Patterns of dry matter partitioning and 14C-photosynthate allocation in 1.5-year-old Scots pine seedlings

Summary

Patterns in Estonian bogs as depicted in color kite aerial photographs

Tiivistelmä: Viron soiden pinnanmuodot värillisten leijailmakuvien valossa

Microfibril angle and density patterns of fertilized and irrigated Norway spruce

Abstract

Local and Regional Scale Determinants of Biodiversity Patterns in Boreal Agricultural Landscapes

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.

Formation and Control of Trace Metal Emissions in Co-Firing of Biomass, Peat, and Wastes in Fluidised Bed Combustors

Environmentally harmful consequences of fossil fuel utilisation andthe landfilling of wastes have increased the interest among the energy producers to consider the use of alternative fuels like wood fuels and Refuse-Derived Fuels, RDFs. The fluidised bed technology that allows the flexible use of a variety of different fuels is commonly used at small- and medium-sized power plants ofmunicipalities and industry in Finland. Since there is only one mass-burn plantcurrently in operation in the country and no intention to build new ones, the co-firing of pre-processed wastes in fluidised bed boilers has become the most generally applied waste-to-energy concept in Finland. The recently validated EU Directive on Incineration of Wastes aims to mitigate environmentally harmful pollutants of waste incineration and co-incineration of wastes with conventional fuels. Apart from gaseous flue gas pollutants and dust, the emissions of toxic tracemetals are limited. The implementation of the Directive's restrictions in the Finnish legislation is assumed to limit the co-firing of waste fuels, due to the insufficient reduction of the regulated air pollutants in the existing flue gas cleaning devices. Trace metals emission formation and reduction in the ESP, the condensing wet scrubber, the fabric filter, and the humidification reactor were studied, experimentally, in full- and pilot-scale combustors utilising the bubbling fluidised bed technology, and, theoretically, by means of reactor model calculations. The core of the model is a thermodynamic equilibrium analysis. The experiments were carried out with wood chips, sawdust, and peat, and their refuse-derived fuel, RDF, blends. In all, ten different fuels or fuel blends were tested. Relatively high concentrations of trace metals in RDFs compared to the concentrations of these metals in wood fuels increased the trace metal concentrations in the flue gas after the boiler ten- to hundred-folds, when RDF was co-fired with sawdust in a full-scale BFB boiler. In the case of peat, lesser increase in trace metal concentrations was observed, due to the higher initial trace metal concentrations of peat compared to sawdust. Despite the high removal rate of most of the trace metals in the ESP, the Directive emission limits for trace metals were exceeded in each of the RDF co-firing tests. The dominat trace metals in fluegas after the ESP were Cu, Pb and Mn. In the condensing wet scrubber, the flue gas trace metal emissions were reduced below the Directive emission limits, whenRDF pellet was used as a co-firing fuel together with sawdust and peat. High chlorine content of the RDFs enhanced the mercuric chloride formation and hence the mercury removal in the ESP and scrubber. Mercury emissions were lower than theDirective emission limit for total Hg, 0.05 mg/Nm3, in all full-scale co-firingtests already in the flue gas after the ESP. The pilot-scale experiments with aBFB combustor equipped with a fabric filter revealed that the fabric filter alone is able to reduce the trace metal concentrations, including mercury, in the flue gas during the RDF co-firing approximately to the same level as they are during the wood chip firing. Lower trace metal emissions than the Directive limits were easily reached even with a 40% thermal share of RDF co-firing with sawdust.Enrichment of trace metals in the submicron fly ash particle fraction because of RDF co-firing was not observed in the test runs where sawdust was used as the main fuel. The combustion of RDF pellets with peat caused an enrichment of As, Cd, Co, Pb, Sb, and V in the submicron particle mode. Accumulation and release oftrace metals in the bed material was examined by means of a bed material analysis, mass balance calculations and a reactor model. Lead, zinc and copper were found to have a tendency to be accumulated in the bed material but also to have a tendency to be released from the bed material into the combustion gases, if the combustion conditions were changed. The concentration of the trace metal in the combustion gases of the bubbling fluidised bed boiler was found to be a summary of trace metal fluxes from three main sources. They were (1) the trace metal flux from the burning fuel particle (2) the trace metal flux from the ash in the bed, and (3) the trace metal flux from the active alkali metal layer on the sand (and ash) particles in the bed. The amount of chlorine in the system, the combustion temperature, the fuel ash composition and the saturation state of the bed material in regard to trace metals were discovered to be key factors affecting therelease process. During the co-firing of waste fuels with variable amounts of e.g. ash and chlorine, it is extremely important to consider the possible ongoingaccumulation and/or release of the trace metals in the bed, when determining the flue gas trace metal emissions. If the state of the combustion process in regard to trace metals accumulation and/or release in the bed material is not known,it may happen that emissions from the bed material rather than the combustion of the fuel in question are measured and reported.

