Environmental assessment of industrial chemical and primary sector processes from a life cycle perspective

During the PhD program in chemistry at the University of Bologna, the environmental sustainability of some industrial processes was studied through the application of the LCA methodology. The efforts were focused on the study of processes under development, in order to assess their environmental impacts to guide their transfer on an industrial scale. Processes that could meet the principles of Green Chemistry have been selected and their environmental benefits have been evaluated through a holistic approach. The use of renewable sources was assessed through the study of terephthalic acid production from biomass (which showed that only the use of waste can provide an environmental benefit) and a new process for biogas upgrading (whose potential is to act as a carbon capture technology). Furthermore, the basis for the development of a new methodology for the prediction of the environmental impact of ionic liquids has been laid. It has already shown good qualities in identifying impact trends, but further research on it is needed to obtain a more reliable and usable model. In the context of sustainable development that will not only be sector-specific, the environmental performance of some processes linked to the primary production sector has also been evaluated. The impacts of some organic farming practices in the wine production were analysed, the use of the Cereal Unit parameter was proposed as a functional unit for the comparison of different crop rotations, and the carbon footprint of school canteen meals was calculated. The results of the analyses confirm that sustainability in the industrial production sector should be assessed from a life cycle perspective, in order to consider all the flows involved during the different phases. In particular, it is necessary that environmental assessments adopt a cradle-to-gate approach, to avoid shifting the environmental burden from one phase to another.

Advanced decision-support methods for the design, control, and optimization of perishable products life cycle

In the last decades, global food supply chains had to deal with the increasing awareness of the stakeholders and consumers about safety, quality, and sustainability. In order to address these new challenges for food supply chain systems, an integrated approach to design, control, and optimize product life cycle is required. Therefore, it is essential to introduce new models, methods, and decision-support platforms tailored to perishable products. This thesis aims to provide novel practice-ready decision-support models and methods to optimize the logistics of food items with an integrated and interdisciplinary approach. It proposes a comprehensive review of the main peculiarities of perishable products and the environmental stresses accelerating their quality decay. Then, it focuses on top-down strategies to optimize the supply chain system from the strategical to the operational decision level. Based on the criticality of the environmental conditions, the dissertation evaluates the main long-term logistics investment strategies to preserve products quality. Several models and methods are proposed to optimize the logistics decisions to enhance the sustainability of the supply chain system while guaranteeing adequate food preservation. The models and methods proposed in this dissertation promote a climate-driven approach integrating climate conditions and their consequences on the quality decay of products in innovative models supporting the logistics decisions. Given the uncertain nature of the environmental stresses affecting the product life cycle, an original stochastic model and solving method are proposed to support practitioners in controlling and optimizing the supply chain systems when facing uncertain scenarios. The application of the proposed decision-support methods to real case studies proved their effectiveness in increasing the sustainability of the perishable product life cycle. The dissertation also presents an industry application of a global food supply chain system, further demonstrating how the proposed models and tools can be integrated to provide significant savings and sustainability improvements.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.

Utilizzo della metodologia Life Cycle Assessment combinata al modello RothC per valutare gli impatti ambientali in aziende vitivinicole a diverso regime di conduzione

A causa del riscaldamento globale, tutti i settori produttivi sono incentivati ad attuare strategie e tecnologie volte a ridurre le emissioni climalteranti. Per il settore agricolo, una gestione più sostenibile del suolo permetterebbe di rimuovere CO2 dall’atmosfera, stoccandola come C organico nel suolo. Il presente studio si pone l’obiettivo di quantificare gli impatti della produzione dell’uva e del vino imbottigliato dal punto di vista degli aspetti ambientali più rilevanti, approfondendo particolarmente il cambiamento climatico attraverso la metodologia Life Cycle Assessment (LCA). Inoltre, attraverso la determinazione delle dinamiche del C organico nel suolo mediante il modello RothC, lo studio cerca di capire se l'integrazione dei risultati di uno studio LCA con quelli del modello RothC possano fornire informazioni aggiuntive utili a un miglioramento della performance ambientale del prodotto agricolo. Il caso studio riguarda due aziende vitivinicole, situate in Emilia-Romagna che attuano due diverse tipologie di gestione (naturale e convenzionale). La metodologia LCA è stata applicata ad entrambi gli scenari selezionando i parametri metodologici più appropriati a seconda dello scenario in esame, e.g. i confini del sistema e l’unità funzionale, mentre, il modello RothC è stato applicato unicamente alla fase di coltivazione dell’uva. I risultati LCA mostrano le migliori prestazioni per la produzione dell’uva dell’azienda naturale per quasi tutte le categorie d’impatto, incluso il cambiamento climatico. Nella produzione del vino imbottigliato, la fase di coltivazione e quella di imbottigliamento risultano le più impattanti. I risultati di RothC evidenziano invece migliori prestazioni da parte dell’azienda convenzionale. L’integrazione dei risultati LCA con quelli di RothC rappresentano dunque un’operazione cruciale nel determinare quale sia l’effettivo impatto delle aziende agricole sul cambiamento climatico e come migliorarlo in futuro.

