• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.587-601
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• 2020

Exposure to hazardous substances occurs through multiple pathways. Aggregated risk assessment, which includes all potential exposure pathways to a single toxicant, is necessary to prevent exposure to harmful substances. We aimed to estimate cadmium and lead exposure through various media, such as food, water, air, smoking, cosmetics, and female hygiene products. This study covered 10,733 subjects from the Seventh Korea National Health and Nutrition Examination Survey(2016, 2017). Dietary exposure was estimated using 24-hour recall data. For water and inhalational exposure, regional variations were considered. Water was classified as tap, bottled, and public water. Inhalational exposure was estimated using the '2014 Time Use Survey' based on daily lifestyle and social status. The frequency and volume of cosmetic usage were randomly approximated by sex and age. Post-menarcheal and premenopausal women were assumed to use feminine hygiene products. Non-carcinogenic aggregated risks were estimated using the Aggregate Risk Index from EPAs and the Total Exposure Hazard Index from Korean government guidelines. For carcinogenic risk assessment, excessive cancer risk was estimated. Ingestion, especially food, was the major route for both cadmium and lead exposure. Smoking was also associated with high cadmium exposure. Exposure to lead from cosmetics was remarkable but not critical. In aggregate risk assessments, median cadmium and lead exposure did not exceed the reference value. Sex, age, smoking status, and income affected exposure levels, unlike to regional variations.

• Analytical Science and Technology
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• v.34 no.2
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• pp.87-98
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• 2021

In this study, we developed the nanoparticle multi-generator by 3D printer fusion deposition modeling (FDM) method that can reliably generate and deliver nanoparticles at a constant concentration for inhalation risk assessment. A white ABS filament was used as the test material, and SMPS was used for concentration analysis such as particle size and particle distribution. In the case of particle size, the particle size was divided by 100 nm or less and 100 to 1,000 nm, and the number of particles concentration, mass concentration, median diameter of particles, geometric average particle diameter, etc were measured. The occurrence conditions were the extruder temperature, the extruding speed of the nozzle, and the air flow rate, and experiments were conducted according to the change of conditions including the manufacturer's standard conditions. In addition, the utility of inhalation risk assessment was reviewed through a stability maintenance experiment for 6 h. As a result of the experiment, the size of the nanoparticles increased as the discharger temperature increased, as the discharge speed of the nozzle increased, and as the air flow rate decreased. Also, a constant pattern was shown according to the conditions. Even when particles were generated for a long time (6 h), the concentration was kept constant without significant deviation. The distribution of the particles was approximately 80 % for particles of 60 nm to 260 nm, 1.7 % for 1 ㎛ or larger, 0.908 mg/㎥ for the mass concentration, 111 nm for MMAD and 2.10 for GSD. Most of the ABS particles were circular with a size of less than 10 nm, and these circular particles were aggregated to form a cluster of grape with a size of several tens to several hundred nm.

• Wind and Structures
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• v.23 no.5
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• pp.449-464
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• 2016

Catastrophe models appraise the natural risk of the built-infrastructure simulating the interaction of its exposure and vulnerability with a hazard. Because of unique configurations and reduced number, mid/high-rise buildings present singular challenges to the assessment of their damage vulnerability. This paper presents a novel approach to estimate the vulnerability of mid/high-rise buildings (MHB) which is used in the Florida Public Hurricane Loss Model, a catastrophe model developed for the state of Florida. The MHB vulnerability approach considers the wind pressure hazard exerted over the building's height as well as accompanying rain. The approach assesses separately the damages caused by wind, debris impact, and water intrusion on building models discretized into typical apartment units. Hurricane-induced water intrusion is predicted combining the estimates of impinging rain with breach and pre-existing building defect size estimates. Damage is aggregated apartment-by-apartment and story-by-story, and accounts for vertical water propagation. The approach enables the vulnerability modeling of regular and complex building geometries in the Florida exposure and elsewhere.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.325-335
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• 2006

This paper evaluates and maps the quality of life in the Atlanta, Georgia metropolitan area in 2000. Three environmental variables from Landsat TM data, four socioeconomic variables from census data, and a hazard-related variable from toxic release inventory (TRI) database were integrated into a geographic information system (GIS) environment for the quality of life assessment. To solve the incompatibility problem in areal units among different data, the four socioeconomic variables aggregated by zonal units were spatially disaggregated into individual pixels. Principal components analysis (PCA) was employed to integrate and transform environmental, socioeconomic, and hazard-related variables into a resultant quality of life score for each pixel. Results indicate that the highest quality of life score was found around Sandy Springs, Roswell, Alphretta, and the northern parts of Fulton County along Georgia 400 whereas the lowest quality of life score was clustered around Smyma of Cobb County, the inner city of Atlanta, and Hartsfield-Jackson International Airport. The results also reveals that normalized difference vegetation index (NDVI) and relative risk from TRI facilities are two versatile indicators of environmental and socioeconomic quality of an urban area in the United States.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.