Discrete mathematical data analysis method in support of sustainable chemistry

Sustainable chemistry is a chemical philosophy encouraging the design of products and processes that reduce or eliminate the use and generation of hazardous substances. In this respect, metrical scientific disciplines like Chemometrics, Environmetrics, Biometrics, Chemoinformatics, Environmental Informatics, etc. support this principle. The effects of environmental contaminants on health are a major concern because exposure is associated with a number of diseases, including cancer, diabetes, congenital malformations and infertility. Hence it is obvious that there is increasing pressure to intensify the research and to more efficiently evaluate the data on persistent and bioaccumulative chemicals in the environment as well as in human bodies. The data analysis method used in our approach is based on the theory of partially ordered sets. This theory is a discipline of Discrete Mathematics and one may consider partial order as an example of mathematics without numerical arithmetic. The graphical representation of partial orders is laid down in so-called Hasse diagrams. In our paper we investigated data-sets of breast milk samples of 130 women in Denmark and Finland which contained measurable levels of 32 Persistent Organic Pollutants (POPs). The aim of this discrete mathematical approach, supported by the software package PyHasse, is to find differences in the chemicals' contamination first between Denmark and Finland and furthermore between the healthy boys and those boys who were suffering from congenital malformations (cryptorchidism) in Denmark as an example. We detect differences comparing Denmark and Finland, as well as Danish healthy and cryptorchidism data. This research activity can be regarded as an ordinal approach within sustainable chemistry, on the one hand demonstrating the danger of existing chemicals in the environment and humans and on the other hand methods like these can be applied for finding out more sustainable chemicals.