Risk assessment of chemicals an introduction,where to buy emergency kit for car,faraday shields,flood safety kit - PDF Review

It is estimated that more than 13 million workers in the United States are potentially exposed to chemicals that can be absorbed through the skin. NIOSH has developed a strategy for assigning multiple skin notations (SK) capable of delineating between the systemic, direct and immune-mediated effects caused by dermal contact with chemicals.
Contact dermatitis is one of the most common types of occupational illness, with estimated annual costs exceeding $1 billion. Causes of OSD include chemical agents, mechanical trauma, physical agents, and biological agents. Mechanical trauma includes friction, pressure, abrasions, lacerations and contusions (scrapes, cuts and bruises). Dermal absorption is the transport of a chemical from the outer surface of the skin both into the skin and into the body. The rate of dermal absorption depends largely on the outer layer of the skin called the stratum corneum (SC). Research has revealed that skin absorption occurs via diffusion, the process whereby molecules spread from areas of high concentration to areas of low concentration.
As shown in Figure 2, another pathway for chemicals to be absorbed into and through the skin is transcellular, or cell-to-cell, permeation whereby molecules diffuse directly through the corneocytes. Contact dermatitis, also called eczema, is defined as an inflammation of the skin resulting from exposure to a hazardous agent.
Irritant contact dermatitis (ICD) is a non-immunologic reaction that manifests as an inflammation of the skin caused by direct damage to the skin following exposure to a hazardous agent.
Allergic contact dermatitis (ACD) is an inflammation of the skin caused by an immunologic reaction triggered by dermal contact to a skin allergen. Because the symptoms and presentation of ICD and ACD are so similar, it is extremely difficult to distinguish between the two forms of contact dermatitis without clinical testing (e.g. Objectives: We aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments.
Results: Modeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Conclusions: Mechanistic exposure modeling is suitable for screening and prioritizing large numbers of chemicals. The authors have consulted for government agencies such as Health Canada, Environment Canada, the U.K. The primary objective of chemical assessment programs is to identify and regulate chemicals that may cause harmful effects to humans and ecosystems.
Methods to screen and prioritize chemicals for more comprehensive evaluations include “separate” persistence, bioaccumulation, and toxicity (PBT) classification categories and “holistic” multimedia, multipathway mass balance exposure and risk assessment models that simulate key processes in the source–receptor relationship.
In this article, we describe the parameterization and application of a mass balance model to screen and prioritize > 12, 000 organic chemicals using four far-field human exposure and human exposure potential assessment metrics.
Table 1 – Summary of model input parameters and associated Cfs [ranges (medians)] for 12, 619 organic substances. We used confidence factors (Cf), also referred to as distribution factors (Slob 1994), to quantify uncertainty (variance) in model input parameters.
We assumed model input parameters to be log-normally distributed, and because of data gaps, we assigned C?s using professional judgment. Figure 2 illustrates the screening and ranking of 12, 619 organic substances based on four far-field exposure and exposure potential metrics. Figure 2 – Relative ranking of 12, 619 organic substances for far-field model estimates of iFs (A), CUs (B), iRAs (C), and CAs (D). Figure 3 provides a statistical summary of CV for modeled exposure metrics (output) as a function of model input parameters for all chemicals.
Figure 4 – Statistical summary of the modeled output Cfs for far-field human iFs, CUs, iRAs, and CAs for the 12, 619 substances. An internal exposure metric may be the most biologically and toxicologically relevant because the site of toxic action is typically located inside the body. We emphasize that the screening results for “actual” exposures should be interpreted with some skepticism. Approximately 33% of the chemicals have predicted partitioning properties outside of the range of current measurements. This study has provided a quantitative perspective on the uncertainty in exposure data to better address uncertainty in screening-level exposure and risk assessment. EHP is now using Editorial Manager for manuscript submissions. All user accounts have been transferred to Editorial Manager—just log into Editorial Manager and reset your password.
DisclaimerPublication of articles in EHP does not mean that the National Institute of Environmental Health Sciences (NIEHS) condones, endorses, approves, or recommends the use of any products, services, materials, methodology, or policies stated therein. The most common mistakes made by students in this area relate to choosing equipment for measuring (volume in particular) and heating.
