Greenhouse gas emissions from peat and biomass-derived fuels, electricity and heat — Estimation of various production chains by using LCA methodology

More discussion is required on how and which types of biomass should be used to achieve a significant reduction in the carbon load released into the atmosphere in the short term. The energy sector is one of the largest greenhouse gas (GHG) emitters and thus its role in climate change mitigation is important. Replacing fossil fuels with biomass has been a simple way to reduce carbon emissions because the carbon bonded to biomass is considered as carbon neutral. With this in mind, this thesis has the following objectives: (1) to study the significance of the different GHG emission sources related to energy production from peat and biomass, (2) to explore opportunities to develop more climate friendly biomass energy options and (3) to discuss the importance of biogenic emissions of biomass systems. The discussion on biogenic carbon and other GHG emissions comprises four case studies of which two consider peat utilization, one forest biomass and one cultivated biomasses. Various different biomass types (peat, pine logs and forest residues, palm oil, rapeseed oil and jatropha oil) are used as examples to demonstrate the importance of biogenic carbon to life cycle GHG emissions. The biogenic carbon emissions of biomass are defined as the difference in the carbon stock between the utilization and the non-utilization scenarios of biomass. Forestry-drained peatlands were studied by using the high emission values of the peatland types in question to discuss the emission reduction potential of the peatlands. The results are presented in terms of global warming potential (GWP) values. Based on the results, the climate impact of the peat production can be reduced by selecting high-emission-level peatlands for peat production. The comparison of the two different types of forest biomass in integrated ethanol production in pulp mill shows that the type of forest biomass impacts the biogenic carbon emissions of biofuel production. The assessment of cultivated biomasses demonstrates that several selections made in the production chain significantly affect the GHG emissions of biofuels. The emissions caused by biofuel can exceed the emissions from fossil-based fuels in the short term if biomass is in part consumed in the process itself and does not end up in the final product. Including biogenic carbon and other land use carbon emissions into the carbon footprint calculations of biofuel reveals the importance of the time frame and of the efficiency of biomass carbon content utilization. As regards the climate impact of biomass energy use, the net impact on carbon stocks (in organic matter of soils and biomass), compared to the impact of the replaced energy source, is the key issue. Promoting renewable biomass regardless of biogenic GHG emissions can increase GHG emissions in the short term and also possibly in the long term.

Modeling and Parameter Estimation of Double-Star Permanent Magnet Synchronous Machines

The power rating of wind turbines is constantly increasing; however, keeping the voltage rating at the low-voltage level results in high kilo-ampere currents. An alternative for increasing the power levels without raising the voltage level is provided by multiphase machines. Multiphase machines are used for instance in ship propulsion systems, aerospace applications, electric vehicles, and in other high-power applications including wind energy conversion systems. A machine model in an appropriate reference frame is required in order to design an efficient control for the electric drive. Modeling of multiphase machines poses a challenge because of the mutual couplings between the phases. Mutual couplings degrade the drive performance unless they are properly considered. In certain multiphase machines there is also a problem of high current harmonics, which are easily generated because of the small current path impedance of the harmonic components. However, multiphase machines provide special characteristics compared with the three-phase counterparts: Multiphase machines have a better fault tolerance, and are thus more robust. In addition, the controlled power can be divided among more inverter legs by increasing the number of phases. Moreover, the torque pulsation can be decreased and the harmonic frequency of the torque ripple increased by an appropriate multiphase configuration. By increasing the number of phases it is also possible to obtain more torque per RMS ampere for the same volume, and thus, increase the power density. In this doctoral thesis, a decoupled d–q model of double-star permanent-magnet (PM) synchronous machines is derived based on the inductance matrix diagonalization. The double-star machine is a special type of multiphase machines. Its armature consists of two three-phase winding sets, which are commonly displaced by 30 electrical degrees. In this study, the displacement angle between the sets is considered a parameter. The diagonalization of the inductance matrix results in a simplified model structure, in which the mutual couplings between the reference frames are eliminated. Moreover, the current harmonics are mapped into a reference frame, in which they can be easily controlled. The work also presents methods to determine the machine inductances by a finite-element analysis and by voltage-source inverters on-site. The derived model is validated by experimental results obtained with an example double-star interior PM (IPM) synchronous machine having the sets displaced by 30 electrical degrees. The derived transformation, and consequently, the decoupled d–q machine model, are shown to model the behavior of an actual machine with an acceptable accuracy. Thus, the proposed model is suitable to be used for the model-based control design of electric drives consisting of double-star IPM synchronous machines.

