A Study on the Prediction of Long-Term Carbon Absorption by Applying the Renewal Scenario of Forest in Korea

Abstract

As global warming has emerged as an essential global solution, the role of carbon neutrality is required to respond to rapidly changing environmental policies. Forests are an important means for achieving carbon neutrality as they act as a key carbon sink, and, among them, forest management called afforestation is emerging as a decisive factor. However, although various studies are being conducted to enhance carbon absorption capacity, there are not many long-term research cases on afforestation. In this study, the cumulative carbon absorption for a total of 90 years from 1 January 2020 to 31 December 2100 was set as the baseline. Various changes were made according to the cyclical trend of the species and age classes planted nationwide, and various results were derived through the regeneration scenario. As a result of the study, the difference between the maximum value and the baseline CO₂ absorption was approximately 130 million t CO₂ when compared with the 90-year cumulative value. When converted into an annual unit, it increased by more than 14 million t CO₂. Based on the highest figures, compared with statistics from the Ministry of Environment’s Greenhouse Gas Information Center, it was confirmed that the forest absorption source, which was offset by 6.26 percent in 2019, could be changed by up to 8.74 percent. When analyzing the maximum figures from this study, depending on the method of afforestation, the greenhouse gases emitted by approximately 9.32 million passenger cars per year could be offset. In conclusion, among the carbon neutrality tasks that must be addressed at the national level, it is very important to establish long-term direction decisions and detailed plans for the forest sector, which is the core of carbon sinks, and a strategic approach is essential. Based on this study, it is expected that a more systematic direction can be presented for planning and implementing future afforestation.

1. Introduction

As it has become a critical environmental issue, achieving carbon neutrality at a national level is essential, globally, to adapt to changing environmental policies [1]. Over the past 30 years, the global average temperature has risen by 1.4 °C, primarily due to the excessive use of fossil fuels and industrial activities focused on manufacturing [2]. Consequently, addressing national challenges like climate change has become increasingly important [3].

Forests are key carbon sinks and play a vital role in advancing the 2050 carbon neutral strategy [4]. In South Korea, the net CO₂ absorption by domestic forests was estimated at 45.6 million tons of CO₂ (Mt CO₂) in 2018, accounting for just 6.3% of the country’s total emissions of 728 Mt CO₂ [5]. This capacity is gradually declining. South Korea’s forests were heavily impacted during the Japanese colonial era and the Korean War, leading to intensive greening projects in the 1960s and 1970s. As a result, the current forest stand age class structure is uneven, with about 72% of the area occupied by tree species aged 40 years or older, while only 6% falls within the 1-to-20-year age class. This uneven distribution poses additional challenges for forest management [6].

Long-term forecasting of carbon absorption values using forest management scenarios is crucial as forests lose absorption capacity with age [7]. Due to the age class imbalance, carbon absorption is predicted to decrease rapidly over time [8]. If this trend continues, carbon absorption could fall from over 40 million tons of CO₂ (t CO₂) in 2020 to 16 million t CO₂ by 2050. Thus, a continuous and strategic forest management paradigm is essential to restore and enhance forest carbon absorption [9].

Recent studies support the necessity for adaptive forest management strategies, emphasizing reforestation and afforestation with diverse and resilient species to enhance carbon sequestration and ecosystem services [10]. Innovative practices such as assisted migration and selective breeding of tree species to withstand climatic stresses are also important [11]. By embracing these approaches, South Korea can improve its forest carbon sink capacity, contributing more effectively to global climate stabilization efforts [12].

As shown in

Table 1. Status of afforestation and reforestation in South Korea over the past ten years.

Year	Afforestation Area (Unit: Thousand ha)	Planting Trees (Unit: Thousand ha)
2012	20	253
2013	22	371
2014	23	293
2015	23	279
2016	24	284
2017	24	306
2018	23	255
2019	23	211
2020	23	228
2021	20	209
Total	225	2689

, over the past 10 years, afforestation has been carried out on more than 20,000 hectares annually, with over 225,000 hectares afforested during this period. As a result, more than 3.58% of the forested area (approximately 6,286,000 hectares) has been planted, and the actual tree species area covers more than 3.78% of the distribution area (approximately 5,949,000 hectares). The afforestation process over 90 years could account for 32.21% of the nation’s forest area and 34.03% of the tree species distribution area, which is relatively high compared to previous figures [13].

However, the rate of afforestation is relatively low through the forest silvicultural system. Afforestation is classified into new afforestation, involving planting trees in non-forest areas, and reforestation, which involves planting in previously forested areas that have been destroyed. A few new reforestation targets have been successfully completed in South Korea [14].

Customized afforestation projects tailored to the characteristics of each region and mountain owners are continuously promoted. However, despite the success of these projects and forest silviculture, issues like decreasing carbon absorption due to age class imbalance in forests remain unsolved.

