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The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget

The Impacts of and Utilisation of Products on the European Budget

Thies Eggers

European Institute Internal Report 9, 2002 EFI Internal Report 9, 2002 The Impacts of Manufacturing and Utlilisation of Wood Products on the European Carbon Budget

Eggers, Thies

Publisher: European Forest Institute Torikatu 34, FI-80100 Joensuu Tel. + 358 13 252 020 Fax. + 358 13 124 393 Email: [email protected] http://www.efi.fi/

Editor-in-Chief: Risto Päivinen

The views expressed are those of the authors and do not necessarily represent those of the European Forest Institute. This paper has been accepted as a Master‘s Thesis at the of Göttingen, Germany.

© European Forest Institute 2002 Contents

1. ABSTRACT...... 5 1. ZUSAMMENFASSUNG ...... 7

2. INTRODUCTION ...... 9 2.1 IN AND WOOD PRODUCTS ...... 9 2.2 BACKGROUND AND AIM OF THIS STUDY ...... 11 2.3 CONSIDERATION OF CARBON STOCK CHANGES IN WOOD PRODUCTS ...... 11

3. METHODS AND MATERIALS ...... 17 3.1 THE EUROPEAN FOREST INFORMATION SCENARIO MODEL (EFISCEN) ...... 17 3.2 RAW DATA FOR MODEL PARAMETERISATION AND INPUT DATA ...... 18 3.3 THE EFISCEN WOOD PRODUCT MODEL ...... 19 3.4 APPLIED SCENARIOS ...... 34 3.5 ASSUMPTIONS AND UNCERTAINTIES ...... 36

4. RESULTS ...... 39 4.1 CARBON STOCKS IN WOOD PRODUCTS ...... 39 4.2 OF CARBON WITHIN THE WOODEN ...... 46 4.3 CARBON FLOWS IN THE WOOD PRODUCT SECTOR ...... 48 4.4 AVERAGE LIFESPAN OF CARBON IN WOOD PRODUCTS ...... 53 4.5 EU REGULATION ON DISPOSAL ...... 54 4.6 EQUIVALENT OF FOSSIL FUELS FOR ALL BURNED WOOD PRODUCTS ...... 56

5. DISCUSSION AND CONCLUSIONS ...... 61 5.1 EVALUATION OF THE APPLIED APPROACH ...... 61 5.2 VALUATION OF THE COUNTRY RESULTS ...... 62 5.3 OUTLOOK AND CONCLUSIONS ...... 65

6. ACKNOWLEDGEMENTS ...... 67

7. REFERENCES ...... 69

8. APPENDICES ...... 75

1. ABSTRACT

In this study the contribution of wood-based products to absorbing atmospheric carbon (C) is estimated as part of the EU-funded LTEEF-II project “Long-term regional effects of climate change on European forests: impact assessment and consequences for carbon budgets” (ENV4-CT97-0577, DG 12 - EHKN). Based on wood use in the past, carbon stocks in wood products for 1990 are calculated by a wood product model (Karjalainen et al. 1994) which is coupled with the European Forest Information Scenario Model (EFISCEN). In addition to the estimation of the initial carbon stock in wood products, also scenarios of the future development of the carbon stock in wood products are done up to the year 2050. This is based on scenarios on future growth of forest resources, future harvesting levels as well as the usage of wood products.

Beside the modelling, this study focused on data-collection and the data-analysis for those 27 European countries that are included in the LTEEF-II project. The main data source on historic removals (roundwood production) and production (fuelwood, sawn timber, wood-based panels, and pulpwood) is the FAOSTAT products database. Furthermore commodity producer information have been implemented in order to get the model as precise as possible. The future data on removals are taken from the EFISCEN results. In order to get the initial carbon stock for wood products realistic, past wood use, conversion from to final products, use of final products and use of discarded products needs to be precise since in this project it is not possible to do direct inventories on wood product carbon stocks.

In 1990 the IPCC stock-change approach with the exclusion of trade resulted in an European carbon stock in wood products of 769 Tg C, which will increase to 870 Tg C in 2050. This represents 6% of the total forest sector carbon budget in 1990 and 5% in 2050. The carbon stocks and fluxes for 5 sample countries (Austria, Finland, Germany, Norway, and ) and also for Europe in toto are presented as well in more detail. The applied scenarios consider different forest options and a scenario on the EU Council Directive on the landfill of waste. Beside the carbon stocks and carbon fluxes, the possible energy- equivalents of the burned side-products and discarded products are also calculated in means of TWh and tons oil-equivalents.

Finally the results of this study are evaluated with results from other studies, which also deal with carbon sequestration in harvested wood and wood-based products.

Keywords: CO2, modelling, wood products, IPCC stock-change approach, Europe, Austria, Finland, Germany, Norway, Portugal, carbon stocks, carbon fluxes, landfill, energy- equivalents.

1. ZUSAMMENFASSUNG

Im Rahmen des durch die EU geförderten LTEEF-II Projekts „Long-term regional effects of climate change on European forests: impact assessment and consequences for carbon budgets” (ENV4-CT97-0577, DG 12 - EHKN) wurde in dieser Studie der Beitrag von Holzprodukten zur Speicherung von atmosphärischem Kohlenstoff (C) und damit zum globalen Klimaschutz ermittelt. Anhand der Holzverwendung in der Vergangenheit konnte mit Hilfe eines Holzprodukt-Modells (Karjalainen et al. 1994), welches mit einem Waldwachstums-Modell (European Forest Information Scenario Model; EFISCEN) kombiniert ist, die Menge an gespeichertem Kohlenstoff in Holzprodukten für 1990 ermittelt werden. Zusätzlich zu dieser Vorratsschätzung wurden mit Hilfe von Szenarien die Entwicklung der C-Vorräte in Holzprodukten bis zum Jahr 2050 berechnet. Dieses geschah mit Waldwachstumsszenarien und Prognosen zu zukünftigen Holzeinschlagsmengen und der Verwendung von Holzprodukten.

Diese Studie hat sich neben der Modellierung hauptsächlich mit Datenbeschaffung und der Datenanalyse für die 27 im LTEEF-II Projekt eingebundenen europäischen Länder befasst. Hauptdatenquelle bezüglich der Produktion von Rundholz und den unterschiedlichen Holzprodukten (Brennholz, Schnittholz, Holzwerkstoffe und Zellstoff/Papier) war die statistische Datenbank der FAO zu forstlichen Produkten (FAOSTAT forestry products database). Zusätzlich konnte auf Informationen von der holzverarbeitenden Industrie zurückgegriffen werden, die die Modellierung präzisieren konnten. Die Produktionsdaten für Rundholz nach 1990 wurde durch das EFISCEN modelliert. Um den anfänglichen Kohlenstoffvorrat möglichst genau ermitteln zu können, mussten neben der bisherigen Holzverwendung auch die Produktionsprozesse, die Verwendung der Holzprodukte und die endgültige Bestimmung (Wiederverwertung, Deponierung oder Verbrennung) möglichst exakt parametrisiert werden, da es bisher nicht möglich ist, auf Inventurergebnisse von Holzprodukt-Vorräten zurückzugreifen.

Zur Bestimmung der Kohlenstoffvorräte und -flüsse wurde der “IPCC stock-change”-Ansatz verwendet. Für 1990 ergab sich somit für Europa ein Vorrat von 769 Tg C, der bis 2050 auf 870 Tg C ansteigen wird. Diese Menge entspricht ca. 6 % des 1990 im gesamten Forstsektor (Wälder, Waldböden und Holzprodukte) gebundenen Kohlenstoffs; im Jahr 2050 sind es ca. 5 %. Neben Ergebnissen für Europa insgesamt werden die Kohlenstoffvorräte und -flüsse auch für 5 europäische Länder (Österreich, Finnland, Deutschland, Norwegen und Portugal) dargestellt. Die verwendeten Szenarien beziehen sich auf unterschiedliche Waldbewirtschaftungskonzepte, und ein Szenario implementiert die EU-Richtlinie über Abfalldeponien. Zusätzlich werden neben den Vorräten und Flüssen auch mögliche Energieäquivalente der verbrannten Nebenprodukte und Holzabfälle in Form von TWh und Öläquivalenten angegeben.

Im letzten Kapitel werden die Ergebnisse dieser Studie mit Ergebnissen vergleichbarer Studien, die sich ebenfalls mit der Funktion von Holzprodukten in der Kohlenstoffspeicherung befasst haben, bewertet.

Stichwörter: CO2, Modellierung, Holzprodukte, IPCC stock-change approach, Europa, Österreich, Finnland, Deutschland, Norwegen, Portugal, Kohlenstoffvorräte, Kohlenstoffflüsse, Deponien, Energieäquivalente

2. INTRODUCTION

2.1 CARBON SEQUESTRATION IN FORESTS AND WOOD PRODUCTS

Plants absorb carbon (C) in the form of (CO2) from the atmosphere. With the energy from the sun this carbon is transformed to carbohydrates (e.g. sugars, and ) in the -process (gross primary production, GPP). These carbohydrates are partly re-used for respiration-processes (growth and maintenance respiration), but a majority is used for the growth of the plant (trunk, roots, branches, leafs / needles). Only a rather small part of the net-primary production (NPP, NPP = GPP – respiration) remains over a longer period in the plant because most of the NPP is translocated again by the litterfall. Due to the forest growth, can continue to sequester carbon from years to centuries. Forests are thus a very effective land use type in the context of carbon fixation because a large amount of carbon is withdrawn from the atmosphere for a long time, if the forest ecosystem is not disturbed by natural or human-induced processes, such as forest fires or harvesting activities.

In the last decade, many efforts towards mitigation of greenhouse gases and climate change also influenced research in the forest sector. Forest, as being the world’s largest terrestrial biome (4.1·109 ha, which equals about 28% of the land surface), represent an enormous potential for stabilising, and potentially decreasing, the concentration of carbon dioxide in the atmosphere if carbon stocks in the forests could be increased. The forest-vegetation contains about 86% (483 Pg C; 1 Pg = 1015 g = 109 t = 1 Gt) of the global above ground terrestrial carbon and also roughly 40% of all below-ground terrestrial carbon is stored in forests soils (Sedjo 1992, Dixon et al. 1994). With their lifespan of some decades in up to several centuries in mature forests, they form a sink or equilibrium of carbon if they are not disturbed. Dixon et al. (1994) show on the one hand that the in low latitudes is a substantial source of carbon, in 1990 it was estimated that 1.6 ± 0.4 Pg C·yr-1 were emitted from the low latitude forests. But on the other hand the forests in the middle and high latitudes are enlarging and increasing and thus, under certain circumstances, they form a potentially carbon sink (in 1990 0.7 ± 0.2 Pg C·yr-1 were sequestered in the middle and high latitude forests), which shows that forests do impact the dynamics of the terrestrial carbon cycle in both ways. There was a slight carbon source of 0.9 ± 0.4 Pg C·yr-1 from forests world-wide in 1990. In comparison, recent studies (IPCC 2000) show that of fossil fuels are a source of 6.3 ± 0.6 Pg C·yr-1 and land-use change from 1989 to 1998 of 1.6 ± 0.8 Pg C·yr-1. Global oceans are estimated to absorb 2.3 ± 0.8 Pg C·yr-1, and the accumulation in the atmosphere is about 3.3 ± 0.2Pg C·yr-1.

Studies like Dixon et al. (1994) and Winjum et al. (1998) provide large-scale accounts of the global carbon cycle. These studies and that by Houghton (1998), giving an overview of the pre-industrial global carbon cycle, give important background information for more focused studies on the multiple issues of forests in climate change mitigation. More detailed, country level reports of the forest sector have been provided by Row and Phelps (1990) for the United States of America, Kurz et al. (1992) for Canada, and Harmon et al. (1996) for the U.S. states of and .

In Europe, studies have been carried out by, inter alia, Burschel et al. (1993) for Germany, Böswald (1996) for Bavaria, Dewar and Cannell (1992) for plantations in the U.K., Gjesdal 10 Thies Eggers et al. (1996, 1998) and Flugsrud et al. (1998) for Norway, and Karjalainen et al. (1994) for Finland. Jäkel et al. (1999) included Austria, Finland, Germany, and Portugal in the biosphere part of the European Study of Carbon in the Ocean, Biosphere and Atmosphere (ESCOBA). Obersteiner (1999) published a report on the carbon budget of the forest of the Russian Federation. Liski et al. (2000) estimated the function of trees as sinks or sources of carbon in the European Union.

After the harvest of wood, forest products also continue to store C for a certain time. Thus forests provide at the same time a store of carbon and as well new raw material for industrial purposes. After a certain period of time both, forests and wood products, will release C back to the atmosphere through decay of litter and organic material in the soil, emissions from production processes, and the decay of wood-based products. The general conclusion on wood products and their importance for the mitigation of climate change is that wood products have a small, but nevertheless an important role in sequestering carbon. Research on this topic is still young and all researchers state that there are great uncertainties in particular in the lifespans and usage of wood taken from the forests.

The role of forestry in mitigation of climate change may have several aspects. The most direct impacts might be different management strategies in the managed forests because they are responsible for the treatment of forest stands. Other impacts might be in the further chain of custody, meaning the further use and processing of the harvested wood. Management strategies include:

• Conservation management: The role of this management strategy is to prevent emissions into the atmosphere by conserving existing carbon pools in the forests. This can be achieved by a slow-down of ongoing deforestation, by the establishment of new forest reserves, where harvesting activities are restricted, and by possible changes in thinning intensity and the rotation length. Beside of this an improved technique in controlling fires and pests damages can result in larger carbon stocks in forest ecosystems. The global potentials of these strategies are large.

• Storage management: This means an increase of the amount of carbon in vegetation and soil by increasing the forest area and / or the carbon density in natural or forests. As a result of higher harvest levels, an increase of the carbon storage in wood products can be obtained. By , , as well as changes in thinning intensity and rotation length a higher pool of carbon can be reached. An extended lifespan for wood products by higher rates also is possible. The potential of these management strategies varies regionally due to the local circumstanc- es. The effect will be possible on the short-term.

• Substitution management: As a long term solution for using forests, activities, and wood products in acting against climate change, the transfer of wood into products (, furnishing, etc.) and the substitution on based energy production must be favoured and thus increased. The global potentials are large and this usage of wood and wood products is a very sustainable solution in the long run. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 11

2.2 BACKGROUND AND AIM OF THIS STUDY

2.2.1 Background

The “Long-term regional effects of climate change on European forests: impact assessment and consequences for carbon budgets” (LTEEF-II) project comprises the second phase of a major research effort undertaken as part of the European Union (EU) Environment and Climate research program under the 4th framework program of the European Commission. During the first phase of LTEEF (1994–1997), existing forest models were extended and applied to conditions representative of a range of sites throughout Europe under present-day and future climate scenarios. In that part of the project, the emphasis had been on development of process-based models and their comparison. In the recently finished second phase of the LTEEF project, LTEEF-II (1998–2000), model performance was evaluated on the basis of applications to the EUROFLUX sites (eddy-covariance flux measurements). In addition, models were evaluated against long-term growth and yield data from permanent plots as used in traditional growth and yield research. Based on these results, regional impact studies have been carried out to assess potential climate change impacts of forest ecosystems throughout Europe. With process-based models, different strategies of forest management under changing climatic conditions have been studied. The regional impact assessments are scaled up to European level using i) national data and information from process-based models in large-scale modelling and ii) remote sensing techniques. The LTEEF-II project has produced estimates of the current carbon balance for the forest sector, as well as assessments of timber production and forest carbon budgets per country under future climate scenarios and under selected forest management scenarios (Karjalainen et al. 2001).

2.2.2 Aim of this study

This study estimates the contribution of wood-based products in absorbing atmospheric carbon on a European scale as part of the LTEEF-II project. The focus is on data-collection, data-analysis, model-parameterisation, and model-application for those European countries that are included in the LTEEF-II project (Figure 2.1). The aim is to estimate the carbon stock of wood products in Europe and in more detail for Austria, Finland, Germany, Norway and Portugal from 1990 to 2050. The sample countries were chosen because recent studies had also assessed the pool of carbon in wood products and so comparable data are available to evaluate the results more carefully. In this study Europe means those countries included in the LTEEF-II study (Figure 2.1). The carbon accounting was dealt according to other studies. We used the so called ‘stock-change approach with exclusion of trade’ (see chapter 2.323), where the approach only takes into account when, but not where stock changes occur, e.g. when wood is exported to another country.

2.3 CONSIDERATION OF CARBON STOCK CHANGES IN WOOD PRODUCTS

2.3.1 Background

During the last decades a general focus on climate related research was put on climate change scenarios due to increasing greenhouse gas concentrations in the atmosphere and especially on the increasing concentrations of carbon dioxide. In order to get an 12 Thies Eggers international agreement and strategy on the changing environment the Intergovernmental Negotiating Committee (INC) met for the first time in February 1991. Nearly one year later, in May 1992, the INC adopted by consensus the United Nations Framework Convention on Climate Change (UNFCCC). The Climate Convention (UN 1992) was opened for signature at the UN Conference on Environment and Development (UNCED), the so-called “Earth Summit”, in Rio de Janeiro, Brazil, in June 1992, and came into force in March 1994. Today, 181 governments and the European are parties to the Convention. It is the first global step towards the mitigation of climate change and an ultimate joint objective of both, developed and developing countries to against increasing greenhouse gas concentrations in the atmosphere. Signatories to the UNFCCC have to provide inventories on greenhouse gas emissions and removals. The Intergovernmental Panel on Climate Change (IPCC) has provided guidelines for these inventories. The Kyoto Protocol, which was agreed in November 1997 is the first international agreement that set quantified targets for emission reductions for the industrialised countries.

SWE FIN NOR

DNK IRL GBR NLD BEL DEU POL

LUX CZE SVK FRA CHE AUT HUN SVN ROM ITA HRV PRT BIH YUG ESP BGR MKD ALB GRC TUR

LTEEF-countries included in this study

LTEEF-countries not included in this study

Non-LTEEF-countries

Figure 2.1. Overview on the LTEEF countries according to their consideration in this study. Countries included: Albania (ALB), Austria (AUT), Belgium (BEL), Bulgaria (BGR), Croatia (HRV), Czech Republic (CZE), Denmark (DEN), Finland (FIN), France (FRA), Germany (DEU), Hungary (HUN), Ireland (IRL), Italy (ITA), Luxembourg (LUX), The Frm. Yug. Rep. of Macedonia (MAC), Netherlands (NLD), Norway (NOR), (POL), Portugal (PRT), Romania (ROM), Slovak Republic (SVK), Slovenia (SVN), Spain (ESP), Sweden (SWE), Switzerland (CHE), United Kingdom (GBR) and Yugoslavia (YUG). The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 13

2.3.2 Guidelines for greenhouse gas inventories

The IPCC has prepared guidelines for inventorying the greenhouse gas emissions and removals. The ‘Revised 1996 Guidelines for National Greenhouse Gas Inventories’ (IPCC 1997a, b) are meant to help the countries under the UNFCCC to report their national greenhouse gas inventories for following categories: energy, , solvent and other product use, , land-use change and forestry, waste, and other. Land-use change and forestry is further divided into changes in forest and other woody biomass stocks, forest and grassland conversion, abandonment of managed lands, CO2 emissions and removals from soils, and other.

Wood products are dealt in the IPCC guidelines in the chapter of ‘land-use change and forestry’ (LUCF) mainly under the aspect of , which has the most direct impact on the carbon balance because of its short lifespan. Changes in forests and other woody biomass stocks, define the annual harvest from stocks as the total fuelwood demand minus the quantity of fuelwood from cleared forests plus the commercial and other non-fuel harvests (IPCC 1997b). The ‘Greenhouse Gas Inventory Reference Manual’ (IPCC 1997a) gets a little more in detail, how wood products should be accounted.

The flux of carbon into or from the atmosphere is assumed to be equal to changes in carbon stocks in existing biomass (living and dead) and soils. The above already mentioned ‘changes in forests and other woody biomass stocks’ are considered to be a single broad category, which includes commercial management, harvest of industrial roundwood and fuelwood, production and use of wood commodities, and establishment and operation of forest plantations as well as planting trees in urban, village and other non-forest locations. The harvested wood releases its carbon at rates dependent upon its method of processing and its end-use. Wooden waste and fuelwood are usually burned immediately or within a couple of years in case of paper products, paper decays in up to 5 years (although landfilling of paper can result in long-term carbon storage), and timber decays in up to decades.

