Developing markets of energy biomass – local and global perspectives

The thesis explores global and national-level issues related to the development of markets for biomass for energy. The thesis consists of five separate papers and provides insights on selected issues. The aim of Paper I was to identify methodological and statistical challenges in assessing international solid and liquid biofuels trade and provide an overview of the Finnish situation with respect to the status of international solid and liquid biofuels trade. We found that, for the Finnish case, it is possible to qualify direct and indirect trade volumes of biofuels. The study showed that indirect trade of biofuels has a highly significant role in Finland and may be a significant sector also in global biofuels trade. The purpose of Paper II was to provide a quantified insight into Finnish prospects for meeting the national 2020 renewable energy targets and concurrently becoming a largescale producer of forest-biomass-based second-generation biofuels for feeding increasing demand in European markets. We found that Finland has good opportunities to realise a scenario to meet 2020 renewable energy targets and for large-scale production of wood-based biofuels. The potential net export of transport biofuels from Finland in 2020 would correspond to 2–3% of European demand. Paper III summarises the global status of international solid and liquid biofuels trade as illuminated by several separate sources. International trade of biofuels was estimated at nearly 1 EJ for 2006. Indirect trade of biofuels through trading of industrial roundwood and material by-products comprises the largest proportion of the trading, with a share of about two thirds. The purpose of Paper IV was to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value-added chain of biomass and bioenergy. Regardless of the intensive work that has been done in the field of sustainability schemes and principles concerning use of biomass for energy, weaknesses still exist. The objective of Paper V was to clarify the alternative scenarios for the international biomass market until 2020 and identify the underlying steps needed toward a wellfunctioning and sustainable market for biomass for energy purposes. An overall conclusion drawn from this analysis concerns the enormous opportunities related to the utilisation of biomass for energy in the coming decades.

Solution Business Model for Energy Efficiency

This study examined solution business models and how they could be applied into energy efficiency business. The target of this study was to find out, what a functional solution business model applied to energy efficiency improvement projects is like. The term “functionality” was used to refer not only to the economic viability but to environmental and legal aspects and also to the implement of Critical Success Factors (CSFs) and the ability to overcome the most important market barriers and risks. This thesis is based on a comprehensive literature study on solution business, business models and energy efficiency business. This literature review was used as a foundation to an energy efficiency solution business model scheme. The created scheme was tested in a case study which studied two different energy efficiency improvement projects, illustrated the functionality of the created business model and evaluated their potential as customer targets. Solution approach was found to be suitable for energy efficiency business. The most important characteristics of a good solution business model were identified to be the relationship between the supplier and customer, a proper network, knowledge on the customer’s process and supreme technological expertise. Thus the energy efficiency solution business was recognized to be particularly suitable for example for energy suppliers or technological equipment suppliers. Because the case study was not executed from a certain company’s point of view, the most important factors such as relationships and the availability of funding could not be evaluated. Although the energy efficiency business is recognized to be economically viable, the most important factors influencing the profitability and the success of energy efficiency solution business model were identified to be the proper risk management, the ability to overcome market barriers and the realization of CSFs.

Cyanobacteria from the Baltic Sea and Finnish lakes as an energy source and modulators of bioenergetic pathways

Cyanobacteria are a diverse group of oxygenic photosynthetic bacteria that inhabit in a wide range of environments. They are versatile and multifaceted organisms with great possibilities for different biotechnological applications. For example, cyanobacteria produce molecular hydrogen (H2), which is one of the most important alternatives for clean and sustainable energy. Apart from being beneficial, cyanobacteria also possess harmful characteristics and may become a source of threat to human health and other living organisms, as they are able to form surface blooms that are producing a variety of toxic or bioactive compounds. The University of Helsinki Culture Collection (UHCC) maintains around 1,000 cyanobacterial strains representing a large number of genera and species isolated from the Baltic Sea and Finnish lakes. The culture collection covers different life forms such as unicellular and filamentous, N2-fixing and non-N2-fixing strains, and planktonic and benthic cyanobacteria. In this thesis, the UHCC has been screened to identify potential strains for sustainable biohydrogen production and also for strains that produce compounds modifying the bioenergetic pathways of other cyanobacteria or terrestrial plants. Among the 400 cyanobacterial strains screened so far, ten were identified as high H2-producing strains. The enzyme systems involved in H2 metabolism of cyanobacteria were analyzed using the Southern hybridization approach. This revealed the presence of the enzyme nitrogenase in all strains tested, while none of them are likely to have contained alternative nitrogenases. All the strains tested, except for two Calothrix strains, XSPORK 36C and XSPORK 11A, were suggested to contain both uptake and bidirectional hydrogenases. Moreover, 55 methanol extracts of various cyanobacterial strains were screened to identify potent bioactive compounds affecting the photosynthetic apparatus of the model cyanobacterium, Synechocystis PCC 6803. The extract from Nostoc XPORK 14A was the only one that modified the photosynthetic machinery and dark respiration. The compound responsible for this effect was identified, purified, and named M22. M22 demonstrated a dual-action mechanism: production of reactive oxygen species (ROS) under illumination and an unknown mechanism that also prevailed in the dark. During summer, the Baltic Sea is occupied by toxic blooms of Nodularia spumigena (hereafter referred to as N. spumigena), which produces a hepatotoxin called nodularin. Long-term exposure of the terrestrial plant spinach to nodularin was studied. Such treatment resulted in inhibition of growth and chlorosis of the leaves. Moreover, the activity and amount of mitochondrial electron transfer complexes increased in the leaves exposed to nodularin-containing extract, indicating upregulation of respiratory reactions, whereas no marked changes were detected in the structure or function of the photosynthetic machinery. Nodularin-exposed plants suffered from oxidative stress, evidenced by oxidative modifications of various proteins. Plants initiated strategies to combat the stress by increasing the levels of alpha-tocopherol, mitochondrial alternative oxidase (AOX), and mitochondrial ascorbate peroxidase (mAPX).

