Exhaled nitric oxide : Variability and association with bronchial hyperresponsiveness and atopy

Airway inflammation is a key feature of bronchial asthma. In asthma management, according to international guidelines, the gold standard is anti-inflammatory treatment. Currently, only conventional procedures (i.e., symptoms, use of rescue medication, PEF-variability, and lung function tests) were used to both diagnose and evaluate the results of treatment with anti-inflammatory drugs. New methods for evaluation of degree of airway inflammation are required. Nitric oxide (NO) is a gas which is produced in the airways of healthy subjects and especially produced in asthmatic airways. Measurement of NO from the airways is possible, and NO can be measured from exhaled air. Fractional exhaled NO (FENO) is increased in asthma, and the highest concentrations are measured in asthmatic patients not treated with inhaled corticosteroids (ICS). Steroid-treated patients with asthma had levels of FENO similar to those of healthy controls. Atopic asthmatics had higher levels of FENO than did nonatopic asthmatics, indicating that level of atopy affected FENO level. Associations between FENO and bronchial hyperresponsiveness (BHR) occur in asthma. The present study demonstrated that measurement of FENO had good reproducibility, and the FENO variability was reasonable both short- and long-term in both healthy subjects and patients with respiratory symptoms or asthma. We demonstrated the upper normal limit for healthy subjects, which was 12 ppb calculated from two different healthy study populations. We showed that patients with respiratory symptoms who did not fulfil the diagnostic criteria of asthma had FENO values significantly higher than in healthy subjects, but significantly lower than in asthma patients. These findings suggest that BHR to histamine is a sensitive indicator of the effect of ICS and a valuable tool for adjustment of corticosteroid treatment in mild asthma. The findings further suggest that intermittent treatment periods of a few weeks’ duration are insufficient to provide long-term control of BHR in patients with mild persistent asthma. Moreover, during the treatment with ICS changes in BHR and changes in FENO were associated. FENO level was associated with BHR measured by a direct (histamine challenge) or indirect method (exercise challenge) in steroid-naïve symptomatic, non-smoking asthmatics. Although these associations could be found only in atopics, FENO level in nonatopic asthma was also increased. It can thus be concluded that assessment of airway inflammation by measuring FENO can be useful for clinical purposes. The methodology of FENO measurements is now validated. Especially in those patients with respiratory symptoms who did not fulfil the diagnostic criteria of asthma, FENO measurement can aid in treatment decisions. Serial measurement of FENO during treatment with ICS can be a complementary or an alternative method for evaluation in patients with asthma.

Evaluation and modelling of the spatial and temporal variability of particulate matter in urban areas

This thesis contains three subject areas concerning particulate matter in urban area air quality: 1) Analysis of the measured concentrations of particulate matter mass concentrations in the Helsinki Metropolitan Area (HMA) in different locations in relation to traffic sources, and at different times of year and day. 2) The evolution of traffic exhaust originated particulate matter number concentrations and sizes in local street scale are studied by a combination of a dispersion model and an aerosol process model. 3) Some situations of high particulate matter concentrations are analysed with regard to their meteorological origins, especially temperature inversion situations, in the HMA and three other European cities. The prediction of the occurrence of meteorological conditions conducive to elevated particulate matter concentrations in the studied cities is examined. The performance of current numerical weather forecasting models in the case of air pollution episode situations is considered. The study of the ambient measurements revealed clear diurnal variation of the PM10 concentrations in the HMA measurement sites, irrespective of the year and the season of the year. The diurnal variation of local vehicular traffic flows seemed to have no substantial correlation with the PM2.5 concentrations, indicating that the PM10 concentrations were originated mainly from local vehicular traffic (direct emissions and suspension), while the PM2.5 concentrations were mostly of regionally and long-range transported origin. The modelling study of traffic exhaust dispersion and transformation showed that the number concentrations of particles originating from street traffic exhaust undergo a substantial change during the first tens of seconds after being emitted from the vehicle tailpipe. The dilution process was shown to dominate total number concentrations. Minimal effect of both condensation and coagulation was seen in the Aitken mode number concentrations. The included air pollution episodes were chosen on the basis of occurrence in either winter or spring, and having at least partly local origin. In the HMA, air pollution episodes were shown to be linked to predominantly stable atmospheric conditions with high atmospheric pressure and low wind speeds in conjunction with relatively low ambient temperatures. For the other European cities studied, the best meteorological predictors for the elevated concentrations of PM10 were shown to be temporal (hourly) evolutions of temperature inversions, stable atmospheric stability and in some cases, wind speed. Concerning the weather prediction during particulate matter related air pollution episodes, the use of the studied models were found to overpredict pollutant dispersion, leading to underprediction of pollutant concentration levels.