Because of the latter fact, forest harvest could result in a net uptake of carbon if the harvested wood is used for long-term products such as timber, and the regrowth is relatively rapid. It gets a significant importance if this may become a response strategy. But it is critical if the carbon-inputs to forest and wood products remain under the output from those pools. In May 1998 the IPCC held a special meeting in Dakar, Senegal, where experts reviewed and evaluated three approaches for accounting for carbon from forest harvesting and wood products (Brown et al. 1998), which are just touched in the LUCF section of the IPCC guidelines. The outcome of this meeting were 3 different accounting methods, of which one should be applied for the reporting under the Convention. They are the atmospheric-flow approach, the stock-change approach and the stock-change approach with exclusion of trade, where differences occur due to changing system boundaries in these approaches. In the atmospheric-flow approach the flow of carbon in-between atmosphere and biosphere is calculated within national boundaries where and when it occurs. This is different in the stock-change approaches where net carbon changes are tracked in the forest and wood product pools.

These approaches, which should be used beside the default IPCC approach, are described and evaluated in Lim et al. (1999) and they had been already used among others by Jäkel et al. (1999) in the ESCOBA study. As already mentioned they differ in the way where and when the carbon is accounted for a certain country. From the technical point of view, the 14 Thies Eggers differences among the approaches are not large globally. They all will generate the same net carbon exchange with the atmosphere, but at the national level, however, they differ as described in the following. In general the accounting differences may influence domestic activities for conservation of carbon stocks and of , for the use of traded wood products and fuels, and for waste minimisation strategies.

2.3.2.1 The atmospheric-flow approach

In the atmospheric-flow approach the boundary is in-between the country or a specific region and the atmosphere showing the carbon flow between the biosphere and the atmosphere. Exported wood products are accounted for the country where they decay or are incinerated, whereas the uptake of carbon from forest growth is accounted to the producing country/region (Winjum et al. 1998). So any carbon flows to the atmosphere from the oxidation or combustion of imported products are accounted for the inventory of the importing country/region. If the wood is domestically produced and consumed, both flows to and from the atmosphere are accounted for in the same country.

Atmospheric flow = forest growth – slash – decomposition or combustion of wood consumed

Atmosphere Forest Decomposition/combustion growth Slash of wood consumed

Export

Wood

production Import

National boundary System boundary

Figure 2.2. Outline of the IPCC Atmospheric Flow Approach (Lim et al. 1999)

2.3.2.2 The stock-change approach

Net changes of the wood product and forest carbon stock are estimated in the stock- change approach within the national boundaries (Figure 2.3). Also this has been described in Winjum et al. (1998) and means that stock changes for the forests are reckoned for the producing country, whereas changes in the wood product pool are accounted for the consuming country. So any traded carbon stocks are transferred from one country’s inventory to another.

Stock change = (stock change forests) – (stock change consumed wood products) – (forest growth – slash – ) + (wood consumed – decomposition or combustion of wood consumed) The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 15

Atmosphere Forest Decomposition/combustion growth Slash of wood consumed

Export

Wood

production Import

National boundary System boundary

Figure 2.3. Outline of the IPCC Stock-Change Approach (Lim et al. 1999)

2.3.2.3 The stock-change approach with exclusion of trade

In this approach changes of carbon stock in the forests and in the wood product pool are estimated (Figure 2.4). For the producing country stock changes in the forests are accounted as well as the stock changes for exported wood products remain accounted for the producing country. The stock-change approach with exclusion of trade estimates changes in the forest and wood products stock by counting them in the country where the wood is grown or the product is produced. When wood is exported to another country this approach takes only into account when, but not where stock changes occur. Any carbon stock that crosses a national boundary is not transferred from the producing country’s inventory to the consuming country’s inventory. The exported carbon stocks remain in the inventory of the exporting country. The producing country is the country where the wood is grown and the consuming country is the country where the wood product is used. The producing and consuming countries can often be the same but with the trade of industrial roundwood and wood products the stock of wood within a country will vary due to the natural resources of that country. In the mentioned publications of Brown et al. (1998) and Lim et al. (1999) this approach is called ‘production approach’, which is a little misleading and results from a misunderstanding during the meeting in Dakar (Karjalainen 2001).

Stock change = (stock change forests) – (stock change domestic grown wood products) = (forest growth – slash – wood production) + (wood production – decomposition or combustion of wood grown in the country)

2.3.3 Kyoto Protocol

For the implementation of the Climate Convention, the Kyoto Protocol is the first tool. The Kyoto Protocol to the UNFCCC (UN 1997) commits its parties to individual, legally- binding targets to limit or reduce their greenhouse gas emissions, adding up to a total cut of at least 5% from 1990 levels in the first commitment period 2008– 2012. The individual targets for the parties are listed in the Protocol’s Annex B, and range from an 8% cut for the EU and several other countries, to e.g. a 10% increase for Iceland. Under the terms of the 16 Thies Eggers

Protocol, the EU has redistributed its target among its 15 member states and it has already reached agreement on such a scheme. But it is also important to mention that the countries listed in Annex B are just industrialised countries and for the developing countries there are no targets set by now. The targets of the Kyoto Protocol cover emissions of the six greenhouse gases (Kyoto Protocol, Annex A): carbon dioxide (CO2), (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulphur hexafluoride (SF6).

Some specified activities in the land-use change and forestry sector (afforestation, reforestation and deforestation) that emit or remove carbon dioxide into or from the atmosphere are also covered. To clarify the very theoretical formulations of the Protocol the IPCC has worked out a special report (IPCC 2000) on ‘Land Use, Land-Use Change, and Forestry’ (LULUCF) activities. For wood products it is not clear under which Article of the Protocol they should be counted among. Either under Article 3.3 (direct human-induced land-use change and forestry activities) and / or under Article 3.4 (additional human-induced activities). Changes in carbon stocks in wood products could potentially be accounted as part of the activity, which is the source of the wood products, or as an independent wood products management activity. If the management of wood products is treated as an additional activity under Article 3.4, then it may be necessary to exclude wood products from accounting under other Article 3.3 or other 3.4 activities in order to avoid double counting. Once wood products are in trade, they would be difficult to trace in most instances. The current IPCC default approach assumes that the wood product pool remains constant over time, and therefore does not account for the approach. However, if the pool of wood products is changing significantly over time, a potentially important pool may be ignored. That is one reason why the already mentioned accounting approaches (see Chapter 2.3.2) were developed. In general the Kyoto Protocol states a potential for carbon uptake into biomass, which may be stored over a time period of decades in wood products. Furthermore, biomass used for energy purposes, based on waste by-products of wood or trees grown specifically for this purpose, has the potential to lead to a reduction in net greenhouse gas emissions by substituting for fossil fuels.

Atmosphere Forest Decomposition/combustion growth Slash of wood grown in country

Export

Wood

production Import

National boundary System boundary

Figure 2.4. Outline of the IPCC Stock-Change Approach with Exclusion of Trade (Lim et al. 1999) 3. METHODS AND MATERIALS

This study combines historical data on removals, simulated future harvesting levels and wood utilisation parameters. The historical data are derived from the database of the Food and Agricultural Organisation of the United Nations (FAO). The simulated data are generated with the European Forest Information Scenario model (EFISCEN). These data sources are combined and used for the parameterisation and input of a modified wood product model, which has been developed and used by Karjalainen et al. (1994) modelling the carbon budget of the Finnish forest sector. Due to the structures in the model and available data, the impact of the trade of industrial roundwood and wood products could not be implemented directly in the output. According to the IPCC ‘stock-change approach with exclusion of trade’, the re- sults represent changes in the forest and wood products stock by country, meaning for the country where the wood is grown or the product is produced.

This chapter covers the wide field of the used data sources, developed parameters, and imple- mented assumptions. Chapter 3.1 describes briefly the European Forest Information Scenario model (EFISCEN) and its scheme, strategy, and results. As the applied wood product model was developed as a co-model for the EFISCEN forest model and uses EFISCEN results on harvest levels as data input it was seen necessary to include a more detailed description of this model in the Appendices (Chapter 8.1, see also Pussinen et al. 2001).

The FAO raw-data, which were used for the parameterisation and initialisation are discussed briefly in Chapter 3.2, while Chapter 3.3 contains the information on the used wood product model. It describes how the wood product model was parameterised and how the model cal- culates the carbon in wood products.

The used scenarios for the future prediction of the carbon stocks in wood products are de- scribed in Chapter 3.4. The impacts of two EFISCEN scenarios on different forest manage- ment regimes and one scenario which influences the treatment of discarded wood products are analysed. Finally, Chapter 3.5 lists the most important assumptions and known uncertain- ties for the model in general and the focused countries.

3.1 THE EUROPEAN FOREST INFORMATION SCENARIO MODEL (EFISCEN)

The amount of carbon in the wood product model after 1990 was calculated with EFISCEN. This matrix-based model uses specific forest information of the analysed countries to predict forest growth and harvests. This information is based on the Forest Resource Database at the European Forest Institute (Nabuurs 1996, Nabuurs and Päivinen 1996). The original model was developed in the 1980s by Sallnäs (1990) and has been used in large-scale studies for Europe (Nilsson et al. 1992). Further developed, it was used at EFI for the analysis of the European forest resources (Päivinen and Nabuurs 1997, Nabuurs et al. 1998, Päivinen et al. 1999) and is in its current form known as EFISCEN (Pussinen et al. 2001).

The output of the EFISCEN model and thus the input to the wood product model is harvested roundwood in terms of coniferous and non-coniferous timber for each country. The model takes forest management strategies into account and is also capable of simulating the influ- ence of climate change on forest growth. For the purposes of this study, EFISCEN inputs from 18 Thies Eggers model runs excluding climate change were used. There is little difference between them and the ones implementing climate change as EFISCEN uses given harvesting levels, i.e. a fixed harvest level is applied. The main difference between these two types of scenarios is that the growing stock and the increment are higher when climate change is included as a variable.

3.2 RAW DATA FOR MODEL PARAMETERISATION AND INPUT DATA

The data on historical removals (roundwood production) and commodity production (fuelwood, sawn timber, wood-based panels, and pulpwood) used as the input for calculating the country specific parameters has been derived from the Food and Agricultural Organisation’s statistical database (FAOSTAT) on forestry (FAO 2000a), which is also recommended by IPCC (IPCC 1997b). Commodity producer supplied additional data on production efficiency of the re- garded products. In order to make the initial carbon stock for wood products in 1990 as real- istic as possible, several factors were taken into account. Past wood use, conversion from raw material to final products, use of final products, and use of discarded products needed to be precise since in this project it is not possible to fall back on direct inventories on wood prod- uct carbon stocks.

The parameterisation has been done on country or region level, depending on the availability of initial data. Regions (Figure 3.1) have been adopted from Kuusela’s classification used in his study on European forest resources (Kuusela 1994). For the scenario on wood products the same regions were chosen because their -species composition and timber assortments are assumed to be similar. The broadest database for this large-scale project would have been

Northern

Atlantic

Central

Sub-Atlantic Alpic Pannonic

Mediterranean West Mediterranean Mediterranean East Middle

Figure 3.1. Regions for parameterisation used in this study. These regions are the same as in Kuusela (1994). The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 19 either the EUROSTAT forest statistics (EU 1998) or the data from FAOSTAT, which is avail- able both in printed format (FAO 1996, 2000b) and on the (FAO 2000a). Since EUROSTAT statistics cover only the EU countries, data from FAOSTAT (wood and paper databases) have been used although it is known that FAO includes older data if recent data are not available. The most updated source to gather the needed data is the interactive web data- base of FAO (2000a), which can be found on the Food and Agricultural Organisation’s (http://apps.fao.org/page/collections?subset=forestry).

The quality of commodity data in the FAO database is generally sufficient for this kind of approach (Brown et al. 1998). FAO collects the data from countries through questionnaires. Typically, countries collect the commodity data using standard collection procedures speci- fied under trade agreements. FAO also compares the national data with the COMTRADE statistics as consistency check. The United Nations Statistical Division (UNSTAT) COMTRADE statistics on wood products (UN 1999) have been introduced and analysed by Michie and Wardle (1998). The error in the data is about ±10–15% for member countries of the Organisation for Economic Co-operation and Development (OECD) and ±50% for non- OECD countries (rough estimation by Michie 2000). Roundwood production data are less reliable than trade statistics as there are no independent checks. For example, when a country exports wood products, the production figure will be raised to the export level although there is no import and less production of the commodity. It is also recognised that the FAOSTAT figures on fuelwood are uncertain due to informally gathered data (Brown et al. 1998). The scale of these discrepancies varies from country to country also depending on the unrecorded removals of fuelwood from the forests.

FAO forest products database has also been used in antecedent studies (e.g. Winjum et al. 1998). They describe the FAOSTAT database as an internationally recognised source of data but mention that several conversion factors are required to express harvested wood in terms of dry mass before oxidation because the FAO database reports most quantities in volume units. These conversions are explained in the Chapter 3.3.

3.3 THE EFISCEN WOOD PRODUCT MODEL

In this study, the contribution of wood-based products in absorbing atmospheric carbon is estimated for the European countries covered in the LTEEF studies. Based on past wood use, carbon stocks in wood products for 1990 are estimated with an existing wood product model (Karjalainen et al. 1994), which has been slightly modified to serve the demands of this study (EFISCEN wood product model). In addition to the estimation of the initial carbon stock in wood products in 1990, scenarios of the future development of the carbon stock in wood products are run up to the year 2050. These are based on scenarios of future harvesting levels, forest management regimes, and variation in the wood product end-use options.

3.3.1 Initial carbon stock

The initial carbon stock for 1990 was calculated by using input data from FAOSTAT on indus- trial roundwood–wood in the rough (IRW-WIR) production, which is equal to removals under bark (u.b.) for coniferous (con.), non-coniferous (non-con.) and aggregated timber. FAO pro- 20 Thies Eggers vides time series for IRW-WIR starting in 1961. This study uses FAO data for 30 years ending in 1990, but to get a more realistic initial carbon stock, the values for 1961 have been re-used for the period 1931–1960, simulating a model start in 1931.

The given figures by FAO are, according to the FAO definition (see Appendices), removals u.b. and thus a bark fraction had to be added. As in Haygreen and Bowyer (1989), we used a common bark fraction of 11% for coniferous and 13% for non-coniferous tree species in all countries. Thus the conversion figure of coniferous wood for removals u.b. to removals over bark (removals o.b.) is 1.1236 and for non-coniferous removals u.b. to removals o.b. is 1.1494. Since input data from EFISCEN forest model to the EFISCEN wood product model are re- movals o.b. there is no backward conversion of this kind after the year 1990.

A conversion factor from removals o.b. to fellings was calculated in order to assume the total amount of fellings in the forests. Two main references for conversion were used. First the countries were divided in the same country groups (Figure 3.1), which Kuusela used in his

Table 3.1. residues in percent of fellings and calculated conversion figures; according to UN/ECE 1992, The Forest Resources of the Temperate Zones, The Forest Resource Assessment 1990.

Country group Logging residues in % of fellings Conversion figures from removals o.b. to fellings Coniferous Non-coniferous Coniferous Non-coniferous

Northern 4.6 18.1 1.0481 1.2206 Central 3.3 4.3 1.0342 1.0453 Atlantic 10.0 10.2 1.1109 1.1133 Sub-Atlantic 9.1 16.8 1.1006 1.2013 Alpic 4.8 7.6 1.0509 1.0817 Pannonic 4.5 4.9 1.0469 1.0515 Mediterranean West 1.0 3.1 1.0103 1.0316 Mediterranean Middle 13.3 11.4 1.1538 1.1286 Mediterranean East 15.2 15.3 1.1795 1.1802

Table 3.2. Comparison of data on logging residues of stemwood for European country groups: UN/ECE (1992) with Kuusela (1994).

Logging residues in percent (%) of fellings, aggregated figures (coniferous and non-coniferous)

Country group UN/ECE (1992) Kuusela (1994)

Northern 7.1 7.3 Central 3.6 2.1 Atlantic 10.0 8.4 Sub-Atlantic 13.1 9.1 Alpic 5.4 5.4 Pannonic 4.8 5.0 Mediterranean West 1.9 1.8 Mediterranean Middle 11.9 10.9 Mediterranean East 15.2 16.3 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 21 study (1994), and then UN/ECE (1992) data, which provided specific data for at least one country in each country group, was applied. Next, the conversion figures for removals o.b. to fellings could be calculated. These figures show parallels to figures that have been published by Kuusela (1994) on regional level. The Table 3.1 shows the used conversion figures and percentages of logging residues for each country group (a listing of LTEEF-II project coun- tries and their regions can be found in Table 8.1 in the Appendices; also see Figure 3.1).

Table 3.1 shows both realistic and vague figures. This is due to the available input data that have been used for calculations in this approach, for example, for the Sub-Atlantic region, the only data source is Luxembourg 1987. But this is the only available data source for a compa- rable approach in itself to estimate the current fellings of coniferous and non-coniferous tree species in Europe. Compared with Kuusela (1994), the aggregated amounts for logging residues of fellings show the relations presented in Table 3.2.

3.3.2 Carbon in Harvested Timber

The wood volume, which is divided to coniferous and non-coniferous wood, is converted into dry weight and organic carbon (C) as in Karjalainen and Kellomäki (1991, 1993). The calcu- lations were done for each country using the following variables and formulas:

= ⋅ (3.1) MASSi DWD i V

Where MASSi = the dry mass of stemwood [Mg], V = the volume of stemwood [m3], -3 DWDi = the density of wood [Mg·m ] and I = the wood species (coniferous or non-coniferous).

= ⋅ CMASSi CC i MASS i (3.2)

Where CMASSi =the carbon mass [kg],

CCi =the fraction of C. (In this study a constant of 0.5)

In this case, a common carbon fraction of the organic dry matter of 0.5 was assumed. The wood densities (Table 3.3) for the countries have been calculated by dividing tree biomass by its volume. Both biomass and volume are from UN/ECE (1992), for those countries with no available data, wood densities from neighbouring countries within the same region were used.

3.3.3 Development of carbon stocks and fluxes in wood products

Future carbon calculation for wood products is based on a model which uses EFISCEN roundwood figures as input. The model (Figures 3.2 and 3.4) traces the way of carbon by processing harvested timber into products and follows them until these products are removed from use and the bound C is again released into the atmosphere. The output of the model indicates the total amount of carbon in products in use and in annually taking also into account the recycling of products and the emissions of carbon into the atmosphere from burning or decay in landfill. Carbon emissions from timber harvest and logging activities or fossil fuel burning during the production process were not taken into account, as their magni- tude is small if compared with forest growth or forest net sinks (Karjalainen and Asikainen 1996). 22 Thies Eggers

Book-keeping of annual flux of C for the produced products (PP) was calculated as in Karjalainen et al. (1994):

= + − (3.3) PPt TH t RPt −1 EBt

where PPt = the carbon in produced products,

THt = the carbon in harvested timber at the beginning of the time period,

RPt-1 = the carbon in recycled products from the last time period,

EBt = the carbon, which is released when by-products are burned to gener ate energy and t = the time [year].

Products are removed from use repeatedly and thus this has to be taken into account. C flux for the products in use (PU) is = − − − PU t PPt RPt EPt LDt (3.4a)

= − − − (3.4b) PU t TH t EBt EPt LDt

where PUt = the carbon in produced in use,

RPt = the carbon in recycled products,

EPt = the carbon, which is released when discarded products are burned to generate energy and

LDt = the carbon in products, which are disposed into landfills.

The carbon flux for the products in landfills (LSt) is calculated as = − LS t LDt LRt (3.5)

where LSt = the yearly carbon flux, which goes into landfills and

LRt = the carbon, which is released into the atmosphere from landfills as a constant decay of the C storage in landfills.

The size of the total wood product carbon storage (WP) has been calculated by adding annual fluxes of the two storage (PU and LS) together

n n n = + ∑∑WPt PU t ∑LSt (3.6) t ==00t t = 0 where n = the time horizon [years].