The apparatus chosen for measuring the volume of water or water solutions depends on the precision required.
The most precise volumetric glassware used in a school laboratory are volumetric pipettes and burettes. Every first-hand investigation must have a risk assessment prepared BEFORE the investigation is started. The apparatus chosen for measuring the volume of water or water solutions depends on the precision required.A  Consider how precise the measurement needs to be, then choose the glassware.
Sometimes, in our science laboratories, it is possible to use datalogging.A  Data loggers can record temperature, air pressure, humidity, pH and other variables during an investigation.
Laboratory equipment is expensive and must be disposed of when broken.A  Many chemical wastes are toxic. A review of studies carried out to assess the safety of industrial chemical substances has concluded that 11 substances—including certain metals, organic solvents, pesticides, and flame retardants—can now reliably be classified as developmental neuro­toxicants. The study comes at a time when Congress is looking to update laws that regulate chemical testing and risk assessment.
Grandjean and Landrigan advocate taking a precautionary approach to risk assessment that emphasizes preventing early-life exposures to the suspect chemicals—even in the absence of proof of their toxicity. The researchers conducted a literature search for developmental neurotoxicity and reviewed the clinical and epidemiological studies they discovered.
Grandjean and Landrigan point out that low-level exposure to these chemicals might have little or no effect on adults. But Grandjean and Landrigan have been criticized by other scientists for their “strength of evidence” approach. When it comes to passing judgment on individual substances, Guengerich adds, all chemical substances, including the medicines we take, are toxic at some dose and safe at some dose. Listing fluoride as a developmental neurotoxicant in the study was based primarily on research studying exposure to fluoride in areas of the world where it is at a naturally high concentration in drinking water, Guengerich notes. Several chemical company toxicologists cited those deficits among other reasons in declining to comment for the record for this story. The fact of the matter is some chemicals are harmful others are not,the degree of harm also varies. EPA’s conventional approach to risk assessment limits chemical exposure to levels ten times less than those known to cause adverse effects. The possibility that endocrine disrupting chemicals (EDCs) in our environment contribute to hormonally related effects and diseases observed in human and wildlife populations has caused concern among decision makers and researchers alike.
Please enable JavaScript if you wish to use the adjustment of the display, the search function and character size change button. If you want to change the text size remains disabled JavaScript, please use the font size change function of the browser. EHE is the estimated exposures at which chemicals have effects on humans,, calculated on the basis of assumptions about respiration, amounts of meals, body weight and so on.
The practical exposure level for individuals varies depending on chemicals and the living environment (place of living, foods routinely ingested, and so on).
Not all the chemicals that are contained in the air, drinking water and foods are absorbed, and the absorbed chemical substances do not all affect humans and the living body. EHE is obtained by calculating the monitoring data and data on PRTR emission for an assumed case of maximum human exposure in Japan.
Dermal exposure to hazardous agents can result in a variety of occupational diseases and disorders, including occupational skin diseases (OSD) and systemic toxicity.
Studies show that absorption of chemicals through the skin can occur without being noticed by the worker, and in some cases, may represent the most significant exposure pathway. The SC serves an important barrier function by keeping molecules from passing into and out of the skin, thus protecting the lower layers of skin. The spaces between the corneocytes are filled with substances such as fats, oils, or waxes known as lipids. This pathway is usually insignificant because the surface area of the appendages is very small compared to the total skin area. It is the most common form of reported OSD, and represents an overwhelming burden for workers in developed nations.
The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified.
Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of magnitude.
By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncertainty in human exposure and risk assessment in a systematic manner.
