The Potentially Affected Fraction as a Measure of Ecological Risk

Traas, Theo P.; Meent, Dik van de; Posthuma, Leo; Hamers, Timo; Kater, Belinda J.; Zwart, Dick de; Aldenberg, Tom

doi:10.1201/9781420032314.ch16

Cited by 52 publications

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“…Multiple pesticides: Methodologies used to estimate acute and chronic risks to organisms from being exposed to the joint action of pesticides were adapted from the multiple substance potentially affected fraction (msPAF) assessment approach by Traas et al (2002). This approach is based on the toxic mode of action (TMoA) of each pesticide and toxicological mixture theories of concentration and response addition.…”

Section: Risk Characterizationmentioning

confidence: 99%

Aquatic risk assessment of pesticides in surface waters in and adjacent to the Everglades and Biscayne National Parks: II. Probabilistic analyses

Carriger

Rand

2008

Ecotoxicology

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A screening-level aquatic probabilistic risk assessment was completed to determine the potential risks of organic pesticides found in surface waters of the C-111 freshwater basin (11 sites at the east boundary of the Everglades National Park) and adjacent estuarine tidal zones (two sites in northeast Florida Bay, one site in south Biscayne Bay) in south Florida. It followed the US Environmental Protection Agency (USEPA) ecological risk framework and focused only on the acute and chronic risks of endosulfan and chlorpyrifos individually and jointly with atrazine, metolachlor, and malathion by comparing distributions of surface water exposure concentrations with the distributions of species toxicity data. The highest risk of acute effects was associated with endosulfan exposure to freshwater arthropods at S-178/site C on the C-111 system, followed by endosulfan effects to estuarine arthropods at Joe Bay in northeast Florida Bay. The highest risk of acute effects from joint toxicity of pesticides was to estuarine arthropods in Joe Bay followed by freshwater arthropods in S-178/site C. For fish, the highest acute risk was for endosulfan at S-178/site C. There was low potential for acute risk of endosulfan to fish at estuarine sites. Joint probability curves indicated that the majority of potential risks to arthropods and fish were due to endosulfan concentrations and not to chlorpyrifos, at S-178/site C. In addition, the highest risk of acute effects for saltwater organisms was in Joe Bay, which receives water from the C-111. The potential risk of chronic effects from pesticide exposures was minimal at fresh- and saltwater sites except at S-178/site C, where endosulfan concentrations showed the highest exceedence of species toxicity values. In general, potential risks were higher in February than June.

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Section: Risk Characterizationmentioning

confidence: 99%

Aquatic risk assessment of pesticides in surface waters in and adjacent to the Everglades and Biscayne National Parks: II. Probabilistic analyses

Carriger

Rand

2008

Ecotoxicology

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“…Mixture toxicity considerations as described by Traas et al [14] were used to estimate the aggregated multisubstance potentially affected fraction (msPAF) of NTOs that may be at risk from exposure to Cry1F þ Cry1Ac cotton in representative-use environments. The potentially affected fraction is the fraction of species affected for a given environmental concentration, and, in the case of toxin mixtures, the nature of toxicological responses and the co-occurrence of the environmental stressors must be considered in arriving at the msPAF [14].…”

Section: Methodsmentioning

confidence: 99%

“…The potentially affected fraction is the fraction of species affected for a given environmental concentration, and, in the case of toxin mixtures, the nature of toxicological responses and the co-occurrence of the environmental stressors must be considered in arriving at the msPAF [14]. For the case of Cry1F þ Cry1Ac proteins, the assumed environmental response is that of response addition in which each toxin acts independently and does not interact at the site of toxin action.…”

Section: Methodsmentioning

confidence: 99%

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A mixture toxicity approach for environmental risk assessment of multiple insect resistance genes