The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 23

(immediate release of C) of release (immediate (delayed release of C) of release (delayed

recycling wood burning wood disposal to landfill to disposal he terminal use. terminal use use fuelwood furnishing packing materials structural support materials building materials short life other building materials long-life paperproducts direct re-use products sawn timber particleboards chemical mechanical pulp / veneer side-products

EFISCEN forest model EFISCEN soil model logging residues production processes production fellings removals o.b. raw material & production Detailed schematic outline of the EFISCEN wood product model showing the flow of carbon through different products and use to t Detailed schematic outline of the EFISCEN wood product model showing flow carbon through different Figure 3.2. Figure 24 Thies Eggers

Table 3.3. Average wood-densities for coniferous and non-coniferous timbers in Europe according to UN/ ECE 1990 Forest Resource Assessment (UN/ECE 1992).

Mean wood-densities [Mg·m-3]

Coniferous timber Non-coniferous timber

Austria 0.41 0.51 Belgium 0.42 0.53 Denmark 0.40 0.57 Finland 0.40 0.48 France 0.44 0.57 Germany 0.41 0.54 Greece 0.40 0.54 Ireland 0.35 0.37 Italy 0.40 0.55 Netherlands 0.40 0.55 Norway 0.41 0.52 Portugal 0.39 0.55 Spain 0.42 0.54 Sweden 0.39 0.42 Switzerland 0.41 0.45 United Kingdom 0.38 0.54

3.3.4 Regarded commodities

In this study, the harvested timber was divided into coniferous and non-coniferous timber for all production lines regarding different wood densities and thus carbon amounts in both cat- egories. Timber is used in six production lines, which are generated according to FAOSTAT definitions (see Appendices): • fuelwood, • wood for chemical pulp (aggregating chemical and production), • wood for mechanical pulp (aggregating mechanical and semi-chemical pulp production), • sawn timber and other industrial roundwood, • plywood and veneer, and • particle board and fibreboard.

The group of ‘other industrial roundwood’ is an aggregated category with a wide variety of commodities (e.g. , music instruments, pit props, etc.). It is added as a compromise to sawn timber because of its uncertain and diverse use later on.

The conversion of timber into the different products mentioned above is based on the amount of timber needed to produce a particular product. These values of the conversion efficiencies (see Chapter 3.3.7.2) are those typical of the current wood-processing industry and given now on supra-regional level (see Chapter 3.3.7). This way the model follows the carbon through the manufacturing and consumption until the products are finally discarded and the stored carbon is released back into the atmosphere. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 25

The above mentioned products are later divided into seven use categories (Table 3.4) with four different lifespan options to separate the different usage of wood products and their pos- sible later re-use. At the end of their primary use, products can be either recycled, or burned for energy production or disposed to landfills as waste. In landfills, the wooden waste decom- poses slowly, releasing carbon into the atmosphere.

Table 3.4. Use categories of the EFISCEN wood product model and commodities included to those.

Use category Included commodities

Building materials Products made of sawn timber, plywood / veneer, or (lifespan of 50 years) particleboard used for construction work in , civil and other long-life construction work; e.g. wooden houses or . Other building material Products made of sawn timber, plywood / veneer, or (lifespan of 16 years) particleboard used for maintaining in houses or . Includes also such commodities as fences, frames, panels, wooden floors and . Structural support materials Products made of sawn timber, plywood / veneer, or (lifespan of 1 year) particleboard used for form works, scaffolds, and other wood- based products needed on building sites. Furnishing Products made of sawn timber, plywood / veneer, or (lifespan of 16 years) particleboard used for furnishing houses and offices or other private and public buildings. Packing materials Products made of sawn timber, plywood / veneer, (lifespan of 1 year) particleboard, or paper- and -products used for packing other commodities; e.g. shipping boxes, wrapping, and boxing. Long-life paperproducts Products made of pulp used for longer periods such as , (lifespan of 4 years) maps, or posters. Short-life paperproducts Products made of pulp used for short periods such as newsprint (lifespan of 1 year) and sanitary papers.

3.3.5 Lifespan of wood products

Regarding their lifespan, wood products were divided into 4 groups. The estimated lifespan for the different product groups were 50 years for the long lifespan, 16 years for medium-long lifespan, 4 years for medium-short lifespan and 1 year for short lifespan. These figures are similar or slightly shorter than that of Row and Phelps (1990), Karjalainen et al. (1994), and Pingoud et al. (1996, 2000).

Short lifespan products include fuelwood, newsprint, shares of packing paper, paperboard, and and writing paper, wooden packing materials and shares the structural support materials. Medium-short lifespan products include the rest of packing paper, paperboard, and printing and writing paper. Medium-long lifespan includes part of the sawn timber and wood-based panels, while the rest represents long lifespan products (Table 3.6). More detailed information on the shares of the use categories in the lifespan groups can be found in Table 3.12. 26 Thies Eggers

Table 3.5. Half-life periods of wood products in different studies.

Study Half-life periods (lifespan) [years]

short medium-short medium medium-long long

Row & Phelps (1990) 1 6 12 30 50, 60, 67 Karjalainen et al. (1994) 4 13 30 65 Pingoud et al. (2000) 16 50 LTEEF-II (this study) 1 4 16 50

Table 3.6. Overview on the different lifespans in this study and commodities included in those

Category Lifespan Included commodities [years]

Short lifespan paper-products 1 newsprint, shares of packing paper, paperboard, and printing and writing paper Medium-short lifespan paper-products 4 rest of packing paper, paperboard, and printing and writing paper Short lifespan timber 1 fuelwood, wooden packing materials and structural support materials Medium-long lifespan timber 16 part of the sawn timber and wood-based panels,

Long lifespan timber 50 rest of the sawn timber and wood-based panels

The lifespan of the different product categories were calculated in the same way as by Row et al. (1990) with an extended logistic decay function; i.e. a f ( pu) = d − (3.7) 1+ b *e−c*t where pu = the fraction of products in use, a,b, d = parameters [dimensionless] c = the reciprocal of the half-life period [year-1] and t = the time [year].

Used parameters and resulting figures are shown in Tables 3.7 and 3.8. Figure 3.3 shows the shares of the lifespans over a 100-year period.

When a product reaches the end of its lifespan, it can be recycled, used as energy source or disposed as waste into landfills. In case products are burned to generate energy, C is released immediately to the atmosphere whereas the decomposition of waste in a landfill is slow due to the anaerobic conditions of decay. These emissions are estimated at 0.5 percent per year with a constant rate. These estimates are similar to Row et al. (1990) who refer within their study to Carr (1978), Franklin Associates Ldt. (Characterization of municipal solid waste in the United Sates, 1960–2000 (1988)), the U.S. Environmental Protection Agency (Solid waste disposal in the United States (1988)), and Noble et al. (1989). The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 27

100 short lifespan, 1 year 90 medium short lifespan, 4 years 80 medium long lifespan, 16 years 70 long lifespan, 50 years 60 50 40 30 20 10 0 020406080100 year

Figure 3.3. Calculated amount of carbon in the four different lifespan categories in percent where first year (year of production) = 100%. See also Table 3.8.

Table 3.7. Parameters of the logistic decay function used in the EFISCEN wood product model as the lifespan function for wood products.

Half-life period Parameters of the decay function [years] Ab cd

Short lifespan 1 120 5 3 120 Medium-short lifespan 4 120 5 0.5 120 Medium-long lifespan 16 120 5 0.12 120 Long lifespan 50 120 5 0.04 120

Table 3.8. Percentages of the remaining wood products in the lifespan categories under the used function parameters.

Lifespan category [years] Short Medium-short Medium-long Long (1 yr) (4 yr) (16 yr) (50 yr)

0 100.0 100.0 100.0 100.0 1 23.9 90.2 97.9 99.3 2 0.1 77.7 95.7 98.6 3 0.0 63.3 93.3 97.9 4 0.0 48.4 90.7 97.2 5 0.0 34.9 87.9 96.4 10 0.0 3.9 72.1 92.4 Years 25 0.0 0.0 23.9 77.7 50 0.0 0.0 1.5 72.1 75 0.0 0.0 0.1 23.9 100 0.0 0.0 0.0 10.1 150 0.0 0.0 0.0 1.5 200 0.0 0.0 0.0 0.2 28 Thies Eggers

The lifespan of recycled products may be shorter or equal to that of the original one; i.e. long lifespan products were recycled into long, medium-long, and short lifespan products, me- dium-long into medium-long and short lifespan, medium-short into short lifespan and the same for short lifespan products (Table 3.9). The amount of recycled products is the same for all the countries except for the fraction for paper and paperboard products. These figures were taken for each country from the statistics of the Finnish Statistical Yearbook of Forestry (METLA 1998) assuming that for both possible paper lifespans (1 and 4 years) the recycled proportion is the same.

Table 3.9. Distribution-matrix of products in the recycling process (left column) to new product categories / lifespan categories (1.00 means that everything is recycled to the given category). The rows must always add up to 1.00. Abbreviations for the columns are given in the rows.

Categories Lifespan SPP MPP ST MT LT [years]

short lifespan 1 1.00 0 0 0 0 paper-products (SPP) medium-short lifespan 4 1.00 0 0 0 0 paper-products (MPP) short lifespan timber (ST) 1 0 0 1.00 0 0 medium-long lifespan 16 0 0 0.50 0.50 0 timber (MT) long lifespan timber (LT) 50 0 0 0.33 0.34 0.33

3.3.6 Basic Calculations

The mentioned calculations are extended over the lifespan of products and concern C in a cohort of wood products manufactured in a given year from the timber harvest in the same year, and in consideration of C in different phases of the lifespan of products. The main part of the C in timber is bound into products while the rest of the C is emitted when by-products (, bark, etc.) are burnt to generate energy (process losses). Products can be either kept in use or be abandoned. When they are abandoned, products can be recycled into raw material for new products, they can be burnt to generate energy, or they can be discarded into landfills. Thus the original C is used in further production in the form of recycled products until the entire C is finally emitted into the atmosphere. (Figure 3.4).

The simulation starts in 1990 with the allocation of C in harvested timber into products and C emitted into the atmosphere as a matter of production processes. Thereafter C flows into the products in the form of recycled products and again part of the C is emitted into the atmos- phere. At the same time, products are removed from use and disposed into landfills as waste or burned to energy in which both cases C is emitted into the atmosphere. This procedure was repeated over a period of 60 years up to the year 2050 using output from EFISCEN simulations (harvested timber) as input in the wood product model. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 29

removals o.b. atmosphere 1961 -1990: FAOSTAT forest statistics 1991 - 2050: EFISCEN results

process release

production decay process burning recycling

products in products use removed from

waste disposal

landfill

Figure 3.4. Transfer of carbon through the products to the atmosphere in the EFISCEN wood product model.

3.3.7 Model parameters

In general, model parameters, depending on the availability of source-data, are given on three different levels: country level (Figure 2.1), regional level (Figure 3.1), and supra-regional level (Figure 3.5). The regional level represents the same (ecological) regions as Kuusela’s study (Kuusela 1994). On the supra-regional scale, they are aggregated to 3 major regions: • Northern Europe (Finland, Sweden, Norway), • Central Europe (Germany, Denmark, Poland, Czech Republic, Slovak Republic, Swit- zerland, Austria, Netherlands, Belgium, Luxembourg, France, United Kingdom, Ireland, Hungary, Romania), and • Southern Europe (Portugal, Spain, Italy, Slovenia, Croatia, Yugoslavia, FYR Macedonia, Albania, Bulgaria).

Northern supra-region Central supra-region Southern supra-region

Figure 3.5. Supra-regions used in this study are based on the country regions from Kuusela (1994). 30 Thies Eggers

3.3.7.1 Country parameters

The country parameter files provide explicit flows of wood from fellings to the wood product processing lines for each country. These files describe the amounts for coniferous timber and non-coniferous timber for the following processing steps. The rows describe the amount of wood (respectively carbon) used as:

• logging residues, • bark, • fuelwood, • chemical pulp, • mechanical pulp, • sawn timber, • plywood & veneer, • particleboard, and • other industrial roundwood.

These parameters were calculated by using average FAO figures on the commodity produc- tion from 1990 to 1998 and commodity producer information to receive the roundwood equiva- lent for the products. For the parameter calculation of chemical and mechanical pulp, sawn timber, plywood and veneer, particleboard, and other industrial roundwood, the international trade of industrial roundwood (IRW) was taken into account to get a more realistic stock of IRW, which is the base stock (raw material) for the mentioned products / semi-finished prod- ucts. According to the definitions of FAOSTAT and other publications (Kuusela 1994), the following definitions are useful for the better understanding of the figures:

Fellings = removals o.b. + logging residues Removals o.b. = removals u.b. + bark Removals u.b.= roundwood production in the FAOSTAT database Roundwood production = fuelwood + industrial roundwood (IRW) Industrial roundwood (IRW) =pulpwood + sawnwood + plywood / veneer + particle board + other industrial roundwood

The accuracy of FAOSTAT database has improved during the last years but in some cases the database shows lacks in the aggregated commodity figures. In this study, the sub-categories were added to aggregated figures which had been used in the parameter calculations. The data on import and export of industrial roundwood (IRW-WIR) seems to be less reliable. The IRW trade-figures on coniferous and non-coniferous (including tropical wood) never add up cor- rectly to the aggregated data. This fact has been accepted and acknowledged in this study.

The calculation of the model-country parameters was done using simple mathematical equa- tions, the example provided in Table 3.10 clarifies the calculation.

The idea of the country parameters is to describe the way wood is used in each country, i.e. it describes the structure of the domestic forest industry. The figures must be read as percent- ages of the next higher category (logging residues to fellings; bark fraction to removals over bark, fuelwood and IRW to removals under bark). Logging residues are those stemwood residues, which stay in the forests when the wood is harvested [fellings] and taken to the industries. In this case 3.31% of the coniferous and 4.33% of the non-coniferous wood volume stay in the forests and decomposes naturally (UN/ECE 1992; see Chapter 3.3.1). The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 31

Table 3.10. Country parameters for the EFISCEN wood product model as an example for Germany. ‘con.’ means coniferous wood; ‘non-con.’ means non-coniferous wood. The ‘model parameter’ are those calculated by using the relation of the IRW sub-categories to the total IRW amounts. The ‘adjusted model parameters’ are recalculated from the ‘model parameters’ as described in the text. These parameters for Austria, Finland, Norway and Portugal can be found in the Appendices.

Model parameter Adjusted model parameter Con. Non-con. Con. Non-con.

Natural losses1 0.0331 0.0433 0.0331 0.0433 Bark-fraction2 0.1100 0.1300 0.1100 0.1300 Fuelwood3 0.0439 0.2052 0.0439 0.2052 Pulpwood à chemical pulp3 IRW 0.1749 0.2426 0.1116 0.2045 Pulpwood àmechanical pulp3 IRW 0.1532 0.2125 0.0978 0.1791 Sawn timber3 IRW 0.8461 0.2764 0.5399 0.2330 Veneer & plywood3 IRW 0.0702 0.0702 0.0448 0.0591 Particleboard3 IRW 0.2905 0.2905 0.1854 0.2448 Other IRW3 IRW 0.0323 0.0943 0.0206 0.0795

IRW total 1.5671 1.1866 1.0000 1.0000 1UN/ECE (1992); 2Haygreen et al. (1989); 3FAO (2000a)

Decomposition of logging residues is accounted in the soil-model of EFISCEN. The remain- ing 96.69% for coniferous and 95.67% for non-coniferous [removals o.b.] of the wood biomass is allocated to the next category and is taken as a new input with 100% each. FAOSTAT forestry statistics provide figures in volume without bark. Thus a common bark fraction must be subtracted from the removals o.b. with 11% for coniferous and 13% for non-coniferous timber (Haygreen et al. 1989). This leads to the figures for removals u.b. which are the origi- nal figures from the FAOSTAT internet database (called here roundwood). The amount of roundwood was divided into two major categories: fuelwood and industrial roundwood (IRW). So 4.39% of the coniferous timber and 20.52% of the non-coniferous timber are used as fuelwood and the remaining percentages are the domestic base for the aggregated category IRW.

At this point, the only implementation of the imports and exports in the country parameter calculation took place. This was done on the country level using FAO trade figures on IRW. To the given domestic figures for IRW, the imported and exported amounts of those assort- ments were summed up and offset against the IRW capacity of the country. Thus, the final available amount of IRW was calculated, the basis for the further parameter calcula- tions. All sub-categories of IRW (see Table 3.10) should have added up to this amount of wood, but unfortunately they never did, maybe owing to incomplete records on the production and the used efficiency parameters for the wood processing industries. Therefore, the param- eters were corrected to add up to one (adjusted model parameters).

Due to the fact that FAOSTAT figures for the IRW sub-categories are given in cubic meters of the commodities, a recalculation of the roundwood equivalent was needed. For the regarded groups, this was done as described in the following: • The figures for “other industrial roundwood” (other IRW) are calculated from the direct FAOSTAT figures because no conversion factor is known due to the broad variety of 32 Thies Eggers

products in this category, and as a compromise the amount of carbon of this commodity was added to the pool of sawn timber.

• The “sawn timber” percentages were calculated after the recalculation of the approxi- mate input of wood to sawn timber production. For the Northern supra-region, an effi- ciency of 43.5% for both, coniferous and non-coniferous timber, was assumed (figure from Karjalainen et al. 1994). For the countries of the Central European supra-region, the efficiency figures of the German industry were applied, meaning 61% for coniferous and 67% for non-coniferous timber (figures from Burkart 1999). For the conversion of sawn timber to roundwood equivalents in the Southern European supra- region, figures from Portugal with an efficiency of 43% for both, coniferous and non- coniferous timber, were applied (figure from Direcção-Geral das Florestas 1991).

• Plywood and veneer sheets are produced with an output of 38.4% (figure from Kar- jalainen et al. 1994). So the amount of logs for this production was calculated using the above-mentioned percentage.

• The production of particleboards (medium density fibreboard, hard density fibreboard, oriented strand board, and insulating board) is assumed to work with an output of 66.9%, which represents figures from a German particleboard plant. The efficiency in some production lines might be higher, but no other data were available. The model- parameters for coniferous timber are the same like for non-coniferous ones because the calculation were just possible with aggregated production figures. Thus they were separated equally to both wood assortments.

• The separation of wood pulp to mechanical and chemical pulp grades seemed to be necessary due to rather different usage of each. Mechanical pulp includes the production of mechanical and semi-chemical pulp. Chemical pulp aggregates chemical and dissolv- ing pulp production. Once again, efficiency parameters were used to estimate the input of wood volume to pulp production: 92.8% for mechanical and 47.1% for chemical pulp production (figures from Karjalainen et al. 1994).

Finally the percentages of all IRW sub-categories were summed up and corrected to equal 1.00 using the sum for coniferous and non-coniferous wood as correction figures for each wood class (Table 3.10). The adjusted model parameters were to be used in the model to describe the input amounts to the used timber assortments. This was necessary because the wood product model checks whether the fractions of IRW add up to one or not.

3.3.7.2 Efficiency parameters

The following description explains the meaning and function on the used efficiency param- eters. Due to the lack of other data available for production lines three supra-regions (North- ern Europe, Central Europe and Southern Europe as described in Chapter 3.4.5) were taken into consideration. The efficiency parameters describe in a certain way the production line in the wood processing industry. The harvested timber is distributed to a hypothetical forest industry, where it is further processed. The ratio of timber input [m3] to product output [m3] of these plants was never 100% regarding the main product. With these parameters, the amount of timber, and thus carbon, in products was calculated by assuming a constant production efficiency over time. The losses in the production process are either used for energy produc- tion or distributed to other production lines. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 33

For the northern countries, the parameters from a Finnish study (Karjalainen et al. 1994) were applied. Only the particleboard figures from Germany were copied because the Finnish study did not consider particleboard production as there is only one very small plant in Finland. Parameters for Southern and Middle Europe are partly identical because the lack of informa- tion on this topic from any Southern European country. The general question which rises concerning all efficiency parameters is whether those figures can represent the structures of the forest industries in a reliable way. For example, the figures for the particleboard produc- tion are from a single German company. The same applies to the figures for plywood and veneer production for Middle and Southern Europe.