Arnot, Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4, Canada. In addition, researchers at the University of Toronto receive funding from NSERC, Environment Canada, Health Canada, Canadian Foundation for Climate and Atmospheric Sciences, the United Nations Environmental Programme, the 7th Framework programme of the European Union, and the CEFIC. Tens of thousands of chemicals require evaluation; however, data and resources are limited (Muir and Howard 2006). The propagation of uncertainty in model input parameters is included through the model calculations, thus providing uncertainty estimates for the four assessment metrics. We compiled a database of 12, 619 organic chemicals including organic chemical substances with reported production in Europe, the United States, Canada, Japan, and other countries that participate in the Organisation for Economic Co-operation and Development. A valuable source of information for obtaining chemical partitioning properties and reaction half-lives for chemical screening is the U.S. Estimated “actual” regional-scale emission rates (EA) are needed for estimates of actual exposures and Level III fate calculations require mode-of-entry information. The Cf is a readily interpretable expression of the variance in a log-normally distributed parameter. The use of C?s “is particularly useful when data are scarce and the magnitude of the uncertainty can only be roughly quantified by giving approximate lower and upper bounds using expert judgment” (Slob 1994). Clearly the greatest contribution to uncertainty in estimates of actual internal (Figure 3D) and external (Figure 3C) human exposure is the estimate of EA. For iF simulations, a number of input parameters contribute to variance including (in general order of magnitude) degradation HL in water, biotransformation HL in fish, degradation HL in air, KOW, and KAW. Boxes represent 25th–75th percentiles and whiskers 5th–95th percentiles, crosses (x) indicate ranges, lines within boxes are medians, and small squares are means. Calculated human concentrations can be integrated with toxicity data such as tissue concentrations, providing direct linkages to high throughput toxicity test data for screening-level risk assessment (Judson et al. Because of the complex issues in estimating EA, a high level of error is expected and these errors in some cases may be beyond what we have attempted to quantify. The screening results using CU and iF provide guidance for exposure hazard potential and the relative information can be useful for benchmarking chemicals before considering industrial production (Cowan-Ellsberry et al. This suggests that a large number of chemicals that are being evaluated may have highly uncertain predicted properties; however, there is no regulatory guidance for assessing such chemicals and for addressing the uncertainty of these predictions. The results indicate that more measured data and models are needed for environmental degradation HLs and biotransformation HLs. These CEHN summaries discuss the potential policy implications of current children’s environmental health research. Conclusions and opinions are those of the individual authors and advertisers only and do not reflect the policies or views of the NIEHS. For a student, this should consist of a two-column table showing all the possible hazards and the controls that will be in place to reduce the potential hazards. Such substances have the potential to cause permanent brain damage in developing fetuses and young children. Current regulations require that, once a chemical is on the market, there must be proof it is toxic before its use is restricted or it is removed from commerce. But many people would also agree that it is shortsighted to summarily restrict useful chemical products that benefit consumers and the economy or to replace a chemical with an alternative that may be more problematic.
The Harvard team concluded that 214 industrial chemicals could be labeled human neurotoxicants.
But the Harvard researchers say the chemicals can cause subtle disruptions in critical brain development during pregnancy or in young children and lead to learning and behavioral disabilities.
Their analysis relies on making generalizations based on studying research results that link a cause, such as exposure to a ubiquitous chemical, with an effect, such as autism.


That is different from an acute work-related exposure or consumption of the low levels added to drinking water and toothpaste to prevent cavities. However, their sentiments were summed up in a statement released by the American Chemistry Council, a trade association of chemical manufacturers. And iodine deficiency has increased significantly, now affecting up to 12% of the US population. EDCs challenge principles traditionally applied in chemical risk assessment and the identification and assessment of these compounds has been a much debated topic during the last decade.
Historically, efforts to control workplace exposures to hazardous agents have focused on inhalation rather than skin exposures. Many commonly used chemicals in the workplace could potentially result in systemic toxicity if they penetrate through the skin (i.e.
Some chemicals can penetrate through these lipid-filled intercellular spaces through diffusion.
However, very slowly permeating chemicals may employ this pathway during the initial stage of absorption.
