The substitution effect of harvested wood products from tropical timber producer countries

The substitution effect of harvested wood products from tropical timber producer countries | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The substitution effect of harvested wood products from tropical timber producer countries Tunggul Butarbutar, Michael Köhl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6408090/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: HWPs may contribute to reaching net-zero GHG emissions by sequestering atmospheric CO 2 and lowering emissions in manufacturing processes in comparison to functionally comparable items. The relevant mitigating impacts for HWPs produced from wood harvesting in tropical and subtropical forests have been inadequately examined, even though tropical nations are anticipated to contribute 12% of the global timber output by 2050 and that more than 40% of the world's 4 billion hectares of forests are in tropical regions, encompassing 1.73 billion hectares, or about half of the tropical land area. Here, we examine the effect of HWPs produced by tropical nations and their significance in terms of lowering atmospheric CO2 concentrations. Results: The carbon content of HWP was determined by calculating the annual output of the three essential HWP commodities: sawnwood, wood-based panels, and paper and paperboard products based on data provided by FAO (source). Southeast Asia and the Pacific Islands accounted for 61.6% of the global HWP production in 2018, followed by Latin America (34.6%) and Africa (3.6%). Wood production annually added the inflow to the HWP pool by 28 MtC, contributing to an annual carbon sink of 35.61 MtCO 2 y -1 Southeast Asia and the Pacific led the average carbon stock in HWP during 1990-2017, with 281 Mt C y -1 (53.43%), followed by Latin America with 219 Mt C y -1 (41.86%) and Africa with 24 Mt C y -1 (4.71%). In the reference period, Southeast Asia annually provides 21,76 MtCO 2 to the sink, followed by Latin America with 12,82 MtCO 2 and Africa with 1.01 MtCO 2 . In 1961, the net potential effect of harvested wood products ranged from 624 Mt CO 2 eq with a low displacement factor to 3928 Mt CO 2 eq with a high displacement factor and from 1605 Mt CO 2 eq with a low displacement factor to 9953 Mt CO 2 eq with a high displacement factor in 2017. Conclusions: In mitigating climate change, tropical forests play a multifaceted function. Due to deforestation and forest degradation, they are a significant source for global CO 2 emissions. For sustainably managed tropical forest, the contribution to climate change mitigation must consider the entire life cycle of wood. The energy-substitution effects of harvested wood products and other renewable energy sources such as solar and wind offer prospects for reaching net-zero emissions by the energy transition. Our findings indicate that the mitigating effect of wood consumption cannot be disregarded when making policy decisions and seeking trade-offs between competing forest management objectives. Instead, an effective mitigation approach needs a comprehensive understanding of the possible carbon stock changes in the pool of harvested wood products and the replacement impact. HWP Tropical Forest producers Displacement factor Emission reductions carbon sustainable forest management tropical forest carbon inflow Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background With the Paris Agreement, 196 parties have committed to keeping global warming at 1.5 to 2 degrees Celsius above pre-industrial levels. The measures also cover activities to maintain and improve the sinks and reservoirs of greenhouse gases, including forests (Article 5, Paris Agreement). Furthermore, the European Union has formulated a long-term strategy to confirm Europe’s commitment to lead in global climate action and presented a vision of achieving net-zero greenhouse gas (GHG) emissions by 2050. This vision includes the compensation of unavoidable residual emissions, by either technical (Carbon Capture and Storage, CSS) or nature based solutions ( 1 , 2 ). Beside peatlands, forests are considered as a leading example for supporting nature-based solutions to combat climate change. Forests remove CO 2 from the atmosphere through photosynthesis and convert it into C, which is stored in. After timber harvests a considerable amount of carbon remains stored in harvested wood products (HWPs) for a time span that varies depending on the type of HWPs between months and decades ( 3 ). According to Johnston & Radeloff, (2019) the global HWP pool was a net annual sink of 335 Mt of CO 2 e in 2015 and represents less than 1% of total annual GHG emissions. HWPs are not only a storage of C, but also contribute to the reduction of emissions, since the manufacture of wood products is generally associated with substantially lower emissions than manufacturing functionally equivalent products from non-renewable resources, such as steel, aluminum, or cement. HWPs thus make a dual contribution to achieving net-zero GHG emissions: ( 1 ) as a sink for atmospheric CO 2 and ( 2 ) by reducing emissions in manufacturing processes compared to functionally equivalent products. In general, the use of HWPs produces lower emissions than functionally equivalent products. Life cycle analyses are used to quantify the emissions generated in the manufacturing process. The decisive factor here is the energy mix used for producing the energy used in the production process. The Intergovernmental Panel on Climate Change (IPCC) provides guidance for including HWPs in national Greenhouse Gas (GHG) emission reports ( 5 , 6 ). However, only the change in the C pool of HWPs is considered in national accounting. The emission reductions resulting from the use of HWPs are mainly attributed to the energy sector. To assess the overall contribution of HWPs to achieving net-zero emissions, it is necessary to consider both the storage and the substitution effect. The contribution of the forest-wood chain to mitigating climate change has been widely studied. Geographically, the studies concentrate on European countries ( 7 – 13 ), the US and Canada ( 14 , 15 ), Japan ( 16 – 18 ), China and Taiwan ( 19 – 22 ). The corresponding mitigation effects for HWPs derived from timber harvesting in tropical and subtropical forests have been poorly studied, even though tropical countries by 2050 projected to contribute to 12% of the global timber production.( 23 ) More than 40% of the world’s 4 billion hectares of forests are in tropical regions, covering 1.73 billion hectares, corresponding to nearly half of the tropical land area. However, since 1990 the world has lost 420 million ha of forest due to land-use change and other non-sustainable land-use practices. Most of the forest area loss occurred in tropical forests of Africa, followed by South America. As a result, the global forest carbon stock decreased from 668 Gt C in 1990 to 662 Gt C in 2020 ( 24 ). Between 2005 to 2010 an estimated area of 2.2 billion hectares of tropical forest are subject to forest degradation with an estimated emission of 2.1 billion tons of carbon, of which 53% are due to timber harvests ( 25 ). In sustainably managed boreal and temperate forests, emissions from timber harvests are offset by the storage and mitigation capacity of wood products. Here we investigate to what extent this also applies to tropical and subtropical forests and what conclusions can be drawn for forest management from the perspective of reducing atmospheric CO 2 concentrations. Results The trend in the production of the three commodities under the study. The carbon content of HWP was calculated on the annual basis production of three primary HWP commodities of Sawnwood, wood-based panels, and paper and paperboard products. Sawnwood dominated HWP production in early 1961 with an 87.73% share. It continuously increased until the year 1990 when the production of Sawnwood reached approximately 65 million m 3 . After 1990, the production of Sawnwood was decreased, and only in 2006 did it get its peak temporarily. By 2018, the production of Sawnwood production is substantially reduced to about 49 million m 3 , i.e., approximately 12% of global Sawnwood production. The Wood-based Panel production has continuously increased until 2004, and the increasing rate has slightly slowed down after the year 2004. The rising trend was substantial until 1985. The production, however, expanded from 1 million m 3 in 1961 to 34 million m3 in 2018. By 2018, Wood-based Panel shares 25% of the total output of 3 primary HWP semi-finished products. Figure 1 shows a steady increase in the production of Paper and Paperboard in the last twenty years. Only produced as much as 1,7 million tons in 1961, the annual production reached 57,6 million in 2018. Representing a minor proportion of the total production of the three commodities in 1961, the yearly production of Paper and Paperboard took over the dominance of Sawnwood with a share of 40 percent of the total production of the three by the year 2004 until 2018. Southeast Asia and Pacific Island share 61,6% of total HWP production in 2018, followed by Latin America (34,6%) and Africa (3,7%). The dominance of Southeast Asia and Pacific Island started in 1980, and though there was a sharp decline in 1988, SEAP continued to lead the production share until 2018. Africa steadily share the lowest production for all those three products over time. The production history of the three commodities in three continents is presented in Fig. 2 . Carbon dynamic of Harvested Wood Products The carbon inflow shows additional carbon to the HWP pool. Figure 4 depicts the carbon inflow to the HWP pool. Overall, the carbon inflow to the HWP pool via sawn wood decreased between 1980 and 2018, though periodic variations are noticeable. For example, the inflow of the Sawnwood pool was reduced by 1980, and it increased back in 1997 and 2006. The Sawnwood inflow started to decline steeply after the year 2006. The inflows of Wood-based Panels and Paper and Paperboard, on the other hand, have been steadily increased for the entire period. Compared to the wood-based Panel, Paper and Paperboard flow increased remarkably and profoundly rise in stock in 2017. After taking over the inflow of Wood-based Panels in 1997, Paper and Paperboard continuously increased and overtook the dominance of Sawnwood from 2012 onward. Following the production approach, the total annual carbon inflow by 2017 is 33,6 Mt, consisting of 10.85 Mt of Sawnwood (32%), 8.98 Mt of Wood-based Panel (27%), and 13.77 Mt of Paper and Paperboard (41%). Southeast Asia dominates HWP production and carbon inflow by 58%, followed by Latin America 38.6% and Africa 3.46%. The annual inflow over from 1961 to 2018 is 20 Mt. The carbon inflow influences the HWP stock. Early production from 1961 until 1981 contributed to an adverse change in stock and, from that point, started to contribute positively. By commodities, Wood-based Panel contributes mainly to this positive trend followed by Paper and Paperboard. Sawnwood inflow provides a positive impact in the period of 1982–1998 and 2001–2006, and in the recent year continues the negative direction. We calculate the CO 2 emission or removal resulting from HWP production for individual HWP. From 1961 until 2017, HWP produced from those 33 tropical countries contributed to the total of 1521 Mt CO 2 eq sink/removal, which equals 26.7 Mt CO 2 eq year 1 . The above zero lines in emission/removal are emission, and below the line is removal/sink. HWP production emitted the atmosphere in 1961 until 1963 From 1964 until 2017, HWP contributes to carbon sink an average of 28.21 Mt CO 2 year − 1 . Wood-based Panel mainly contributes to this increase. In 2017, the wood-based Panel contributed to 18 Mt CO 2 eq. (see Fig. 5 ) Southeast Asia contributed mainly to the emission by 1961 with around 19 Mt of CO 2 and started to contribute to removal by 1980. Latin America contributed to the removal/sink of about 2.4 Mt CO 2 in 1961 and continued until 2017. While for Africa, the removal was as high as 0.06 Mt in early 1961. Indonesia, India, and Malaysia are the three biggest emitter countries, while, Mexico, Brazil, and Thailand are among the three most significant contributors to removal/sink (see Fig. 5 and Fig. 7 ) Substitution Effect The volume of annual carbon emissions reduction due to material substitution is presented in Fig. 8 , while Fig. 9 shows more detail of countries and continents. Assuming that wood’s substitution is mainly material substitution for cement, concrete, or steel for construction, we exclude the HWP of Paper and Paper-based in this calculation. For the three scenarios with displacement factor of 0.7, 2.0, and 4.4 we assess the potential emission reduction by HWP produced. The average potential yearly impact of HWP substitution from 1961 to 2017 is ranges from 998.60 Mt to 6276.93 Mt with the middle range of 2,853 Mt CO 2 eq year − 1 . Figure 8 present the potential carbon of substitution effect with 3 scenario levels and net CO 2 sink potential for substitution. For example, in 2017, the net sink from the substitution effect ranges from 1,579 Mt CO 2 eq (DF = 0.7) to 9927 Mt CO 2 eq (DF = 4.4), with the middle range of 4,512 Mt CO 2 eq (DF = 2.0). Total Potential Contribution of HWP Combining the potential removal/emission from the harvested wood product with the potential substitution in different scenario, we find the net potential effect of harvested wood product in year 1961 is range between 624 Mt CO 2 eq with low displacement factor to 3928 Mt CO 2 eq in the high displacement factor scenario and 1605 Mt CO 2 eq with low displacement factor to 9953 Mt CO 2 eq in the high displacement factor in year 2017 as shown in the Table 4 . The total potential net contribution of HWP as a combination of carbon emission/removal from harvested wood carbon pool and potential contribution of substitution. Discussion The results show that the use of wood from tropical and temperate forests, as well as wood from managed boreal and temperate forests, can have a significant carbon effect. Nevertheless, some methodological aspects have to be considered when interpreting the results. The estimations of carbon effects provided in this study are based on the HWP production data available at the FAOSTAT-Forestry database. The quality and reliability of individual country data may vary depending on the completeness and temporal actuality. In some cases, the data are also not based on comprehensive timber market statistics but are more in the nature of expert estimates. Nevertheless, the FAO data represent the most comprehensive collection of data on timber production in Asia, Africa and South America. The tropical regions of Africa, Southeast Asia, and Latin America contribute almost 20 percent to the global harvested wood production (FAO, 2005). Since the 1960’s the demand and production of harvested wood products from the tropical producer countries increased. The increase was mainly led by the substantial rise in the Paper and Paper board production and the steady growth of the Wood Panel production in Southeast Asia, and Latin America. In contrast, sawn timber production was more volatile. Compared to other regions, harvested wood production plays a minor role in Africa. In the period 1961 to 2017 Brazil, India, Indonesia, and