Soil uses in the sugarcane fallow period to improve chemical and physical properties of two latosols (oxisols)

Sugarcane production should be integrated with crop diversification with a view to competitive and sustainable results in economic, social and environmental aspects. The purpose of this study was to assess the influence of different soil uses during the sugarcane fallow period on the chemical and physical properties of eutroferric Red Latosol - LVef (Oxisol) and Acric Latosol - LVw (Acric Oxisol), in Jaboticabal, São Paulo State, Brazil (21º14'05'' S, 48º17'09'' W, 600 m asl). A randomized block design was used with five replications and four treatments, consisting of different soil uses (crops) in the sugarcane fallow period: soybean only, soybean/fallow/soybean, soybean/millet/soybean, and soybean/sunn hemp/soybean. After two soybean crops, the LVef chemical properties remained at intermediate to high levels; while those of the LVw, classified as intermediate to high in the beginning, increased to high levels. Thus, the different soil uses during the sugarcane fallow period allowed the maintenance of LVef fertility levels and the improvement of those of the LVw. Two soybean crops increased macroporosity in the 0.0-0.1 m layer of the LVef; reduced soil aggregates in the 0.0-0.1 and 0.1-0.2 m layers of both soils, and reduced aggregate stability in these two layers of the LVw. Planting pearl millet or sunn hemp between the two soybean growing seasons promoted the formation of larger soil aggregates in the surface layer (0.0-0.1 m) of the LVw.

Automatic Mapping and Classification of Spatial Environmental Data

The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

Origin-related, environmental, sex, and age determinants of immunocompetence, susceptibility to ectoparasites, and disease symptoms in the barn owl

Knowledge of the role of origin-related, environmental, sex, and age factors on host defence mechanisms is important to understand variation in parasite intensity. Because alternative components of parasite defence may be differently sensitive to various factors, they may not necessarily covary. Many components should therefore be considered to tackle the evolution of host-parasite interactions. In a population of barn owls (Tyto alba), we investigated the role of origin-related, environmental (i.e. year, season, nest of rearing, and body condition), sex, and age factors on 12 traits linked to immune responses [humoral immune responses towards sheep red blood cells (SRBC), human serum albumin (HSA) and toxoid toxin TT, T-cell mediated immune response towards the mitogen phytohemagglutinin (PHA)], susceptibility to ectoparasites (number and fecundity of Carnus haemapterus, number of Ixodes ricinus), and disease symptoms (size of the bursa of Fabricius and spleen, proportion of proteins that are immunoglobulins, haematocrit and blood concentration in leucocytes). Cross-fostering experiments allowed us to detect a heritable component of variation in only four out of nine immune and parasitic parameters (i.e. SRBC- and HSA-responses, haematocrit, and number of C. haemapterus). However, because nestlings were not always cross-fostered just after hatching, the finding that 44% of the immune and parasitic parameters were heritable is probably an overestimation. These experiments also showed that five out of these nine parameters were sensitive to the nest environment (i.e. SRBC- and PHA-responses, number of C. haemapterus, haematocrit and blood concentration in leucocytes). Female nestlings were more infested by the blood-sucking fly C. haemapterus than their male nestmates, and their blood was less concentrated in leucocytes. The effect of year, season, age (i.e. reflecting the degree of maturation of the immune system), brood size, position in the within-brood age hierarchy, and body mass strongly differed between the 12 parameters. Different components of host defence mechanisms are therefore not equally heritable and sensitive to environmental, sex, and age factors, potentially explaining why most of these components did not covary.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Using toxicokinetic modeling approach to determine biological reference values (BRVs) and to assess human exposure to pesticides

