• Journal of Climate Change Research
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• v.6 no.4
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• pp.303-310
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• 2015

This study was conducted to estimate of carbon stock and greenhouse gas (GHGs) removals by tree species and forest type at Gangwon province. We used a point sampling data with permanent sample plots in national forest inventory and national emission factors. GHGs emissions was caclulated using the stock change method related to K-MRV and IPCC guidance. Total carbon stock and greenhouse gas removals were high in deciduous forest and species than in coniferous. The range of annual net greenhouse gas emissions in other deciduous species was from $-11,564.83Gg\;CO_2\;yr^{-1}$ to $-13,500.60Gg\;CO_2\;yr^{-1}$ during 3 years (2011~2013). On the other hand, coniferous forest was temporally converted to source due to reducing of growing stock in 2012. It was that growing stocks and forest area were likely to reduce by the deforestation and clear cutting. This study did not consider other carbon pools (soil and dead organic matter) due to the lack of data. This study needs to complement the activity data and emission factors, and then will find the way to calculate the greenhouse gas emissions and removals in the near future.

• Journal of Korean Society of Forest Science
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• v.95 no.4
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• pp.405-414
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• 2006

Korea is expected to be included in the countries of compulsory reduction of greenhouse gas emissions from the 2nd commitment period (2013~2017). For the negotiations in the future, this study was designed to review the tendency of discussions about carbon account in harvested wood products (HWP), which is currently underway around the globe and approach-specific characteristics, and analyze effects on carbon emissions in our country. As a result, most importantly, except the current IPC default approach there is no big difference among the 3 approaches of carbon account in HWP, which were newly suggested on the basis importers because all the HWP circulated at home are accounted for by carbon-stock changes. Under production approach, those HWP produced at home only are evaluated according to carbon-stock changes with the exception of imported HWP. Atmospheric-flow approach is favorable to net wood exporters, because the spot where ultimate decomposition and combustion arising out of the use of HWP occur is regarded as the place of carbon emission. Meanwhile, the estimation of korean carbon-stock change in HWP showed that as of 2004, stock-change approach was 1.567 Tg C, with production approach being 0.581 Tg C and atmospheric-flow approach being -1.425 Tg C, which means stock-change approach is most favorable to Korea as a net wood importer, while atmospheric-flow approach is the least favorable one, in terms of carbon emissions reduction in Korea.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.39-48
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• 2011

Global warming causes the climate change and makes severe damage to ecosystem and civilization Carbon dioxide greatly contributes to global warming, thus many studies have been conducted to estimate the forest biomass carbon stock as an important carbon storage. However, more studies are required for the selection and use of technique and remotely sensed data suitable for the carbon stock estimation in Korea In this study, the aboveground forest biomass carbon stocks of Danyang-Gun in South Korea was estimated using $k$NN($k$-Nearest Neighbor) algorithm and regression model, then the results were compared. The Landsat TM and 5th NFI(National Forest Inventory) data were prepared, and ratio images, which are effective in topographic effect correction and distinction of forest biomass, were also used. Consequently, it was found that $k$NN algorithm was better than regression model to estimate the forest carbon stocks in Danyang-Gun, and there was no significant improvement in terms of accuracy for the use of ratio images.

• Journal of Forest and Environmental Science
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• v.29 no.3
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• pp.194-199
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• 2013

The aim of the present study was to assess the effect of transitional boundary on community composition and soil carbon stock. Five vegetation types were recognized horizontally along the transitional strip based on the dominance of tree species i.e., Pure Anogeissus latifolia forest (P.AL), mixed Pinus roxburghii and Lannea coromandelica forest (M.PR&LC), pure Pinus roxburghii forest (P.PR), mixed Pinus roxburghii and Lannea coromandelica (M.PR&LC) and pure Anogeissus latifolia forest (P.AL). The results revealed that Anogeissus latifolia was reported dominant tree in the outer transitional boundaries of the forest, which reduced dominance of trees towards middle where Pinus roxburghii was found dominant. The soil carbon stock was reported higher in the Anogeissus latifolia dominant forest and reduced with the dominance of Pinus roxburghii in the middle site. Both the species are growing close to one another and competing for survival, but the aggressive nature of Anogeissus latifolia particular in this region may change new growth of Pinus roxburghii and will enhance soil carbon stock. But high anthropogenic pressure on Anogeissus latifolia tree species could be limited chance to further its flourish.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.167-167
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• 2023

