Greenhouse gas mitigation in the agricultural sector in Spain

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Abstract. The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20–25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates, however, remain highly uncertain, jeopardizing the mitigation effectiveness of this sector. Comparisons of global AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding of the reasons behind these differences. Here we compare a variety of AFOLU emission datasets and estimates given in the Fifth Assessment Report for the tropics (2000–2005) to identify plausible explanations for the differences in (i) aggregated gross AFOLU emissions, and (ii) disaggregated emissions by sources and gases (CO2, CH4, N2O). We also aim to (iii) identify countries with low agreement among AFOLU datasets to navigate research efforts. The datasets are FAOSTAT (Food and Agriculture Organization of the United Nations, Statistics Division), EDGAR (Emissions Database for Global Atmospheric Research), the newly developed AFOLU “Hotspots”, “Houghton”, “Baccini”, and EPA (US Environmental Protection Agency) datasets. Aggregated gross emissions were similar for all databases for the AFOLU sector: 8.2 (5.5–12.2), 8.4, and 8.0 Pg CO2 eq. yr−1 (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8–10), 5.9, 5.9, and 5.4 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and agricultural sectors were with 1.9 (1.5–2.5), 2.5, 2.1, and 2.0 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating the emissions by sources, continents, and gases, particularly for the forest sector, with fire leading the differences. Agricultural emissions were more homogeneous, especially from livestock, while those from croplands were the most diverse. CO2 showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (carbon-only vs. multi-gas assessments, definitions, land use vs. land cover, etc.), in methods (tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc.) and in assumptions (carbon neutrality of certain emissions, instantaneous emissions release, etc.) which call for more complete and transparent documentation for all the available datasets. An enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

The Paris Agreement commits 197 countries to stabilizing global average surface temperatures at less than 2 °C above pre-industrial levels. Many industrialized nations, including Italy, aim for climate neutrality by 2050 through “net zero” greenhouse gas (GHG) emissions policies, aimed at decarbonizing all the energy intensive sector. In this context, the role of agriculture, forestry, and other land use (AFOLU) sector play an ambiguous role. Challenges include balancing GHG mitigation with food security, addressing synergies with the energy sector (e.g., bio commodities), and leveraging AFOLU as a net sink to offset emissions from other sectors.Energy system optimization models (ESOMs), as widely used to design cost-optimal decarbonization policies, can be used to determine effective AFOLU management strategies at a national level. Nevertheless, their focus on energy-intensive processes had previously limited detailed AFOLU representation, despite its prominent role in emission mitigation. ESOMs often lack the integration of natural capital constraints, such as land and water availability, as well as the ability to model specific AFOLU commodities like crops, livestock, and forest products. To address this gap, we introduce a novel AFOLU module designed to couple with ESOMs, enabling the formulation of national decarbonization scenarios incorporating a technology-explicit AFOLU representation, biophysical constraints and the possibility to evaluate climate change impacts on the sector.The AFOLU module tracks GHG emissions from livestock, crops, and bioenergy production while optimizing sectoral contributions to national decarbonization goals. Additionally, it projects the evolution of AFOLU commodities, including shifts in crop types, livestock production, and forest management strategies in response to climate and policy drivers. Finally, it can account for biophysical constraints such as land use limitations, crop yield sensitivity to fertilizer and climate change, and forest absorption potential. The module is designed to be directly fed by the Global Agro-Ecological Zones (GAEZ) database from FAO, allowing for the automatized creation of national instances based on up-to-date geospatial datasets.To demonstrate the utility of the module, we integrate it with the open-source energy system optimization model TEMOA, which has been validated in Italian case studies and shown coherence with established models like TIMES, and similar in structure to other ESOMs like MESSAGE, and OSeMOSYS. The integrated model evaluates Italy’s national climate mitigation plans, focusing on the interplay between energy and AFOLU sectors, including land competition for bio crop production.Key outputs of the model include detailed accounting and optimization of AFOLU emissions, land and water use, and cost-effective decarbonization pathways for all the energy intensive sectors. For instance, scenarios explore the potential of organic farming to reduce crop-related emissions, the role of manure management in mitigating livestock emissions, and the benefits of afforestation for carbon sequestration. Preliminary results from the Italian case study reveal critical trade-offs and synergies, such as the tension between bioenergy production and food security, while identifying least-cost pathways to achieve climate neutrality.This research bridges a critical gap in decarbonization modeling by integrating a flexible AFOLU module with energy systems, offering a reproducible framework for other national applications. 