Exposure to various pesticides has been characterized in workers and the general population, but interpretation and assessment of biomonitoring data from a health risk perspective remains an issue. For workers, a Biological Exposure Index (BEI®) has been proposed for some substances, but most BEIs are based on urinary biomarker concentrations at Threshold Limit Value - Time Weighted Average (TLV-TWA) airborne exposure while occupational exposure can potentially occurs through multiple routes, particularly by skin contact (i.e.captan, chlorpyrifos, malathion). Similarly, several biomonitoring studies have been conducted to assess environmental exposure to pesticides in different populations, but dose estimates or health risks related to these environmental exposures (mainly through the diet), were rarely characterized. Recently, biological reference values (BRVs) in the form of urinary pesticide metabolites have been proposed for both occupationally exposed workers and children. These BRVs were established using toxicokinetic models developed for each substance, and correspond to safe levels of absorption in humans, regardless of the exposure scenario. The purpose of this chapter is to present a review of a toxicokinetic modeling approach used to determine biological reference values. These are then used to facilitate health risk assessments and decision-making on occupational and environmental pesticide exposures. Such models have the ability to link absorbed dose of the parent compound to exposure biomarkers and critical biological effects. To obtain the safest BRVs for the studied population, simulations of exposure scenarios were performed using a conservative reference dose such as a no-observed-effect level (NOEL). The various examples discussed in this chapter show the importance of knowledge on urine collections (i.e. spot samples and complete 8-h, 12-h or 24-h collections), sampling strategies, metabolism, relative proportions of the different metabolites in urine, absorption fraction, route of exposure and background contribution of prior exposures. They also show that relying on urinary measurements of specific metabolites appears more accurate when applying this approach to the case of occupational exposures. Conversely, relying on semi-specific metabolites (metabolites common to a category of pesticides) appears more accurate for the health risk assessment of environmental exposures given that the precise pesticides to which subjects are exposed are often unknown. In conclusion, the modeling approach to define BRVs for the relevant pesticides may be useful for public health authorities for managing issues related to health risks resulting from environmental and occupational exposures to pesticides.

Biological monitoring of chemical exposure : toxicokinetic differences due to age and sex

Human biomonitoring is a widely used method in the assessment of occupational exposure to chemical substances and recommended biological limits are published periodically for interpretation and decision-making. However, it is increasingly recognized that a large variability is associated with biological monitoring, making interpretation less efficient than assumed. In order to improve the applicability of biological monitoring, specific factors responsible for this variability should be identified and their contribution quantified. Among these factors, age and sex are easily identifiable, and present knowledge about pharmaceutical chemicals suggests that they play an important role on the toxicokinetics of occupational chemical agents, and therefore on the biological monitoring results.The aim of the present research project was to assess the influence of age and sex on biological indicators corresponding to organic solvents. This has been done experimentally and by toxicokinetic computer simulation. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile.Age differences were identified by numerical simulations using a general toxicokinetic model from a previous study which was applied to 14 chemicals, representing 21 specific biological entities, with, among others, toluene, phenol, lead and mercury. These models were runn with the modified parameters, indicating in some cases important differences due to age. The expected changes are mostly of the order of 10-20 %, but differences up to 50 % were observed in some cases. These differences appear to depend on the chemical and on the biological entity considered.Sex differences were quantified by controlled human exposures, which were carried out in a 12 m3 exposure chamber for three organic solvents separately: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. The human volunteer groups were composed 12 of ten young men and fifteen young women, the latter subdivided into those with and without hormonal contraceptive. They were exposed during six hours at rest and at half of the threshold limit value. The kinetics of the parent compounds (organic volatiles) and their metabolite(s) were followed in blood, urine and expired air over time. Analyses of the solvent and their metabolites were performed by using headspace gas chromatography, CYP2E1 genotypes by using PCR-based RFLP methods. Experimental data were used to calibrate the toxicokinetic models developed for the three solvents. The results obtained for the different biomarkers of exposure mainly showed an effect on the urinary levels of several biomarkers among women due to the use of hormonal contraceptive, with an increase of about 50 % in the metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Simulations showed that it is possible to use simple toxicokinetic tools in order to predict internal exposure when exposed to organic solvents. Our study suggests that not only physiological differences but also exogenous sex hormones could influence CYP2E1 enzyme activity. The variability among the urinary biological indicators levels gives evidence of an interindividual susceptibility, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Integrating life cycle costs and environmental impacts of composite rail car-bodies for a Korean train

