Effect of forest-based biofuels production on carbon footprint, Case: Integrated LWC paper mill

International energy and climate strategies also set Finland’s commitments to increasing the use of renewable energy sources and reducing greenhouse gas emissions. The target can be achieved by, for example, increasing the use of energy wood. Finland’s forest biomass potential is significant compared with current use. Increased use will change forest management and wood harvesting methods however. The thesis examined the potential for integrated pulp and paper mills to increase bioenergy production. The effects of two bioenergy production technologies on the carbon footprint of an integrated LWC mill were studied at mill level and from the cradle-to-customer approach. The LignoBoost process and FT diesel production were chosen as bioenergy cases. The data for the LignoBoost process were obtained from Metso and for the FT diesel process from Neste Oil. The rest of the information is based on the literature and databases of the KCL-ECO life-cycle computer program and Ecoinvent. In both case studies, the carbon footprint was reduced. From the results, it can be concluded that it is possible to achieve a fossil-fuel-free pulp mill with the LignoBoost process. By using steam from the FT diesel process, the amount of auxiliary fuel can be reduced considerably and the bark boiler can be replaced. With a choice of auxiliary fuels for use in heat production in the paper mill and the production methods for purchased electricity, it is possible to affect the carbon footprints even more in both cases.

Forest-based supply chain modelling using the SimPy simulation framework

Proper management of supply chains is fundamental in the overall system performance of forestbased activities. Usually, efficient management techniques rely on a decision support software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains’ nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forestbased supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event systems using operations such as events, processes and resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic behaviours of processing and driving times were simulated. The obtained results validate the SimPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.

On Value Creation at an Industrial Intersection – Bioenergy in the Forest and Energy Sectors

The traditional forest industry is a good example of the changing nature of the competitive environment in many industries. Faced with drastic challenges forestindustry companies are forced to search for new value-creating strategies in order to create competitive advantage. The emerging bioenergy business is now offering promising avenues for value creation for both the forest and energy sectors because of their complementary resources and knowledge with respect to bioenergy production from forest-based biomass. The key objective of this dissertation is to examine the sources of sustainable competitive advantage and the value-creation opportunities that are emerging at the intersection between the forest and energy industries. The research topic is considered from different perspectives in order to provide a comprehensive view of the phenomenon. The study discusses the business opportunities that are related to producing bioenergy from forest-based biomass, and sheds light on the greatest challenges and threats influencing the success of collaboration between the forest and energy sectors. In addition, it identifies existing and potential bioenergy actors, and considers the resources and capabilities needed in order to prosper in the bioenergy field. The value-creation perspective is founded on strategic management accounting, the theoretical frameworks are adopted from the field of strategic management, and the future aspect is taken into account through the application of futures studies research methodology. This thesis consists of two parts. The first part provides a synthesis of the overall dissertation, and the second part comprises four complementary research papers. There search setting is explorative in nature, and both qualitative and quantitative research methods are used. As a result, the thesis lays the foundation for non-technological studies on bioenergy. It gives an example of how to study new value-creation opportunities at an industrial intersection, and discusses the main determinants affecting the value-creation process. In order to accomplish these objectives the phenomenon of value creation at the intersection between the forest and energy industries is theorized and connected with the dynamic resource-based view of the firm.

Container logistic innovations in forest-energy sector: Markets, future service concepts and technical improvements

The report presents the results of the commercialization project called the Container logistic services for forest bioenergy. The project promotes new business that is emerging around overall container logistic services in the bioenergy sector. The results assess the European markets of the container logistics for biomass, enablers for new business creation and required service bundles for the concept. We also demonstrate the customer value of the container logistic services for different market segments. The concept analysis is based on concept mapping, quality function deployment process (QFD) and business network analysis. The business network analysis assesses key shareholders and their mutual connections. The performance of the roadside chipping chain is analysed by the logistic cost simulation, RFID system demonstration and freezing tests. The EU has set the renewable energy target to 20 % in 2020 of which Biomass could account for two-thirds. In the Europe, the production of wood fuels was 132.9 million solid-m3 in 2012 and production of wood chips and particles was 69.0 million solidm3. The wood-based chips and particle flows are suitable for container transportation providing market of 180.6 million loose- m3 which mean 4.5 million container loads per year. The intermodal logistics of trucks and trains are promising for the composite containers because the biomass does not freeze onto the inner surfaces in the unloading situations. The overall service concept includes several packages: container rental, container maintenance, terminal services, RFID-tracking service, and simulation and ERP-integration service. The container rental and maintenance would provide transportation entrepreneurs a way to increase the capacity without high investment costs. The RFID-concept would lead to better work planning improving profitability throughout the logistic chain and simulation supports fuel supply optimization.

