-fluoroalkyl substances (PFAS) are extensively used in commerce leading to their prevalence in the environment. Due to their chemical stability, PFAS are considered to be persistent and bioaccumulative; they are frequently detected in both the environment and humans. Because of this, PFAS as a class (composed of hundreds to thousands of chemicals) are contaminants of very high concern. Little information is available for the vast majority of PFAS, and regulatory agencies lack safety data to determine whether exposure limits or restrictions are needed. Cell-based assays are a pragmatic approach to inform decision-makers on potential health hazards; therefore, we hypothesized that a targeted battery of human in vitro assays can be used to determine whether there are structure-bioactivity relationships for PFAS, and to characterize potential risks by comparing bioactivity (points of departure) to exposure estimates. We tested 56 PFAS from 8 structure-based subclasses in concentration response (0.1–100 μM) using six human cell types selected from target organs with suggested adverse effects of PFAS – human induced pluripotent stem cell (iPSC)-derived hepatocytes, neurons, and cardiomyocytes, primary human hepatocytes, endothelial and HepG2 cells. While many compounds were without effect; certain PFAS demonstrated cell-specific activity highlighting the necessity of using a compendium of in vitro models to identify potential hazards. No class-specific groupings were evident except for some chain length- and structure-related trends. In addition, margins of exposure (MOE) were derived using empirical and predicted exposure data. Conservative MOE calculations showed that most tested PFAS had a MOE in the 1–100 range; ∼20% of PFAS had MOE<1, providing tiered priorities for further studies. Overall, we show that a compendium of human cell-based models can be used to derive bioactivity estimates for a range of PFAS, enabling comparisons with human biomonitoring data. Furthermore, we emphasize that establishing structure-bioactivity relationships may be challenging for the tested PFAS.

Combined in vitro and in silico mechanistic approach to explore the potential of Alternaria mycotoxins alternariol and altertoxin II to hamper γH2AX formation in DNA damage signaling pathways

Risk assessment of food and environmental contaminants is faced by substantial data gaps and novel strategies are needed to support science-based regulatory actions. The Alternaria mycotoxins alternariol (AOH) and altertoxin II (ATXII) have garnered attention for their possible genotoxic effects. Nevertheless, data currently available are rather scattered, hindering a comprehensive hazard characterization. This study combined in vitro/in silico approaches to elucidate the potential of AOH and ATXII to induce double-strand breaks (DSBs) in HepG2 cells. Furthermore, it examines the impact of co-exposure to AOH and the DSB-inducing drug doxorubicin (Doxo) on γH2AX expression. AOH slightly increased γH2AX expression, whereas ATXII did not elicit this response. Interestingly, AOH suppressed Doxo-induced γH2AX expression, despite evidence of increased DNA damage in the comet assay. Building on these observations, AOH was postulated to inhibit γH2AX-forming kinases. Along this line, in silico analysis supported AOH potential interaction with the ATP-binding sites of these kinases and immunofluorescence experiments showed decreased intracellular phosphorylation events. Similarly, in silico results suggested that ATXII might also interact with these kinases. This study emphasizes the importance of understanding the implications of AOH-induced γH2AX expression inhibition on DNA repair processes and underscores the need for caution when interpreting γH2AX assay results.

