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Article

Assessing the Greenhouse Gas Mitigation Potential of Harvested Wood Products in Romania and Their Contribution to Achieving Climate Neutrality

by
Cosmin Ion Braga
1,
Stefan Petrea
1,2,
Alexandru Zaharia
1,
Alexandru Bogdan Cucu
1,
Tibor Serban
1,
Gruita Ienasoiu
1,3 and
Gheorghe Raul Radu
1,*
1
National Institute for Research and Development in Forestry “Marin Drăcea”, 128 Eroilor Boulevard, 077190 Voluntari, Romania
2
Faculty of Silviculture and Forest Engineering, “Transilvania” University of Brașov, Șirul Beethoven 1, 500123 Brașov, Romania
3
Faculty of Forestry, Ștefan cel Mare University of Suceava, 13 Universității, 720229 Suceava, Romania
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(2), 640; https://doi.org/10.3390/su17020640
Submission received: 20 November 2024 / Revised: 12 January 2025 / Accepted: 14 January 2025 / Published: 15 January 2025
(This article belongs to the Special Issue Sustainable Forestry for a Sustainable Future)
Browse Figures
Figure 1
<p>Classification of wood products based on FAO forest product definitions.</p> "> Figure 2
<p>Carbon stored in HWPs in different categories. Left gray area shows data created with Equation (6) based on the country-specific data in 1961.</p> "> Figure 3
<p>Inflow from domestic production in HWPs by different categories.</p> "> Figure 4
<p>Carbon balance (emissions and removals) in HWPs by different categories.</p> "> Figure 5
<p>Roundwood (<b>A</b>), sawnwood (<b>B</b>), and secondary processing ((<b>C</b>) wood-based panel; (<b>D</b>) paper, and paperboard) production, import, and export between 1990 to 2022.</p> "> Figure 6
<p>Emission trends based on historical data and projected BAU scenario through 2050, including Monte Carlo variants (blue lines).</p> "> Figure 7
<p>Projected pathways of CO<sub>2</sub> emissions from 2023 to 2050 across five models.</p> ">
Review Reports Versions Notes

Abstract

:
Forests mitigate greenhouse gas (GHG) emissions by capturing CO₂ and storing it as carbon in various forms, including living biomass, dead wood, soil, and forest litter. Importantly, when trees are harvested, a portion of the above-ground biomass is converted into harvested wood products (HWPs), which can retain carbon for decades. With approximately 7 million hectares of forest (30% of its land area), Romania significantly contributes to the country’s carbon budget through the HWP pool. Using country-specific data from 1961 to 2022 and an IPCC method, we tracked HWP carbon storage and projected future scenarios to evaluate the category’s significance in achieving the 2050 climate target. During this period, the carbon stored in Romanian HWPs more than doubled from 28.20 TgC to 60.76 TgC, with sawnwood products as major contributors. Fluctuations were influenced by domestic policies, market dynamics, and industry changes, notably after the 1990s. Annual carbon inflow dipped to 0.65 TgC in 1994 and peaked at 2.54 TgC in 2013. By analyzing the scenarios, we demonstrated that a moderate growth trajectory in carbon inflow, combined with a focus on producing long-lived wood products, could double carbon stock changes by 2050 to 4.4 TgC—roughly 4% of the country’s current total emissions excluding the LULUCF sector. Additionally, based on sustainable forest management practices in Romania, this approach would significantly enhance the carbon pool and its importance in achieving the country’s climate policies.