Sovelletun rentoutuksen vaikutus psyykkiseen työhyvinvointiin ja sykevaihteluun

Research reveals that more than every fourth Finn experiences work-related exhaustion to some degree. Stress and exhaustion have psychological and physical expressions. The main physical factor in stress is the overloading of the autonomic nervous system, which can be measured for instance by variations of heart rate. Studies show that the work field, management and authority of the work, skill developmental possibilities, and social support inhibit stress overload. The practising of self-relaxation techniques possible inhibits working stress and exhaustion. In this study of preventive rehabilitation, the focus was on the effects of the training of applied relaxation on psychological and physiological variables of stress and empowerment of resources. Participants (n=73) were basically healthy and capable of working, 25-40 of age, workers from the field of mental work. They practised applied relaxation under group conduction for seven weeks. The aim was to learn to relax easily even in everyday occasions. The subjects were tested thirdly. After the first measurement, they were grouped into two groups, of which the first group started the relaxation training. The second group began practising half a year after the second measurement. The third measurement was done one year after the beginning of the study. It was hypothesised that the training of applied relaxation would significantly reduce stress on both psychological and physiological variables and that these variables would correlate positively. Results revealed that the training of applied relaxation reduced psychological stress symptoms rather modestly. The changes were more significant in women, who experienced a slight increase in self-directivity. Physical changes were slight decreases of the sympathetic activation. The correlations of psychological and physiological variables were modest. Some changes were reduced after the active training. There was a positive interrelation between experienced work-related demands of efficiency, insufficient social support and exhaustion. There was a tendency to significance between skill developmental possibilities and psychological stress symptoms. Further implications of the results were discussed.

Routine Measurement of Health-Related Quality of Life in Assessing Cost-Effectiveness in Secondary Health Care

