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The Global Stocktake (GST), implemented by the Paris Agreement, requires rapid developments in the capabilities to quantify annual greenhouse gas (GHG) emissions and removals consistently from the global to the national scale and improvements to national GHG inventories. In particular, new capabilities are needed for accurate attribution of sources and sinks and their trends to natural and anthropogenic processes. On the one hand, this is still a major challenge as national GHG inventories follow globally harmonized methodologies based on the guidelines established by the Intergovernmental Panel on Climate Change, but these can be implemented differently for individual countries. Moreover, in many countries the capability to systematically produce detailed and annually updated GHG inventories is still lacking. On the other hand, spatially-explicit datasets quantifying sources and sinks of carbon dioxide, methane and nitrous oxide emissions from Earth Observations (EO) are still limited by many sources of uncertainty. While national GHG inventories follow diverse methodologies depending on the availability of activity data in the different countries, the proposed comparison with EO-based estimates can help improve our understanding of the comparability of the estimates published by the different countries. Indeed, EO networks and satellite platforms have seen a massive expansion in the past decade, now covering a wide range of essential climate variables and offering high potential to improve the quantification of global and regional GHG budgets and advance process understanding. Yet, there is no EO data that quantifies greenhouse gas fluxes directly, rather there are observations of variables or proxies that can be transformed into fluxes using models. Here, we report results and lessons from the ESA-CCI RECCAP2 project, whose goal was to engage with National Inventory Agencies to improve understanding about the methods used by each community to estimate sources and sinks of GHGs and to evaluate the potential for satellite and in-situ EO to improve national GHG estimates. Based on this dialogue and recent studies, we discuss the potential of EO approaches to provide estimates of GHG budgets that can be compared with those of national GHG inventories. We outline a roadmap for implementation of an EO carbon-monitoring program that can contribute to the Paris Agreement. [ABSTRACT FROM AUTHOR]

Background and aims: In the Jomoro district in Ghana, tree plantations were the first cause of deforestation in the past, drastically reducing the area occupied by primary forests. The aim of this study was to quantify soil organic carbon (SOC) losses due to a change in land use from primary forest to tree plantations (cocoa, coconut, rubber, oil palm) on the different substrates of the district. Secondary forests and mixed plantations were also included in the study. Methods: Soils were sampled at different depths up to 100 cm along a series of chronosequences in each of the three substrates (Granite, Lower Birrimian and Tertiary Sands) present in the area. Results: The highest SOC losses in the 0-30 cm layer were caused by the conversion of primary forests to tree plantations: cocoa −61 % of the original SOC stock, coconut −55 %, rubber −35 % and oil palm 28 %, while mixed plantations and secondary forests showed a loss of 23 % and 21 % of the original SOC stock, respectively. C losses were less apparent from the entire profile (to a depth of 100 cm). Conclusions: All conversions to tree plantations caused substantial SOC losses, comparable to the conversion of forests to agricultural systems. Secondary forests and mixed plantations were the only sustainable land uses that restricted SOC losses considerably. [ABSTRACT FROM AUTHOR]

The aim of this work was to quantify the soil organic C (SOC) stock in the top 30 cm of mineral soil for the whole Italian territory, according to the different land use types of the Intergovernmental Panel on Climate Change (IPCC) cropland category (arable land, agroforestry, vineyards, olive groves, orchards and rice fields), as a basis for future land use scenarios and to address mitigation policy at country level. A database for SOC stock was created with the data from the national project denominated SIAS and partly from regional map reports. All data were referred to the year 2000 since they were derived from surveys conducted from 1995 to 2005. The data were stratified according to the Italian climatic regions, the landscape position and the IPCC cropland subcategories. Taking into account the uncertainty in the estimate, the mean SOC stock values of the different subcategories show significant differences ( p < 0.05) among climatic regions and landscapes, ranging from 41.9 ± 15.9 Mg C ha in the vineyards to 63.3 ± 27.9 Mg C ha in the rice fields. Generally, a small decrease of the SOC stock from the temperate regions toward the Mediterranean ones is observed. Taking into account the mean value of each subcategory and the country area they occupied in 2000, the total C stored in the upper 30 cm of soil was estimated at 490.0 ± 121.7 Tg C. The resulting estimate represents the 17% of the value reported by another study for the soil of the whole country down to 50 cm depth, suggesting the importance of preserving this large C pool. Considering the cropland category as a whole, the estimated mean SOC stock is 52.1 ± 17.4 Mg C ha, similar to that reported for other European countries, 50-60 Mg C ha. In conclusion, the assessment of the mean SOC stock of the different cropland land uses, landscape position and climate regions could notably help when assessing the impact of different agricultural practices and future stock change evaluation. [ABSTRACT FROM AUTHOR]

The purpose of the present work is to asses the possibility of detecting changes in soil organic carbon (SOC) at the end of the 5-years of the first Commitment Period (CP) of the Kyoto Protocol of the United Nation's Framework Convention on Climate Change (1 January, 2008-31 December, 2012), by both direct measurement and the use of an opportunely evaluated SOC model, CENTURY. The investigated soil is young, developed since 28 years on virtually C-free spoil banks and under the influence of two managed forest stands, one a mix of English oak ( Quercus robur L.) and Italian alder ( Alnus cordata Loisel.) and the other pure English oak. The SOC stock of either stand was monitored since the time the stands were planted in 1981, and it was used together with other parameters for the model evaluation, while the future projections for the end of the first (2012) and second (2017) CP were made according to two extreme IPCC climatic scenarios: A1F1, the most dramatic, and B2, among the less impacting. Direct SOC measurements performed at the beginning and at the end of a time frame equivalent to a commitment period (2004-2008) had not shown significant variations in either stands. Compared to the 2008 SOC stock, in both stands the model shows variations at the end of the first CP from 0.7 to 1.8 Mg C ha for the A1F1 scenario and from 0.3 to 1.7 Mg C ha for the B2. These variations are within the standard deviations of the C stocks measured in 2008. On the contrary, at the end of the second CP, the modelled SOC increments range from 2.5 to 3.6 Mg C ha (A1F1) or from 1.9 to 3.4 Mg C ha (B2), indicating the possibility to detect the SOC changes by direct measurement, since the values well agree with the minimum detectable variation estimated for both sites in 3.3-4.5 Mg C ha. This work shows that SOC stock changes measured directly in the field can be minimal at the end of both CPs, and that CENTURY well simulates the SOC dynamics of the stands. The use of such a model, validated at long-term experimental sites, hence represents an effective tool for estimating future changes in SOC amounts in support of direct measurements when a short period of time, such as the CP, is considered. [ABSTRACT FROM AUTHOR]