Woś et al. [15] conducted a study measuring CO₂ absorption by the same tree species under different conditions in a forest area. Numerous studies have similarly focused on deciduous Scots pine (Pinus sylvestris L.) and common birch (Betula pendula Roth). As tree roots and leaves are influenced by environmental conditions and the climate, CO₂ absorption varies even within the same species [16]. This indicates the necessity for further research to provide valuable insights for future afforestation or regeneration scenarios [17]. Moreover, planting density plays a crucial role in ecosystem and forest resilience [18]. Thus, evaluating forest scenarios through diverse decision-making processes is vital [19]. Beyond afforestation, forests are increasingly important for functions such as wood production, biodiversity, and recreation [20]. As different management strategies are employed to tackle these challenges, evaluating various scenarios becomes essential [21]. Many studies on climate and forest development scenarios have been conducted across Europe. FORMIT-M, an open-access forest management simulator for Europe, integrates process-driven and data-driven components using forest inventory data and climate scenarios. The study by Teicha et al. [22] found that forest management impacts carbon stocks and yield potential more significantly than climate change.

Addressing carbon neutrality, a recent South Korean study analyzed CO₂ absorption differences among different age groups of pine and oak trees in the same area under identical conditions [23]. The findings suggested that CO₂ intake increases as forests age, highlighting the need to balance age group distributions to support a circular economy [24]. However, simply adjusting age groups cannot resolve issues such as reliance on overseas afforestation or establishing a domestic wood distribution system [25]. A study on carbon absorption in public green areas across five cities found that forest management, growth environment, and tree density significantly affect carbon absorption sources [26].

South Korea has conducted numerous studies to optimize forest management while promoting economic (wood production) and public interest (watershed conservation) functions alongside environmental benefits (carbon absorption). Key variables include age and type ratios in forest sectors, area ratios of coniferous and broadleaf trees, and wood production and sales data, serving as foundational data for forest planning. Solutions emerge by considering multiple conflicting factors through planning methods like multi-objective linear programming (MOLP), which calculates optimal plan target values using various forest elements [27]. Essential groundwork for forest management supporting a circular economy requires further regional-level research beyond traditional forest management [28]. Additionally, convergence-type studies on groundwater resources, soil, and multipurpose dams in South Korea are on the rise, emphasizing the importance of collaborative efforts among countries, governments, and individuals to find alternatives, select evaluations, and solve problems [29].

The present study conducts a comprehensive, long-term carbon prediction due to the lack of significant improvements in national or long-term carbon absorption. It analyzes renewable scenarios and adjusted imbalance structures (focused on age classes 3–4 and higher) to address carbon absorption limitations. The study’s results are expected to guide strategic and efficient forest management through systematic planning, underscoring its importance in shaping sustainable forestry practices amidst global environmental challenges.

2. Data and Methods

2.1. Study Area

According to the 2020 survey, South Korea has 6,298,134 hectares of forest area and 5,949,864 hectares of actual tree species distribution area. The goals for forest management in South Korea, including afforestation, are established by considering the location and characteristics of tree species at the national and forest physiognomy levels (coniferous, broadleaf, or mixed forest). Systematic afforestation is the most important factor for efficient forest management. Therefore, a preliminary survey was conducted to determine the distribution of the types and levels of forests across the country, which could be applied to forest redevelopment scenarios. Figure 1 shows the nationwide distribution of coniferous and broad-leaved trees in 2020.

Coniferous forests occupy 2,295,022 hectares of the country’s total area, encompassing more than 12 species, including Pinus densiflora, P. koraiensis, Larix kaempferi, P. rigida, and Chamaecyparis obtusa. Broad-leaved forests, which comprise more than 29 species such as Quercus acutissima, Q. mongolica, Q. variabilis, Alnus japonica, and Acer pictum Thunb, cover 2,941,427 hectares, occupying more area than the coniferous forests. Mixed forests occupy 713,415 hectares, showing a relatively lower distribution compared to coniferous and broad-leaved forests.

In summary, at least 41 species are distributed nationwide, covering an area of 5,949,864 hectares with age classes ranging from 1 to 9 or higher. In South Korea, seven representative species are planted and managed according to the climate and terrain. These include five species of broadleaf trees, two species of coniferous trees, as well as mixed forests. These were selected as the research subjects (Figure 2). Accordingly, seven representative tree species from age classes 1 to 9 or higher were planted and classified into different age classes from 1 to 6, as shown in

Table 2. Selection of representative afforestation trees and their classification by age classes (unit: h). (Source: National Institute of Forest Science, 2019).

Type of Tree		1	2	3	4	5	6	Total
Coniferous Species	Pinus densiflora	38,785	8925	114,057	618,950	473,289	78,308	1,332,313
	P. koraiensis	19,413	18,778	43,871	61,627	11,186	1655	156,530
	Larix kaempferi	7686	9581	44,372	161,752	34,992	1640	260,022
	P. rigida	1935	4342	38,003	158,094	36,105	663	239,142
	Chamaecyparis obtusa	19,160	10,952	12,802	8764	455	160	52,293
	Other coniferous trees	9102	9390	40,378	139,166	50,984	5701	254,721
Broadleaf Species	Quercus acutissima	18,163	6616	17,200	51,730	10,800	690	105,199
	Q. mongolica	130	2596	26,259	101,274	108,437	25,383	264,078
	Other broadleaf trees	85,849	91,256	402,341	1,272,744	570,973	148,988	2,572,151
Mixed forest (additional explanation)		12,205	6911	83,079	425,983	163,632	21,604	713,414
Total		212,427	169,347	822,362	3,000,083	1,460,853	284,791	5,949,864

. The age classes, categorized based on the age of the tree, are as follows: age class 1, 0–10 years old; age class 2, 11–20 years old; age class 3, 21–30 years old; age class 4, 31–40 years old; age class 5, 41–50 years old; and age class 6, over 51 years old.