Mexico are on average the largest producer countries. The change in production rates can be attributed to various factors. At the national level, economic development and the associated demand play a role, as do restrictions on timber harvesting in natural forests, the increasing proportion of forests in protected areas, and the expansion of plantation forestry. As wood products are also internationally traded commodities, events such as the global economic crisis between 2007 and 2009, the collapse of the Soviet Union, or timber trade regulations in Europe, the US or Australia have an impact as well. The FAO figures used in this study do not indicate the sources of the wood used for harvested wood production. These can be tropical hardwoods (typically from natural forests), plantation hardwoods (e.g. Eucalyptus, Acacia, Teak, Gmelina and sandalwood), and plantation softwoods (e.g. pines, cypress). While saw logs are mostly from tropical hardwoods, wood panels and paper and paper board are increasingly produced from plantations ( 23 ).Globally, the area of planted forests has increased from 172 million ha to 295 million ha, with 50% of this increase in Asia and 11% in South America, and only 2% in Africa ( 24 ).A direct comparison of the production figures with the depletion of natural tropical forests is therefore possible with caution at most for sawlogs. In the absence of data on the carbon stock of the initial HWP pool, the starting points for the three commodity classes had to be estimated. For this purpose, the Tier 1 approach of IPCC was used, which is based on the average inflows of the first five years. This approach builds up the HWP-pool in the first three decades, so that the selected decay factor does not yet result in a regular outflow from the HWP-pool. It is not until the end of the 1980s that a realistic carbon content of the HWP pool can be assumed. This effect affects the Paper and Paperboard commodity class less, since the half-life here is only 2.5 years. In contrast to North America and Europe, no reliable decay factors are available for HWPs from the tropics and subtropics. Differences are to be expected because, on the one hand, the durability of tropical timber is higher compared to temperate and boreal timber, and, on the other hand, differences in humidity and biotically induced decomposition agents influence the decay processes ( 26 – 28 ). Table 1 Inflow, HWP Stock, Stock change, and Emission/removal of HWP from 1990–2017 Year Inflow (Mt C) Harvested Wood Stock (Mt C) Stock change (Mt C) Emission/removal (Mt CO2) 1990 21,07 387,67 9,80 -35,93 1991 22,02 397,47 10,44 -38,27 1992 22,73 407,91 10,81 -39,65 1993 23,34 418,72 11,07 -40,59 1994 23,30 429,79 10,68 -39,14 1995 24,02 440,47 10,98 -40,27 1996 23,57 451,45 10,02 -36,74 1997 25,82 461,47 11,69 -42,86 1998 22,59 473,16 7,94 -29,11 1999 23,58 481,10 8,45 -30,99 2000 24,80 489,55 9,12 -33,42 2001 24,92 498,67 8,69 -31,86 2002 26,79 507,36 10,03 -36,78 2003 28,00 517,39 10,71 -39,28 2004 29,70 528,10 11,85 -43,43 2005 30,41 539,94 11,98 -43,91 2006 31,80 551,92 12,69 -46,52 2007 31,10 564,61 11,24 -41,20 2008 31,02 575,84 10,40 -38,13 2009 29,66 586,24 8,29 -30,41 2010 31,98 594,54 9,85 -36,12 2011 31,69 604,39 8,83 -32,39 2012 32,13 613,22 8,67 -31,78 2013 32,35 621,89 8,30 -30,45 2014 32,64 630,19 7,96 -29,18 2015 32,67 638,15 7,30 -26,77 2016 33,01 645,45 7,01 -25,70 2017 33,61 652,46 7,11 -26,08 Average 27,87 525,33 9,71 -35,61 Table 1 shows the cut-off Figure from 1990–2017. As shown in Table 1 and Fig. 8 , the inflow is relatively increased, with 33.61 MtC in 2017 added to the HWP stock of 652 MtC and contributing to the sink of 26MtCO 2 eq. The average stock of HWP for this period is around 525.33 MtC with an annual inflow of 27.87 MtC, contributing to the annual sink/removal of 35 Mt CO 2 eq y − 1 . Using the year 1990–2017 as a reference, Southeast Asia and the Pacific dominated the average carbon stock in HWP with 281 Mt C y − 1 (53.43%), followed by Latin America with 219 Mt C y − 1 (41.86%) and Africa with 24 Mt C y − 1 (4.71%). On an annual basis, in the reference time, Southeast Asia contributes to the sink of 21.76 MtCO 2 , followed by Latin America at 12.82 MtCO 2 and Africa at 1.01 MtCO 2 . For 2000–2012 an annual HWP sink of 44.0 Mt CO 2 yr − 1 was estimated for European Union countries ( 11 ), while an annual global HWP sink of 335 Mt CO 2 eq y − 1 is reported for 2015 ( 4 ). Displacement factors are determined by comprehensive life-cycle assessments. A decisive factor for the substitution effects are the emissions of the assumed energy mix. Since it is beyond the scope of the present study to establish the displacement factors corrected for the specific energy mix in the selected countries, we applied a scenario analysis to estimate the substitution effects. The displacement factors used were 0.7, 2.0 and 4.4. They provide a corridor within which the real substitution effects are likely to be located. For the three anticipated displacement factor we found an average annual emission reduction by HWPs between 998 Mt CO 2 eq y − 1 and 6278 Mt CO 2 eq y − 1 . These emission reductions are mainly due to using HWPs for construction purposes. The results support the findings of other studies, which also show a significantly higher carbon effect due to substitution effects than to the increase in the HWP pool ( 8 , 29 – 32 ) Conclusions The role of tropical forests in climate change mitigation is complex. Carbon sequestration and emissions occur in different stages of forest stand development and beyond. Forests sequester atmospheric CO 2 by growth or regrowth and emit CO 2 to the atmosphere due to deforestation and the reduction of carbon density within standing forest. Recovery of the carbon by regrowth and ingrowth contribute considerably to carbon enhancement. Depending on the management of forest production regimes, such as intensity of logging intervention or the use of reduced-impact logging in the tropics, studies show the ability of the logging area to recover within the management cycle ( 33 – 35 ). The study suggests that timber harvesting can be seen as a transition of carbon from the forest carbon pool to the harvested wood products pool. The increasing wood production in use potentially contributes to a net reduction of CO 2 emissions. Domestic consumption will be more appropriate for this strategy when considering the emission from life cycle products. However, the increase in consumption will be only possible with the sustainability of forest management as HWP substitution is determined by the whole life cycle of the wood (Butarbutar et al., 2019). The holistic approach is required in quantifying carbon pools and flows in the forest sector, including the substitution effect. Therefore, it needs to be integrated into other forest-based accounting systems for a more integrative approach. The contribution of HWP to the annual global carbon storage is relatively low. However, the HWP’s potential to substitute energy-intensive materials and emissions-intensive energy sources, such as fossil fuel, exceeds the pooled effect of HWPs by orders of magnitude and is relatively untapped. Wood has been both a common and a historical choice for building construction. Hence, the need for just transition, as we move to a green economy-calling businesses to be leaders. At the same time, the rapid global urbanization trends, growing population, and consumer awareness yield many opportunities for implementing a low carbon economy. Cities and industries are at the forefront of climate action. We need to transform how we generate our energy, design our cities, and manage our lands, including forest lands. The world communities and the emerging actors have opportunities to use biodegradable, renewable, and recyclable organic products, i.e., wood, which presents numerous other “built-in’ advantages; and to reduce the hard-to-abate emissions, such as emissions from cement and steel production. In tandem with other renewable energy sources such as solar and wind, the energy-substitution effects presented by the harvested wood products provide opportunities for the energy transition. We do not argue for considering the substitution effects of wood use in national GHG accounting. Instead, the energy sector implicitly accounts for the mitigation effects of wood use. Our results show, however, that the mitigation effect of the use of wood must not be ignored when making policy decisions and looking for trade-offs between different interests in the optimal treatment of our forests. A better understanding of potential carbon stock changes in the Harvested Wood Products pool and the substitution effect is essential to support an effective mitigation strategy. However, a more comprehensive approach is required that considers the entire forest-wood chain. A decrease of forest carbon stocks by timber harvesting has to be balanced by substitution and storage effects resulting from timber utilization. There are still many unknowns in this impact chain. To name just a few: Re-growth of forests after use interventions, share of durable products in wood use, decay rates, change in displacement factors due to changes in energy mix towards renewables, recovery rates in mill processing. In addition to the consideration of the carbon balance, factors such as biodiversity, economic development and social welfare must not be neglected. Finally, the CO 2 -benefits of HWPs do not offset the emissions caused by tropical deforestation. Methods Data This study uses harvested wood data from the FAOSTAT-Forestry database (Food and Agriculture Organization of the United Nations, 2020). The data base includes statistics on the production, import, and export of different categories of harvested wood products. Following the 2019 IPCC refinement ( 6 ), three commodity classes of semi-finished wood products were used for calculations: (i) Sawnwood, (ii) wood-based Panel, and (iii) paper and paperboard. To compute the fraction of wood products, we use the FAOSTAT data of industrial roundwood, wood-pulp, and recovered-paper. Table 1 shows the tropical timber producer countries included in the study. Table 2. List of Countries involved in the study by region. Estimating the HWP carbon content The FAO database includes annual values for raw wood and wood products beginning in 1961. The wood products are divided into different classes, which were combined for the calculation to commodity classes. Following the IPCC guidelines Tier 1 approach ( 6 ), we use the three commodity classes ( 1 ) Sawnwood, ( 2 ) wood-based panels, and ( 3 ) paper and paperboard The definitions of these commodities are as follows: Sawnwood Wood that has been produced from both domestic and imported roundwood, either by sawing lengthways or by a profile-chipping process and that exceeds 6 mm in thickness. Wood-based panels an aggregate comprising veneer sheets, plywood, particle board, and fiberboard. Paper and paperboard an aggregate category that represents the sum of graphic papers; sanitary and household papers; packaging materials and other paper and paperboard. It excludes manufactured paper products such as boxes, cartons, books and magazines, etc. For further details on the definitions of the three categories we refer to https://www.fao.org/forestry/statistics/80572/en/ . In the FAO database, the production data on sawlogs and wood-based panels produced is expressed in volume units (m3) and on paper products in weight units (t). To calculate the carbon content, these units have to be converted. IPCC (2019) presents uniform carbon conversion factors (cf) of the three aggregated commodity classes for the estimation of the carbon stock of the HWP pool in use (IPCC 2014, Table 2 1.1). The three commodity classes have different retention times in the HWP pool. A constant decay rate (k) is assumed under Tier 1 for the rate at which a commodity class is removed from the HWP pool and is expressed as a half-life in years. The default half-lifes of the three commodity classes are given by IPCC (2014, Table 12.3) and are shown in Table 2 . Table 3 Half-life values and emission factor of commodities (after IPCC, 2014) Commodity Half-live (years) Conversion factor (Mg C/m 3 ) Sawnwood (aggregate) 35 0.229 Wood-based panels (aggregate) 25 0.269 Paper and Paperboard (aggregate) 2 0.386 Following a circular economy approach a substantial amount of paper and paperboard is recovered after its original purpose. According to IPCC (2019) recovered paper includes in addition residues from paper and paperboard production. As only limited country data is available from FAOSTAT on recovered ( 37 , 38 ), we use the generic regional data following Holik, (2013). The respecive recovered paper utilization rates are 69% for Asia, 51% for Europe, and 35% for North America. Displacement Factor. Substituting wood for energy intensive materials reduces GHG emissions ( 40 – 43 ) Displacement factors (DFs) relate the emission reduction when substituting a functionally equivalent non-wood product by a wood product to the carbon mass contained in the wood used. DFs are calculated as $$\:DF=\:\frac{{f}_{NW}-{f}_{W}}{{C}_{W}}$$ where f NW are GHG emissions from the use of non-wood and f W those from the use of wood, both expressed in mass units of carbon equivalent, and C W is the carbon mass content of the wood product. According to Sathre & Gustavsson (2009) DFs range from as low as -2.3 to as high as 15.0. The calculation of for the substitution effect requires detailed information on wood utilization which is not available for most selected countries. Therefore we use a scenario approach, which is based on the average DFs from existing studies ( 42 ) We use three scenarios applying values of DF = 0.7 for a conservative scenario, DF = 4.4 for an optimistic scenario, and DF = 2.0 representing an intermediate scenario (Sathre & Gustavsson, 2009). As Paper and Paper Board commodities generally are not used for replacing non-wood materials, we restrict the calculation of substitution effects on sawnwood and wood-based panels. Carbon stock change in HWP The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019) – hereafter referred to as 2019 IPCC refinement - provides different approaches for estimating CO 2 emissions and removals from HWPs. The different methods are related to the processes (i.e. changes of carbon stocks within defined HWP pools or quantifying CO 2 fluxes from and to the atmosphere from HWPs) and the system boundaries (i.e. consuming or producing countries) applied in the calculation. The resulting approaches are shown in Table 3 . Table 4 Approaches to estimating CO 2 emissions and removals arising from HWPs (after ( 43 ) Approaches Processes and boundaries Stock change Change in the HWP pool accounted for the consuming country Production Change in the HWP pool based on domestically produced stocks. Stock change for HWP of domestic origin (SCAD) Change of HWP pool based on domestically produced and consumed stocks Atmospheric flow Fluxes of CO 2 to the atmosphere from HWP accounted for in the country where they occur Simple decay Carbon transfer from forest carbon pools to HWP pool is counted as emissions from HWP pool at the time of end-of-life of HWP in the producing country Table 5 HWP carbon emission/removal,subsitution effect and potential total contribution to the emission