Exposure assessment review

Reliability of airflow measurements m assessing ventilation systems performance Cobalt - a review of properties, use and levels of exposure A review of respirable crystalline silica - Exposure and control... 

Despite the fact that there exist some differences between both methodologies, the cooperation between the aforementioned tools seems to be advantageous to use in environmental management [7]. Moreover, there are also steps in LCIA that also exist in the risk assessment (i.e., exposure assessment). Therefore, models used in LCIA can be used also to assess human or environmental exposure to chemicals. For that reason LCIA models are also included in the review of models of risk assessment. 

When evaluating the safety of chemicals in humans, it is very important to know the fate of chemicals in the human body and the amounts of exposure in daily activity. This section reviews the metabolic reactions of pyrethroids in humans, and the biomonitoring of pyrethroid metabolites in human urine for the exposure assessment. Mathematical modeling is a useful tool to predict the fate of chemicals in humans. This section also deals with the recent advance of mathematical modeling of pyrethroids to predict the pharmacokinetics of pyrethroids. 

Mr. Don Clay, Director of the Office of Toxic Substances, discussed the premanufacture review procedures and experience with PMNs to date at a meeting of the Organization for Economic Cooperation on Development (OECD) Chemicals Forum in December, (10). He noted that EPA s chemistry, toxicology, and exposure assessment teams normally complete their preliminary evaluation within a week of receipt of a PMN, and, that preliminary assessment eliminates about 50 percent of the substances as chemicals of low concern. They then proceed to structure activity analysis and reasonable worst case assumptions to assess unreasonable risk or the need for more data. 

Also under the IPCS harmonization project, a working group is preparing a harmonized set of principles for the treatment of uncertainty in exposure assessment. The document will review the types of uncertainty analyses used in exposure assessments, evaluate their effectiveness in giving decision-makers the types of information they need, and derive a set of principles for uncertainty analysis (WHO/IPCS 2006). 

US-EPA. 2006. Child Specific Exposure Factors Handbook 2006 (External Review Draft). Washington, DC National Center for Environmental Assessment. Office of Research and Development. Presently undergoing update (In press), http //cfpub.epa.gov/ncea/cfm/recordisplay.cfm7deid = 56747 US-EPA. 2007a. EPA/OPPT Exposure Assessment Tools and Models website, http //www.epa. gov/opptintr/ exposure /pub s/opptexpo. htm... 

Monn C Exposure assessment of air pollutants A review on spatial heterogeneity and indoor/outdoor/personal exposure to suspended particulate matter, nitrogen dioxide and ozone. Atmos Environ 35 1, 2001... 

This paper is written with the aim of providing sufficient background to help understand the mechanism of action of fluoride ion on humans. Current information on the main sources of human exposure to fluoride and current recommendations for Al of fluoride, as well as methods for assessing exposure are reviewed. 

Since risk analysis plays an important role in public policy decision making, efforts have been made to devise a means by which to identify, control, and communicate the risks imposed by agricultural biotechnology. A paradigm of environmental risk assessment was first introduced in the United States by Peterson and Arntzen in 2004. In this risk assessment, a number of assumptions and uncertainties were considered and presented. These include (1) problem formulation, (2) hazard identihcation, (3) dose-response relationships, (4) exposure assessment, and (5) risk characterization. Risk assessment of plant-made pharmaceuticals must be reviewed on a case-by-case basis because the plants used to produce proteins each have different risks associated with them. Many plant-derived biopharmaceuticals will challenge our ability to define an environmental hazard (Howard and Donnelly, 2004). For example, the expression of a bovine-specihc antigen produced in a potato plant and used orally in veterinary medicine would have a dramatically different set of criteria for assessment of risk than, as another example, the expression of a neutralizing nonspecihc oral antibody developed in maize to suppress Campylobacter jejuni in chickens (Peterson and Arntzen, 2004 Kirk et al., 2005). 

Cohen-Hubal EA, Sheldon LS, Burke JM, McCurdy TR, Berry MR, Rigas ML, Zartarian VG, Freeman NC (2000) Children s exposure assessment A review of factors influencing children s exposure, and the data available to characterize and assess that exposure. Environ Health Perspect, 108 475-486. 

