Golfkentän viheriöleikkureiden käytöstä aiheutuvat ympäristövaikutukset

Golfin suosion kasvaessa ja golfkenttien määrän lisääntyessä kenttien ympäristövaikutuksiin on alettu kiinnittää entistä enemmän huomiota. Golfkenttien viheriöiden, esiviheriöiden ja tii-paikkojen ruohon leikkaus on yksi ympäristöön vaikuttava toimenpide kentän hoidossa, koska leikkaus suoritetaan polttomoottorikäyttöisillä viheriöleikkureilla. Tämän diplomityön tilaajana toiminut Actioneco Oy halusi selvittää kehittämänsä uudentyyppisen, akkukäyttöisen viheriöleikkurin käytöstä aiheutuvat ympäristövaikutukset polttomoottorikäyttöiseen leikkuriin verrattuna. Työn tavoitteena oli tuottaa tietoa viheriöleikkureiden ympäristövaikutuksista leikkurivalmistajille ja golfkentille sekä luoda malli, jonka avulla käytöstä syntyviä ympäristövaikutuksia voidaan tarkastella erilaisilla kentillä leikkurityypistä riippuen. Työn tarkoituksena oli myös tuoda esiin hyödyt, joita ympäristöystävällisen leikkurityypin käyttöön liittyy. Viheriöleikkureiden käytön ympäristövaikutukset selvitettiin elinkaariarvioinnin avulla. Merkittävämmäksi ympäristövaikutukseksi osoittautui ilmaston lämpeneminen, joka aiheutui pääasiassa hiilidioksidista. Syntyvien päästöjen määrissä oli kuitenkin huomattava ero tutkittavien leikkurityyppien välillä. Koska akkukäyttöisten leikkureiden käytöstä aiheutuu vähemmän ympäristöön vaikuttavia päästöjä, on niiden käyttö suositeltavampaa polttomoottorikäyttöisten leikkureiden käyttöön verrattuna. Ympäristöystävällisempien leikkureiden käytöllä on mahdollista saavuttaa myösgolfkenttäyhtiön toimintaan positiivisesti vaikuttavia hyötyjä.

Element speciation and behaviour in metal-rich Boreal river and estuarine systems using ultrafiltration and chemical modelling

The bioavailability of metals and their potential for environmental pollution depends not simply on total concentrations, but is to a great extent determined by their chemical form. Consequently, knowledge of aqueous metal species is essential in investigating potential metal toxicity and mobility. The overall aim of this thesis is, thus, to determine the species of major and trace elements and the size distribution among the different forms (e.g. ions, molecules and mineral particles) in selected metal-enriched Boreal river and estuarine systems by utilising filtration techniques and geochemical modelling. On the basis of the spatial physicochemical patterns found, the fractionation and complexation processes of elements (mainly related to input of humic matter and pH-change) were examined. Dissolved (<1 kDa), colloidal (1 kDa-0.45 μm) and particulate (>0.45 μm) size fractions of sulfate, organic carbon (OC) and 44 metals/metalloids were investigated in the extremely acidic Vörå River system and its estuary in W Finland, and in four river systems in SW Finland (Sirppujoki, Laajoki, Mynäjoki and Paimionjoki), largely affected by soil erosion and acid sulfate (AS) soils. In addition, geochemical modelling was used to predict the formation of free ions and complexes in these investigated waters. One of the most important findings of this study is that the very large amounts of metals known to be released from AS soils (including Al, Ca, Cd, Co, Cu, Mg, Mn, Na, Ni, Si, U and the lanthanoids) occur and can prevail mainly in toxic forms throughout acidic river systems; as free ions and/or sulfate-complexes. This has serious effects on the biota and especially dissolved Al is expected to have acute effects on fish and other organisms, but also other potentially toxic dissolved elements (e.g. Cd, Cu, Mn and Ni) can have fatal effects on the biota in these environments. In upstream areas that are generally relatively forested (higher pH and contents of OC) fewer bioavailable elements (including Al, Cu, Ni and U) may be found due to complexation with the more abundantly occurring colloidal OC. In the rivers in SW Finland total metal concentrations were relatively high, but most of the elements occurred largely in a colloidal or particulate form and even elements expected to be very soluble (Ca, K, Mg, Na and Sr) occurred to a large extent in colloidal form. According to geochemical modelling, these patterns may only to a limited extent be explained by in-stream metal complexation/adsorption. Instead there were strong indications that the high metal concentrations and dominant solid fractions were largely caused by erosion of metal bearing phyllosilicates. A strong influence of AS soils, known to exist in the catchment, could be clearly distinguished in the Sirppujoki River as it had very high concentrations of a metal sequence typical of AS soils in a dissolved form (Ba, Br, Ca, Cd, Co, K, Mg, Mn, Na, Ni, Rb and Sr). In the Paimionjoki River, metal concentrations (including Ba, Cs, Fe, Hf, Pb, Rb, Si, Th, Ti, Tl and V; not typical of AS soils in the area) were high, but it was found that the main cause of this was erosion of metal bearing phyllosilicates and thus these metals occurred dominantly in less toxic colloidal and particulate fractions. In the two nearby rivers (Laajoki and Mynäjoki) there was influence of AS soils, but it was largely masked by eroded phyllosilicates. Consequently, rivers draining clay plains sensitive to erosion, like those in SW Finland, have generally high background metal concentrations due to erosion. Thus, relying on only semi-dissolved (<0.45 μm) concentrations obtained in routine monitoring, or geochemical modelling based on such data, can lead to a great overestimation of the water toxicity in this environment. The potentially toxic elements that are of concern in AS soil areas will ultimately be precipitated in the recipient estuary or sea, where the acidic metalrich river water will gradually be diluted/neutralised with brackish seawater. Along such a rising pH gradient Al, Cu and U will precipitate first together with organic matter closest to the river mouth. Manganese is relatively persistent in solution and, thus, precipitates further down the estuary as Mn oxides together with elements such as Ba, Cd, Co, Cu and Ni. Iron oxides, on the contrary, are not important scavengers of metals in the estuary, they are predicted to be associated only with As and PO4.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.