Table 3.11 shows for the Northern Region the efficiency parameters in different production lines and to which other production lines the by-products will be added. The rows describe chemical pulp, mechanical pulp, coniferous sawn timber, non-coniferous sawn timber, ply- wood & veneer, and particleboard. The columns describe the ratio of wood used for the final products, energy-production, pulp-production, and particleboard-production.

Table 3.11. Efficiency parameter for the regarded production lines in the Northern Region. The rows must always add up to one so that no uncertain ways of timber are assumed. The efficiency parameters for the Central and the Southern Region can be found in the Appendices.

Fraction of timber (input) to Production line final productenergy burning pulp production particleboard production

Chemical pulp 0.472 0.528 0.000 0.000 Mechanical pulp 0.928 0.072 0.000 0.000 Sawn timber (con.) 0.435 0.130 0.435 0.000 Sawn timber (non-con.) 0.435 0.130 0.435 0.000 Plywood & veneer 0.384 0.277 0.339 0.000 Particleboard 0.690 0.230 0.080 0.000

3.3.7.3 Parameters for usage, and parameters for the terminal use of commodities

The produced commodities can be distributed in seven usage categories. Each category is connected to a specific lifespan. These lifespans have been described in Chapter 3.4.3. For all regarded countries, all commodities are distributed to these usage categories in the same way. The amount of products (respectively the amount of carbon) going to its usage is a proportion of the whole available product stock during the year. Table 3.12 shows the shares and pur- poses of wood products after their production. These are general parameters for all countries.

After their usage, products can be either recycled, or disposed to a landfill as waste or burned as . The percentages for the timber products are rough estimations and should be im- proved in the future studies. Only the shares of the recycling of paper products were taken from available statistics, namely the Finnish Statistical Yearbook of Forestry (METLA 1998), which refers to Pulp and Paper International, July 1998. It was assumed that the percentage of recycled paper and paperboard comes in equal shares from short and medium-short lifespan paper products. Table 3.13 shows, as an example for Germany, the terminal use ratios for the different lifespan categories. 34 Thies Eggers

Table 3.12. Usage of the regarded products in shares of their total amount after production. Lines must sum up to 1.00.

Building Other build. Structural Furnishing Packing Long life Short life m a t e r i a l s materials paper products

Lifespan [years] 50 16 1 16 1 4 1

Sawn timber 0.35 0.30 0.10 0.15 0.10 0 0 Plywood / veneer 0.05 0.05 0.30 0.30 0.30 0 0 Particleboard 0.20 0.30 0.10 0.20 0.20 0 0 Chemical pulp 0 0 0 0 0.33 0.33 0.34 Mechanical pulp 0 0 0 0 0.34 0.33 0.33

Table 3.13 Terminal uses for the product lifespan categories as shares of the yearly amount of carbon being put out of use in that specific usage (example for Germany).

Category Lifespan Recycling Landfill Burning [years] [%]

Short lifespan paperproducts 1 0.72 0.14 0.14 Medium-short lifespan paperproducts 4 0.72 0.14 0.14 Short lifespan timber 1 0.15 0.45 0.40 Medium-long lifespan timber 16 0.25 0.50 0.25 Long lifespan timber 50 0.30 0.35 0.35

3.4 APPLIED SCENARIOS

Nabuurs et al. (2001) described the forest management scenarios which were applied in the EFISCEN simulations. Two of those EFISCEN scenarios were applied as forest management impact scenarios of wood product stocks in this study (-as-usual, and Multifunctional). One additional wood product management scenario, considering the EU directive 1999/31/ EC for waste (EU 1999) was applied in the landfill options for all regarded countries (EU and non-EU countries) under the both EFISCEN scenarios.

3.4.1 Business-as-Usual Scenario

Business-as-Usual (BaU) scenario means that the level of fellings and the forest management regimes stay on the level of the late 1980s or early 1990s over the simulation period, and thus the input to the applied wood product model. For those countries that were studied in more detail (Austria, Finland, Germany, Norway, and Portugal), this scenario includes the forest management regimes listed in Table 3.14. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 35

Table 3.14. Brief description of the forest management regimes in EFISCEN Business as Usual (BaU) scenario in Austria, Finland, Germany, Norway, Portugal, and all LTEEF-study COUNTIRES in general.

Country Brief description of BaU scenario Austria level of 15.5 million m3·yr-1 of which 30% from thinnings. No forest expansion is assumed. Finland Felling level of 42.4 million m3·yr-1 for coniferous and 11.6 million m3·yr-1for deciduous. Thinning share is 40%. No forest expansion is assumed. Germany Total felling level is 42.8 million m3·yr-1 (33.2 million m3·yr-1for coniferous and 9.6 million m3·yr-1for deciduous). Thinning level is 45% for coniferous and 52% for non-coniferous forests. No forest area expansion. Norway Felling level of 13.4 million m3·yr-1 and a thinning level of 35%. No forest area expansion. Portugal Felling level of 7.54 million m3·yr-1 with a thinning share of 40%. Forestland area was kept constant. LTEEF Fellings will stay on the level of 1990 and the share of thinnings in the total amount of fellings is about 30%. The forest area is stable and will not be expanded during the simulation period.

Table 3.15. Brief description of the forest management regimes in EFISCEN multi-functional (MF) scenario in Austria, Finland, Germany, Norway, Portugal, and LTEEF-study countries in general.

Country Brief description of MF scenario Austria Fellings will increase with approx. 0.7% per year during the whole period 1990–2050. All forests older than 150 years are set aside from forest management. The rotation length of all species is elongated with 20 years and the share of thinnings in total fellings is increased to 50%. The forest area is also increased with 64,000 ha over a period of 40 years. Finland Fellings of will increase with 0.5% during the first 20 years. and aspen stands older than 180 years are set aside from forest management. The rotation length for all species is elongated with 20 years and the forest area will increase in 2000 and 2010 with 96,000 ha each time. The share of thinnings of the total fellings is increased to 50%. Germany Fellings will increase with 2% per year from 1990 to 2010. In 1995, 2000, and 2005 the forest area will increase each time with 35,100 ha. stands older than 160, beech stands older than 180 and other older that 140 years are set aside from forest management. The rotation period is elongated with one age class of 20 years and the thinning regime with one age class. The share of thinnings is gradually in creased to 60%. Norway Same felling levels are used as in BaU scenario, but the forest area will increase until 2010 with 80,000 ha. Forest reserves are created for stands older than 150 years. Thinnings have a share of 50% of total fellings and the rotation period is elongated with 20 years.

Portugal The forest area will increase slightly with about 1% until 2030. Coniferous stands (Pinus pinaster) older than 50 years are set aside as forest reserves. The rotation length is elongated with 10 years and the share of thinnings of total fellings increase to 50%. LTEEF In general fellings will increase with 0.3% per year during the first 30 years. There will be a trend towards nature oriented forest management, i.e. old forests older than 150 years – but the age is depending in the country – are set aside as forest reserves. The proportion of thinnings in fellings will increase to 45% and the forest area will expand with 4.4 million ha. 36 Thies Eggers

3.4.2 Multi-functional Scenario

The multi-functional (MF) scenario includes several changes in the forest conditions com- pared to the BaU scenario and can be regarded as a multi-functional forest management sce- nario with different aspects. This includes i) a rising felling level, ii) nature conservation aspects are considered, i.e. old grown forests are set aside from production, and iii) there are changes in the forest area. These changes vary from country to country according to the state of the forest and national policies. A more detailed description is given in Table 3.15.

3.4.3 EU-landfill Scenario

In this study, the EU Council Directive 1999/31/EC (EU 1999) was applied for both EU and Non-EU countries. It describes in its article 5 the waste and treatment that is not acceptable in landfills anymore. EU member states are obliged to reduce the biodegradable waste going to landfills. This includes also waste from the wood processing industry as well as abandoned wood products. The aim of reducing these inputs to landfills shall be obtained by means of recycling, composting, biogas production or material / energy recovery. The directive refers to 1995 as base-year and shall be fulfilled in three steps:

1. By 2006 at the latest, the biodegradable waste going to landfills must be reduced to 75% of the total amount by weight measured in the base year. 2. By 2009 at the latest, the biodegradable waste going to landfills must be reduced to 50% of the total amount by weight measured in the base year. 3. By 2015 at the latest, the biodegradable waste going to landfills must be reduced to 35% of the total amount by weight measured in the base year.

In this study, it was assumed that the recovered wooden ‚waste‘ is distributed evenly to woodfuel and recycling, i.e. from 2006 onwards 25% of the amount of carbon, which would normally go to a landfill is recycled or used as an energy source, and the same applies from 2008 onwards to 50%, and from 2015 onwards to 65% of the annual new wooden waste.

3.5 ASSUMPTIONS AND UNCERTAINTIES

As every model analysis also this study contains certain assumptions that had to be made in order to achieve the set goal. This chapter shall give a brief overview on the most evident assumptions and known uncertainties. Some of them had been mentioned earlier in the de- scription of the parameter calculation and model structure. A validation or a sensitive analysis of the used wood product model have not been done until now, but is of course needed to validate the later shown results. The model development and improvement is still ongoing and will be continued in the future.

The model structure is static, meaning that the given parameters are used for the whole simu- lation period with exception in the EU landfill scenario, where the end-use options change over time. But in the case of efficiency parameters and country parameters, no changes are assumed to take place. In reality, there might be improvements in the wood processing indus- tries and thus the efficiencies of timber-processing will rise. Scenarios like this were consid- ered in the ESCOBA study by Jäkel et al. (1999). Also changes in the demand of certain The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 37 products or the general range of products could not be considered, but would have been nec- essary to represent the wood processing sector and the wood product market in a more realis- tic way.

Due to the way of its development, the model uses from 1990 onwards already modelled data (EFISCEN forest model output on removals) as input to its own calculations. Therefore, natu- ral disturbances cannot be implemented by using current data. Using the historical data until 1990 showed that these hazards did have an impact on the results. The huge amount of wind thrown timber, which was the result of the severe storms in late 1989 in central Europe, can been seen among others in the results especially for Germany, where nearly twice as much timber as normal was input to the wood product model. The implementation of natural haz- ards and trade-flows of roundwood and commodities in EFISCEN models is under prepara- tion. A general database on forest disturbances was recently launched at EFI (Schelhaas et al. 2001) and the already mentioned COMTRADE statistics on wood products are also available.

The data accessibility was in some cases insufficient and thus data from other studies or expert-assessments (estimates) needed to be adopted to the model. Due to the rather large scale of this approach also countries had to be gathered to regions and known parameters for one country included in the region had to be transferred to the other countries in this region. The scale of this transfer varies from country-, regional-, supra-regional- and European level. For example the usage of timber (Table 3.12) and the distribution of recycled products (Table 3.9) are used in the same way for all countries. As well as the lifespans, where the duration of these periods is a result from study comparison. The efficiency parameters (Table 3.11) are used on supra-regional, logging residues (Table 3.1) and wood densities (Table 3.3) on re- gional and production parameters (Table 3.10) on country level.

In general the used input data and the data for parameterisation are comparable to other stud- ies of this magnitude and thus should be sufficient for this kind of approach. Improvement of parameters and input data has to be in relation with the later output and results. According to the IPCC approaches the used stock-change approach with the exclusion of trade is one pos- sible approach to report under the Kyoto Protocol and is already an improvement to the IPCC Default approach, where wood products are not considered in this detailed way. The results of this study should be seen as an first attempt to model the impacts of manufacturing and utili- sation of wood products for the European carbon budget in a large scale approach. Further studies on this topic will follow and should also summarise and analyse the results of the few but recent studies in this area of research.

4. RESULTS

The following results have been generated by using the historical FAOSTAT data on forest removals until 1990 and from then on with modelled removals by the EFISCEN as input to the wood product model. Due to the uncertainties in the parameterisation of the wood processing industries and the usage of produced wood products as well as the usage of already modelled data as input these results have to be considered as one possible scenario for Europe.

4.1 CARBON STOCKS IN WOOD PRODUCTS

4.1.1 Business as usual forest management scenario

Wood products cover only a small part of the total forest sector carbon budget. The magnitude varies from about 12% to less than 4% in the focussed countries. In the European view the amount is 6% in the year 2000 and is even decreasing within this scenario to 5% in 2050 (Fig. 4.1). This decrease can be explained with the largely increasing stock of carbon in the trees and forest soil due to relatively low felling levels and high increment rates (see Figure 8.9 in the Appendices). The figures for Austria, Finland, Germany, Norway, Portugal and the whole of Europe are shown in Table 4.1 as stocks in Tg C (1 Teragram [Tg] = 1012g = 1Mt). Table 4.2 shows the same figures in percentages to the total amount of carbon stored in the forest sector. Beside that the share of wood products in the carbon budget of the whole forest sector is low, it must be mentioned that this stock is still increasing in those countries except Portugal, where the forest management shows less fellings in the model (Figure 8.8 in the Appendices) than in the historic development. The changes in carbon stocks for the business as usual (BaU) scenario in the wood products are shown in figure 4.2 where the amount of carbon which was calculated for 1990 was set as the reference value (100%). The differences between the countries are due to the diverse usages of wood and the removals as input to the model. Please note that the lines in Figure 4.2 show the development within one country and not the comparison among the countries in relation to their total socks.

Looking at the total carbon stock these figures reflect always also the capacity of each country to produce timber and thus wood products. In the applied approach with the exclusion of trade of both timber and wood products do large forest areas with productive tree species and by this also high felling levels lead to larger carbon stocks than in countries where those settings are not present. In this case it might be interesting to put the carbon stocks into perspective with the total forest area, which was used to ‘produce’ these stocks. By this it is possible to compare countries with different forest areas and thus different wood production in a better way. In Tables 4.3 to 4.5 this is shown for the average carbon stock in wood products, the average yearly change in the wood product carbon stock and the average carbon balance of wood products (= products discarded into landfills + products in use – carbon release of landfills). The difference between the two latter ones is that the first includes the change in the stock for wood products in use, while the latter includes in addition the chance in the stock of wood products in landfills, too. 40 Thies Eggers

2000 2025 2050 12000

10000

8000

6000

4000

carbon stocks [Tg C] 2000

0 trees soil products

Figure 4.1. Carbon stocks in the European forest sector for 2000, 2025 and 2050 in trees, forest soil and wood products in Tg C for the business as usual (BaU) scenario.

170 160 150 Norway Austria 140 Europe 130 Finland 120 Germany 110 Portugal 100 90 compared to initial start in 1990 (=100%) development of wood product stock [%] 80 2000 2025 2050 Year

Figure 4.2. Development of the carbon stock in wood products in relation to the initial stock (1990) for Austria, Finland, Germany, Norway, Portugal and Europe. 1990 was set as 100 %. (BaU scenario).

Table 4.1. Carbon stocks [Tg C] of trees, forest soils and wood products in the forest sector of Austria, Finland, Germany, Norway, Portugal and Europe in 2000, 2025 and 2050.

Austria Finland Germany Norway Portugal Europe

2000 Trees 278 659 847 228 43 6894 Forest soils 334 745 598 208 65 6086 Wood products 42 61 129 19 15 769

2025 Trees 357 813 1133 288 65 8693 Forest soils 347 771 626 218 70 6321 Wood products 49 67 134 22 15 847

2050 Trees 411 939 1304 332 70 10001 Forest soils 355 800 647 229 71 6541 Wood products 52 69 137 24 14 885 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 41

Table 4.2. Shares of carbon stocks [%] of trees, forest soils and wood products in the forest sector of Austria, Finland, Germany, Norway, Portugal and Europe in 2000, 2025 and 2050 as their fraction of the total C stored in that year.

Austria Finland Germany Norway Portugal Europe

2000 Trees 43 45 54 50 35 50 Forest soils 50 51 38 46 53 44 Wood products 7 4 8 4 12 6

2025 Trees 47 48 60 55 44 55 Forest soils 46 47 33 41 47 40 Wood products 7 4 7 4 10 5

2050 Trees 50 52 62 57 45 57 Forest soils 44 44 31 39 46 38 Wood products 6 4 7 4 9 5

Table 4.3. Average carbon stock in wood products in total [Tg C] and per ha forest area [Mg C·ha-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1990. (BaU Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C] 38.3 57.0 121.0 16.1 15.2 735.5 per ha [Mg C ha-1] 13.0 2.9 12.1 2.3 10.1 5.7

2011–2020 total [Tg C] 47.3 65.6 132.6 21.4 14.6 832.1 per ha [Mg C ha-1] 16.1 3.3 13.3 3.0 9.7 6.5

2041–2050 total [Tg C] 51.6 68.9 136.9 23.5 14.3 866.9 per ha [Mg C ha-1] 17.5 3.5 13.7 3.3 9.5 6.7 42 Thies Eggers

Table 4.4. Average yearly change in wood product carbon stock in total [Tg C yr-1] and per ha forest area [kg C·ha-1 yr-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1990. (BaU Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C yr-1] 0.48 0.34 1.88 0.23 0.20 7.92 per ha [kg C ha-1 yr-1] 163 17 188 32 130 61

2011–2020 total [Tg C yr-1] 0.21 0.18 0.20 0.11 -0.01 1.96 per ha [kg C ha-1 yr-1] 71 9 21 15 -7 15

2041–2050 total [Tg C yr-1] 0.09 0.07 0.08 0.04 -0.01 0.75 per ha [kg C ha-1 yr-1]313 8 6 -76

Table 4.5. Average carbon balance in total wood product carbon stocks in total [Tg C yr-1] and per ha forest area [kg C·ha-1 yr-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are historical FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1990. (BaU Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C yr-1] 1.14 2.36 4.38 0.75 0.65 25.53 per ha [kg C ha-1 yr-1] 388 120 438 105 431 198

2011–2020 total [Tg C yr-1] 0.90 2.13 2.31 0.72 0.27 17.91 per ha [kg C ha-1 yr-1] 306 109 231 101 181 139

2041–2050 total [Tg C yr-1] 0.75 1.81 1.95 0.60 0.23 14.99 per ha [kg C ha-1 yr-1] 254 92 195 85 155 116 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 43

4.1.2 Multifunctional forest management scenario

The main differences between the multifunctional scenario and the business as usual scenario are higher felling levels and a higher increment in the forests (see Figure 8.2 in Chapter 8.1). The higher felling levels must lead to a higher carbon stock in the domestic wood products (Figure 4.3) as no roundwood and commodities are traded to another country. This is due to the used stock-change approach with the exclusion of trade and can be clearly seen when one compares this figure with Figure 4.2. Concerning the interpretation of Figure 4.3, the same comments as given for Figure 4.2 apply. But as the wood product stock is not that high, the increasing stock does not change much in its percentage to the total. There is only a slightly noticeable increase in the relation of wood products to the other two main stocks of the forest sector (trees and soils). Tables 4.6 and 4.7 show the development of these three stocks for 2000, 2025 and 2050 under the multifunctional forest management scenario.

As introduced in the previous chapter the results for the multi-functional scenario will be also put into perspective with the available forest area to make them comparable with one another. Once again only the results for those 5 countries and for Europe will be shown in Tables 4.8 to 4.10. These results show already in the first period variations to those from the business as usual scenario. This is due to the last year of this decade, which represents data from the first modelled year with EFISCEN and the multi-functional scenario does already increase the fellings in this year.

170 160 150 Austria Norway 140 Germany 130 Europe 120 Finland 110 Portugal 100 90 development of wood product stock [%] compared to initial start in80 1990 (=100%) 2000 2025 2050 Year

Figure 4.3. Development of the carbon stock in wood products in relation to the initial stock (1990) for Austria, Finland, Germany, Norway, Portugal and Europe. 1990 was set as 100 %. (Multi-functional scenario). 44 Thies Eggers

Table 4.6. Carbon stocks [Tg C] of trees, forest soils and wood products in the forest sector of Austria, Finland, Germany, Norway, Portugal and Europe in 2000, 2025 and 2050 (MF scenario).

Austria Finland Germany Norway Portugal Europe

2000 Trees 273 661 830 230 43 6906 Forest soils 335 742 599 209 66 6057 Wood products 44 62 134 19 15 775

2025 Trees 342 837 1055 299 66 8678 Forest soils 347 774 624 221 70 6336 Wood products 56 70 168 24 14 925

2050 Trees 396 954 1135 350 70 9834 Forest soils 355 810 637 234 70 6576 Wood products 64 74 188 25 16 1018

Table 4.7. Shares of carbon stocks [%] of trees, forest soils and wood products in the forest sector of Austria, Finland, Germany, Norway, Portugal and Europe in 2000, 2025 and 2050 as their fraction of the total C stored in that year (MF scenario).

