A Practical Approach to Exposure Assessment Programs in the Private Sector: A Partial Validation Study of a Qualitative Chemical Exposure Assessment Model

2001 ◽  
Vol 16 (2) ◽  
pp. 257-262 ◽  
Author(s):  
M. L. Dunham ◽  
W. H. Bullock ◽  
R. K. Oestenstad
Keyword(s):  
Private Sector ◽  
Exposure Assessment ◽  
Validation Study ◽  
Chemical Exposure ◽  
Assessment Model ◽  
Practical Approach

The Integrated Model Evaluation System (IMES): A Database for Evaluation of Exposure Assessment Models

1991 ◽  
Vol 24 (6) ◽  
pp. 315-322 ◽  
Author(s):  
S. P. Schreiner ◽  
M. Gaughan ◽  
H. L. Schultz ◽  
R. Walentowicz
Keyword(s):  
Surface Water ◽  
Exposure Assessment ◽  
Model Evaluation ◽  
Evaluation System ◽  
Chemical Exposure ◽  
Integrated Model ◽  
Assessment Model ◽  
Other Information ◽  
Access Information ◽  
Query Systems

The USEPA Office of Health and Environmental Assessment develops methodologies for conducting exposure and risk assessments. Protocols appropriate for specific analyses have been developed to aid in the selection of an exposure assessment model and to assess the validation and uncertainties associated with models used for toxic chemical exposure assessments in surface water, groundwater, and air. A software package has been developed to provide users with a quick and intuitive tool to access information for selected models and applications based on these protocols. The Integrated Model Evaluation System (IMES) is composed of three modules: 1) Selection, query systems for selecting a model based on technical criteria (currently for surface water, non-point source, and groundwater models); 2) Validation, a database containing validation and other information on over 50 models in various media; and 3) Uncertainty, a database demonstrating uncertainty simulations for several surface water models applied to exposure assessments of several chemicals. The selection modules are linked to the uncertainty and validation modules to access information for chosen models. The PC-based software system employs pull-down menus, help screens, and graphics to display its information.

scholarly journals Quantitative risk assessment of Bacillus cereus in pasteurised milk produced in the Slovak Republic

2014 ◽  
Vol 32 (No. 2) ◽  
pp. 122-131 ◽  
Author(s):  
P. Ačai ◽  
Ľ. Valík ◽  
D. Liptáková
Keyword(s):  
Risk Assessment ◽  
Bacillus Cereus ◽  
Exposure Assessment ◽  
Dose Response ◽  
Slovak Republic ◽  
Reporting Rate ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Milk Consumption ◽  
Using Data

Quantitative risk assessment of Bacillus cereus using data from pasteurised milk produced in Slovakia was performed. Monte Carlo simulations were used for probability calculation of B. cereus density at the time of pasteurised milk consumption for several different scenarios. The results of the general case exposure assessment indicated that almost 14% of cartons can contain &gt; 10<sup>4</sup> CFU/ml of B. cereus at the time of pasteurised milk consumption. Despite the absence of a generally applicable dose-response relationship that limits a full risk assessment, the probability of intoxication per serving and the estimated number of cases in the population were calculated for the general exposure assessment scenario using an exponential dose-response model based on Slovak data. The mean number of annual cases provided by the risk assessment model for pasteurised milk produced in Slovakia was 0.054/100 000 population. In comparison, the overall reporting rate of the outbreaks in the EU in which B. cereus toxins were the causative agent was 0.02/100 000 population in 2010. Our assessment is in accordance with a generally accepted fact that reporting data for alimentary intoxication are underestimated, mostly due to the short duration of the illness. &nbsp;

Exposure and Risk Assessment with Respect to Contaminated Soil: Significance of Biomarkers and Bioavailability

1997 ◽  
Vol 16 (4-5) ◽  
pp. 419-432 ◽  
Author(s):  
Urvashi Rangan ◽  
Christine Hedli ◽  
Michael Gallo ◽  
Paul Lioy ◽  
Robert Snyder
Keyword(s):  
Health Risk ◽  
Exposure Assessment ◽  
Health Risks ◽  
Contaminated Soil ◽  
Biological Effects ◽  
Chemical Exposure ◽  
Subsequent Exposure ◽  
Gastrointestinal Barrier ◽  
Exposure Levels