Here, the Korean forest statistics are distinguished by the following classification criteria that are different from those used in other developed countries in the definition of mixed forests. The classification criteria for mixed forests are defined as stands where the basal area ratio of conifers and broad-leaved trees exceeds 25% and is less than 75%, respectively.

2.2. Selection of Representative Afforestation Species

Apart from the representative tree species shown in Figure 2, other species of coniferous, broadleaf, and mixed forest trees were also included for afforestation. In this study, more than 42 species, including 12 coniferous, 29 broadleaf, and mixed forest tree species were identified as standard carbon absorption sources through preliminary surveys, and 10 tree species including P. densiflora, P. koraiensis, L. kaempferi, P. rigida, C. obtusa, Q. acutissima, and Q. mongolica were chosen as subjects in the present study.

2.3. Standard Carbon Absorption by Major Forest Species

Table 3. Annual CO₂ absorption by major tree species (unit: t CO₂ ha⁻¹/yr). (Source: National Institute of Forest Science, 2019) [30].

Sortation	Trees Type/the Age of Trees	10	20	30	40	50	60
Coniferous trees	Pinus densiflora (average)	5.5	8.5	11	7.3	5	3.6
	P. koraiensis	5.4	11.8	10.8	9.1	7.6	6.5
	Larix kaempferi	9.1	10.5	9.5	8.5	7.9	7.5
	P. rigida	4.5	13.9	12.4	8.7	5.8	4.1
	Chamaecyparis obtusa	5.2	8.8	8.2	6.6	5.2	4.1
Coniferous trees (average)		5.94	10.70	10.38	8.04	6.30	5.16
Broadleaf trees	Quercus acutissima	11.2	15.9	14	12.3	10.9	9.8
	Q. mongolica	8.6	15.0	9.3	8.4	7.5	6.8
Broad-leaved trees (average)		9.9	15.45	11.65	10.35	9.2	8.3
Mixed forest (coniferous trees, broad-leaved trees average)		7.92	13.08	11.02	9.20	7.75	6.73

lists the annual standard CO₂ absorption values (t CO₂ ha⁻¹/year) for each major tree species as reported by the National Institute of Forest Science. The table clearly shows that trees between 20 and 40 years of age are the highest sources of CO₂ absorption annually. Additionally, as the age class increases, the annual CO₂ absorption decreases. Currently, the average age of domestic forests is approximately 30–40 years, during which they actively absorb CO₂. However, as they continue to age, their growth rate will slow down, eventually reducing their carbon absorption capability.

The standard carbon absorption for the aforementioned major tree species was calculated according to the carbon storage method outlined in the IPCC guidelines (IPCC, 2006) [31]. This calculation involved multiplying the average growth rate of each species occupying the forests in 2009 by factors such as basic wood density, biomass expansion coefficient, root content ratio, and carbon emission coefficient [32] (1).

Forests are classified as land use, land use change, and forestry under the United Nations Framework Convention on Climate Change (UNFCCC, 2009), and they are recognized as important carbon storage systems [33]. To assess the efficacy of forests in reducing greenhouse gases, it is essential to calculate and report their carbon storage according to IPCC guidelines. These guidelines suggest a methodology for calculating forest carbon storage by multiplying forest tree accumulation (activity data) by the corresponding emission coefficients [34]. In this study, carbon emission factors were classified based on wood density, biomass expansion, root content ratio, and carbon conversion efficiency. The reliability of carbon storage estimates can be enhanced by developing a unique carbon emission coefficient and applying it nationwide (IPCC, 2006) [35].

Research on carbon emission coefficients for domestic forests has been conducted on 22 species since the early 2000s at the National Forest Research Institute of South Korea. Considering the changes in forest vegetation zones due to global warming, a unique national carbon emission coefficient for two forest physiognomy level trials involving 20 species was registered in 2018 [36]. As a result, a system was established to calculate the carbon storage of major tree types in forests (Greenhouse Gas Information Center, 2018). The standard carbon absorption rates for major forest species were publicly announced on 14 November 2012, by the South Korea Forest Service and the National Forest Research Institute (Version 1.0), with updates for additional species released in 2013 (Version 1.1). These data, which confirm the greenhouse gas reduction effects of forests, are also utilized to assess energy substitution impacts. As trees grow, forests absorb and store greenhouse gases captured from the atmosphere. For instance, a 30-year-old oak tree in South Korea absorbs approximately 14.0 t CO₂ per hectare annually, the highest absorption rate per unit area among the eight major species mentioned earlier in South Korea.

