Combinatorial Computational Chemistry is developed as a standard tool to tackle complex problems in chemistry and materials science. The method employs a series of state-of-the-art methods, ranging from empirical molecular mechanics to first principles calculations, as well as of mathematical (graph theoretical and combinatorial) methods. The process is similar as in experimental combinatorial chemistry: First, a large set of candidate structures is generated which is complete in the sense that the best possible structure for a particular purpose must be found among the set. This structure is then identified using computational chemistry. We will apply methodologies at different stages in hierarchical order and successively screen the set of candidate structures. Screening criteria are based on the computer simulations and include geometry, stability and properties of the candidate structures. Detailed characteristics of the final materials will be simulated, including the X-ray diffraction pattern, the electronic structure, and the target properties. We will apply C3 to two important problems of environmental science. (i) We will optimise nanoporous materials to act as molecular sieves to separate water from ethanol, an important task for the production of biofuels. Here, materials are optimised to transport ethanol, but not water (or vice versa). The tuning parameters are the channel size of the material and its polarity. (ii) We will optimise nanoporous materials to transport protons, an important task for the design of energy-efficient fuel cells, by distributing flexible functional groups, acting as hopping sites for the protons, in the framework.