Estimation of weed dry biomass and grain yield as a function of growth and yield traits under allelopathic weed management in maize

Growing concerns about toxicity and development of resistance against synthetic herbicides have demanded looking for alternative weed management approaches. Allelopathy has gained sufficient support and potential for sustainable weed management. Aqueous extracts of six plant species (sunflower, rice, mulberry, maize, brassica and sorghum) in different combinations alone or in mixture with 75% reduced dose of herbicides were evaluated for two consecutive years under field conditions. A weedy check and S-metolachlor with atrazine (pre emergence) and atrazine alone (post emergence) at recommended rates was included for comparison. Weed dynamics, maize growth indices and yield estimation were done by following standard procedures. All aqueous plant extract combinations suppressed weed growth and biomass. Moreover, the suppressive effect was more pronounced when aqueous plant extracts were supplemented with reduced doses of herbicides. Brassica-sunflower-sorghum combination suppressed weeds by 74-80, 78-70, 65-68% during both years of study that was similar with S-metolachlor along half dose of atrazine and full dose of atrazine alone. Crop growth rate and dry matter accumulation attained peak values of 32.68 and 1,502 g m-2 d-1 for brassica-sunflower-sorghum combination at 60 and 75 days after sowing. Curve fitting regression for growth and yield traits predicted strong positive correlation to grain yield and negative correlation to weed dry biomass under allelopathic weed management in maize crop.

A simple model for the estimation of congenital malformation frequency in racially mixed populations

A simple model is proposed, using the method of maximum likelihood to estimate malformation frequencies in racial groups based on data obtained from hospital services. This model uses the proportions of racial admixture, and the observed malformation frequency. It was applied to two defects: postaxial polydactyly and cleft lip, the frequencies of which are recognizedly heterogeneous among racial groups. The frequencies estimated in each racial group were those expected for these malformations, which proves the applicability of the method.

A priori estimation of accuracy and of the number of wells to be employed in limiting dilution assays

The use of limiting dilution assay (LDA) for assessing the frequency of responders in a cell population is a method extensively used by immunologists. A series of studies addressing the statistical method of choice in an LDA have been published. However, none of these studies has addressed the point of how many wells should be employed in a given assay. The objective of this study was to demonstrate how a researcher can predict the number of wells that should be employed in order to obtain results with a given accuracy, and, therefore, to help in choosing a better experimental design to fulfill one's expectations. We present the rationale underlying the expected relative error computation based on simple binomial distributions. A series of simulated in machina experiments were performed to test the validity of the a priori computation of expected errors, thus confirming the predictions. The step-by-step procedure of the relative error estimation is given. We also discuss the constraints under which an LDA must be performed.

Thermal reactions of the major hydrocarbon components of biomass gasification gas

Gasification of biomass is an efficient method process to produce liquid fuels, heat and electricity. It is interesting especially for the Nordic countries, where raw material for the processes is readily available. The thermal reactions of light hydrocarbons are a major challenge for industrial applications. At elevated temperatures, light hydrocarbons react spontaneously to form higher molecular weight compounds. In this thesis, this phenomenon was studied by literature survey, experimental work and modeling effort. The literature survey revealed that the change in tar composition is likely caused by the kinetic entropy. The role of the surface material is deemed to be an important factor in the reactivity of the system. The experimental results were in accordance with previous publications on the subject. The novelty of the experimental work lies in the used time interval for measurements combined with an industrially relevant temperature interval. The aspects which are covered in the modeling include screening of possible numerical approaches, testing of optimization methods and kinetic modelling. No significant numerical issues were observed, so the used calculation routines are adequate for the task. Evolutionary algorithms gave a better performance combined with better fit than the conventional iterative methods such as Simplex and Levenberg-Marquardt methods. Three models were fitted on experimental data. The LLNL model was used as a reference model to which two other models were compared. A compact model which included all the observed species was developed. The parameter estimation performed on that model gave slightly impaired fit to experimental data than LLNL model, but the difference was barely significant. The third tested model concentrated on the decomposition of hydrocarbons and included a theoretical description of the formation of carbon layer on the reactor walls. The fit to experimental data was extremely good. Based on the simulation results and literature findings, it is likely that the surface coverage of carbonaceous deposits is a major factor in thermal reactions.

The estimation of tuberculosis transmission parameters using ABC and MCMC methods

The aim of this work is to apply approximate Bayesian computation in combination with Marcov chain Monte Carlo methods in order to estimate the parameters of tuberculosis transmission. The methods are applied to San Francisco data and the results are compared with the outcomes of previous works. Moreover, a methodological idea with the aim to reduce computational time is also described. Despite the fact that this approach is proved to work in an appropriate way, further analysis is needed to understand and test its behaviour in different cases. Some related suggestions to its further enhancement are described in the corresponding chapter.