Improving strategic decision-making with simulation based decision support systems

Combating climate change is one of the key tasks of humanity in the 21st century. One of the leading causes is carbon dioxide emissions due to usage of fossil fuels. Renewable energy sources should be used instead of relying on oil, gas, and coal. In Finland a significant amount of energy is produced using wood. The usage of wood chips is expected to increase in the future significantly, over 60 %. The aim of this research is to improve understanding over the costs of wood chip supply chains. This is conducted by utilizing simulation as the main research method. The simulation model utilizes both agent-based modelling and discrete event simulation to imitate the wood chip supply chain. This thesis concentrates on the usage of simulation based decision support systems in strategic decision-making. The simulation model is part of a decision support system, which connects the simulation model to databases but also provides a graphical user interface for the decisionmaker. The main analysis conducted with the decision support system concentrates on comparing a traditional supply chain to a supply chain utilizing specialized containers. According to the analysis, the container supply chain is able to have smaller costs than the traditional supply chain. Also, a container supply chain can be more easily scaled up due to faster emptying operations. Initially the container operations would only supply part of the fuel needs of a power plant and it would complement the current supply chain. The model can be expanded to include intermodal supply chains as due to increased demand in the future there is not enough wood chips located close to current and future power plants.

Evaluating the Maturity of Data Management Practices in a Major Energy Provider Company

Data is the most important asset of a company in the information age. Other assets, such as technology, facilities or products can be copied or reverse-engineered, employees can be brought over, but data remains unique to every company. As data management topics are slowly moving from unknown unknowns to known unknowns, tools to evaluate and manage data properly are developed and refined. Many projects are in progress today to develop various maturity models for evaluating information and data management practices. These maturity models come in many shapes and sizes: from short and concise ones meant for a quick assessment, to complex ones that call for an expert assessment by experienced consultants. In this paper several of them, made not only by external inter-organizational groups and authors, but also developed internally at a Major Energy Provider Company (MEPC) are juxtaposed and thoroughly analyzed. Apart from analyzing the available maturity models related to Data Management, this paper also selects the one with the most merit and describes and analyzes using it to perform a maturity assessment in MEPC. The utility of maturity models is two-fold: descriptive and prescriptive. Besides recording the current state of Data Management practices maturity by performing the assessments, this maturity model is also used to chart the way forward. Thus, after the current situation is presented, analysis and recommendations on how to improve it based on the definitions of higher levels of maturity are given. Generally, the main trend observed was the widening of the Data Management field to include more business and “soft” areas (as opposed to technical ones) and the change of focus towards business value of data, while assuming that the underlying IT systems for managing data are “ideal”, that is, left to the purely technical disciplines to design and maintain. This trend is not only present in Data Management but in other technological areas as well, where more and more attention is given to innovative use of technology, while acknowledging that the strategic importance of IT as such is diminishing.