Aims: The aims of this study were 1) to identify and describe health economic studies that have used quality-adjusted life years (QALYs) based on actual measurements of patients' health-related quality of life (HRQoL); 2) to test the feasibility of routine collection of health-related quality of life (HRQoL) data as an indicator of effectiveness of secondary health care; and 3) to establish and compare the cost-utility of three large-volume surgical procedures in a real-world setting in the Helsinki University Central Hospital, a large referral hospital providing secondary and tertiary health-care services for a population of approximately 1.4 million. Patients and methods: So as to identify studies that have used QALYs as an outcome measure, a systematic search of the literature was performed using the Medline, Embase, CINAHL, SCI and Cochrane Library electronic databases. Initial screening of the identified articles involved two reviewers independently reading the abstracts; the full-text articles were also evaluated independently by two reviewers, with a third reviewer used in cases where the two reviewers could not agree a consensus on which articles should be included. The feasibility of routinely evaluating the cost-effectiveness of secondary health care was tested by setting up a system for collecting HRQoL data on approximately 4 900 patients' HRQoL before and after operative treatments performed in the hospital. The HRQoL data used as an indicator of treatment effectiveness was combined with diagnostic and financial indicators routinely collected in the hospital. To compare the cost-effectiveness of three surgical interventions, 712 patients admitted for routine operative treatment completed the 15D HRQoL questionnaire before and also 3-12 months after the operation. QALYs were calculated using the obtained utility data and expected remaining life years of the patients. Direct hospital costs were obtained from the clinical patient administration database of the hospital and a cost-utility analysis was performed from the perspective of the provider of secondary health care services. Main results: The systematic review (Study I) showed that although QALYs gained are considered an important measure of the effectiveness of health care, the number of studies in which QALYs are based on actual measurements of patients' HRQoL is still fairly limited. Of the reviewed full-text articles, only 70 reported QALYs based on actual before after measurements using a valid HRQoL instrument. Collection of simple cost-effectiveness data in secondary health care is feasible and could easily be expanded and performed on a routine basis (Study II). It allows meaningful comparisons between various treatments and provides a means for allocating limited health care resources. The cost per QALY gained was 2 770 for cervical operations and 1 740 for lumbar operations. In cases where surgery was delayed the cost per QALY was doubled (Study III). The cost per QALY ranges between subgroups in cataract surgery (Study IV). The cost per QALY gained was 5 130 for patients having both eyes operated on and 8 210 for patients with only one eye operated on during the 6-month follow-up. In patients whose first eye had been operated on previous to the study period, the mean HRQoL deteriorated after surgery, thus precluding the establishment of the cost per QALY. In arthroplasty patients (Study V) the mean cost per QALY gained in a one-year period was 6 710 for primary hip replacement, 52 270 for revision hip replacement, and 14 000 for primary knee replacement. Conclusions: Although the importance of cost-utility analyses has during recent years been stressed, there are only a limited number of studies in which the evaluation is based on patients own assessment of the treatment effectiveness. Most of the cost-effectiveness and cost-utility analyses are based on modeling that employs expert opinion regarding the outcome of treatment, not on patient-derived assessments. Routine collection of effectiveness information from patients entering treatment in secondary health care turned out to be easy enough and did not, for instance, require additional personnel on the wards in which the study was executed. The mean patient response rate was more than 70 %, suggesting that patients were happy to participate and appreciated the fact that the hospital showed an interest in their well-being even after the actual treatment episode had ended. Spinal surgery leads to a statistically significant and clinically important improvement in HRQoL. The cost per QALY gained was reasonable, at less than half of that observed for instance for hip replacement surgery. However, prolonged waiting for an operation approximately doubled the cost per QALY gained from the surgical intervention. The mean utility gain following routine cataract surgery in a real world setting was relatively small and confined mostly to patients who had had both eyes operated on. The cost of cataract surgery per QALY gained was higher than previously reported and was associated with considerable degree of uncertainty. Hip and knee replacement both improve HRQoL. The cost per QALY gained from knee replacement is two-fold compared to hip replacement. Cost-utility results from the three studied specialties showed that there is great variation in the cost-utility of surgical interventions performed in a real-world setting even when only common, widely accepted interventions are considered. However, the cost per QALY of all the studied interventions, except for revision hip arthroplasty, was well below 50 000, this figure being sometimes cited in the literature as a threshold level for the cost-effectiveness of an intervention. Based on the present study it may be concluded that routine evaluation of the cost-utility of secondary health care is feasible and produces information essential for a rational and balanced allocation of scarce health care resources.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Spatial and temporal variability in midge (Nematocera) assemblages in shallow Finnish lakes (60−70 °N) : community-based modelling of past environmental change

Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.

Do Measurement Errors in GDP Announcements Cause Output Fluctuations?