Cholinergic stimulation with pyridostigmine reduces the QTc interval in coronary artery disease

Parasympathetic dysfunction is an independent risk factor in patients with coronary artery disease; thus, cholinergic stimulation is a potential therapeutic measure that may be protective by acting on ventricular repolarization. The purpose of the present study was to determine the effects of pyridostigmine bromide (PYR), a reversible anticholinesterase agent, on the electrocardiographic variables, particularly QTc interval, in patients with stable coronary artery disease. In a randomized double-blind crossover placebo-controlled study, simultaneous 12-lead electrocardiographic tracings were obtained at rest from 10 patients with exercise-induced myocardial ischemia before and 2 h after the oral administration of 45 mg PYR or placebo. PYR increased the RR intervals (pre: 921 ± 27 ms vs post: 1127 ± 37 ms; P<0.01) and, in contrast with placebo, decreased the QTc interval (pre: 401 ± 3 ms vs post: 382 ± 3 ms; P<0.01). No other electrocardiographic variables were modified (PR segment, QT interval, QT and QTc dispersions). Cholinergic stimulation with PYR caused bradycardia and reduced the QTc interval without important side effects in patients with coronary disease. These effects, if confirmed in studies over longer periods of administration, may suggest a cardioprotection by cholinergic stimulation with PYR.

Chronic converting enzyme inhibition normalizes QT interval in aging rats

The aim of the present study was to investigate the effects of converting enzyme inhibition by captopril on ECG parameters in aged rats. Four-month-old male rats received captopril dissolved in tap water (0.5 mg/l) or tap water for 2 or 20 months. At the end of treatment, under anesthesia, RR and PR interval, P wave and QRS duration, QT and corrected QT interval were measured in all animals. On the following day, chronic ECG (lead II) recordings were performed to quantify supraventricular (SVPB) or ventricular premature beats (VPB). After sacrifice, the hearts were removed and weighed. RR interval was similar in young and untreated aged rats, but significantly larger in aged rats treated with captopril. P wave and QRS length did not differ among groups. PR interval was significantly larger in old than in young rats and was not affected by captopril. Corrected QT interval was larger in aged than in young rats (117 ± 4 vs 64 ± 6 ms, P<0.05) and was reduced by captopril (71 ± 6 ms, P<0.05). VPB were absent in young rats and highly frequent in untreated old animals (8.4 ± 3.0/30 min). Captopril significantly reduced VPB in old rats (0.3 ± 0.1/30 min, P<0.05). The cardiac hypertrophy found in untreated aged rats was prevented by captopril (3.44 ± 0.14 vs 3.07 ± 0.10 mg/g, P<0.05). The beneficial effects of angiotensin converting enzyme inhibition on the rat heart during the aging process are remarkable.

Advanced epithelial ovarian cancer – studies on preoperative [18F] FDG PET/CT and HE4 profile during primary chemotherapy

Epithelial ovarian cancer (EOC) is usually diagnosed in an advanced stage. The prognosis depends highly on the amount of the residual tumor in surgery. In patients with extensive disease, neoadjuvant chemotherapy (NACT) is used to diminish the tumor load before debulking surgery. New non-invasive methods are needed to preoperatively evaluate the disease dissemination and operability. [18F] FDG PET/CT (Positron emission tomography/computed tomography) is a promising method for cancer diagnostics and staging. The biomarker profiles during treatment can predict patient’s outcome. This prospective study included 41 EOC patients, 21 treated with primary surgery and 20 with NACT and interval surgery. The performances of preoperative contrast enhanced PET/CT (PET/ceCT) and diagnostic CT (ceCT) were compared. Perioperative visual estimation of tumor spread was studied in primary and interval surgery. The profile of the serum marker HE4 (Human epididymis 4) during primary chemotherapy was evaluated. In primary surgery, surgical findings were found to form an adequate reference standard for imaging studies. After NACT, the sensitivity for visual estimation of cancer dissemination was significantly worse. Preoperative PET/ceCT was more effective than ceCT alone in detecting extra-abdominal disease spread. The high number of supradiaphragmatic lymph node metastases detected by PET/ceCT at the time of diagnosis brings new insight in EOC spread patterns. The sensitivity of both PET/CT and ceCT remained modest in intra-abdominal areas important to operability. The HE4 profile was in concordance with the CA125 profile during primary chemotherapy. Its role in the evaluation of EOC chemotherapy response will be clarified in further studies.