$${\mathrm{C}\mathrm{O}}_2 \mathrm{r}\mathrm{e}\mathrm{m}\mathrm{o}\mathrm{v}\mathrm{a}\mathrm{l}\mathrm{s}=\mathrm{V}\mathrm{o}\mathrm{l}\times \mathrm{W}\mathrm{D}\times \mathrm{B}\mathrm{E}\mathrm{F}\times (1+\mathrm{R})\times \mathrm{C}\mathrm{F}\times {\displaystyle \frac{44}{12}}$$

(1)

The expression is CO₂ removal: carbon absorption by a species (t CO₂ ha⁻¹/yr).

Vol: regular average growth of the species (m³/ha).

WD: wood basic density (td.m/m³).

BEF: biomass expansion coefficient.

R: root content ratio.

CF: carbon conversion factor.

44/12: carbon–carbon dioxide fraction.

2.4. Calculation of Forest Afforestation Modification

The regeneration scenarios of domestic forests were calculated using the formula mentioned in (2). To analyze various ways for increasing carbon absorption, this research was formulated to make long-term predictions by calculating the combined figures for 90 years, from 2020 to 2100.

$$S=\sum _{y=2020}^Y\left[\sum _{a=1}^6\left(Dta\times Cta\right)\right]$$

(2)

S = total carbon absorption combined (2020–2100).

y = 2020 [Y = 2100 (90 years in total)].

a = the age of a tree (1–6 age classes of a tree).

D = the age-specific area of a tree.

C = CO₂ absorption coefficient (data from the development of a carbon absorption model of the National Institute of Forest Science (by species)).

t = a representative tree species (10 tree species in total).

The average of Pinus densiflora, P. koraiensis, Larix kaempferi, P. rigida, Chamaecyparis obtusa, other coniferous trees, Q. acutissima, Q. mongolica, broadleaf trees, and mixed forest trees (10 tree species in total).

※ The tree species are marked by their scientific name

Additionally, all tree species have been planted in domestic forests; however, forest protection areas could not be afforested. The total forest area of 450,186 hectares includes the disaster prevention zone of 3063 hectares, the livelihood environment zone of 13 hectares, the landscape zone of 16,556 hectares, and the watershed conservation zone of 257,957 hectares (with the 1st class watershed conservation zone at 87,547 hectares, the 2nd class at 10,678 hectares, and the 3rd class at 159,732 hectares). The status of the forest reserve designations is shown in

Table 4. Status of forest reserve designation (unit: ha).

Year	Disaster Prevention	Livelihood Environment	Landscape	Watershed Conservation				Forest Genetic Resources	Total
				1st Class Watershed Conservation	2nd Class Watershed Conservation	3rd Class Watershed Conservation	Sum
2016	4787	11	19,116	98,841	11,890	157,561	268,292	152,366	444,572
2017	4890	11	17,365	98,040	10,724	151,549	260,313	152,428	435,007
2018	4977	11	16,289	94,210	8947	150,865	254,022	171,332	446,631
2019	4276	13	16,162	90,443	8878	155,813	255,134	172,049	447,634
2020	3063	13	16,566	87,547	10,678	159,732	257,957	172,587	450,186

. Forest reserves were excluded from this study.

2.5. Setting up Forest Regeneration Scenarios

It is beyond the scope of the existing forest resource development policy to establish social and economic added value through the production and utilization of forest resources [37]. Therefore, a forest resource circulation system strives to actively use forest resources beyond current policies and focuses on preservation [38]. The core of the forest resource circulation system is the production and use of wood for resource circulation. Inefficiencies in the wood resource sector continue to be problematic; for instance, trees planted in the past have matured and approached the wood production period but are not being properly utilized, and abundant wood resources are not linked to forestry income. The main policies of the forest circulation system include approaches to induce the sustainable recycling of resources through logging, reforestation, and domestic wood consumption. Several guidelines aim to improve the economy of South Korea [39]. Forests act as carbon circulation systems that encompass afforestation, forest cultivation, logging, and wood utilization, while forest management promotes the nation’s growth [40]. A circulation system to achieve this can only be established when trees are properly cut down, high-quality seeds are planted, and the trees are well cared for and eventually reharvested, resulting in healthy forests with increased biodiversity and soil fertility. Only the establishment of such economically viable forests will increase water source absorption and stabilize the supply and demand for domestic wood. Therefore, three scenarios were applied in the present study by reducing forest regeneration periods by 10 years for durations of 60, 50, and 40 years (Figure 3).

3. Results and Discussion

The results of this study were calculated by dividing the change rate between the standard of each tree species and the total standard of the corresponding grade by 5%, 10%, 15%, and 20%. The total value of carbon absorption from the 60-year regeneration was used as the baseline for comparison.