Background, aim, and scope A coupled Life Cycle Costing and life cycle assessment has been performed for car-bodies of the Korean Tilting Train eXpress (TTX) project using European and Korean databases, with the objective of assessing environmental and cost performance to aid materials and process selection. More specifically, the potential of polymer composite car-body structures for the Korean Tilting Train eXpress (TTX) has been investigated. Materials and methods This assessment includes the cost of both carriage manufacturing and use phases, coupled with the life cycle environmental impacts of all stages from raw material production, through carriage manufacture and use, to end-of-life scenarios. Metallic carriages were compared with two composite options: hybrid steel-composite and full-composite carriages. The total planned production for this regional Korean train was 440 cars, with an annual production volume of 80 cars. Results and discussion The coupled analyses were used to generate plots of cost versus energy consumption and environmental impacts. The results show that the raw material and manufacturing phase costs are approximately half of the total life cycle costs, whilst their environmental impact is relatively insignificant (3-8%). The use phase of the car-body has the largest environmental impact for all scenarios, with near negligible contributions from the other phases. Since steel rail carriages weigh more (27-51%), the use phase cost is correspondingly higher, resulting in both the greatest environmental impact and the highest life cycle cost. Compared to the steel scenario, the hybrid composite variant has a lower life cycle cost (16%) and a lower environmental impact (26%). Though the full composite rail carriage may have the highest manufacturing cost, it results in the lowest total life cycle costs and lowest environmental impacts. Conclusions and recommendations This coupled cost and life cycle assessment showed that the full composite variant was the optimum solution. This case study showed that coupling of technical cost models with life cycle assessment offers an efficient route to accurately evaluate economic and environmental performance in a consistent way.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Coliform density in oyster culture waters and its relationship with environmental factors

The objective of this work was to evaluate the total and thermotolerant coliform densities in the oyster culture water of Cananeia, SP, Brazil, correlating these densities with environmental variables and tidal variations. Superficial water samples were collected in two tide conditions (spring and neap) from three areas of Cananéia municipality (Mandira, Itapitangui and Cooperostra). The three studied areas showed good conditions for the culture regarding coliform densities. The two tidal conditions differed significantly as to total coliform concentration; however, the same procedure was not performed for thermotolerant coliforms. No correlation was observed between water temperature, pH, and concentrations of total and thermotolerant coliforms. Coliform density was positively correlated with rainfall and negatively correlated with salinity. Spring and neap tides differed significantly as to coliform number. Simple diagnosis of environmental conditions of the crop fields is insufficient to assess water quality of shellfish cultivation. A continuous monitoring program of planted areas is necessary both for the assessment of water quality potential for marine culture and for ensuring safe consumption of seafood, besides constituting an important tool to understand the relationships between contamination and the involved environmental variables.

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.

R&D Performance Analysis: Case Studies on the Challenges and Promotion of the Evaluation and Measurement of R&D

