Post-industrial Intervention : An Activity-Theoretical Expedition Tracing the Proximal Development of Forms of Conducting Interventions

Ei saatavilla

Econometric models of Finnish non-industrial private forest owners' timber supply and timber stock

This dissertation examines the short- and long-run impacts of timber prices and other factors affecting NIPF owners' timber harvesting and timber stocking decisions. The utility-based Faustmann model provides testable hypotheses of the exogenous variables retained in the timber supply analysis. The timber stock function, derived from a two-period biomass harvesting model, is estimated using a two-step GMM estimator based on balanced panel data from 1983 to 1991. Timber supply functions are estimated using a Tobit model adjusted for heteroscedasticity and nonnormality of errors based on panel data from 1994 to 1998. Results show that if specification analysis of the Tobit model is ignored, inconsistency and biasedness can have a marked effect on parameter estimates. The empirical results show that owner's age is the single most important factor determining timber stock; timber price is the single most important factor in harvesting decision. The results of the timber supply estimations can be interpreted using utility-based Faustmann model of a forest owner who values a growing timber in situ.

Metsänomistajakunnan rakenteen ennustaminen

The general change in the population structure and its impacts on the forest ownership structure were investigated in the thesis. The research assumed that the structural change in society has an effect on the outlook of the non-industrial private forest ownership. The changes in the structure of society were mainly restricted to population, education and occupation structures. The migration of the rural population into cities was also taken into consideration. The structural changes both in society and the non-industrial private forest ownership were examined as phenomena and their development directions were investigated since the middle of the 1970s. It could be established that the changes in the structures were mainly of the same kind in society as in forest owner structure. The clearest similarities between the changes in population and forest owner structure could be found in an increased mean age, a decrease in the 18 to 39 age bracket, those without a degree and in the farmers' shares. Furthermore it could be stated that migration into cities had taken place among both the forest owners and the general population. The main part of the research was concentrated on estimating regression models that explain the non-industrial private forest ownership change by the structural change in the population. A panel data was gathered from population statistics and previous forest ownership research information. The panel contained the years 1990 and 1999. With the assistance of the panel data it was possible to estimate regression and fixed effects' models that explained the structural changes in the non-industrial private forest ownership by evolution in the whole population. In the use of the estimated models authorities' forecasts considering the population were exploited. Only a few of the estimated models were statistically significant. This could be explained due to lack of a larger panel data. In addition the structural change of the non-industrial forest ownership was forecasted by trends.

The Spin-Statistics Relation and Noncommutative Quantum Field Theory

The efforts of combining quantum theory with general relativity have been great and marked by several successes. One field where progress has lately been made is the study of noncommutative quantum field theories that arise as a low energy limit in certain string theories. The idea of noncommutativity comes naturally when combining these two extremes and has profound implications on results widely accepted in traditional, commutative, theories. In this work I review the status of one of the most important connections in physics, the spin-statistics relation. The relation is deeply ingrained in our reality in that it gives us the structure for the periodic table and is of crucial importance for the stability of all matter. The dramatic effects of noncommutativity of space-time coordinates, mainly the loss of Lorentz invariance, call the spin-statistics relation into question. The spin-statistics theorem is first presented in its traditional setting, giving a clarifying proof starting from minimal requirements. Next the notion of noncommutativity is introduced and its implications studied. The discussion is essentially based on twisted Poincaré symmetry, the space-time symmetry of noncommutative quantum field theory. The controversial issue of microcausality in noncommutative quantum field theory is settled by showing for the first time that the light wedge microcausality condition is compatible with the twisted Poincaré symmetry. The spin-statistics relation is considered both from the point of view of braided statistics, and in the traditional Lagrangian formulation of Pauli, with the conclusion that Pauli's age-old theorem stands even this test so dramatic for the whole structure of space-time.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

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.