Austria Finland Germany Norway Portugal Europe

2000 Trees 42 45 53 50 35 50 Forest soils 51 51 38 46 53 44 Wood products 7 4 9 4 12 6

2025 Trees 46 50 57 55 44 54 Forest soils 46 46 34 41 47 40 Wood products 8 4 9 4 10 6

2050 Trees 49 52 58 57 45 56 Forest soils 44 44 32 38 45 38 Wood products 8 4 10 4 10 6

Table 4.8. Average carbon stock in wood products in total [Tg C] and per ha forest area [Mg C·ha-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1989. (MF Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C] 38.3 57.0 121.0 16.1 15.2 735.4 per ha [Mg C ha-1] 13.0 2.9 12.1 2.3 10.1 5.7

2011–2020 total [Tg C] 52.9 68.5 160.9 22.7 14.3 891.8 per ha [Mg C ha-1] 17.7 3.5 16.0 3.2 9.5 6.8

2041–2050 total [Tg C] 63.8 74.1 187.0 25.3 15.9 1004.1 per ha [Mg C ha-1] 21.1 3.7 18.5 3.6 10.6 7.6 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 45

Table 4.9. Average yearly change in wood product carbon stock in total [Tg C yr-1] and per ha forest area [kg C·ha-1 yr-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1989. (MF Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C yr-1] 0.52 0.34 1.95 0.23 0.19 7.86 per ha [kg C ha-1 yr-1] 175 17 195 32 126 61

2011–2020 total [Tg C yr-1] 0.44 0.28 1.13 0.14 -0.01 4.95 per ha [kg C ha-1 yr-1] 148 14 112 20 -4 38

2041–2050 total [Tg C yr-1] 0.21 0.12 0.57 0.04 0.04 2.20 per ha [kg C ha-1 yr-1]686 576 2517

Table 4.10. Average carbon balance in total wood product carbon stocks in total [Tg C yr-1] and per ha forest area [kg C·ha-1 yr-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are historical FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1989. (MF Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C] 1.18 2.36 4.44 0.74 0.64 25.43 per ha [kg C ha-1] 400 120 445 105 427 197

2011–2020 total [Tg C] 1.26 2.41 4.06 0.82 0.26 23.04 per ha [kg C ha-1] 422 122 402 116 174 175

2041–2050 total [Tg C] 1.08 2.05 3.49 0.66 0.36 19.79 per ha [kg C ha-1] 357 104 346 93 236 149 46 Thies Eggers

4.2 DISTRIBUTION OF CARBON WITHIN THE WOODEN COMMODITIES

The amount of carbon in a specific usage category depends from country to country on the parameterisation of the wood processing industry and the regional settings for production efficiency and product recycling. The following figures will show the modelled results for the distribution of carbon stocks in wood-based products. Carbon emissions from harvesting activities and the later wood processing are not included.

The lifespan of those commodities also has, beside those country- or region-specific consequences, an important effect on the carbon stocks. A category with high input rates (high efficiency) and a rather long lifespan must have a greater stock than a category with the same input but a shorter lifespan. The biggest stocks can be found in the categories with long lifespans like ‘building materials’, ‘other building materials’ and ‘furnishing’. These three categories gather usually more than 75% of all carbon stored in wood products. The following figure and table show the distribution of carbon in wood-based products for Europe and the sample countries and the development of those proportions over time. Even though the figures do not vary largely over time it must be noticed that there is an increasing stock in the total amount of wood products.

other building material 23% structural furnishing support material 8% 2% packing material 3% further long-life paper 14% 4% short-life paper 2% fuelwood building 2% materials 56%

Figure 4.4. Shares of different wood product categories in Europe under the business as usual (BaU) scenario in 1990. The total amount of carbon in wood products was 769 Tg C. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 47 , Germany, Norway and Portugal in , Germany, materials material products products of carbon building material support material paper paper [Tg C] [%] [%] [%] [%] [%] [%] [%] [%] 2025205020252050 847.8 870.2200020252050 58.3 49.1 58.3 52.020002025 62.22050 63.2 67.0 23.8 63.6 69.22000 24.22025 129.2 46.62050 134.4 47.9 6.5 137.2 48.5 21.8 6.3 22.22025 55.6 19.42050 57.4 25.2 22.3 6.3 57.4 1.9 25.6 23.7 6.0 1.9 25.9 44.6 6.7 24.0 2.6 47.2 14.5 6.4 23.8 2.5 48.6 3.0 14.3 6.2 24.2 2.8 7.7 3.3 59.2 26.1 1.2 6.7 2.5 3.2 58.2 26.8 1.1 6.5 2.3 26.9 1.1 1.7 4.6 6.0 4.0 1.1 1.7 4.3 5.7 3.7 1.0 24.2 4.1 5.4 3.7 24.9 1.9 9.4 3.9 1.8 1.0 8.8 3.7 1.9 6.5 1.0 8.5 3.6 1.7 6.5 1.6 2.0 4.3 1.1 6.2 1.9 4.0 1.1 5.4 1.9 3.9 1.7 5.1 2.0 1.7 2.2 1.9 8.2 2.0 1.8 7.2 2.0 2.4 6.7 0.7 2.5 0.7 5.6 0.7 4.9 3.6 4.6 3.7 1.4 1.2 1.8 1.1 1.8 0.6 0.6 Year Amount Total Building Other Furnishing Structural Packing Long life Short life Fuelwood Shares of wood products in proportion to the total amount of carbon stored in 2000, 2025 and 2050 for Europe, Austria, Finland Shares of wood products in proportion to the total amount carbon stored 2000, 2025 and 2050 for Europe, Europe 2000 794.7 57.0 23.6 7.2 2.1 2.7 3.5 1.9 2.0 AustriaFinland 2000Germany 43.4Norway 61.6Portugal 21.6 2000 7.1 14.7 3.3 58.5 2.8 1.2 24.9 1.1 7.8 1.3 1.7 2.2 2.9 1.5 0.5 Table 4.11. Table the Business as Usual (BaU) scenario. 48 Thies Eggers

4.3 CARBON FLOWS IN THE WOOD PRODUCT SECTOR

Beside the above mentioned stocks, several fluxes of carbon in the wood products sector occur. The first flux into these commodities is the flux of harvested timber into the pool of carbon for the wood processing industries. This flux varies from 0.3 to 1.6 Mg C ha-1 yr-1, depending on the natural settings and forest management in the countries (site class, tree species, felling level, etc.). In Tables 4.12 and 4.13 those fluxes are shown for the 5 sample countries and Europe in total. The figures represent 10-year averages in the period from 1981 to 1990, 2011 to 2020 and from 2041 to 2050 for both the business as usual (BaU) and the multi-functional scenario (MF).

Table 4.12. Carbon input into wood product carbon stocks in total [Tg C yr-1] and as relation per ha forest area [Mg C·ha-1 yr-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are historical FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1990. (BaU Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C] 3.4 9.7 11.4 2.4 2.2 86.5 per ha [Mg C ha-1] 1.2 0.5 1.1 0.3 1.5 0.7

2011–2020 total [Tg C] 3.0 10.2 8.6 2.7 1.4 78.4 per ha [Mg C ha-1] 1.0 0.5 0.9 0.4 0.9 0.6

2041–2050 total [Tg C] 3.0 10.2 8.7 2.7 1.4 78.1 per ha [Mg C ha-1] 1.0 0.5 0.9 0.4 0.9 0.6

Table 4.13. Carbon input into wood product carbon stocks in total [Tg C yr-1] and as relation per ha forest area [Mg C·ha-1 yr-1] as average figures from 1981 to 1990, 2011 to 2020 and 2041 to 2050 (where the data for 1981 to 1989 are historical FAOSTAT data and the other are modelled with EFISCEN) for Austria, Finland, Germany, Norway, Portugal and Europe. The figures for the first period include the storm damages from 1990. (MF Scenario)

Austria Finland Germany Norway Portugal Europe Forest area [Mha] 2.942 19.628 9.984 7.070 1.508 128.881

1981–1990 total [Tg C] 3.5 9.7 11.5 2.4 2.2 86.4 per ha [Mg C ha-1] 1.2 0.5 1.2 0.3 1.4 0.7

2011–2020 total [Tg C] 3.8 10.9 12.5 3.0 1.3 90.5 per ha [Mg C ha-1] 1.3 0.6 1.2 0.4 0.9 0.7

2041–2050 total [Tg C] 4.0 11.0 12.9 3.0 1.7 93.3 per ha [Mg C ha-1] 1.3 0.6 1.3 0.4 1.2 0.7 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 49

The carbon in harvested timber runs through several stages and storages until it is finally released again into the atmosphere. The fluxes of carbon are yearly processes whereas the stocks may sequester the carbon for some years to several decades. Figure 4.5 shows a flowchart of carbon through the EFISCEN wood product model with fluxes and stocks for Europe in 2000 under the business as usual scenario. The amount of carbon in removals o.b. are smaller than in Table 4.12 because in this table the storm damages of 1990 are included whereas the flowchart shows modelled data with ‘normal’ felling levels. Fluxes are indicated with and stocks are represented by boxes. The results for Austria, Finland, Germany, Norway, Portugal and Europe for both BaU and MF scenario are presented in Tables 4.14 to 4.15. Further flowcharts are printed in the Appendices. When looking at Table 4.16, showing the differences between the two scenarios it can be seen that even there are high changes in the fluxes, the stocks do not change in the same extent due to their magnitude. The changes in Austria and Germany are rather larger due to the applied forest management scenarios, where the felling levels are increasing significantly during the simulation period. Resulting from this there is an higher input into the model and consequently also higher product fluxes and stocks. The opposite effect can be seen for Portugal, where the applied forest management scenario results in decreasing stocks and fluxes.

forests atmosphere

removals o.b. recycling (from last year) 78 Tg C 26 Tg C

raw material 104 Tg C

process release decay 21 Tg C 6 Tg C production burning (incl. fuelwood) process 32 Tg C into products 83 Tg C waste disposal products in use discarded products 23 Tg C landfill 794 Tg C 81 Tg C 1121 Tg C

recycling (to next year) 26 Tg C

Figure 4.5. Flowchart of carbon fluxes and stocks in wood products for Europe in 2000 under the business as usual scenario. Fluxes are indicated with arrows; stocks with boxes. 50 Thies Eggers g C = 1 Mt C] 12 Austria Finland Germany Norway Portugal Europe ] for 2000 in Austria, Finland, Germany, Norway, Portugal, and Europe in the business as usual scenario of Norway, Austria, Finland, Germany, ] for 2000 in -1 + (7) – (8) 43.4 62.2 129.1 19.4 14.7 794.2 t-1 + (10) – (11) 38.6 157.8 153.3 35.5 22.8 1120.5 ] t-1 -1 Carbon stocks [Tg C] and carbon fluxes C yr Carbon stocks [Tg C] (1) Products in use = (1) Carbon fluxes [Tg C×yr (2) Landfill = (2) (3)(4)(5)(6) Removals o.b.(7) Recycled products (from last year)(8) Raw material = (3) + (4)(9) = (5) – (7) Process release (energy) (10) Carbon into products = (5) – (6)(11) Discarded products = (9) + (10) (12)(12) Burned products = (8) – (10) (12) disposal = (8) – (9) (12) Waste (13) Landfill release = (2) * 0.005(14) Recycled products (to next year) = (8) – (9) (10)(15) emissions into the atmosphere = (6) + (9) (11) Total Net-increase of wood product stock = (7) – (8) Net-increase of landfill stock = (10) – (11) 2.0 0.7 2.0 2.0 4.1 2.4 4.4 5.0 1.2 3.5 0.3 3.0 7.8 2.4 0.9 8.7 8.5 9.0 12.5 0.7 3.5 0.2 10.2 2.0 0.3 6.1 15.0 8.4 2.8 15.1 17.0 1.4 2.1 3.4 0.8 8.6 0.8 0.1 1.9 3.1 1.4 3.2 3.3 4.1 0.4 2.6 0.8 0.9 2.7 0.5 0.2 1.0 1.2 0.4 0.8 26.2 1.2 1.7 0.6 0.4 0.2 21.2 1.3 58.5 80.6 0.0 26.2 0.4 104.2 83.0 0.3 31.7 0.1 78.0 2.3 22.7 17.2 5.5 Table 4.14. Table EFISCEN wood product model. The amount of carbon released by burning fuelwood is included in flux (9). [1 Tg C = 10 The amount of carbon released by burning fuelwood is included in flux (9). [1 EFISCEN wood product model. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 51 g C = 1 Mt C] 12 Austria Finland Germany Norway Portugal Europe ] for 2000 in Austria, Finland, Germany, Norway, Portugal, and Europe in the multifunctional scenario of Norway, Austria, Finland, Germany, ] for 2000 in -1 + (7) – (8) 45.8 63.0 137.4 19.7 14.5 805.7 t-1 + (10) – (11) 39.1 158.1 154.9 35.6 22.6 1121.4 t-1 ] -1 [Tg C] [Tg C×yr Carbon stocks [Tg C] and carbon fluxes C yr Carbon stocks (1) Products in use = (1) (2) Landfill = (2) Carbon fluxes (3)(4)(5)(6) Removals o.b.(7) Recycled products (from last year)(8) Raw material = (3) + (4)(9) = (5) – (7) Process release (energy) (10) Carbon into products = (5) – (6)(11) Discarded products = (9) + (10) (12)(12) Burned products = (8) – (10) (12) disposal = (8) – (9) (12) Waste (13) Landfill release = (2) * 0.005(14) Recycled products (to next year) = (8) – (9) (10)(15) emissions into the atmosphere = (6) + (9) (11) Total Net-increase of wood product stock = (7) – (8) Net-increase of landfill stock = (10) – (11) 2.3 0.8 2.3 2.3 4.6 2.5 5.0 5.8 1.3 3.7 0.4 3.5 8.0 2.5 1.0 8.9 9.7 9.3 13.0 0.8 3.6 0.2 10.6 2.7 0.4 7.2 17.2 9.9 2.9 18.5 21.2 1.4 2.1 3.8 0.8 11.5 0.9 1.3 2.0 3.2 1.4 3.5 3.4 4.2 0.4 2.7 0.8 0.9 2.8 0.5 0.2 1.0 1.1 0.4 0.8 27.8 1.2 1.7 0.7 0.4 0.2 1.4 22.5 60.5 83.8 0.1 28.1 0.4 111.3 88.8 0.3 32.5 83.5 0.1 4.9 23.2 17.7 5.5 Table 4.15. Table EFISCEN wood product model. The amount of carbon released by burning fuelwood is included in flux (9). [1 Tg C = 10 The amount of carbon released by burning fuelwood is included in flux (9). [1 EFISCEN wood product model. 52 Thies Eggers multifunctional scenario to the 13 100 112 # . -1 Austria Finland Germany Norway Portugal Europe to 1.3 Tg C.yr to 1.3 -1 + (7) – (8) 6 1 6 1 -1 1 t-1 + (10) – (11) 1 0 1 0 -1 0 t-1 Changes in carbon stocks [%] and carbon fluxes [%] for 2000 in Austria, Finland, Germany, Norway, Portugal, and Europe in the Norway, Austria, Finland, Germany, Changes in carbon stocks [%] and fluxes for 2000 This high percentage results from an increase from 0.1 Tg C×yr This high percentage results from an increase 0.1 Carbon stocks (1) Products in use = (1) # Carbon fluxes (3)(4)(5)(6) Removals o.b.(7) Recycled products (from last year)(8) Raw material = (3) + (4)(9) = (5) – (7) Process release (energy) (10) Carbon into products = (5) – (6)(11) Discarded products = (9) + (10) (12)(12) Burned products = (8) – (10) (12) disposal = (8) – (9) (12) Waste (13) Landfill release = (2) * 0.005(14) Recycled products (to next year) = (8) – (9) (10) emissions into the atmosphere = (6) + (9) (11) Total Net-increase of wood product stock = (7) – (8) 12 15 11 13 11 14 3 14 11 54 16 4 3 9 3 3 4 15 4 0 2 36 34 4 19 18 15 3 23 1378 24 3 13 0 34 6 3 10 4 3 3 -3 4 1 1 4 4 0 3 -3 0 0 6 -5 1 0 2 6 -3 4 4 7 7 2 7 0 7 2 0 (2) Landfill = (2) (15) Net-increase of landfill stock = (10) – (11) 11 3 12 3 -3 3 Table 4.16. Table base scenario of the EFISCEN wood product model. The amount of carbon released by burning fuelwood is included in flux (9). base scenario of the EFISCEN wood product model. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 53

4.4 AVERAGE LIFESPAN OF CARBON IN WOOD PRODUCTS

One possible criterion to measure the amount of carbon in wood products is the average lifespan of carbon in those commodities. This figure represents the ratio of the yearly input of carbon (harvested carbon) to the current carbon stock of wood products.

CS = t CLt (4.1) CI t where CLt = average lifespan of carbon in wood products during the period t,

CSt = average carbon stock of wood products in during period t,.

CIt = average carbon input to the wood product stock during the period t, and T = the time period.

The average between 1981 and 1990 all over the focused countries is about 8.6 years, varying from 14 years in Romania, to 5 years in FYR Macedonia. All details can be found in Table 4.17.

One has to take into account that in our calculations the current stock excludes the trade of wood products and so the current stocks might be over- (net-exporting country) or underestimated (net-importing country) and also the assumed lifespans and parameters do effect on the carbon pools. Countries with a high production of short lifespan wood products (e.g. the Nordic countries with their pulp production) do have shorter lifespan as those countries with a large production of long-life products (e.g. Austria, Germany having a large sawmilling industry). So the presented figures result from (i) the harvest levels, (ii) the structure of the model (carbon accounting approach), and (iii) the parameterisation of the wood processing industries. But with these figures a rough estimation of the actual carbon stock in wood products is possible by multiplying the average carbon lifespan with the annually harvest level of carbon.

Table 4.17. Average lifespan of carbon in wood products in the studied countries during the period from 1980 to 1990.

Country Carbon-lifespan Country Carbon-lifespan Country Carbon-lifespan [years] [years] [years]

Albania 9 Germany 11 Portugal 7 Austria 11 Hungary 6 Romania 14 Belgium 9 Ireland 6 Slovakia 7 Bulgaria 7 Italy 7 Slovenia 9 Croatia 11 Luxembourg 9 Spain 7 Czech Republic 9 FYR Macedonia 5 Sweden 6 Denmark 10 Netherlands 10 Switzerland 11 Finland 6 Norway 7 United Kingdom 9 France 9 Poland 9 Yugoslavia 13 54 Thies Eggers

4.5 EU REGULATION ON LANDFILL DISPOSAL

The effects of the EU regulations on the landfill disposal of organic material can be seen in several fluxes of the subcategories due to the new distribution of wooden disposals. No products, which would have been normally disposed to landfills, are recycled to the categories ‘fuelwood’, ‘building material’, ‘furnishing’ and ‘long life paper products’ and thus no changes in the carbon pools of these categories take place. The only options for recycling are the categories of ‘packing material’, ‘other building material’, ‘structural support materials’ and ‘short life paper products’ and thus also the total carbon stock in wood products does change under this scenario. These recycling possibilities are the normal options, which are also used in the other scenarios and the forest management is the same as on the business as usual scenario. By a larger re-use of wooden waste instead of dumping it to landfills the carbon stocks in landfills is decreasing over time substantially and the carbon stock in wood products in use is increasing as well as the amount of carbon burned for energy production.

When talking about ‘waste’, it should be kept in mind that this amount of wood cannot be used for the initial production process anymore and has to be transferred to another process. These side-products are again raw material for e.g. energy production or “less quality” products and thus cannot be ‘waste’, i.e. the wood processing industry is utilising approx. 100% of the raw material (roundwood) to primary or secondary products.

