Evaluating the environmental hazard of industrial chemicals from data collected during the REACH registration process

Registration dossiers for 11678 industrial chemicals were retrieved from the database of the European Chemicals Agency, of which 3566 provided a numerical entry for the corresponding predicted no effect concentration for the freshwater environment (PNEC). A distribution-based examination of 2244 of these entries reveals that the average PNEC of an industrial chemical in Europe is 238 nmol/L, covering a span of 9 orders of magnitude. A comparison with biocides, pesticides, pharmaceuticals and WFD-priority pollutants reveals that, in average, industrial chemicals are least hazardous (hazard ranking: industrial chemicals << pharmaceuticals < pesticides < Water Framework Directive priority pollutants < biocides). However, 280 industrial chemicals have a lower environmental threshold than the median pesticide and 73 have a lower environmental threshold than even the median biocide. Industrial chemicals produced and/or imported in higher tonnages have, on average, higher PNECs which most likely is due to the lower assessment factors used for the PNEC determination. This pattern indicates that the initial AF of 1000 comprises a measure of conservatism. The vast majority of PNEC values are driven by EC50 and NOEC data from tests with Daphnia magna. Tests with marine species are rarely provided for the hazard characterization of industrial chemicals.

Evaluating the environmental hazard of industrial chemicals from data collected during the REACH registration process

Registration dossiers for 11678 industrial chemicals were retrieved from the database of the European Chemicals Agency, of which 3566 provided a numerical entry for the corresponding predicted no effect concentration for the freshwater environment (PNEC). A distribution-based examination of 2244 of these entries reveals that the average PNEC of an industrial chemical in Europe is 238 nmol/L, covering a span of 9 orders of magnitude. A comparison with biocides, pesticides, pharmaceuticals and WFD-priority pollutants reveals that, in average, industrial chemicals are least hazardous (hazard ranking: industrial chemicals << pharmaceuticals < pesticides < Water Framework Directive priority pollutants < biocides). However, 280 industrial chemicals have a lower environmental threshold than the median pesticide and 73 have a lower environmental threshold than even the median biocide. Industrial chemicals produced and/or imported in higher tonnages have, on average, higher PNECs which most likely is due to the lower assessment factors used for the PNEC determination. This pattern indicates that the initial AF of 1000 comprises a measure of conservatism. The vast majority of PNEC values are driven by EC50 and NOEC data from tests with Daphnia magna. Tests with marine species are rarely provided for the hazard characterization of industrial chemicals.

Evaluating the environmental hazard of industrial chemicals from data collected during the REACH registration process

Registration dossiers for 11678 industrial chemicals were retrieved from the database of the European Chemicals Agency, of which 3566 provided a numerical entry for the corresponding predicted no effect concentration for the freshwater environment (PNEC). A distribution-based examination of 2244 of these entries reveals that the average PNEC of an industrial chemical in Europe is 238 nmol/L, covering a span of 9 orders of magnitude. A comparison with biocides, pesticides, pharmaceuticals and WFD-priority pollutants reveals that, in average, industrial chemicals are least hazardous (hazard ranking: industrial chemicals << pharmaceuticals < pesticides < Water Framework Directive priority pollutants < biocides). However, 280 industrial chemicals have a lower environmental threshold than the median pesticide and 73 have a lower environmental threshold than even the median biocide. Industrial chemicals produced and/or imported in higher tonnages have, on average, higher PNECs which most likely is due to the lower assessment factors used for the PNEC determination. This pattern indicates that the initial AF of 1000 comprises a measure of conservatism. The vast majority of PNEC values are driven by EC50 and NOEC data from tests with Daphnia magna. Tests with marine species are rarely provided for the hazard characterization of industrial chemicals.

Investigating the genetic architecture of conditional strategies using the environmental threshold model

The threshold expression of dichotomous phenotypes that are environmentally cued or induced comprise the vast majority of phenotypic dimorphisms in colour, morphology, behaviour and life history. Modelled as conditional strategies under the framework of evolutionary game theory, the quantitative genetic basis of these traits is a challenge to estimate. The challenge exists firstly because the phenotypic expression of the trait is dichotomous and secondly because the apparent environmental cue is separate from the biological signal pathway that induces the switch between phenotypes. It is the cryptic variation underlying the translation of cue to phenotype that we address here. With a ‘half-sib common environment’ and a ‘family-level split environment’ experiment, we examine the environmental and genetic influences that underlie male dimorphism in the earwig Forficula auricularia . From the conceptual framework of the latent environmental threshold (LET) model, we use pedigree information to dissect the genetic architecture of the threshold expression of forceps length. We investigate for the first time the strength of the correlation between observable and cryptic ‘proximate’ cues. Furthermore, in support of the environmental threshold model, we found no evidence for a genetic correlation between cue and the threshold between phenotypes. Our results show strong correlations between observable and proximate cues and less genetic variation for thresholds than previous studies have suggested. We discuss the importance of generating better estimates of the genetic variation for thresholds when investigating the genetic architecture and heritability of threshold traits. By investigating genetic architecture by means of the LET model, our study supports several key evolutionary ideas related to conditional strategies and improves our understanding of environmentally cued decisions.

FALLING THROUGH THE GAPS OF THE REGISTRATION CONVENTION: A NEED FOR REVISION

In this paper, I address the areas of law that have been left unregulated by the Registration Convention, as well as the need to develop the treaty using the cornerstones of space law as a foundation for such development. My first enquiry relates to the definition of a space object and the implications of limiting the treaty’s scope to ‘objects launched into earth’s orbit or beyond’. Further, to what extent can this definition accommodate the registration of objects that are constructed in outer space? My second enquiry focuses on a lacuna that is largely unaddressed by space law in general and does not only lack in the Registration Convention. Currently, there is no system regulating the status of objects that are either wholly or partly constructed using lunar resources. It is questionable whether such a construction would pass the environmental threshold required by the due regard principle. However, should such a construction be deemed lawful it is uncertain to what extent a state may lawfully exercise jurisdiction over such an object without its authority being deemed an act of national appropriation. In this paper I will not attempt to creatively interpret available space law in order to accommodate missing regulations. Instead, I rely on the core of space law — represented by the Outer Space Treaty — to provide a contextual backdrop against which the above questions can be answered or highlighted as incomplete.