Exploring socioeconomic impacts of forest based mitigation projects: Lessons from Brazil and Bolivia

This paper aims to contribute new insights globally and regionally on how carbon forest mitigation contributes to sustainable development in South America. Carbon finance has emerged as a potential policy option to tackling global climate change, degradation of forests, and social development in poor countries. This paper focuses on evaluating the socioeconomic impacts of a set of forest based mitigation pilot projects that emerged under the United Nations Framework Convention on Climate Change. The paper reviews research conducted in 2001–2002, drawing from empirical data from four pilot projects, derived from qualitative stakeholder interviews, and complemented by policy documents and literature. Of the four projects studied three are located in frontier areas, where there are considerable pressures for conversion of standing forest to agriculture. In this sense, forest mitigation projects have a substantial role to play in the region. Findings suggest however, that all four projects have experienced cumbersome implementation processes specifically, due to weak social objectives, poor communication, as well as time constraints. In three out of four cases, stakeholders highlighted limited local acceptance at the implementation stages. In the light of these findings, we discuss opportunities for implementation of future forest based mitigation projects in the land use sector.

Random Forest Based Approach for Concept-Drift Handling

Algorithms for concept drift handling are important for various applications including video analysis and smart grids. In this paper we present decision tree ensemble classication method based on the Random Forest algorithm for concept drift. The weighted majority voting ensemble aggregation rule is employed based on the ideas of Accuracy Weighted Ensemble (AWE) method. Base learner weight in our case is computed for each sample evaluation using base learners accuracy and intrinsic proximity measure of Random Forest. Our algorithm exploits both temporal weighting of samples and ensemble pruning as a forgetting strategy. We present results of empirical comparison of our method with îriginal random forest with incorporated replace-the-looser forgetting andother state-of-the-art concept-drift classiers like AWE2.

Forest natural regeneration and biomass production after slash and burn in a seasonally dry forest in the Southern Brazilian Amazon

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Biomass consumption and CO2, CO and main hydrocarbon gas emissions in an Amazonian forest clearing fire

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Use of levoglucosan, potassium, and water-soluble organic carbon to characterize the origins of biomass-burning aerosols

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Use of levoglucosan, potassium, and water-soluble organic carbon to characterize the origins of biomass-burning aerosols

Three chemical species related to biomass burning, levoglucosan, potassium and water-soluble organic carbon (WSOC), were measured in aerosol samples collected in a rural area on the outskirts of the municipality of Ourinhos (Sao Paulo State, Brazil). This region is representative of the rural interior of the State, where the economy is based on agro-industrial production, and the most important crop is sugar cane. The manual harvesting process requires that the cane be first burned to remove excess foliage, leading to large emissions of particulate materials to the atmosphere. Most of the levoglucosan (68-89%) was present in small particles (<1.5 mu m), and its concentration in total aerosol ranged from 25 to 1186 ng m(-3). The highest values were found at night, when most of the biomass burning occurs. In contrast, WSOC showed no diurnal pattern, with an average concentration of 5.38 +/- 2.97 mu g m(-3) (n = 27). A significant linear correlation between levoglucosan and WSOC (r = 0.54; n = 26; p < 0.0001) confirmed that biomass burning was in fact an important source of WSOC in the study region. A moderate (but significant) linear correlation between levoglucosan and potassium concentrations (r = 0.62; n = 40; p < 0.0001) was indicative of the influence of other sources of potassium in the study region, such as soil resuspension and fertilizers. When only the fine particles (<1.5 pm; typical of biomass burning) were considered, the linear coefficient increased to 0.91 (n = 9). In this case, the average levoglucosan/K+ ratio was 0.24, which may be typical of biomass burning in the study region. This ratio is about 5 times lower than that previously found for Amazon aerosol collected during the day, when flaming combustion prevails. This suggests that the levoglucosan/K+ ratio may be especially helpful for characterization of the type of vegetation burned (such as crops or forest), when biomass-burning is the dominant source of potassium. The relatively high concentrations of WSOC (and inorganic ions) suggest an important influence on the formation of cloud condensation nuclei, which is likely to affect cloud formation and precipitation patterns. (C) 2012 Elsevier Ltd. All rights reserved.

Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar

Madagascar is currently developing a policy and strategies to enhance the sustainable management of its natural resources, encouraged by United Nations Framework Convention on Climate Change (UNFCCC) and REDD. To set up a sustainable financing scheme methodologies have to be provided that estimate, prevent and mitigate leakage, develop national and regional baselines, and estimate carbon benefits. With this research study this challenge was tried to be addressed by analysing a lowland rainforest in the Analanjirofo region in the district of Soanierana Ivongo, North East of Madagascar. For two distinguished forest degradation stages: “low degraded forest” and “degraded forest” aboveground biomass and carbon stock was assessed. The corresponding rates of carbon within those two classes were calculated and linked to a multi-temporal set of SPOT satellite data acquired in 1991, 2004 and 2009. Deforestation and particularly degradation and the related carbon stock developments were analysed. With the assessed data for the 3 years 1991, 2004 and 2009 it was possible to model a baseline and to develop a forest prediction for 2020 for Analanjirofo region in the district of Soanierana Ivongo. These results, developed applying robust methods, may provide important spatial information regarding the priorities in planning and implementation of future REDD+ activities in the area.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Micropatterning of single-walled carbon nanotube forest

In this work, high-aligned single-walled carbon nanotube (SWCNT) forest have been grown using a high-density plasma chemical vapor deposition technique (at room temperature) and patterned into micro-structures by photolithographic techniques, that are commonly used for silicon integrated circuit fabrication. The SWCNTs were obtained using pure methane plasma and iron as precursor material (seed). For the growth carbon SWCNT forest the process pressure was 15 mTorr, the RF power was 250W and the total time of the deposition process was 3 h. The micropatterning processes of the SWCNT forest included conventional photolithography and magnetron sputtering for growing an iron layer (precursor material). In this situation, the iron layer is patterned and high-aligned SWCNTs are grown in the where iron is present, and DLC is formed in the regions where the iron precursor is not present. The results can be proven by Scanning Electronic Microscopy and Raman Spectroscopy. Thus, it is possible to fabricate SWCNT forest-based electronic and optoelectronic devices. (C) 2010 Elsevier B.V. All rights reserved.

Energiapuuta Etelä-Savosta

Energiapuuta Etelä-Savosta hankkeessa tutkittiin ja kehitettiin energiapienpuun mahdollisuuksia osana suurimittakaavaista alueellista hankintaa. Energiapienpuun potentiaali suurimittakaavaisena polttoaineena on lupaava johtuen hyvästä biomassan saatavuudesta ja tarjontahalukkuudesta, korjuun teknologisesta edistyksestä ja logististen ratkaisujen monipuolisuudesta sekä käyttömäärien kasvusta. Hanke kokonaisuus sisälsi seuraavia osatutkimuksia: Etelä-Savon energiatase, metsänomistajakysely, asiantuntijahaastattelu, metsänkasvatussimulointi, metsäpolttoaineiden saatavuuslaskenta, puun kosteuden seurantatutkimus, logistiikan demonstraatioita sekä energiapuun hankintalogistiikan kustannusvertailuja. Hankkeessa käsiteltiin energiapienpuun arvoketjua metsänkasvatuksesta lopputuotteen käyttöön asti. Tutkimuksen tulokset osoittavat, että energiapienpuulla on mahdollisuudet suurimittakaavaisessa hankinnassa, kunhan toimitusketjussa panostetaan tehokkuuden ja laadun jatkuvaan parantamiseen.

Diversification benefits for a Finnish non-industrial private forest investor: Real Estate Investment Trusts in the USA

This thesis examined both domestic and international forest investment options for a Finnish non-industrial private forest investor. The focus was on forest-based investment instruments. The influence of movements of currency exchange rates on foreign returns were also taken into account. Annual data from 1995 to 2011 was used. The main portfolio optimization model in this study was the Mean-Variance model but the results were also validated by using the Value at Risk and Expected Shortfall models. In addition, the exchange rate risk hedging was established by using one-week-maturity forward contracts. The results suggested that 75 % of the total wealth should be invested in Finnish private forests and the rest, 25 %, to a US REIT, in this case Rayonier. With hedging, the total return on the portfolio was 7.21 % (NIPF 5.3%) with the volatility of 6.63 % (NIPF 7.9%). Taxation supported US investments in this case. As a conclusion, a Finnish private forest investor may, as evidenced, benefit in diversifying a portfolio using REITs in the US.