reduction Year Emission/Removal from HWP (Mt CO 2 eq) (a) Substitution effect of different scenario (Mt CO 2 eq) (b) Total Potential Net Contribution of HWP (Mt CO 2 eq) (a + b) DF 0.7 DF 2.0 DF 4.4 DF 0.7 DF 2.0 DF 4.4 1961 0,84 625,09 1785,98 3929,17 624,25 1785,14 3928,32 1962 0,41 624,41 1784,03 3924,86 624,00 1783,62 3924,45 1963 0,12 624,16 1783,31 3923,27 624,03 1783,18 3923,15 1964 -0,68 623,97 1782,78 3922,12 624,65 1783,46 3922,80 1965 -1,51 624,31 1783,75 3924,26 625,82 1785,26 3925,77 1966 -3,34 625,17 1786,20 3929,64 628,51 1789,54 3932,98 1967 -4,08 627,28 1792,22 3942,88 631,35 1796,30 3946,96 1968 -4,77 629,94 1799,83 3959,62 634,71 1804,60 3964,39 1969 -5,83 633,36 1809,59 3981,09 639,19 1815,42 3986,93 1970 -8,86 637,42 1821,20 4006,64 646,28 1830,06 4015,49 1971 -8,86 642,38 1835,37 4037,81 651,24 1844,23 4046,67 1972 -11,20 647,41 1849,74 4069,42 658,61 1860,94 4080,62 1973 -11,71 654,17 1869,06 4111,93 665,88 1880,77 4123,64 1974 -11,17 661,17 1889,05 4155,91 672,34 1900,22 4167,08 1975 -14,60 668,27 1909,35 4200,57 682,87 1923,95 4215,17 1976 -18,77 677,81 1936,60 4260,52 696,58 1955,37 4279,29 1977 -21,95 689,98 1971,37 4337,01 711,93 1993,31 4358,96 1978 -23,33 704,37 2012,48 4427,45 727,69 2035,81 4450,78 1979 -24,09 719,53 2055,79 4522,74 743,61 2079,88 4546,82 1980 -27,47 735,13 2100,37 4620,81 762,60 2127,84 4648,28 1981 -27,03 753,06 2151,60 4733,52 780,09 2178,63 4760,55 1982 -31,19 771,57 2204,50 4849,90 802,76 2235,69 4881,09 1983 -32,88 792,15 2263,28 4979,21 825,03 2296,16 5012,09 1984 -34,12 814,35 2326,71 5118,76 848,47 2360,83 5152,88 1985 -35,83 837,22 2392,07 5262,55 873,05 2427,89 5298,38 1986 -37,59 861,28 2460,81 5413,78 898,87 2498,39 5451,36 1987 -40,94 886,48 2532,80 5572,16 927,42 2573,74 5613,10 1988 -41,98 913,87 2611,06 5744,34 955,86 2653,05 5786,32 1989 -42,64 941,88 2691,09 5920,39 984,52 2733,72 5963,03 1990 -35,93 970,45 2772,72 6099,98 1006,38 2808,65 6135,91 1991 -38,27 994,95 2842,70 6253,94 1033,21 2880,97 6292,21 1992 -39,65 1021,06 2917,31 6418,08 1060,71 2956,96 6457,73 1993 -40,59 1048,03 2994,38 6587,63 1088,62 3034,97 6628,22 1994 -39,14 1075,42 3072,62 6759,75 1114,56 3111,76 6798,90 1995 -40,27 1102,06 3148,76 6927,26 1142,34 3189,03 6967,53 1996 -36,74 1128,52 3224,34 7093,56 1165,26 3261,09 7130,30 1997 -42,86 1151,76 3290,75 7239,65 1194,62 3333,61 7282,50 1998 -29,11 1178,86 3368,18 7410,00 1207,97 3397,29 7439,11 1999 -30,99 1197,49 3421,40 7527,07 1228,48 3452,39 7558,06 2000 -33,42 1216,49 3475,67 7646,48 1249,91 3509,10 7679,91 2001 -31,86 1236,94 3534,10 7775,02 1268,80 3565,96 7806,88 2002 -36,78 1256,83 3590,94 7900,07 1293,61 3627,72 7936,85 2003 -39,28 1280,21 3657,74 8047,02 1319,48 3697,01 8086,30 2004 -43,43 1305,44 3729,83 8205,62 1348,87 3773,26 8249,05 2005 -43,91 1333,43 3809,81 8381,58 1377,35 3853,72 8425,50 2006 -46,52 1361,78 3890,79 8559,74 1408,30 3937,31 8606,26 2007 -41,20 1390,63 3973,22 8741,08 1431,82 4014,42 8782,28 2008 -38,13 1415,77 4045,05 8899,11 1453,90 4083,18 8937,24 2009 -30,41 1438,17 4109,05 9039,90 1468,57 4139,45 9070,31 2010 -36,12 1455,57 4158,76 9149,28 1491,69 4194,89 9185,40 2011 -32,39 1476,22 4217,78 9279,11 1508,61 4250,17 9311,50 2012 -31,78 1495,42 4272,63 9399,78 1527,20 4304,41 9431,56 2013 -30,45 1514,99 4328,54 9522,78 1545,44 4358,99 9553,23 2014 -29,18 1533,06 4380,17 9636,38 1562,24 4409,36 9665,57 2015 -26,77 1549,84 4428,13 9741,88 1576,61 4454,89 9768,64 2016 -25,70 1564,41 4469,73 9833,42 1590,11 4495,44 9859,12 2017 -26,08 1579,35 4512,42 9927,33 1605,43 4538,50 9953,41 Since the analyses shown here aim at a global consideration of the corresponding substitution and storage effects, it is irrelevant in which country the harvested wood is converted into HWPs and where the HWPs are consumed. Taking into account import and export commodities would unnecessarily complicate the calculations and would not result in different emissions and removals in the aggregate compared to a direct comparison of national production data. Therefore, a modified production approach is used. According to Sato & Nojiri (2019) the production approach is a trade neutral approach and thus best suited for the current study. We extend the production approach by considering only the production of HWPs in a country, regardless of whether the timber is domestic origin or not. Estimating emissions and removals According to 2019 IPCC refinement (IPCC, 2019) the net change of the carbon stock in year i is calculated for each in commodity class l , ΔC l (i). The total CO 2 emissions and removal from net changes of the carbon stock in HWP in use during the year i , ∆CO 2TOTAL (i) , is obtained by the sum of the l individual ΔC l (i). Since the unit of the ΔC l (i) is C, a factor of 44/12 needs to be applied to obtain CO 2 values. Δ C l (i) is calculated by reducing the HWP pool at the beginning of year i + 1, C l (i + 1) , by the HWP pool at the beginning of year i , C l (i) . $$\:\varDelta\:\:{C}_{l}\left(i\right)={C}_{l}\left(i+1\right)-{C}_{l}\left(i\right).$$ Therefore, a positive value represents an increase in the HWP pool during the year under consideration, i.e. a removal. Since, according to the IPCC conventions, removals are designated with a negative sign, the calculated difference must be denoted with a negative sign. Intuitively, it would be simpler to calculate ΔC l (i) as \(\:\varDelta\:\:{C}_{l}\left(i\right)=\:{C}_{l}\left(i\right)-{C}_{l}\left(i+1\right)\) , since this would directly result in the IPCC-compliant negative sign for removals. IPCC (2017), Eq. 12.1 presents the respective calculations: \(\:\varDelta\:\:{CO}_{2\:TOTAL}\left(i\right)=-\frac{44}{12}*\sum\:_{l=1}^{n}\varDelta\:{C}_{l}\left(i\right)\) IPCC (2019), Eq. 12.1. where l is an index number of a semi-finished HWP commodity class and n is the number of selected commodity classes of the semi-finished HWP commodities. Here n = 3, as the three aggregated commodity classes sawnwood, wood-based panels, and paper and paperboard are considered. The carbon stock in the particular HWP commodity class l at the beginning of the year i + 1, C l (i + 1) , is based on the respective carbon stock at the beginning of year i , C l (i) , the first order decay (FOD) and the carbon inflow to commodity class l in year i , Inflow l ( i) . \(\:{C}_{l}\left(i+1\right)={e}^{-k}*{C}_{l}\left(i\right)+\left[\frac{\left(1-{e}^{-k}\right)}{k}\right]\:*I{nflow}_{l}\left(i\right)\) IPCC (2019), Eq. 12.2 Some authors suggest that a Chi-square distribution is more accurate than the exponential distribution to describe decay ( 44 – 46 )). To be consistent with the IPCC guidelines, we use the decay function following an exponential distribution function (IPCC, 2019, Eq. 12.2). IPCC (2019) omits in Eq. 12.2 an index for commodity classes for the decay constant k . However, k must still be determined separately for each respective commodity class l . According to IPCC (2019), Eq. 12.3 Inflow l (i) depends on the approach chosen for system boundaries, i.e. carbon inflow from domestic consumption or carbon inflow from the production from domestic harvests. Here inflow is the total domestic production of HWPs, regardless of the origin of the timber. The FOD for HWP commodity class l is taken into account by calculating a decay constant, k l , for each commodity class l over the corresponding half-life, H l . \(\:{k}_{l}=\frac{\text{ln}\left(2\right)}{{HL}_{l}}\) after IPCC (2019) Following IPCC 2019, Eq. 12.7, the annual carbon inflow from the production to the carbon stock of each HWP commodity class l, Inflow l (i) i , is calculated by \(\:{Inflow}_{PAl}\:\left(i\right)={HWP}_{{DP}_{l}}\left(i\right)*{cf}_{l}\) IPCC Eq. 12.7 \(\:{HWP}_{{DP}_{l}}\left(i\right)={HWP}_{{P}_{l}}\left(i\right)*{f}_{R}\:\left(i\right)\) IPCC Eq. 12.7 where cf l = carbon conversion factor of commodity class l f R (i) = Share of woody feedstock commodity class R (IRW, PULP or RecP) for the production of the particular semi-finished HWP commodity class originating from domestic harvest in the year i The FAO-statistics provide data on HWP for most countries since 1961. No data are available for the initial HWP-pool. The initial HWP-pool was estimated following the Tier 1 approach of IPCC (2019). As a proxy it is assumed that the HWP-pool at time 1 is in a steady state, i.e. ΔC(t 0 ) is 0. For each commodity class l the steady state HWP-carbon stock at time 0 is estimated by \(\:{C}_{l}\left({t}_{0}\right)=\frac{{Inflow}_{{l}_{average}}}{k}\) IPCC Eq. 12.4 where the average inflow is calculated as the mean of the inflows of the first 5 years. $$\:{Inflow}_{{l}_{average}}=\frac{\sum\:_{i={t}_{0}}^{{t}_{4}}{Inflow}_{l}\left(i\right)}{5}$$ Abbreviations If abbreviations are used in the text they should be defined in the text at first use, and a list of abbreviations can be provided. Declarations Consent to Publish declaration: not applicable Ethics and Consent to Participate declarations: not applicable Funding Declaration: This research was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC 2037 ’CLICCS—Climate, Climatic Change, and Society’—Project Number: 390683824, contribution to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg. Availability of data and materials The data used for this study generated from FAOSTAT database Competing interests The authors declare that they have no competing interests. Authors' contributions TB carried out the study design and conduct data preparation and analysis. TB wrote and MK revised the manuscript. All authors have read and approved the final manuscript. Acknowledgements We thank Georg Buchholz (GIZ) and Prem Neupane (Hamburg University) for helpful discussion and comment. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6408090","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451478404,"identity":"475c4e36-5a39-4e8c-ba8a-f16a31753ec5","order_by":0,"name":"Tunggul Butarbutar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIiWNgGAWjYPACCwYDEMXYACKZDzAkwNhYAA+EkgBqYQYrk2BgYEsgWQsPko1YgL1E7uGXX9skGMwl8g9+rtxxuI5/9pnPLx78YZDtx2WLRF6atSxQi+WMZGbJs2cOS0icy91mkcDDYDwThzU8EjlmxpJALQY3khkkG9sOSzCc4d1mkCDBkLjhAGEtzD9BWuTP8DwzSDBgSNyPW4vxw48QLWxgWwzO8DA/SEgA2oLLL2femDEznJPgsex5bGbZeCZdcuMZNjOGhAMSxjNw2MLenmP88UeZjZw5e+Ljm407rPnlzjA//vjjj41sPw7vAwGbNA88fqAiEqCYwgOYP/5AF/mAT/0oGAWjYBSMOAAAn9pZShOy7MQAAAAASUVORK5CYII=","orcid":"","institution":"University of Hamburg, World Forestry","correspondingAuthor":true,"prefix":"","firstName":"Tunggul","middleName":"","lastName":"Butarbutar","suffix":""},{"id":451478405,"identity":"ca19e590-dff8-4c5b-a433-2da19886026b","order_by":1,"name":"Michael Köhl","email":"","orcid":"","institution":"University of Hamburg, World Forestry","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Köhl","suffix":""}],"badges":[],"createdAt":"2025-04-09 05:08:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6408090/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6408090/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82061536,"identity":"9dc74901-a208-48eb-9c74-b8589f81d68b","added_by":"auto","created_at":"2025-05-06 11:47:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":218412,"visible":true,"origin":"","legend":"\u003cp\u003eThe Historical trend production of (i)Sawnwood, (ii) Wood-based Panel, and (iii)Paper and Paperboard in the continents- Southeast Asia and Pacific Islands (SEAP), Latin America (LAM), and Africa (AFR). The data are taken from the FAOSTAT-Forestry database.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/fbf91006829c1391fe139f69.png"},{"id":82061560,"identity":"93db2a74-44f8-4d2e-9fa1-f99770974b85","added_by":"auto","created_at":"2025-05-06 11:47:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":155288,"visible":true,"origin":"","legend":"\u003cp\u003eThe Historical production of Sawnwood, Wood-based Panel, and Paper and Paper Board by three different continents- Southeast Asia and Pacific Islands (SEAP), Latin America (LAM), and Africa (AFR)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/e702e64311e5c9fb449d6d1d.png"},{"id":82061558,"identity":"2e22a039-244e-4cd0-bedc-c91aaaf8c852","added_by":"auto","created_at":"2025-05-06 11:47:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":374282,"visible":true,"origin":"","legend":"\u003cp\u003eInflow, HWP C-Stock, by region and in total.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/3af5398dfcb6a609192a1ab3.png"},{"id":82061537,"identity":"1943a224-5799-47f3-a62e-15561e9d85b3","added_by":"auto","created_at":"2025-05-06 11:47:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":383583,"visible":true,"origin":"","legend":"\u003cp\u003eStock change and carbon removal by commodities\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/189df8d758f525a7d4d3c06c.png"},{"id":82061562,"identity":"3897d7a7-edc8-47f5-b926-61c526ace4f1","added_by":"auto","created_at":"2025-05-06 11:47:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":421492,"visible":true,"origin":"","legend":"\u003cp\u003eEmission or removal from different continents\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/67393af2f4bc05b5ef1b3e29.png"},{"id":82061564,"identity":"c59c49f9-9339-40ab-bb40-5a64a22a4d25","added_by":"auto","created_at":"2025-05-06 11:47:24","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":199366,"visible":true,"origin":"","legend":"\u003cp\u003ePotential and net CO\u003csub\u003e2 \u003c/sub\u003eeffect of Substitution in Mt CO\u003csub\u003e2\u003c/sub\u003e eq.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/380cf9d0d831ded6c3659de8.png"},{"id":82061552,"identity":"b4fa5eaa-1d46-4f9d-a760-ba2b4ca81c63","added_by":"auto","created_at":"2025-05-06 11:47:22","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":69013,"visible":true,"origin":"","legend":"\u003cp\u003eAverage annual of Harvested wood Production, C-Stock and Emission/removal (DF=1.0 ) in Tropical Timber Producer Countries from 1961-2017\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/d704422176fe7843121e129e.png"},{"id":82061546,"identity":"92dbb7ce-175a-4f06-aa1c-9b5b0269fb2a","added_by":"auto","created_at":"2025-05-06 11:47:21","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":292931,"visible":true,"origin":"","legend":"\u003cp\u003eInflow, Stock Change and Sink/Removal of HWP from 1990-2017\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/ddb2d63199fc3448ee3a0046.png"},{"id":82062704,"identity":"b8cb3925-a4ed-4329-be03-1494fe080b34","added_by":"auto","created_at":"2025-05-06 12:03:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3597625,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6408090/v1/f4d49222-8894-4cfa-a4e4-b4da337f135c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The substitution effect of harvested wood products from tropical timber producer countries","fulltext":[{"header":"Background","content":"\u003cp\u003eWith the Paris Agreement, 196 parties have committed to keeping global warming at 1.5 to 2 degrees Celsius above pre-industrial levels. The measures also cover activities to maintain and improve the sinks and reservoirs of greenhouse gases, including forests (Article 5, Paris Agreement). Furthermore, the European Union has formulated a long-term strategy to confirm Europe\u0026rsquo;s commitment to lead in global climate action and presented a vision of achieving net-zero greenhouse gas (GHG) emissions by 2050. This vision includes the compensation of unavoidable residual emissions, by either technical (Carbon Capture and Storage, CSS) or nature based solutions (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Beside peatlands, forests are considered as a leading example for supporting nature-based solutions to combat climate change. Forests remove CO\u003csub\u003e2\u003c/sub\u003e from the atmosphere through photosynthesis and convert it into C, which is stored in. After timber harvests a considerable amount of carbon remains stored in harvested wood products (HWPs) for a time span that varies depending on the type of HWPs between months and decades (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). According to Johnston \u0026amp; Radeloff, (2019) the global HWP pool was a net annual sink of 335 Mt of CO\u003csub\u003e2\u003c/sub\u003ee in 2015 and represents less than 1% of total annual GHG emissions.