Table 4.18. shows that the categories of use with a short lifespans do already reach quite early (2015) a steady state in their reduction of disposed carbon into landfills whereas those with a higher lifespan still have an increasing change in their carbon flow into landfills. Due to the settings in the EU regulation no large changes will occur before 2000. In 2000, just 1332 Gg C are reused for recycling or energy production. This figure rises in 2010 to 6986 Gg C, in 2020 to 10289 Gg C, in 2030 to 11718 Gg C, in 2040 to 12578 Gg C and reaches

Table 4.18. Yearly amount of carbon [Gg C·yr-1] from the different usage categories in the EFISCEN wood product model, which is not disposed to landfills as a consequence of the EU landfill regulations for Europe, where the regulations were applied for all countries (EU and non-EU countries).

Year Building Other build. Structural Furnishing Packing Long life Short life m a t e r i a l s materials paper products

2000 9 45 13 333 480 122 331 2005 33 184 53 655 955 411 627 2010 92 524 149 1521 2225 973 1503 2015 175 1028 290 1836 2704 1470 1809 2020 272 1601 450 1813 2701 1680 1773 2025 378 2142 602 1790 2695 1717 1757 2030 492 2584 728 1769 2684 1715 1747 2035 612 2898 820 1758 2686 1714 1748 2040 737 3093 880 1742 2675 1710 1741 2045 864 3200 917 1738 2678 1709 1743 2050 992 3249 940 1746 2695 1717 1753 2055 1117 3264 953 1743 2695 1720 1753 2060 1237 3259 961 1739 2690 1718 1750 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 55

- 15.0

10.0

5.0

0.0 1990 2000 2010 2020 2030 2040 2050 -5.0

-10.0 ] in comparison to BaU scenario 1

changes of fluxes and stocks [Tg C yr -15.0 year

recycling energy burning flow into landfills products in use landfill release Figure 4.6. Yearly changes of carbon stocks and carbon fluxes [Tg C·yr-1] of the EU landfill scenario in comparison to the BaU scenario for Europe.

Table 4.19. Cumulative annual changes in the wood product and landfill stocks as well as in the amount of carbon burned for energy production under the EU landfill scenario for 2000, 2010, 2020, 2030, 2040 and 2050 in comparison to the business as usual scenario. The amount, which is put less to the landfill stock is distributed to other products in use or burned for energy production. In case figures do not add up, rounding errors took place.

Cumulative changes in the carbon stocks [Tg C yr-1] 2000 2010 2020 2030 2040 2050 Austria Wood product stock 0.06 0.46 1.09 1.77 2.52 3.23 Landfill stock -0.14 -1.53 -4.73 -8.72 -13.15 -17.75 Energy burning 0.08 1.07 3.64 6.95 10.64 14.51

Finland Wood product stock 0.18 1.21 2.26 3.20 4.26 5.25 Landfill stock -0.55 -6.20 -18.69 -32.59 -46.71 -60.61 Energy burning 0.38 5.00 16.43 29.39 42.45 55.36

Germany Wood product stock 0.22 1.72 3.90 5.94 8.07 10.03 Landfill stock -0.53 -5.57 -16.82 -30.30 -44.86 -59.67 Energy burning 0.31 3.86 12.92 24.36 36.79 49.64

Norway Wood product stock 0.06 0.44 0.89 1.23 1.61 1.96 Landfill stock -0.16 -1.80 -5.41 -9.45 -13.61 -17.74 Energy burning 0.10 1.35 4.52 8.22 12.00 15.77

Portugal Wood product stock 0.02 0.16 0.33 0.53 0.75 0.95 Landfill stock -0.06 -0.73 -2.32 -4.15 -6.10 -8.05 Energy burning 0.04 0.58 1.98 3.62 5.35 7.10

Europe Wood product stock 1.29 9.34 19.94 31.46 44.57 56.97 Landfill stock -3.85 -42.63 -130.14 -232.59 -340.98 -450.27 Energy burning 2.54 33.23 110.13 201.02 296.29 393.15 56 Thies Eggers in 2050 the amount of 13092 Gg C, which is not disposed into landfills. Half of this amount is assumed to be recycled and the other half in used as biofuel for energy production. By such kind of reuse at least half of the carbon, which would usually be stored in the landfill stock is released immediately into the atmosphere when the disposed wood products are burned. First this might give a wrong impression, how wood products can help to work for the mitigation of climate change. But when one assumes that this energy would have been produced by using fossil fuels it gets clear that wooden waste is a valuable energy source and a potential substitute for fossil fuels. These results will be presented in the following chapter.

The changes in the EU regulations on the disposal of organic waste take place in 3 time- steps as already described in Chapter 3.4.3. These are 2006, 2009 and 2015 until when the reductions had to effect the waste treatment. Several countries do have of course earlier steps for the fulfilment of their reduction-percentages or even other aims do reduce their disposal of organic materials in higher terms. So the following figure shows the theoretical effect of the EU regulations in comparison to the business as usual scenario. Due to the re- recycling of wood-based products the flux of recycled products does even extent the negative flux of carbon into landfills. The stock of wooden products in use is just increasing with a little more than 1 Tg C per year owing to the mostly rather short lifespan of recycled products and the huge amount of wooden disposal, which are used to produce energy. The release of gaseous carbon emissions from landfills starts to decrease slowly but significant due to a smaller input of organic (wooden) matters into landfills. By 2050 it has already reached the yearly reduction of 2 Tg C.

Table 4.19 shows the cumulative changes for the landfill scenario within the settings of the business as usual scenario, which is assumed to be the normal base scenario in terms of forest management. By 2050 more than 450 Tg of carbon can be used for energy production (393 Tg C) and re-used as secondary raw materials (57 Tg C) for other purposes.

4.6 EQUIVALENT OF FOSSIL FUELS FOR ALL BURNED WOOD PRODUCTS

In this chapter we will have a brief look on energy equivalents of carbon from wood products. Discarded wood products do form an energy source, which gains more and more importance globally. The energy content of fuelwood is about 15 MJ·kg-1 (Hall et al. 1994), Leach and Gowen (1987) give figures for wood with different moisture contents, and their -1 -1 figures vary from 10.9 MJ·kg (40% moisture), over 15.5 MJ·kg (20% moisture) and 16.6 MJ·kg-1 (15% moisture) to 20.6 MJ·kg-1 (0% moisture). Paper usually has, owing to its higher density, higher energy equivalents than wood alone. Alakangas (2000) presents in her report figures for different paper grades, showing energy contents for normal moisture content from 12.2 MJ·kg-1 to 26.3 MJ·kg-1. The mean value is about 17 MJ·kg-1 to 18 MJ·kg-1 for the most common paper grades (newspaper, wrapping paper, paper boards). As the carbon fluxes from process release and burning products for energy production in the EFISCEN wood product model are aggregated figures in carbon units, the following energy equivalents are calculated using a energy value of 16 MJ·kg-1 biomass, a carbon content of 50% in the biomass and the equivalent of 1 MJ to 0.2778 kWh (2 Gg biomass = 1 Gg carbon = 32 TJ·Gg C-1 = 8.8896 GWh·Gg C-1). The oil-equivalents (oe) had been calculated by assuming an equivalent of 2.388·10-5 Mtoe from 1 TJ (IEA 2001). The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 57

Table 4.20. Energy- and oil-equivalents of carbon released during production process and energy burning of fuelwood and recycled products. Fuelwood is included in the category of energy from products. Business as usual scenario.

Year Process Energy from Sum Energy-equivalents Oil- release products equivalent [Gg C] [Gg C] [Gg C] [PJ] [TWh] [Mtoe] Europe 2000 21213.6 31719.6 52933.2 1693.9 470.6 40.4 2025 21245.6 32537.0 53782.6 1721.0 478.1 41.1 2050 21323.0 32824.3 54147.3 1732.7 481.3 41.4 Austria 2000 649.5 1175.9 1825.4 58.4 16.2 1.4 2025 653.6 1246.4 1900.1 60.8 16.9 1.5 2050 653.7 1283.6 1937.3 62.0 17.2 1.5 Finland 2000 3543.1 3491.4 7034.5 225.1 62.5 5.4 2025 3551.3 3583.9 7135.3 228.3 63.4 5.5 2050 3550.8 3608.0 7158.8 229.1 63.6 5.5 Germany 2000 1989.9 3359.2 5349.1 171.2 47.6 4.1 2025 2016.6 3414.5 5431.1 173.8 48.3 4.2 2050 2016.7 3466.4 5483.1 175.5 48.7 4.2 Norway 2000 823.8 922.0 1745.8 55.9 15.5 1.3 2025 825.1 955.7 1780.8 57.0 15.8 1.4 2050 820.8 971.1 1792.0 57.3 15.9 1.4 Portugal 2000 502.0 388.7 890.7 28.5 7.9 0.7 2025 541.7 425.3 967.0 30.9 8.6 0.7 2050 530.6 437.2 967.8 31.0 8.6 0.7

Table 4.21. Energy- and oil-equivalents of carbon released during production process and energy burning of fuelwood and recycled products. Fuelwood is included in the category of energy from products. Multi- functional scenario.

Year Process Energy from Sum Energy-equivalents Oil- release products equivalent [Gg C] [Gg C] [Gg C] [PJ] [TWh] [Mtoe] Europe 2000 22523.5 32473.5 54996.9 1759.9 488.9 42.0 2025 24955.9 37740.1 62696.0 2006.3 557.3 47.9 2050 24736.0 38756.9 63492.9 2031.8 564.4 48.5 Austria 2000 750.3 1312.8 2063.0 66.0 18.3 1.6 2025 887.9 1533.3 2421.2 77.5 21.5 1.9 2050 842.7 1635.7 2478.4 79.3 22.0 1.9 Finland 2000 3690.8 3567.6 7258.4 232.3 64.5 5.5 2025 3860.6 3752.5 7613.0 243.6 67.7 5.8 2050 3859.9 3854.0 7713.9 246.8 68.6 5.9 Germany 2000 2670.5 3810.7 6481.2 207.4 57.6 5.0 2025 2997.8 4749.9 7747.7 247.9 68.9 5.9 2050 2983.8 4981.1 7964.9 254.9 70.8 6.1 Norway 2000 865.1 933.3 1798.3 57.5 16.0 1.4 2025 906.8 1075.9 1982.7 63.4 17.6 1.5 2050 881.8 1107.7 1989.5 63.7 17.7 1.5 Portugal 2000 515.0 372.8 887.8 28.4 7.9 0.7 2025 677.1 419.1 1096.2 35.1 9.7 0.8 2050 676.6 534.6 1211.2 38.8 10.8 0.9 58 Thies Eggers

The figures in Tables 4.20 and 4.21 show that with wooden ‘waste’ as side-products during the production process and recycled wood products a certain amount of energy is connected with this renewable energy source. Once again the figures represent the structure of the wood processing industries (namely the efficiency of the production process) and the general input of wood to the production process. For example Finland shows the highest country-figures. This results first of all from a high harvest level and a large pulp- and paper producing industry with quite low efficiency levels and this high amounts of side products, which are burned to generate energy.

The oil-equivalent for Europe might be roughly from 40 to 48 Mt. All the presented figures are estimates assuming the mentioned conversion factors and a high efficiency while burning. The process releases should have high efficiencies as the wood is burned mostly in huge power plants connected to or pulpmills (e.g. the burning of sawdust or black ). In addition is the energy from products, which also includes the use of fuelwood, potentially produced in smaller heating and burning devices with lower efficiency rates.

The comparison of the different scenarios in the view of energy equivalents is presented in Table 4.22 for the multi-functional scenario in comparison to the business as usual scenario and the landfill business as usual scenario in comparison to the business as usual scenario. There is no real trend to be seen in this comparison. Some countries produce more energy in the multi-functional scenario (e.g. Austria and Germany) and others have significantly higher energy outputs in the landfill scenario (e.g. Finland and Norway). This is dependent on the input rates of either roundwood (multifunctional scenario) or recycled products (landfill scenario).

The relation of these energy- or oil-equivalents to the country’s energy supply or electricity consumption varies from country to country. This is linked to the amount of carbon, which is released during production process, the later use of carbon while burning discarded wood products, and the energy consumption in each country. Data on energy supply in terms of Mt oil-equivalents (Mtoe) and electricity consumption (TWh) are available from the International Energy Agency (IEA), which is an autonomous agency linked with the Organisation for Economic Co-operation and Development (OECD). The following tables (Table 4.22 and Table 4.23) show the ratio of energy supply (Mtoe) and electricity consumption (TWh) of the sample countries (IEA 2001) to the potential energy or electricity gained from energy burning of wood products. The comparable high percentages for Austria and Finland in both tables result once again from the high energy respectively electricity equivalent obtained from burning wood products and energy production from side-products (process release). The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 59

Table 4.22. Changes of energy as equivalents for carbon released while burning side-products and recycled wood-based products in-between the multi-functional (MF) and the business as usual (BaU) scenario (left columns) and the landfill BaU scenario and the BaU scenario (right columns).

Year MF - BaU LF BaU – BaU PJ TWh Mtoe PJ TWh Mtoe Europe 2000 66.0 18.4 1.6 31.0 8.6 0.7 2025 285.2 79.2 6.8 318.0 88.3 7.6 2050 299.1 83.1 7.1 381.6 106.0 9.1

Austria 2000 7.6 2.1 0.2 1.0 0.3 0.0 2025 16.7 4.6 0.4 11.6 3.2 0.3 2050 17.3 4.8 0.4 15.4 4.3 0.4

Finland 2000 7.2 2.0 0.2 4.6 1.3 0.1 2025 15.3 4.3 0.4 45.4 12.6 1.1 2050 17.8 4.9 0.4 50.4 14.0 1.2

Germany 2000 36.2 10.1 0.9 3.7 1.0 0.1 2025 74.1 20.6 1.8 40.1 11.1 1.0 2050 79.4 22.1 1.9 50.7 14.1 1.2

Norway 2000 1.7 0.5 0.0 1.2 0.4 0.0 2025 6.5 1.8 0.2 13.0 3.6 0.3 2050 6.3 1.8 0.2 14.8 4.1 0.4

Portugal 2000 -0.1 0.0 0.0 0.5 0.1 0.0 2025 4.1 1.2 0.1 5.6 1.6 0.1 2050 7.8 2.2 0.2 6.8 1.9 0.2

Table 4.23. Ratio of the potential energy gained from burning of side products and discarded products in 2000 to the total primary energy supply in 1998 for Austria, Finland, Germany, Norway, and Portugal in the 3 applied scenarios (BaU, MF, LF BaU).

Austria Finland Germany Norway Portugal

Total primary energy supply Mtoe 28.81 33.46 344.51 25.42 21.85

Ratio of Mtoe from products, BaU % 4.8 16.1 1.2 5.2 3.1 Ratio of Mtoe from products, MF % 5.5 16.6 1.4 5.4 3.1 Ratio of Mtoe from products, LF BaU % 4.9 16.4 1.2 5.4 3.2

Table 4.24. Ratio of the potential electricity gained from burning of side products and discarded products in 2000 to the electricity consumption in 1998 for Austria, Finland, Germany, Norway, and Portugal in the 3 applied scenarios (BaU, MF, LF BaU).

Austria Finland Germany Norway Portugal Electricity consumption TWh 53.93 76.51 531.64 111.79 36.02 Ratio of TWh from products, BaU % 30.1 81.7 8.9 13.9 22.0 Ratio of TWh from products, MF % 34.0 84.3 10.8 14.3 21.9 Ratio of TWh from products, LF BaU % 30.6 83.4 9.1 14.2 22.4

5. DISCUSSION AND CONCLUSIONS

Some of the results, which are presented in Chapter 4, were already discussed respectively commented in that chapter. This chapter will be divided in 3 parts. First the applied approach will be discussed, then the results for the sample countries will be evaluated with results from other studies on carbon stocks and flows of wood-based products and finally a general outlook for this kind of model and conclusions of this study will be made.

5.1 EVALUATION OF THE APPLIED APPROACH

The results of this study represent carbon stocks and fluxes of the IPCC stock-change approach with the exclusion of trade. The possible IPCC approaches were presented earlier in this paper and for more details refer to Brown et al. (1998). The applied carbon counting approach neglects the trade of roundwood and wood products and thus all produced products are counted for the producing country. This results in an overestimation for net- exporting countries and in an underestimation for net-importing countries in means of roundwood and wood-based products. But never the less this approach is to be favoured in comparison to the IPCC default approach where wood products are regarded with a lifespan of 1 year, meaning that the storage capacity of long-living wood products is neglected. The best and also most realistic approach would be the ‘real’ stock-change approach where the trade of roundwood and wood-based products is implemented. This would show rather realistic flows and stocks in the forest sector. At the moment, in the applied models, EFISCEN and the coupled wood product model, this feature is not implemented but it is aimed to future model-versions to apply this important factor.

The differences between the mentioned approached were shown by Jäkel et al. (2001). In this paper, which also presents results from the European Study of Carbon in the Ocean, Biosphere and Atmosphere (ESCOBA, see Jäkel et al. 1999), they show a comparison of three different methods for carbon accounting in the forest sector. The following Table 5.1 is taken from this paper, showing the calculation of carbon sources and sinks from forestry and forest products for three different approaches in Austria and Germany: the 1995 IPCC approach (assuming that the carbon stock change in wood products is negligible and it considers only the stock change in a country’s forest), the atmospheric-flow approach (assessing the net of carbon flows to and from the atmosphere) and the stock-change approach with the exclusion of trade (considering the change of wood product carbon stocks). The differences to the stock-change approach applied in this study are that in the ESCOBA carbon emissions from wood harvesting and processing activities are considered and the wood products are only divided in two groups (<5 years lifespan and >5 years lifespan).

The results presented in Table 5.1 were calculated by using also FAOSTAT data on forest products and a forest growth simulator (Frankfurt Biosphere Model, FBM) coupled with a wood product model (Graz/Oak Ridge Carbon Accounting Model, GORCAM). The authors conclude that these kinds of calculations can bring out misleading results. First of all the model input must be considered carefully. Natural hazards like wind trough and forest pests can lead to higher roundwood production than usual (e.g. in 1990 the roundwood production in Germany was nearly twice as high as normal due to storm damages). So it is suggested to use mean values of for example 5-year periods. The second aspect is the applied carbon 62 Thies Eggers counting approach. Table 5.1 shows the differences for the whole forest sector. When looking at the figures it can clearly be seen that the 1995 IPCC approach is not favourable for both countries. The flow method favours net exporters of wood over net importers of wood. Germany, a net wood importer, is better off with the stock-change method than with the flow method, whereas Austria, a net wood exported, is better off with the flow method.

Table 5.1. Calculation of carbon sources and sinks [Tg C] from forestry and forest products for three different carbon counting approaches for Austria in 1990 and Germany in 1989 (Jäkel et al. 2001).

1995 IPCC Atmospheric-flow Stock-change approach with approach approach the exclusion of trade Germany Austria Germany Austria Germany Austria

Roundwood production (-) 8.78 3.87 8.78 3.87 8.78 3.87

Roundwood-trade (import – export) (-) - - -0.50 0.87 - -

Slash left in forest (-) 3.46 1.04 3.46 1.04 3.46 1.04

Commodity use for >5 years (+) - - 7.24 1.14 7.24 1.14

Commodity-trade (import – export) (-) - - 1.66 -1.44 - -

Inherited Emissions (-) - - 3.16 0.67 3.16 0.67

C uptake in the forests (+) 19.05 8.90 19.05 8.90 19.05 8.90

Total sink 6.81 4.00 9.73 5.04 10.89 4.47

5.2 VALUATION OF THE COUNTRY RESULTS

This chapter will give a valuation on the calculated results for the chosen sample countries Austria, Finland, Germany, Norway and Portugal. Like mentioned in the introduction these five countries were chosen because recent studies on national wood product carbon budgets are available. Most of these studies are also model-based and for the others the carbon stocks are estimated in another way. Real inventories on carbon stocks of wood and wood- based products are very rare. In this case only the study of Pingoud et al. (2000) for Finland included recent inventory results. This kind of research is very important to validate models on wood products, as this is the only available possibility to compare gained model results. Up to now it is difficult to include risk factors into the modelling of both forest resources and wood products. Whereas the risk modelling for forests is already quite advanced, inventories of carbon stocks in wood products can show uncertainties and risks in this sector. Also the trade of both roundwood and wood products has an important effect on the carbon stocks. Including all these mentioned factors in forest resource and wood products The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 63 models is an important task for the future and needs to be further developed in order to reach proper results from modelling.

