Análise crítica do consumo de energia na indústria de faiança

Com este trabalho pretende-se analisar o consumo de energia na indústria de faiança e identificar medidas de poupança energética. Em 2014, o consumo específico foi de 191 kgep/t e a intensidade carbónica 2,15 tCO2e/t, tendo havido uma redução de, respectivamente, 50,2% e 1,3%, comparativamente a 2010. O consumo total correspondeu a 1108 tep, sendo 66% relativo ao consumo de gás natural. Foi utilizado um analisador de energia eléctrica nos principais equipamentos consumidores, e na desagregação de consumos térmicos, efectuaram-se leituras no contador geral de gás natural e foram utilizados dados das auditorias ambiental e energética. O processo de cozedura é responsável por 58% do consumo térmico da instalação, seguido da pintura com 24%. A conformação é o sector com maior consumo de energia eléctrica, correspondendo a 23% do consumo total. As perdas térmicas pelos gases de exaustão dos equipamentos de combustão e pela envolvente do forno, considerando os mecanismos de convecção natural e radiação, correspondem a cerca de 6% do consumo térmico total, sendo necessário tomar medidas a nível do isolamento térmico e da redução do excesso de ar. A instalação de variadores de velocidade nos ventiladores do ar de combustão do forno poderia resultar em poupanças significativas, em particular, no consumo de gás natural – redução de 4 tep/ano e cerca de 2500€/ano– tendo um tempo de retorno do investimento inferior a 1 ano. Deverá ser, no entanto, garantida a alimentação de ar combustão a todos os queimadores, bem como, a combustão completa do gás natural. O funcionamento contínuo do forno poderia resultar no aumento da sua eficiência energética, com redução de custos de operação e manutenção, sendo necessário avaliar os custos adicionais de stock e de mão de obra. Verificou-se que as medidas relacionadas com a monitorização de consumos, eliminação de fugas de ar comprimido e a instalação de variadores de velocidade nos ventiladores do ar de combustão do forno poderiam resultar em reduções de consumo de 26 tep e de emissões de 66tCO2e, num total de quase 14 000€.

Metabonomic studies to assess beer quality and stability

The work reported in this thesis aimed at applying the methodology known as metabonomics to the detailed study of a particular type of beer and its quality control, with basis on the use of multivariate analysis (MVA) to extract meaningful information from given analytical data sets. In Chapter 1, a detailed description of beer is given considering the brewing process, main characteristics and typical composition of beer, beer stability and the commonly used analytical techniques for beer analysis. The fundamentals of the analytical methods employed here, namely nuclear magnetic resonance (NMR) spectroscopy, gas-chromatography-mass spectrometry (GC-MS) and mid-infrared (MIR) spectroscopy, together with the description of the metabonomics methodology are described shortly in Chapter 2. In Chapter 3, the application of high resolution NMR to characterize the chemical composition of a lager beer is described. The 1H NMR spectrum obtained by direct analysis of beer show a high degree of complexity, confirming the great potential of NMR spectroscopy for the detection of a wide variety of families of compounds, in a single run. Spectral assignment was carried out by 2D NMR, resulting in the identification of about 40 compounds, including alcohols, amino acids, organic acids, nucleosides and sugars. In a second part of Chapter 3, the compositional variability of beer was assessed. For that purpose, metabonomics was applied to 1H NMR data (NMR/MVA) to evaluate beer variability between beers from the same brand (lager), produced nationally but differing in brewing site and date of production. Differences between brewing sites and/or dates were observed, reflecting compositional differences related to particular processing steps, including mashing, fermentation and maturation. Chapter 4 describes the quantification of organic acids in beer by NMR, using different quantitative methods: direct integration of NMR signals (vs. internal reference or vs. an external electronic reference, ERETIC method) and by quantitative statistical methods (using the partial least squares (PLS) regression) were developed and compared. PLS1 regression models were built using different quantitative methods as reference: capillary electrophoresis with direct and indirect detection and enzymatic essays. It was found that NMR integration results generally agree with those obtained by the best performance PLS models, although some overestimation for malic and pyruvic acids and an apparent underestimation for citric acid were observed. Finally, Chapter 5 describes metabonomic studies performed to better understand the forced aging (18 days, at 45 ºC) beer process. The aging process of lager beer was followed by i) NMR, ii) GC-MS, and iii) MIR spectroscopy. MVA methods of each analytical data set revealed clear separation between different aging days for both NMR and GC-MS data, enabling the identification of compounds closely related with the aging process: 5-hydroxymethylfurfural (5-HMF), organic acids, γ-amino butyric acid (GABA), proline and the ratio linear/branched dextrins (NMR domain) and 5-HMF, furfural, diethyl succinate and phenylacetaldehyde (known aging markers) and, for the first time, 2,3-dihydro-3,5-dihydroxy-6-methyl-4(H)-pyran-4-one xii (DDMP) and maltoxazine (by GC-MS domain). For MIR/MVA, no aging trend could be measured, the results reflecting the need of further experimental optimizations. Data correlation between NMR and GC-MS data was performed by outer product analysis (OPA) and statistical heterospectroscopy (SHY) methodologies, enabling the identification of further compounds (11 compounds, 5 of each are still unassigned) highly related with the aging process. Data correlation between sensory characteristics and NMR and GC-MS was also assessed through PLS1 regression models using the sensory response as reference. The results obtained showed good relationships between analytical data response and sensory response, particularly for the aromatic region of the NMR spectra and for GC-MS data (r > 0.89). However, the prediction power of all built PLS1 regression models was relatively low, possibly reflecting the low number of samples/tasters employed, an aspect to improve in future studies.

The impact of biofuels for road traffic on air quality : a modelling approach

The selection of the energy source to power the transport sector is one of the main current concerns, not only relative with the energy paradigm but also due to the strong influence of road traffic in urban areas, which highly affects human exposure to air pollutants and human health and quality of life. Due to current important technical limitations of advanced energy sources for transportation purposes, biofuels are seen as an alternative way to power the world’s motor vehicles in a near-future, helping to reduce GHG emissions while at the same time stimulating rural development. Motivated by European strategies, Portugal, has been betting on biofuels to meet the Directive 2009/28/CE goals for road transports using biofuels, especially biodiesel, even though, there is unawareness regarding its impacts on air quality. In this sense, this work intends to clarify this issue by trying to answer the following question: can biodiesel use contribute to a better air quality over Portugal, particularly over urban areas? The first step of this work consisted on the characterization of the national biodiesel supply chain, which allows verifying that the biodiesel chain has problems of sustainability as it depends on raw materials importation, therefore not contributing to reduce the external energy dependence. Next, atmospheric pollutant emissions and air quality impacts associated to the biodiesel use on road transports were assessed, over Portugal and in particular over the Porto urban area, making use of the WRF-EURAD mesoscale numerical modelling system. For that, two emission scenarios were defined: a reference situation without biodiesel use and a scenario reflecting the use of a B20 fuel. Through the comparison of both scenarios, it was verified that the use of B20 fuels helps in controlling air pollution, promoting reductions on PM10, PM2.5, CO and total NMVOC concentrations. It was also verified that NO2 concentrations decrease over the mainland Portugal, but increase in the Porto urban area, as well as formaldehyde, acetaldehyde and acrolein emissions in the both case studies. However, the use of pure diesel is more injurious for human health due to its dominant VOC which have higher chronic hazard quotients and hazard indices when compared to B20.