Epidemiological data indicate that contact dermatitis constitutes approximately 90-95% of all cases of OSD in the United States. Available data indicates that ICD represents approximately 80% of all cases of occupational contact dermatitis. Subsequent exposures of the skin to the allergenic agent may elicit an immunologic reaction resulting in inflammation of the skin. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. Prioritizing Chemicals and Data Requirements for Screening-Level Exposure and Risk Assessment. Environmental Protection Agency, the Climate and Pollution Agency of Norway, and various chemical industry companies and organizations including ExxonMobil Biomedical Sciences, Dow Chemical, Unilever, and the European Oleochemicals and Allied Products Group. In particular, monitoring data that could be used in exposure assessment are available for only 1–2% of the chemicals for which there are at least some toxicity data (Egeghy et al. A primary objective was to use these results as a case study to obtain a better quantitative perspective of the relative uncertainties in chemical information required for screening-level exposure and risk assessment. Far-field exposures are the result of human contact with chemicals in outdoor air, drinking water, and food as a result of general chemical use and release throughout the chemical life cycle and subsequent chemical fate and transport in the physical environment (air, water, soil, and sediment) and food web bioaccumulation. We used the Risk Assessment IDentification And Ranking (RAIDAR) version 2.0 model (Arnot and Mackay 2008) because it calculates all four exposure metrics of interest and it allows for the inclusion of chemical-specific biotransformation rate information for vertebrate species, a process that has been shown to strongly affect exposures (Arnot et al.
This database comprises a broad range of chemical properties and production volumes and is considered to represent much of the diversity of current-use organics [for details, see Supplemental Material, p. Environmental Protection Agency’s (EPA) Estimation Program Interface Suite (EPI Suite™) software program (U.S.
We used production volume estimates and the European Union Technical Guidance Document (EU TGD) emission factor scenarios (European Commission 2003) to estimate EA and chemical mode-of-entry to the environment [see Supplemental Material, pp. We used an analytical method to estimate uncertainty in our modeled exposure data because of its relative simplicity, and because of the extensive data gaps, the uncertainty in most of the chemical parameters can only be approximated using QSA(P)R models and expert judgment (MacLeod et al. A C? of 10 suggests that 95% of all of the values in the distribution are within 10 and 0.1 times the median value. C?s can be calculated from estimates of variance such as SDs for log-transformed, lognormal distributions (?logX; base 10 logarithm) as described by MacLeod et al. EPA 2011) QSA(P)R training and testing sets to guide the application of professional judgment for calculating and assigning screening-level Cfs using Equation 4.
The upper tails of the rankings suggest that all methods have the capacity to differentiate chemicals with relatively higher exposure and exposure potential from all chemicals in the database; however, the actual exposure metrics show larger ranges than the comparative exposure potential metrics because of the greater range of possible EA values. For certain chemicals the CV on iF can be 1 for most input parameters (as noted by the maxima points), the only exceptions being for the degradation HLs in soil and sediment. This order predominantly reflects the greater level of uncertainty associated with estimating exposure rather than exposure potential as a result of the high uncertainties in EA.
EPA and the National Research Council recognize the need to develop, apply, and evaluate a systems approach that fully integrates exposure and toxicity information in a holistic framework for risk assessment (Cohen Hubal 2009). In particular, the EU TGD emission scenarios are considered “realistic worst case” for screening-level objectives; therefore, the “actual” exposure estimates are expected to be conservative, particularly for high production volume chemicals that are used as intermediates or not released to the environment following the assumed emission scenario estimates. We consider estimates of the uncertainty in chemical information only and do not consider variability related to numerous physical and biological processes. It is stressed that the Cfs we selected here to address uncertainty in chemical information (model input parameters) necessarily required professional judgment because of substantial data gaps in measured and predicted chemical information. If uncertainties in other chemical properties are reduced through refined property measurement and QSA(P)R development, chemical assessments will still be highly uncertain because of the prevailing contribution to uncertainty of EA. A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in fish.
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Out of the frying pan and out of the fire: the indispensable role of exposure science in avoiding risks from replacement chemicals.
Evaluating and expressing the propagation of uncertainty in chemical fate and bioaccumulation models. Uncertainty and variability in human exposures to soil contaminants through home-grown food: a Monte Carlo assessment.
Bioaccumulation of organic contaminants in humans: a multimedia perspective and the importance of biotransformation. Comparison of two screening level risk assessment approaches for six disinfectants and pharmaceuticals.
Assessment of chemical screening outcomes based on different partitioning property estimation methods.