The top five tree species targeted for changes in afforestation area were selected based on their occupied area in 2020. They were ranked in the following decreasing order: other broadleaf trees (43.23% of the total area), Pines densiflora (22.39% of the total area), mixed forest trees (11.99% of the total area), Quercus Mongolica (4.43% of the total area), and Larix Kamepferi (4.37% of the total area). Accordingly, the overall absorption value was calculated and analyzed by altering the afforestation area in the order of their occupied areas, as shown in Figure 4a. In addition to the representative tree species, further studies were conducted on P. densiflora, which occupies the largest area as a single tree species (Figure 4b).

The research framework was designed to change the target tree species area ratio and the total age class area ratio. The regeneration scenarios were defined as 60, 50, and 40 years. Forest management is gradually aligning policies and plans to create economic forests. The tree species were organized in this circular management method to achieve a virtuous cycle system that allows for rapid harvesting and replanting [41].

Before changing the tree type, the regeneration scenario was set to reduce the age classes. To transition to a circular economy in forestry, various policies are being planned based on research and the latest trends in forest management [42]. Beyond merely preserving forests, a future-oriented concept, tailored to the latest trends for healthier forests, can only be achieved when a circular system structure is adopted.

All calculations for regeneration scenarios by age classes were performed in the same manner. The regeneration scenario was set to 60 years, based on a total of 90 years (from 1 January 2020 to 31 December 2100). Subsequently, the regeneration scenarios for 50 and 40 years were calculated sequentially, as shown in

Table 5. Comparison of the regeneration scenarios results (60, 50, and 40 years).

(1) 60-Year Regeneration Scenario
(Unit: t CO2 ha−1/yr)
2020	2030	2040	2050	2060	Ratio
53,429,019	46,821,271	45,586,809	54,779,621	67,577,672	100.000
2070	2080	2090	2100	Total
62,756,807	53,429,019	46,821,271	45,586,809	428,788,298
(2) 50-yearregenerationscenario
(Unit:t CO2 ha−1/yr)
2020	2030	2040	2050	2060	Ratio
53,429,019	49,137,490	56,814,606	68,624,333	63,402,056	110.009
2070	2080	2090	2100	Total
53,723,574	49,137,490	56,814,606	68,623,433	471,706,607
(3) 40-yearregenerationscenario
(Unit:t CO2 ha−1/yr)
2020	2030	2040	2050	2060	Ratio
53,429,019	50,340,123	71,902,966	67,497,258	56,471,753	116.107
2070	2080	2090	2100	Total
50,340,123	71,902,966	67,497,258	56,471,753	497,853,219

. The results illustrate the total carbon absorption sources from 2020 to 2100 by converting the relevant age classes and carbon absorption sources into annual units.

When the regeneration scenario was confirmed after shortening the age classes without changing the tree type, the total CO₂ absorption for 60, 50, and 40 years was 428,788,298, 471,706,607, and 497,853,219 tons, respectively. Additionally, the ratios of the regeneration scenarios for 60, 50, and 40 years were 100.000, 110.009, and 116.107, respectively. When these figures were converted into annual absorption, the average values obtained for 60, 50, and 40 years of regeneration were approximately 4,764,314, 5,241,185, and 5,531,702 tons of CO₂, respectively.

The absorption value (129.551) calculated based on the baseline data was observed when more than 20% of the P. densiflora per unit area was replaced by Q. acutissima. The second highest carbon absorption value (125.785) was noted when more than 15% of the P. densiflora per unit area was replaced by Q. acutissima. The third highest carbon absorption value (125.301) was recorded when more than 20% of the P. densiflora per unit area was replaced by other broadleaf trees. The fourth highest carbon absorption value (123.090) was observed when 20% or more of the P. densiflora per unit area was replaced by an equal ratio of other broadleaf trees and mixed forest trees (in a 1:1 ratio). The fifth highest carbon absorption value (122.914) was noted when 20% or more of the P. densiflora per unit area was replaced by all other tree species. The results are summarized in

Table 6. High ranking of carbon uptake by a ratio.

Change Rate	Tree Species Change Rate	Regeneration Scenarios	Carbon Absorption Result Value
5%	[1st] Pinus densiflora → Quercus acutissima [2nd] P. densiflora → Other broadleaf trees [3rd] P. densiflora → Other broadleaf trees, mixed forest (each 50%) [4th] P. densiflora → All the other trees [5th] All the other trees → Other broadleaf trees	40 years (total)	118.367 117.189 116.637 116.593 116.377
10%	[1st] P. densiflora → Q. acutissima [2nd] P. densiflora → Other broadleaf trees [3rd] P. densiflora → All the other trees [4th] P. densiflora → Other broadleaf trees, mixed forest (each 50%) [5th] All the other trees → Other broadleaf trees	40 years (total)	122.018 119.893 119.009 118.788 118.268
15%	[1st] P. densiflora → Q. acutissima [2nd] P. densiflora → Other broadleaf trees [3rd] P. densiflora → All the other trees [4th] P. densiflora → Other broadleaf trees, mixed forest (each 50%) [5th] All the other trees → Other broadleaf trees	40 years (total)	125.785 122.597 120.939 120.807 120.159
20%	[1st] P. densiflora → Q. acutissima [2nd] P. densiflora → Other broadleaf trees [3rd] P. densiflora → Other broadleaf trees, mixed forest (each 50%) [4th] P. densiflora → All the other trees [5th] All the other trees → Other broadleaf trees	40 years (total)	129.551 125.301 123.090 122.914 122.050
Overall Ranking	[1st] P. densiflora → Q. acutissima (20%) [2nd] P. densiflora → Q. acutissima (15%) [3rd] P. densiflora → Other broadleaf trees (20%) [4th] P. densiflora → Other broadleaf trees, mixed forest (each 50%) (20%) [5th] P. densiflora → All the other trees (20%)	40 years (total)	129.551 125.785 125.301 123.090 122.914

