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Despite the large amount of data available, the great effort put into searches for the ‘best’ parameters and many comparative modelling studies, considerable uncertainties continue to plague chemical thermodynamics. An important factor in this ongoing failure has been the notion that the problem can be solved by better assessment of data quality on a case-by-case basis. This approach has proved strikingly unsuccessful. A different methodology must therefore be found to meet the general requirements of thermodynamic modelling in aquatic chemistry. This paper discusses current practices in quality assessment of thermodynamic data and the problems associated with them. It outlines a general approach which might address the above problem based on two concepts: (i) using large databases to store as much of the available data as possible in the form that it appears in the literature along with an assessed ‘score’ or ‘measure of information content’ and (ii) then using automatic mechanisms informed by this score to produce the thermodynamically consistent datasets needed for modelling calculations.

Chemical modelling of multicomponent mixtures: quality assurance is more than just equilibrium data quality assessment