South Africa is a signatory to the United Nations Framework Convention on Climate Change (UNFCCC) and as such is required to report on Greenhouse gas (GHG) emissions from the Energy, Transport, Waste and the Agriculture, Forestry and Other Land Use (AFOLU) sectors every two years in national inventories. The AFOLU sector is unique in that it comprises both sources and sinks for GHGs. Emissions from the AFOLU sector are estimated to contribute a quarter of the total global greenhouse gas emissions. GHG emissions sources from agriculture include enteric fermentation; manure management; manure deposits on pastures, and soil fertilization. Emissions sources from Forestry and Other Land Use (FOLU) include anthropogenic land use activities such as: management of croplands, forests and grasslands and changes in land use cover (the conversion of one land use to another). South Africa has improved the quantification of AFOLU emissions and the understanding of the dynamic relationship between sinks and sources over the past decade through projects such as the 2010 GHG Inventory, the Mitigation Potential Analysis (MPA), and the National Terrestrial Carbon Sinks Assessment (NTCSA). These projects highlight key mitigation opportunities in South Africa and discuss their potentials. The problem remains that South Africa does not have an emissions baseline for the AFOLU sector against which the mitigation potentials can be measured. The AFOLU sector as a result is often excluded from future emission projections, giving an incomplete picture of South Africa’s mitigation potential. The purpose of this project was to develop a robust GHG emissions baseline for the AFOLU sector which will enable South Africa to project emissions into the future and demonstrate its contribution towards the global goal of reducing emissions.

Greenhouse gas (GHG) emissions from agriculture, including crop and livestock production, forestry and associated land use changes, are responsible for a significant fraction of anthropogenic emissions, up to 30% according to the Intergovernmental Panel on Climate Change (IPCC). Yet while emissions from fossil fuels are updated yearly and by multiple sources—including national-level statistics from the International Energy Agency (IEA)—no comparable efforts for reporting global statistics for agriculture, forestry and other land use (AFOLU) emissions exist: the latest complete assessment was the 2007 IPCC report, based on 2005 emission data. This gap is critical for several reasons. First, potentially large climate funding could be linked in coming decades to more precise estimates of emissions and mitigation potentials. For many developing countries, and especially the least developed ones, this requires improved assessments of AFOLU emissions. Second, growth in global emissions from fossil fuels has outpaced that from AFOLU during every decade of the period 1961–2010, so the relative contribution of the latter to total climate forcing has diminished over time, with a need for regular updates. We present results from a new GHG database developed at FAO, providing a complete and coherent time series of emission statistics over a reference period 1961–2010, at country level, based on FAOSTAT activity data and IPCC Tier 1 methodology. We discuss results at global and regional level, focusing on trends in the agriculture sector and net deforestation. Our results complement those available from the IPCC, extending trend analysis to a longer historical period and, critically, beyond 2005 to more recent years. In particular, from 2000 to 2010, we find that agricultural emissions increased by 1.1% annually, reaching 4.6 Gt CO2 yr−1 in 2010 (up to 5.4–5.8 Gt CO2 yr−1 with emissions from biomass burning and organic soils included). Over the same decade 2000–2010, the ratio of agriculture to fossil fuel emissions has decreased, from 17.2% to 13.7%, and the decrease is even greater for the ratio of net deforestation to fossil fuel emissions: from 19.1% to 10.1%. In fact, in the year 2000, emissions from agriculture have been consistently larger—about 1.2 Gt CO2 yr−1 in 2010—than those from net deforestation.

This study uses GLOBIOM ‒ the most detailed global economic model of agriculture, land use and greenhouse gas (GHG) emissions ‒ to assess the effectiveness of different policies in cutting net emissions from the Agriculture, Forestry and Other Land Use (AFOLU) sector, with a view to helping limit long-term global temperature increases to 1.5°C and 2°C. Trade-offs between emission reductions and impacts on food producers, consumers and government budgets are also evaluated for each policy package. A full complement of policy options is deployed globally across AFOLU, comprising emission taxes for emitting AFOLU activities and subsidies rewarding carbon sequestration. Using a carbon price consistent with the 2°C target (1.5°C target), this is projected to mitigate 8 GtCO2 eq/yr (12 GtCO2 eq/yr) in 2050, representing 89% (129%) reduction in net AFOLU emissions, and 12% (21%) of total anthropogenic GHG emissions. Nearly two-thirds of the net emission reductions are from the Land Use, Land-Use Change and Forestry (LULUCF) component of AFOLU, mostly from reduced deforestation. A global carbon tax on AFOLU is found to be twice as effective in lowering emissions as an equivalently priced emission abatement subsidy because the latter keeps high emitting producers in business. However, a tax has trade-offs in terms of lower agricultural production and food consumption, which a subsidy avoids. A shift to lower emission diets by consumers has a much smaller impact on reducing agricultural emissions than any of the policy packages involving taxes on emissions.