Structural and operational optimisation : applications in energy systems

In this work mathematical programming models for structural and operational optimisation of energy systems are developed and applied to a selection of energy technology problems. The studied cases are taken from industrial processes and from large regional energy distribution systems. The models are based on Mixed Integer Linear Programming (MILP), Mixed Integer Non-Linear Programming (MINLP) and on a hybrid approach of a combination of Non-Linear Programming (NLP) and Genetic Algorithms (GA). The optimisation of the structure and operation of energy systems in urban regions is treated in the work. Firstly, distributed energy systems (DES) with different energy conversion units and annual variations of consumer heating and electricity demands are considered. Secondly, district cooling systems (DCS) with cooling demands for a large number of consumers are studied, with respect to a long term planning perspective regarding to given predictions of the consumer cooling demand development in a region. The work comprises also the development of applications for heat recovery systems (HRS), where paper machine dryer section HRS is taken as an illustrative example. The heat sources in these systems are moist air streams. Models are developed for different types of equipment price functions. The approach is based on partitioning of the overall temperature range of the system into a number of temperature intervals in order to take into account the strong nonlinearities due to condensation in the heat recovery exchangers. The influence of parameter variations on the solutions of heat recovery systems is analysed firstly by varying cost factors and secondly by varying process parameters. Point-optimal solutions by a fixed parameter approach are compared to robust solutions with given parameter variation ranges. In the work enhanced utilisation of excess heat in heat recovery systems with impingement drying, electricity generation with low grade excess heat and the use of absorption heat transformers to elevate a stream temperature above the excess heat temperature are also studied.

The energy efficiency of chilled beam systems in an office building at different climates

Besides the sustaining of healthy and comfortable indoor climate, the air conditioning system should also achieve for energy efficiency. The target indoor climate can be ob-tained with different systems; this study focuses on comparing the energy efficiency of different air conditioning room unit systems in different climates. The calculations are made with dynamic energy simulation software IDA ICE by comparing the indoor cli-mate and energy consumption of an office building with different systems in different climates. The aim of the study is to compare the energy efficiency of chilled beam systems to other common systems: variable air volume, fan coil and radiant ceiling systems. Besides the annual energy consumption also the sustainability of target indoor climate is compared between the simulations. Another aim is to provide conclusions to be used in the product development of the chilled beam systems’ energy efficiency. The adaptable chilled beam system and the radiant ceiling system prove to be energy efficient independent of the climate. The challenge of reliable comparison is that other systems are not able to reach the target indoor climate as well as the others. The complex calculation environment of the simulation software, made assumptions and excluding of the financial aspects complicate comparing the big picture. The results show that the development of the chilled beam systems should concentrate on energy efficient night heating, flexible demand based ventilation and capacity control and possibilities on integrating the best practices with other systems. 

Energy Efficiency of a Diesel-Electric MobileWorking Machine

The power demand of many mobile working machines such as mine loaders, straddle carriers and harvesters varies significantly during operation, and typically, the average power demand of a working machine is considerably lower than the demand for maximum power. Consequently, for most of the time, the diesel engine of a working machine operates at a poor efficiency far from its optimum efficiency range. However, the energy efficiency of dieseldriven working machines can be improved by electric hybridization. This way, the diesel engine can be dimensioned to operate within its optimum efficiency range, and the electric drive with its energy storages responds to changes in machine loading. A hybrid working machine can be implemented in many ways either as a parallel hybrid, a series hybrid or a combination of these two. The energy efficiency of hybrid working machines can be further enhanced by energy recovery and reuse. This doctoral thesis introduces the component models required in the simulation model of a working machine. Component efficiency maps are applied to the modelling; the efficiency maps for electrical machines are determined analytically in the whole torque–rotational speed plane based on the electricalmachine parameters. Furthermore, the thesis provides simulation models for parallel, series and parallel-series hybrid working machines. With these simulation models, the energy consumption of the working machine can be analysed. In addition, the hybridization process is introduced and described. The thesis provides a case example of the hybridization and dimensioning process of a working machine, starting from the work cycle of the machine. The selection and dimensioning of the hybrid system have a significant impact on the energy consumption of a hybrid working machine. The thesis compares the energy consumption of a working machine implemented by three different hybrid systems (parallel, series and parallel-series) and with different component dimensions. The payback time of a hybrid working machine and the energy storage lifetime are also estimated in the study.