Hazards often encountered include burns, scalds, cuts, eye injury, poisoning by ingestion or inhalation and environmental damage. Hazards often encountered include burns, scalds, cuts, eye injury, poisoning by ingestion or inhalation and environmental damage.A  Controls wold include wearing safety equipment, performing investigations in a fume cupboard or ensuring adequate ventilation, selection of appropriate equipment for heating and correct methods of disposal of chemicals. As a result of their findings, the Harvard scientists call for mandated worldwide assessment of the neurotoxicity of chemicals used in commerce. Toxicities of many chemicals used in industry and in consumer products have not been adequately tested, often because they were on the market prior to current regulations.
They add that these effects could hamper academic achievement and economic welfare later in life, as well as lead to criminal behavior. Critics say that a more rigorous assessment of the amount and duration of exposure and factoring in the potency of a substance are needed.
You may be laudatory or critical, but please stay on topic and be respectful of the author and your fellow readers. State of the science reports and risk assessments of potential EDCs have been criticized for not using systematic and transparent approaches in the evaluation of evidence. As a result, assessment strategies and methods are well developed for evaluating inhalation exposures in the workplace; standardized methods are currently lacking for measuring and assessing skin exposures. Sensitizers may not cause immediate skin reactions, but repeated exposure can result in allergic reactions.
The human biotransformation half-life is the second greatest source of uncertainty in estimated concentrations.
Although uncertainty is prevalent because of data gaps and the necessary reliance on models (Arnot and Gobas 2006; Zhang et al.
In addition, we consider external and internal human exposure metrics and discuss recommendations for future research needs to improve assessments. A 95% probability for a log-normally distributed parameter X with a median M is expressed as described by MacLeod et al. Estimates of actual exposures span approximately 15 and 17 orders of magnitude for iRA and CA, respectively.
These results also reflect that the sensitivity of the model exposure calculations to the actual emission rate is 1.
Calculations for CA are generally more uncertain than calculations for iRA because of the additional uncertainty associated with biotransformation HLs in humans. Such an approach is envisioned to identify and reduce uncertainties in current risk assessment approaches (Sheldon and Cohen Hubal 2009). Biomonitoring data, such as those obtained through National Health and Nutrition Examination Survey (NHANES), are valuable sources of exposure information for science and regulatory purposes.
There are many chemicals in the case study that are consistently ranked relatively high or relatively low by all exposure metrics; however, correlations in ranking results are not strong, confirming that the metrics provide different information.
Because of the data gaps and the current screening-level approach, some codependence in uncertainty in model input parameters may occur in some instances; however, given the overall limitations in obtaining robust uncertainty estimates for all input parameters and the generally large uncertainties in model output, the issue of codependence is best addressed at higher tier assessments or when better data are available to characterize uncertainty.
Although continued academic research may result in some modest improvements in estimating EA and the associated uncertainty in this parameter, any substantial improvements to reduce this key source of uncertainty in exposure and risk assessment will ostensibly require coordinated efforts with the chemical regulatory, manufacturing, and use communities.
Part II: Assessing parameter uncertainty and human variability in the calculation of toxicity potentials.
So scientists and regulatory agencies have little understanding of how the compounds might work alone or in combination to cause harm—or whether they are harmless.
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In the fields of medicine and health care, systematic review methodologies have been developed and used to enable objectivity and transparency in the evaluation of scientific evidence for decision making. These chemicals enter the blood stream and cause health problems away from the site of entry. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients.
The Canadian Domestic Substances List categorization highlighted that of the approximately 11, 300 listed organic chemicals merely 3% have measured bioaccumulation data (only in fish), 4% have measured half-lives in air (based on laboratory simulated reactions), and only 12 chemicals have measured biodegradation half-lives in water, soil, or sediment (Arnot and Gobas 2006; Environment Canada 2006).
The EU TGD emission factors (Supplemental Material, Table S1) represent “default” recommended values and are assumed to provide information for the relative release of a chemical to air, water, and soil using physical–chemical properties alone. The sensitivity of a model input parameter quantifies the change in model output as a function of a defined change in the model input parameter. Estimates of exposure potential span approximately 7 and 13 orders of magnitude for iF and CU, respectively.