1. Introduction

Global warming represents the most important and complex environmental issue that society faces today. Forest ecosystems are essential in mitigating global warming by capturing significant amounts of atmospheric carbon dioxide (CO₂) and storing it in various carbon pools, including living biomass, dead wood, litter, and soil [1,2,3]. However, besides the net stock of living biomass, part of the loss in tree biomass, due to harvest activity, does not imply that the entire carbon stock in these reservoirs is released into the atmosphere [4]. Instead, when trees are harvested, harvested wood products (HWPs) extend the forest’s carbon-storing function, incorporating the carbon cycle as long-term storage reservoirs [5,6,7]. HWPs vary widely in lifespan, ranging from a few months to several centuries [8], with their carbon content remaining stored until the products decompose or are burned [9].
In the European Union, forests and HWPs collectively store approximately 13% of total CO₂ emissions, with HWPs alone accounting for about 10% of this sequestration [3,7]. HWPs also play a role in reducing emissions from high-energy construction materials like steel and concrete, contributing to the long-term reduction in CO₂ emissions [10,11]. This contribution aligns with the objectives of international climate frameworks, such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Paris Agreement, which emphasize comprehensive carbon stock reporting within the Agriculture, Forestry, and Other Land Use (AFOLU) sector using IPCC guidelines [6,12].
The mitigation potential of HWPs, recognized by the Kyoto Protocol [13], is realized through two primary mechanisms: (1) carbon sequestration, where HWPs serve as carbon reservoirs, and (2) the substitution effect, whereby HWPs replace carbon-intensive materials and fossil fuels [3,7,14]. Consequently, HWPs are integral in reducing CO₂ emissions and associated pollutants [15]. Nonetheless, the sustainability of carbon storage in HWPs depends on sustained wood consumption. A reduction in wood usage could decrease demand for timber, slowing sustainable forest management practices and reducing the production of long-lived HWPs that store carbon [16]. This could also lead to greater reliance on materials with higher carbon footprints, diminishing future carbon sequestration benefits [17]. Although the carbon stock in HWPs has increased significantly in recent years, particularly for certain countries, and is projected to grow further [4,6], recent projections indicate a global increase in wood consumption of approximately 54% by 2050 relative to 2010 levels [18].
HWPs encompass a diverse array of products, such as sawnwood, wood-based panels, furniture, and paper products (Figure 1), each with unique carbon storage properties and life cycles [4,8]. Long-lasting items, such as furniture, retain carbon for extended periods, delaying its release back into the atmosphere [19]. Short-lived items, like cardboard packaging or paper, may also store carbon over long periods, especially when disposed of in anaerobic landfills where decomposition is slow and incomplete [1]. The contribution of HWPs to climate mitigation, therefore, depends on the entire life cycle of these products, encompassing their use, recycling, and final disposal through burning or decomposition [2].
By promoting the sustainable production of wooden furniture, practices that result in long-term climate change mitigation are encouraged, while also supporting the maintenance of carbon stocks [20]. As a significant consumer of wood, the wood processing and furniture industry can become a key player in carbon capture and storage.
A series of factors contribute to the annual rate of carbon accumulation in HWPs. These factors are determined by the annual wood harvest, the final destination of these products, the lifespan of the products, and their disposal (burning) or recycling at the end of their life [3,21]. Besides these primary factors, there is also a category of secondary factors affecting the annual rate of carbon stock variation in HWPs. These are characterized by the types of fluxes used to calculate a country’s stock changes and the methods used for estimating these carbon stocks [22]. The annual capacity of carbon entering HWP stocks is substantial compared to the annual amount of carbon stored in forests. However, these estimates are also uncertain [23]. Determining this annual carbon storage capacity in HWPs relies on a robust methodological framework, integrating methods and equations from the IPCC guidelines for National Greenhouse Gas Inventories and the Revised Supplementary Methods and Good Practice Guidance derived from the Kyoto Protocol, as well as publications from the specialized literature [24]. Past studies [3,11,25] have made estimates regarding the annual carbon storage in HWPs at the European level, including for Romania.
The forest area covers approximately 30% of Romania and is composed mostly of native species [26]. The forestry and wood processing industry are an important branch of the Romanian economy [27]. Forests capture approximately 26% of Romania’s total CO2 emissions [28]. Annually, forests accumulate approximately 6.5 million tons of carbon (including all C pools), equivalent to 26 million tons of CO2 [28]. Most of the forests are covered by deciduous trees, with beech being the most representative species, and natural regeneration is the most common form of new forest establishment.
According to the National Forest Accounting Plan (NFAP) and the National Forest Inventory (NFI, second cycle 2018), there is an overall increase in above-ground forest carbon stock, as the majority of Romania’s forest stands are in the 40–80-year age classes due to historical factors [26,29]. This implies that most of these stands will reach maturity between 2030 and 2050, potentially leading to an increase in the availability of wood for harvest during this period. However, approximately half of Romania’s annual timber production is used for energy purposes, primarily in households, highlighting a significant gap between production and apparent consumption [30].
Based on the annual GHG reports, Romania has made progress in reducing emissions [28]. However, projections highlight challenges in meeting future targets under certain scenarios [12]. While the perception of climate change among the Romanian population is primarily linked to deforestation, industrial activities, and increasing urbanization [31], HWPs can serve as a potential tool for mitigating climate change [32]. However, there are limited studies assessing HWPs in Romania, with some published in nationally recognized journals [33,34] or national communications [35].
To meet national climate goals, ongoing monitoring of HWPs’ contributions to carbon stock and GHG mitigation is essential, and enhanced monitoring tools are needed to support these objectives and to respond to national commitments on GHG reporting such as the National Greenhouse Gas Inventory.
This study aims to (1) employ IPCC-recommended tools for accounting HWPs, (2) establish a framework for assessing the national-level contributions of HWPs to carbon stock, and (3) project HWP carbon stock changes until 2050 under different scenarios, using Romania-specific forestry data from the FAOSTAT dataset, based on national statistics.

