Matemaattis-luonnontieteellinen tiedekunta


Recent Submissions

  • Partanen, Lauri (Helsingin yliopisto, 2017)
    Sulfuric and hydrochloric acids participate in several important chemical processes occurring in the atmosphere. Due to its tendency to react with water molecules, sulfuric acid is an important factor in cloud formation and related phenomena. Hydrochloric acid is heavily implicated in stratospheric ozone depletion because of its role as a temporary reservoir for chlorine radicals. In this thesis, the thermodynamics and dynamics of these two acids are investigated. The dynamic part focuses on the chemical processes following collision of HCl on water and amorphous ice surfaces at different temperatures. By utilizing ab initio molecular dynamics, it is observed that the surface temperature and the initial kinetic energy of the HCl molecule have important and not wholly overlapping effects on its ionization behaviour. The results add to the understanding of hydrochloric acid dissociation on water surfaces in various parts of the atmosphere, potentially illuminating new pathways for related chemical reactions, such as the formation of ClNO on amorphous ice surfaces. The thermodynamic studies revolve around the impact of multiple low-lying stable conformers, or global anharmonicity, on the thermodynamic properties. The studies for this part focus on complexes of sulfuric acid, especially sulfuric acid monohydrate. Due to the relatively small size of the monohydrate, high-level ab initio methods can be employed to obtain accurate values for its thermodynamic properties, thus providing a reliable basis for comparison with less accurate approaches. New ways of accounting for global anharmonicity are developed both for small- and medium-sized clusters. For small clusters, an approximation is presented where the large amplitude motions connecting different conformers are treated separately from the rest of the vibrations, resulting in direct quantum mechanical accounting of the different conformers. In the case of medium-sized clusters, an equation based on statistical mechanics is derived to replace the erroneous Boltzmann averaging formula that has seen wide use in the literature.
  • Zou, Yuan (Helsingin yliopisto, 2017)
    Model selection is one of the fundamental tasks in scientific research. In this thesis, we addresses several research problems in statistical model selection, which aims to select a statistical model that fits the data best. We focus on the model selection problems in Bayesian networks and logistic regression from both theoretical and practical aspects. We first compare different model selection criteria for learning Bayesian networks and focus on the Fisher information approximation (FIA) criterion. We describe how FIA fails when the candidate models are complex and there is only limited data available. We show that although the Bayesian information criterion (BIC) is a more coarse than FIA, it achieves better results in most of the cases. Then, we present a method named Semstem, based on the structural expectation maximization algorithm, for learning stemmatic trees as a special type of Bayesian networks, which model the evolutionary relationships among historical manuscripts. Semstem selects best models by the maximum likelihood criterion, which is equivalent to BIC in this case. We show that Semstem achieves results with usually higher accuracies and better interpretability than other popular methods when applied on two benchmark data sets. Before we turn to the topic of learning another type of Bayesian networks, we start with a study on how to efficiently learn interactions among variables. To reduce the search space, we apply basis functions on the input variables and transform the original problem into a model selection problem in logistic regression. Then we can use Lasso to select a small set of effective predictors out of a large set of candidates. We show that the Lasso-based method is more robust than an earlier method under different situations. We extend the Lasso-based method for learning Bayesian networks with local structure, i.e. regularities in conditional probability distributions. We show that our method is more suitable than some classic methods that do not consider local structure. Moreover, when the local structure is complex, our method outperforms two other methods that are also designed for learning local structure.
  • Vira, Julius (Helsingin yliopisto, 2017)
    Atmospheric chemistry and transport models are used for a wide range of applications which include predicting dispersion of a hazardous pollutants, forecasting regional air quality, and modelling global distribution of aerosols and reactive gases. However, any such prediction is uncertain due to inaccuracies in input data, model parametrisations and lack of resolution. This thesis studies methods for integrating remote sensing and in-situ observations into atmospheric chemistry models with the aim of improving the predictions. Techniques of data assimilation, originally developed for numerical weather prediction, are evaluated for improving regional-scale predictions in two forecast experiments, one targeting the photochemical pollutants ozone (O3) and nitrogen dioxide (NO2), the other targeting sulphur dioxide (SO2). In both cases, assimilation of surface-based air quality monitoring data is found to initially improve the forecast when assessed on monitoring stations not used in assimilation. However, as the forecast length increased, the forecast converged towards the reference simulations where no data assimilation was used. The relaxation time was 6-12 hours for SO2 and SO2 and about 24 hours for O3. An alternative assimilation scheme was tested for SO2. In addition to the initial state of the forecast, the scheme adjusted the gridded emission fluxes based on the observations within the last 24 hours. The improvements due to adjustment of emissions were generally small but, where observed, the improvements persisted throughout the 48 hour forecast. The assimilation scheme was further adapted for estimating emission fluxes in volcanic eruptions. Assimilating retrievals of the Infrared Atmospheric Sounding Interferometer (IASI) instrument allowed reconstructing both the vertical and horizontal profile of SO2 emissions during the 2010 eruption of Eyjafjallajökull in Iceland. As a novel feature, retrievals of plume height were assimilated in addition to the commonly used column density retrievals. The results for Eyjafjallajökull show that the plume height retrievals provide a useful additional constraint in conditions where the vertical distribution would otherwise remain ambiguous. Finally, the thesis presents a rigorous description and evaluation of a numerical scheme for solving the advection equation. The scheme conserves tracer mass and non-negativity, and is therefore suitable for regional and global atmospheric chemistry models. The scheme is particularly adapted for handling discontinuous solutions; for smooth solutions, the scheme is nevertheless found to perform comparably to other state-of-art schemes used in atmospheric models.