\u003c/p\u003e \u003cp\u003eHWPs are not only a storage of C, but also contribute to the reduction of emissions, since the manufacture of wood products is generally associated with substantially lower emissions than manufacturing functionally equivalent products from non-renewable resources, such as steel, aluminum, or cement. HWPs thus make a dual contribution to achieving net-zero GHG emissions: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) as a sink for atmospheric CO\u003csub\u003e2\u003c/sub\u003e and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) by reducing emissions in manufacturing processes compared to functionally equivalent products. In general, the use of HWPs produces lower emissions than functionally equivalent products. Life cycle analyses are used to quantify the emissions generated in the manufacturing process. The decisive factor here is the energy mix used for producing the energy used in the production process.\u003c/p\u003e \u003cp\u003eThe Intergovernmental Panel on Climate Change (IPCC) provides guidance for including HWPs in national Greenhouse Gas (GHG) emission reports (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, only the change in the C pool of HWPs is considered in national accounting. The emission reductions resulting from the use of HWPs are mainly attributed to the energy sector. To assess the overall contribution of HWPs to achieving net-zero emissions, it is necessary to consider both the storage and the substitution effect.\u003c/p\u003e \u003cp\u003eThe contribution of the forest-wood chain to mitigating climate change has been widely studied. Geographically, the studies concentrate on European countries (\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11 CR12\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), the US and Canada (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), Japan (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), China and Taiwan (\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The corresponding mitigation effects for HWPs derived from timber harvesting in tropical and subtropical forests have been poorly studied, even though tropical countries by 2050 projected to contribute to 12% of the global timber production.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eMore than 40% of the world\u0026rsquo;s 4\u0026nbsp;billion hectares of forests are in tropical regions, covering 1.73\u0026nbsp;billion hectares, corresponding to nearly half of the tropical land area. However, since 1990 the world has lost 420\u0026nbsp;million ha of forest due to land-use change and other non-sustainable land-use practices. Most of the forest area loss occurred in tropical forests of Africa, followed by South America. As a result, the global forest carbon stock decreased from 668 Gt C in 1990 to 662 Gt C in 2020 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Between 2005 to 2010 an estimated area of 2.2\u0026nbsp;billion hectares of tropical forest are subject to forest degradation with an estimated emission of 2.1\u0026nbsp;billion tons of carbon, of which 53% are due to timber harvests (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In sustainably managed boreal and temperate forests, emissions from timber harvests are offset by the storage and mitigation capacity of wood products. Here we investigate to what extent this also applies to tropical and subtropical forests and what conclusions can be drawn for forest management from the perspective of reducing atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentrations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eThe trend in the production of the three commodities under the study.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe carbon content of HWP was calculated on the annual basis production of three primary HWP commodities of Sawnwood, wood-based panels, and paper and paperboard products. Sawnwood dominated HWP production in early 1961 with an 87.73% share. It continuously increased until the year 1990 when the production of Sawnwood reached approximately 65\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e. After 1990, the production of Sawnwood was decreased, and only in 2006 did it get its peak temporarily. By 2018, the production of Sawnwood production is substantially reduced to about 49\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e, i.e., approximately 12% of global Sawnwood production.\u003c/p\u003e \u003cp\u003eThe Wood-based Panel production has continuously increased until 2004, and the increasing rate has slightly slowed down after the year 2004. The rising trend was substantial until 1985. The production, however, expanded from 1\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e in 1961 to 34\u0026nbsp;million m3 in 2018. By 2018, Wood-based Panel shares 25% of the total output of 3 primary HWP semi-finished products.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows a steady increase in the production of Paper and Paperboard in the last twenty years. Only produced as much as 1,7\u0026nbsp;million tons in 1961, the annual production reached 57,6\u0026nbsp;million in 2018. Representing a minor proportion of the total production of the three commodities in 1961, the yearly production of Paper and Paperboard took over the dominance of Sawnwood with a share of 40 percent of the total production of the three by the year 2004 until 2018.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSoutheast Asia and Pacific Island share 61,6% of total HWP production in 2018, followed by Latin America (34,6%) and Africa (3,7%). The dominance of Southeast Asia and Pacific Island started in 1980, and though there was a sharp decline in 1988, SEAP continued to lead the production share until 2018. Africa steadily share the lowest production for all those three products over time. The production history of the three commodities in three continents is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCarbon dynamic of Harvested Wood Products\u003c/h2\u003e \u003cp\u003eThe carbon inflow shows additional carbon to the HWP pool. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e depicts the carbon inflow to the HWP pool. Overall, the carbon inflow to the HWP pool via sawn wood decreased between 1980 and 2018, though periodic variations are noticeable. For example, the inflow of the Sawnwood pool was reduced by 1980, and it increased back in 1997 and 2006. The Sawnwood inflow started to decline steeply after the year 2006. The inflows of Wood-based Panels and Paper and Paperboard, on the other hand, have been steadily increased for the entire period. Compared to the wood-based Panel, Paper and Paperboard flow increased remarkably and profoundly rise in stock in 2017. After taking over the inflow of Wood-based Panels in 1997, Paper and Paperboard continuously increased and overtook the dominance of Sawnwood from 2012 onward.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFollowing the production approach, the total annual carbon inflow by 2017 is 33,6 Mt, consisting of 10.85 Mt of Sawnwood (32%), 8.98 Mt of Wood-based Panel (27%), and 13.77 Mt of Paper and Paperboard (41%). Southeast Asia dominates HWP production and carbon inflow by 58%, followed by Latin America 38.6% and Africa 3.46%. The annual inflow over from 1961 to 2018 is 20 Mt.\u003c/p\u003e \u003cp\u003eThe carbon inflow influences the HWP stock. Early production from 1961 until 1981 contributed to an adverse change in stock and, from that point, started to contribute positively. By commodities, Wood-based Panel contributes mainly to this positive trend followed by Paper and Paperboard. Sawnwood inflow provides a positive impact in the period of 1982\u0026ndash;1998 and 2001\u0026ndash;2006, and in the recent year continues the negative direction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe calculate the CO\u003csub\u003e2\u003c/sub\u003e emission or removal resulting from HWP production for individual HWP. From 1961 until 2017, HWP produced from those 33 tropical countries contributed to the total of 1521 Mt CO\u003csub\u003e2\u003c/sub\u003e eq sink/removal, which equals 26.7 Mt CO\u003csub\u003e2\u003c/sub\u003e eq year \u003csup\u003e1\u003c/sup\u003e. The above zero lines in emission/removal are emission, and below the line is removal/sink. HWP production emitted the atmosphere in 1961 until 1963 From 1964 until 2017, HWP contributes to carbon sink an average of 28.21 Mt CO\u003csub\u003e2\u003c/sub\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Wood-based Panel mainly contributes to this increase. In 2017, the wood-based Panel contributed to 18 Mt CO\u003csub\u003e2\u003c/sub\u003e eq.\u0026nbsp;(see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSoutheast Asia contributed mainly to the emission by 1961 with around 19 Mt of CO\u003csub\u003e2\u003c/sub\u003e and started to contribute to removal by 1980. Latin America contributed to the removal/sink of about 2.4 Mt CO\u003csub\u003e2\u003c/sub\u003e in 1961 and continued until 2017. While for Africa, the removal was as high as 0.06 Mt in early 1961. Indonesia, India, and Malaysia are the three biggest emitter countries, while, Mexico, Brazil, and Thailand are among the three most significant contributors to removal/sink (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSubstitution Effect\u003c/h3\u003e\n\u003cp\u003eThe volume of annual carbon emissions reduction due to material substitution is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, while Fig.\u0026nbsp;9 shows more detail of countries and continents.\u003c/p\u003e \u003cp\u003eAssuming that wood\u0026rsquo;s substitution is mainly material substitution for cement, concrete, or steel for construction, we exclude the HWP of Paper and Paper-based in this calculation. For the three scenarios with displacement factor of 0.7, 2.0, and 4.4 we assess the potential emission reduction by HWP produced. The average potential yearly impact of HWP substitution from 1961 to 2017 is ranges from 998.60 Mt to 6276.93 Mt with the middle range of 2,853 Mt CO\u003csub\u003e2\u003c/sub\u003e eq year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e present the potential carbon of substitution effect with 3 scenario levels and net CO\u003csub\u003e2\u003c/sub\u003e sink potential for substitution. For example, in 2017, the net sink from the substitution effect ranges from 1,579 Mt CO\u003csub\u003e2\u003c/sub\u003e eq (DF\u0026thinsp;=\u0026thinsp;0.7) to 9927 Mt CO\u003csub\u003e2\u003c/sub\u003eeq (DF\u0026thinsp;=\u0026thinsp;4.4), with the middle range of 4,512 Mt CO\u003csub\u003e2\u003c/sub\u003eeq (DF\u0026thinsp;=\u0026thinsp;2.0).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTotal Potential Contribution of HWP\u003c/h3\u003e\n\u003cp\u003eCombining the potential removal/emission from the harvested wood product with the potential substitution in different scenario, we find the net potential effect of harvested wood product in year 1961 is range between 624 Mt CO\u003csub\u003e2\u003c/sub\u003eeq with low displacement factor to 3928 Mt CO\u003csub\u003e2\u003c/sub\u003eeq in the high displacement factor scenario and 1605 Mt CO\u003csub\u003e2\u003c/sub\u003eeq with low displacement factor to 9953 Mt CO\u003csub\u003e2\u003c/sub\u003eeq in the high displacement factor in year 2017 as shown in the Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The total potential net contribution of HWP as a combination of carbon emission/removal from harvested wood carbon pool and potential contribution of substitution.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results show that the use of wood from tropical and temperate forests, as well as wood from managed boreal and temperate forests, can have a significant carbon effect. Nevertheless, some methodological aspects have to be considered when interpreting the results.\u003c/p\u003e \u003cp\u003eThe estimations of carbon effects provided in this study are based on the HWP production data available at the FAOSTAT-Forestry database. The quality and reliability of individual country data may vary depending on the completeness and temporal actuality. In some cases, the data are also not based on comprehensive timber market statistics but are more in the nature of expert estimates. Nevertheless, the FAO data represent the most comprehensive collection of data on timber production in Asia, Africa and South America.\u003c/p\u003e \u003cp\u003eThe tropical regions of Africa, Southeast Asia, and Latin America contribute almost 20 percent to the global harvested wood production (FAO, 2005). Since the 1960\u0026rsquo;s the demand and production of harvested wood products from the tropical producer countries increased. The increase was mainly led by the substantial rise in the Paper and Paper board production and the steady growth of the Wood Panel production in Southeast Asia, and Latin America. In contrast, sawn timber production was more volatile. Compared to other regions, harvested wood production plays a minor role in Africa. In the period 1961 to 2017 Brazil, India, Indonesia, and Mexico are on average the largest producer countries. The change in production rates can be attributed to various factors. At the national level, economic development and the associated demand play a role, as do restrictions on timber harvesting in natural forests, the increasing proportion of forests in protected areas, and the expansion of plantation forestry. As wood products are also internationally traded commodities, events such as the global economic crisis between 2007 and 2009, the collapse of the Soviet Union, or timber trade regulations in Europe, the US or Australia have an impact as well.\u003c/p\u003e \u003cp\u003eThe FAO figures used in this study do not indicate the sources of the wood used for harvested wood production. These can be tropical hardwoods (typically from natural forests), plantation hardwoods (e.g. Eucalyptus, Acacia, Teak, Gmelina and sandalwood), and plantation softwoods (e.g. pines, cypress). While saw logs are mostly from tropical hardwoods, wood panels and paper and paper board are increasingly produced from plantations (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).Globally, the area of planted forests has increased from 172\u0026nbsp;million ha to 295\u0026nbsp;million ha, with 50% of this increase in Asia and 11% in South America, and only 2% in Africa (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).A direct comparison of the production figures with the depletion of natural tropical forests is therefore possible with caution at most for sawlogs.