2. Materials and Methods

2.1. Method Used

Regarding the methods for estimating the carbon stock in HWPs, the following main approaches can be identified: (a) the stock-change approach, (b) the production approach, (c) the atmospheric-flow approach and the simply decay approach [6,19,22,36]. These approaches are also presented as Tiers I-III. Based on ongoing debates, the EU decided in 2009 to support approach (b) based on production from domestic harvests, with options to include exports when emissions occur and/or to account for exports as being immediately oxidized or not considered in calculations [22]. For estimating the annual changes in the carbon stock for HWPs in Romania, a production approach (Tier II; [19]) is proposed, aimed at evaluating wood consumption and creating long-lasting products. Based on the specificities of different types of HWPs, the level of processing, destination, and life cycle are analyzed. Data for estimating the carbon stock had been obtained from official industry reports [37,38], reflecting annual production and historical records. Carbon stock changes in the HWP pool were calculated accounting for feedstock fractions and annual additions to HWP based on industrial roundwood, sawnwood, wood-based panels, and paper products (Table 1).
The methodology uses a first-order decay function to model the rate at which HWPs release stored carbon over time, according to Equation 12.2 of [39] based on the lifespan and decay rates of different HWP categories. This function accounts for carbon release during the product’s useful life and potential end-of-life scenarios, such as landfill disposal or combustion. To apply the decay function, default values for the half-lives of various HWPs are needed, extracted from the 2019 IPCC Refinement guidelines.
According to Equations (1) and (2), the annual change in the carbon stock in HWPs of each category (sawnwood, wood-based panels, paper and paper products) is calculated by considering both the inflow of new HWPs entering use and the outflow as older HWPs decompose and release the stored carbon.
C i + 1 = e − k × C i + 1 − e − k k × I n f l o w i
∆ C i = C i + 1 − C ( i )
where C(i)—the carbon stock at year i, Mt C; k—decay constant of first-order decay for each HWP category class given in units yr−1; k = ln(2)/HL, where HL represents the half-life values. We used 35, 25, and 2 years for sawnwood, wood-based panels, and paper products, according to 2019 IPCC Refinement default values; Inflow(i)—the carbon inflow to the particular HWP category during the year i, Mt C yr−1; ∆C(i): carbon stock change in the HWP category class during the year i, Mt C yr−1.
Equation (3) was applied to differentiate between imported timber used in HWP production and HWPs derived from domestic harvests. Additionally, Equations (4) and (5) complement the overall calculation.
I n f l o w ( i ) = P × f D P ( i )
f I R W i = I R W P i − I R W E X i   I R W P i + I R W I M i + I R W E X i
f P U L P i = P U L P P i − P U L P E X i   P U L P P i + P U L P I M i + P U L P E X i
where f D P i = {   f I R W i , for sawnwood and wood-based panels, f I R W i × f P U L P i , for paper and paperboard}; Inflow(i)—the amount of wood entering HWPs from year i, measured in gigagrams of carbon per year (Gg C y−1); P—annual carbon production from wood and paper products; IM—imports; EX—exports; IRW—roundwood industry; PULP—paper and paperboard; ΔC(i)—carbon annual stock, in Gg C y−1. The source of all Equations (1)–(5) represents the Refinement IPCC 2019 guidelines.
Equation (6) shows the extrapolated growth for the period between 1900 and 1960, as data were only available from 1961 onward in the FAOSTAT database.
V t = V 1961 × e ( U × ( t − 1961 )
where t—year; Vt—annual quantity of wood derived from production, imports, and exports for the year t (Gg C yr−1); V1961—annual quantity of wood derived from production, imports, and exports for the year 1961 (Gg C yr−1); U—annual estimated rates for roundwood consumption (from 1900 to 1960), with default values specific to each continent (U = 0.0151 yr−1, Europe).
Based on 2019 refinement IPCC guidelines, the methodology for estimating carbon stock and CO2 emissions in HWPs, Equations (7) and (8), involves using conversion factors, carbon content values, and density values to translate the volume of HWPs into figures for carbon stock and CO2.
C ( i ) = C F × D × V 1 + ω / 100
H W P C O 2 = ∆ C ( i ) × ( − 44 / 12 )
where CF—carbon fraction; D—wood density; V—volume; ω—wood moisture; HWPCO2—removal of CO2 from HWPs.
The annual input of HWPs is equal to the annual rate of change in the total HWP carbon stock. Equation (9) estimates the removals and emissions from the HWP carbon pool using the production approach. Thus, annual change in carbon stock ( ∆ C P A   ) HWPs in use ( ∆ C H W P _ D H ), and HWPs for products made from wood domestically harvested specific each country ( ∆ C S W D S _ D H ) are used.
∆ C P A = ∆ C H W P _ D H + ∆ C S W D S _ D H

2.2. Uncertainty Analysis

The uncertainty in FAO data on wood products arises from various factors related to data collection, reporting practices, estimation methods, and potential data gaps. The IPCC provides guidance on default uncertainty values for activity data; typical uncertainty ranges were as follows: (i) production data: ±10% to ±30%, (ii) import and export data: ±5% to ±20%. We chose production data with uncertainty ±10% because Romania likely has reliable production data due to regulatory requirements and enforcement mechanisms like the “Traceability Timber” System (SUMAL 2.0). In addition, we chose import and export data with uncertainty ±5%, because customs data are generally accurate, but minor discrepancies can occur due to misclassification or reporting errors.
The carbon fraction factor (CF) for wood products refers to the proportion of the product’s dry mass which is C. The uncertainty is generally considered to be ±5% of the CF value, reflecting the natural variability in wood composition due to species differences, growing conditions, and processing methods [19].
Wood density (WD) is a crucial parameter in calculating the carbon content of HWPs, especially when converting volume measurements to mass. Just like the CF, WD has inherent variability due to differences in species, moisture content, and processing methods. The standard deviation for wood density is generally considered to be around ±10% of the mean value unless more precise data are available.
Uncertainties from WD and CF were combined to find the overall uncertainty in the C content. Assuming the uncertainties are independent and random, we used the root-sum-square method, shown as follows in Equation (10):
u C = u D 2 + u C F 2 = ( 0.10 ) 2 + ( 0.05 ) 2 = 11.18 %
Uncertainties of the decay rates (half-life values) were assigned values based on literature values, typically ±10%.