  • Votsis, Athanasios (Helsingin yliopisto, 2017)
    As the adaptation of cities to climate change is increasingly overlapping sustainable urban development, the necessity to harmonize climate-proofing with economic objectives becomes ever clearer. Climate-sensitive ecological risks and amenities, and their role in markets and urban planning, are central in this issue. This research explores the reaction of urban housing markets to changes related to green amenities and flood risks; deepens the understanding of complex spatial processes, in housing markets and urban growth, that relate to the implementation of sustainable adaptation strategies; and develops advanced spatial modelling methodology that renders urban economic analysis better suitable to address questions of sustainable and climate-proof urban planning. The results demonstrate that physical or behavioral planning interventions surrounding climate-sensitive ecological risks and amenities generate economic benefits via multiple channels, when attuned with market mechanisms. This is an important building block in synchronizing climate-proofing with economic development objectives, therefore facilitating urban adaptation that is also sustainable. The synchronization requires an evidence-based understanding of the effects linked to particular interventions, at concrete locations and spatiotemporal scales. The overall message is that, while trade-offs are unavoidable, if green cities maintain agglomeration benefits, ensure increased information flows about ecological risks and amenities, while implementing amenities in a spatially parameterized manner, they are able to achieve both climate-proofing and sustainability objectives. The thesis consists of five quantitative analysis articles, while the introductory chapter synthesizes the results in the context of urban planning, spatial economics, and climate change adaptation. The first three articles apply empirical microeconometric methodologies (spatial hedonic and difference-in-differences analysis) to explore the response of housing markets to changes in green infrastructure and to policy instruments related to flood risk information. The fourth and fifth articles apply spatial complexity methods (cellular automata, fractal geometry) to extend the intuitions of microeconometric estimations into dynamic spatial processes in housing prices and urban growth. The five articles use environmental-economic datasets developed by this dissertation research, covering the urban region of Helsinki (Helsinki, Espoo, and Vantaa) and the cities of Pori and Rovaniemi.
  • Kieloaho, Antti-Jussi (Helsingin yliopisto, 2017)
    Low-molecular-weight alkyl amines are reactive organic nitrogen compounds that are im- portant precursors in secondary aerosol formation. Atmospheric aerosols have direct and indirect effects on Earth's climate system. Alkyl amines are emitted from marine and terrestrial ecosystems, agricultural activities and other anthropogenic sources. In terrestrial ecosystems, the quantities in the different parts of an ecosystem and formation processes are not well understood. Alkyl amine soil concentration and biosphere atmosphere exchange measurements are scarce. The main focus of this thesis is to determine concentrations of alkyl amines in ambient air in boreal forest and urban area, and further identify possible sources and reservoirs of alkyl amines in boreal forest. The main results presented in the thesis consist of a timeseries of gas- phase concentrations of alkyl amines measured over several months, concentrations of alkyl amines in the soil and fungal biomass, and an emission estimation based on the measured concentrations. Alkyl amines were studied in two northern latitude environments: in a boreal Scots pine (Pinus sylvestris L.) forest at the SMEAR II station in Hyytiälä and in an urban background area at the SMEAR III station in Helsinki. To quantify ambient air concentrations of alkyl amines in these environments, sample collection and analytical methods were developed. Ambient air concentrations of alkyl amines were measured from May to October 2011 in the forest site and from May to August 2011 in the urban site. The effect of the measured ambient air concentrations of alkyl amines on the local air chemistry was also assessed together with aromatic hydrocarbons and terpenoids. To assess boreal forest soil as a source of alkyl amines, a pot-scale experiment was set up. In the experiment Scots pine seedlings were grown on humus soil collected from the forest site, and the effects of Scots pine and soil organic matter (SOM) degrading enzymes on alkyl amine soil concentrations were studied. In addition, fungal strains common in boreal forest soils were cultured, and the alkyl amine concentrations in the grown fungal biomass were quanti- fied. The role of boreal forest soil as a source or as a sink of atmospheric alkyl amines was studied using a gradient-diffusion approach. In