The evaluation of health risk from chemical exposure is evolving in concept and practice. The ability to sensitively detect levels of chemicals in the environment has served as the traditional foundation for determining exposure levels and consequent health risks. More recently, however, other parameters have been constructed to probe the pathway between environmental levels of a chemical and the biological effects of subsequent exposure. Among these, two that are discussed in this paper are bioavailability and biomarker determinations. Chemicals in the environment often are associated with a medium such as airborne particulate, water, or soil. The interaction between the chemical and its medium is dependent on the physicochemical properties of the system. In some cases, such as 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin (TCDD) in soil, the chemical becomes partially and irreversibly bound to the medium. Animalingestion studies of TCDD-contaminated soil suggest that some of the TCDD remains bound to the soil and does not cross the gastrointestinal barrier during digestion, and therefore only a fraction of the TCDD enters the blood and becomes bioavailable. The characterization of bioavailability provides for more accurate exposure assessment. Biomarker information potentially can validate exposure assessment information from bioavailability studies, elucidate specific biological effects from chemical exposure, and investigate genetic susceptibility issues that may increase the likelihood that an individual or population will experience increased health risks. Benzene-induced chromosome damage is discussed as an example of a significant biomarker that has demonstrated the potential for providing information useful for accurately prediction health risk.

scholarly journals Study on Exposure Assessment Model of Dioxane in Shampoo

2012 ◽  
Vol 43 ◽  
pp. 407-412 ◽  
Author(s):  
Guozhong Huang ◽  
Haichao Bu ◽  
Siheng Sun ◽  
Aiji Chen ◽  
Yang Zhou
Keyword(s):  
Exposure Assessment ◽  
Assessment Model

scholarly journals A High Resolution Spatiotemporal Fine Particulate Matter Exposure Assessment Model for the Contiguous United States

2021 ◽  
Author(s):  
Cole Brokamp
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Exposure Assessment ◽  
Fine Particulate Matter ◽  
Model Performance ◽  
Assessment Model ◽  
Fine Particulate ◽  
Prediction Confidence ◽  
Geographic Regions ◽  
Cv Model

Currently available nationwide prediction models for fine particulate matter (PM2.5) lack prediction confidence intervals and usually do not describe cross validated (CV) model performance at different spatiotemporal resolutions and extents. We used 41 different spatiotemporal predictors, including data on land use, meteorology, aerosol optical density, emissions, wildfires, population, traffic, and spatiotemporal indicators to train a machine learning model to predict daily averages of PM2.5 concentrations at 0.75 sq km resolution across the contiguous United States from 2000 through 2020. We utilized a generalized random forest model that allowed us to generate asymptotically-valid prediction confidence intervals and took advantage of its usefulness as an ensemble learner to quickly and cheaply characterize leave-one-location-out (LOLO) CV model performance for different temporal resolutions and geographic regions. Using a variable importance metric, we selected 8 predictors that were able to accurately predict daily PM2.5, with an overall LOLO CV median absolute error (MAE) of 1.20 &mu;gm3, an R2 of 0.84, and confidence interval coverage fraction of 95%. When considering aggregated temporal windows, the model achieved LOLO CV MAEs of 0.99, 0.76, 0.63, and 0.60 &mu;gm3 for weekly, monthly, annual, and all-time exposure assessments, respectively. We further describe the model&rsquo;s CV performance at different geographic regions in the United States, finding that it performs worse in the Western half of the country where there are less monitors. The code and data used to create this model are publicly available and we have developed software packages to be used for exposure assessment. This accurate exposure assessment model will be useful for epidemiologists seeking to study the health effects of PM2.5 across the continential United States, while possibly considering exposure estimation accuracy and uncertainty specific to the the spatiotemporal resolution and extent of their study design and population.

Sign in / Sign up

Export Citation Format

Share Document