Agriculture and forestry are the two major land use classes providing sustenance to the human population. With the pace of development, these two land use classes continue to change over time. Land use change is a dynamic process under the influence of multiple drivers including climate change. Therefore, tracing the trajectory of the changes is challenging. The artificial neural network (ANN) has successfully been applied for tracing such a dynamic process to capture nonlinear responses. We test the application of the multilayer perceptron neural network (MLP-NN) to project the future Agriculture, Forestry and Other Land Use (AFOLU) for the year 2050 for the South Asian Association for Regional Cooperation (SAARC) nations which is a geopolitical union of Afghanistan, Bangladesh, Bhutan, India, Nepal, Maldives, Pakistan and Sri Lanka. The Intergovernmental Panel on Climate Change (IPCC) and Food and Agriculture Organization (FAO) use much frequently the term 'AFOLU' in their policy documents. Hence, we restricted our land use classification scheme as AFOLU for assessing the influence of climate change scenarios of the IPCC fifth assessment report (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5). Agricultural land would increase in all the SAARC nations, with the highest increase in Pakistan and Maldives; moderate increase in Afghanistan, India and Nepal; and the least increase in Bangladesh, Bhutan and Sri Lanka. The forestry land use will witness a decreasing trend under all scenarios in all of the SAARC nations with varying levels of changes. The study is expected to assist planners and policymakers to develop nations' specific strategy to proportionate land use classes to meet various needs on a sustainable basis.

BackgroundThe Agriculture, Forestry and Other Land Use (AFOLU) sector is responsible for almost a quarter of the global Greenhouse gases (GHG) emissions. The emissions associated with AFOLU activities are projected to increase in the future. The agriculture sector in Thailand accounted for 21.9% of the country’s net GHG emissions in 2013. This study aims to estimate the GHG emissions in the AFOLU sector and mitigation potential at various carbon prices during 2015–2050. This study uses an AFOLU bottom-up (AFOLUB) model to estimate GHG emissions in a business-as-usual (BAU) scenario, and then identifies no-regret options, i.e. countermeasures that are cost-effective without any additional costs. In addition, the study also identifies countermeasure options and mitigation potential at various carbon prices.ResultsResults show that emissions from the agriculture sector in the BAU will increase from 45.3 MtCO2eq in 2015 to 63.6 MtCO2eq in 2050, whereas net emission from the AFOLU will be 8.3 MtCO2eq in 2015 and 24.6 MtCO2eq in 2050. No-regret options would reduce emissions by 6.1 and 6.8 MtCO2eq in 2030 and 2050, respectively. The carbon price above $10 per tCO2eq will not be effective to achieve significant additional mitigation/sequestration.ConclusionsIn 2050, no-regret options could reduce total AFOLU emissions by 27.5%. Increasing carbon price above $10/tCO2eq does not increase the mitigation potential significantly. Net sequestration (i.e., higher carbon sequestration than GHG emissions) in AFOLU sector would be possible with the carbon price. In 2050, net sequestration would be 1.2 MtCO2eq at carbon price of $5 per tCO2eq, 21.4 at $10 per tCO2eq and 26.8MtCO2eq at $500 per tCO2eq.

Abstract. The Paris Agreement commits 197 countries to achieve climate stabilisation at a global average surface temperature less than 2 ∘C above pre-industrial times using nationally determined contributions (NDCs) to demonstrate progress. Numerous industrialised economies have targets to achieve territorial climate neutrality by 2050, primarily in the form of “net zero” greenhouse gas (GHG) emissions. However, particular uncertainty remains over the role of countries' agriculture, forestry, and other land use (AFOLU) sectors for reasons including the potential trade-offs between GHG mitigation and food security, a non-zero emission target for methane as a short-lived GHG, and the requirement for AFOLU to act as a net sink to offset residual emissions from other sectors. These issues are represented at a coarse level in integrated assessment models (IAMs) that indicate the role of AFOLU in global pathways towards climate stabilisation. However, there is an urgent need to determine appropriate AFOLU management strategies at a national level within NDCs. Here, we present a new model designed to evaluate detailed AFOLU scenarios at national scale using the example of Ireland, where approximately 40 % of national GHG emissions originate from AFOLU. GOBLIN (General Overview for a Backcasting approach of Livestock INtensification) is designed to run randomised scenarios of agricultural activities and land use combinations within biophysical constraints (e.g. available land area, livestock productivities, fertiliser-driven grass yields, and forest growth rates). Using AFOLU emission factors from national GHG inventory reporting, GOBLIN calculates annual GHG emissions out to the selected target year for each scenario (2050 in this case). The long-term dynamics of forestry are represented up to 2120 so that scenarios can also be evaluated against the Paris Agreement commitment to achieve a balance between emissions and removals over the second half of the 21st century. Filtering randomised scenarios according to compliance with specific biophysical definitions (GHG time series) of climate neutrality will provide scientific boundaries for appropriate long-term actions within NDCs. We outline the rationale and methodology behind the development of GOBLIN, with an emphasis on biophysical linkages across food production, GHG emissions, and carbon sinks at a national level. We then demonstrate how GOBLIN can be applied to evaluate different scenarios in relation to a few possible simple definitions of “climate neutrality”, discussing opportunities and limitations.