Wolt

2011

Enviro Toxic and Chemistry

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Multiple substance considerations applied to chemical mixtures in ecological risk assessments can be logically extended to nontarget organism (NTO) risk assessment for pyramided trait crops expressing multiple insect resistance genes. A case instance is developed that considers a two-protein pyramid of Cry1F and Cry1Ac synthetic proteins expressed in cotton (Gossypium hirsutum L.). A mixture toxicity approach was used to arrive at the aggregated multisubstance potentially affected fraction (msPAF) of NTOs that may be at risk from exposure to Cry1F + Cry1Ac cotton in representative-use environments. Development of the msPAF for putative susceptible NTOs considered laboratory toxicity data for Lepidoptera expressed in terms of additive mixture toxicity as well as data on in planta expression of the Cry1F and Cry1Ac proteins and their translation into environmental loads and exposure concentrations. The msPAF based on tier 1 estimated environmental concentrations (EECs) and toxicity to Lepidoptera species-used as surrogate data for adverse effects to a putative susceptible species-provided a highly conservative estimate of effects on beneficial species and therefore is a ready means to conduct screening-level NTO risk assessments for pyramided crops.

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“…T HE SSD is an extrapolation method used to extrapolate from laboratory toxicity to realistic environmental toxicity or from single species laboratory toxicity to multi species environmental toxicity by allowing for natural variation among species ECHA, 2011). The SSD is the distribution of toxicity values (OECD, 1992;Traas et al, 2002). These values can, in principle, be taken to be any toxicity test endpoint (NOEC, LC 50 , EC 50 etc.)…”

Section: Outline Of the Thesismentioning

confidence: 99%

Statistical modelling of variability and uncertainty in risk assessment of nanoparticles

Jacobs

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Engineered nanoparticles (ENPs) are used everywhere and have large technological and economic potential. Like all novel materials, however, ENPs have no history of safe use.Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the societal acceptance and safe use of nanotechnology.Risk assessment of ENPs has been hampered by lack of knowledge about ENPs, their environmental fate, toxicity, testing considerations, characterisation of nanoparticles and human and environmental exposures and routes. This lack of knowledge results in uncertainty in the risk assessment. Moreover, due to the novelty of nanotechnology, risk assessors are often confronted with small samples of data on which to perform a risk assessment. Dealing with this uncertainty and the small sample sizes are main challenges when it comes to risk assessment of ENPs. The objectives of this thesis are (i) to perform a transparent risk assessment of nanoparticles in the face of large uncertainty in such a way that it can guide future research to reduce the uncertainty and (ii) to evaluate empirical and parametric methods to estimate the risk probability in the case of small sample sizes.To address the first objective, I adapted an existing Integrated Probabilistic Risk Assessment (IPRA) method for use in nanoparticle risk assessment. In IPRA, statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment in a two-dimensional Monte Carlo algorithm. This method was applied in a human health (nanosilica in food) and an environmental (nanoT iO 2 in water) risk context. I showed that IPRA leads to a more transparent risk assessment and can direct further environmental and toxicological research to the areas in which it is most needed.For the second objective, I addressed the problem of small sample size of the critical effect concentration (CEC) in the estimation of R = P (E xpC > C EC ), where E xpC is the exposure concentration. First I assumed normality and investigated various parametric and non-parametric estimators. I found that, compared to the non-parametric estimators, the parametric estimators enable us to better estimate and bound the risk when sample sizes and/or small risks are small. Moreover, the Bayesian estimator out-ABSTRACT performed the maximum likelihood estimators in terms of coverage and interval lengths.Second, I relaxed the normality assumption for the tails of the exposure and effect distributions. I developed a mixture model to estimate the risk, R = P (E xpC > C EC ), with the assumption of a normal distribution for the bulk data and generalised Pareto distributions for the tails. A sensitivity analysis showed significant influence of the tail heaviness on the risk probability, R, especially for low risks.In conclusion, to really be able to focus the research into the risks of ENPs to the most needed areas, probabilistic methods as used and developed in this thesis need to be implemented on a larger scale. With these methods,...

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The Potentially Affected Fraction as a Measure of Ecological Risk

Cited by 52 publications

References 0 publications

Aquatic risk assessment of pesticides in surface waters in and adjacent to the Everglades and Biscayne National Parks: II. Probabilistic analyses

Aquatic risk assessment of pesticides in surface waters in and adjacent to the Everglades and Biscayne National Parks: II. Probabilistic analyses

A mixture toxicity approach for environmental risk assessment of multiple insect resistance genes

Statistical modelling of variability and uncertainty in risk assessment of nanoparticles

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