Carbon factors and models for forest carbon estimates for the 2005–2011 National Greenhouse Gas Inventories of the United States

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).

Forest carbon accounting methods and the consequences of forest bioenergy for national greenhouse gas emissions inventories

Evaluation of simulated estimates of forest ecosystem carbon stocks using ground plot data from Canada's National Forest Inventory

In December 2010, parties to the United Nations Framework Convention on Climate Change (UNFCCC) agreed to encourage reductions in greenhouse gas emissions from forest losses with the financial support of developed countries. This important international agreement followed about seven years of effort among governments, non-governmental organizations (NGO) and the scientific community, and is called REDD+, the program for Reducing Emissions from Deforestation and Forest Degradation. REDD+ could achieve its potential to slow emissions from deforestation and forest degradation either as a new market option to offset emissions from developed nations, or as a mitigation option for developing countries themselves. Aside from representing an important step towards reducing greenhouse gas emissions, a growing list of potential co-benefits to REDD+ include improved forestry practices, forest restoration, sustainable development, and biodiversity protection. Indeed the agreement is heralded as a win–win for climate change mitigation and tropical forest conservation, and it could end up contributing to a global economy based on carbon and ecosystem services.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

<p><strong>Abstract.</strong> Calculation of land use and land use change matrix is one of the key elements for the national greenhouse gas (GHG) inventory in land use, land use change and forestry (LULUCF) sector. Main purpose of the land use and land use change matrix is to present comprehensive and harmonized land use and land use change information nationwide over certain time period. Information on land use and land use changes is further used to calculate other parameters important for determination of carbon stock changes and GHG emissions like the stock changes of living and dead biomass, as well as basic information on applied management measures. Aim of this study is to improve methodology for development and maintenance of land use and land use change matrix in the national GHG inventory system using geospatial data information of National forest inventory (NFI) and auxiliary data sources. Creation of land use and land use change matrix is performed in semi-automated way by using GIS tools, which eliminates possible impurities of reported data and have made the calculation process less time consuming than before. New calculation method takes into account present land use data from NFI and land use data from two previous NFI cycles, considerably reducing uncertainty of the estimates, and takes into account land management practices which may alter the land use category in long-term. Auxiliary data, like national land parcel information systems (LPIS), has been introduced to increase certainty, consistency and accuracy for determination of final land-use category. Year-by-year land use change extent detection is carried out by using linear interpolation and extrapolation method is used for the consecutive years for which NFI data are not available.</p><p><strong>Key words: </strong>ERA-GAS INVENT, land use and land use changes, national forest inventory, greenhouse gas inventory.</p>

For many developing countries, the land use sector, particularly agriculture and forestry, represents a large proportion of their greenhouse gas (GHG) emissions, making this sector a priority for GHG mitigation activities. Previous global surveys (e.g., IPCC 2000) as well as the most recent IPCC assessment report clearly indicate that the greatest technical potential for carbon sequestration and reductions of non-CO2 GHG emissions from the land use sector is in developing countries. Estimates that consider economic feasibility suggest that agriculture and forestry together provide among the greatest opportunities for short-term and low-cost mitigation measures across all sectors of the global economy1 (IPCC 2007). In addition, it is widely recognized that the ecosystem changes entailed by most mitigation practices, i.e., building soil organic matter, reducing losses and tightening nutrient cycles, more efficient production systems and preserving native vegetation, are well aligned with goals of increasing food security and rural development as well as buffering land use systems against climate change (Lal 2004). Hence, there is growing interest in jump-starting the capacity for broad-based engagement in agriculturally-based GHG mitigation projects in developing countries.

As a signatory to the United Nations Framework Convention on Climate Change (UNFCCC), the United States has been reporting an economy-wide Inventory of greenhouse gas (GHG) emissions and removals since the mid-1990s (US EPA 2020). Forest land, harvested wood products (HWPs), and urban trees within the land sector collectively represent the largest net carbon (C) sink in the United States, offsetting more than 11 percent of total GHG emissions annually (US EPA 2020). Estimates of GHG emissions and removals are compiled by U.S. Department of Agriculture (USDA) Forest Service researchers and are based primarily on National Forest Inventory (NFI) data collected and maintained by the Forest Inventory and Analysis (FIA) program within the USDA Forest Service. This report--the second in a new series of annual updates--provides an overview of the status and trends of GHG emissions and removals from forest land, woodlands in the grassland category, HWPs, and urban trees in settlements in the United States from 1990 to 2018. The estimates for the United States summarized here are based on the compilation reported in the Land Use, Land-Use Change, and Forestry chapter of the US EPA (2020) submission to the UNFCCC. New in this report, most of the national scale estimates are also reported by individual U.S. state (Fig. 1) and are available online for the entire 1990-2018 time series (see appendix).

Estimation of biomass, volume and growth of subtropical forests in Shitai County, China