\u003c/p\u003e \u003cp\u003eIn the absence of data on the carbon stock of the initial HWP pool, the starting points for the three commodity classes had to be estimated. For this purpose, the Tier 1 approach of IPCC was used, which is based on the average inflows of the first five years. This approach builds up the HWP-pool in the first three decades, so that the selected decay factor does not yet result in a regular outflow from the HWP-pool. It is not until the end of the 1980s that a realistic carbon content of the HWP pool can be assumed. This effect affects the Paper and Paperboard commodity class less, since the half-life here is only 2.5 years.\u003c/p\u003e \u003cp\u003eIn contrast to North America and Europe, no reliable decay factors are available for HWPs from the tropics and subtropics. Differences are to be expected because, on the one hand, the durability of tropical timber is higher compared to temperate and boreal timber, and, on the other hand, differences in humidity and biotically induced decomposition agents influence the decay processes (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInflow, HWP Stock, Stock change, and Emission/removal of HWP from 1990\u0026ndash;2017\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInflow (Mt C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHarvested Wood Stock\u003c/p\u003e \u003cp\u003e(Mt C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStock change\u003c/p\u003e \u003cp\u003e(Mt C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmission/removal\u003c/p\u003e \u003cp\u003e(Mt CO2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21,07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e387,67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-35,93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e397,47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-38,27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e407,91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-39,65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23,34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e418,72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-40,59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23,30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e429,79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-39,14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24,02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e440,47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-40,27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23,57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e451,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-36,74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e461,47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-42,86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e473,16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-29,11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23,58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e481,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-30,99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24,80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e489,55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-33,42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24,92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e498,67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-31,86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26,79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e507,36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-36,78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e517,39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-39,28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29,70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e528,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-43,43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30,41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e539,94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-43,91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e551,92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12,69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-46,52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e564,61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-41,20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e575,84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-38,13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29,66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e586,24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-30,41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e594,54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-36,12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e604,39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-32,39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e613,22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-31,78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e621,89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-30,45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32,64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e630,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-29,18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32,67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e638,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-26,77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33,01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e645,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-25,70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33,61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e652,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-26,08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27,87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e525,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-35,61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the cut-off Figure from 1990\u0026ndash;2017. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the inflow is relatively increased, with 33.61 MtC in 2017 added to the HWP stock of 652 MtC and contributing to the sink of 26MtCO\u003csub\u003e2\u003c/sub\u003e eq.\u0026nbsp;The average stock of HWP for this period is around 525.33 MtC with an annual inflow of 27.87 MtC, contributing to the annual sink/removal of 35 Mt CO\u003csub\u003e2\u003c/sub\u003eeq y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Using the year 1990\u0026ndash;2017 as a reference, Southeast Asia and the Pacific dominated the average carbon stock in HWP with 281 Mt C y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e(53.43%), followed by Latin America with 219 Mt C y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (41.86%) and Africa with 24 Mt C y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (4.71%). On an annual basis, in the reference time, Southeast Asia contributes to the sink of 21.76 MtCO\u003csub\u003e2\u003c/sub\u003e, followed by Latin America at 12.82 MtCO\u003csub\u003e2\u003c/sub\u003e and Africa at 1.01 MtCO\u003csub\u003e2\u003c/sub\u003e. For 2000\u0026ndash;2012 an annual HWP sink of 44.0 Mt CO\u003csub\u003e2\u003c/sub\u003e yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was estimated for European Union countries (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), while an annual global HWP sink of 335 Mt CO\u003csub\u003e2\u003c/sub\u003eeq y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is reported for 2015 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDisplacement factors are determined by comprehensive life-cycle assessments. A decisive factor for the substitution effects are the emissions of the assumed energy mix. Since it is beyond the scope of the present study to establish the displacement factors corrected for the specific energy mix in the selected countries, we applied a scenario analysis to estimate the substitution effects. The displacement factors used were 0.7, 2.0 and 4.4. They provide a corridor within which the real substitution effects are likely to be located. For the three anticipated displacement factor we found an average annual emission reduction by HWPs between 998 Mt CO\u003csub\u003e2\u003c/sub\u003e eq y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 6278 Mt CO\u003csub\u003e2\u003c/sub\u003e eq y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. These emission reductions are mainly due to using HWPs for construction purposes. The results support the findings of other studies, which also show a significantly higher carbon effect due to substitution effects than to the increase in the HWP pool (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe role of tropical forests in climate change mitigation is complex. Carbon sequestration and emissions occur in different stages of forest stand development and beyond. Forests sequester atmospheric CO\u003csub\u003e2\u003c/sub\u003e by growth or regrowth and emit CO\u003csub\u003e2\u003c/sub\u003e to the atmosphere due to deforestation and the reduction of carbon density within standing forest. Recovery of the carbon by regrowth and ingrowth contribute considerably to carbon enhancement. Depending on the management of forest production regimes, such as intensity of logging intervention or the use of reduced-impact logging in the tropics, studies show the ability of the logging area to recover within the management cycle (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study suggests that timber harvesting can be seen as a transition of carbon from the forest carbon pool to the harvested wood products pool. The increasing wood production in use potentially contributes to a net reduction of CO\u003csub\u003e2\u003c/sub\u003e emissions. Domestic consumption will be more appropriate for this strategy when considering the emission from life cycle products. However, the increase in consumption will be only possible with the sustainability of forest management as HWP substitution is determined by the whole life cycle of the wood (Butarbutar et al., 2019). The holistic approach is required in quantifying carbon pools and flows in the forest sector, including the substitution effect. Therefore, it needs to be integrated into other forest-based accounting systems for a more integrative approach.\u003c/p\u003e \u003cp\u003eThe contribution of HWP to the annual global carbon storage is relatively low. However, the HWP\u0026rsquo;s potential to substitute energy-intensive materials and emissions-intensive energy sources, such as fossil fuel, exceeds the pooled effect of HWPs by orders of magnitude and is relatively untapped. Wood has been both a common and a historical choice for building construction. Hence, the need for just transition, as we move to a green economy-calling businesses to be leaders. At the same time, the rapid global urbanization trends, growing population, and consumer awareness yield many opportunities for implementing a low carbon economy. Cities and industries are at the forefront of climate action. We need to transform how we generate our energy, design our cities, and manage our lands, including forest lands. The world communities and the emerging actors have opportunities to use biodegradable, renewable, and recyclable organic products, i.e., wood, which presents numerous other \u0026ldquo;built-in\u0026rsquo; advantages; and to reduce the hard-to-abate emissions, such as emissions from cement and steel production. In tandem with other renewable energy sources such as solar and wind, the energy-substitution effects presented by the harvested wood products provide opportunities for the energy transition.\u003c/p\u003e \u003cp\u003eWe do not argue for considering the substitution effects of wood use in national GHG accounting. Instead, the energy sector implicitly accounts for the mitigation effects of wood use. Our results show, however, that the mitigation effect of the use of wood must not be ignored when making policy decisions and looking for trade-offs between different interests in the optimal treatment of our forests. A better understanding of potential carbon stock changes in the Harvested Wood Products pool and the substitution effect is essential to support an effective mitigation strategy. However, a more comprehensive approach is required that considers the entire forest-wood chain. A decrease of forest carbon stocks by timber harvesting has to be balanced by substitution and storage effects resulting from timber utilization. There are still many unknowns in this impact chain. To name just a few: Re-growth of forests after use interventions, share of durable products in wood use, decay rates, change in displacement factors due to changes in energy mix towards renewables, recovery rates in mill processing. In addition to the consideration of the carbon balance, factors such as biodiversity, economic development and social welfare must not be neglected. Finally, the CO\u003csub\u003e2\u003c/sub\u003e-benefits of HWPs do not offset the emissions caused by tropical deforestation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\"\u003e\n \u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eData\u003c/h2\u003e\n \u003cp\u003eThis study uses harvested wood data from the FAOSTAT-Forestry database (Food and Agriculture Organization of the United Nations, 2020). The data base includes statistics on the production, import, and export of different categories of harvested wood products. Following the 2019 IPCC refinement (\u003cspan\u003e6\u003c/span\u003e), three commodity classes of semi-finished wood products were used for calculations: (i) Sawnwood, (ii) wood-based Panel, and (iii) paper and paperboard. To compute the fraction of wood products, we use the FAOSTAT data of industrial roundwood, wood-pulp, and recovered-paper. Table \u003cspan\u003e1\u003c/span\u003e shows the tropical timber producer countries included in the study.\u003c/p\u003e\n \u003cp\u003eTable 2. List of Countries involved in the study by region.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1746530997.png\"\u003e\u003cbr\u003e\u003c/div\u003e \u0026nbsp;\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eEstimating the HWP carbon content\u003c/h3\u003e\n\u003cp\u003eThe FAO database includes annual values for raw wood and wood products beginning in 1961. The wood products are divided into different classes, which were combined for the calculation to commodity classes. Following the IPCC guidelines Tier 1 approach (\u003cspan\u003e6\u003c/span\u003e), we use the three commodity classes (\u003cspan\u003e1\u003c/span\u003e) Sawnwood, (\u003cspan\u003e2\u003c/span\u003e) wood-based panels, and (\u003cspan\u003e3\u003c/span\u003e) paper and paperboard The definitions of these commodities are as follows:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSawnwood\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWood that has been produced from both domestic and imported roundwood, either by sawing lengthways or by a profile-chipping process and that exceeds 6 mm in thickness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWood-based panels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ean aggregate comprising veneer sheets, plywood, particle board, and fiberboard.