.

The absorption value (93.538) calculated based on the baseline data was observed when 20% of the other broadleaf trees were replaced by P. densiflora. The second lowest carbon absorption value (94.857) was noted when 20% of the area occupied by all other trees was replaced by P. densiflora. The third lowest carbon absorption value (95.158) was recorded when 15% of the area occupied by other broadleaf trees was replaced by P. densiflora. The fourth lowest carbon absorption value (95.528) was observed when 20% or more of the area occupied by other broadleaf trees was replaced by all the other trees. The fifth lowest carbon absorption value (95.933) was noted when 20% or more of the Q. mongolica area was replaced by P. densiflora. The results are summarized in

Table 7. Low ranking of carbon uptake by ratio.

Change Rate	Tree Species Change Rate	Regeneration Scenarios	Carbon Absorption Result Value
5%	[1st] Other broadleaf trees → Pinus densiflora [2nd] All the other trees → P. densiflora [3rd] Q. acutissima → P. densiflora [4th] Mixed forest → P. densiflora [5th] All the other trees → Other broadleaf trees	60 years (total)	98.386 98.714 98.983 99.016 99.028
10%	[1st] Other broadleaf trees → P. densiflora [2nd] All the other trees → P. densiflora [3rd] Other broadleaf trees → All the other tree [4th] Q. mongolica → P. densiflora [5th] Mixed forest → P. densiflora	60 years (total)	96.772 97.428 97.764 97.967 98.033
15%	[1st] Other broadleaf trees → P. densiflora [2nd] All the other trees → P. densiflora [3rd] Other broadleaf trees → All the other trees [4th] Q. mongolica → P. densiflora [5th] Mixed forest → P. densiflora	60 years (total)	95.158 96.143 96.646 96.950 97.049
20%	[1st] Other broadleaf trees → P. densiflora [2nd] All the other trees → P. densiflora [3rd] Other broadleaf trees → All the other trees [4th] Q. mongolica → P. densiflora [5th] Mixed forest → P. densiflora	60 years (total)	93.538 94.857 95.528 95.933 96.065
Overall Ranking	[1st] Other broadleaf trees → P. densiflora (20%) [2nd] All the other trees → P. densiflora (20%) [3rd] Other broadleaf trees → P. densiflora (15%) [4th] Other broadleaf trees → All the other trees (20%) [5th] Q. mongolica → P. densiflora (20%)	60 years (total)	93.538 94.857 95.158 95.528 95.933

.

The graphical representation of the highest (decreasing order) and lowest (increasing order) ratios of total carbon absorption rates are shown in Figure 5.

As shown in Figure 6, the cumulative CO₂ absorption value of 440,695,424 t CO₂ ha⁻¹ was observed when the current area-wise distribution of tree species and regeneration was maintained as the baseline. The maximum absorption value of 570,924,690 t CO₂ ha⁻¹ was recorded when the area occupied by P. densiflora was replaced with the area occupied by Q. acutissima, assuming a total regeneration time frame of 40 years. Conversely, the minimum absorption value of 412,218,889 t CO₂ ha⁻¹ was noted when the area of other broadleaf trees was converted to the total area of pine trees for a duration of 60 years.

The difference between the baseline and maximum CO₂ absorption was approximately 130,229,266 t CO₂ ha⁻¹, which translates to an estimated annual increase of about 14,469,918 t CO₂ ha⁻¹. In contrast, the difference between the baseline and minimum CO₂ absorption was approximately 28,476,525 t CO₂ ha⁻¹, with an estimated annual decrease of around 3,164,058 t CO₂ ha⁻¹. The comparison between maximum and minimum CO₂ absorption indicated a value of about 158,705,791 t CO₂ ha⁻¹, reflecting an annual difference of approximately 17,996,977 t CO₂ ha⁻¹.

These findings underscore the significant impact that strategic tree species selection and management practices can have on enhancing carbon absorption in forest ecosystems. The ability to achieve higher CO₂ absorption rates through the careful planning and implementation of regeneration strategies highlights the importance of adaptive management in the context of climate change. Effective regeneration not only enhances the carbon sink capacity of forests, but also contributes to overall ecosystem health and resilience. As such, future research should focus on exploring the interactions between various tree species and their ecological roles, enabling more informed decision-making for sustainable forest management.