2.3. Monte Carlo Analysis

To enhance the robustness of our projections and quantify the uncertainties associated with both historical data and future predictions (i.e., the business-as-usual scenario), we conducted a Monte Carlo simulation analysis with 500 variants. This analysis included uncertainties for emission factors such as wood density (WD), carbon fraction (CF), and decay rates used in carbon stock calculations. Probability distributions, based on standard deviations and data characteristics, were assigned to each uncertain parameter. In each simulation run, random values were drawn from these distributions and carbon stocks were recalculated to produce a range of possible outcomes. We then calculated the mean, as well as the 5th and 95th percentiles, to define a 90% confidence interval for carbon stock changes. This Monte Carlo analysis provided a statistically robust dataset that captures the variability in projected carbon stocks for HWPs.

2.4. Projections Description

2.4.1. Business as Usual

The methodology for projecting carbon stock change in the HWP pool from 2023 to 2050 is based on historical data, with a reference period from 2010 to 2022. This period incorporates both national and EU policies to ensure realistic projections. The reference period, which overlaps with NFI measurements, indicates that the forest area has remained relatively stable. According to the NFI results and the age class distribution, the growing stock has an average stand age of 40–80 years, placing it in its most productive period [29]. Consequently, many stands are expected to reach peak maturity (i.e., the typical harvest age) between 2030 and 2050, which is likely to increase the volume of wood available for harvest. Projections under the business-as-usual (BAU) projection use a constrained linear growth model that starts with historical averages of production, imports, and exports, moving to historical maximum values by 2050. It incorporates an expected increase in the wood available for harvest. Still, it assumes no significant policy shifts affecting the balance between wood used for energy purposes (e.g., firewood) and wood allocated for long-lived products. This approach is grounded in observed data, limiting unrealistic extrapolation and reflecting achievable growth.

2.4.2. Baseline Static Averages

This projection is a theoretical assumption designed to demonstrate how the accounting of the HWP pool would behave if a relatively consistent annual amount of feedstock were maintained for the inflow into the wood products pool. Based on this scenario, future production, imports, and exports are projected by maintaining the historical average values from 2010 to 2022 throughout the projected period from 2023 to 2050. This approach assumes no major shifts in policies, market dynamics, or technological advancements, essentially reflecting a „business-as-usual” scenario with stable forestry sector conditions. The methodology involves calculating the average annual values for production, imports, and exports of HWPs from the reference period and keeping these constants over the projection period.

2.4.3. Product Mix Shift Scenario

This scenario examines the impact of reallocating HWP composition toward sawnwood, a product with a longer lifespan, to increase carbon storage without increasing the total annual feedstock entering the wood product pool. This scenario seeks to enhance carbon sequestration, as sawnwood’s long half-life (about 35 years) allows for extended carbon retention. Starting with the same total inflow values as the business-as-usual (BAU) scenario, the product mix was adjusted gradually from 2023 to 2050, raising the sawnwood proportion while reducing the shares of shorter-lived products like wood-based panels and paper products. This shift assumes growing market demand for sawnwood, encouraged by policies that promote long-lived wood products for climate mitigation, as well as the industry’s capacity to adapt to increased sawnwood output.

2.4.4. Moderate Growth Scenario

This scenario projects a 30% increase in production and of annual inflow of wood into the wood product pool from 2023 to 2050, reflecting the influence of EU Circular Economy goals under the Green Deal. Starting with the historical average values from 2010 to 2022, linear growth of 30% is distributed evenly over the 2023–2050 period, representing a moderate annual increase. This specific scenario provides insights into how policy-driven growth and sustainable market demand could increase Romania’s HWP carbon storage, contributing to climate mitigation goals. We use the same considerations for carbon modeling, according to prior scenarios presented.

2.4.5. Moderate Decline Scenario

In this scenario, a 30% reduction in the annual inflow of harvested wood products is projected from 2023 to 2050. This anticipated decline reflects a cautious approach to forest management, driven by strengthened environmental protections, reduced harvesting limits, and a community focus on conservation and biodiversity. The model assumes a gradual decline from the historical average values (2010–2022), with annual reductions calculated to achieve a 30% decrease by 2050. For carbon modeling, we applied the same methodology used in prior scenarios.

3. Results

3.1. Carbon Stock in HWP by Different Categories

A general overview of the accumulated carbon stock in the main categories of harvested wood products (HWPs) in Romania for the period 1900–2022 is provided in Figure 2. The quantity of carbon in HWPs has been estimated starting from 1900, but the results between 1900 and 1960 were extrapolated using Equation (6). However, we only analyzed the data from 1961 to 2022, using the FAOSTAT database. For the analyzed period, a characteristic of the HWP carbon stock has been continuous growth or accumulation. Thus, the total quantity of carbon in HWPs increased from 28.77 TgC in 1961 to 60.76 TgC in 2022, meaning 111.17% growth of HWPs in 61 years.
Regarding the other HWP stocks (sawnwood, wood panels, and paper products), they experienced significant growth over the analyzed period. Sawnwood showed an upward trend in carbon stocks, with nearly double values reported for 2022 (44.20 TgC, with 23.46 TgC from softwood and 20.74 TgC from hardwood) compared to 1961 (27.47 TgC, with 16.57 TgC from softwood and 10.90 TgC from hardwood). Similarly, the carbon stock in wood panels exhibited an upward trend. For the relatively recent situation in 2022, the highest value (16.04 TgC) of the carbon stock in wood panels was recorded, compared to the reference year 1961 (1.06 TgC). Additionally, the carbon stock in paper products reached a peak in 1988 (0.91 TgC), but by 2022, it had decreased to approximately half (0.52 TgC) compared to the maximum value recorded during this period analyzed (1961–2022).

