Urban water system metabolism assessment using WaterMet2 model

12th International Conference on Computing and Control for the Water Industry, CCWI2013, 2013-09-06, 2013-09-09, Perugia, ItalyThis paper presents a new "WaterMet2" model for integrated modelling of an urban water system (UWS). The model is able to quantify the principal water flows and other main fluxes in the UWS. The UWS in WaterMet2 is characterised using four different spatial scales (indoor area, local area, subcatchment and system area) and a daily temporal resolution. The main subsystems in WaterMet2 include water supply, water demand, wastewater and cyclic water recovery. The WaterMet2 is demonstrated here through modelling of the urban water system of Oslo city in Norway. Given a fast population growth, WaterMet2 analyses a range of alternative intervention strategies including 'business as usual', addition of new water resources, increased rehabilitation rates and water demand schemes to improve the performance of the Oslo UWS. The resulting five intervention strategies were compared with respect to some major UWS performance profiles quantified by the WaterMet2 model and expert's opinions. The results demonstrate how an integrated modelling approach can assist planners in defining a better intervention strategy in the future.This work was carried out as part of the ‘TRansition to Urban water Services of Tomorrow’ (TRUST) project. The authors wish to acknowledge the European Commission for funding TRUST project in the 7th Framework Programme under Grant Agreement No. 265122

On the influence of Si:Al ratio and hierarchical porosity of FAU zeolites in solid acid catalysed esterification pretreatment of bio-oil

A family of faujasite (FAU) zeolites with different Si:Al ratio, and/or hierarchical porosity introduced via post-synthetic alkaline desilication treatment, have been evaluated as solid acid catalysts for esterification pretreatments of pyrolysis bio-oil components. Acetic acid esterification with aliphatic and aromatic alcohols including methanol, anisyl alcohol, benzyl alcohol, p-cresol and n-butanol was first selected as a model reaction to identify the optimum zeolite properties. Materials were fully characterised using N2 porosimetry, ICP, XRD, XPS, FT-IR, pyridine adsorption, NH3 TPD, In-situ ATR and inverse gas chromatography (IGC). IGC demonstrates that the surface polarity and hence hydrophobicity of FAU decreases with increased Si:Al ratio. Despite possessing a higher acid site loading and acetic acid adsorption capacity, high Al-content FAU possess weaker acidity than more siliceous catalysts. Esterification activity increases with acid strength and decreasing surface polarity following the order FAU30>FAU6>FAU2.6. The introduction of mesoporosity through synthesis of a hierarchical HFAU30 material further enhances esterification activity through improved acid site accessibility and hydrophobicity. Methanol was the most reactive alcohol for esterification, and evaluated with HFAU30 for the pretreatment of a real pyrolysis bio-oil, reducing the acid content by 76% under mild conditions

Use of the descriptor fingerprints to clustering of chemical datasets

A novel approach in the area of chemoinformatics, the use of descriptor fingerprints has been applied to the problem of clustering of chemical databases. This approach coupled with the clustering method of Butina (originally created for structural fingerprints) was tested with a set of 96 biodiesel fuels. The influence of the threshold values from 0.0 to 1.0 of the Tanimoto index on the clustering results was studied. The results show a good discrimination power of the method, biodiesels of the same oils fall in one the same clusters. It was also shown that similar cetane number (CN) values of biodiesels within the statistical accuracy fall in the same cluster