National Greenhouse Gas Inventories Research Articles

Changes in carbon stocks according to stand development stages in oriental beech forests in the Marmara Region of Türkiye.

This study was conducted to determine the changes in carbon stocks of oriental beech (Fagus orientalis) according to stand development stage in the Marmara Region of Türkiye. For this purpose, sample plots were taken from a total of 32 areas encompassing four stand development stages (young, middle age, mature and overmature stand). The diameter at breast height and height of all trees in the sample plots were measured, and only three dominant trees's ages per plot were determined. Aboveground carbon stock was calculated using equations developed for beech forests, while the coefficients in the Agriculture, Forestry and Other Land Use guide were used to determine belowground carbon stocks. A soil pit was dug in each plot and soil samples were taken at different depths (0-10, 10-30, 30-60, 60-100cm). In addition, litters were sampled from four different 25 × 25cm sections in each plot, and then the physical and chemical properties of the soil and litters were analysed. The variations in carbon stocks in above- and below-ground tree mass, litter and soil, and in ecosystem carbon stocks according to development stage were examined by analysis of variance and Duncan test, and the relationships between the carbon stocks were investigated by correlation analysis. Aboveground (AG) and belowground (BG) tree, soil and ecosystem carbon stocks showed significant differences between the four stand development stages (P < 0.05), but not the litter carbon stocks (P > 0.05). AG and BG tree and ecosystem carbon stocks increased with progressive stand development stages, while the soil carbon stock was the highest at the young stage. These findings will contribute to the preparation of forest management plans and the national greenhouse gas inventory.

Enhancing Transparency of Climate Efforts: MITICA’s Integrated Approach to Greenhouse Gas Mitigation

Under the Paris Agreement, countries must articulate their most ambitious mitigation targets in their Nationally Determined Contributions (NDCs) every five years and regularly submit interconnected information on greenhouse gas (GHG) aspects, including national GHG inventories, NDC progress tracking, mitigation policies and measures (PAMs), and GHG projections in various mitigation scenarios. Research highlights significant gaps in the definition of mitigation targets and the reporting on GHG-related elements, such as inconsistencies between national GHG inventories, projections, and mitigation targets, a disconnect between PAMs and mitigation scenarios, as well as varied methodological approaches across sectors. To address these challenges, the Mitigation-Inventory Tool for Integrated Climate Action (MITICA) provides a methodological framework that links national GHG inventories, PAMs and GHG projections, applying a hybrid decomposition approach that integrates machine learning regression techniques with classical forecasting methods for developing GHG emission projections. MITICA enables mitigation scenario generation until 2050, incorporating over 60 PAMs across Intergovernmental Panel on Climate Change (IPCC) sectors. It is the first modelling approach that ensures consistency between reporting elements, aligning NDC progress tracking and target setting with IPCC best practices while linking climate change with sustainable economic development. MITICA’s results include projections that align with observed trends, validated through cross-validation against test data, and employ robust methods for evaluating PAMs, thereby establishing its reliability.

Including Methane Emissions from Agricultural Ponds in National Greenhouse Gas Inventories.

Agricultural ponds are a significant source of greenhouse gases, contributing to the ongoing challenge of anthropogenic climate change. Nations are encouraged to account for these emissions in their national greenhouse gas inventory reports. We present a remote sensing approach using open-access satellite imagery to estimate total methane emissions from agricultural ponds that account for (1) monthly fluctuations in the surface area of individual ponds, (2) rates of historical accumulation of agricultural ponds, and (3) the temperature dependence of methane emissions. As a case study, we used this method to inform the 2024 National Greenhouse Gas Inventory reports submitted by the Australian government, in compliance with the Paris Agreement. Total annual methane emissions increased by 58% from 1990 (26 kilotons CH4 year-1) to 2022 (41 kilotons CH4 year-1). This increase is linked to the water surface of agricultural ponds growing by 51% between 1990 (115 kilo hectares; 1,150 km2) and 2022 (173 kilo hectares; 1,730 km2). In Australia, 16,000 new agricultural ponds are built annually, expanding methane-emitting water surfaces by 1,230 ha yearly (12.3 km2 year-1). On average, the methane flux of agricultural ponds in Australia is 0.238 t CH4 ha-1 year-1. These results offer policymakers insights into developing targeted mitigation strategies to curb these specific forms of anthropogenic emissions. For instance, financial incentives, such as carbon or biodiversity credits, can mobilize widespread investments toward reducing greenhouse gas emissions and enhancing the ecological and environmental values of agricultural ponds. Our data and modeling tools are available on a free cloud-based platform for other countries to adopt this approach.