Quantitative microbial risk assessment of Salmonella in fresh chicken patties

Quantitative microbial risk assessment (QMRA) has witnessed rapid development within the context of food safety in recent years. As a means of contributing to these advancements, a QMRA for Salmonella spp. in fresh chicken patties for the general European Union (EU) population was developed. A two-dimensional (Second Order) Monte-Carlo simulation method was used for separating variability and uncertainty of model’s parameters. The stages of industrial processing, retail storage, domestic storage, and cooking in the domestic environment were considered in the exposure assessment. For hazard characterization, a dose-response model was developed by combining 8 published dose-response models using a Pert distribution for describing uncertainty. The QMRA model predicted a mean probability of illness of 1.19*10−4 (5.28*10−5 – 3.57*10−4 95 % C.I.), and a mean annual number of illnesses per 100,000 people of 2.13 (0.96 – 6.59 95 % C.I.). Moreover, sensitivity analysis was performed, and variability in cooking preferences was found to be the most influential model parameter (r = −0.39), followed by dose-response related variability (r = 0.22), and variability in the concentration of Salmonella spp. at the time of introduction at the processing facility (r = 0.11). Various mitigation strategy scenarios were tested, from which, “increasing the internal temperature of cooking” and “decreasing shelf life” were estimated to be the most effective in reducing the predicted risk of illness. Salmonella-related illnesses exhibit particularly high severity, making them some of the most prominent zoonotic diseases in the EU. Regular monitoring of this hazard in order to further highlight its related parameters and causes is a necessary procedure. This study not only provides an updated assessment of Salmonella spp. risk associated with chicken patties, but also facilitates the identification of crucial targets for scientific investigation and implementation of real-world intervention strategies.

Application of Machine Learning in the Characterization and Classification of Hazards in Underwater Operations in the Oil and Gas Industry

Application of Machine Learning in the Characterization and Classification of Hazards in Underwater Operations in the Oil and Gas Industry

Enabling novel paradigms: a biological questions-based approach to human chemical hazard and drug safety assessment.

Throughput needs, costs of time and resources, and concerns about the use of animals in hazard and safety assessment studies are fueling a growing interest in adopting new approach methodologies for use in product development and risk assessment. However, current efforts to define "next-generation risk assessment" vary considerably across commercial and regulatory sectors, and an a priori definition of the biological scope of data needed to assess hazards is generally lacking. We propose that the absence of clearly defined questions that can be answered during hazard assessment is the primary barrier to the generation of a paradigm flexible enough to be used across varying product development and approval decision contexts. Herein, we propose a biological questions-based approach (BQBA) for hazard and safety assessment to facilitate fit-for-purpose method selection and more efficient evidence-based decision-making. The key pillars of this novel approach are bioavailability, bioactivity, adversity, and susceptibility. This BQBA is compared with current hazard approaches and is applied in scenarios of varying pathobiological understanding and/or regulatory testing requirements. To further define the paradigm and key questions that allow better prediction and characterization of human health hazard, a multidisciplinary collaboration among stakeholder groups should be initiated.

Metabolites in the regulatory risk assessment of pesticides in the EU.

A large majority of chemicals is converted into metabolites through xenobiotic-metabolising enzymes. Metabolites may present a spectrum of characteristics varying from similar to vastly different compared with the parent compound in terms of both toxicokinetics and toxicodynamics. In the pesticide arena, the role of metabolism and metabolites is increasingly recognised as a significant factor particularly for the design and interpretation of mammalian toxicological studies and in the toxicity assessment of pesticide/metabolite-associated issues for hazard characterization and risk assessment purposes, including the role of metabolites as parts in various residues in ecotoxicological adversities. This is of particular relevance to pesticide metabolites that are unique to humans in comparison with metabolites found in in vitro or in vivo animal studies, but also to disproportionate metabolites (quantitative differences) between humans and mammalian species. Presence of unique or disproportionate metabolites may underlie potential toxicological concerns. This review aims to present the current state-of-the-art of comparative metabolism and metabolites in pesticide research for hazard and risk assessment, including One Health perspectives, and future research needs based on the experiences gained at the European Food Safety Authority.

