Theoretical environmental disciplines in support of sustainable chemistry.

It has been evident for decades that environmental chemicals pose an enormous risk to the environment as well as to humans. However, this important topic is still underestimated in every part of society. Over the last 20 years, anthropogenic chemicals research, often closely connected with endocrine disruption research, has shown how chemicals in our environment can profoundly affect development, growth, maturation, and reproduction by mimicking hormones or interacting with hormone receptors. 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. Sustainable Chemistry is a chemical philosophy encouraging the design of products and processes that reduce or eliminate the use and generation of hazardous substances. Sustainability and sustainable development are effectively ethical concepts, expressing desirable outcomes from economic and social decisions. The important matter of principle, therefore, becomes a victim of the desire to set targets and measure progress. In this respect, metrical scientific disciplines like Chemometrics, Environmetrics, Biometrics, Chemoinformatics, Environmental Informatics, etc. are of great importance. It is evident 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. Our research focuses on the data-analysis of data-sets concerning environmental chemicals in order to gain information out of the data and draw conclusions concerning the prevention of those chemicals. The data-analysis method used is the method of partially ordered sets. Partial order is a discipline of Discrete Mathematics and one may consider partial order as an example of mathematics without numerical arithmetic. A good overview can be found in a book edited by the last author. The graphical representation of partial orders is laid down in so-called Hasse diagrams. In complex data-sets it is often necessary to compare different sets of criteria (attributes). In the similarity analysis we intend to calculate the similarity of different posets. This similarity analysis is an important feature of the newly developed software package called PyHasse. The first example presented, will be the evaluation study of Persistent Organic Pollutants (POPs) in mineral soil samples from the Alps. It was demonstrated that the altitude has a considerable influence on the concentration of some organic chemicals in humus: The concentrations of some chemicals increase with the altitude. In the second data-analysis approach we investigated data-sets of breast milk samples of 130 women in Denmark and Finland which contained measurable levels of POPs. The aim is to find differences in the chemicals’ contamination between the healthy boys and those boys who were suffering from congenital malformations (cryptorchidism). This research activity is still ongoing. One interim result is that disparities can be observed when the Finnish and Danish data-sets are compared concerning cryptorchidism