Soil organic carbon (SOC) is a critical component of soil health and is crucial in mitigating climate change by sequestering carbon from the atmosphere. Accurate estimation of SOC storage is essential for understanding SOC dynamics and developing effective soil management strategies. This study aimed to investigate the factors influencing the spatial distribution of SOC storage in South Korea, using bulk density (BD) prediction to estimate SOC stock. The study utilized data from 393 soil series collected from various land uses across South Korea established by Korea Rural Development Administration from 1968-1999. The samples were analyzed for soil properties such as soil texture, pH, and BD, and SOC stock was estimated using a predictive model based on BD. The average SOC stock in South Korea at 30 cm topsoil was 49.1 Mg/ha. The study results revealed that soil texture and land use were the most significant factors influencing the spatial distribution of SOC storage in South Korea. Forested areas had significantly higher SOC storage than other land use types. Climate variables such as temperature and precipitation had a relative influence on SOC storage. The findings of this study provide valuable insights into the factors influencing the spatial distribution of SOC storage in South Korea.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.99-108
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• 2023

This study's goal is to investigate the effects of board size, the number of annual board meetings, the profitability of the company, and the audit Committee on the disclosure of climate change in Saudi companies listed on the stock exchange. It was conducted to evaluate affecting some factors on carbon emissions by the regression model. The study uses the content analysis method. Data was collected from the annual and sustainability reports, and the platform database Refinitiv, an LSEG (London Stock Exchange Group Company) for the period 2018 to 2021. The study sample is 51 companies. The study findings showed Saudi Arabia saw its first significant overall drop in CO2 emissions with a 22.61 MtCO2 decline (3.93%) in 2018. The study revealed a positive connection between the size of the director's board, and the disclosure of carbon emissions in Saudi firms listed on the stock market. While other factors are not related to the number of director's board meetings, the audit committee, and the profitability of the company on the disclosure of carbon emissions in the Saudi companies listed on the stock exchange.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.446-452
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• 2014

This research aimed to provide a method to estimate growing stock and carbon stock using the characteristics of forest type map such as the age-class, DBH class and crown density class. We transformed the growing stock data of national forest inventory (mainly Kangwon-do province) onto those of time when the forest type map was established. We developed a simulation model for the growing stock using the transformed data and the characteristics of forest type map by the quantification method I. By comparing partial correlation coefficient, we found that quantification of growing stock was largely affected by age-class followed by crown density class, forest type and DBH class. The growing stock, was estimated as minimum in the broadleaved forest with age-class II, DBH class 'Small', and crown density class 'Low' as $20.0m^3/ha$, whereas showed maximum value in the coniferous forest with age-class VI, DBH class 'Large', and crown density class 'High' as $305.0m^3/ha$. The growing stock for coniferous, broadleaved, and mixed forest were estimated as $30.5{\sim}305.0m^3/ha$, $20.0{\sim}200.4m^3/ha$, and $23.8{\sim}238.1m^3/ha$, respectively. When we compared the carbon stock by forest type, the carbon stock by age class based on growing stock was maximum when DBH class was 'Large' and crown density class was 'High' regardless of forest type. This estimation of growing stock by using characteristic of forest type can be used to estimate the changes in growing stock and carbon stock resulting from deforestation or natural disaster. In addition, we hope it provide a useful advice when forest officials and policy makers have to make decisions in regard to forest management.

• International Area Studies Review
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• v.21 no.4
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• pp.223-245
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• 2017

This study is examined interaction between carbon market with stock market using a multivariate GARCH(DCC) model. Carbon market is EU ETS EUA price, stock market is the iron and cement stock price which has relatively energy intensive and massive carbon emissions sector in the industrial sector. It also analyzed changes in the correlation between the markets through an analysis of correlation coefficients. Moreover, it checked whether there was marketability expansion(or expansion of carbon emissions reduction) through the analysis above. As a result of empirical tests, it showed that the price spillover effect was insignificant. In addition, it represented that there was a weak correlation between the two markets since the volatility spillover effect disappeared in the second phase by an external shock(a financial crisis). Moreover, it was revealed that there were no significant changes although there was a weak upward trend in terms of the correlation between the carbon market and the stock market. This implies that emission rights could not expand marketability to financial market as a commodity(or did not play its natural role of the reduction of carbon emission).

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.439-445
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• 2014

In this study, we developed a dynamic stand yield model to estimate the baseline carbon stock, which is essentially required for a forest carbon offset project based on forest management. For developing the yield model, the data was acquired from the databases of the $5^{th}$ National Forest Inventory. The model was validated by comparing its estimations with field measurements that were conducted from 4 study sites (14 plots with thinning treatments) located in Hong-chun, Hoeng-sung, Yang-yang Daechi and Yang-yang Jungja. The difference between the estimations and the field measurements was less than 5%. Using the dynamic stand yield model, we estimated the changes in stand yield volume and carbon stocks for each species according to the baseline scenarios. As the results, we found that baseline carbon stock was the highest at Quercus acutissima stand (83.01tC/ha), while the lowest at Pinus rigida stand (32.17tC/ha) and Pinus densiflora stand of central region (39.09tC/ha). Hence, a project provider could get more carbon emission credits from an improved forest management project when considering the project with Pinus rigida stand or Pinus densiflora stand (central region). The baseline carbon stock and the dynamic stand yield model developed from this study would be useful for designing carbon offset projects based on improved forest management.