Nitrogen compounds play a crucial role in the earth's ecosystems, being continually converted from one form to another as they pass from the atmosphere to living organisms on land and in the sea. Nitric oxide gas (NO), for example, is a key intermediate in the global nitrogen cycle, and plays important roles in many processes in almost all forms of life, often acting as a signalling molecule. However, emissions of NO and the toxic gas nitrogen dioxide (collectively known as NOx) from heavy industry and motor vehicles alter the composition of nitrogen compounds in the atmosphere and are highly damaging both directly and indirectly to the human respiratory system. The removal of NOx from exhaust emissions is a pressing environmental concern and an important target for industrial catalysis research, an area of extreme importance to the UK economy. We propose to study the chemistry of nitrogen oxides in biological and industrial environments where a full understanding of how the gases are controlled is crucial but still lacking. In both cases the chemistry is controlled by transition metals: cytochrome c' proteins have evolved an extraordinary degree of control of NO through binding to an iron complex which discriminates against other diatomic gases, while in zeolite catalysts (microporous aluminosilicate structures) NOx gases can be converted into safer by-products at copper centres through the addition of ammonia in a process known as selective catalytic reduction (SCR). The precise mechanisms, however, are not currently proven. We will investigate the chemistry of nitrogen dioxide and nitrogen oxide in both systems by computational simulations performed on high performance clusters. The resulting data will be used to model spectroscopic signatures, i.e. how electromagnetic radiation (such as light or X-rays) interacts with matter. These will be compared with the results of infrared, Raman, UV-visible and X-ray absorption experiments on the two systems to better understand the processes involved in the chemical reactions, which will inform the future design of improved zeolite catalysts and bioengineered proteins. We will use quantum mechanical/molecular mechanical (QM/MM) modelling to identify the reaction mechanisms and calculate spectroscopic signatures of the two systems. In this approach the zeolite and protein active sites will be treated using a highly accurate, but computationally expensive, quantum mechanical level of theory, embedded in an environment described by an efficient classical calculation. New QM/MM methods will be implemented that can enable larger QM regions to be calculated and more accurate spectroscopic signatures including anharmonic vibrational effects. Importantly, our approach for combining computational modelling with experimental results will be generally applicable to any chemical processes in complex systems, including other industrial catalysts and biomolecules.