Our research results were compared and analyzed alongside those reported by the Ministry of Environment in the National Greenhouse Gas Statistics (inventory report). According to the 2018 inventory report, carbon absorption by forests was approximately 45.6 million tons, which constitutes 6.3% of the country’s annual greenhouse gas emissions of CO₂ (727.6 million tons) and nearly half the CO₂ emissions generated by the transport sector (98.1 million tons).

A numerical comparison was performed based on the CO₂ absorbed by forests, estimated at about 45.6 million t CO₂ (

Table 8. Comparison with the national inventory and figures.

Sortation				Amount of Carbon
Total national greenhouse gas emissions in 2018				(a) 727,600,000
Greenhouse gas absorption of the forests in 2018				(b) 45,600,000
[Case 1] Maximum–minimum difference				(c) 17,996,977
[Case 2] Maximum–baseline difference				(d) 14,469,918
[Case 3] Baseline–minimum difference				(e) −3,164,058
Forest section in 2018 (b) + [Case 1] (c)				(f) 63,596,977
Forest section in 2018 (b) + [Case 2] (d)				(g) 60,069,918
Forest section in 2018 (b) + [Case 3] (e)				(h) 42,435,942
Percentage ratio (%)	6.26	8.74	8.25	5.83
	(b)/(a)	(f)/(a)	(g)/(a)	(h)/(a)

). By considering the difference between the highest and lowest amounts of carbon absorption (17,996,977 t CO₂), the total carbon absorbed by forests was determined to be 63,596,977 t CO₂, representing an increase of approximately 6.03% to 8.74%. Furthermore, based on the difference between the baseline and maximum absorption (14,469,918 t CO₂), the total carbon absorbed by forests increased by around 8.25%. Meanwhile, the difference between the baseline and minimum absorption (−3,164,058 t CO₂) indicated a reduction in the total carbon absorption by approximately 5.83%.

These findings highlight the crucial role that forests play in carbon sequestration and their potential to mitigate greenhouse gas emissions. The ability of forests to absorb significant amounts of CO₂ underscores the importance of effective forest management and restoration practices. Enhancing the carbon absorption capacity through strategic planning, including the selection of appropriate tree species and the implementation of sustainable practices, is paramount for achieving climate goals. Moreover, the contrasting absorption values illustrate the impact of management choices on forest carbon dynamics. Future research should focus on evaluating the long-term effects of different forest management strategies on carbon absorption, as well as the socio-economic benefits of maintaining robust forest ecosystems. By doing so, stakeholders can develop more informed policies that not only aim for greater carbon neutrality, but also promote biodiversity, enhance ecosystem services, and support community livelihoods. Ultimately, integrating ecological understanding with economic incentives will be key to fostering resilient forest landscapes capable of meeting both environmental and societal needs.

In this study, the results were converted into annual units. The difference between the baseline and the maximum absorption source mentioned above was 14,469,918 t CO₂, which is 29.55% higher than the average value of the baseline. Conversely, the difference between the baseline and the minimum absorption source was 3,164,058 t CO₂, reflecting a decrease of 6.46% compared to the baseline. The gap between the maximum and minimum absorption sources stood at 17,633,977 t CO₂, representing a significant difference of 36.01% relative to the baseline. As shown in

Table 9. Comparison of the study results (baseline, maximum, minimum) (unit: t CO₂).

Sortation	Total (1 January 2020–31 December 2100)	Overall Rate After Exclusion of Forest Reserve (92.43%)	Annual Unit	Ratio
Baseline (a)	476,788,298	440,695,424	48,966,158	100.000
1st high ranking (b)	617,683,317	570,924,690	45,802,100	129.551
1st low ranking (c)	445,979,551	412,218,899	63,436,077	93.538
Sortation		Overall Rate After Exclusion of Forest Reserve Difference	Annual Unit Difference	Ratio Difference
1st high ranking (b)–baseline (a)		130,229,266	14,469,918	29,55%
Baseline (a)–1st low ranking (c)		28,476,525	3,164,058	6.46%
1st high ranking (b)–1st low ranking (c)		158,705,791	17,633,977	36.01%

, there was a variation of up to 36% or more depending on the afforestation method employed.