3.2. Carbon Inflow from Domestic Production in HWPs by Different Categories

Regarding the total carbon stock due to inflow from domestic production (IDP) during the period 1961–2022 (Figure 3), a minimum value was recorded in 1994 (0.65 TgC), with two peak values in 1984 (1.99 TgC) and 2013 (2.54 TgC). Similarly, the smallest values were obtained for the carbon stock in the paper, with the minimum value recorded in 1962 (0.04 TgC) and the maximum value in 1978 (0.32 TgC). The carbon stock in panels recorded a minimum value in 1960 (0.04 TgC), while the highest stock was recorded in 2016 (1.23 TgC). Regarding the carbon stock in sawnwood, minimum values were recorded in 1992 (0.18 TgC for softwood) and 1998 (0.20 TgC for hardwood), with maximum values in 2020 (0.81 TgC for softwood) and 1984 (0.85 TgC for hardwood).

3.3. Carbon Balance in HWPs by Different Categories

During the analyzed period (1961–2022), the annual carbon stock change from HWPs generally increased over time, as shown in Figure 4. The initial values were around 1.2 TgC in 1961, progressively increasing in recent years (2012–2022) and peaking at 2.54 TgC in 2013. Similarly, the sawnwood production from conifers generally increased over time, reached a peak in 2017 at 0.37 TgC, and then showed a moderate decline in 2022 to 0.27 TgC. On the other hand, the broadleaf sawnwood production displayed more variability. It recorded the highest production in 1967 at 0.43 TgC, exhibited a gradual decline starting in 1980, and fluctuated at around 0.03 Tg C in recent years, reaching −0.01 TgC in 2022. The production of wood panels showed a generally upward trend from 1961 through the early 2000s, reaching its highest value of 0.94 in 2013. Afterwards, the values stabilized and showed minor fluctuations. The lowest value occurred in 1994 at −0.08TgC and the production in 2022 was 0.37 TgC. Furthermore, paper and paperboard production saw a sharp decline during the 1990s and early 2000, reaching negative values in some years. A modest recovery occurred after 2010, with a value of 0.04 TgC in 2022.

3.4. Carbon Flow in HWPs by Different Categories

Since the FAO database has provided information regarding the imports and exports of forest products only after 1990, subsequent analyses focused solely on this period (1990–2022). Over the past 30 years, the situation of roundwood imports and exports has shown a more or less distinct dynamic. Thus, starting from 2010, roundwood has exhibited an upward trend, marked by significantly higher imports compared to exports, which have remained relatively constant over the past few decades (Figure 5A). Compared to imports, the exports of roundwood for various uses (e.g., sawnwood) have been significantly higher. Sawnwood, the main product of roundwood, has shown an upward trend in exports since 1990 (Figure 5A,B). After 2007, panels, another important category of forest products, recorded high export values that were maintained until the end of the analyzed period (Figure 5A,C). In contrast to these, paper products have experienced an upward trend in imports compared to exports, especially after 2007 (Figure 5A,D).

3.5. Projections

In the business-as-usual (BAU) scenario (Figure 6), which includes a Monte Carlo simulation with 500 iterations, the mean value indicates a gradual increase in annual CO₂ removals. By 2050, the projected total CO₂ capture reaches approximately −2630 kT CO₂. However, uncertainty remains high, at 86%, resulting in a wide range of potential values by 2050, from −1300 kT CO₂ to −3700 kT CO₂. Despite this variability, the harvested wood product pool consistently acts as a net carbon absorber throughout the projection period.
According to Table 2 and Figure 7, each scenario provides a clear overview of the projected effectiveness in reducing CO₂ emissions up to 2050. Alongside the BAU scenario, the Static Average scenario shows a greater overall decline, achieving −1584.25 kT CO₂ by 2050. Initial reductions in this scenario are strong, but the rate of decline slows after 2030, leading to diminishing returns by the mid-century. In the Product Mix Shift scenario, emissions are projected to decrease from −2372.53 kT CO₂ in 2022 to −3185.87 kT CO₂ by 2050, with a steady increase in reduction percentage, reaching 46% by 2050 due to a successful shift toward lower-emission products. The Moderate Growth scenario delivers the most substantial reductions, with emissions reaching −4420.81 kT CO₂ by 2050, representing a more than 100% improvement over the BAU scenario. Conversely, the Moderate Decline scenario initially achieves reductions but ultimately reverses, resulting in emissions of 593.42 kT CO₂ by 2050—a 127.19% increase from the 2020 baseline, signaling an unsustainable long-term trend.
The quantitative differences across the various emissions scenarios are outlined in Table 2, at key intervals up to 2050. Information presented for each scenario allows for a clear comparison of the impact on CO₂ emissions over time, highlighting how different policy choices extend emissions reductions. For comparison purposes, the table also shows the percentage differences according to the baseline scenario (considered BAU) and examines each scenario’s effectiveness at distinct milestones, offering a basis for evaluating long-term climate goals and the potential cumulative impact of each approach by the mid-century.