Inventory and Distribution Characteristics of Carbon Emissions from Agricultural Sources in Henan Province from 2011 to 2020

Agriculture is an important part of Henan's economic development, and agricultural production is also an important source of greenhouse gas emissions. In this paper, the activity level data of agricultural carbon emissions in 18 cities in Henan Province were collected. Based on the calculation method provided by the Guidelines for Compiling Provincial Greenhouse Gas Inventories and referring to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, agricultural CO2, CH4 and N2O emissions were carefully estimated. An agricultural greenhouse gas inventory was compiled for Henan Province from 2011 to 2020. Then, based on the spatial distribution and emission intensity, the carbon emissions of each city in Henan Province in 2019 were further analyzed. The results show that carbon emissions decreased from 57,603,500 tons in 2011 to 44,517,300 tons in 2020, with an average annual decrease rate of about 2.66%. The total agricultural carbon emissions in Henan showed a downward trend, and agricultural land was the dominant factor of carbon emissions, accounting for about 47% of the total carbon emissions over the years.

A national accounting framework for fire and carbon dynamics in Australian savannas

Background Tropical savannas represent a large proportion of the area burnt each year globally, with growing evidence that management to curtail fire frequency and intensity in some of these regions can contribute to mitigation of climate change. Approximately 25% of Australia’s fire-prone tropical savanna region is currently managed for carbon projects, contributing significantly to Australia’s National Greenhouse Gas Inventory. Aims To improve the accuracy of Australia’s national carbon accounting model (FullCAM) for reporting of fire emissions and sequestration of carbon in savanna ecosystems. Methods Field data from Australian savannas were collated and used to calibrate FullCAM parameters for the prediction of living biomass, standing dead biomass and debris within seven broad vegetation types. Key results Revised parameter sets and improved predictions of carbon stocks and fluxes across Australia’s savanna ecosystems in response to wildfire and planned fire were obtained. Conclusions The FullCAM model was successfully calibrated to include fire impacts and post-fire recovery in savanna ecosystems. Implications This study has expanded the capability of FullCAM to simulate both reduced emissions and increased sequestration of carbon in response to management of fire in tropical savanna regions of Australia, with implications for carbon accounting at national and project scales.

Evaluation of Contribution to Greenhouse Gas Reduction and Economic Benefits of Livestock Manure based Solid Fuel