Characterization of flood and drought hazards on the Gereb-Geba water supply dam in the semi-arid northern Ethiopian highlands

Evaluating the flood and drought hazards provides vital information for sustainable water resources management, particularly in semi-arid, water-deficit environments. Most prior studies were limited in exploring the flood and drought hazards, which are important for early warning systems and preparedness. This study characterized the hydrological extreme hazards on the Gereb-Geba reservoir, namely the Suluh, Genfel, and Agula rivers. Flood frequency analysis was performed using the fitted flood frequency distribution in MATLAB. The 2D hydrodynamic model HEC-RAS was implemented to produce a flood-inundation map. Meteorological, agricultural, and hydrological droughts were analyzed using the Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), and Streamflow Drought Index (SDI), respectively. Using the Generalized Extreme Value (GEV), the estimated flood magnitude showed an increasing tendency in all the rivers across all the return periods (2-, 5-, 10-, 20-, 50-, and 100-years). The reservoir inundated an area of 12.8 km2 at an elevation of 1830 m.a.s.l. with a water depth of 80 m at the outlet. Suluh experienced more severe to extreme hydrological drought episodes than the Agula and Genfel rivers. Severe to extreme meteorological droughts were also observed in the respective catchments. Moreover, severe agricultural drought prevalence was also detected across all the river catchments. This study provides vital and comprehensive flood and drought information for water resources planning, management, and development.

A landscape-based ecological hazard evaluation and characterization of influencing factors in Laos

The study of the spatiotemporal evolution of landscape ecological hazard and human and natural influences is essential for conservative management and regional sustainable development. This study applied a landscape pattern analysis method and geodetector to multi-source data for 2000, 2010, and 2020 to analyze changes in and drivers of landscape ecological hazard in Laos. The results indicated that: (1) There were more prominent changes in landscape types in Laos. Forest area decreased, whereas the areas of other landscape types increased. There was an overall steady change in the landscape patterns of Laos. Besides for significant changes in the artificial surface landscape index, landscape indices remained stable; (2) The cumulative high and extreme ecological hazard areas increased by 1,947.81 km2, whereas the cumulative areas of low and minimal ecological hazard decreased by 8,461.8 km2. Areas of low and moderate ecological hazard accounted for &amp;gt; 85% of the total area. Areas of low ecological hazard were mainly in the northwest and southeast. The area of high ecological hazard was concentrated in the central and northeastern regions. The distributions of different landscape ecological hazards in Laos during the study period were similar, with general patterns of decreasing hazard from north to south; (3) A positive Moran’s I of landscape ecological hazard in Laos was obtained. While the agglomeration effect was pronounced, it decreased over time, resulting in a weakening in spatial autocorrelation. A significant positive autocorrelation was observed in the spatial distribution of landscape ecological hazard in the study area. Agglomerated areas of high and low ecological hazard were mainly concentrated in the northeast and southeast, respectively; (4) The spatiotemporal evolution of landscape ecological hazard in Laos over the last 20 years could be attributed to interactions between natural and anthropogenic influences. Natural influences were a significant driver of changes to landscape ecological hazard in Laos, with annual precipitation and average temperature being the most significant. Anthropogenic influences, including socioeconomic factors and regional accessibility, significantly impacted local ecological deterioration in Laos.

High-level characterisation and mapping of key climate-change hazards in European coastal cities

Sea-level and temperature rise due to climate change exacerbate existing climate-related hazards in coastal areas. In this work, an approach based on Coastal City Living Labs is developed to carry out a high-level characterisation of key climate-related hazards for ten European coastal cities. The Coastal City Living Labs are conceived as physical and virtual spaces in which stakeholders meet for collaboration, co-creation and co-ideation to solve the challenges posed by climate-related hazards. The information on past extreme climate events and local knowledge thus obtained are combined to identify the main hazards for each city. Subsequently, these hazards are categorised based on the recommendations of the recent Sixth Assessment Report from the Intergovernmental Panel on Climate Change. The main climate-related hazards are found to be storms, coastal and land flooding, and coastal erosion. Importantly, significant differences are found between the specific cities as to the main hazards of concern. Even within the same coastal city, relevant differences are found in respect of the main hazards, depending on the area considered. It follows that granularity in the characterisation of the hazards is fundamental in designing mitigation measures. To clarify the spatial extent of the different hazards in each coastal city, bespoke maps are produced through GIS software. In addition to the interest of the results for the specific cities investigated, this work provides a methodology to assess climate-related hazards in coastal areas using Coastal City Living Labs, which can be applied elsewhere.