4. Discussion

In this study, we estimated the carbon stock and carbon stock change in HWPs at the national level from 1961 to 2022. We conducted a Monte Carlo uncertainty analysis based on available data and emission factors. Using a defined reference period, we simulated future projection pathways to assess the most plausible contribution of the HWP pool to mitigation strategies and to determine the potential ranges of these projections. A particular focus was on the period after 1989, which is the base year under the UNFCCC convention, according to the methodology from the Revised KP Supplement Document [40]. As in other European studies [1,22,41,42] and also at the global level [20,43,44,45], our results indicate a significant and continuous accumulation of carbon in HWPs (Figure 2). This gradual increase in the carbon stock reflects the growing use and extended lifecycle of HWPs, which are critical factors in improving carbon storage and supporting GHG mitigation [15]. The total HWP carbon stock doubled over the analyzed period, suggesting a positive contribution of the forestry sector to Romania carbon balance (Figure 2). A significant trend is the increase in sawnwood carbon stock. The peak values observed in the mid-1980s for both softwood and hardwood indicate a period of high logging activity and market demand, possibly linked to economic or policy changes at that time [46,47]. In contrast, the carbon stock in paper products displayed a different trend, peaking in 1988 and subsequently declining by half in 2022. According to this period, a possible explanation for this decline could be associated with changes in paper consumption patterns, a shift toward digital media, and improved recycling practices [48]. The panels category demonstrated the most significant growth relative to its initial value, with carbon stock increasing from 1.04 TgC in 1960 to 15.00 TgC in 2020. This dramatic rise suggests a growing demand for engineer wood productions such as plywood and fiberboard, which have become crucial today for the building sector [49].
The analysis of carbon stock inflows from domestic production (IDP) for the period 1961–2022 reveals fluctuating patterns across different categories of HWPs (Figure 3). These variations are indicative of possible changes in domestic wood production, market demand, and external socio-economic factors influencing the forestry sector in Romania. The total carbon stock from IDP showed a notable minimum in 1994 (0.65 TgC), coinciding with a period of economic transition and restructuring in Romania [34,50]. The decline in domestic production during this time likely resulted from the economic instability and changes in forest management following the political and economic reforms of the early 1990s, for instance, by forest privatization [51]. In contrast, peak values recorded in 1984 (1.99 TgC) and 2013 (2.54 TgC) may reflect periods of heightened domestic production, driven by increased demand for wood products. In addition, sawnwood, a major contributor to the HWP pool, showed significant fluctuations in both pool categories (Figure 3). The minimum values recorded in the early 1990s and late 1990s correspond to periods of economic downturn and reduced logging activities [27]. For the carbon stock in the paper products, the observed minimum in 1962 (0.04 TgC) and peak in 1978 (0.32 TgC) suggest a significant increase in paper production and consumption during the latter period, attributed to industrial development and the expansion of the publishing and packaging sectors in Romania, especially in the early 1970s [34]. On the other hand, the panels category exhibited an increase in carbon stock from a minimum of 0.04 TgC in 1960 to a maximum of 1.23 TgC in 2016. This trend reflects the increased adoption of panel products (i.e., particleboard and fiberboard) in the construction and furniture industries over the last few decades; this trend has also been confirmed in other countries [52]. Furthermore, the peak in 2016 can be possible due to a combination of factors such as increased investment in the manufacturing sector and advancements in wood processing technology [34].
Overall, the carbon stock change in HWPs showed an increase from 1961 to 2022, peaking in 2013 at 2.54 TgC (Figure 4), a possible explanation being reflected by the harvest rates and durability of forest products used [22]. Furthermore, the sawnwood production from conifers increased until 2017 before a moderate decline by 2022, while broadleaf sawnwood production peaked in 1967 and then steadily declined, reaching negative values in 2022, likely reflecting market challenges [53]. Wood panel production grew steadily until 2013 before stabilizing, while paper and paperboard production declined sharply in the 1990s and early 2000s, probably due to the digitalization process, with a modest recovery after 2010.
The trade dynamics of HWPs in Romania from 1990 to 2022 (Figure 5) reveal distinct patterns of imports and exports, probably influenced by both domestic and international factors. The analysis indicates a significant shift in the trade balance of various forest products, highlighting changes in demand, production capacity, and policy regulations over the past three decades. Thus, starting in 2010, the import of roundwood has shown a distinct upward trend, surpassing exports, which have remained relatively constant (Figure 5A). This shift suggests an increasing dependence on imported raw materials to support the domestic wood processing industry, a fact highlighted by a prior study [34]. On the other hand, the consistent exports of roundwood and the significant increase in sawnwood exports since 1990 indicate that Romania has developed a strong capacity for processing raw wood into value-added products compared with the wood processing industry, where investments have been limited; this trend has also been observed in Slovakia [54]. Additionally, the export of panels has shown a substantial increase, particularly after 2007, and has remained high throughout the analyzed period (Figure 5C). This trend probably reflects the growing role of Romania as a key supplier of panel products in Europe [55]. In contrast, the import of paper and paperboard products has shown a marked increase compared to exports, especially after 2007 (Figure 5D). These increases could also indicate a growing consumption of paper and paperboard for packaging, driven by the expansion of e-commerce and changes in consumer behavior [56].
The overall trends in Romanian HWP trade highlight a dual role as both a significant exporter of processed wood products (i.e., sawnwood) and an importer of raw materials (i.e., roundwood) and certain finished products (i.e., wood-based panels). This dynamic suggests, on the one hand, the development of the wood processing industry in recent decades, and on the other hand, the potential vulnerabilities, such as dependence on imported raw material (i.e., roundwood) and limited domestic production (paper and paperboard). These patterns could have potential implications for the sustainability of the forest sector in Romania [32].
The methodology for projecting HWPs in Romania from 2023 to 2050 is grounded in historical data and incorporates national and European Union (EU) policies, as well as sectoral developments, to ensure realistic and robust outcomes [3]. The scenario analysis aims to explore the implications of each, comparing their effectiveness in reducing emissions and their alignment with sustainable climate strategies. The business-as-usual scenario demonstrates the gradual increase in annual CO2 removals, which indicates a modest but steady approach to carbon sequestration, which lasts for a long time as there is a C inflow from HWPs and sustainable forest management [57]. However, the high uncertainty (86%) suggests that external factors such as changes in policy, technological development, and economic conditions, could significantly affect outcomes [58]. Additionally, the implantation of SUMAL 2.0. introduced improved functionalities, providing reliable data on wood harvest volumes and reinforcing due diligence measures on wood legality and supply. These developments have significantly improved enforcement, reduced illegal logging, and enhanced the reputation of Romanian HWPs in EU markets [59]. The Static Average scenario shows a stronger initial reduction in CO2 emissions with a notable achievement of −1584.25 kT CO2 by 2050. This scenario provides a baseline against which other scenarios can be compared, helping us to understand the potential impacts of changes in policies, market dynamics, or technological innovations on HWP production and associated carbon stocks. However, the slowing rate of decline after 2030 suggests diminishing returns, which could reflect the limitations of maintaining the same strategies (i.e., forest practices) over time without further innovation or adaptation. In contrast, the Product Mix Shift scenario shows that switching to lower-emission products leads to continuous emissions reductions. In addition, this scenario demonstrates how altering the composition of HWPs toward products with longer lifespans can enhance carbon storage in the sector, contributing to Romania’s climate change mitigation efforts. Thus, by 2050, the emission reduction will increase to 46%, driven by the shift toward products that inherently have a smaller carbon footprint. The Moderate Growth scenario delivers the most substantial reductions, with emissions reaching −4420.81 kT CO2 by 2050, a more than 100% improvement over the BAU scenario (Table 2). This fact will offset emissions from other sectors [60]. This scenario assumes the successful implementation of policies promoting the circular economy, increased demand for sustainable materials, and sustainable forest management practices ensuring resource availability. This result highlights the importance of combining strong carbon reduction policies with significant technological advancements in energy production and industrial processes. On the other hand, the Moderate Decline scenario illustrates how initial emissions reductions can be reversed if unsustainable practices are adopted. In addition, this scenario reflects a conservative approach toward harvesting, driven by environmental concerns, stricter regulations, and a societal shift prioritizing forest conservation and biodiversity protection. Thus, the Moderate Growth projection offers the best opportunity for significant emissions reductions, while other scenarios highlight the risks of stagnation or regression if efforts are insufficient.