Waste-to-Energy Scenarios in the China Context

Waste incineration plants are increasingly established in China. A low heating value and high moisture content, due to a large proportion of biowaste in the municipal solid waste (MSW), can be regarded as typical characteristics of Chinese MSW. Two incineration technologies have been mainly established in China: stoker grate and circular fluidized bed (CFB). Both of them are designed to incinerate mixed MSW. However, there have been difficulties to reach the sufficient temperature in the combustion process due to the low heating value of the MSW. That is contributed to the usage of an auxiliary fossil fuel, which is often used during the whole incineration process. The objective of this study was to design alternative Waste-to-energy (WTE) scenarios for existing WTE plants with the aim to improve the material and energy efficiency as well as the feasibility of the plants. Moreover, the aim of this thesis was to find the key factors that affect to the feasibility of the scenarios. Five different WTE plants were selected as study targets. The necessary data for calculation was gained from literature as well as received from the operators of the target WTE plants. The created scenarios were based on mechanical-biological treatment (MBT) technologies, in which the produced solid recovered fuel (SRF) was fed as an auxiliary fuel into a WTE plant replacing the fossil fuel. The mechanically separated biowaste was treated either in an anaerobic digestion (AD) plant, a biodrying plant, a thermal drying plant, or a combined AD plant + thermal drying plant. An interactive excel spreadsheet based computation tool was designed to estimate the viability of the scenarios in different WTE cases. The key figures of the improved material and energy efficiency, such as additional electricity generated and avoided waste for landfill, were got as results. Furthermore, economic indicators such as annual profits (or costs), payback period, and internal rate of return (IRR) were gained as results. The results show that the AD scenario was the most profitable in most of the cases. The current heating value of MSW and the tipping fee for the received MSW appeared as the most important factor in terms of feasibility.

Actively crafting customer value or merely representing a solution? Linking value-based selling to salesperson performance

Value-based selling is a salesperson behavioral mode which concentrates on generating superior customer value. Although service dominant logic emphasizes customer value as a central tenet for achieving strategic objectives, sales management literature has predominantly circumvented the subject matter of customer value. The purpose of this thesis is to demonstrate the distinctiveness and positive sales performance outcomes of value-based selling. Additionally, performance outcomes of value-based selling are contrasted with other key sales behaviors, selling skills and motivational orientations. As a part of this thesis, large-scale survey of 730 respondents was collected. The survey was tailored for the needs of a value-based selling research group led by Ph.D. Harri Terho. The research group used convenience sampling to select the salespeople of 25 medium- and large-scale companies in Finland which currently either practice value-based selling or consider developing these activities. This thesis contains three key findings: value-based selling is established as a distinct sales behavior, it relates directly and positively to salesperson performance and it explains the link between customer-oriented selling and salesperson performance. Value-based selling relates to salesperson performance especially in the following GICS-sectors: energy, industrials and materials. However, relationship selling relates to performance strongest in the energy sector and adaptive selling in industrials sector. In sum, it is evident that actively crafting customer value is a successful sales behavior in many business-to-business marketing environments while other sales behaviors, excluding customer-oriented selling, still uphold their significance.

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.

The effects of location, feedstock availability, and supply-chain logistics on the greenhouse gas emissions of forest-biomass energy utilization in Finland

Forest biomass represents a geographically distributed feedstock, and geographical location affects the greenhouse gas (GHG) performance of a given forest-bioenergy system in several ways. For example, biomass availability, forest operations, transportation possibilities and the distances involved, biomass end-use possibilities, fossil reference systems, and forest carbon balances all depend to some extent on location. The overall objective of this thesis was to assess the GHG emissions derived from supply and energy-utilization chains of forest biomass in Finland, with a specific focus on the effect of location in relation to forest biomass’s availability and the transportation possibilities. Biomass availability and transportation-network assessments were conducted through utilization of geographical information system methods, and the GHG emissions were assessed by means of lifecycle assessment. The thesis is based on four papers in which forest biomass supply on industrial scale was assessed. The feedstocks assessed in this thesis include harvesting residues, smalldiameter energy wood and stumps. The principal implication of the findings in this thesis is that in Finland, the location and availability of biomass in the proximity of a given energyutilization or energy-conversion plant is not a decisive factor in supply-chain GHG emissions or the possible GHG savings to be achieved with forest-biomass energy use. Therefore, for the greatest GHG reductions with limited forest-biomass resources, energy utilization of forest biomass in Finland should be directed to the locations where most GHG savings are achieved through replacement of fossil fuels. Furthermore, one should prioritize the types of forest biomass with the lowest direct supply-chain GHG emissions (e.g., from transport and comminution) and the lowest indirect ones (in particular, soil carbon-stock losses), regardless of location. In this respect, the best combination is to use harvesting residues in combined heat and power production, replacing peat or coal.