This thesis studies empirically whether measurement errors in aggregate production statistics affect sentiment and future output. Initial announcements of aggregate production are subject to measurement error, because many of the data required to compile the statistics are produced with a lag. This measurement error can be gauged as the difference between the latest revised statistic and its initial announcement. Assuming aggregate production statistics help forecast future aggregate production, these measurement errors are expected to affect macroeconomic forecasts. Assuming agents’ macroeconomic forecasts affect their production choices, these measurement errors should affect future output through sentiment. This thesis is primarily empirical, so the theoretical basis, strategic complementarity, is discussed quite briefly. However, it is a model in which higher aggregate production increases each agent’s incentive to produce. In this circumstance a statistical announcement which suggests aggregate production is high would increase each agent’s incentive to produce, thus resulting in higher aggregate production. In this way the existence of strategic complementarity provides the theoretical basis for output fluctuations caused by measurement mistakes in aggregate production statistics. Previous empirical studies suggest that measurement errors in gross national product affect future aggregate production in the United States. Additionally it has been demonstrated that measurement errors in the Index of Leading Indicators affect forecasts by professional economists as well as future industrial production in the United States. This thesis aims to verify the applicability of these findings to other countries, as well as study the link between measurement errors in gross domestic product and sentiment. This thesis explores the relationship between measurement errors in gross domestic production and sentiment and future output. Professional forecasts and consumer sentiment in the United States and Finland, as well as producer sentiment in Finland, are used as the measures of sentiment. Using statistical techniques it is found that measurement errors in gross domestic product affect forecasts and producer sentiment. The effect on consumer sentiment is ambiguous. The relationship between measurement errors and future output is explored using data from Finland, United States, United Kingdom, New Zealand and Sweden. It is found that measurement errors have affected aggregate production or investment in Finland, United States, United Kingdom and Sweden. Specifically, it was found that overly optimistic statistics announcements are associated with higher output and vice versa.

Food intake, growth and social interactions of signal crayfish, Pacifastacus leniusculus (Dana)

The knowledge about the optimal rearing conditions, such as water temperature and quality, photoperiod and density, with the understanding of animal nutritional requirements forms the basis of economically stable aquaculture for freshwater crayfish. However, the shift from a natural environment to effective culture conditions induces several changes, not only at the population level, but also at the individual level. The social contacts between conspecifics increase with increasing animal density. The competition for limited resources (e.g. food, shelter, mates) is more severe with the presence of agonistic behaviour and may lead to unequal distribution of these. The objectives of this study were to: 1) study the distribution of a common food resource between communally reared signal crayfish (Pacifastacus leniusculus) and to assign potential feeding hierarchy on the basis of individual food intake measurements, 2) explore the possibilities of size distribution manipulations to affect population dynamics and food intake to improve growth and survival in culture and 3) study the effect of food ration and spatial distribution on food intake and to explore the effect of temperature and food ration on growth and body composition of freshwater crayfish. The feeding ranks between animals were assigned with a new method for individual food intake measurement of communally reared crayfish. This technique has a high feasibility and a great potential to be applied in crayfish aquaculture studies. In this study, signal crayfish showed high size-related variability in food consumption both among individuals within a group (inter-individual) and within individual day-to-day variation (intra-individual). Increased competition for food led to an unequal distribution of this resource and this may be a reason for large growth differences between animals. The consumption was significantly higher when reared individually in comparison with communal housing. These results suggest that communally housed crayfish form a feeding hierarchy and that the animal size is the major factor controlling the position in this hierarchy. The optimisation of the social environment ( social conditions ) was evaluated in this study as a new approach to crayfish aquaculture. The results showed that the absence of conspecifics (individual rearing vs. communal housing) affects growth rate, food intake and the proportion of injured animals, whereas size variation between animals influences the number and duration of agonistic encounters. In addition, animal size had a strong influence on the fighting success of signal crayfish reared in a social milieu with a wide size variation of conspecifics. Larger individuals initiated and won most of the competitions, which suggests size-based social hierarchy of P. leniusculus. This is further supported by the fact that the length and weight gain of smaller animals increased after size grading, maybe because of a better access to the food resource due to diminished social pressure. However, the high dominance index was not based on size under conditions of limited size variation, e.g. those characteristic of restocked natural populations and aquaculture, indicating the important role of behaviour on social hierarchy.