Limitations

The uncertainties in this study may arise from several factors. Firstly, there may be errors in the original data on the production of HWPs and in the carbon conversion factors. FAOSTAT lacks data on HWP trade (exports and imports) before 1990, so these data were assumed to be zero and the analysis of HWP exports and imports was conducted only for the period 1990–2022. Additionally, data for the period 1900–1960 on HWP production were obtained through extrapolation methods.

5. Conclusions

Harvested wood products (HWPs) can be considered an important carbon reservoir in decision-making associated with climate change mitigation and carbon monitoring.
The analysis of HWP carbon stock from 1961 to 2022, particularity for Romania, highlights a consistent increase in carbon accumulation, with total carbon stock doubling. Sawnwood showed the most significant growth, followed by wood panels, while paper products experienced declines in recent decades. Carbon inflows from domestic production exhibited variability and overall stock changes trended upward, indicating the long-term carbon storage potential of HWPs. Future projections under the business-as-usual (BAU) scenario suggest HWPs will remain a net carbon sink, with CO₂ removals reaching −2630 kT CO₂ by 2050, despite uncertainties. Due to forest carbon pools, alternative scenarios demonstrate significant potential for emissions reduction, particularly under the Moderate Growth scenario. One the other hand, maximizing the climate mitigation benefits of HWPs depends on integrating sustainable forest management practices. Specifically, maintaining balanced harvest levels, ensuring forest regeneration, and prioritizing the production of longer-lived wood products is key. To further advance the understanding of HWP carbon storage in Romania, future research should focus on improving data accuracy, examining climate change scenarios, or developing alternative forest management practices.