Substance flow analysis in Finland : Four case studies on N and P flows

Nitrogen (N) and phosphorus (P) are essential elements for all living organisms. However, in excess, they contribute to several environmental problems such as aquatic and terrestrial eutrophication. Globally, human action has multiplied the volume of N and P cycling since the onset of industrialization. The multiplication is a result of intensified agriculture, increased energy consumption and population growth. Industrial ecology (IE) is a discipline, in which human interaction with the ecosystems is investigated using a systems analytical approach. The main idea behind IE is that industrial systems resemble ecosystems, and, like them, industrial systems can then be described using material, energy and information flows and stocks. Industrial systems are dependent on the resources provided by the biosphere, and these two cannot be separated from each other. When studying substance flows, the aims of the research from the viewpoint of IE can be, for instance, to elucidate the ways how the cycles of a certain substance could be more closed and how the flows of a certain substance could be decreased per unit of production (= dematerialization). In Finland, N and P are studied widely in different ecosystems and environmental emissions. A holistic picture comparing different societal systems is, however, lacking. In this thesis, flows of N and P were examined in Finland using substance flow analysis (SFA) in the following four subsystems: I) forest industry and use of wood fuels, II) food production and consumption, III) energy, and IV) municipal waste. A detailed analysis at the end of the 1990s was performed. Furthermore, historical development of the N and P flows was investigated in the energy system (III) and the municipal waste system (IV). The main research sources were official statistics, literature, monitoring data, and expert knowledge. The aim was to identify and quantify the main flows of N and P in Finland in the four subsystems studied. Furthermore, the aim was to elucidate whether the nutrient systems are cyclic or linear, and to identify how these systems could be more efficient in the use and cycling of N and P. A final aim was to discuss how this type of an analysis can be used to support decision-making on environmental problems and solutions. Of the four subsystems, the food production and consumption system and the energy system created the largest N flows in Finland. For the creation of P flows, the food production and consumption system (Paper II) was clearly the largest, followed by the forest industry and use of wood fuels and the energy system. The contribution of Finland to N and P flows on a global scale is low, but when compared on a per capita basis, we are one of the largest producers of these flows, with relatively high energy and meat consumption being the main reasons. Analysis revealed the openness of all four systems. The openness is due to the high degree of internationality of the Finnish markets, the large-scale use of synthetic fertilizers and energy resources and the low recycling rate of many waste fractions. Reduction in the use of fuels and synthetic fertilizers, reorganization of the structure of energy production, reduced human intake of nutrients and technological development are crucial in diminishing the N and P flows. To enhance nutrient recycling and replace inorganic fertilizers, recycling of such wastes as wood ash and sludge could be promoted. SFA is not usually sufficiently detailed to allow specific recommendations for decision-making to be made, but it does yield useful information about the relative magnitude of the flows and may reveal unexpected losses. Sustainable development is a widely accepted target for all human action. SFA is one method that can help to analyse how effective different efforts are in leading to a more sustainable society. SFA's strength is that it allows a holistic picture of different natural and societal systems to be drawn. Furthermore, when the environmental impact of a certain flow is known, the method can be used to prioritize environmental policy efforts.

Analyzing changes in macro-level drivers of country-specific emissions : The role of consumption, technology and trade