the approach, the soil atmosphere exchange of selected alkyl amines was estimated. This was done by describing dissolution/volatilisation on water and transport processes, and utilizing the quantified soil and ambient air gas-phase concentrations of the selected alkyl amines found in the studied boreal forest. The gas-phase concentrations of alkyl amines in ambient air were found to be higher in the forest site than in the urban site. In the forest site, the atmospheric concentrations appeared to be linked to soil and vegetation activity based on the seasonal course of the measured alkyl amines. Litterfall, a phenological event, coincides with the concentration maxima of some of the measured alkyl amines. In the pot-scale experiment, the SOM degrading enzymes were found to have no effect on the soil concentrations of alkyl amine while the presence of Scots pine was found to have an effect on the concentrations of some of the measured alkyl amines. The soil concentrations of alkyl amines were found to be lower than those measured from the fungal biomass. The most abundant fungal groups (ectomycorrhizal and saprotrhopic fungi) in the forest soil contained the highest quantities of alkyl amines revealing that fungal biomass may be an important reservoir of alkyl amines in boreal forest soil. Based on the flux estimate, the boreal forest soil was found to act as both a source and a sink of alkyl amines. The direction of the flux was dependent on the studied alkyl amines and environmental conditions in the forest site. Soil pH was found to be one of the most critical factors determining the direction of the flux between the soil and the atmosphere.
  • Prank, Marje (Helsingin yliopisto, 2017)
    Atmospheric composition has strong influence on human health, ecosystems and also Earth's climate. Among the atmospheric constituents, particulate matter has been recognized as both a strong climate forcer and a significant risk factor for human health, although the health relevance of the specific aerosol characteristics, such as its chemical composition, is still debated. Clouds and aerosols also contribute the largest uncertainty to the radiative budget estimates for climate projections. Thus, reliable estimates of emissions and distributions of pollutants are necessary for assessing the future climate and air-quality related health effects. Chemistry-transport models (CTMs) are valuable tools for understanding the processes influencing the atmospheric composition. This thesis consists of a collection of developments and applications of the chemistry-transport model SILAM. SILAM's ability to reproduce the observed aerosol composition was evaluated and compared with three other commonly used CTM-s in Europe. Compared to the measurements, all models systematically underestimated dry PM10 and PM2.5 by 10-60%, depending on the model and the season of the year. For majority of the PM chemical components the relative underestimation was smaller than that, exceptions being the carbonaceous particles and mineral dust - species that suffer from relatively small amount of available observational data. The study stressed the necessity for high-quality emissions from wild-land fires and wind-suspended dust, as well as the need for an explicit consideration of aerosol water content in model-measurement comparison. The average water content at laboratory conditions was estimated between 5 and 20% for PM2.5 and between 10 and 25% for PM10. SILAM predictions were used to assess the annual mortality attributable to short-term exposures to vegetation-fire originated PM2.5 in different regions in Europe. PM2.5 emitted from vegetation fires was found to be a relevant risk factor for public health in Europe, more than 1000 premature deaths per year were attributed to vegetation-fire released PM2.5. CTM predictions critically depend on emission data quality. An error was found in the EMEP anthropogenic emission inventory regarding the SOx and PM emissions of metallurgy plants on the Kola Peninsula and SILAM was applied to estimate the accuracy of the proposed correction. Allergenic pollen is arguably the type of aerosol with most widely recognised effect to health. SILAM's ability to predict allergenic pollen was extended to include Ambrosia Artemisiifolia - an invasive weed spreading in Southern Europe, with extremely allergenic pollen capable of inducing rhinoconjuctivitis and asthma in the sensitive individuals even in very low concentrations. The model compares well with the pollen observations and predicts occasional exceedances of allergy relevant thresholds even in areas far from the plants' habitat. The variations of allergenicity in grass pollen were studied and mapped to the source areas by adjoint computations with SILAM. Due to the high year-to-year variability of the observed pollen potency between the studied years and the sparse observational network, no clear geographic pattern of pollen allergenicity was detected.