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaper and paperboard\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ean aggregate category that represents the sum of graphic papers; sanitary and household papers; packaging materials and other paper and paperboard. It excludes manufactured paper products such as boxes, cartons, books and magazines, etc.\u003c/p\u003e\n\u003cp\u003eFor further details on the definitions of the three categories we refer to \u003cspan\u003e\u003cspan\u003ehttps://www.fao.org/forestry/statistics/80572/en/\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eIn the FAO database, the production data on sawlogs and wood-based panels produced is expressed in volume units (m3) and on paper products in weight units (t). To calculate the carbon content, these units have to be converted. IPCC (2019) presents uniform carbon conversion factors (cf) of the three aggregated commodity classes for the estimation of the carbon stock of the HWP pool in use (IPCC 2014, Table \u003cspan\u003e2\u003c/span\u003e1.1). The three commodity classes have different retention times in the HWP pool. A constant decay rate (k) is assumed under Tier 1 for the rate at which a commodity class is removed from the HWP pool and is expressed as a half-life in years. The default half-lifes of the three commodity classes are given by IPCC (2014, Table 12.3) and are shown in Table \u003cspan\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv\u003e \u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eHalf-life values and emission factor of commodities (after IPCC, 2014)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCommodity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHalf-live (years)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConversion factor (Mg C/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSawnwood \u003cem\u003e(aggregate)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWood-based panels \u003cem\u003e(aggregate)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePaper and Paperboard \u003cem\u003e(aggregate)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.386\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFollowing a circular economy approach a substantial amount of paper and paperboard is recovered after its original purpose. According to IPCC (2019) recovered paper includes in addition residues from paper and paperboard production. As only limited country data is available from FAOSTAT on recovered (\u003cspan\u003e37\u003c/span\u003e, \u003cspan\u003e38\u003c/span\u003e), we use the generic regional data following Holik, (2013). The respecive recovered paper utilization rates are 69% for Asia, 51% for Europe, and 35% for North America.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisplacement Factor.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSubstituting wood for energy intensive materials reduces GHG emissions (\u003cspan\u003e40\u003c/span\u003e\u0026ndash;\u003cspan\u003e43\u003c/span\u003e) Displacement factors (DFs) relate the emission reduction when substituting a functionally equivalent non-wood product by a wood product to the carbon mass contained in the wood used. DFs are calculated as\u003c/p\u003e\n\u003cdiv id=\"Equa\"\u003e\n \u003cdiv id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:DF=\\:\\frac{{f}_{NW}-{f}_{W}}{{C}_{W}}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere f\u003csub\u003eNW\u003c/sub\u003e are GHG emissions from the use of non-wood and f\u003csub\u003eW\u003c/sub\u003e those from the use of wood, both expressed in mass units of carbon equivalent, and C\u003csub\u003eW\u003c/sub\u003e is the carbon mass content of the wood product. According to Sathre \u0026amp; Gustavsson (2009) DFs range from as low as -2.3 to as high as 15.0. The calculation of for the substitution effect requires detailed information on wood utilization which is not available for most selected countries. Therefore we use a scenario approach, which is based on the average DFs from existing studies (\u003cspan\u003e42\u003c/span\u003e) We use three scenarios applying values of DF\u0026thinsp;=\u0026thinsp;0.7 for a conservative scenario, DF\u0026thinsp;=\u0026thinsp;4.4 for an optimistic scenario, and DF\u0026thinsp;=\u0026thinsp;2.0 representing an intermediate scenario (Sathre \u0026amp; Gustavsson, 2009). As Paper and Paper Board commodities generally are not used for replacing non-wood materials, we restrict the calculation of substitution effects on sawnwood and wood-based panels.\u003c/p\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eCarbon stock change in HWP\u003c/h2\u003e\n \u003cp\u003eThe 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019) \u0026ndash; hereafter referred to as 2019 IPCC refinement - provides different approaches for estimating CO\u003csub\u003e2\u003c/sub\u003e emissions and removals from HWPs. The different methods are related to the processes (i.e. changes of carbon stocks within defined HWP pools or quantifying CO\u003csub\u003e2\u003c/sub\u003e fluxes from and to the atmosphere from HWPs) and the system boundaries (i.e. consuming or producing countries) applied in the calculation. The resulting approaches are shown in Table \u003cspan\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv\u003e \u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003eApproaches to estimating CO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e \u003cem\u003eemissions and removals arising from HWPs (after\u003c/em\u003e (\u003cspan\u003e43\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eApproaches\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProcesses and boundaries\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStock change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChange in the HWP pool accounted for the consuming country\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChange in the HWP pool based on domestically produced stocks.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStock change for HWP of domestic origin (SCAD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChange of HWP pool based on domestically produced and consumed stocks\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtmospheric flow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFluxes of CO\u003csub\u003e2\u003c/sub\u003e to the atmosphere from HWP accounted for in the country where they occur\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSimple decay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarbon transfer from forest carbon pools to HWP pool is counted as emissions from HWP pool at the time of end-of-life of HWP in the producing country\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e \u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eHWP carbon emission/removal,subsitution effect and potential total contribution to the emission reduction\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eEmission/Removal from HWP (Mt CO\u003csub\u003e2\u003c/sub\u003e eq)\u003c/p\u003e\n \u003cp\u003e(a)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSubstitution effect of different scenario (Mt CO\u003csub\u003e2\u003c/sub\u003e eq)\u003c/p\u003e\n \u003cp\u003e(b)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTotal Potential Net Contribution of HWP (Mt CO\u003csub\u003e2\u003c/sub\u003e eq)\u003c/p\u003e\n \u003cp\u003e(a\u0026thinsp;+\u0026thinsp;b)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDF 0.7\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDF 2.0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDF 4.4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDF 0.7\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDF 2.0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDF 4.4\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e625,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1785,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3929,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1785,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3928,32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1784,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3924,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1783,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3924,45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1783,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3923,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1783,18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3923,15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0,68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e623,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1782,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3922,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1783,46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3922,80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1783,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3924,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e625,82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1785,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3925,77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e625,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1786,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3929,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e628,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1789,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3932,98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e627,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1792,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3942,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e631,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1796,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3946,96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e629,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1799,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3959,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e634,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1804,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3964,39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e633,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1809,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3981,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e639,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1815,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3986,93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e637,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1821,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4006,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e646,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1830,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4015,49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e642,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1835,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4037,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e651,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1844,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4046,67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-11,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e647,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1849,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4069,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e658,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1860,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4080,62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-11,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e654,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1869,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4111,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e665,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1880,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4123,64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-11,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e661,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1889,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4155,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e672,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1900,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4167,08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-14,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e668,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1909,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4200,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e682,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1923,95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4215,17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-18,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e677,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1936,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4260,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e696,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1955,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4279,29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-21,95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e689,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1971,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4337,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e711,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1993,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4358,96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-23,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e704,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2012,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4427,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e727,69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2035,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4450,78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-24,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e719,53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2055,79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4522,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e743,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2079,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4546,82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-27,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e735,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2100,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4620,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e762,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2127,84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4648,28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-27,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e753,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2151,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4733,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e780,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2178,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