Objectives : In the context where the greenhouse gas (GHG) emissions from livestock manure (LSM) account for more than half of the GHG emissions in the livestock sector, it is necessary to find alternatives to composting due to the decrease in agricultural land. This study aims to calculate the GHG reduction contribution and economic benefits when converting LSM into solid fuel as an alternative to traditional composting.Methods : The study compares the results of converting the entire LSM generated domestically into solid fuel replacing it with hard coal for fuel (HC-F), bituminous coal for raw materials (BC-R), bituminous coal for fuel (BC-F). The GHG reduction contribution is calculated following the domestic GHG inventory methodology, using the IPCC guidelines and the method for calculating carbon emission reduction effects. For the assessment of economic benefits, were evaluated by aggregating the impacts of reducing coal imports and GHG reduction benefits in line with EU-ETS standards. Economic benefits are assessed by combining the effects of avoiding coal imports and the GHG reduction benefits according to the EU-ETS.Results and Discussion : The GHG reduction effect was found to be highest when replacing with HC-F, and this is attributed to the lower heating value and higher GHG emission coefficient of HC-F compared to BC-R, and BC-F, indicating that the substitution with HC-F is most effective in terms of import avoidance. If 20% of the annual coal consumption in 2022 is replaced with solid fuel from LSM, the GHG reduction effects for coal substitution are 1.4% for HC-F, 2.1% for BC-R, and 1.9% for BC-F based on the LSM generation CO&lt;sub&gt;2&lt;/sub&gt; emissions from biomass fuel are considered climate-neutral and are excluded from the national total emissions. Solid fuel from LSM serves as an alternative in addressing the GHG generated during the LSM treatment process, contributing to potential reduction. If all generated LSM is replaced with HC-F, BC-R, or BC-F, there are respective GHG reduction effects of 13,193,591 tGHG, 11,320,572 tGHG, and 11,226,331 tGHG.Conclusion In 2018, the livestock sector accounted for approximately 42% of the GHG emissions in the agricultural sector, totaling 9.4 million tCO&lt;sub&gt;2&lt;/sub&gt; eq. Assuming the complete conversion of LSM into solid fuel for coal substitution, regardless of the type of coal replaced, it offsets the entire GHG emissions from the agricultural sector. Currently, there is limited demand for the conversion of LSM into solid fuel due to a lack of proof and awareness, but with some coal-fired power plants scheduled for partial shutdown and the government considering energy options for LSM, a promising stage is anticipated in the future for the substitution and expanded use of solid fuel from LSM in place of coal in the coal fuel. Although it may not be possible to entirely replace the coal used in power plants and steel mills with solid fuel from LSM, it can be utilized by increasing the proportion of coal blending. However, even if not reported in the national GHG inventory, the treatment of pollutants generated by solid fuel combustion remains an ongoing challenge. As solid fuel becomes more commonplace in the future, a comprehensive assessment of the entire process, including potential environmental impacts throughout the life cycle, will be necessary to establish a basis for GHG reduction measures.

Is the organic carbon-to-clay ratio a reliable indicator of soil health?

Climate action plans under the Paris Climate Agreement and other national commitments aimed at improving soil-based ecosystem services require the operational monitoring of soil carbon (C). The European Union is aiming to enhance soil health, and as part of the proposed Soil Monitoring Law, the European Commission recommends the monitoring of the soil C loss indicator among other soil health indicators. In this study, we evaluate the feasibility of the proposed soil C loss indicator by assessing its performance using the EU-wide 2009 LUCAS soil survey data. The proposed indicator is the soil organic carbon (SOC) to clay ratio, with a threshold value of 1:13. The results are also compared with the C stock changes reported by countries to the climate convention (UNFCCC). Our results reveal that the variation in SOC and clay content at European scale exceeds that of the data used to develop the proposed indicator. We also found that the variation in the SOC content was influenced not only by clay content but also by climate and land-use reflecting C input levels. Therefore, the defined threshold is inadequate for detecting degraded soils if the SOC and clay content are beyond the conditions used to establish the criteria. Furthermore, major discrepancies were observed between the soil carbon stock changes reported by the national greenhouse gas (GHG) inventories and the proportions of degraded soils identified by using the soil C loss indicator. We conclude that employing a single indicator such as SOC:Clay ratio with one threshold value for all soils across various land covers, management practices, and climatic conditions, as defined by the European Commission for the Soil Monitoring Law, is inappropriate for monitoring soil C loss.

Greenhouse gas emissions from cattle enclosures in semi-arid sub-Saharan Africa: The case of a rangeland in South-Central Kenya