Characterisation and source identification of pollution episodes caused by long-range transported aerosols

Aerosol particles can cause detrimental environmental and health effects. The particles and their precursor gases are emitted from various anthropogenic and natural sources. It is important to know the origin and properties of aerosols to efficiently reduce their harmful effects. The diameter of aerosol particles (Dp) varies between ~0.001 and ~100 μm. Fine particles (PM2.5: Dp < 2.5 μm) are especially interesting because they are the most harmful and can be transported over long distances. The aim of this thesis is to study the impact on air quality by pollution episodes of long-range transported aerosols affecting the composition of the boundary-layer atmosphere in remote and relatively unpolluted regions of the world. The sources and physicochemical properties of aerosols were investigated in detail, based on various measurements (1) in southern Finland during selected long-range transport (LRT) pollution episodes and unpolluted periods and (2) over the Atlantic Ocean between Europe and Antarctica during a voyage. Furthermore, the frequency of LRT pollution episodes of fine particles in southern Finland was investigated over a period of 8 years, using long-term air quality monitoring data. In southern Finland, the annual mean PM2.5 mass concentrations were low but LRT caused high peaks of daily mean concentrations every year. At an urban background site in Helsinki, the updated WHO guideline value (24-h PM2.5 mean 25 μg/m3) was exceeded during 1-7 LRT episodes each year during 1999-2006. The daily mean concentrations varied between 25 and 49 μg/m3 during the episodes, which was 3-6 times higher than the mean concentration in the long term. The in-depth studies of selected LRT episodes in southern Finland revealed that biomass burning in agricultural fields and wildfires, occurring mainly in Eastern Europe, deteriorated air quality on a continental scale. The strongest LRT episodes of fine particles resulted from open biomass-burning fires but the emissions from other anthropogenic sources in Eastern Europe also caused significant LRT episodes. Particle mass and number concentrations increased strongly in the accumulation mode (Dp ~ 0.09-1 μm) during the LRT episodes. However, the concentrations of smaller particles (Dp < 0.09 μm) remained low or even decreased due to the uptake of vapours and molecular clusters by LRT particles. The chemical analysis of individual particles showed that the proportions of several anthropogenic particle types increased (e.g. tar balls, metal oxides/hydroxides, spherical silicate fly ash particles and various calcium-rich particles) in southern Finland during an LRT episode, when aerosols originated from the polluted regions of Eastern Europe and some open biomass-burning smoke was also brought in by LRT. During unpolluted periods when air masses arrived from the north, the proportions of marine aerosols increased. In unpolluted rural regions of southern Finland, both accumulation mode particles and small-sized (Dp ~ 1-3 μm) coarse mode particles originated mostly from LRT. However, the composition of particles was totally different in these size fractions. In both size fractions, strong internal mixing of chemical components was typical for LRT particles. Thus, the aging of particles has significant impacts on their chemical, hygroscopic and optical properties, which can largely alter the environmental and health effects of LRT aerosols. Over the Atlantic Ocean, the individual particle composition of small-sized (Dp ~ 1-3 μm) coarse mode particles was affected by continental aerosol plumes to distances of at least 100-1000 km from the coast (e.g. pollutants from industrialized Europe, desert dust from the Sahara and biomass-burning aerosols near the Gulf of Guinea). The rate of chloride depletion from sea-salt particles was high near the coasts of Europe and Africa when air masses arrived from polluted continental regions. Thus, the LRT of continental aerosols had significant impacts on the composition of the marine boundary-layer atmosphere and seawater. In conclusion, integration of the results obtained using different measurement techniques captured the large spatial and temporal variability of aerosols as observed at terrestrial and marine sites, and assisted in establishing the causal link between land-bound emissions, LRT and air quality.