Industrial ecology is an important field of sustainability science. It can be applied to study environmental problems in a policy relevant manner. Industrial ecology uses ecosystem analogy; it aims at closing the loop of materials and substances and at the same time reducing resource consumption and environmental emissions. Emissions from human activities are related to human interference in material cycles. Carbon (C), nitrogen (N) and phosphorus (P) are essential elements for all living organisms, but in excess have negative environmental impacts, such as climate change (CO2, CH4 N2O), acidification (NOx) and eutrophication (N, P). Several indirect macro-level drivers affect emissions change. Population and affluence (GDP/capita) often act as upward drivers for emissions. Technology, as emissions per service used, and consumption, as economic intensity of use, may act as drivers resulting in a reduction in emissions. In addition, the development of country-specific emissions is affected by international trade. The aim of this study was to analyse changes in emissions as affected by macro-level drivers in different European case studies. ImPACT decomposition analysis (IPAT identity) was applied as a method in papers I III. The macro-level perspective was applied to evaluate CO2 emission reduction targets (paper II) and the sharing of greenhouse gas emission reduction targets (paper IV) in the European Union (EU27) up to the year 2020. Data for the study were mainly gathered from official statistics. In all cases, the results were discussed from an environmental policy perspective. The development of nitrogen oxide (NOx) emissions was analysed in the Finnish energy sector during a long time period, 1950 2003 (paper I). Finnish emissions of NOx began to decrease in the 1980s as the progress in technology in terms of NOx/energy curbed the impact of the growth in affluence and population. Carbon dioxide (CO2) emissions related to energy use during 1993 2004 (paper II) were analysed by country and region within the European Union. Considering energy-based CO2 emissions in the European Union, dematerialization and decarbonisation did occur, but not sufficiently to offset population growth and the rapidly increasing affluence during 1993 2004. The development of nitrogen and phosphorus load from aquaculture in relation to salmonid consumption in Finland during 1980 2007 was examined, including international trade in the analysis (paper III). A regional environmental issue, eutrophication of the Baltic Sea, and a marginal, yet locally important source of nutrients was used as a case. Nutrient emissions from Finnish aquaculture decreased from the 1990s onwards: although population, affluence and salmonid consumption steadily increased, aquaculture technology improved and the relative share of imported salmonids increased. According to the sustainability challenge in industrial ecology, the environmental impact of the growing population size and affluence should be compensated by improvements in technology (emissions/service used) and with dematerialisation. In the studied cases, the emission intensity of energy production could be lowered for NOx by cleaning the exhaust gases. Reorganization of the structure of energy production as well as technological innovations will be essential in lowering the emissions of both CO2 and NOx. Regarding the intensity of energy use, making the combustion of fuels more efficient and reducing energy use are essential. In reducing nutrient emissions from Finnish aquaculture to the Baltic Sea (paper III) through technology, limits of biological and physical properties of cultured fish, among others, will eventually be faced. Regarding consumption, salmonids are preferred to many other protein sources. Regarding trade, increasing the proportion of imports will outsource the impacts. Besides improving technology and dematerialization, other viewpoints may also be needed. Reducing the total amount of nutrients cycling in energy systems and eventually contributing to NOx emissions needs to be emphasized. Considering aquaculture emissions, nutrient cycles can be partly closed through using local fish as feed replacing imported feed. In particular, the reduction of CO2 emissions in the future is a very challenging task when considering the necessary rates of dematerialisation and decarbonisation (paper II). Climate change mitigation may have to focus on other greenhouse gases than CO2 and on the potential role of biomass as a carbon sink, among others. The global population is growing and scaling up the environmental impact. Population issues and growing affluence must be considered when discussing emission reductions. Climate policy has only very recently had an influence on emissions, and strong actions are now called for climate change mitigation. Environmental policies in general must cover all the regions related to production and impacts in order to avoid outsourcing of emissions and leakage effects. The macro-level drivers affecting changes in emissions can be identified with the ImPACT framework. Statistics for generally known macro-indicators are currently relatively well available for different countries, and the method is transparent. In the papers included in this study, a similar method was successfully applied in different types of case studies. Using transparent macro-level figures and a simple top-down approach are also appropriate in evaluating and setting international emission reduction targets, as demonstrated in papers II and IV. The projected rates of population and affluence growth are especially worth consideration in setting targets. However, sensitivities in calculations must be carefully acknowledged. In the basic form of the ImPACT model, the economic intensity of consumption and emission intensity of use are included. In seeking to examine consumption but also international trade in more detail, imports were included in paper III. This example demonstrates well how outsourcing of production influences domestic emissions. Country-specific production-based emissions have often been used in similar decomposition analyses. Nevertheless, trade-related issues must not be ignored.

Ultrastructure of Biofilms Formed by Bacteria from Industrial Processes

Microorganisms exist predominantly as sessile multispecies communities in natural habitats. Most bacterial species can form these matrix-enclosed microbial communities called biofilms. Biofilms occur in a wide range of environments, on every surface with sufficient moisture and nutrients, also on surfaces in industrial settings and engineered water systems. This unwanted biofilm formation on equipment surfaces is called biofouling. Biofouling can significantly decrease equipment performance and lifetime and cause contamination and impaired quality of the industrial product. In this thesis we studied bacterial adherence to abiotic surfaces by using coupons of stainless steel coated or not coated with fluoropolymer or diamond like carbon (DLC). As model organisms we used bacterial isolates from paper machines (Meiothermus silvanus, Pseudoxanthomonas taiwanensis and Deinococcus geothermalis) and also well characterised species isolated from medical implants (Staphylococcus epidermidis). We found that coating of steel surface with these materials reduced its tendency towards biofouling: Fluoropolymer and DLC coatings repelled all four biofilm formers on steel. We found great differences between bacterial species in their preference of surfaces to adhere as well as their ultrastructural details, like number and thickness of adhesion organelles they expressed. These details responded differently towards the different surfaces they adhered to. We further found that biofilms of D. geothermalis formed on titanium dioxide coated coupons of glass, steel and titanium, were effectively removed by photocatalytic action in response to irradiation at 360 nm. However, on non-coated glass or steel surfaces irradiation had no detectable effect on the amount of bacterial biomass. We showed that the adhesion organelles of bacteria on illuminated TiO2 coated coupons were complety destroyed whereas on non-coated coupons they looked intact when observed by microscope. Stainless steel is the most widely used material for industrial process equipments and surfaces. The results in this thesis showed that stainless steel is prone to biofouling by phylogenetically distant bacterial species and that coating of the steel may offer a tool for reduced biofouling of industrial equipment. Photocatalysis, on the other hand, is a potential technique for biofilm removal from surfaces in locations where high level of hygiene is required. Our study of natural biofilms on barley kernel surfaces showed that also there the microbes possessed adhesion organelles visible with electronmicroscope both before and after steeping. The microbial community of dry barley kernels turned into a dense biofilm covered with slimy extracellular polymeric substance (EPS) in the kernels after steeping in water. Steeping is the first step in malting. We also presented evidence showing that certain strains of Lactobacillus plantarum and Wickerhamomyces anomalus, when used as starter cultures in the steeping water, could enter the barley kernel and colonise the tissues of the barley kernel. By use of a starter culture it was possible to reduce the extensive production of EPS, which resulted in a faster filtration of the mash.