  • Cole, Elizabeth (Helsingin yliopisto, 2017)
    The universe is populated with magnetically active stars. This magnetic activity is thought to be generated by dynamos operating in turbulent stellar convection zones, a process by which kinetic energy is converted into magnetic energy. The solar dynamo is but one dynamo type possible for stars. Rapidly rotating late-type stars are observed to have large spots, activity cycles, flip-flops, and active longitudes, all indicating a different dynamo mechanism may be responsible. Numerical simulations provide a tool for better understanding some of the mechanisms responsible for these dynamos. In this thesis, direct numerical simulations in spherical wedges are used to study dynamo mechanisms in the stellar convection zone. These spherical wedges are used to investigate the dependence of the resulting magnetic field on input parameters such as the density stratification and rotation rate. Mean-field models are used to evaluate the assumption that the wedges can be used to approximate full spheres. As rotation increases, differential rotation decreases in the models, in agreement with observations where more rapidly rotating stars have smaller estimates for differential rotation. As density stratification approaches more realistic values, a lat- itudinal dynamo wave with equatorward propagation is found. The impact of the domain size in the azimuthal direction on the results is explored. When the domain size is increased to 2pi in the azimuthal direction, a non-axisymmetric m = 1 mode is excited. This non-axisymmetry is reminiscent of the field configurations of rapidly rotating late-type stars. The azimuthal dynamo wave rotates nearly independently of latitude and depth, and its rotation rate is slower than that of the mean rotation of the model. This azimuthal dynamo can provide a possible explanation for the observed rotational difference of spots from the mean rotation observed on stars. The wedges use the perfect conductor boundary conditions at the latitudinal boundary to compensate for the omission of polar regions due to the time step becoming prohibitively small there. Simple mean-field models with only a latitudinal extent and perfectly conducting boundaries do not oscillate when the model is extended to the poles. Thus oscillations near the polar region may be an artifact of the boundary condition. However, when the alpha effect from mean-field dynamo theory and magnetic diffusivity are concentrated towards lower latitudes, oscillatory solutions with equatorward migration are found. When sufficient shear is added, oscillatory solutions are again found, and the Parker-Yoshimura rule for latitudinal dynamo wave propagation is obeyed. It is concluded that numerical simulations where the alpha effect and diffusivity are found to be stronger at lower latitudes and simulations with sufficient shear are considered good approximations of full spheres. These numerical simulations are put into context with stellar observations. Two young solar analogs are selected, V352 Canis Majoris and LQ Hydrae. V352 CMa is considered an active star, while LQ Hya is classified as a super-active star. The continuous period search method is applied to the low-amplitude light curves of V352 CMa. Stable active longitudes with rotation periods of 7.157 days are found. This is faster than the mean rotation of 7.24 days. Such active longitudes may be due to the underlying magnetic structure with azimuthal dynamo waves competing with differential rotation. LQ Hya rotates even more rapidly with a rotation period of only 1.600 days. A carrier period is selected of 1.605 days using the D2 statistical analysis. Primary and secondary light curve minima are found with the carrier fit analysis. No stable active longitudes are found, instead, there is only a short period spanning a few years where an active longitude may exist, but the rotation period is poorly defined. Several possible flip-flop events are identified. The azimuthal dynamo waves in numerical simulations with comparable rotation rates have a similar chaotic nature. The Doppler Imaging technique is applied to LQ Hya to examine the latitudinal spot structure. Spots at high and low latitudes are in agreement with the bimodal structure of the D2 statistic used in the carrier fit analysis. Temperature maps of LQ Hya spanning four years show an increase and a decrease in spot coverage, but no cycle can be found. Because LQ Hya is a rapidly rotating star, differential rotation is estimated to be very small. The azimuthal dynamo wave presents a new possible explanation for the jumps and trends of the spots in observations of this star.
  • Holopainen, Jani (Helsingin yliopisto, 2017)
    Bone is a fibrous nanocomposite material with a complex hierarchical system of different macro-, micro- and nanostructures. The structure elegantly supports the bone cell functions and facilitates bone remodeling by cellular activity. Injuries and diseases, e.g. osteoporosis, can cause bone fractures and loss that need to be treated with orthopedic implants. The global orthopedic market was estimated at $30 500 000 000 in 2012 and predicted to grow rapidly. A substantial amount of this goes to revision surgery due to implant failures. This not only causes unnecessary costs and work but reduces the quality of life for patients. The key for improving the performance of current implants lies in optimizing both the surface chemistry and structure from macro- to nanoscale. At best bone defects can be treated with bone scaffolds that induce formation of new bone via cellular functions and are degraded by the body thus evading the need for implant removal surgery. However, combining the favorable mechanical, structural and chemical properties poses challenges for the design and preparation methods used for bone implants and scaffolds. The aim of this work was to investigate the preparation of thin film and fibrous biomaterials for bone implants and scaffolds. New processes were developed for various biomaterials and their properties were thoroughly characterized. A method to convert CaCO3 nanostructures to nanocrystalline hydroxyapatite (HA) by treatment in phosphate solution was used to prepare HA thin films and fibers from atomic layer deposited (ALD) and electrospun CaCO3, respectively. HA fibers were also fabricated conventionally by annealing electrospun composite fibers that incorporated Ca and P precursors. Biocomposite fibers of HA nanoparticles and polylactic acid (nHA/PLA) were directly electrospun. These different nanofibers are highly interesting for bone scaffolds owing to their high surface area and the structural similarity to the fibrous nanostructure found in bone. However, conventional electrospinning is limited by its modest production rate. A needleless twisted wire electrospinning (NTWE) setup was developed to increase the production rate and was studied for the preparation of HA fibers for the bone scaffolds. Solution blow spinning (SBS) and electroblowing (EB) of HA were studied as other upscaling alternatives. Promising results were obtained in cell culture studies with the different materials. The electrospun materials could find use in fibrous bone scaffolds. The HA fibers were found out to be very interesting from a biological standpoint, but the fragility of the fibers limits their usability as such and therefore methods to incorporate bioceramic fibers into more rigid support structures should be developed. The method to prepare nanocrystalline HA by the conversion of CaCO3 proved to be highly conformal as evidenced by its ability to preserve the original shape of the ALD films and electrospun fibers. NTWE and EB were shown to be capable of producing high quality nanofibers and to provide a viable upscaling route to conventional electrospinning. In contrast, the quality of the SBS fibers needs improvement. Further work would be required to conclude if EB and NTWE are upscalable to industrial scale production levels.