Predicting Listeria monocytogenes virulence potential using whole genome sequencing and machine learning

Contamination with food-borne pathogens, such as Listeria monocytogenes, remains a big concern for food safety. Hence, rigorous and continuous microbial surveillance is a standard procedure. At this point, however, the food industry and authorities only focus on detection of Listeria monocytogenes without characterization of individual strains into groups of more or less concern. As whole genome sequencing (WGS) gains increasing interest in the industry, this methodology presents an opportunity to obtain finer resolution of microbial traits such as virulence. Within this study, we therefore aimed to explore the use of WGS in combination with Machine Learning (ML) to predict L. monocytogenes virulence potential on a sub-species level.The WGS datasets used in this study for ML model training consisted of i) national surveillance isolates (n = 169, covering 38 MLST types) and ii) publicly available isolates acquired through the GenomeTrakr network (n = 2880, spanning 80 MLST types). We used the clinical frequency, i.e., ratio of the number of clinical isolates to total amount of isolates, as estimate for virulence potential. The predictive performance of input features from three different genomic levels (i.e., virulence genes, pan-genome genes, and single nucleotide polymorphisms (SNPs)) and six machine learning algorithms (i.e., Support Vector Machine with a linear kernel, Support Vector Machine with a radial kernel, Random Forrest, Neural Networks, LogitBoost, and Majority Voting) were compared.Our machine learning models predicted sub-species virulence potential with nested cross-validation F1-scores up to 0.88 for the majority voting classifier trained on national surveillance data and using pan-genome genes as input features. The validation of the pre-trained ML models based on 101 previously in vivo studied isolates resulted in F1-scores up to 0.76. Furthermore, we found that the more rapid and less computationally intensive raw read alignment yields comparably accurate models as de novo assembly.The results of our study suggest that a majority voting classifier trained on pan-genome genes is the best and most robust choice for the prediction of clinical frequency. Our study contributes to more rapid and precise characterization of L. monocytogenes virulence and its variation on a sub-species level. We further demonstrated a possible application of WGS data in the context of microbial hazard characterization for food safety. In the future, predictive models may assist case-specific microbial risk management in the food industry. The python code, pre-trained models, and prediction pipeline are deposited at (https://github.com/agmei/LmonoVirulenceML).

Geomorphic flood hazard mapping: from floodplain delineation to flood hazard characterization

ABSTRACTRecent studies show how geomorphic descriptors, retrieved from digital elevation models (DEMs), can be used for flood hazard mapping. As they strictly depend on the accuracy of the input DEMs and reference flood hazard maps used for training, DEM-based flood hazard models may display severe inconsistencies. Our study shows the application of two advanced DEM-based models to a large study area, and presents two main innovative points. First, the delicate tasks of appropriately selecting the input DEM and flood hazard map are specifically addressed with newly defined methods. Second, the ability of DEM-based models to exploit their natural features to enhance flood hazard mapping over the study region is investigated. Our results show (a) the benefits of considering multiple geomorphic descriptors, (b) the potential of DEM-based models for completing the information of imperfect reference flood hazard maps, and (c) the advantages of continuous representation of hazard over binary flood maps.

The footprint of a historical paleoearthquake: the sixth-century-CE event in the European western Southern Alps

Abstract. Low-deformation regions are characterized by long earthquake recurrence intervals. Here, it is fundamental to extend back the record of past events as much as possible to properly assess seismic hazards. Evidence from single sites or proxies may be not compelling, whereas we obtain a more substantial picture from the integration of paleo- and archeoseismic evidence at multiple sites, eventually supplemented with historical chronicles. In the city of Como (N Italy), we perform stratigraphic and sedimentological analyses on the sedimentary sequences at Via Manzoni and we document earthquake archeological effects at the Roman baths by means of structure from motion and field surveys. Radiocarbon dating and chronological constraints from the archeological site allow us to bracket the time of occurrence of the deformations to the sixth century CE. We interpret the observed deformations as due to earthquake ground shaking and provide constraints on the lower threshold for the triggering of such evidence. We move toward a regional view to infer possible relevant seismic sources by exploiting a dataset of published paleoseismic evidence in Swiss and N Italy lakes. We perform an inverse grid search to identify the magnitude and location of an earthquake that can explain all the positive and negative evidence consistent with the time interval of the event dated at Como. Our results show that an earthquake (minimum Mw 6.32) with epicenter located at the border between Italy and Switzerland may account for all the observed effects; a similar event in the sixth century CE has not been documented so far by historical sources. Our study calls for the need to refine the characterization of the local seismic hazard, especially considering that this region seems unprepared to face the effects of an earthquake size similar to the one inferred for the sixth-century-CE event.