5.2.1 Finland

Available studies for Finland are the ones from Pingoud et al. (1996, 2000), Jäkel at al. (1999), and the one from Karjalainen et al. (1994), which was also the basis for this research. The latter one used the same wood product model with nearly the same model- structure, but including other lifespans (see Table 3.5) and also emissions of fossil fuels from harvesting. The studies of Pingoud et al. are based on the inventories on some wood products in Finland in 1980, 1990 and 1995 and on modelling with the same model that has also been used by the above mentioned study of Karjalainen et al. (1994) and other studies like Pussinen et al. (1997).

All these studies show rather same results as this study due to the similar model approach. Karjalainen et al. (1994) used a slightly smaller input of carbon to the wood products model. They used constant 9.89 Tg C whereas in this study the input was about 10.02 Tg C and increasing to 10.17 Tg C in the simulation period in BaU and to 11.01 Tg C in the MF scenario. As the efficiency parameters and model structure are the same or similar the study leads, as one can expect, to comparable results. Pingoud et al. (1996) estimated the total stock of products in use for 1990 from 40 – 50 Tg C based on the product inventories. The results of this study show a higher total carbon stock with 59 Tg C for the same year. Also the stock in landfills, which was estimated by Pingoud (1996) to 70–90 Tg C is in this study much higher (137 Tg C). Possible causes for these dissimilarities are different model structures and other recycling options. Jäkel et al. (1999) calculated for 1990 about 51 Tg C to be stored in long-lived products rising to 65 Tg C in 2050.

5.2.2 Germany

A very extensive and often cited study for carbon budgets of the German forest sector is the study by Burschel et al. (1993). They looked at the forest sector in various ways and one chapter deals also with wood products and carbon sequestration and the use of wood in mitigation of CO2 emissions. They stated a carbon stock in wood products of 128 Tg C with an annual increment of 1.1 Tg C, which shows that the C-storage in wood-based products approaches an certain equilibrium. This storage is divided in three major categories: 89 Tg C in construction timber, 34 Tg C in furnishing and 5 Tg C in paper products, packing materials as well as fuelwood. These figures were calculated by assuming certain amounts of wood in each household and then multiplying this figure with the total amount of households in Germany.

The comparability of Burschel’s results and the results for Germany from this study is rather high. This research calculates for Germany a total carbon stock of products in use 131 Tg C compared to 128 Tg C in the study of Burschel et al. But when looking at the results in more detail the carbon stocks in the categories vary more largely (see Table 5.2).

The annual increment in the wood product stock in this study in even lower than Burschel et al. estimate. They assumed it to be around 1.1 Tg C·yr-1 whereas in the business as usual scenario of this study the range varies from 0.2 to 0.04 Tg C·yr-1, which also shows that a certain equilibrium is reached. 64 Thies Eggers

Table 5.2. Comparison of carbon stocks in wood products between the study of Burschel et al. (1993) and the results from this study, where some categories had been aggregated according to their usage to correspond with the categories of Burschel et al.

Burschel et al. (1993) LTEEF-II (this study) Construction timber 89 98 Furnishing and structural support 34 18 Paper, packing and fuelwood 5 15 Total 128 131

Another study, which presents, among others, results for Germany is the ESCOBA (Jäkel et al. 1999). The model structure of this study was already described in Chapter 5.1. The carbon counting method is the same as in this study, namely the stock-change approach with the exclusion of trade. As the lifespans in the ESCOBA are little different to the ones used in this study, the results are to be seen in context as well as that products in use and abundant products in landfills are included in the category of long-lived products. This leads in 2000 to a carbon stock in wood products of 274 Tg C compared to a stock of 282 Tg C (129 Tg C in products in use + 153 Tg C in products in landfills) in 2000 in this study. For 2050 Jäkel et al. (1999) assume more than 382 Tg C to be stored in long-lived products. Within this study the stock will be 399 Tg C (137 Tg C + 262 Tg C) in 2050.

5.2.3 Austria

The correspondence of the results for Germany of the ESCOBA and this model do not occur in Austria even though both countries have a rather similar structure in the wood processing industry. The ESCOBA calculates for 2000 31 Tg C and in 2050 59 Tg C to be stored in long-lived products. In 2000 the model applied in this study results to 43 Tg C in products in use plus 38 Tg C in products in landfills and shows 52 Tg C plus 74 Tg C in 2050. From the results it is not possible to say, where the main discrepancies take place. It might be either in the input or in the parameterisation.

5.2.4 Norway

Gjesdal et al. (1996) estimated on the basis of available statistics and expert judgements the carbon budget for wood products in Norway. In their approach they used a similar method like Burschel et al. (1993), namely assessing the amount of carbon stored in different kind of households and which is needed for new . By this they stated a wood products carbon reservoir of 9.2 Tg C (buildings, , paper and waste) and an additional reservoir of 0.4 Tg C in textiles. The pool of waste (0.7 Tg C) contained also carbon from discarded textiles.

This pool is only 60% of the one, which was calculated in our study (15.7 Tg C). But Norway is a net exporting country of wood products and this is regarded within the Norwegian study whereas our approach does not regard the trade of wood-based products. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 65

5.2.5 Portugal

The same as for Austria applies for Portugal as well. The available studies show rather large variations in the results for the carbon stocks on wood products. In 2000 ESCOBA concluded in a 13 Tg C reservoir of long-lived products and in 2050 to 21 Tg C, whereas much higher results are achieved within our calculations 15 Tg C plus 23 Tg C in 2000 and 14 Tg C plus 37 Tg C in 2050. Also here the question why these high discrepancies occur cannot be answered at this state of research.

5.3 OUTLOOK AND CONCLUSIONS

This study has shown several aspects of the future development of the European wood product carbon budget in general and in detail for the five sample countries Austria, Finland, Germany, Norway, and Portugal. These predictions are based on historical data and include two forest management scenarios and one possible scenario for the treatment of discarded wood products in landfills.

The valuation and comparison of the results on wood-based products carbon stocks show that this kind of research is still on its way to a harmonisation of the different model approaches. Also the various carbon counting approaches, which can be applied to report under the UNFCCC lead already for one country to a variation of possible carbon stocks depending on how carbon stocks and fluxes are accounted (see Table 5.1). This makes a direct comparison among countries more difficult and needs to be regarded, when looking at results from different approaches or studies.

This study shows that the applied wood product model coupled with the EFISCEN is feasible to do predictions on the wood-based product budget for at least several decades. Nabuurs et al. (2000) already did the validation of the EFISCEN, whereas the validation of the coupled wood product model is still a task for future research. The problem for such validation is the need of having comparable data, which must be gathered by inventories on wood and wood-based products in households and other storage. But this kind of data is difficult to gather and also without such a validation the results look promising.

The present calculations are still tentative ones and include, as mentioned before, many uncertainties and simplifications, even though the amount of C sequestered in forest growth and stored in stemwood is rather accurately known and the future predictions are reliable. For example, the exact amount of wood-based products in use is not known nor the amount of wood-based products, which is disposed in landfills or burned for energy production. This makes it difficult to compare the total sizes of the carbon reservoirs in the forest sector. Furthermore, the estimates of lifespan for the different wood products and usage categories could be inaccurate just like the recycling options and the decay rates for landfilled wood products. If products are recycled, most of the C will be kept in use and thus stored for a longer time, but the C will be released directly to the atmosphere when the products are burned. Finally the energy, which is produced by this kind of final treatment, is also dependent on the scale and facilities of the power plant and the kind of wood-based product, which is incinerated.

6. ACKNOWLEDGEMENTS

This study was performed as part of the EU funded LTEEF-II project “Long-term regional effects of climate change on European forests: impact assessment and consequences for carbon budgets” (ENV4-CT97-0577, DG 12-EHKN). European Forest Institute (EFI) in Joensuu, Finland granted further research by a 3-month EFI-Member-Scholarship.

I have really appreciated the support from my supervisors. Prof. Dr. Klaus von Gadow of the Institute of Forest Resource Management, Faculty of Forest Science and at the Georg-August-University in Göttingen supported me with kind counsels and annotations throughout my studies and especially with the planning and preparations for my several stays in Finland.

My special thanks go to my second supervisor Dr. Timo Karjalainen, who is the head of the research area of Forest Ecology and Management at the EFI. His helpful advice and comments on my Master’s thesis and studies in general were of significant influence on my further professional career. The research carried out by Karjalainen et al. (1994) on the role of wood-based products in absorbing atmospheric carbon in Finland has been the inspiration for this study.

In addition, I would like to thank the whole staff at EFI for having such a nice and fruitful time at the institute, in Joensuu and in Finland. In particular I would like to thank Mr. Ari Pussinen of EFI, who did the modelling and implementations of the new features in the wood product model and Mr. Gert-Jan Nabuurs of ALTERRA in Wageningen on his comments and explanations on EFISCEN. Additional information was provided by Mr. Jari Liski of the University of Helsinki, Mr. Wolfgang Schopfhauser of the Confederation of European Paper Industries (CEPI) in Brussels, Mr. Kim Pingoud of the Technical Research Centre of Finland (VTT Energy) in Helsinki, and Mr. Bernhard Schlamadinger of Joanneum Research, Graz. Also, my special thanks to Ms. Minna Korhonen who helped me with the final layout of this thesis and her baby daughter Aino who let her.

Last but not least I would like to mention my parents and my family who all supported me during my studies. This also goes to many friends and colleagues, which I have met during that time.

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Noble, J. J., T. Nunez-McNally and B. Tansel (1989). The effects of mass-transfer on landfill stabilization rates. In: 43rd Purdue Industrial Waste Conference Proceedings, Survey, Estimate. N.N. (eds.). N.N., Chelsea (MI): pp. 153–159.

Obersteiner, M. (1999). Carbon Budget of the Forest Industry of the Russian Federation: 1928- 2012. IIASA, Laxenburg: 31 p.

Päivinen, R. and G.-J. Nabuurs (1997). Scenario modelling for European forests as a tool for assessing criteria and indications for sustainable forest management. In: XI . Part G, Session 33: Forestry Sector Planning, Antalya: pp. 291 (summary).

Päivinen, R., G.-J. Nabuurs, A. V. Lioubimow and K. Kuusela (1999). The state, utilisation and possible future development of Leningrad region forests. European Forest Institute (EFI), Joensuu: 59 p.

Pingoud, K., A. Perälä and A. Pussinen (2000). Inventorying and modelling of carbon dynamics in wood products. Proceedings of: Bioenergy for mitigation of CO2 emissions: to power, transportation and industrial sectors in Gatlinburg, Joanneum Research: pp. 125–140.

Pingoud, K., I. Savolainen and H. Seppälä (1996). Greenhouse impact of the Finnish forest sector including forest products and waste management. Ambio 25(5): pp. 318–326.

Pussinen, A., M.-J. Schelhaas, E. Verkaik, E. Heikkinen, J. Liski, R. Päivinen and G.-J. Nabuurs (2001). Manual for the European Forest Information Scenario Model (EFISCEN 2.0). European Forest Institute (EFI), Joensuu: 47 p.

Pussinen, A., T. Karjalainen and S. Kellomäki (1997). Potential contribution of the forest sector to carbon sequestration in Finland. Biomass and Bioenergy 13(2): pp. 377–387.

Row, C. and R. B. Phelps (1990). Tracing the flow of carbon through U.S. Forest Product Sector. IUFRO, 19th World Congress, Montreal: 13 p. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 73

Sallnäs, O. (1990). A matrix growth model of the Swedish forest. Swedish University of Agricultural Sciences, Faculty of Forestry, Uppsala: 23 p.

Schelhaas, M.-J., S. Varis and A. Schuck (2001). Database on Forest Disturbances in Europe (DFDE). European Forest Institute (EFI), Joensuu, Finland: http://www.efi.fi/projects/dfde/.

Sedjo, R. A. (1992). Temperate Forest Ecosystems in the Global Carbon Cycle. Ambio 21(4): pp. 274–277.

Solid waste disposal in the United States (1988). U.S. Environmental Protection Agency, Washington D.C.: v.p.

UN (1992). United Nations Framework Convention on Climate Change (UNFCCC). United Nations, New York / Geneva: 33 p.

UN (1997). Kyoto Protocol to the Unites Nations Framework Convention on Climate Change. United Nations, New York / Geneva: 23 p.

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Winjum, J. K., S. Brown and B. Schlamadinger (1998). Forest Harvests and Wood Products: Sources and Sinks of Atmospheric Carbon Dioxide. Forest Science 44(2): pp. 272–284.

8. APPENDICES

8.1 DESCRIPTION OF THE EUROPEAN FOREST INFORMATION SCENARIO MODEL (EFISCEN)

The forest resource database at the European Forest Institute (Nabuurs 1996) provides Europe-wide the forests growing stock (stemwood) as well as its growth, which is used in the EFISCEN approach (described in Karjalainen et al. (1997)). This database contains information of the forest resources in 30 European countries: forest area, standing volume, and increment. The information is provided on different levels by country, region, owner class, site class, tree species, and age class. The details of information vary between the countries from very detailed to rather poor inventory data. This is the reason, why just very simple model runs of EFISCEN could have been done for Bosnia and Herzegovina, Greece, and and thus they unfortunately cannot be included yet in the analysis. The total forest area that is covered in the database is 146.5 million ha, distributed over 2527 forest types (Nabuurs et al. 1997).

The original model was developed at the Swedish University of Agricultural Sciences (Sallnäs 1990) and has been already used to project development of forest resources in Europe (Nilsson et al. 1992). The model has been further improved and used for new analyses of the future development of forest resources in Europe (e.g. Nabuurs and Päivinen 1996; Nabuurs et al. 1998; Päivinen et al. 1999), and is now known as EFISCEN (Pussinen et al. 2001). For a detailed description of the EFISCEN model also refer to Pussinen et al. (2001).

30 European Process based national forest models inventories. Growth (EEFR) changes due to climate change

EFISCEN core model: projections of stemwood Whole tree Natural mortality / volume, felling potential, biomass natural age classes, increment, by disturbances country, tree species etc.

Litter Forest management

Soil Wood products International trade in wood Society > policies > products preferences in management: Landfills e.g. nature oriented management

Figure 8.1. Schematic outline of the European Forest Information Scenario Model (EFISCEN) (Pussinen et al. 2001). 76 Thies Eggers

The current state of the forest is described in EFISCEN as an area distribution over age and volume classes and the dynamics of volume increment are expressed as transitions between volume and age classes in this area-based matrix type of model. Harvest (thinnings and final fellings) and regeneration are simulated in the model. EFISCEN is run for each forest type in each of the countries included in the forest inventory database (Pussinen et al. 2001).

A carbon -keeping module is included in the model in order to calculate the forest carbon budget (Figure 8.1). EFISCEN includes the whole tree biomass, soil organic matter (according to Liski et al. 1998), and a separate model is run for carbon stocks in wood products using the simulated harvest levels (according to Karjalainen et al. 1994). The results of this model runs are presented in this study. The current net annual increment, biomass allocation and litter production of EFISCEN is adjusted also for changing climatic conditions based on information from process-based models in the regional impact assessment. Selected forest management scenarios are applied for current climatic and changing climatic conditions, providing predictions of the future development of forest carbon stocks and fluxes. The results are presented as European forest and wood product carbon budget and flows for the period 1990 to 2050. Figure 8.2 shows EFISCEN results as an example for Germany. Results for the other countries (Austria, Finland, Norway, Portugal) and Europe are printed at the end of this chapter.

The EFISCEN forest model is a timber assessment matrix model (Figure 8.3); i.e. the model simulates the development of forest recourses under given amount of fellings. Thus the model calculates the fellings, which are converted to roundwood over bark (o.b.). This is the input to the wood product model. EFISCEN simulates the recourse development of the forests for several decades. It is to be expected that growth rates might change during such long periods due to changes in the environment, e.g. climate change. To pay attention to this fact, EFISCEN can also simulate the impact of climate change and forest growth, but this study will focus only on the model-runs without climate change because the differences in

12.0 600 ]

11.0 550 -1 10.0 500 ]

-1 9.0 450

yr 8.0 400 -1

ha 7.0 350 6.0 300 net annual increment gr ow ing stock [m³ ha

and annual fellings [m³ 5.0 250 4.0 200 1995 2005 2015 2025 2035 2045 2055 year

fellings BaU fellings MF increment BaU increment MF growing stock BaU growing stock MF

Figure 8.2. Simulated net annual increment, fellings and growing stem wood stock for Germany under the business as usual (BaU) and the multi-functional (MF) scenario. The figures are 5-year-average values covering 9.9Mha (BaU) and 10.1Mha (MF) of forest land. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 77 harvest levels under both scenarios are just small. The basis for growth calculations in EFISCEN is always the growth as calculated by the incorporated functions, which are based on inventory data of the early 1990s. The following figure will show a comparison of historical data on removals from FAOSTAT (FAO 2000a) with the first simulated EFISCEN removals. The linear function represents a ratio of 1 to 1. It can be seen that EFISCEN seems to underestimate the removals a little bit in case that FAOSTAT figures are more reliable.

Forest management in EFISCEN is provided for in terms of thinning and final felling regimes and total volumes to be thinned, and clear-cut by tree species groups. Final felling is expressed as a probability, dependent on the stand age or actual standing volume. These probabilities are converted into a proportion of the area in each matrix cell that will be felled. The actual area felled in a cell depends of the requested volume to be harvested and volume available in the species group. A felled area is moved to a bare-forest-land class (Figure 8.3). Regeneration is regarded as the movement of area from the bare-forest-land class to the first volume and age class. The amount of area that is regenerated is regulated by a parameter that expresses the intensity of the regeneration (young forest coefficient). This parameter is a percentage of the area in the bare-forest-land class that will move to the first volume and age class during the following 5 years. It is possible to change the tree species after clear-cut. The tree species to be regenerated on clear felled areas can be defined by regions and forest types. Forest area can change as a consequence of afforestation and deforestation.

15.00

10.00

5.00 Tg C in 1990 (EFISCEN)

0.00 0.00 5.00 10.00 15.00 Tg C in 1987 (FAOSTAT)

Carbon in harvested timber Linear (Linear function 1=1)

Figure 8.3. Comparison of historic (FAOSTAT) and simulated (EFISCEN) data on carbon in harvested timber. The historical data is from 1987 and the simulated for the first modeled EFISCEN year 1990. 78 Thies Eggers

Forest types

Volume

X 44

X 33

Age

Growth Harvests

Figure 8.4. EFISCEN area matrix approach (Nilsson et al. 1992). The figure shows the possible transitions of forest areas within the age-volume-matrix. The dashed line shows the clear-cut activities moving forest area to bare forest land, while the arrows indicate changes within age or volume of the forest type.

A validation of EFISCEN was done by Nabuurs et al. (2000). They focused in their study on Finland, because both inventory data starting in the 1920’s, and several projections based on different methods were available. Using historical inventory data from the national forest inventory, from 1921 to 1924, EFISCEN was parameterised. The results of this run were compared with results from the following 7 forest inventories. Based on this comparison, modifications in the model, and future predictions, starting in 1990, had been done. The results of the validation showed that EFISCEN is capable of making reliable large-scale projections of forest resources for periods up to 60 years. Based on the validation, the model was improved concerning simulations of age development, thinning regimes and regrowth after thinning.

Four general approaches to validate large-scale models were applied:

1. Validating the applied growth functions against other growth functions or data sets, 2. Comparing the resulting projections against other projections carried out for the same forests, 3. Running the model on historic data and comparing the output to the present state of the forests, and 4. Propagation of variance assessments (e.g. Monte Carlo simulation) to gain insight in accuracy. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 79

All four approaches had been applied either for EFISCEN or for other similar large-scale models before. Kangas (1997, 1998) formulated in general four main reasons for possible error sources in projections. They are i) stochastic character of the estimated model coefficients (i.e. growth variation and management irregularity are not incorporated), ii) measurement and sampling errors in the data used for model construction, iii) accuracy of fit of the utilised models, and iv) assumptions in the model. Those sources of error have to be kept in mind when looking on both the results of EFISCEN as input for the wood product model, and as well as the carbon projections in the wood-based product stock.