An analysis of the electrocardiogram QT interval

No reports testing the efficacy of the use of the QT/RR ratio <1/2 for detecting a normal QTc interval were found in the literature. The objective of the present study was to determine if a QT/RR ratio <=1/2 can be considered to be equal to the normal QTc and to compare the QT and QTc measured and calculated clinically and by a computerized electrocardiograph. Ratios (140 QT/RR) of 28 successive electrocardiograms obtained from 28 consecutive patients in a tertiary level teaching hospital were analyzed clinically by 5 independent observers and by a computerized electrocardiograph. The QT/RR ratio provided 56% sensitivity and 78% specificity, with an area under the receiver operator characteristic curve of 75.8% (95%CI: 0.68 to 0.84). The divergence in QT and QTc interval measurements between clinical and computerized evaluation were 0.01 ± 0.03 s (95%CI: 0.04-0.02) and 0.01 ± 0.04 s (95%CI: -0.05-0.03), respectively. The QT and QTc values measured clinically and by a computerized electrocardiograph were similar. The QT/RR ratio <=1/2 was not a satisfactory index for QTc evaluation because it could not predict a normal QTc value.

Net working capital estimation model in project business

The objective of this Master’s thesis is to develop a model which estimates net working capital (NWC) monthly in a year period. The study is conducted by a constructive research which uses a case study. The estimation model is designed in the need of one case company which operates in project business. Net working capital components should be linked together by an automatic model and estimated individually, including advanced components of NWC for example POC receivables. Net working capital estimation model of this study contains three parts: output template, input template and calculation model. The output template gets estimate values automatically from the input template and the calculation model. Into the input template estimate values of more stable NWC components are inputted manually. The calculate model gets estimate values for major affecting components automatically from the systems of a company by using a historical data and made plans. As a precondition for the functionality of the estimation calculation is that sales are estimated in one year period because the sales are linked to all NWC components.

Power efficiency estimation and simulation of different control methods for the rotary screw compressor

Nowadays the energy efficiency has become one of the most concerned topics. Compressors are the equipment, which is very common in industry. Moreover, they tend to operate during long cycles and therefore even small decrease in power consumption can significantly reduce electricity costs during the year. And therefore it is important to investigate ways of increasing the energy efficiency of the compressors. In the thesis rotary screw compressor alongside with different control approaches is described. Simulation models for various control types of rotary screw compressor are developed. Analysis of laboratory equipment is conducted and results are compared with simulation. Suggestions of the real laboratory equipment improvement are given.

Training-related changes in the R-R interval at the onset of passive movements in humans

The aim of the present study was to determine whether training-related alterations in muscle mechanoreflex activation affect cardiac vagal withdrawal at the onset of exercise. Eighteen male volunteers divided into 9 controls (26 ± 1.9 years) and 9 racket players (25 ± 1.9 years) performed 10 s of voluntary and passive movement characterized by the wrist flexion of their dominant and non-dominant limbs. The respiratory cycle was divided into four phases and the phase 4 R-R interval was measured before and immediately following the initiation of either voluntary or passive movement. At the onset of voluntary exercise, the decrease in R-R interval was similar between dominant and non-dominant forearms in both controls (166 ± 20 vs 180 ± 34 ms, respectively; P > 0.05) and racket players (202 ± 29 vs 201 ± 31 ms, respectively; P > 0.05). Following passive movement, the non-dominant forearm of racket players elicited greater changes than the dominant forearm (129 ± 30 vs 77 ± 17 ms; P < 0.05), as well as both the dominant (54 ± 20 ms; P < 0.05) and non-dominant (59 ± 14 ms; P < 0.05) forearms of control subjects. In contrast, changes in R-R interval elicited by the racket players' dominant forearm were similar to that observed in the control group, indicating that changes in R-R interval at the onset of passive exercise were not attenuated in the dominant forearm of racket players. In summary, cardiac vagal withdrawal induced by muscle mechanoreflex stimulation is well-maintained, despite long-term exposure to training.

A simple test of muscle coactivation estimation using electromyography

In numerous motor tasks, muscles around a joint act coactively to generate opposite torques. A variety of indexes based on electromyography signals have been presented in the literature to quantify muscle coactivation. However, it is not known how to estimate it reliably using such indexes. The goal of this study was to test the reliability of the estimation of muscle coactivation using electromyography. Isometric coactivation was obtained at various muscle activation levels. For this task, any coactivation measurement/index should present the maximal score (100% of coactivation). Two coactivation indexes were applied. In the first, the antagonistic muscle activity (the lower electromyographic signal between two muscles that generate opposite joint torques) is divided by the mean between the agonistic and antagonistic muscle activations. In the second, the ratio between antagonistic and agonistic muscle activation is calculated. Moreover, we computed these indexes considering different electromyographic amplitude normalization procedures. It was found that the first algorithm, with all signals normalized by their respective maximal voluntary coactivation, generates the index closest to the true value (100%), reaching 92 ± 6%. In contrast, the coactivation index value was 82 ± 12% when the second algorithm was applied and the electromyographic signal was not normalized (P < 0.04). The new finding of the present study is that muscle coactivation is more reliably estimated if the EMG signals are normalized by their respective maximal voluntary contraction obtained during maximal coactivation prior to dividing the antagonistic muscle activity by the mean between the agonistic and antagonistic muscle activations.