In other words, the response of the model is linear for this input parameter, so a 2-fold change in EA results in a 2-fold change in iRA and CA. In general, KOW is shown to have a greater CV in exposure metrics than KAW despite a relatively greater degree of uncertainty in KAW than in KOW (Table 1). On average the range associated with a 95% probability in CA covers 8 orders of magnitude (Figure 2D). We compiled the chemical data required to screen and evaluate more than 12, 000 organic chemicals using four metrics for far-field human exposure and exposure potential calculated with a mass balance multimedia model and included the propagation of uncertainty in chemical property data on exposure estimates. Exposure models that include human concentrations can more fully a) maximize the value of biomonitoring data by quantitatively linking emission rates and exposure pathways to internal doses (Woodruff et al.
Clearly, changes to the model or simulation assumptions will result in some changes in the relative ranking and the large-scale uncertainty analysis. We expect uncertainty estimates for information used in chemical evaluations to evolve with the availability of more measured data and improved measurement techniques, better QSA(P)R models, and experience. Email addresses are required so that we can verify you are not a robot overlord and in case we need to contact you about your comment privately.
Lately, such approaches have also been promoted for use in the environmental health sciences and risk assessment of chemicals.
Furthermore, it would be impossible to measure all chemicals in all media to which humans and ecological receptors are exposed. The primary objective of RAIDAR is to provide a consistent evaluative framework for risk and exposure information for priority setting objectives and for comparative chemical assessments. We assumed that the chemicals are used widely and that advective loss from one regional environment is compensated for by advective inflow from a neighboring region. In general, the primary biotransformation HL (HLBIO) in mammals is the input parameter with the second greatest contribution to variance in CA calculations.
By comparison, on average the range associated with a 95% probability in iF covers about 3–4 orders of magnitude (Figure 2A).
2011), and b) complete model evaluations through comparisons with biomonitoring data (Cowan-Ellsberry et al.
For example, the representative human dietary preferences in the model are constant, and the assumed mode-of-entry information is based on default EU TGD emissions scenarios.


Improved information on chemical production and usage and addressing key sources of uncertainty such as biotransformation and environmental degradation HLs and continued model refinement are required to improve chemical screening and prioritization efforts. Systematic review approaches could provide a tool for improving the evaluation of evidence for decision making regarding EDCs, e.g.
These data gaps necessitate the development and application of conceptual, mass balance, and quantitative structure–activity (property) relationship [QSA(P)R] models.
Aggregate exposures are the sum of all of the exposure pathways considered in the assessment. The advective flow residence times in air and water were set to 1011 hr to parameterize the model to satisfy this assumption.
This is because the primary biotransformation HL in the human is a key determinant of the overall residence time in the body for many parent chemicals. For the same reasons discussed earlier for CA, the calculation of CU is also often sensitive to the biotransformation HL input parameter.
Approximately one-third of the chemicals in the case study have predicted physical-chemical partitioning property estimates that are outside of the selected domains. Because of a lack of data and models for parameterizing and simulating far-field human exposures to diverse types of ionogenic chemicals, we did not include dissociation in this case study. Because there are so many chemicals requiring assessment and such extensive data gaps, it is difficult to determine which chemicals pose the greatest exposure and risk and what chemical information contributes the greatest uncertainty in these assessments.
Intake rates do not account for chemical absorption, distribution, metabolism, and excretion (ADME) processes in the receptor of interest; however, internal concentrations do account for ADME processes. For some chemicals, the QSA(P)R-predicted properties are beyond the domain of measured values used to develop and test the QSA(P)Rs.
In general terms, the degradation HL in water, the biotransformation HL in fish and KOW are other parameters contributing the most variance in CU calculations.
The mass balance approach may therefore be more effective when seeking possible alternatives for chemical replacement (Lakind and Birnbaum 2010; Lavoie et al. The implications of this assumption are unquantifiable errors in the exposure estimates for chemicals that are appreciably dissociated at environmental and physiological pH. In this review we discuss the advantages and challenges of applying systematic review methodology in the identification and assessment of EDCs. Actual exposure estimates are applicable in risk-based chemical assessments by comparing concentrations or intake rates with concentrations or rates of intake associated with effect or no-effect levels; however, it is often difficult to obtain reliable actual emission rate information. Briefly, RAIDAR combines user-supplied information on chemical emissions and properties with a mechanistic description of chemical phase distribution, intermedia transport, and degradation processes to calculate concentrations in air, water, soil, and sediment of a generic regional-scale (100, 000 km2) environment. Although it is possible for properties to exist beyond the range of currently measured domains, these QSA(P)R predictions may have substantial errors.