Uso combinato della metodologia Life Cycle Assessment e del modello RothC per stimare le prestazioni ambientali della produzione di uva in due aziende a conduzione convenzionale

Lo studio ha applicato la metodologia Life Cycle Assessment (LCA) con l’obiettivo di valutare i potenziali impatti ambientali derivanti dalla coltivazione dell’uva in due aziende a conduzione convenzionale del ravennate, denominate DZ e NG. Successivamente è stato applicato il modello RothC per simulare scenari sulla variazione del Soil Organic Carbon (SOC) e valutare in che misura le diverse pratiche agronomiche di gestione del suolo influenzino la variazione del SOC e la relativa emissione di CO2. Infine, i risultati dell’LCA sono stati integrati con quelli del modello RothC. Gli esiti dell’LCA indicano che, generalmente, sui diversi aspetti ambientali l’azienda DZ ha impatti superiori a quelli di NG soprattutto a causa di un maggiore utilizzo di fertilizzanti e pesticidi. Per quanto riguarda il contributo al riscaldamento globale (GWP), DZ mostra un impatto circa doppio di quello di NG. Il modello RothC ha individuato quali pratiche culturali aumentano il SOC mitigando le emissioni di CO2eq., in particolare: l’inerbimento perenne, la scelta di forme di allevamento con elevata produzione di residui culturali e l’utilizzo di ammendanti. L’integrazione dei valori dei due strumenti ha permesso di ottenere un bilancio globale di CO2eq. in cui le emissioni totali rispetto al GWP aumentano in DZ e diminuiscono in NG, portando a un impatto di DZ circa tre volte superiore rispetto a quello di NG. Fertilizzazione, potatura e lavorazione del suolo sono pratiche considerate nel calcolo del GWP in termini di consumo ed emissione dei processi produttivi, ma non come input di carbonio fornibili al suolo, determinando sovra o sottostima delle effettive emissioni di CO2eq. Questo studio dimostra l’utilità di incentivare la diffusione dell’applicazione integrata dei due strumenti nel settore viticolo, determinante per la comprensione e quantificazione delle emissioni di CO2 associate alla fase di coltivazione, sulla quale quindi indirizzare ottimizzazioni e approfondimenti.

Towards the sustainable production of methyl methacrylate: A comparative analysis of industrial chemical production processes using life cycle assessment methodology

Increasing environmental awareness has been a significant driving force for innovations and process improvements in different sectors and the field of chemistry is not an outlier. Innovating around industrial chemical processes in line with current environmental responsibilities is however no mean feat. One of such hard to overhaul process is the production of methyl methacrylate (MMA) commonly produced via the acetone cyanohydrin (ACH) process developed back in the 1930s. Different alternatives to the ACH process have emerged over the years and the Alpha Lucite process has been particularly promising with a combined plant capacity of 370,000 metric tonnes in Singapore and Saudi Arabia. This study applied Life Cycle Assessment methodology to conduct a comparative analysis between the ACH and Lucite processes with the aim of ascertaining the effect of applying principles of green chemistry as a process improvement tool on overall environmental impacts. A further comparison was made between the Lucite process and a lab-scale process that is further improvement on the former, also based on green chemistry principles. Results showed that the Lucite process has higher impacts on resource scarcity and ecosystem health whereas the ACH process has higher impacts on human health. On the other hand, compared to the Lucite process the lab-scale process has higher impacts in both the ecosystem and human health categories with lower impacts only in the resource scarcity category. It was observed that the benefits of process improvements with green chemistry principles might not be apparent in some categories due to some limitations of the methodology. Process contribution analysis was also performed and it revealed that the contribution of energy is significant, therefore a sensitivity analysis with different energy scenarios was performed. An uncertainty analysis using Monte Carlo analysis was also performed to validate the consistency of the results in each of the comparisons.