Risk Assessment for Hepatobiliary Toxicity Liabilities in Drug Development.

Risk assessment of hepatobiliary toxicities represents one of the greatest challenges and, more often than not, one of the most rewarding activities in which toxicologic pathologists can partake, and often times lead. This is in part because each liver toxicity picture is a bit different, informed by a broad range and diversity of relevant data, and also in part because the heavily relied upon animal models are imperfect regarding predictivity of hepatic effects in humans. Following identification and characterization of a hepatotoxicity hazard, typically in nonclinical toxicology studies, a holistic and integrated assessment of liver-relevant endpoints is conducted that typically incorporates ADME (absorption, distribution, metabolism, and excretion) information (ideally, including extensive transporter data, exposure margins, and possibly concentration of parent/metabolite at region of injury), target expression/function, in silico prediction data, in vitro hepatocyte data, liver/circulating biomarkers, and importantly, species specificity of any of these data. Of course, a thorough understanding, developed in close partnership with clinical colleagues, of the anticipated liver disease status of intended patient populations is paramount to hepatic risk assessment. This is particularly important since the likelihood of translatable determinant hepatic events observed in nonclinical models to occur in humans has been reasonably well established.

Correlation between seismic intensity measures and engineering demand parameters of reinforced concrete frame buildings through nonlinear time history analysis

In this paper, the correlation between different seismic intensity measures (IM) and engineering demand parameters (EDP) of reinforced concrete (RC) buildings was evaluated by means of nonlinear dynamic analyses (NLDA). The Costa Rican ground motion database and four RC buildings (4-, 6-, 8- and 10-stories) were considered in this research. Estimations of conventional IMs were derived directly from the ground motion records as well as from the response of a single degree of freedom (SDOF) linear oscillator, with a period equal to that of the fundamental period of the buildings. NLDAs were performed using unscaled and scaled records to account for different intensity levels, and the performance of the buildings was characterized in terms of three EDPs: the average inter-story drift ratio, the maximum inter-story drift ratio, and the Park & Ang damage index. Results demonstrate a significant improvement in the correlation between IMs and EDPs when the dynamic characteristics of the structure are accounted for through the response of the SDOF oscillator. On the other hand, the peak ground velocity turned out to be an effective IM, independent of the dynamic characteristics of the buildings. This is very useful when assessing potential seismic damage both for immediate decision-making and for the characterization of the seismic hazard of a region.

The ToxCast pipeline: updates to curve-fitting approaches and database structure.

Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb. Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting. Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.