2007), and biotransformation is a key factor for reducing bioaccumulation potential over a wide range of chemical partitioning properties (McLachlan et al. 2010) because uncertainty in chemical information, particularly emission rates, can be included and the results compared. Most notably, the biotransformation HL parameter generally contributes a substantial amount of uncertainty in the calculated human concentrations. There is a general need to improve measurements, models and monitoring data for ionogenic chemicals. The authors certify that their freedom to design, conduct, interpret, and publish this analysis was not compromised by any of the sponsors of the included research.
Exposure models also provide the opportunity to better understand key mechanistic processes in the source–receptor relationship and the model predictions (hypothesis based) can be evaluated with monitoring data (test derived) (Cowan-Ellsberry et al. A consistent, arbitrary unit emission rate (EU; kilograms per hour or nanograms per day) for all chemicals can be used to provide estimates of relative exposure potential for screening and prioritizing chemicals in a hazard-based context.
As a part of this case study, we identified and counted predicted partitioning properties outside of the current measurement domains. High throughput screening-level “near-field” human exposure models are not currently available but are required to better screen human exposures and expand the mass balance framework to more fully quantify source-to-dose relationships.
We replaced predicted properties outside of the measured domains with selected measured “maxima” or “minima” values for these simulations. For more water-soluble and volatile chemicals, urinary excretion and respiration can be relatively quicker routes of elimination; thus for these types of chemicals, HLBIO is not as important in the calculation of CA.
Finally, although the actual chemical emission rate clearly influences exposure and risk, it is not directly included in a PBT assessment. We selected the iF, iRA, CU, and CA metrics to consider a range of possible far-field human exposure assessment objectives. Primary producers and invertebrates bioconcentrate chemicals from their ambient environment of air, water, soil, or sediment, whereas vertebrates bioaccumulate chemicals from their ambient environment and from their diet. RAIDAR calculates concentrations in outdoor air, water, soil, sediment, and biota, including humans, using either EU or EA for a particular simulation.
Further details on the selection of partitioning properties are in the Supplemental Material, pp. Further details on the selection of degradation half-lives are in the Supplemental Material, pp.
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Gestational and chronic low-dose PFOA exposures and mammary gland growth and differentiation in three generations of CD-1 mice. Perinatal exposure to the xenoestrogen bisphenol-a induces mammary intraductal hyperplasias in adult CD-1 mice. Effect of neonatal treatment of rats with potent or weak (environmental) oestrogens, or with a GnRH antagonist, on leydig cell development and function through puberty into adulthood.
Non-monotonic dose effects of in utero exposure to di(2-ethylhexyl) phthalate (DEHP) on testicular and serum testosterone and anogenital distance in male mouse fetuses. Estradiol and bisphenol a stimulate androgen receptor and estrogen receptor gene expression in fetal mouse prostate mesenchyme cells.
Early life exposure to endocrine-disrupting chemicals causes lifelong molecular reprogramming of the hypothalamus and premature reproductive aging. Anxiogenic effects of developmental bisphenol a exposure are associated with gene expression changes in the juvenile rat amygdala and mitigated by soy. Evidence of altered brain sexual differentiation in mice exposed perinatally to low, environmentally relevant levels of bisphenol a. Ethological methods to study the effects of maternal exposure to estrogenic endocrine disrupters: a study with methoxychlor. Prenatal exposure to low doses of the estrogenic chemicals diethylstilbestrol and o,p'-DDT alters aggressive behavior of male and female house mice. Effects of prenatal exposure to low doses of diethylstilbestrol, o,p'DDT, and methoxychlor on postnatal growth and neurobehavioral development in male and female mice.
Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment. Assessing dose-response relationships for endocrine disrupting chemicals (EDCs): a focus on non-monotonicity.



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