Transparent, accurate, comparable, and complete estimates of greenhouse gas emissions and removals are needed to support mitigation goals and performance assessments under the Paris Agreement. Here, we present a comparative analysis of the agriculture forestry and other land use (AFOLU) emission estimates from different datasets, including National Greenhouse Gas Inventories (NGHGIs), FAOSTAT, the BLUE, OSCAR, and Houghton (here after updated H&N2017) bookkeeping models; Emissions Database for Global Atmospheric Research (EDGAR); and the US Environmental Protection Agency (EPA). We disaggregate the fluxes for the forestry and other land use (FOLU) sector into forest land, deforestation, and other land uses (including non-forest land uses), while agricultural emissions are disaggregated according to the sources (i.e., livestock, croplands, rice cultivation, and agricultural fires). Considering different time periods (1990–1999, 2000–2010, and 2011–2018), we analyse the trend of the fluxes with a key focus on the tropical regions (i.e., Latin America, sub-Saharan Africa, and South and Southeast Asia). Three of the five data sources indicated a decline in the net emissions over the tropics over the period 1990–2018. The net FOLU emissions for the tropics varied with values of 5.47, 5.22, 4.28, 3.21, and 1.17 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs, respectively) over the recent period (2011–2018). Gross deforestation emissions over the same period were 5.87, 7.16, 5.48, 3.96, and 3.74 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs). The net forestland sink was −1.97, −3.08, −2.09, −0.53, and −3.00 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs). Continental analysis indicated that the differences between the data sources are much large in sub-Saharan Africa and South and Southeast Asia than in Latin America. Disagreements in the FOLU emission estimates are mainly explained by differences in the managed land areas and the processes considered (i.e., direct vs indirect effects of land use change, and gross vs net accounting for deforestation). Net agricultural emissions from cropland, livestock, and rice cultivation were more homogenous across the FAOSTAT, EDGAR, and EPA datasets, with all the data sources indicating an increase in the emissions over the tropics. However, there were notable differences in the emission from agricultural fires. This study highlights the importance of investing and improving data sources for key fluxes to achieve a more robust and transparent global stocktake.

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.

Greenhouse gas (GHG) emissions resulting from the Land Use, Land-Use Change, and Forestry sector (LULUCF) are estimated and reported in National Communications to the United Nations Framework Convention on Climate Change (UNFCCC). By definition, the LULUCF sector is a “greenhouse gas (GHG) inventory sector that covers emissions and removals of greenhouse gases resulting from direct human-induced land use, land-use change and forestry activities”. In principle, the annual GHG national inventory should be transparent, consistent, comparable, complete, and accurate. Also, it should be able to systematically account for all changes in land use and forest cover over many years. In this context, it is essential to investigate the development of an automated approach for mapping local GHG emissions/removals from the LULUCF sector for integration at the national level. In view of that, the aim of this work was to develop a semi-automated model for estimating GHG emissions and removals form the LULUCF sector at the local level. The specific objectives were to 1) map changes in land use and forest cover between two consecutive years, and 2) assess GHG emissions and removals from the LULUCF sector. The methodology of work comprised the use of Geographic Object-Based Image Analysis (GEOBIA) for modelling changes in the LULUCF sector and, subsequently, estimating GHG emissions/removals between two consecutive years. The combined use of Very High Resolution (VHR) SPOT imagery (2.5 m colour) and field data was involved in identifying and mapping land-use changes between 2014 and 2015. Subsequently, GHG emissions and removals were estimated using customized features in GEOBIA and following the 2003 Intergovernmental Panel on Climate Change “Good Practice Guidance for Land Use, Land-Use Change and Forestry”, which adopts a land use category-based approach to estimate emissions/removals from all land categories and all relevant GHGs. An accuracy assessment of the initial classification was conducted with the use of reference data. The overall classification accuracy of the LULUCF mapping in 2014 was found to be 83%, while the Kappa Index of Agreement (KIA) was 0.74. The developed GEOBIA model estimated for the year 2015 net annual GHG removals of -1.613 Gg of CO2 eq. (i.e., an approximate increase of 12.7% in removals between 2014 and 2015). Future work will involve further development of the model to account for all possible changes in the LULUCF sector and test the transferability of the model to other sites.

Societal Impact StatementForest ecosystems absorb and store about 25% of global carbon dioxide emissions annually and are increasingly shaped by human land use and management. Climate change interacts with land use and forest dynamics to influence observed carbon stocks and the strength of the land carbon sink. We show that climate change effects on modeled forest land carbon stocks are strongest in tropical wildlands that have limited human influence. Global forest carbon stocks and carbon sink strength may decline as climate change and anthropogenic influences intensify, with wildland tropical forests, especially in Amazonia, likely being especially vulnerable.Summary Human effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling. Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900‐present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO2 and temperature change for different anthromes among regions. Modeled global forest carbon stock responses are positive for CO2 increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO2 and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests. The net effect of anthropogenic activities—including land‐use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands.

BackgroundForests are significant terrestrial biomes for carbon storage, and annual carbon accumulation of forest biomass contributes offsets affecting net greenhouse gases in the atmosphere. The immediate loss of stored carbon through fire on forest lands reduces the annual offsets provided by forests. As such, the United States reporting includes annual estimates of direct fire emissions in conjunction with the overall forest stock and change estimates as a part of national greenhouse gas inventories within the United Nations Framework Convention on Climate Change. Forest fire emissions reported for the United States, such as the 129 Tg CO2 reported for 2022, are based on the Wildland Fire Emissions Inventory System (WFEIS). Current WFEIS estimates are included in the Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2022 published in 2024 by the United States Environmental Protection Agency. Here, we describe WFEIS the fire emissions inventory system we used to address current information needs, and an analysis to confirm compatibility of carbon mass between estimated forest fire emissions and carbon in forest stocks.ResultsThe summaries of emissions from forests are consistent with previous reports that show rates and interannual variability in emissions and forest land area burned are generally greater in recent years relative to the 1990s. Both emissions and interannual variability are greater in the western United States. The years with the highest CO2 emissions from forest fires on the 48 conterminous states plus Alaska were 2004, 2005, and 2015. In some years, Alaska emissions exceed those of the 48 conterminous states, such as in 2022, for example. Comparison of forest fire emission to forest carbon stocks indicate there is unlikely any serious disconnect between inventory and fire emissions estimates.ConclusionsThe WFEIS system is a user-driven approach made available via a web browser. Model results are compatible with the scope and reporting needs of the annual national greenhouse gas inventories.

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. .