4760,55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-31,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e771,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2204,50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4849,90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e802,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2235,69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4881,09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-32,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e792,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2263,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4979,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e825,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2296,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5012,09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-34,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e814,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2326,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5118,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e848,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2360,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5152,88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-35,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e837,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2392,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5262,55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e873,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2427,89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5298,38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-37,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e861,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2460,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5413,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e898,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2498,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5451,36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-40,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e886,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2532,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5572,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e927,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2573,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5613,10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-41,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e913,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2611,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5744,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e955,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2653,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5786,32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-42,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e941,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2691,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5920,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e984,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2733,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5963,03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-35,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e970,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2772,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6099,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1006,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2808,65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6135,91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-38,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e994,95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2842,70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6253,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1033,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2880,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6292,21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-39,65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1021,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2917,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6418,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1060,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2956,96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6457,73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-40,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1048,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2994,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6587,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1088,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3034,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6628,22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-39,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1075,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3072,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6759,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1114,56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3111,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6798,90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-40,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1102,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3148,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6927,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1142,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3189,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6967,53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-36,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1128,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3224,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7093,56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1165,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3261,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7130,30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-42,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1151,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3290,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7239,65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1194,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3333,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7282,50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-29,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1178,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3368,18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7410,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1207,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3397,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7439,11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-30,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1197,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3421,40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7527,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1228,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3452,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7558,06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-33,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1216,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3475,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7646,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1249,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3509,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7679,91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-31,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1236,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3534,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7775,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1268,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3565,96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7806,88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-36,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1256,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3590,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7900,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1293,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3627,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7936,85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-39,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1280,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3657,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8047,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1319,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3697,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8086,30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-43,43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1305,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3729,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8205,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1348,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3773,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8249,05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-43,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1333,43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3809,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8381,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1377,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3853,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8425,50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-46,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1361,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3890,79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8559,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1408,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3937,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8606,26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-41,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1390,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3973,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8741,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1431,82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4014,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8782,28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-38,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1415,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4045,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8899,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1453,90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4083,18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8937,24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-30,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1438,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4109,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9039,90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1468,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4139,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9070,31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-36,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1455,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4158,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9149,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1491,69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4194,89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9185,40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-32,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1476,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4217,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9279,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1508,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4250,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9311,50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-31,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1495,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4272,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9399,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1527,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4304,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9431,56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-30,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1514,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4328,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9522,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1545,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4358,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9553,23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-29,18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1533,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4380,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9636,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1562,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4409,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9665,57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-26,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1549,84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4428,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9741,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1576,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4454,89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9768,64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-25,70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1564,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4469,73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9833,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1590,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4495,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9859,12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-26,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1579,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4512,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9927,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1605,43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4538,50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9953,41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSince the analyses shown here aim at a global consideration of the corresponding substitution and storage effects, it is irrelevant in which country the harvested wood is converted into HWPs and where the HWPs are consumed. Taking into account import and export commodities would unnecessarily complicate the calculations and would not result in different emissions and removals in the aggregate compared to a direct comparison of national production data. Therefore, a modified production approach is used. According to Sato \u0026amp; Nojiri (2019) the production approach is a trade neutral approach and thus best suited for the current study. We extend the production approach by considering only the production of HWPs in a country, regardless of whether the timber is domestic origin or not.