  • Luoma, Samrit (Helsingin yliopisto, 2016)
    This thesis clarifies the potential impacts of climate change and sea-level rise under future climate scenarios on groundwater recharge and surface leakage, and consequently on the groundwater vulnerability of a shallow, unconfined, low-lying coastal sedimentary aquifer in southern Finland. The study utilised multiple approaches, including field investigations, well monitoring, three-dimensional (3D) geological modelling, 3D groundwater flow modelling, multivariate statistical approaches (principal component analysis (PCA) and hierarchical cluster analysis (HCA)), the stable isotopes δ2H and δ18O, conventional hydrogeochemistry and groundwater intrinsic vulnerability assessment methods. The UZF1 model was coupled with the 3D groundwater MODFLOW model to simulate flow from the unsaturated zone through the aquifer. The well-calibrated groundwater flow model was used to simulate and predict the potential impacts of climate change on groundwater recharge under future climate and sea-level rise scenarios. The results indicate changes in the groundwater recharge patterns during the years 2071 2100, with recharge occurring earlier in winter and early spring. Because the aquifer is located in a cold snow-dominated region, the seasonal impacts of climate change on groundwater recharge were more significant, with land surface overflow resulting in flooding during the winter and early spring and drought during the summer. Rising sea levels would cause some parts of the aquifer to be submerged under the sea, compromising groundwater quality due to the intrusion of seawater. This, together with increased groundwater recharge, would raise the groundwater level and consequently contribute to more surface leakage. The groundwater geochemistry of the coastal aquifer in Hanko is very similar to that of inland shallow aquifers generally in Finland, where the groundwater is mainly of the Ca HCO3 type, with low dissolved element concentrations, low pH and alkalinity, and low Ca and Mg concentrations due to rapid percolation or the short residence time. The stable isotopes δ2H and δ18O clearly suggest that the Hanko aquifer recharges directly from meteoric water (snowmelt and rainfall), with minor or insignificant contributions from the Baltic Sea and surface water. However, the geochemistry of the groundwater suggests sulphate reduction in the mixed zone between freshwater and seawater, indicating that local seawater intrusion may temporarily take place, although the contribution of seawater was found to be very low. Further inland, the influence of surface water could be observed from higher levels of KMnO4 consumption in wells near the lake above the aquifer. The findings also demonstrated that the use of stable isotopes δ2H and δ18O alone to identify seawater aquifer interaction is not sufficient to determine the rate of water exchange. The high temporal variation in groundwater chemistry directly corresponded to groundwater recharge. With an increase in groundwater recharge, KMnO4 consumption, EC, alkalinity and Ca concentrations also increased in most wells, while Fe, Al, Mn and SO4 were occasionally increased during the spring after snowmelt under specific geological conditions. Based on the future climate scenarios, precipitation in the Hanko area is expected to increase and the Baltic Sea level to rise. This could cause increased recharge of the aquifer from surface water, but also some seawater intrusion due to the sea-level rise and storm surges, as well as increased groundwater abstraction. An increase in the concentrations of some dissolved elements and changes in groundwater geochemistry along the coastline can be expected in the future. Thus, in coastal aquifers with low hydraulic gradients, the hydrogeochemistry should be used to confirm the intrusion of seawater. The PCA and HCA multivariate statistical approaches are useful tools to extract the main components that are able to identify the vulnerable areas of the aquifer impacted by natural or human activities, either on regional or site-specific scales. The integration of PCA and HCA with conventional classification of groundwater types, as well as with the hydrogeochemical data, provided an understanding of the complex groundwater flow systems, supporting aquifer vulnerability assessment and groundwater management in the future. The degree of groundwater vulnerability in the Hanko aquifer has been greatly impacted by seasonal variations in groundwater recharge during the year, and will also vary depending on climate change variability in the long term. The potential for high groundwater vulnerability to contamination from sources on the ground surface occurs during the period with a high groundwater recharge rate after snowmelt, while high vulnerability to seawater intrusion could occur when there is a low groundwater recharge rate in the dry season. This thesis study highlighted the importance of the integration of groundwater vulnerability assessment methods for shallow, unconfined, low-lying coastal aquifers from a comparison of three intrinsic vulnerability mapping methods: the AVI, a modified version of SINTACS and the GALDIT method. The modified SINTACS could be used as a guideline for groundwater vulnerability assessment of glacial and deglacial deposits in inland aquifers, and in combination with GALDIT, it could provide a useful tool for assessing groundwater vulnerability to both contamination from sources on the ground surface and to seawater intrusion for shallow, unconfined, low-lying coastal aquifers under future climate change.