Life cycle assessment (LCA) of a bio-fuel cell fed with waste biomass: potential for scale-up and process optimization

In this Thesis, a life cycle analysis (LCA) of a biofuel cell designed by a team from the University of Bologna was done. The purpose of this study is to investigate the possible environmental impacts of the production and use of the cell and a possible optimization for an industrial scale-up. To do so, a first part of the paper was devoted to studying the present literature on biomass, and fuel cell treatments and then LCA studies on them. The experimental part presents the work done to create the Life Cycle Inventory and Life Cycle Impact Assessment. Several alternative scenarios were created to study process optimization. Reagents and energy supply were changed. To examine whether this technology can be competitive, a comparison was made with some biofuel cell use scenarios with traditional biomass treatment technologies. The result of this study is that this technology is promising from an environmental point of view in case it is possible to recover nutrients in output, without excessive energy consumption, and to minimize the use of energy used to prepare the solution.

Sustainability Evaluation of Biodiesel Produced from Microalgae Chlamydomonas sp Grown in Brewery Wastewater

This study performs a sustainability evaluation of biodiesel from microalga Chlamydomonas sp. grown in 20 % (v/v) of brewery’s wastewater, blended with pentose sugars (xylose, arabinose or ribose resulting from the hydrolysis of brewer’s spent grains (BSG). The life cycle steps considered for the study are: microalgae cultivation, biomass processing and lipids extraction at the brewery site, and its conversion to biodiesel at a dedicated external biofuel’s plant. Three sustainability indicators (LCEE, FER and GW) were considered and calculated using experimental data. Literature data was used, whenever necessary, to complement life cycle data, thus allowing a more accurate sustainability evaluation. A comparative analysis of the biodiesel life cycle steps was also conducted, with the main goal of identifying which steps need to be improved. Results show that biomass processing, especially cell harvesting, microalgae cultivation, and lipids extraction are the main process bottlenecks. It is also analysed the influence on the microalgae biodiesel sustainability of adding each pentose sugar to the cultivation media, concluding that it strongly influences the biomass and lipid productivity. In particular, the addition of xylose is preferable in terms of lipid productivity, but from a sustainability point of view, ribose is the best, though the difference from xylose is not significant. Nevertheless, culture without pentose addition presents the best sustainability results.

Dokumenttien hallinta voimalaitosliiketoiminnassa

Diplomityön tavoitteena oli löytää voimalaitosprojektin dokumenttien hallinnan epäjatkuvuuskohdat, mikä ne aiheuttaa ja millä toimenpiteillä dokumenttien hallintaa voidaan parantaa. Tietojärjestelmien, tiedon ja dokumenttien hallinnan merkitys kasvaa yhä enenevässä määrin globaalissa verkostoliiketoiminnassa. Tieto on varastoituna voimalaitoksen suunnittelu-, rakentamis- sekä käyttö- ja ylläpitodokumenteissa. Dokumentit pitää pystyä jäljittämään tietojärjestelmistä ajasta ja paikasta riippumatta laitoksen koko elinkaaren ajan. Laitosdokumentaatiota hyödynnetään laitoksen käyttö- ja ylläpitotoimintojen, tuotekehityksen sekä uusien projektien lähtötietona. Haastatteluilla selvitettiin dokumentoinnin tilaa eräässä laajassa hajautetussa voimalaitosprojektissa. Haastattelujen tuloksia ja yrityksen sisäistä dokumentoinnin ohjeistusta vertaamalla havaittiin, että tiedon siirtoa myynniltä projektille tulee kehittää, samoin kuin dokumenttien tarkastus- ja hyväksymiskäytäntöjä. Dokumenttien käytettävyys edellyttää tietojärjestelmien integrointia ja metatietojen määrittelyä. Työn tuloksena on syntynyt karkean tason tietovirtakaavio sekä dokumentoinnin prosessikuvaukset parantamaan yrityksen ja sen alihankkijoiden välistä kommunikaatiota.