Qualitative welfare risks of cows offered to a Dutch mobile slaughter unit

In the Netherlands, a pilot was initiated of a mobile slaughter unit (MSU) for the killing of cull dairy cattle not fit for transport but suitable for slaughter, in order to save valuable meat. The Office for Risk Assessment &amp;amp; Research (BuRO) was asked to assess the risks for animal welfare. As a thorough risk assessment would have been very time consuming, a qualitative framework was used instead. The goal of the current study was to qualitatively describe the relevant risks for cow welfare involved in the use of an MSU compared with current practice by carrying out a rapid comparative risk assessment of animal welfare. The assessment framework consisted of the following steps: identification and description of scenarios, followed by assessment and comparison of the most relevant animal welfare risks in these scenarios, including hazard identification, hazard characterization, exposure, and characterization of the risk to animal welfare. Two main scenarios were identified, one with and one without an MSU. The second scenario was split into three sub-scenarios: killing on the farm/in a housing unit, emergency slaughter, and conventional transport to the slaughterhouse. The most relevant risks associated with operating an MSU were as follows: leaving the cow alive on the farm when it was not fit for slaughter; forcing the cow to walk to and into the MSU (however, this risk is likely higher under conventional transport of unfit cows); and insufficient stunning and bleeding, leading to questionable unconsciousness (however, this risk is likely higher in an emergency slaughter scenario). The MSU is a means of preventing the exacerbation of welfare deterioration in cows that are unfit for transport but fit for slaughter, and it reduces exposure to stressors (hazards) that are conventionally present during transport and at a stationary slaughterhouse. This rapid comparative risk assessment of animal welfare supported swift decision-making: the national competent authority (i.e., the NVWA in the Netherlands) and policymakers were able to improve and develop risk-mitigating actions and to decide on allowing the use of an MSU. When appropriately designed and used, and with sufficient supervision, mobile slaughter facilities can reduce welfare risks in cull dairy cows that are unfit for transport but fit for slaughter.

MONTE CARLO SIMULATION OF BARRIER-ISLAND SYSTEMS AND TSUNAMI HAZARDS

Robust characterization of the future tsunami hazard is critically important for resilient planning and engineering in coastal communities prone to tsunami inundation. The hazard from earthquake-generated tsunami waves is not only determined by the earthquake's characteristics and distance to the earthquake area, but also by the geomorphology of the nearshore and onshore areas, which can change over time. In coastal hazard assessments, a changing coastal environment is commonly taken into account by increasing the sea-level to projected values (static). However, sea-level changes and other climate-change impacts influence the entire coastal system causing morphological change (dynamic). Here, we present the modeling framework and results initially published in Weiss et al. (2022), which employs within a Monte Carlo framework the barrier island-marsh, lagoon- marsh evolution model of Lorenzo-Trueba and Mariotti (2017) and the tsunami model Geoclaw (e.g., LeVeque et al. 2011). We compare the runup of the same suite of earthquake-generated tsunamis to a barrier system for statically adjusted and dynamically adjusted sea level and bathymetry over the period from 2000 to 2100. We employ Representative Concentration Pathways 2.6 and 8.5 without and with treatment of Antarctic ice-sheet processes (e.g., Kopp et al. 2017) as different sea-level projections.

Extending Multi-Pathway Human Health Risk Assessment from Regional to Country-Wide—A Case Study on Kuwait

Air pollution has emerged as a pressing global issue in recent decades. While criteria pollutants and greenhouse gases contribute to the problem, this article explicitly addresses hazardous air pollutants (HAPs). This work estimates the country-wide cumulative human health impacts from exposure to HAPs. Kuwait is used as the case study due to data availability and non-fragmentation of data. At present, the evaluation of multi-pathway human health risks arising from exposure to HAPs is incomplete, as indirect pathways have not been considered. Furthermore, only a few HAPs, such as benzene, have established ambient air quality standards specifically intended to safeguard human health, leaving many HAPs unregulated. This study considers several pathways (both direct and indirect) and various environmental media (air, water, plants, soil, and animal tissue). The findings indicate that cumulative health risks in the coastal air quality zone are within acceptable limits but are notably higher when compared to the other air quality zones. For cancer risks, only the Ahmadi Hospital, with a cancer risk of 1.09 × 10−5 for the resident adult exposure scenario, slightly exceeds the acceptable risk level of 1 × 10−5. The proposed methodology integrates the results from a country-wide emissions inventory composed of different air quality zones, air dispersion and deposition modeling, multi-pathway transport-and-fate analysis, exposure quantification, and health risk and hazard characterization. It also extends and adapts EPA methodologies initially designed for hazardous waste combustion facilities to additional emission sources and provides a case study for a region seldom subjected to such human health risk assessments.