Extensive livestock production in pastoral areas supports millions of livestock keepers in Sub-Saharan Africa (SSA). However, it is also linked to environmental externalities such as greenhouse gas (GHG) emissions. Corralling of livestock overnight in fenced enclosures (“bomas” in Kiswahili) is common to protect animals from theft and predation and is practiced across SSA. Boma manure is usually not removed and accumulates over years, making bomas GHG emission hotspots. The following study presents the first full year of CO2, CH4, and N2O emissions measurements from cattle bomas in a savanna ecosystem in Kenya, comparing active (in use) and inactive (i.e., abandoned) bomas. Active bomas were used for 1–3 months before being abandoned and cattle were moved to a new boma. GHG emissions were measured using static chambers inside three replicate bomas and along three 100 m transects from bomas into undisturbed savanna. Compared to savanna background fluxes, it was found that GHG flux rates from bomas were elevated by several orders of magnitude, with mean fluxes of 487 ± 8 mg CO2-C m−2 h−1, 325 ± 11 µg N2O-N m−2 h−1, and 3245 ± 234 µg CH4-C m−2 h−1 for active bomas, and 167 ± 52 mg CO2-C m−2 h−1, 610 ± 186 µg N2O-N m−2 h−1, and 3127 ± 1262 µg CH4-C m−2 h−1 for inactive bomas, while surrounding savanna soils only emitted 22.3 ± 18.2 mg CO2-C m−2 h−1, 2.5 ± 2.2 µg N2O-N m−2 h−1, and 0.1 ± 0.7 µg CH4-C m−2 h−1. Assuming that bomas are used for 45 days per year, annual manure emission factors were 2.43 ± 0.42%N for N2O and 0.49 ± 0.07%C for CH4, which corresponds to 2.64 ± 0.37 g CH4 kg−1 volatile solids (VS). These emission factors were similar to IPCC default values for feedlots for low-producing cattle in warm climates; however, the IPCC only considers emissions in year when bomas are in use and does not account for emissions following boma abandonment. At the farm scale, boma manure contributed little (2.2%) to total CH4 emissions, which were dominated by enteric CH4 emissions (97.6%); but bomas were a substantial source for N2O, contributing over 32% to total N2O emissions on the farm. This calls for the inclusion of active and inactive bomas in the activity data collection for national GHG inventories, as bomas are currently overlooked hotspots for GHG emissions that are not represented in the GHG budgets of African nations. To mitigate GHG emissions, manure should be removed regularly and used as fertilizer to return nutrients to the grassland, preventing nutrient mining and ensuring long-term rangeland productivity and resilience, or it might be used to grow crops and livestock feeds.

Using remote sensing to map degraded mountain peatlands with high climate mitigation potential in Colombia's Central Cordillera

Peatlands are the most carbon-dense ecosystems on earth. In tropical mountains, peatlands are numerous and susceptible to rapid degradation and carbon loss after human disturbances. Quantifying where peatlands are located and how they are affected by land use is key in creating a baseline of carbon stocks and greenhouse gas fluxes from tropical mountain peatlands. However, mapping peatlands in the páramo of the Northern Andes is difficult because they are in a topographically complex environment with nearly continuous cloud cover and frequent conversion to pastures or cropland. The goal of this effort was to identify the different types of páramo peatlands and their degradation patterns in the Colombian Central Cordillera. Moderate resolution cloud-free composites of optical imagery, temporal variance in ALOS- PALSAR L-band SAR, Sentinel-1 C-band SAR, and topography data were used as inputs in a machine learning classifier to identify was used to map 12 land cover classes including peatlands with natural vegetation and peatlands converted to pasture. Field data from 507 control points collected across the study area, including information on the vegetation and carbon content on the top 20 cm of the soil, were used to train and validate the classifier. Results show that the use of multiple platforms and image dates, including variance of the radar returns, is necessary for a clear separation of disturbed and undisturbed peatland classes. Peatland area varied across the study region, covering 7% and 20% of the landscape in the northern and southern portions of the study area, respectively. Disturbed peatlands with exotic grasses cover nearly 2% of the area. The overall accuracy of the peatland classes was 82.6%. Disturbed peatlands with exotic grasses had less carbon in the top 20 cm than undisturbed peatlands with natural vegetation. These results highlight the prevalence of peatlands in the tropical Andes and a promising approach to detecting peatlands converted to agriculture. Understanding the distribution and extent of these carbon dense ecosystems can facilitate the restoration and protection of peatlands in the northern Andes, with implications for the future trajectories of the national greenhouse gas inventory.