Effect of sugarcane harvesting systems on soil carbon stocks in Brazil: an examination of existing data

Agricultural management practices that promote net carbon (C) accumulation in the soil have been considered as an important potential mitigation option to combat global warming. The change in the sugarcane harvesting system, to one which incorporates C into the soil from crop residues, is the focus of this work. The main objective was to assess and discuss the changes in soil organic C stocks caused by the conversion of burnt to unburnt sugarcane harvesting systems in Brazil, when considering the main soils and climates associated with this crop. For this purpose, a dataset was obtained from a literature review of soils under sugarcane in Brazil. Although not necessarily from experimental studies, only paired comparisons were examined, and for each site the dominant soil type, topography and climate were similar. The results show a mean annual C accumulation rate of 1.5 Mg ha-1 year-1 for the surface to 30-cm depth (0.73 and 2.04 Mg ha-1 year-1 for sandy and clay soils, respectively) caused by the conversion from a burnt to an unburnt sugarcane harvesting system. The findings suggest that soil should be included in future studies related to life cycle assessment and C footprint of Brazilian sugarcane ethanol.

Modelling life history strategies with capture-recapture data: Evolutionary demography of the water skink Eulamprus tympanum

Matrix population models, elasticity analysis and loop analysis can potentially provide powerful techniques for the analysis of life histories. Data from a capture-recapture study on a population of southern highland water skinks (Eulamprus tympanum) were used to construct a matrix population model. Errors in elasticities were calculated by using the parametric bootstrap technique. Elasticity and loop analyses were then conducted to identify the life history stages most important to fitness. The same techniques were used to investigate the relative importance of fast versus slow growth, and rapid versus delayed reproduction. Mature water skinks were long-lived, but there was high immature mortality. The most sensitive life history stage was the subadult stage. It is suggested that life history evolution in E. tympanum may be strongly affected by predation, particularly by birds. Because our population declined over the study, slow growth and delayed reproduction were the optimal life history strategies over this period. Although the techniques of evolutionary demography provide a powerful approach for the analysis of life histories, there are formidable logistical obstacles in gathering enough high-quality data for robust estimates of the critical parameters.

Studies on Procamallanus (Spirocamallanus) pereirai Annereaux, 1946 (Nematoda: Camallanidae), with new host records and new morphological data on the larval stages

Larval stages and adults of Procamallanus (Spirocamallanus) pereirai Annereaux, 1946 are described from naturally infected Paralonchurus brasiliensis (Steindachner) (Sciaenidae) from the coast of the State of Rio de Janeiro, Brazil. The translucent first-stage larvae have a denticulate process at the anterior end, no buccal capsule or esophagus undifferentiated into anterior muscular and posterior glandular parts and an elongate tail; third-stage larvae have a tail with three terminal projections, a buccal capsule divided into an anterior portion with 12-20 ridges running to the left and a posterior smooth portion, and an esophagus with muscular and glandular regions. Fourth-stage larvae exhibit a buccal capsule lacking a distinct basal ring with ridges running to the right and a tail with two terminal processes, as in adults. New host records are reported and their role in its life-cycle are discussed.

Life tables and reproductive parameters of Lutzomyia spinicrassa (Diptera: Psychodidae) under laboratory conditions

Lutzomyia spinicrassa is a vector of Leishmania braziliensis in Colombia. This sand fly has a broad geographical distribution in Colombia and Venezuela and it is found mainly in coffee plantations. Baseline biological growth data of L. spinicrassa were obtained under experimental laboratory conditions. The development time from egg to adult ranged from 59 to 121 days, with 12.74 weeks in average. Based on cohorts of 100 females, horizontal life table was constructed. The following predictive parameters were obtained: net rate of reproduction (8.4 females per cohort female), generation time (12.74 weeks), intrinsic rate of population increase (0.17), and finite rate of population increment (1.18). The reproductive value for each class age of the cohort females was calculated. Vertical life tables were elaborated and mortality was described for the generation obtained of the field cohort. In addition, for two successive generations, additive variance and heritability for fecundity were estimated.

Life Expectancy and All Age All Cause Mortality Monitoring (Overall and Health Inequalities) - Update to include data for 2007

The latest annual update on life expectancy data and all age all cause mortality rates, with data updated to 2005-07, which are used to monitor progress against Department of Health targets for overall life expectancy in England, and for the gap in life expectancy between the areas with the worst health and deprivation indicators (the Spearhead group) and the England average, was released on 13th November 2008 according to the arrangements approved by the UK Statistics Authority.

Lyfe-cycle effects on household expenditures: A latent-variable approach

Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.