12.0 600 3 ]

11.0 550 -1 10.0 500 ]

-1 9.0 450 yr 8.0 400 -1

ha 7.0 350 6.0 300 net annual increment

5.0 250 gr ow ing stock [m³ ha and annual fellings [m 4.0 200 1995 2005 2015 2025 2035 2045 2055 year

fellings BaU fellings MF increment BaU increment MF growing stock BaU growing stock MF

Figure 8.5. Simulated net annual increment, fellings and growing stem wood stock for Austria under the business as usual (BaU) and the multi-functional (MF) scenario. The figures are 5-year-average values covering 2.9Mha (BaU) and 3.0Mha (MF) of forest land.

4.5 180 3 ] -1 4.0 160 ]

-1 3.5 140 yr -1 3.0 120 ha

2.5 100 net annual increment gr ow ing stock [m³ ha and annual fellings [m 2.0 80 1995 2005 2015 2025 2035 2045 2055 year

fellings BaU fellings MF increment BaU increment MF growing stock BaU growing stock MF

Figure 8.6. Simulated net annual increment, fellings and growing stem wood stock for Finland under the business as usual (BaU) and the multi-functional (MF) scenario. The figures are 5-year-average values covering 19.6Mha (BaU) and 19.8Mha (MF) of forest land. 80 Thies Eggers

4.0 180 3 ] -1 160 3.5 ]

-1 140 yr 3.0 -1 120 ha 2.5 100 net annual increment gr owing stock [m³ ha and annual fellings [m 2.0 80 1995 2005 2015 2025 2035 2045 2055 year

fellings BaU fellings MF increment BaU increment MF growing stock BaU growing stock MF

Figure 8.7. Simulated net annual increment, fellings and growing stem wood stock for Norway under the business as usual (BaU) and the multi-functional (MF) scenario. The figures are 5-year-average values covering 7.1Mha (BaU and MF) of forest land.

8.0 190 ] -1 7.0 170 ]

-1 6.0 150 yr -1 5.0 130 ha

4.0 110 net annual increment growing stock [m³ ha and annual fe llings [m³ 3.0 90 1995 2005 2015 2025 2035 2045 2055 year

fellings BaU fellings MF increment BaU increment MF growing stock BaU growing stock MF

Figure 8.8. Simulated net annual increment, fellings and growing stem wood stock for Portugal under the business as usual (BaU) and the multi-functional (MF) scenario. The figures are 5-year-average values covering 1.5Mha (BaU and MF) of forest land.

6.0 300 - ] yr -1 -1 5.0 250 ]

1 4.0 200

3.0 150 growing stock [m³ ha net annual increment and annual fellings [m³ ha 2.0 100 1995 2005 2015 2025 2035 2045 2055 year

fellings BaU fellings MF increment BaU increment MF growing stock BaU growing stock MF

Figure 8.9. Simulated net annual increment, fellings and growing stem wood stock for Europe under the business as usual (BaU) and the multi-functional (MF) scenario. The figures are 5-year-average values covering 129Mha (BaU) and 132Mha (MF) of forest land. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 81

8.2 FAO DEFINITIONS ON WOOD AND WOOD BASED PRODUCTS (FAO 2000a)

Removals. The term “removals” is synonymous with roundwood production.

Coniferous. All wood derived from trees classified botanically as Gymnospermae, e.g. fir (Abies), Paraná pine (Araucaria), deodar (), ginkgo (Ginkgo), (Larix), spruce (Picea), pine, chir, kail (Pinus), etc. These are generally referred to as .

Non-coniferous. All wood derived from trees classified botanically as Angiospermae, e.g. maple (Acer), alder (Alnus), ebony (Diospyros), beech (Fagus), lignum vitae (Guaiacum), poplar (), oak (Quercus), sal (Shorea), (Tectona), casuarina (Casuarina), etc. These are generally referred to as broadleaves or hardwoods.

Roundwood. Wood in the rough. Wood in its natural state as felled or otherwise harvested, with or without bark, round, split, roughly squared or in other form (e.g. roots, stumps, burls, etc.). I may also be impregnated (e.g. telegraph poles) or roughly shaped or pinted. It comprises all wood obtained from removals, i.e. the quantities removed from forests and from trees outside the forest, including wood recovered from natural. Felling and logging losses during the period calendar year or forest year. Commodities included are sawlogs and veneer logs, pulpwood, other industrial roundwood (including pitprops) and fuelwood. The statistics include recorded volumes, as well as estimated unrecorded volumes as indicated in the notes. Statistics for trade include, as well as roundwood from removals, the estimated roundwood equivalent of chips and particles, wood residues and .

Industrial roundwood. The commodities included are sawlogs or veneer logs, pulpwood, other industrial roundwood and, in the case of trade, chips and particles and wood residues.

Sawnwood. Sawnwood, including sleepers, unplaned, planed, grooved, tongued, etc., sawn lengthwise or produced by a profile-chipping process (e.g. planks, beams, joists, boards, rafters, scantlings, laths, boxboards, “”, etc.) and planed wood, which may also be finger-jointed, tongued or grooved, chamfered, rabbeted, V-jointed, beaded, etc. Wood is excluded. With few exceptions, sawnwood exceeds 5 mm in thickness.

Other industrial roundwood. Roundwood used for , distillation, blocks, gazogenes, poles, piling, posts, pitprops, etc.

Pulpwood and particles. Pulpwood, chips, particles and wood residues. In production, the commodities included are pulpwood coniferous and non-coniferous. In trade, the aggregate includes, in addition, chips and particles and wood residues.

Plywood. Plywood, veneer plywood, core plywood, including veneered wood, blockboard, laminboard and battenboard. Other plywood, such as cellular board and composite plywood. Veneer plywood is plywood manufactured by bonding together more than two veneer sheets. The grain of alternate veneer sheets is crossed, generally at right angles. Core plywood is plywood whose core (i.e. central layer, generally thicker than the other plies) is solid and consists of narrow boards, blocks or strips of wood placed side by side, which may or may not be glued together. (This item includes veneered wood in sheets or panels in which a thin veneer of wood is affixed to a base, usually of inferior wood, by glueing under pressure.) Cellular board is plywood with a core of cellular construction, while composite plywood is plywood with the core or certain layers made of material other than solid wood or veneers. 82 Thies Eggers

Particle board . A sheet material manufactured from small pieces of wood or other ligno- cellulosic materials (e.g. chips, flakes, splinters, strands, shreds, shives, etc.) agglomerated by use of an organic binder together with one or more of the following agents: heat, pressure, humidity, a catalyst, etc. (Flaxboard is included. Wood and other particle boards, with inorganic binders, are excluded.)., Data for USA particle board production include OSB (oriented strand board) only starting from 1995.

Mechanical wood pulp. Wood pulp obtained by grinding or milling coniferous or non- coniferous rounds, quarters, billets, etc. into fibres, or through refining coniferous or non- coniferous chips. Also called groundwood pulp and refiner pulp. It may be bleached or unbleached. This aggregate excludes exploded and defibrated pulp, and includes chemi- mechanical and thermo-mechanical pulp.

Semi-chemical wood pulp. Wood pulp, chemi-mechanical and semi-chemical. Wood pulp obtained by subjecting coniferous or non-coniferous wood to a series of mechanical and chemical treatments, none of which alone is sufficient to make the fibres separate readily. According to the order and importance of the treatment, such pulp is variously named: semi- chemical, chemi-groundwood, chemi-mechanical, etc. It may be bleached or unbleached.

Chemical wood pulp. Sulphate (kraft) and soda and sulphite wood pulp, except dissolving grades, bleached, semi-bleached and unbleached. Where detail is available, statistics for the following four component pulps are given:

· Sulphite pulp: Wood pulp, sulphite, except dissolving grades. Wood pulp obtained by mechanically reducing coniferous or non-coniferous wood to small pieces that are subsequently cooked in a pressure vessel in the presence of a bisulphite cooking liquor. Bisulphites such as ammonium, calcium, magnesium and sodium are commonly used. The two classes are bleached (including semi-bleached) and unbleached. · Sulphate pulp: Wood pulp, sulphate (kraft) and soda, except dissolving grades. Wood pulp obtained by mechanically reducing coniferous or non-coniferous wood to small pieces that are subsequently cooked in a pressure vessel in the presence of sodium hydroxide cooking liquor ( soda pulp) or a mixture of sodium hydroxide and sodium sulphite cooking liquor ( sulphate pulp). The two classes are bleached (including semi- bleached) and unbleached. · Dissolving pulp: Wood pulp, dissolving grades. Chemical pulp (sulphate, soda or sul- phite) from coniferous or non-coniferous wood, of special quality, with a very high alpha-cellulose content (usually 90 percent and over), readily adaptable for uses other than paper-making. These pulps are always bleached. They are used principally as a source of cellulose in the manufacture of products such as synthetic fibres, cellulosic plastic materials, lacquers and . · Other pulp: Pulp of fibrous vegetable materials other than wood. Including straw, bam- boo, bagasse, esparto, other reeds or grasses, cotton linters, flax, hemp, rags and other textile wastes. Used for the manufacture of paper, paperboard and fibreboard.

Dissolving wood pulp. Wood pulp, dissolving grades chemical pulp (sulphate, soda or sulphite) from coniferous or non-coniferous wood, or special quality, with a very high alpha- cellulose content (usually 90% and over), readily adaptable for uses other than paper making. These pulps are always bleached. They are used principally as a source of cellulose in the manufacture of products such as synthetic fibres, cellulosic plastic materials, lacquers, explosives. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 83

8.3 COUNTRY LISTING

Table 8.1. LTEEF-II countries, their codes and their region used for parameterisation in this study.

Name Code Country group

Albania ALB Mediterranean Middle Austria AUT Alpic Belgium BEL Sub-Atlantic Bosnia-Herzegovina*) BIH Mediterranean Middle Bulgaria BGR Mediterranean East Croatia HRV Mediterranean Middle Czech Republic CZE Central Denmark DNK Central Finland FIN Northern France FRA Sub-Atlantic Germany DEU Central Greece*) GRC Mediterranean East Hungary HUN Pannonic Ireland IRL Atlantic Italy ITA Mediterranean Middle Luxembourg LUX Sub-Atlantic The Former Yugoslav Republic of Macedonia MKD Mediterranean Middle Netherlands NLD Sub-Atlantic Norway NOR Northern Poland POL Central Portugal PRT Mediterranean West Romania ROM Pannonic Slovak Republic SVK Central Slovenia SVN Mediterranean Middle Spain ESP Mediterranean West Sweden SWE Northern Switzerland CHE Alpic Turkey*) TUR Mediterranean East United Kingdom GBR Atlantic Yugoslavia (Serbia and Montenegro) YUG Mediterranean Middle *) not included in the model runs 84 Thies Eggers

8.4. ADDITIONAL PARAMETERS

8.4.1. Country parameters for Austria, Finland, Norway, and Portugal

Table 8.2. Country parameters for the EFISCEN wood product model for Austria. ‘con.’ means coniferous wood; ‘non-con.’ means non-coniferous wood. The ‘model parameter’ are those calculated by using the relation of the IRW sub-categories to the total IRW amounts. The ‘adjusted model parameters’ are recalculated from the ‘model parameters’ as described in the text (Chapter 3.3.7.1).

Model parameter Adjusted model parameter Con. Non-con. Con. Non-con.

Natural losses1 0.0331 0.0433 0.0331 0.0433 Bark-fraction2 0.1100 0.1300 0.1100 0.1300 Fuelwood3 0.1476 0.5527 0.1476 0.5527 Pulpwood à chemical pulp3 IRW 0.1431 0.1377 0.1146 0.2130 Pulpwood à mechanical pulp3 IRW 0.0249 0.0240 0.0200 0.0371 Sawn timber3 IRW 0.8647 0.1980 0.6927 0.3063 Veneer & plywood3 IRW 0.0283 0.0283 0.0227 0.0438 Particleboard3 IRW 0.1576 0.1576 0.1262 0.2437 Other IRW3 IRW 0.0297 0.1010 0.0238 0.1562

IRW total 1.2483 0.6467 1.0000 1.0000 1UN/ECE (1992); 2Haygreen and Bowyer (1989); 3FAO (2000a)

Table 8.3. Country parameters for the EFISCEN wood product model for Finland. ‘con.’ means coniferous wood; ‘non-con.’ means non-coniferous wood. The ‘model parameter’ are those calculated by using the relation of the IRW sub-categories to the total IRW amounts. The ‘adjusted model parameters’ are recalculated from the ‘model parameters’ as described in the text (chapter 3.3.7.1).

Model parameter Adjusted model parameter Con. Non-con. Con. Non-con.

Natural losses1 0.0459 0.1807 0.0459 0.1807 Bark-fraction2 0.1100 0.1300 0.1100 0.1300 Fuelwood3 0.0331 0.3178 0.0331 0.3178 Pulpwood à chemical pulp3 IRW 0.3296 0.3258 0.3183 0.6241 Pulpwood à mechanical pulp3 IRW 0.1180 0.1166 0.1140 0.2235 Sawn timber3 IRW 0.5236 0.0173 0.5056 0.0332 Veneer & plywood3 IRW 0.0412 0.0412 0.0398 0.0790 Particleboard3 IRW 0.0156 0.0156 0.0151 0.0299 Other IRW3 IRW 0.0076 0.0054 0.0073 0.0104

IRW total 1.0356 0.5220 1.0000 1.0000 1UN/ECE (1992); 2Haygreen et al. (1989); 3FAO (2000a) The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 85

Table 8.4. Country parameters for the EFISCEN wood product model for Norway. ‘con.’ means coniferous wood; ‘non-con.’ means non-coniferous wood. The ‘model parameter’ are those calculated by using the relation of the IRW sub-categories to the total IRW amounts. The ‘adjusted model parameters’ are recalculated from the ‘model parameters’ as described in the text (Chapter 3.3.7.1).

Model parameter Adjusted model parameter Con. Non-con. Con. Non-con

Natural losses1 0.0459 0.1807 0.0459 0.1807 Bark-fraction2 0.1100 0.1300 0.1100 0.1300 Fuelwood3 0.0179 0.5966 0.0179 0.5966 Pulpwood à chemical pulp3 IRW 0.1989 0.1784 0.1922 0.3653 Pulpwood àmechanical pulp3 IRW 0.2026 0.1818 0.1958 0.3722 Sawn timber3 IRW 0.5562 0.0437 0.5375 0.0895 Veneer & plywood3 IRW 0.0022 0.0022 0.0021 0.0045 Particleboard3 IRW 0.0553 0.0553 0.0534 0.1132 Other IRW3 IRW 0.0196 0.0269 0.0189 0.0552

IRW total 1.0348 0.4883 1.0000 1.0000 1UN/ECE (1992); 2Haygreen et al. (1989); 3FAO (2000a)

Table 3.5. Country parameters for the EFISCEN wood product model for Portugal. ‘con.’ means coniferous wood; ‘non-con.’ means non-coniferous wood. The ‘model parameter’ are those calculated by using the relation of the IRW sub-categories to the total IRW amounts. The ‘adjusted model parameters’ are recalculated from the ‘model parameters’ as described in the text (Chapter 3.3.7.1).

Model parameter Adjusted model parameter Con. Non-con. Con. Non-con

Natural losses1 0.0102 0.0306 0.0102 0.0306 Bark-fraction2 0.1100 0.1300 0.1100 0.1300 Fuelwood3 0.0339 0.0732 0.0339 0.0732 Pulpwood à chemical pulp3 IRW 0.2440 0.8132 0.2363 0.7168 Pulpwood à mechanical pulp3 IRW 0.0000 0.0000 0.0000 0.0000 Sawn timber3 IRW 0.6225 0.1760 0.6027 0.1551 Veneer & plywood3 IRW 0.0359 0.0359 0.0347 0.0316 Particleboard3 IRW 0.1047 0.1047 0.1014 0.0923 Other IRW3 IRW 0.0257 0.0047 0.0249 0.0041

IRW total 1.0328 1.1345 1.0000 1.0000 1UN/ECE (1992); 2Haygreen et al. (1989); 3FAO (2000a) 86 Thies Eggers

8.4.2 Efficiency parameters for the Central Region and the Southern Region

Table 8.6. Efficiency parameter for the regarded production lines in the Central Region. The rows must always add up to one so that no uncertain ways of timber are assumed.

Fraction of timber (input) to Production line Final Energy Pulp Particleboard product burning production production

Chemical pulp 0.472 0.528 0.000 0.000 Mechanical pulp 0.928 0.072 0.000 0.000 Sawn timber (con.) 0.610 0.097 0.141 0.152 Sawn timber (non-con.) 0.610 0.082 0.119 0.129 Plywood & veneer 0.530 0.375 0.000 0.095 Particleboard 0.669 0.230 0.080 0.021

Table 8.7. Efficiency parameter for the regarded production lines in the Southern Region. The rows must always add up to one so that no uncertain ways of timber are assumed.

Fraction of timber (input) to Production line Final Energy Pulp Particleboard product burning production production

Chemical pulp 0.472 0.528 0.000 0.000 Mechanical pulp 0.928 0.072 0.000 0.000 Sawn timber (con.) 0.430 0.170 0.130 0.270 Sawn timber (non-con.) 0.430 0.170 0.130 0.270 Plywood & veneer 0.530 0.375 0.000 0.095 Particleboard 0.669 0.230 0.080 0.021 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 87

8.5. ADDITIONAL RESULTS

8.5.1 Carbon Flowcharts 2000

forests atmosphere

removals o.b. recycling (from last year) 3.0 Tg C

raw material 5.0 Tg C

process release decay 0.2 Tg C production burning (incl. fuelwood) process 1.2 Tg C into products 4.3 Tg C waste disposal products in use discarded products 0.9 Tg C landfill 43.4 Tg C 4.1 Tg C 38.6 Tg C

recycling (to next year) 2.0 Tg C

Figure 8.10. Flowchart of carbon fluxes [Tg·yr-1] and stocks [Tg] in wood products for Austria in 2000 under the business as usual scenario. Fluxes are indicated with arrows; stocks with boxes.

forests atmosphere

removals o.b. recycling (from last year) 10.2 Tg C

raw material 12.6 Tg C

process release decay 0.8 Tg C production burning (incl. fuelwood) process 3.5 Tg C into products 9.1 Tg C waste disposal products in use discarded products 2.8 Tg C landfill 62.2 Tg C 8.7 Tg C 157.8 Tg C

recycling (to next year) 2.4 Tg C

Figure 8.11. Flowchart of carbon fluxes [Tg·yr-1] and stocks [Tg] in wood products for Finland in 2000 under the business as usual scenario. Fluxes are indicated with arrows; stocks with boxes. 88 Thies Eggers

forests atmosphere

removals o.b. recycling (from last year) 8.6 Tg C

raw material 17.1 Tg C

process release decay 0.8 Tg C production burning (incl. fuelwood) process 3.4 Tg C into products 15.1 Tg C waste disposal products in use discarded products 3.2 Tg C landfill 129.1 Tg C 15.0 Tg C 153.3 Tg C

recycling (to next year) 8.4 Tg C

Figure 8.12. Flowchart of carbon fluxes [Tg·yr-1] and stocks [Tg] in wood products for Germany in 2000 under the business as usual scenario. Fluxes are indicated with arrows; stocks with boxes.

forests atmosphere

removals o.b. recycling (from last year) 2.7 Tg C

raw material 4.1 Tg C

process release decay 0.2 Tg C production burning (incl. fuelwood) process 0.9 Tg C into products 3.3 Tg C waste disposal products in use discarded products 0.8 Tg C landfill 19.4 Tg C 3.1 Tg C 35.5 Tg C

recycling (to next year) 1.4 Tg C

Figure 8.13. Flowchart of carbon fluxes [Tg·yr-1] and stocks [Tg] in wood products for Norway in 2000 under the business as usual scenario. Fluxes are indicated with arrows; stocks with boxes. The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget 89

forests atmosphere

removals o.b. recycling (from last year) 1.3 Tg C

raw material 1.7 Tg C

process release decay 0.1 Tg C production burning (incl. fuelwood) process 0.4 Tg C into products 1.2 Tg C waste disposal products in use discarded products 0.4 Tg C landfill 14.7 Tg C 1.2 Tg C 22.8 Tg C

recycling (to next year) 0.4 Tg C

Figure 8.14. Flowchart of carbon fluxes [Tg·yr-1] and stocks [Tg] in wood products for Portugal in 2000 under the business as usual scenario. Fluxes are indicated with arrows; stocks with boxes.

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