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eEstimating emissions and removals\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eAccording to 2019 IPCC refinement (IPCC, 2019) the net change of the carbon stock in year \u003cem\u003ei\u003c/em\u003e is calculated for each in commodity class \u003cem\u003el\u003c/em\u003e, \u0026Delta;C\u003csub\u003el\u003c/sub\u003e(i). The total CO\u003csub\u003e2\u003c/sub\u003e emissions and removal from net changes of the carbon stock in HWP in use during the year \u003cem\u003ei\u003c/em\u003e, \u003cem\u003e∆CO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2TOTAL\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i)\u003c/em\u003e, is obtained by the sum of the \u003cem\u003el\u003c/em\u003e individual \u0026Delta;C\u003csub\u003el\u003c/sub\u003e(i). Since the unit of the \u0026Delta;C\u003csub\u003el\u003c/sub\u003e(i) is C, a factor of 44/12 needs to be applied to obtain CO\u003csub\u003e2\u003c/sub\u003e values. \u0026Delta;\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i)\u003c/em\u003e is calculated by reducing the HWP pool at the beginning of year \u003cem\u003ei\u0026thinsp;+\u0026thinsp;1, C\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i\u0026thinsp;+\u0026thinsp;1)\u003c/em\u003e, by the HWP pool at the beginning of year \u003cem\u003ei\u003c/em\u003e, \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i)\u003c/em\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Equb\"\u003e\n \u003cdiv id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:\\varDelta\\:\\:{C}_{l}\\left(i\\right)={C}_{l}\\left(i+1\\right)-{C}_{l}\\left(i\\right).$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eTherefore, a positive value represents an increase in the HWP pool during the year under consideration, i.e. a removal. Since, according to the IPCC conventions, removals are designated with a negative sign, the calculated difference must be denoted with a negative sign. Intuitively, it would be simpler to calculate \u0026Delta;C\u003csub\u003el\u003c/sub\u003e(i) as \u003cspan\u003e\u003cspan\u003e\\(\\:\\varDelta\\:\\:{C}_{l}\\left(i\\right)=\\:{C}_{l}\\left(i\\right)-{C}_{l}\\left(i+1\\right)\\)\u003c/span\u003e\u003c/span\u003e, since this would directly result in the IPCC-compliant negative sign for removals. IPCC (2017), Eq.\u0026nbsp;12.1 presents the respective calculations:\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(\\:\\varDelta\\:\\:{CO}_{2\\:TOTAL}\\left(i\\right)=-\\frac{44}{12}*\\sum\\:_{l=1}^{n}\\varDelta\\:{C}_{l}\\left(i\\right)\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e IPCC (2019), Eq. 12.1.\u003c/p\u003e\n \u003cp\u003ewhere \u003cem\u003el\u003c/em\u003e is an index number of a semi-finished HWP commodity class and \u003cem\u003en\u003c/em\u003e is the number of selected commodity classes of the semi-finished HWP commodities. Here n\u0026thinsp;=\u0026thinsp;3, as the three aggregated commodity classes sawnwood, wood-based panels, and paper and paperboard are considered.\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eThe carbon stock in the particular HWP commodity class \u003cem\u003el\u003c/em\u003e at the beginning of the year \u003cem\u003ei\u0026thinsp;+\u0026thinsp;1, C\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i\u0026thinsp;+\u0026thinsp;1)\u003c/em\u003e, is based on the respective carbon stock at the beginning of year \u003cem\u003ei\u003c/em\u003e, \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i)\u003c/em\u003e, the first order decay (FOD) and the carbon inflow to commodity class \u003cem\u003el\u003c/em\u003e in year \u003cem\u003ei\u003c/em\u003e, Inflow\u003csub\u003el\u003c/sub\u003e(\u003cem\u003ei)\u003c/em\u003e.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(\\:{C}_{l}\\left(i+1\\right)={e}^{-k}*{C}_{l}\\left(i\\right)+\\left[\\frac{\\left(1-{e}^{-k}\\right)}{k}\\right]\\:*I{nflow}_{l}\\left(i\\right)\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e IPCC (2019), Eq. 12.2\u003c/p\u003e\n \u003cp\u003eSome authors suggest that a Chi-square distribution is more accurate than the exponential distribution to describe decay (\u003cspan\u003e44\u003c/span\u003e\u0026ndash;\u003cspan\u003e46\u003c/span\u003e)). To be consistent with the IPCC guidelines, we use the decay function following an exponential distribution function (IPCC, 2019, Eq. 12.2). IPCC (2019) omits in Eq. 12.2 an index for commodity classes for the decay constant \u003cem\u003ek\u003c/em\u003e. However, \u003cem\u003ek\u003c/em\u003e must still be determined separately for each respective commodity class \u003cem\u003el\u003c/em\u003e.\u003c/p\u003e\n \u003cp\u003eAccording to IPCC (2019), Eq. 12.3 \u003cem\u003eInflow\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(i)\u003c/em\u003e depends on the approach chosen for system boundaries, i.e. carbon inflow from domestic consumption or carbon inflow from the production from domestic harvests. Here inflow is the total domestic production of HWPs, regardless of the origin of the timber. The FOD for HWP commodity class \u003cem\u003el\u003c/em\u003e is taken into account by calculating a decay constant, \u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e, for each commodity class \u003cem\u003el\u003c/em\u003e over the corresponding half-life, \u003cem\u003eH\u003c/em\u003e\u003csub\u003e\u003cem\u003el\u003c/em\u003e\u003c/sub\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(\\:{k}_{l}=\\frac{\\text{ln}\\left(2\\right)}{{HL}_{l}}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e after IPCC (2019)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eFollowing IPCC 2019, Eq.\u0026nbsp;12.7, the annual carbon inflow from the production to the carbon stock of each HWP commodity class l, Inflow\u003csub\u003el\u003c/sub\u003e (i)\u003csub\u003ei\u003c/sub\u003e, is calculated by\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(\\:{Inflow}_{PAl}\\:\\left(i\\right)={HWP}_{{DP}_{l}}\\left(i\\right)*{cf}_{l}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e IPCC Eq. 12.7\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(\\:{HWP}_{{DP}_{l}}\\left(i\\right)={HWP}_{{P}_{l}}\\left(i\\right)*{f}_{R}\\:\\left(i\\right)\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e IPCC Eq. 12.7\u003c/p\u003e\n \u003cp\u003ewhere\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003ecf\u003csub\u003el\u003c/sub\u003e = carbon conversion factor of commodity class \u003cem\u003el\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ef\u003csub\u003eR\u003c/sub\u003e(i)\u0026thinsp;=\u0026thinsp;Share of woody feedstock commodity class R (IRW, PULP or RecP) for the production of the particular semi-finished HWP commodity class originating from domestic harvest in the year i\u003c/p\u003e\n \u003cp\u003eThe FAO-statistics provide data on HWP for most countries since 1961. No data are available for the initial HWP-pool. The initial HWP-pool was estimated following the Tier 1 approach of IPCC (2019). As a proxy it is assumed that the HWP-pool at time 1 is in a steady state, i.e. \u0026Delta;C(t\u003csub\u003e0\u003c/sub\u003e) is 0. For each commodity class l the steady state HWP-carbon stock at time 0 is estimated by\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(\\:{C}_{l}\\left({t}_{0}\\right)=\\frac{{Inflow}_{{l}_{average}}}{k}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e IPCC Eq. 12.4\u003c/p\u003e\n \u003cp\u003ewhere the average inflow is calculated as the mean of the inflows of the first 5 years.\u003c/p\u003e\n \u003cdiv id=\"Equc\"\u003e\n \u003cdiv id=\"FileID_Equc\" name=\"EquationSource\"\u003e$$\\:{Inflow}_{{l}_{average}}=\\frac{\\sum\\:_{i={t}_{0}}^{{t}_{4}}{Inflow}_{l}\\left(i\\right)}{5}$$\u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIf abbreviations are used in the text they should be defined in the text at first use, and a list of abbreviations can be provided.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration: not applicable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate declarations: not applicable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany\u0026rsquo;s Excellence Strategy\u0026mdash;EXC 2037 \u0026rsquo;CLICCS\u0026mdash;Climate, Climatic Change, and Society\u0026rsquo;\u0026mdash;Project Number: 390683824, contribution to the Center for Earth System Research and Sustainability (CEN) of Universit\u0026auml;t Hamburg.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used for this study generated from FAOSTAT database\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTB carried out the study design and conduct data preparation and analysis. TB wrote and MK revised the manuscript. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Georg Buchholz (GIZ) and Prem Neupane (Hamburg University) for helpful discussion and comment. \u0026nbsp;Our sincere thank go to the editor and anonymous reviewers for their constructive comments that helped us to improve the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEuropean Commission. A Clean Planet for all. A European long-term strategic vision for a prosperous, modern, competitive and climate neutral economy. Com(2018) 773 [Internet]. 2018;25. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018DC0773\u0026amp;from=EN\u003c/li\u003e\n\u003cli\u003eGeden O, Schenuit F. Unconventional Mitigation: Carbon Dioxide Removal as a New Approach in EU Climate Policy. 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J For Econ. 2017 Apr 1;27:50\u0026ndash;9. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"carbon-balance-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cbam","sideBox":"Learn more about [Carbon Balance and Management](https://cbmjournal.biomedcentral.com/)","snPcode":"13021","submissionUrl":"https://submission.nature.com/new-submission/13021/3","title":"Carbon Balance and Management","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HWP, Tropical Forest producers, Displacement factor, Emission reductions, carbon, sustainable forest management, tropical forest, carbon inflow","lastPublishedDoi":"10.21203/rs.3.rs-6408090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6408090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHWPs may contribute to reaching net-zero GHG emissions by sequestering atmospheric CO\u003csub\u003e2 \u003c/sub\u003eand lowering emissions in manufacturing processes in comparison to functionally comparable items. The relevant mitigating impacts for HWPs produced from wood harvesting in tropical and subtropical forests have been inadequately examined, even though tropical nations are anticipated to contribute 12% of the global timber output by 2050 and that more than 40% of the world's 4 billion hectares of forests are in tropical regions, encompassing 1.73 billion hectares, or about half of the tropical land area. Here, we examine the effect of HWPs produced by tropical nations and their significance in terms of lowering atmospheric CO2 concentrations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe carbon content of HWP was determined by calculating the annual output of the three essential HWP commodities: sawnwood, wood-based panels, and paper and paperboard products based on data provided by FAO (source). Southeast Asia and the Pacific Islands accounted for 61.6% of the global HWP production in 2018, followed by Latin America (34.6%) and Africa (3.6%).\u003c/p\u003e\n\u003cp\u003eWood production annually added the inflow to the HWP pool by 28 MtC, contributing to an annual carbon sink of 35.61 MtCO\u003csub\u003e2\u003c/sub\u003e y\u003csup\u003e-1\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eSoutheast Asia and the Pacific led the average carbon stock in HWP during 1990-2017, with 281 Mt C y\u003csup\u003e-1\u003c/sup\u003e (53.43%), followed by Latin America with 219 Mt C y\u003csup\u003e-1\u003c/sup\u003e (41.86%) and Africa with 24 Mt C y\u003csup\u003e-1\u003c/sup\u003e (4.71%). In the reference period, Southeast Asia annually provides 21,76 MtCO\u003csub\u003e2\u003c/sub\u003e to the sink, followed by Latin America with 12,82 MtCO\u003csub\u003e2\u003c/sub\u003e and Africa with 1.01 MtCO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eIn 1961, the net potential effect of harvested wood products ranged from 624 Mt CO\u003csub\u003e2\u003c/sub\u003eeq with a low displacement factor to 3928 Mt CO\u003csub\u003e2\u003c/sub\u003eeq with a high displacement factor and from 1605 Mt CO\u003csub\u003e2\u003c/sub\u003eeq with a low displacement factor to 9953 Mt CO\u003csub\u003e2\u003c/sub\u003eeq with a high displacement factor in 2017.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u0026nbsp; In mitigating climate change, tropical forests play a multifaceted function.\u0026nbsp; Due to deforestation and forest degradation, they are a significant source for global CO\u003csub\u003e2\u003c/sub\u003e emissions. For sustainably managed tropical forest, the contribution to climate change mitigation must consider the entire life cycle of wood. The energy-substitution effects of harvested wood products and other renewable energy sources such as solar and wind offer prospects for reaching net-zero emissions by the energy transition.\u003c/p\u003e\n\u003cp\u003eOur findings indicate that the mitigating effect of wood consumption cannot be disregarded when making policy decisions and seeking trade-offs between competing forest management objectives. Instead, an effective mitigation approach needs a comprehensive understanding of the possible carbon stock changes in the pool of harvested wood products and the replacement impact.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"The substitution effect of harvested wood products from tropical timber producer countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 11:47:15","doi":"10.21203/rs.3.rs-6408090/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-15T14:43:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-14T07:49:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110729759104791845548882960420214684436","date":"2025-06-28T07:11:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-23T17:01:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200031049174615593761373462973360694123","date":"2025-05-03T14:46:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-01T12:55:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-18T14:13:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-18T14:11:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Carbon Balance and Management","date":"2025-04-09T05:00:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"carbon-balance-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cbam","sideBox":"Learn more about [Carbon Balance and Management](https://cbmjournal.biomedcentral.com/)","snPcode":"13021","submissionUrl":"https://submission.nature.com/new-submission/13021/3","title":"Carbon Balance and Management","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"15c16f86-cd1b-4074-a8ef-709d4118b3fe","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-21T08:38:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-06 11:47:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6408090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6408090","identity":"rs-6408090","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}