Author Contributions

Conceptualization, G.R.R. and C.I.B.; methodology, C.I.B. and G.R.R.; software, G.R.R., S.P. and C.I.B.; validation, G.R.R. and S.P.; formal analysis, C.I.B. and G.R.R.; investigation, G.R.R. and S.P.; resources, C.I.B. and G.R.R.; data curation, S.P. and G.R.R.; writing—original draft preparation, C.I.B.; writing—review and editing, C.I.B., G.R.R., S.P., A.B.C., T.S., A.Z. and G.I.; visualization, G.R.R., S.P. and C.I.B.; supervision, G.R.R. and S.P.; project administration, G.R.R.; funding acquisition, G.R.R. and C.I.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the European Union Horizon Europe program as part of the project “OPTimising FORest management decisions for a low-carbon, climate resilient future in Europe” (OptFor-EU), under Grant agreement no. 101060554, and partially funded by the Ministry of Water, Environment and Forests, under the Contract 798/M/20.12.2024 and HG 1415/2024.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Classification of wood products based on FAO forest product definitions.
Figure 1. Classification of wood products based on FAO forest product definitions.
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Figure 2. Carbon stored in HWPs in different categories. Left gray area shows data created with Equation (6) based on the country-specific data in 1961.
Figure 2. Carbon stored in HWPs in different categories. Left gray area shows data created with Equation (6) based on the country-specific data in 1961.
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Figure 3. Inflow from domestic production in HWPs by different categories.
Figure 3. Inflow from domestic production in HWPs by different categories.
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Figure 4. Carbon balance (emissions and removals) in HWPs by different categories.
Figure 4. Carbon balance (emissions and removals) in HWPs by different categories.
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Figure 5. Roundwood (A), sawnwood (B), and secondary processing ((C) wood-based panel; (D) paper, and paperboard) production, import, and export between 1990 to 2022.
Figure 5. Roundwood (A), sawnwood (B), and secondary processing ((C) wood-based panel; (D) paper, and paperboard) production, import, and export between 1990 to 2022.
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Figure 6. Emission trends based on historical data and projected BAU scenario through 2050, including Monte Carlo variants (blue lines).
Figure 6. Emission trends based on historical data and projected BAU scenario through 2050, including Monte Carlo variants (blue lines).
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Figure 7. Projected pathways of CO2 emissions from 2023 to 2050 across five models.
Figure 7. Projected pathways of CO2 emissions from 2023 to 2050 across five models.
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Table 1. Carbon conversion factors in HWPs used in the models.
Table 1. Carbon conversion factors in HWPs used in the models.
HWPs CategoriesC Conversion Factor
Units(per air dry volume) [MgC/m3]
Coniferous sawnwood0.225
Broadleaf sawnwood0.280
Wood-based panels0.269
Units(per air dry mass) [Mg C/Mg]
Paper and paperboard0.386
Coniferous roundwood0.225
Broadleaf roundwood0.295
Table 2. Projected reductions in CO2 emissions under different scenarios.
Table 2. Projected reductions in CO2 emissions under different scenarios.
ScenarioUnits202220232025203020402050
BAUValue (kT CO2)−2372.53−2362.74−2378.68−2434.54−2543.29−2630.01
Static AverageValue (Kt CO2)−2372.53−3003.94−2899.43−2592.16−2027.96−1584.25
Diff. %0.00+27.14+21.89+6.47−20.26−39.76
Product Mix Shift Value (Kt CO2)−2372.53−3028.35−3038.32−3080.29−3150.64−3185.87
Diff. %0.00+28.17+27.73+26.52+23.88+21.14
Moderate GrowthValue (Kt CO2)−2372.53−2722.13−2883.84−3266.81−3913.67−4420.81
Diff. %0.00+15.21+21.24+34.19+53.88+68.09
Moderate DeclineValue (Kt CO2)−2372.53−2208.63−1909.84−1265.80−223.29593.42
Diff. %0.00−6.52−19.71−48.01−91.22−122.56
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MDPI and ACS Style

Braga, C.I.; Petrea, S.; Zaharia, A.; Cucu, A.B.; Serban, T.; Ienasoiu, G.; Radu, G.R. Assessing the Greenhouse Gas Mitigation Potential of Harvested Wood Products in Romania and Their Contribution to Achieving Climate Neutrality. Sustainability 2025, 17, 640. https://doi.org/10.3390/su17020640

AMA Style

Braga CI, Petrea S, Zaharia A, Cucu AB, Serban T, Ienasoiu G, Radu GR. Assessing the Greenhouse Gas Mitigation Potential of Harvested Wood Products in Romania and Their Contribution to Achieving Climate Neutrality. Sustainability. 2025; 17(2):640. https://doi.org/10.3390/su17020640

Chicago/Turabian Style

Braga, Cosmin Ion, Stefan Petrea, Alexandru Zaharia, Alexandru Bogdan Cucu, Tibor Serban, Gruita Ienasoiu, and Gheorghe Raul Radu. 2025. "Assessing the Greenhouse Gas Mitigation Potential of Harvested Wood Products in Romania and Their Contribution to Achieving Climate Neutrality" Sustainability 17, no. 2: 640. https://doi.org/10.3390/su17020640

APA Style

Braga, C. I., Petrea, S., Zaharia, A., Cucu, A. B., Serban, T., Ienasoiu, G., & Radu, G. R. (2025). Assessing the Greenhouse Gas Mitigation Potential of Harvested Wood Products in Romania and Their Contribution to Achieving Climate Neutrality. Sustainability, 17(2), 640. https://doi.org/10.3390/su17020640

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