  • Sukselainen, Leena (Helsingin yliopisto, 2016)
    Pliopithecoidea is an extinct and diverse superfamily of primitive catarrhine primates with no known descendants. They first appear in the fossil record in the late early Miocene China, ca. 18 17 million years ago (Ma). They were widely distributed throughout Eurasia between ca. 17 and 7 Ma and were among the first primates to be discovered and described. Despite their wide distribution, pliopithecoids are rarely found together with the contemporaneous and equally widely distributed hominoid primates. The latest known occurrence of pliopithecoids is also from China where they co-existed with hominoids in the late Miocene ca 6.9 6.2 Ma. Continuing climatic deterioration and dispersal of cercopithecoid primates from Africa may have contributed to their demise. The main objective of this study is to produce new information on pliopithecoids, their environments, as well as on environmental conditions in Eurasia during the Miocene (23 5.3 Ma), with a special focus on the middle Miocene Inner Mongolian locality of Damiao. These goals are approached first by inspecting the differences between pliopithecoid localities and other contemporaneous localities with particular focus on the rare localities of co-occurring pliopithecoid and hominoid primates. To do this we used both traditional ecological diversity analysis as well as direct ecometric method based on hypsodonty in mammalian herbivores. A closer examination of the Inner Mongolian pliopithecoid locality, Damiao, will follow, using small mammal taphonomy, faunal similarity, ecometrics, and stable isotope analyses. The aim is to understand the presence of humid-favouring pliopithecoid primates in central Asia after the middle Miocene climatic optimum (MMCO; ca. 17 15 Ma). The reason this is interesting is because it seems to contradict the general trend of strengthening climatic zonality and increasing aridity from the early Miocene onwards. The results show that pliopithecoids inhabited more humid environments than other contemporary primate groups, suggesting an inability to adapt to changing environmental conditions. The conservative nature of pliopithecoid adaptations seems to have restricted the co-occurrence of pliopithecoids and hominoids, and has been therefore rarely documented. The study also suggests that direct ecometric analysis gives a better separation of the ecological preferences of these primates than do analyses of taxonomically based community structure. The results in Damiao support previous inferences concerning the presence of locally humid environments within the increasingly arid surroundings that characterized Central Asia. Environments within the DM01 locality may have been more humid and possibly more forested and wooded, as suggested by hypsodonty, estimated mean annual precipitation (MAP), local sedimentology and large mammal fossils. We compared our results with the adjacent fossil-rich middle Miocene Tunggur localities. However, the small mammal fauna and isotope data are consistent with a mosaic of forest and grassland environment for all Damiao localities. Based on our results, Tunggur may have been too seasonal or not sufficiently humid for pliopithecoids. This idea is supported by the higher mean hypsodonty and lower predicted MAP estimates, as well as slightly higher δ13C values. We suggest that DM01, the driest known Asian pliopithecoid locality, may have been a more humid refugium within a generally drier regional context. The bone material in Damiao was mainly accumulated by predators and deposited in a fluvial setting. Some reworking by fluvial process took place in DM01 and DM02. DM16 represents the distal part of the floodplain; DM01 portrays a channel-fill; and DM02 is a result of an episodic flood discharge to the floodplain. We also show that systematic excavation for small mammals is possible, and allows for the reduction of some of the damage collecting always causes.