Spatial multicriteria decision analysis for the siting of on-shore wind power in Kemiönsaari

Wind power is a low-carbon energy production form that reduces the dependence of society on fossil fuels. Finland has adopted wind energy production into its climate change mitigation policy, and that has lead to changes in legislation, guidelines, regional wind power areas allocation and establishing a feed-in tariff. Wind power production has indeed boosted in Finland after two decades of relatively slow growth, for instance from 2010 to 2011 wind energy production increased with 64 %, but there is still a long way to the national goal of 6 TWh by 2020. This thesis introduces a GIS-based decision-support methodology for the preliminary identification of suitable areas for wind energy production including estimation of their level of risk. The goal of this study was to define the least risky places for wind energy development within Kemiönsaari municipality in Southwest Finland. Spatial multicriteria decision analysis (SMCDA) has been used for searching suitable wind power areas along with many other location-allocation problems. SMCDA scrutinizes complex ill-structured decision problems in GIS environment using constraints and evaluation criteria, which are aggregated using weighted linear combination (WLC). Weights for the evaluation criteria were acquired using analytic hierarchy process (AHP) with nine expert interviews. Subsequently, feasible alternatives were ranked in order to provide a recommendation and finally, a sensitivity analysis was conducted for the determination of recommendation robustness. The first study aim was to scrutinize the suitability and necessity of existing data for this SMCDA study. Most of the available data sets were of sufficient resolution and quality. Input data necessity was evaluated qualitatively for each data set based on e.g. constraint coverage and attribute weights. Attribute quality was estimated mainly qualitatively by attribute comprehensiveness, operationality, measurability, completeness, decomposability, minimality and redundancy. The most significant quality issue was redundancy as interdependencies are not tolerated by WLC and AHP does not include measures to detect them. The third aim was to define the least risky areas for wind power development within the study area. The two highest ranking areas were Nordanå-Lövböle and Påvalsby followed by Helgeboda, Degerdal, Pungböle, Björkboda, and Östanå-Labböle. The fourth aim was to assess the recommendation reliability, and the top-ranking two areas proved robust whereas the other ones were more sensitive.

Homogeneous assay technologies in drug screening: Quenching Resonance Energy Transfer (QRET) technique

Information gained from the human genome project and improvements in compound synthesizing have increased the number of both therapeutic targets and potential lead compounds. This has evolved a need for better screening techniques to have a capacity to screen number of compound libraries against increasing amount of targets. Radioactivity based assays have been traditionally used in drug screening but the fluorescence based assays have become more popular in high throughput screening (HTS) as they avoid safety and waste problems confronted with radioactivity. In comparison to conventional fluorescence more sensitive detection is obtained with time-resolved luminescence which has increased the popularity of time-resolved fluorescence resonance energy transfer (TR-FRET) based assays. To simplify the current TR-FRET based assay concept the luminometric homogeneous single-label utilizing assay technique, Quenching Resonance Energy Transfer (QRET), was developed. The technique utilizes soluble quencher to quench non-specifically the signal of unbound fraction of lanthanide labeled ligand. One labeling procedure and fewer manipulation steps in the assay concept are saving resources. The QRET technique is suitable for both biochemical and cell-based assays as indicated in four studies:1) ligand screening study of β2 -adrenergic receptor (cell-based), 2) activation study of Gs-/Gi-protein coupled receptors by measuring intracellular concentration of cyclic adenosine monophosphate (cell-based), 3) activation study of G-protein coupled receptors by observing the binding of guanosine-5’-triphosphate (cell membranes), and 4) activation study of small GTP binding protein Ras (biochemical). Signal-to-background ratios were between 2.4 to 10 and coefficient of variation varied from 0.5 to 17% indicating their suitability to HTS use.

Magnesium hydroxide-based peroxide bleaching of high-brightness mechanical pulps

A high final brightness is desired in most paper and board products. This requires bleaching processes that are able to produce high-brightness pulps. Mechanical pulps are widely bleached for high brightness using alkaline hydrogen peroxide with traditional sodium hydroxide and sodium silicate as additives. With high doses however, peroxide bleaching causes high organic loads in the mill effluent and anionic trash carry-over to papermaking. To alleviate the problems that arise from the use of sodium-based additives in peroxide bleaching, interest in the use of alternative magnesium-based chemicals has increased. In this study, a new, technical high-purity magnesium hydroxide-based bleaching additive was evaluated on laboratory-scale, pilot-scale and mill-scale experiments and trials for its ability to produce a high brightness in peroxide bleaching without the known problems of sodium-based chemicals. The key findings of this study include: a high brightening potential of peroxide bleaching using the Mg(OH)2-based additive, significant reductions (40-70%) in all categories of environmental load, and cationic demand lowered by 60-70% in bleached pulp with no loss in strength properties or in sheet bulk. When used in TMP refiner bleaching, the Mg(OH)2-based additive resulted in savings in specific energy consumption and provided a good bleaching response.