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From a theoretical point of view, it has often been argued that the model of independent action (IA) is the most correct reference model to use for predicting the joint effect of mixtures of chemicals with different molecular target sites. The theory of IA, however, relies on a number of assumptions that are rarely fulfilled in practice. It has even been argued that, theoretically, the concentration addition (CA) model could be just as correct. In the present study, we tested the accuracy of both IA and CA in describing binary dose-response surfaces of chemicals with different molecular targets using statistical software. We compared the two models to determine which best describes data for 158 data sets. The data sets represented 98 different mixtures of, primarily, pesticides and pharmaceuticals tested on one or several of seven test systems containing one of the following: Vibrio fischeri, activated sludge microorganisms, Daphnia magna, Pseudokirchneriella subcapitata, Lemna minor, Tripleurospermum inodorum, or Stellaria media. The analyses showed that approximately 20% of the mixtures were adequately predicted only by IA, 10% were adequately predicted only by CA, and both models could predict the outcome of another 20% of the experiment. Half of the experiments could not be correctly described with either of the two models. When quantifying the maximal difference between modeled synergy or antagonism and the reference model predictions at a 50% effect concentration, neither of the models proved significantly better than the other. Thus, neither model can be selected over the other on the basis of accuracy alone.

Fungicides inhibiting the biosynthesis of ergostrol, such as the triazoles and imidazoles, have been shown to enhance the effect of insecticides on birds, mammals and invertebrates in the terrestrial environment. The synergy is proposed to be due to an effect on P450 monooxygenase enzymes active in pesticide metabolism in these organisms. Fungicides often enter the aquatic environment jointly with other pesticides. It is therefore possible that they could act as synergists also in the aquatic environment. In this study we tested the joint effect of the imidazole fungicide prochloraz together with the herbicides acifluorfen, diquat and terbuthylazine, the fungicide azoxystrobin and the insecticides chlorfenvinphos, dimethoate, and pirimicarb on the bacteria Vibrio fischeri (six binary mixtures), the crustacean Daphnia magna (four binary mixtures), the algae Pseudokirchneriella subcapitata (four binary mixtures) and the floating plant Lemna minor (three binary mixtures). All the binary mixtures were evaluated both in relation to the model of concentration addition (CA) and independent action (IA) using isobolograms. The study showed strong synergy in relation to CA between prochloraz and azoxystrobin, diquat and esfenvalerat on D. magna with sums of toxic units for the 50:50% effect mixture ( summation TU(50:50)) as low as 0.25. The mixture with dimethoate was however antagonistic with summation TU(50:50) of 2.04. Four out of the six mixtures testes on V. fisheri showed synergy in relation to CA, but for three of the mixtures the response could be explained by IA. Only the mixture with diquat showed synergy in relation to both IA and CA with summation TU(50:50) around 0.50. There was no significant synergy for any of the combinations tested on the plant and the algae species in relation to CA and only for diquat in the algae-test in relation to IA. Hence, prochloraz does synergise the effect of some pesticides in the aquatic environment, but not consistently across species. The organism most susceptible to synergy by prochloraz in this study was D. magna. Especially the combination with insecticides such as esfenvalerate, where the concentration needed to immobilize 50% of the daphnia was reduced from3microgL(-1) to less than 0.5microgL(-1) when prochloraz was added, could be problematic as these concentrations are environmentally realistic. Furthermore, insecticides and ergostrol-biosynthesis-inhibitors (EBI-fungicides) are often applied together, and are therefore likely to co-exist in surface waters, enhancing the problem of the already very potent insecticides.

Exposure assessment is crucial for risk assessment for nanomaterials. We propose a framework to aid exposure assessment in consumer products. We determined the location of the nanomaterials and the chemical identify of the 580 products listed in the inventory maintained by the Woodrow Wilson International Center for Scholars, of which 37% used nanoparticles suspended in liquids, whereas1% contained "free airborne nanoparticles". C(60) is currently only used as suspended nanoparticles in liquids and nanosilver is used more as surface bound nanoparticles than as particles suspended in liquids. Based on the location of the nanostructure we were able to further group the products into categories of: (1) expected, (2) possible, and (3) no expected exposure. Most products fall into the category of expected exposure, but we were not able to complete a quantitative exposure assessment mainly due to the lack of information on the concentration of the nanomaterial in the products--a problem that regulators and industry will have to address if we are to have realistic exposure assessment in the future. To illustrate the workability of our procedure, we applied it to four product scenarios using the best estimates available and/or worst-case assumptions. Using the best estimates available and/or worst-case assumptions we estimated the consumer exposure to be 26, 15, and 44 microg kg(-1) bw year(-1) for a facial lotion, a fluid product, and a spray product containing nanoparticles, respectively. The application of sun lotion containing 2% nanoparticles result in an exposure of 56.7 mg kg(-1) bw d(-1) for a 2-year-old child, if the amounts applied correspond to the European Commission recommendations on use of sunscreen.