Due to the intense international competition, demanding, and sophisticated customers, and diverse transforming technological change, organizations need to renew their products and services by allocating resources on research and development (R&D). Managing R&D is complex, but vital for many organizations to survive in the dynamic, turbulent environment. Thus, the increased interest among decision-makers towards finding the right performance measures for R&D is understandable. The measures or evaluation methods of R&D performance can be utilized for multiple purposes; for strategic control, for justifying the existence of R&D, for providing information and improving activities, as well as for the purposes of motivating and benchmarking. The earlier research in the field of R&D performance analysis has generally focused on either the activities and considerable factors and dimensions - e.g. strategic perspectives, purposes of measurement, levels of analysis, types of R&D or phases of R&D process - prior to the selection of R&Dperformance measures, or on proposed principles or actual implementation of theselection or design processes of R&D performance measures or measurement systems. This study aims at integrating the consideration of essential factors anddimensions of R&D performance analysis to developed selection processes of R&D measures, which have been applied in real-world organizations. The earlier models for corporate performance measurement that can be found in the literature, are to some extent adaptable also to the development of measurement systemsand selecting the measures in R&D activities. However, it is necessary to emphasize the special aspects related to the measurement of R&D performance in a way that make the development of new approaches for especially R&D performance measure selection necessary: First, the special characteristics of R&D - such as the long time lag between the inputs and outcomes, as well as the overall complexity and difficult coordination of activities - influence the R&D performance analysis problems, such as the need for more systematic, objective, balanced and multi-dimensional approaches for R&D measure selection, as well as the incompatibility of R&D measurement systems to other corporate measurement systems and vice versa. Secondly, the above-mentioned characteristics and challenges bring forth the significance of the influencing factors and dimensions that need to be recognized in order to derive the selection criteria for measures and choose the right R&D metrics, which is the most crucial step in the measurement system development process. The main purpose of this study is to support the management and control of the research and development activities of organizations by increasing the understanding of R&D performance analysis, clarifying the main factors related to the selection of R&D measures and by providing novel types of approaches and methods for systematizing the whole strategy- and business-based selection and development process of R&D indicators.The final aim of the research is to support the management in their decision making of R&D with suitable, systematically chosen measures or evaluation methods of R&D performance. Thus, the emphasis in most sub-areas of the present research has been on the promotion of the selection and development process of R&D indicators with the help of the different tools and decision support systems, i.e. the research has normative features through providing guidelines by novel types of approaches. The gathering of data and conducting case studies in metal and electronic industry companies, in the information and communications technology (ICT) sector, and in non-profit organizations helped us to formulate a comprehensive picture of the main challenges of R&D performance analysis in different organizations, which is essential, as recognition of the most importantproblem areas is a very crucial element in the constructive research approach utilized in this study. Multiple practical benefits regarding the defined problemareas could be found in the various constructed approaches presented in this dissertation: 1) the selection of R&D measures became more systematic when compared to the empirical analysis, as it was common that there were no systematic approaches utilized in the studied organizations earlier; 2) the evaluation methods or measures of R&D chosen with the help of the developed approaches can be more directly utilized in the decision-making, because of the thorough consideration of the purpose of measurement, as well as other dimensions of measurement; 3) more balance to the set of R&D measures was desired and gained throughthe holistic approaches to the selection processes; and 4) more objectivity wasgained through organizing the selection processes, as the earlier systems were considered subjective in many organizations. Scientifically, this dissertation aims to make a contribution to the present body of knowledge of R&D performance analysis by facilitating dealing with the versatility and challenges of R&D performance analysis, as well as the factors and dimensions influencing the selection of R&D performance measures, and by integrating these aspects to the developed novel types of approaches, methods and tools in the selection processes of R&D measures, applied in real-world organizations. In the whole research, facilitation of dealing with the versatility and challenges in R&D performance analysis, as well as the factors and dimensions influencing the R&D performance measure selection are strongly integrated with the constructed approaches. Thus, the research meets the above-mentioned purposes and objectives of the dissertation from the scientific as well as from the practical point of view.

Project Success through Effective Decisions: Case Studies on Project Goal Setting, Success Evaluation and Managerial Decision Making

