The BEAM-project: prediction and assessment of mixture toxicities in the aquatic environment

Backhaus, Thomas; Altenburger, Rolf; Arrhenius, Åsa; Blanck, Hans; Faust, Martin L.; Finizio, Antonio; Gramatica, Paola; Grote, Matthias; Junghans, Marion; Meyer, Wiebke; Pavan, Manuela; Porsbring, Tobias; Scholze, Martin; Todeschini, Roberto; Vighi, Marco; Walter, Helge; Grimme, L. Horst

doi:10.1016/j.csr.2003.06.002

Cited by 108 publications

(56 citation statements)

References 28 publications

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“…The 95% confidence bands of the predictions were estimated by the re-sampling method described in the SI. The errors of all input parameters of eq 15 are assumed to follow a log-normal distribution, except for the parameter slope, the error of which is assumed to be normally distributed.The IA prediction is always lower than the CA prediction, which is in accord with mixture theory (32,62). Compared to the upper confidence limit of IA, CA predictions differ by a maximum factor of 1.3 during the whole period of observation.…”

supporting

confidence: 69%

“…This is particularly relevant for herbicides with similar modes of action (22,(25)(26)(27). For this reason, several authors have discussed the necessity of including mixtures of pesticides in the water quality regulation (18,22,(28)(29)(30)(31)(32). However, so far only Canada (13) has proposed WQC for pesticide mixtures, and then only for the short-term occurrence of herbicides (acute WQC).…”

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confidence: 99%

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Including Mixtures in the Determination of Water Quality Criteria for Herbicides in Surface Water

Chèvre

Loepfe

Singer

et al. 2005

Environ. Sci. Technol.

118

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Monitoring programs throughout America and Europe have demonstrated the common occurrence of herbicides in surface water. Nevertheless, mixtures are rarely taken into account in water quality regulation. Taking mixtures into account is only feasible if the water quality criteria (WQC) of the single compounds are derived by a common and consistent methodology, which overcomes differences in data quality without settling on the lowest common denominator but making best use of all available data. In this paper, we present a method of defining a risk quotient for mixtures of herbicides with a similar mode of action (RQ m ). Consistent and comparable WQC are defined for single herbicides as a basis for the calculation of the RQ m . Derived from the concentration addition model, the RQ m can be expressed as the sum of the ratios of the measured environmental concentration and the WQC for each herbicide. The RQ m should be less than one to ensure an acceptable risk to aquatic life. This approach has the advantage of being easy to calculate and communicate, and is proposed as a replacement for the current limit of 0.1 µg/L for herbicides in Switzerland. We illustrate the proposed approach on the example of five commonly applied herbicides (atrazine, simazine, terbuthylazine, isoproturon, and diuron). Their risk profile, i.e., the RQ m as a function of time for one exemplary river, clearly shows that the single compounds rarely exceeded their individual WQC. However, the contribution of peaks of different seasonally applied herbicides, whose application periods partially overlap, together with the continuously emitted herbicides from nonagricultural use, results in the exceedance of the RQ m threshold value of one upon several occasions. IntroductionPesticides, including herbicides, differ from most industrial organic compounds in being introduced into the environment with the explicit intention of exerting effects on one or more target organisms. Unfortunately, they do not exert their toxic action only where they are applied, but can, through persistence and transport, reach other compartments of the ecosystem. Monitoring programs throughout North America and Europe have demonstrated the widespread presence of pesticides in various freshwater bodies (1-6). Over the past decade, as public concern has focused on the possible impacts of pesticides on the environment, several European and North American countries (7)(8)(9)(10)(11)(12)(13)(14) have defined specific water quality criteria (WQC) for each pesticide in surface waters. Within the EU, these WQC are often equivalent to the predicted no-effect concentration (PNEC), which aims to ensure the overall protection of aquatic life (9,12,14). This parameter is usually estimated by finding the lowest reliable aquatic effect concentration and applying a safety factor to account for various uncertainties, such as interspecies differences in sensitivity, acute-to-chronic ratios, and laboratory-to-field extrapolations (for review see refs 15-17). The drawback of this approach is...

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supporting

confidence: 69%

mentioning

confidence: 99%

Including Mixtures in the Determination of Water Quality Criteria for Herbicides in Surface Water

Chèvre

Loepfe

Singer

et al. 2005

Environ. Sci. Technol.

118

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“…However, toxicity in natural ecosystems typically does not result from single toxicant exposure, but is rather a result of exposure to mixtures of toxicants (Altenburger et al, 1996;Gardner et al, 1998) and therefore mixture toxicity has been a subject of ecotoxicological interest for several decades (Hermens et al, 1984;Altenburger et al, 1996;Silva et al, 2002;Backhaus et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Mixture toxicity of three toxicants with similar and dissimilar modes of action to Daphnia magna

Syberg

Elleby

Pedersen

et al. 2008

Ecotoxicology and Environmental Safety

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“…Besides, one of the results reached by the EU BEAM project (BEAM: Bridging Effect Assessment of Mixtures to Ecosystem Situations and Regulations) demonstrated that the ratio between CA/IA generally does not exceed the value of 4 (Backhaus et al, 2003). This means that the overestimation of CA could be acceptable in a frame of worst-case analysis (Finizio et al, 2005).…”

Section: Introductionmentioning

confidence: 95%

“…The concentration addition (CA) assumes that the toxicity of the mixture is the sum of the toxicity of each component of the mixture (Loewe, 1953). This assumption is always valid if each component in the mixture presents the same mode of action (route of toxicological action) in the organism (Backhaus et al, 2003;Finizio et al, 2005). So this gives us a maximum allowable concentration which is the corner stone in the calculation of grey water.…”

Section: Methodsmentioning

confidence: 99%

A mathematical model to estimate the volume of grey water of pesticide mixtures

Paraíba

Pazianotto

Luiz

et al. 2014

Span. j. agric. res.

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The usual method to calculate grey water footprint does not take into account the volume of water required to dilute concentrations of pesticide mixtures in freshwater and it also depends on maximum concentration limit acceptable in water. We propose a model to estimate the grey water footprint of crops by calculating the volume of water necessary to dilute pesticide mixtures reaching freshwaters. The model requires short-term toxicity data from aquatic organisms based on EC50 values, soil pesticide half-life and soil sorption coefficient values, and does not require maximum concentration limit acceptable in water. The lixiviation rate and runoff rate of each pesticide was estimated by attenuation factor and by Soilfug model, respectively. The usefulness of the proposed model was illustrated by estimating the volume of grey water required to dilute the 17 most widely used herbicides in sugarcane crops of Brazil. The grey water footprint corresponding to the recommended agronomic dose for each herbicide varied between 4.20×106 m3 yr-1 and 1.20×1012 m3 yr-1 and the grey water footprint of the mixture of herbicides was 2.36×1012 m3 yr-1 in a cultivated area of 8.4×106 ha. These results establish the ranking position of each herbicide in the composition of the grey water footprint of mixture of herbicides. The rank of each herbicide could be used to create a label to be placed on the package of the pesticide, thus informing farmers about the volume of grey water per hectare due to the use of this herbicide.

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The BEAM-project: prediction and assessment of mixture toxicities in the aquatic environment

Cited by 108 publications

References 28 publications

Including Mixtures in the Determination of Water Quality Criteria for Herbicides in Surface Water

Including Mixtures in the Determination of Water Quality Criteria for Herbicides in Surface Water

Mixture toxicity of three toxicants with similar and dissimilar modes of action to Daphnia magna

A mathematical model to estimate the volume of grey water of pesticide mixtures

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