From environmental concerns towards sustainable food provisioning. : Material flow and food consumption scenario studies on sustainability of agri-food systems

Agriculture is an economic activity that heavily relies on the availability of natural resources. Through its role in food production agriculture is a major factor affecting public welfare and health, and its indirect contribution to gross domestic product and employment is significant. Agriculture also contributes to numerous ecosystem services through management of rural areas. However, the environmental impact of agriculture is considerable and reaches far beyond the agroecosystems. The questions related to farming for food production are, thus, manifold and of great public concern. Improving environmental performance of agriculture and sustainability of food production, sustainabilizing food production, calls for application of wide range of expertise knowledge. This study falls within the field of agro-ecology, with interphases to food systems and sustainability research and exploits the methods typical of industrial ecology. The research in these fields extends from multidisciplinary to interdisciplinary and transdisciplinary, a holistic approach being the key tenet. The methods of industrial ecology have been applied extensively to explore the interaction between human economic activity and resource use. Specifically, the material flow approach (MFA) has established its position through application of systematic environmental and economic accounting statistics. However, very few studies have applied MFA specifically to agriculture. The MFA approach was used in this thesis in such a context in Finland. The focus of this study is the ecological sustainability of primary production. The aim was to explore the possibilities of assessing ecological sustainability of agriculture by using two different approaches. In the first approach the MFA-methods from industrial ecology were applied to agriculture, whereas the other is based on the food consumption scenarios. The two approaches were used in order to capture some of the impacts of dietary changes and of changes in production mode on the environment. The methods were applied at levels ranging from national to sector and local levels. Through the supply-demand approach, the viewpoint changed between that of food production to that of food consumption. The main data sources were official statistics complemented with published research results and expertise appraisals. MFA approach was used to define the system boundaries, to quantify the material flows and to construct eco-efficiency indicators for agriculture. The results were further elaborated for an input-output model that was used to analyse the food flux in Finland and to determine its relationship to the economy-wide physical and monetary flows. The methods based on food consumption scenarios were applied at regional and local level for assessing feasibility and environmental impacts of relocalising food production. The approach was also used for quantification and source allocation of greenhouse gas (GHG) emissions of primary production. GHG assessment provided, thus, a means of crosschecking the results obtained by using the two different approaches. MFA data as such or expressed as eco-efficiency indicators, are useful in describing the overall development. However, the data are not sufficiently detailed for identifying the hot spots of environmental sustainability. Eco-efficiency indicators should not be bluntly used in environmental assessment: the carrying capacity of the nature, the potential exhaustion of non-renewable natural resources and the possible rebound effect need also to be accounted for when striving towards improved eco-efficiency. The input-output model is suitable for nationwide economy analyses and it shows the distribution of monetary and material flows among the various sectors. Environmental impact can be captured only at a very general level in terms of total material requirement, gaseous emissions, energy consumption and agricultural land use. Improving environmental performance of food production requires more detailed and more local information. The approach based on food consumption scenarios can be applied at regional or local scales. Based on various diet options the method accounts for the feasibility of re-localising food production and environmental impacts of such re-localisation in terms of nutrient balances, gaseous emissions, agricultural energy consumption, agricultural land use and diversity of crop cultivation. The approach is applicable anywhere, but the calculation parameters need to be adjusted so as to comply with the specific circumstances. The food consumption scenario approach, thus, pays attention to the variability of production circumstances, and may provide some environmental information that is locally relevant. The approaches based on the input-output model and on food consumption scenarios represent small steps towards more holistic systemic thinking. However, neither one alone nor the two together provide sufficient information for sustainabilizing food production. Environmental performance of food production should be assessed together with the other criteria of sustainable food provisioning. This requires evaluation and integration of research results from many different disciplines in the context of a specified geographic area. Foodshed area that comprises both the rural hinterlands of food production and the population centres of food consumption is suggested to represent a suitable areal extent for such research. Finding a balance between the various aspects of sustainability is a matter of optimal trade-off. The balance cannot be universally determined, but the assessment methods and the actual measures depend on what the bottlenecks of sustainability are in the area concerned. These have to be agreed upon among the actors of the area