The objective of the thesis is to structure and model the factors that contribute to and can be used in evaluating project success. The purpose of this thesis is to enhance the understanding of three research topics. The goal setting process, success evaluation and decision-making process are studied in the context of a project, business unitand its business environment. To achieve the objective three research questionsare posed. These are 1) how to set measurable project goals, 2) how to evaluateproject success and 3) how to affect project success with managerial decisions.The main theoretical contribution comes from deriving a synthesis of these research topics which have mostly been discussed apart from each other in prior research. The research strategy of the study has features from at least the constructive, nomothetical, and decision-oriented research approaches. This strategy guides the theoretical and empirical part of the study. Relevant concepts and a framework are composed on the basis of the prior research contributions within the problem area. A literature review is used to derive constructs of factors withinthe framework. They are related to project goal setting, success evaluation, and decision making. On the basis of this, the case study method is applied to complement the framework. The empirical data includes one product development program, three construction projects, as well as one organization development, hardware/software, and marketing project in their contexts. In two of the case studiesthe analytic hierarchy process is used to formulate a hierarchical model that returns a numerical evaluation of the degree of project success. It has its origin in the solution idea which in turn has its foundation in the notion of projectsuccess. The achieved results are condensed in the form of a process model thatintegrates project goal setting, success evaluation and decision making. The process of project goal setting is analysed as a part of an open system that includes a project, the business unit and its competitive environment. Four main constructs of factors are suggested. First, the project characteristics and requirements are clarified. The second and the third construct comprise the components of client/market segment attractiveness and sources of competitive advantage. Together they determine the competitive position of a business unit. Fourth, the relevant goals and the situation of a business unit are clarified to stress their contribution to the project goals. Empirical evidence is gained on the exploitation of increased knowledge and on the reaction to changes in the business environment during a project to ensure project success. The relevance of a successful project to a company or a business unit tends to increase the higher the reference level of project goals is set. However, normal performance or sometimes performance below this normal level is intentionally accepted. Success measures make project success quantifiable. There are result-oriented, process-oriented and resource-oriented success measures. The study also links result measurements to enablers that portray the key processes. The success measures can be classified into success domains determining the areas on which success is assessed. Empiricalevidence is gained on six success domains: strategy, project implementation, product, stakeholder relationships, learning situation and company functions. However, some project goals, like safety, can be assessed using success measures that belong to two success domains. For example a safety index is used for assessing occupational safety during a project, which is related to project implementation. Product safety requirements, in turn, are connected to the product characteristics and thus to the product-related success domain. Strategic success measures can be used to weave the project phases together. Empirical evidence on their static nature is gained. In order-oriented projects the project phases are oftencontractually divided into different suppliers or contractors. A project from the supplier's perspective can represent only a part of the ¿whole project¿ viewed from the client's perspective. Therefore static success measures are mostly used within the contractually agreed project scope and duration. Proof is also acquired on the dynamic use of operational success measures. They help to focus on the key issues during each project phase. Furthermore, it is shown that the original success domains and success measures, their weights and target values can change dynamically. New success measures can replace the old ones to correspond better with the emphasis of the particular project phase. This adjustment concentrates on the key decision milestones. As a conclusion, the study suggests a combination of static and dynamic success measures. Their linkage to an incentive system can make the project management proactive, enable fast feedback and enhancethe motivation of the personnel. It is argued that the sequence of effective decisions is closely linked to the dynamic control of project success. According to the used definition, effective decisions aim at adequate decision quality and decision implementation. The findings support that project managers construct and use a chain of key decision milestones to evaluate and affect success during aproject. These milestones can be seen as a part of the business processes. Different managers prioritise the key decision milestones to a varying degree. Divergent managerial perspectives, power, responsibilities and involvement during a project offer some explanation for this. Finally, the study introduces the use ofHard Gate and Soft Gate decision milestones. The managers may use the former milestones to provide decision support on result measurements and ad hoc critical conditions. In the latter milestones they may make intermediate success evaluation also on the basis of other types of success measures, like process and resource measures.

Kestävän kehityksen näkökulmien huomioiminen kunnan energiaratkaisussa

Diplomityön tavoitteena on tuottaa informaatiota kunnalliseen päätöksentekoon, jonka avulla kestävän kehityksen näkökulmia voidaan huomioida kunnan energiaratkaisusta päätettäessä. Yhtenä työn lähtökohtana on ollut myös uusi EU-direktiivi, jonka mukaan ympäristönäkökohtia voidaan huomioida julkisten hankintojen tarjouspyyntömenettelyssä valintaperusteena. Tarkastelun kohteena oli kokoluokaltaan 0,5–3 MW:n aluelämpölaitokset sekä polttoaineiden tuotantoketjut. Työssä vertailtavat polttoaineet olivat metsähake, raskas polttoöljy, kevyt polttoöljy ja turve. Diplomityössä on perehdytty kestävän kehityksen käsitteeseen ja muodostettu sen mukaan ekologiselle, sosiaaliselle ja taloudelliselle näkökulmalle kunnallisen energiaratkaisun indikaattoreita. Empiirisessä osassa käsitellään kestävän kehityksen näkökulmien muodostumista Enon energiaosuuskunnan toimintaan perustuen. Käytettävät kestävän kehityksen näkökulmien mukaiset indikaattorit ovat polttoaineen tuotannosta ja käytöstä aiheutuvat kasvihuonekaasupäästöt, polttoaineen tuotannon työllisyysvaikutukset sekä energian hinnan muodostuminen osuuskunnan asiakkaille. Tässä diplomityössä tarkastelluilla kestävän kehityksen indikaattoreilla mitattuna, metsähakkeen käytöllä energiantuotannossa on positiivinen vaikutus niin kunnan kasvihuonekaasutaseessa, työllisyystilanteessa sekä myös enemmän kuluttajaystävällinen asema, lämmön hinnan vakauden ansiosta, kuin muilla työssä käsiteltävillä polttoaineilla. Polttoaineen tuotantoketjun osalta metsähakkeelle saatiin tuotannon ja käytön aiheuttamaksi kasvihuonekaasupäästöksi 2,9–4,2 g CO2-ekv/MJ. Tulos perustuu Enon energiaosuuskunnan polttoaineen hankinnassa käytössä oleviin keskimääräisiin etäisyyksiin metsäkuljetuksessa (250 m) ja kaukokuljetuksessa (15 km). Tuotannon ja käytön aiheuttamat kasvihuonekaasupäästöt olivat raskaalla polttoöljyllä 88,2 g CO2-ekv/MJ, kevyellä polttoöljyllä 85,0 g CO2-ekv/MJ ja turpeella 104,0–108,1 g CO2-ekv/MJ. Metsähakkeen osalta polttoaineen tuotannon osuus koko tarkastellun energiaketjun kasvihuonekaasupäästöistä oli noin 43–57 %. Enon energiaosuuskunnan tapauksessa vuoden 2005 odotetulla toiminta-asteella metsähakkeella tuotetun lämmön tuotantoketjun kasvihuonekaasupäästöt ovat noin 160 t CO2-ekv. Kevyellä polttoöljyllä tuotetun lämmön tuotantoketjun kasvihuonekaasupäästöt olisivat noin 3700 t CO2-ekv sekä turpeen (50 %) ja metsähakkeen (50 %) seoskäyttöön perustuvalla ketjulla noin 2300–2400 t CO2-ekv. Samaisella toiminta-asteella työllisyysvaikutukset ovat käytettäessä metsähaketta 2,2–8,6 htv, raakaöljyä 0,12 htv ja turvetta 1,4–1,6 htv. Metsähakkeen käyttö aluelämpölaitosten pääpolttoaineena takaa myös vakaan hintakehityksen osuuskunnan asiakkaille.