  • Kangas, Juho-Kustaa (Helsingin yliopisto, 2016)
    Graphical models are a framework for representing joint distributions over random variables. By capturing the structure of conditional independencies between the variables, a graphical model can express the distribution in a concise factored form that is often efficient to store and reason about. As constructing graphical models by hand is often infeasible, a lot of work has been devoted to learning them automatically from observational data. Of particular interest is the so-called structure learning problem, of finding a graph that encodes the structure of probabilistic dependencies. Once the learner has decided what constitutes a good fit to the data, the task of finding optimal structures typically involves solving an NP-hard problem of combinatorial optimization. While first algorithms for structure learning thus resorted to local search, there has been a growing interest in solving the problem to a global optimum. Indeed, during the past decade multiple exact algorithms have been proposed that are guaranteed to find optimal structures for the family of Bayesian networks, while first steps have been taken for the family of decomposable graphical models. This thesis presents combinatorial algorithms and analytical results with applications in the structure learning problem. For decomposable models, we present exact algorithms for the so-called full Bayesian approach, which involves not only finding individual structures of good fit but also computing posterior expectations of graph features, either by exact computation or via Monte Carlo methods. For Bayesian networks, we study the empirical hardness of the structure learning problem, with the aim of being able to predict the running time of various structure learning algorithms on a given problem instance. As a result, we obtain a hybrid algorithm that effectively combines the best-case performance of multiple existing techniques. Lastly, we study two combinatorial problems of wider interest with relevance in structure learning. First, we present algorithms for counting linear extensions of partially ordered sets, which is required to correct bias in MCMC methods for sampling Bayesian network structures. Second, we give results in the extremal combinatorics of connected vertex sets, whose number bounds the running time of certain algorithms for structure learning and various other problems.
  • Väänänen, Riikka (Helsingin yliopisto, 2016)
    Atmospheric aerosols have an impact on the global radiation budget, and thus on climate, they reduce the air quality and visibility, and have multiple harmful health effects. The climatic significance of aerosols result from their ability to scatter and absorb solar radiation, and, if being large enough, mediate the cloud albedo and lifetime by acting as cloud condensation nuclei (CCN). The climatic effect, however, has a notable uncertainty. Particles can be either directly emitted to atmosphere or they can form there from precursor vapors. The latter is called new particle formation (NPF). Globally, NPF has been estimated to be responsible for even half of CCN sized tropospheric particles. The understanding of the NPF mechanisms and the spatial and temporal variation of NPF in many scales is necessary to correctly represent aerosols in climate models. In this work, we quantified the importance of biogenic organic vapours and anthropogenic sulfuric emissions in the NPF in northern boreal environment. Aerosol number size distribution data from three measurement sites were used to calculate the average continuous increase in aerosol particle diameter and number concentration when air masses travelled over land. A 14-year-long time series of aerosol and gas measurements were used to determine the effect of reduced Kola Peninsula SO2 emissions on aerosol population at Eastern Finnish Lapland. Secondly, this thesis describes in-situ aerosol measurements conducted with a light aircraft within the lowest 4 km of the troposphere. The data were used to determine the vertical and horizontal extent and variability of the NPF events in the surroundings of the Hyytiälä SMEAR II station. The airborne and ground level measurements were compared to find out the representativeness of the on ground measurements in the lowest parts of the atmosphere, in the planetary boundary layer. The results showed that the Aitken mode particles grew, on average, at the apparent rate of around 1 nm h−1 when they travelled over the northern boreal environment during the growing season. The average calculated growth rates during the NPF events were 3 6 times higher than this apparent average growth rate. The result implied that the condensation has a significant role in the particle growth even when NPF is not explicit. Also, the NPF events inside the planetary boundary layer were found to occur in area over a hundred kilometers. However, within this area, a notable variation in nucleation mode particles was observed.
  • Holding, Ashley John (Helsingin yliopisto, 2016)
    In this thesis, the synthesis and application of tetraalkylphosphonium-based ionic liquids towards the dissolution of cellulose (and lignocellulose) is explored. Ionic liquids were synthesised from trialkylphosphines by quaternisation with alkyl halides or dimethylcarbonate and subsequent anion exchange reactions. The ionic liquids were used to dissolve lignin, and were found only to dissolve cellulose upon addition of a polar aprotic molecular solvent, such as DMSO (dimethylsulfoxide). The cellulose dissolution capabilities of a range of these phosphonium ionic liquids in combination with DMSO was studied. It was found that these organic electrolyte solutions were very effective solvents for cellulose, with a high molar dissolution capacity. At the greatest extent, only one mole of ionic liquid per glucose units in cellulose is needed to dissolve cellulose. The role of the cation and anion in the dissolution process is explored, with the aid of solvent parametisation techniques and NMR studies. Other solvents, including GVL (gamma-valerolactone), were explored as greener replacements for DMSO. For the shorter chain phosphonium ionic liquids with DMSO and GVL, upper critical solution temperature behaviour was observed and explored in more detail. In these solutions, cellulose is only soluble at high temperatures, and reforms at low temperatures to form a gel with a spherical micro-particle morphology. The phase behaviour of hydrophobic phosphonium ionic liquids, DMSO, and water was studied and applied to the recovery of the ionic liquid after cellulose dissolution in the electrolyte solutions. Ternary phase diagrams of three of the hydrophobic ionic liquids in combination with DMSO and water were constructed. Finally, phosphonium ionic liquid and deuterated DMSO electrolytes were studied and successfully used for the NMR analysis of high molecular weight cellulose materials. Future work in this area is expected to focus further on the theoretical understanding of cellulose dissolution in phosphonium ionic liquid-based organic electrolyte solutions - with expanded NMR measurements, and other experimental techniques, in tandem with molecular dynamics modelling. Additionally, it is expected that techniques for the solution-state NMR of cellulose will be applied at extended range of analytes, including but not limited to, whole biomass, modified and unmodified nano-celluloses, and high molecular weight cellulose derivatives. The thermo-responsive behaviour (UCST-type) phase-separation of cellulose will continue to be explored especially in its application to new materials, included fibres and shaped spherical particles.