Nitrous oxide emissions from selected natural and managed northern ecosystems

Microbial activity in soils is the main source of nitrous oxide (N2O) to the atmosphere. Nitrous oxide is a strong greenhouse gas in the troposphere and participates in ozone destructive reactions in the stratosphere. The constant increase in the atmospheric concentration, as well as uncertainties in the known sources and sinks of N2O underline the need to better understand the processes and pathways of N2O in terrestrial ecosystems. This study aimed at quantifying N2O emissions from soils in northern Europe and at investigating the processes and pathways of N2O from agricultural and forest ecosystems. Emissions were measured in forest ecosystems, agricultural soils and a landfill, using the soil gradient, chamber and eddy covariance methods. Processes responsible for N2O production, and the pathways of N2O from the soil to the atmosphere, were studied in the laboratory and in the field. These ecosystems were chosen for their potential importance to the national and global budget of N2O. Laboratory experiments with boreal agricultural soils revealed that N2O production increases drastically with soil moisture content, and that the contribution of the nitrification and denitrification processes to N2O emissions depends on soil type. Laboratory study with beech (Fagus sylvatica) seedlings demonstrated that trees can serve as conduits for N2O from the soil to the atmosphere. If this mechanism is important in forest ecosystems, the current emission estimates from forest soils may underestimate the total N2O emissions from forest ecosystems. Further field and laboratory studies are needed to evaluate the importance of this mechanism in forest ecosystems. The emissions of N2O from northern forest ecosystems and a municipal landfill were highly variable in time and space. The emissions of N2O from boreal upland forest soil were among the smallest reported in the world. Despite the low emission rates, the soil gradient method revealed a clear seasonal variation in N2O production. The organic topsoil was responsible for most of the N2O production and consumption in this forest soil. Emissions from the municipal landfill were one to two orders of magnitude higher than those from agricultural soils, which are the most important source of N2O to the atmosphere. Due to their small areal coverage, landfills only contribute minimally to national N2O emissions in Finland. The eddy covariance technique was demonstrated to be useful for measuring ecosystem-scale emissions of N2O in forest and landfill ecosystems. Overall, more measurements and integration between different measurement techniques are needed to capture the large variability in N2O emissions from natural and managed northern ecosystems.

Fluorescence properties of Baltic Sea phytoplankton

To obtain data on phytoplankton dynamics with improved spatial and temporal resolution, and at reduced cost, traditional phytoplankton monitoring methods have been supplemented with optical approaches. In this thesis, I have explored various fluorescence-based techniques for detection of phytoplankton abundance, taxonomy and physiology in the Baltic Sea. In algal cultures used in this thesis, the availability of nitrogen and light conditions caused changes in pigmentation, and consequently in light absorption and fluorescence properties of cells. In the Baltic Sea, physical environmental factors (e.g. mixing depth, irradiance and temperature) and related seasonal succession in the phytoplankton community explained a large part of the seasonal variability in the magnitude and shape of Chlorophyll a (Chla)-specific absorption. The variability in Chla-specific fluorescence was related to the abundance of cyanobacteria, the size structure of the phytoplankton community, and absorption characteristics of phytoplankton. Cyanobacteria show very low Chla-specific fluorescence. In the presence of eukaryotic species, Chla fluorescence describes poorly cyanobacteria. During cyanobacterial bloom in the Baltic Sea, phycocyanin fluorescence explained large part of the variability in Chla concentrations. Thus, both Chla and phycocyanin fluorescence were required to predict Chla concentration. Phycobilins are major light harvesting pigments for cyanobacteria. In the open Baltic Sea, small picoplanktonic cyanobacteria were the main source of phycoerythrin fluorescence and absorption signal. Large filamentous cyanobacteria, forming harmful blooms, were the main source of the phycocyanin fluorescence signal and typically their biomass and phycocyanin fluorescence were linearly related. Using phycocyanin fluorescence, dynamics of cyanobacterial blooms can be detected at high spatial and seasonal resolution not possible with other methods. Various taxonomic phytoplankton pigment groups can be separated by spectral fluorescence. I compared multivariate calibration methods for the retrieval of phytoplankton biomass in different taxonomic groups. Partial least squares regression method gave the closest predictions for all taxonomic groups, and the accuracy was adequate for phytoplankton bloom detection. Variable fluorescence has been proposed as a tool to study the physiological state of phytoplankton. My results from the Baltic Sea emphasize that variable fluorescence alone cannot be used to detect nutrient limitation of phytoplankton. However, when combined with experiments with active nutrient manipulation, and other nutrient limitation indices, variable fluorescence provided valuable information on the physiological responses of the phytoplankton community. This thesis found a severe limitation of a commercial fast repetition rate fluorometer, which couldn t detect the variable fluorescence of phycoerythrin-lacking cyanobacteria. For these species, the Photosystem II absorption of blue light is very low, and fluorometer excitation light did not saturate Photosystem II during a measurement. This thesis encourages the use of various in vivo fluorescence methods for the detection of bulk phytoplankton biomass, biomass of cyanobacteria, chemotaxonomy of phytoplankton community, and phytoplankton physiology. Fluorescence methods can support traditional phytoplankton monitoring by providing continuous measurements of phytoplankton, and thereby strengthen the understanding of the links between biological, chemical and physical processes in aquatic ecosystems.