An Evaluation of the Paper Profile - a comparative assessment of the applicability of an emerging environmental communication tool in pulp and paper industry

Diplomityön tavoitteena oli arvioida uutta sellu-, paperi- ja kartonkiteollisuuden Paper Profile -ympäristötuoteselostetta. Paper Profilen tarkoituksena on tarjota paperiteollisuuden asiakkaille ja muille kiinnostuneilla sidosryhmille yhtenäistä ympäristöinformaatiota koskien paperituotteiden koostumusta ja tuotteiden tärkeimpiä ympäristöparametrejä. Työn tärkein tavoite oli arvioida kriittisesti Paper Profilea ja verrata konseptia ISO:n, Kansainvälisen stardardisoimisliiton tuoteselosteeseen sekä löytää konseptien yhtäläisyydet ja erot. Tärkein tehtävä oli tunnistaa ne avaintekijät, joiden avulla Paper Profile -tuoteselostetta voitaisiin pitää yhtenevänä ISO/TR 14025 teknisen raportin kanssa. Lisäksi Paper Profile -tuoteselosteen mahdolliset kehittämistarpeet arvioitiin ISO-tuoteselosteen näkökulmasta. Työn toinen tavoite oli kerätä ja analysoida uuteen tuoteselosteeseen liittyvä asiakaspalaute ja verrata sitä Stora Enson tehtaiden ympäristöpäälliköiden antamiin Paper Profilea koskeviin kommentteihin. Työn tuloksena huomattiin, että Paper Profile -konsepti sellaisenaan ei ole kovin informatiivinen vaan tuoteseloste jättää monia ympäristökysymyksiä avoimeksi. Siitä huolimatta Paper Profile tarjoaa riittävän taustan eri paperituotteiden ympäristökuormitusten keskinäiselle vertailuille. Konseptin viestinnällinen näkökulma paranisi huomattavasti, jos tuoteselosteeseen lisättäisiin kolmannen osapuolen verifiointi. Lisäksi referenssiarvot kertoisivat asiakkaille paremmin esitettyjen parametrien taustoista. Stora Enson tehtaiden ympäristöpäälliköiden, samoin kuin asiakkaidenkin mielestä Paper Profile on yleisesti ottaen potentiaalinen ympäristöviestinnän työkalu, mutta silti konseptiin ehdotettiin joitakin pieniä muutoksia. Avoinna olevat metsäsertifiointikysymykset ja niiden puutteellinen tiedottaminen tuoteselosteessa puhututtivat sekä tehtaiden henkilöstöä että yritysasiakkaita.