Photochemical degradation of triclosan: a comparison between different light sources

New emerging contaminants could represent a danger to the environment and Humanity with repercussions not yet known. One of the major worldwide pharmaceutical and personal care productions are antimicrobials products, triclosan, is an antimicrobial agent present in most products. Despite the high removal rate of triclosan present in wastewater treatments, triclosan levels are on the rise in the environment through disposal of wastewater effluent and use of sewage sludge in land application. Regulated in the EC/1272/2008 (annex VI, table 3.1), this compound is considered very toxic to aquatic life and it has been reported that photochemical transformation of triclosan produces dioxins. In the current work it was defined three objectives; determination of the most efficient process in triclosan degradation, recurring to photochemical degradation methods comparing different sources of light; identification of the main by-products formed during the degradation and the study of the influence of the Fenton and photo-Fenton reaction. Photochemical degradation methods such as: photocatalysis under florescent light (UV), photocatalysis under visible light (sunlight), photocatalysis under LEDs, photo-Fenton and Fenton reaction have been compared in this work. The degradation of triclosan was visualized through gas chromatography/mass spectrometry (GC/MS). In this study photo-Fenton reaction has successfully oxidized triclosan to H2O and CO2 without any by-products within 2 hours. Photocatalysis by titanium dioxide (TiO2) under LEDs was possible, having a degradation rate of 53% in an 8 hours essay. The degradation rate of the Fenton reaction, UV light and sunlight showed degradation between 90% and 95%. The results are reported to the data observed without statistic support, since this was not possible during the work period. Hydroquinone specie and 2,4-dichlorophenol by-products were identified in the first hour of photocatalysis by UV. A common compound, possibly identified has C7O4H , was present at the degradation by UV, sunlight and LEDs and was concluded to be a contaminant. In the future more studies in the use of LEDs should be undertaken given the advantages of long durability and low consumption of energy of these lamps and that due to their negative impact on the environment fluorescent lamps are being progressively made unavailable by governments, requiring new solutions to be found. Fenton and photo-Fenton reactions can also be costly processes given the expensive reagents used.

The thermal effects on the methanol-to-olefins reaction: A modelling and experimental approach

With the projection of an increasing world population, hand-in-hand with a journey towards a bigger number of developed countries, further demand on basic chemical building blocks, as ethylene and propylene, has to be properly addressed in the next decades. The methanol-to-olefins (MTO) is an interesting reaction to produce those alkenes using coal, gas or alternative sources, like biomass, through syngas as a source for the production of methanol. This technology has been widely applied since 1985 and most of the processes are making use of zeolites as catalysts, particularly ZSM-5. Although its selectivity is not especially biased over light olefins, it resists to a quick deactivation by coke deposition, making it quite attractive when it comes to industrial environments; nevertheless, this is a highly exothermic reaction, which is hard to control and to anticipate problems, such as temperature runaways or hot-spots, inside the catalytic bed. The main focus of this project is to study those temperature effects, by addressing both experimental, where the catalytic performance and the temperature profiles are studied, and modelling fronts, which consists in a five step strategy to predict the weight fractions and activity. The mind-set of catalytic testing is present in all the developed assays. It was verified that the selectivity towards light olefins increases with temperature, although this also leads to a much faster catalyst deactivation. To oppose this effect, experiments were carried using a diluted bed, having been able to increase the catalyst lifetime between 32% and 47%. Additionally, experiments with three thermocouples placed inside the catalytic bed were performed, analysing the deactivation wave and the peaks of temperature throughout the bed. Regeneration was done between consecutive runs and it was concluded that this action can be a powerful means to increase the catalyst lifetime, maintaining a constant selectivity towards light olefins, by losing acid strength in a steam stabilised zeolitic structure. On the other hand, developments on the other approach lead to the construction of a raw basic model, able to predict weight fractions, that should be tuned to be a tool for deactivation and temperature profiles prediction.

Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.