A considerable amount of development has happened in the last two decades in the area of measurements, dispersion modelling and exposure assessment studies related to airborne nanoparticles. This is clearly evident from the ever-increasing number of published studies in Europe, and elsewhere in general. This study presented PNCs over 45 sampling locations covering about 30 cities and 15 European countries. While reviewing the literature, it was felt that there are still a number of European countries where nanoparticle-related studies are scarce. 

The exposure assessment characterizes the pathways, magnitude, frequency, and duration of human exposures from various sources. Chapter 5 provides an overview of these components and addresses the principles of exposure assessment in children. General principles of exposure assessment have been reviewed in a number of publications (USEPA, 1992a, 2005a IPCS, 1999a, 2000 Needham et al., 2005). This chapter will focus on the considerations that are important when applying the exposure data to a children s health risk assessment (see Box 2). 

Risk characterization The synthesis of critically evaluated information and data from exposure assessment, hazard identification, and dose-response considerations into a summary that identifies clearly the strengths and weaknesses of the database, the criteria applied to evaluation and validation of all aspects of methodology, and the conclusions reached from the review of scientific information. 

Through the review of approaches to explicit qualitative consideration of contributing sources, this section offers a framework to facilitate and promote a qualitative consideration of the impact of uncertainties on exposure assessment where data are very limited and/or as a prelude to more quantitative characterization of uncertainties. Transparency to address uncertainties and specification of those uncertainties that impact most on outcome are essential to effective decision-making in risk management. 

What is the pedigree of the numbers used as input to an exposure assessment This question deals with issues of who developed the numbers, how they were developed and who has reviewed them. For example, have they been subject to scientific peer review Are the numbers based upon measurements, or are these preliminary estimates based... 

Adequate documentation of all aspects of the uncertainty analysis for the exposure assessment is also critical to ensure transparency to reviewers and stakeholders. This includes sufficient documentation to enable independent replication of results and necessitates detailed description of qualitative and quantitative aspects pertaining to data, scenarios, methods, inputs, models, outputs, sensitivity analysis and interpretation of results. 

Clearness and transparency with respect to the choice of models, methods, assumptions, distributions and parameters are two prerequisites for trust and confidence openness about uncertainties is another. Exposure assessment as an applied science should follow the main scientific desiderata empirical testing, documentation and reproducibility of results, explicit reporting of uncertainty, peer review and an open debate about underlying theories and models. This way, the main attributes for characterizing uncertainty discussed in the last chapter, the appraisal of the knowledge base and the subjectivity of choices, are clarified. 

Transparent documentation of assumptions used in exposure assessments is also critical. Most exposure assessments require making a number of assumptions (often made on the basis of reference to other data or situations thought to be sufficiently similar) because of the difficulty and expense of collecting data for all necessary input parameters. Transparency requires that the presence of these assumptions be acknowledged and their rationale and limitations explained. These steps provide the opportunity for the reasonableness of these assumptions to be judged by those reviewing or using the exposure assessment. 

In the previous sections, different methods for human and ecological risk assessment of mixtures have been reviewed and discussed. Some typical mixture issues were briefly mentioned within the context of this methodological review, but they have not been extensively discussed. Examples of such issues are 1) exposure assessment, 2) sufficient similarity, 3) interactions vs. additivity, 4) QSARs, 5) uncertainties, and 6) risk perception of mixtures. These topics are discussed in more detail in the following sections. 

U.S. EPA (1994), EPA 600/6-88/005Cb. Estimating Exposure to Dioxin-like Compounds, Vol. II Properties, Sources, Occurence and Background Exposure External Review Draft", U.S. EPA, Office of Health and Environmental Assessment, Washington, D.C. 

The model or set of models to be used in the exposure assessment to relate the presence of a substance to human exposure/absorbed dose should be stated. The model s general description should provide enough detail so that the user or reviewer understands the input variables, underlying mathematical algorithms and data transformations and output/results, such that the model can be easily compared to other alternatives. The basis for each model, whether deterministic, empirical or statistical, should be described. The statement of the model should include which variables are measured and which are assumed. A description should be provided of how uncertainties in the parameters and the model itself are to be evaluated and treated. 

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