Comparison of the combined monitoring-based and modelling-based priority setting scheme with partial order theory and random linear extensions for ranking of chemical substances.
The combined monitoring-based and modelling-based priority setting scheme (COMMPS) used to establish a priority setting list within the EU Water Framework Directive plays a major role in the European environmental policy on chemical substances. The COMMPS procedure can be classified as a so-called scoring method. The applied functional relationship and weight factors are established based on expert judgement, which unfortunately appears to be vulnerable to subjective inputs. In this study an alternative priority setting methods based on partial order theory (POT) and random linear extensions (RLE) is suggested and compared to the COMMPS procedure. The POT/RLE is characterised as being based on fewer assumptions concerning functional relationships and does not apply weighting factors. Using the POT/RLE methodology a different ranking result occur than when using the COMMPS procedure. Eight of the top 20 substances from the COMMPS procedure are not ranked within the top 20 when using POT/RLE. From the viewpoint of environmental protection, especially the substances that have been given low priority in the COMMPS procedure, but a high rank in POT/RLE, are of interest in a regulatory context. These substances are naphthalene, trichloromethane, isoproturon, metolachlor, endosulfan, acenaphthene, alachlor and dichloromethane. An analysis of the ability of the descriptors to separate the single substance discloses that the most significant descriptor is the concentrations detected in the environment. Further, the frequency of detection is not applied as a descriptor in the COMMPS procedure. However, if this descriptor was to be applied the analysis revealed that it would have been the third most significant descriptor.
Lerche
Dorte
D
Institute of Chemistry, University of Copenhagen, Denmark. dbl@dmu.dk
Sørensen
Peter B
PB
Larsen
Henrik Sørensen
HS
Carlsen
Lars
L
Nielsen
Ole John
OJ
D000465:Algorithms; D003198:Computer Simulation; D004777:Environment; D016014:Linear Models; D008956:Models, Chemical; D009930:Organic Chemicals / Q000009:adverse effects* / Q000737:chemistry*; D012044:Regression Analysis; D018570:Risk Assessment; D014874:Water Pollutants, Chemical / Q000009:adverse effects*
D009930:Organic Chemicals; D014874:Water Pollutants, Chemical