Based on these results, we compared and analyzed them from two perspectives. First, when compared with the statistical data of the Ministry of Environment’s Greenhouse Gas Information Center, it was confirmed that the forestry sector sink, which had been offset by more than 6.26% as of 2019, could be changed by up to 8.74%. Second, when analyzed within the scope of this study, it was confirmed that the comparison value between the maximum and minimum sinks could increase by up to 36% depending on the forest management method. In addition, among the research data mentioned in the text, there was a result according to which pine trees absorb 11.0 tons of CO₂ per ha per year, and the sink offsets the greenhouse gases emitted by 5.7 passenger cars per year. When the maximum comparison value of 17,996,977 t CO₂ of carbon sinks was combined with the greenhouse gas offset effect of passenger cars, the conclusion was that it offsets the greenhouse gases emitted by approximately 9.32 million passenger cars per year. This is a figure that can offset more than 37.43% based on the 24.91 million domestically registered automobiles as of the end of 2021 announced by the Ministry of Land, Infrastructure and Transport. It is judged that it will be difficult to achieve the carbon sink target unless various interpretations and models for long-term renewal scenarios such as this study are developed in the forestry sector in the future. The major issues that have been recently debated in forest management are the extension of age ranges and the preservation and maintenance of forests from logging or deforestation, but this is far from the actual development and cultivation of forest resources. It is realistically impossible to increase carbon sinks with only small-scale forest management activities such as thinning and mowing. In order to continuously strengthen and increase carbon absorption capacity, forest circulation management should be strengthened based on expanded afforestation projects and planted tree species. By planting, cultivating, and harvesting tree species sustainably and utilizing them, added value such as the environment (carbon sink) and the economy (stable wood production) should be stably created. To do so, it is necessary to implement a more strategic approach, such as long-term afforestation, age reduction, and systematic logging systems in line with the circular economy. The important implication of this study is to maximize the utilization value of forest resources focusing on carbon sinks more efficiently.

These findings emphasize the considerable impact of various afforestation strategies on carbon absorption rates. The substantial increase in CO₂ absorption associated with the maximum scenario suggests that strategic tree selection and management practices can play a vital role in enhancing carbon sequestration. This aligns with current research suggesting that targeted afforestation efforts, when properly executed, can lead to significantly higher carbon storage in forest ecosystems.

On the other hand, the decline observed in the minimum absorption scenario highlights potential risks associated with less effective management practices or inappropriate species selection. It serves as a reminder of the necessity for evidence-based planning in afforestation projects to ensure that ecological integrity and carbon absorption potential are maximized. Furthermore, the variation in absorption levels underscores the interconnectedness between forest management practices and broader climate change mitigation efforts. Policymakers and forestry managers should take these findings into account when developing guidelines and targets for afforestation projects. Aligning afforestation strategies with the principles of sustainable forest management could contribute not only to carbon neutrality goals, but also to biodiversity conservation and ecosystem stability. Ultimately, this study provides valuable insights that can help shape future forestry practices and climate strategies, aiming for long-term ecological and economic sustainability.

4. Conclusions

This study approached the optimization of forest management based on tree species and age classes, examining long-term changes in carbon intake through various regeneration scenarios. It focused on all tree species distributed nationwide in 2020, selecting representative species for future planting. Regeneration scenarios were established at 60, 50, and 40 years, with a change rate set to 20%, gradually adjusted by 5%.

From 2020 to 2100, the cumulative carbon absorption was set as the baseline, with the highest absorption recorded at 570,924,690 CO₂ over 90 years when the P. densiflora area was changed to the Q. acutissima area under the 40-year scenario. The lowest absorption occurred when broadleaf areas were converted to P. densiflora. A significant difference in CO₂ absorption between the baseline and maximum absorption was noted, indicating potential gains from improved forest management.

A comparative analysis confirmed that absorption rates in the forest sector could increase from 6.26% to 8.74%, and that the difference between maximum and minimum absorption could reach 36%, emphasizing the importance of tailored management strategies. Enhancing carbon absorption in domestic forests is crucial for achieving carbon neutrality; however, issues remain regarding age class imbalance and reliance on overseas afforestation, necessitating dedicated research into forest management techniques.

While this study provides valuable insights, it has limitations. The analysis primarily focused on specific tree species and did not consider the potential impacts of emerging climate change scenarios, pest invasions, or disease outbreaks that could affect forest health and carbon uptake. There is a limitation in not being able to reflect the dynamic stand growth changes under climate change scenarios (such as RCP, SSP, etc.) considering factors like temperature and precipitation.

Additionally, the generalizability of the findings may be limited to South Korea, and insights may differ in other regions with varying ecological conditions. To maximize efficiency in afforestation efforts, integrating forestry mechanization and improving infrastructure is essential. To successfully execute the afforestation after harvesting timber without delays, a systematic seedling system should be in place. Additionally, efforts should be made to maximize carbon storage and the substitution effect of carbon-intensive materials by prioritizing the use of timber produced for long-life-span, high-value purposes such as wooden construction and furniture. A long-term perspective on management planning, with specific mid- to short-term goals, is needed to align with carbon neutrality objectives. Efforts should be accompanied by prioritizing the use of wood produced through species renewal for long-life, high-value-added applications such as timber construction and wooden furniture, in order to maximize carbon storage and the effect of substituting carbon-intensive materials.

Ultimately, addressing carbon neutral tasks requires a strategic and collaborative approach at the national level, focusing on clarifying the long-term management directions of forests. A systematic framework for future afforestation planning and implementation should be prioritized to effectively tackle these challenges. This study is expected to be used as basic data for establishing detailed implementation plans for the forestry sector based on scientific evidence to carry out carbon neutrality policies. In the future, we aim to develop an integrated forecasting model that incorporates forest dynamic growth models, forest disasters such as wildfires, and trends in wood utilization in order to predict more accurately the changes in forest carbon absorption.