Measuring irregularities and surface defects from printed patterns

Quality inspection and assurance is a veryimportant step when today's products are sold to markets. As products are produced in vast quantities, the interest to automate quality inspection tasks has increased correspondingly. Quality inspection tasks usuallyrequire the detection of deficiencies, defined as irregularities in this thesis. Objects containing regular patterns appear quite frequently on certain industries and science, e.g. half-tone raster patterns in the printing industry, crystal lattice structures in solid state physics and solder joints and components in the electronics industry. In this thesis, the problem of regular patterns and irregularities is described in analytical form and three different detection methods are proposed. All the methods are based on characteristics of Fourier transform to represent regular information compactly. Fourier transform enables the separation of regular and irregular parts of an image but the three methods presented are shown to differ in generality and computational complexity. Need to detect fine and sparse details is common in quality inspection tasks, e.g., locating smallfractures in components in the electronics industry or detecting tearing from paper samples in the printing industry. In this thesis, a general definition of such details is given by defining sufficient statistical properties in the histogram domain. The analytical definition allowsa quantitative comparison of methods designed for detail detection. Based on the definition, the utilisation of existing thresholding methodsis shown to be well motivated. Comparison of thresholding methods shows that minimum error thresholding outperforms other standard methods. The results are successfully applied to a paper printability and runnability inspection setup. Missing dots from a repeating raster pattern are detected from Heliotest strips and small surface defects from IGT picking papers.

Design Patterns in EPOC Software Development

Työssä tutkittiin oliosuunnittelumalleja EPOC-käyttöjärjestelmässä. Työssä tutkittiin sekä yleisiä suunnittelumalleja että EPOC-ympäristössä esiintyviä oliorakenteita, niiden aiheuttamia vaatimuksia sovelluksille sekä niiden käyttämisestä saatavia hyötyjä. Työssä toteutettiin EPOC-ohjelmiston suunnittelu hyödyntäen suunnittelumalleja ja periaatteita. Oliosuunnittelumallit ovat yleistyneet huomattavasti viime vuosina. Suunnittelumallien lähtökohtana ovat sekä yleiset että ympäristökohtaiset suunnitteluperiaatteet ja säännöt. Suunnittelumallit ovat osa isompaa rakennekokonaisuutta, joka käsittää sekä prosessi-, analyysi-, arkkitehtuuri- ym. malleja. Oliosuunnittelumallit nopeuttavat ja helpottavat suunnittelua sekä parantavat uudelleenkäytettävyyttä korkeammalla abstraktiotasolla. EPOC on tulevaisuuden mobiililaitteiden yleisimpiä käyttöjärjestelmiä. EPOC on kokonaisuudessaan oliopohjainen ja sisältää lukuisia oliorakenteita, joiden ymmärtäminen on sovelluskehityksen kannalta elintärkeää. Koska ympäristöt, joissa EPOC-käyttöjärjestelmää käytetään, ovat yleensä resurssien puolesta rajoittuneita, on yleisten suunnittelumallien käytössä oltava tarkkana. EPOC vaatii yleisiin suunnittelumalleihin muutoksia ja estää joidenkin käytön kokonaan.

Process intensification: From optimised flow patterns to microprocess technology

This thesis is focused on process intensification. Several significant problems and applications of this theme are covered. Process intensification is nowadays one of the most popular trends in chemical engineering and attempts have been made to develop a general, systematic methodology for intensification. This seems, however, to be very difficult, because intensified processes are often based on creativity and novel ideas. Monolith reactors and microreactors are successful examples of process intensification. They are usually multichannel devices in which a proper feed technique is important for creating even fluid distribution into the channels. Two different feed techniques were tested for monoliths. In the first technique a shower method was implemented by means of perforated plates. The second technique was a dispersion method using static mixers. Both techniques offered stable operation and uniform fluid distribution. The dispersion method enabled a wider operational range in terms of liquid superficial velocity. Using dispersion method, a volumetric gas-liquid mass transfer coefficient of 2 s-1 was reached. Flow patterns play a significant role in terms of the mixing performance of micromixers. Although the geometry of a T-mixer is simple, channel configurations and dimensions had a clear effect on mixing efficiency. The flow in the microchannel was laminar, but the formation of vortices promoted mixing in micro T-mixers. The generation of vortices was dependent on the channel dimensions, configurations and flow rate. Microreactors offer a high ratio of surface area to volume. Surface forces and interactions between fluids and surfaces are, therefore, often dominant factors. In certain cases, the interactions can be effectively utilised. Different wetting properties of solid materials (PTFE and stainless steel) were applied in the separation of immiscible liquid phases. A micro-scale plate coalescer with hydrophilic and hydrophobic surfaces was used for the continuous separation of organic and aqueous phases. Complete phase separation occurred in less than 20 seconds, whereas the separation time by settling exceeded 30 min. Fluid flows can be also intensified in suitable conditions. By adding certain additives into turbulent fluid flow, it was possible to reduce friction (drag) by 40 %. Drag reduction decreases frictional pressure drop in pipelines which leads to remarkable energy savings and decreases the size or number of pumping facilities required, e.g., in oil transport pipes. Process intensification enables operation often under more optimal conditions. The consequent cost savings from reduced use of raw materials and reduced waste lead to greater economic benefits in processing.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Market entry patterns of Finnish SMEs entering China

In 2011 China became the world’s second largest economy overtaking Japan. With its rapidly growing middle class buying diverse goods from consumption products to sophisticated technology and luxury products, it is also the fastest growing export market in the world. The purpose of this study is to examine what types of market entry modes Finnish SMEs use in China, which factors affect on their decisions and whether they have switched or combined the strategies after entering China. The goal is to understand the relevance of the entry mode choice related to the internationalization process and to evaluate how well it suits the Chinese business environment. The empirical part of the study is a semi structured qualitative analysis of six case companies that represent different industry fields. The cases were selected based on the recent literature about the Finnish industry fields China is interested in to gain knowledge and expertise from. Companies included in the study are an architect office, two pharmaceutical development companies, an ICT company, a plastic mechanics company and a clean tech company. The results of this study indicated that the market entry patterns of Finnish SMEs in China differ from each other based on the factors related to company’s background, mode concerns and Chinese market influences.