Abstract. The current country is the result of changes from the original country, mainly due to human influence. The external appearance of the landscape is represented by landscape cover. Within the EU, the Copernicus program, coordinated by the European Environment Agency (EEA), is dedicated to Earth and environmental monitoring. The outputs of the program are information services based on satellite observations of the Earth and ground-based collection of spatial data - implemented in cooperation with individual Member States of the EU. The Copernicus Land Monitoring Service (CLMS) and the collection of geographical information about land cover and land cover changes, land use, vegetation status, water cycles and the energy of the Earth's surface are provided.The Slovak Republic has been involved in the program since 1990. Corine Land Cover (CLC) data are freely available for 1990, 2000, 2006, 2012 and 2018. The CLC legend is a mutual combination of land cover and land use, the highest - third hierarchical level of the CLC classification identifies 44 classes. Data are available in the form of vectors and rasters, with a scale of 1 : 100 000, coordinate system: ETRS89, minimum mapping unit of 25 ha was selected.In this paper, we focus on the identification of the condition and spatial modeling of landscape changes with emphasis on forests. Forests as important carbon sinks are an environmental factor that influences the impact of emissions on the development of greenhouse gases and climate change. According to the Intergovernmental Panel on Climate Change (IPCC), member countries report changes in land cover categories according to the AFOLU (Agriculture, Forestry and Other Land Use) classification. For the purposes of estimating greenhouse gas emissions, the AFOLU methodology distinguishes six categories: forest land; cropland; grassland; wetlands; settlements; other areas.The main goal of the paper is the development and presentation of an integrated geographical database of land cover data of the Slovak Republic from CLC datasets (in the period 1990 to 2018), a tool for reclassification of the third hierarchical level CLC and creation of data structures of land use categories according to AFOLU.The specific goal is the development and presentation of an interactive tool - a web application for retrospective assessment of land cover changes from the integrated geographical database according to the CLC classification and interactive assessment of land cover changes according to the AFOLU classification. The outputs of the interactive evaluation of land cover changes will focus on the forest land cover category, evaluation of changes according to adjustable time intervals in CLC and AFOLU and the statistical evaluation of changes.The output is a freely available web application with interactive functionality for datasets, database modeling of land cover changes, statistical evaluation of changes and creation of map outputs. A case study of data processing for the area of the Bratislava region (205 270 ha) in the years 1990 to 2018 (five CLC datasets) is presented. The datasets are suitable for continuously identifying the state of land cover, modeling its changes over time and interpreting land cover change processes over time.

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The land use, land use change and forestry (LULUCF) sector is a greenhouse gas (GHG) inventory sector that covers the emissions of GHGs from and their removal by terrestrial carbon stocks, living biomass, dead organic matter and soil organic carbon according to six main anthropogenic land use categories: Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land. According to the United Nations Framework Convention on Climate Change (UNFCCC), all Parties shall periodically report an update inventory of anthropogenic emissions and removals of GHGs using comparable methodologies provided by the Intergovernmental Panel on Climate Change (IPCC). Parties are also required to report and account for such emissions under the Kyoto Protocol (KP). These emission inventories are then factored into an international reduction target commitment. In recent years, international negotiations have resulted in the adoption of new rules for the second commitment period of the KP (CP2: 2013-2020), e.g. mandatory accounting of Forest management. Furthermore, Decision 529/2013/EU goes beyond the international UNFCCC negotiations by adding the mandatory accounting of Cropland management and Grassland management. All these changes pose new challenges that Member States (MS) will need to address from 2015 (i.e. the start of the CP2 reporting period). This report describes the actions undertaken in the context of the JRC’s “LULUCF MRV” (Monitoring, Reporting, and Verification) Administrative Arrangement with DG CLIMA, through a sequence of tasks (described in detail in the Annexes). The aim of the AA is to support MS in improving the quality and comparability of their LULUCF reporting during CP2, in line with IPCC methods and the new UNFCCC and EU rules. .

Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration. Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration.

This review places in context the role agricultural soils play in global carbon dynamics, and their potential interaction with climate change through soil carbon sequestration. The paper first examine the potential of soils as carbon sinks, agricultural practices and dynamics in soil organic carbon, emerging agreements on payments for environmental services (PES) that mitigate global warming through enhanced carbon sinks, exclusion of agricultural activities in PES under Kyoto Protocol, and the basis for inclusion of agricultural soil carbon sinks through sustainability based production systems. Soils are one of the planet's largest sinks for carbon and hold potential for expanded carbon sequestration through changes in management. The global soil organic carbon (SOC) inventory is estimated to be 1200-1600 billion metric tonnes, which is equal to or slightly greater than amounts stored in terrestrial vegetation (500-700 billion metric tonnes) and the atmosphere (750 billion metric tonnes), combined. Agricultural soils, having been depleted of much of their native carbon stocks, and occupying an estimated 1.7 billion hectares, have a more significant potential SOC sink capacity. Global estimates of this sink capacity are in the order of 20-30 billion metric tonnes over the next 50-100 years. The total global agricultural soils' SOC stocks are estimated at 167-170 billion metric tonnes. When soil is put into cultivation, associated biological and physical processes result in a release of SOC over time, often 50% or more, depending on soil conditions and agricultural practices. Consequently, there is potential to increase SOC in most cultivated soils. Many management practices have been demonstrated to increase SOC, including incorporation of crop residues, and increases in cropping intensity and fertilization. Past and on-going biophysical studies have been able to identify and demonstrate organic based soil fertility management practices, with modest applications of mineral fertilizers that would concurrently lead to improvement in SOC levels, nutrient loss amelioration and improved agricultural productivity. Management practices that could add 4 T C ha-1 yr-1 in the system have been demonstrated. Due to the potential impacts of climate change on the environment as a result of increasing concentration of GHGs in the atmosphere, particularly carbon dioxide, the world community established the Intergovernmental Panel on Climate Change (IPCC) in 1988. The responsibility of IPCC is to undertake an assessment of the science, impacts, adaptation, and mitigation options in relation to climate change and advise the Conference of Parties (COP) of the United Nations Framework Convention on Climate Change (UNFCCC). At the sixth Conference of the Parties (COP-6) in Marrakech, Morocco, limits were placed on the nature of activities that could be undertaken and the amount of carbon credits that could be generated through land use change and forestry activities to benefit from PES. These limits excluded all activities associated with management of natural forests and agricultural lands. This review argues that a demonstration of sustainability of carbon sinks in agricultural soils under empirically derived predictable management practices could serve as a basis for arguing the case for inclusion of carbon sinks in such systems in payments for environmental services under the Clean Development (CDM) of Kyoto Protocol.

The development of country-specific emission factors in relation to the Agriculture, Forestry, and Other Land Use (AFOLU) sector has the potential to improve national greenhouse gas inventory systems. Forests are carbon sinks in the AFOLU that can play an important role in mitigating global climate change. According to the United Nations Framework Convention on Climate Change (UNFCCC), signatory countries must report forest carbon stocks, and the changes within them, using emission factors from the Intergovernmental Panel on Climate Change (IPCC) or from country-specific values. This study was conducted to estimate forests carbon stocks and to complement and improve the accuracy of national greenhouse gas inventory reporting in South Korea. We developed country-specific emissions factors and estimated carbon stocks and their changes using the different approaches and methods described by the IPCC (IPCCEF: IPCC default emission factors, CSFT: country-specific emission factors by forest type, and CSSP: country-specific emission factors by species). CSFT returned a result for carbon stocks that was 1.2 times higher than the value using IPCCEF. Using CSSP, CO2 removal was estimated to be 60,648 Gg CO2 per year with an uncertainty of 22%. Despite a reduction in total forest area, forests continued to store carbon and absorb CO2, owing to differences in the carbon storage capacities of different forest types and tree species. The results of this study will aid estimations of carbon stock changes and CO2 removal by forest type or species, and help to improve the completeness and accuracy of the national greenhouse gas inventory. Furthermore, our results provide important information for developing countries implementing Tier 2, the level national greenhouse gas inventory systems recommended by the IPCC.