Photobiological studies of Baltic Sea phytoplankton

Phytoplankton ecology and productivity is one of the main branches of contemporary oceanographic research. Research groups in this branch have increasingly started to utilise bio-optical applications. My main research objective was to critically investigate the advantages and deficiencies of the fast repetition rate (FRR) fluorometry for studies of productivity of phytoplankton, and the responses of phytoplankton towards varying environmental stress. Second, I aimed to clarify the applicability of the FRR system to the optical environment of the Baltic Sea. The FRR system offers a highly dynamic tool for studies of phytoplankton photophysiology and productivity both in the field and in a controlled environment. The FRR metrics obtain high-frequency in situ determinations of the light-acclimative and photosynthetic parameters of intact phytoplankton communities. The measurement protocol is relatively easy to use without phases requiring analytical determinations. The most notable application of the FRR system lies in its potential for making primary productivity (PP) estimations. However, the realisation of this scheme is not straightforward. The FRR-PP, based on the photosynthetic electron flow (PEF) rate, are linearly related to the photosynthetic gas exchange (fixation of 14C) PP only in environments where the photosynthesis is light-limited. If the light limitation is not present, as is usually the case in the near-surface layers of the water column, the two PP approaches will deviate. The prompt response of the PEF rate to the short-term variability in the natural light field makes the field comparisons between the PEF-PP and the 14C-PP difficult to interpret, because this variability is averaged out in the 14C-incubations. Furthermore, the FRR based PP models are tuned to closely follow the vertical pattern of the underwater irradiance. Due to the photoacclimational plasticity of phytoplankton, this easily leads to overestimates of water column PP, if precautionary measures are not taken. Natural phytoplankton is subject to broad-waveband light. Active non-spectral bio-optical instruments, like the FRR fluorometer, emit light in a relatively narrow waveband, which by its nature does not represent the in situ light field. Thus, the spectrally-dependent parameters provided by the FRR system need to be spectrally scaled to the natural light field of the Baltic Sea. In general, the requirement of spectral scaling in the water bodies under terrestrial impact concerns all light-adaptive parameters provided by any active non-spectral bio-optical technique. The FRR system can be adopted to studies of all phytoplankton that possess efficient light harvesting in the waveband matching the bluish FRR excitation. Although these taxa cover the large bulk of all the phytoplankton taxa, one exception with a pronounced ecological significance is found in the Baltic Sea. The FRR system cannot be used to monitor the photophysiology of the cyanobacterial taxa harvesting light in the yellow-red waveband. These taxa include the ecologically-significant bloom-forming cyanobacterial taxa in the Baltic Sea.