Local systems, global impacts : Using life cycle assessment to analyse the potential and constraints of industrial symbioses

Human activities extract and displace different substances and materials from the earth s crust, thus causing various environmental problems, such as climate change, acidification and eutrophication. As problems have become more complicated, more holistic measures that consider the origins and sources of pollutants have been called for. Industrial ecology is a field of science that forms a comprehensive framework for studying the interactions between the modern technological society and the environment. Industrial ecology considers humans and their technologies to be part of the natural environment, not separate from it. Industrial operations form natural systems that must also function as such within the constraints set by the biosphere. Industrial symbiosis (IS) is a central concept of industrial ecology. Industrial symbiosis studies look at the physical flows of materials and energy in local industrial systems. In an ideal IS, waste material and energy are exchanged by the actors of the system, thereby reducing the consumption of virgin material and energy inputs and the generation of waste and emissions. Companies are seen as part of the chains of suppliers and consumers that resemble those of natural ecosystems. The aim of this study was to analyse the environmental performance of an industrial symbiosis based on pulp and paper production, taking into account life cycle impacts as well. Life Cycle Assessment (LCA) is a tool for quantitatively and systematically evaluating the environmental aspects of a product, technology or service throughout its whole life cycle. Moreover, the Natural Step Sustainability Principles formed a conceptual framework for assessing the environmental performance of the case study symbiosis (Paper I). The environmental performance of the case study symbiosis was compared to four counterfactual reference scenarios in which the actors of the symbiosis operated on their own. The research methods used were process-based life cycle assessment (LCA) (Papers II and III) and hybrid LCA, which combines both process and input-output LCA (Paper IV). The results showed that the environmental impacts caused by the extraction and processing of the materials and the energy used by the symbiosis were considerable. If only the direct emissions and resource use of the symbiosis had been considered, less than half of the total environmental impacts of the system would have been taken into account. When the results were compared with the counterfactual reference scenarios, the net environmental impacts of the symbiosis were smaller than those of the reference scenarios. The reduction in environmental impacts was mainly due to changes in the way energy was produced. However, the results are sensitive to the way the reference scenarios are defined. LCA is a useful tool for assessing the overall environmental performance of industrial symbioses. It is recommended that in addition to the direct effects, the upstream impacts should be taken into account as well when assessing the environmental performance of industrial symbioses. Industrial symbiosis should be seen as part of the process of improving the environmental performance of a system. In some cases, it may be more efficient, from an environmental point of view, to focus on supply chain management instead.  

Global, Local and Vector-Valued Tb Theorems on Non-Homogeneous Metric Spaces

Various Tb theorems play a key role in the modern harmonic analysis. They provide characterizations for the boundedness of Calderón-Zygmund type singular integral operators. The general philosophy is that to conclude the boundedness of an operator T on some function space, one needs only to test it on some suitable function b. The main object of this dissertation is to prove very general Tb theorems. The dissertation consists of four research articles and an introductory part. The framework is general with respect to the domain (a metric space), the measure (an upper doubling measure) and the range (a UMD Banach space). Moreover, the used testing conditions are weak. In the first article a (global) Tb theorem on non-homogeneous metric spaces is proved. One of the main technical components is the construction of a randomization procedure for the metric dyadic cubes. The difficulty lies in the fact that metric spaces do not, in general, have a translation group. Also, the measures considered are more general than in the existing literature. This generality is genuinely important for some applications, including the result of Volberg and Wick concerning the characterization of measures for which the analytic Besov-Sobolev space embeds continuously into the space of square integrable functions. In the second article a vector-valued extension of the main result of the first article is considered. This theorem is a new contribution to the vector-valued literature, since previously such general domains and measures were not allowed. The third article deals with local Tb theorems both in the homogeneous and non-homogeneous situations. A modified version of the general non-homogeneous proof technique of Nazarov, Treil and Volberg is extended to cover the case of upper doubling measures. This technique is also used in the homogeneous setting to prove local Tb theorems with weak testing conditions introduced by Auscher, Hofmann, Muscalu, Tao and Thiele. This gives a completely new and direct proof of such results utilizing the full force of non-homogeneous analysis. The final article has to do with sharp weighted theory for maximal truncations of Calderón-Zygmund operators. This includes a reduction to certain Sawyer-type testing conditions, which are in the spirit of Tb theorems and thus of the dissertation. The article extends the sharp bounds previously known only for untruncated operators, and also proves sharp weak type results, which are new even for untruncated operators. New techniques are introduced to overcome the difficulties introduced by the non-linearity of maximal truncations.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.