  • Seitola, Teija (Helsingin yliopisto, 2016)
    The ability of climate models to simulate the climate variability is of great importance when considering the reliability of, for instance, multi-annual or longer-term predictions. The aim of this thesis is to study the 20th century low-frequency variability patterns in the Earth system and how these patterns are represented by the current modelling systems. Another, equally important objective is to enable efficient spatio-temporal analysis of high-dimensional climate data sets. Decadal scale variability and predictability, from the point of view of the Nordic region, is also summarised in this study. The work is based on the near-surface temperature of two 20th century reanalyses, obtained from the NOAA/OAR/ESRL and ECMWF, and historical climate model simulations from the coupled model intercomparison project5 (CMIP5) data archive. In addition, a millennial Earth system model simulation is analysed. The analysis relies on a powerful dimensionality reduction method, called random projection (RP), which is introduced as a preprocessing for high-dimensional climate data sets to enhance or enable the analysis. The spectral decomposition of the data sets is based on randomised multi-channel singular spectrum analysis (RMSSA), which is one of the main achievements of this thesis. It is shown that dimensionality reduction obtained by RP preserves the main spatial and temporal patterns with high accuracy. In addition, RMSSA is shown to provide an efficient tool for identifying different variability modes in high-dimensional climate data sets. This study shows that the 20th century variability patterns in the two reanalysis data sets are very similar. It is also shown that none of the studied climate models can closely reproduce all the variability modes identified in the reanalyses, although many aspects are simulated well. Taking into account the rapidly accumulating amount of data and increasing dimensionality of data sets, RP is a promising method for dimensionality reduction. The results of the model evaluation can be useful in model development due better understanding of the deficiencies in representing the low-frequency modes. In addition to near-surface temperature, it would be a natural extension to include more variables in the analysis, especially because RP allows efficient data compression.
  • Tenkanen, Tommi (Helsingin yliopisto, 2016)
    Cosmic inflation, an era of rapid expansion in the early universe, and dark matter, an unknown non-baryonic matter component exceeding the amount of the usual baryonic matter by a factor of five, are known to play an important role in describing the physics of the early universe and in explaining the contents of the universe we observe today. Yet the reason for the occurrence of inflation and for the production of dark matter, or their properties, are not known. In this thesis we study the observational consequences of a class of particle physics models related to inflation and dark matter which are challenging to test by direct experiments, such as particle colliders, but which can be tested by cosmological and astrophysical observations. In particular, we concentrate on observational properties of self-interacting Higgs portal dark matter. Whenever a model contains scalar fields which are light and energetically subdominant during cosmic inflation, so-called spectator fields , they acquire large fluctuations which may leave observable imprints on the Cosmic Microwave Background radiation. Carefully investigating the spectator field dynamics during cosmic inflation, we solve for typical initial conditions for post-inflationary dynamics and calculate the dark matter yield originating from non-thermal decay of spectator condensates. As a result, we find a novel connection between the energy scale of inflation and the dark matter abundance. We also study alternative thermal histories of hidden sector dark matter and demonstrate how the usual dark matter production mechanisms may not be sufficient to correctly describe the evolution of dark matter relic density from its generation to the present day. We show that even if the coupling between the hidden and visible sectors is almost negligible, the scenario has observable consequences. Especially a positive observation of primordial tensor perturbations would immensely affect not only models of inflation but also very weakly coupled dark matter models, ruling out large portions of the otherwise viable parameter space. The derived bounds are generic to most weakly coupled portal models with light scalar fields, and qualitatively similar results are also expected to arise in other portal type extensions of the Standard Model of particle physics.