Dietary Concentrate Supplementation Increases Milk Production and Reduces Predicted Greenhouse Gas Emissions Intensity in Pasture-based Commercial Dairy Farms

Controlled studies have extensively documented that concentrate supplements typically increase enteric methane (CH4) emissions and milk yield and reduce emissions per unit of milk produced and dry matter intake. However, there have been no studies conducted to determine the effect of concentrate on predicted greenhouse gas emissions from dairy farms representing the Australian pasture-based farming system. Thus, this study sought to determine how dietary concentrate supplementation affects enteric and manure CH4, and N2O of Australian pasture-based dairy farms. The Australian Dairy Carbon Calculator was used, which incorporates emission factors and methodologies used in the National Greenhouse Gas Inventory as reported to the International Panel on Climate Change. Primary data were collected and analyzed from 120 commercial farms in Australia's major dairy regions. Then the farms were divided into 4 groups based on their dietary concentrate supplementation: ≤ 1 (low; 15 farms), 1-2 (moderate;35 farms), 2-3 (high; 35 farms), and ≥ 3 (very high; 35 farms) ton (t) of concentrate dry matter per cow per year. Sources of greenhouse gas emissions were CO2 from concentrate production, enteric CH4, and manure CH4 and N2O. Total dry matter intake, milk yield, and daily enteric CH4 production (g/day) quadratically increased with concentrate level, whereas greenhouse gas emission intensity of milk production (kg CO2eq/kg fat and protein corrected milk) decreased by 14% for farms supplementing with ≥ 3 tDM/cow per year compared with those supplementing with ≤ 1 tDM/cow per year of dietary concentrate. The emissions of N2O and CH4 from manure increased quadratically and linearly, respectively, with the increasing supplementation of concentrate. Farms supplementing 2-3 tDM/cow per year showed substantial increases in gross income, gross margin, earnings before interest and tax, and net income ($/cow/year) compared with those supplementing of ≤ 1, 1-2, and ≥ 3 tDM/cow per year. In conclusion, increasing dietary concentrate supplementation for dairy cows resulted in increased milk production per cow, reduced greenhouse gas emissions per unit of milk produced, and increased income and profit. However, a comprehensive life cycle assessment study is needed to account for carbon sequestration by other farm components such as pastures and trees, which were not considered in the present study. In addition, the present study was based on modeling and did not gather ground truth information for DMI, digestibility, crude protein, and urinary and fecal N excretion. Therefore, data should be interpreted with caution, and studies gathering such information are encouraged.

IMPACT OF GREEN CAMPUS TRANSPORTATION PROGRAMS ON EMISSION REDUCTION TARGET 2030

The effects of climate change on the environment, human health, and economy are significant. Global warming and climate change are primarily caused by emissions of greenhouse gases, especially carbon dioxide. In response, Sebelas Maret University, an Indonesian higher education institution located in Surakarta, Central Java, established the Emission-Free Day, held on the first Friday of every month beginning in July 2020. This study aims to evaluate the efficiency of the Emission-Free Day in achieving 2030 emission reduction goals. This study analyzes the effect of the Emission-Free Day on reducing emissions from motorized vehicles on college campuses. The Tier-1 method, applying emission factors from the Guidelines for National Greenhouse Gas Inventory published in 2006 by the Intergovernmental Panel on Climate Change (IPCC), was used to estimate the emission reduction. The findings indicate that while the Zero Emissions Program aligns with the Sebelas Maret University Green Campus Policy, its contribution to the 2030 emission reduction targets specified in the Nationally Determined Contribution (NDC) is negligible. Additional measures are required to enhance emission reduction efforts, such as the establishment of a Centralized Parking Facility, the implementation of an RFID card system to restrict vehicle access to the campus, the introduction of a ridesharing program, the provision of employee shuttle services, and the promotion of the use of public transportation. These attempts will support global emission reduction efforts and significantly contribute to achieving NDC targets. The study emphasizes the significance of instituting a variety of complementary programs to effectively combat emissions from motorized vehicles and promote a sustainable and low-carbon campus environment.

Pantropical CO2 emissions and removals for the AFOLU sector in the period 1990–2018

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.

A fuzzy logic evaluation of synergies and trade-offs between agricultural production and climate change mitigation

This study introduces a trade-off evaluation system, the Σommit index, which considers four components: crop yield, soil carbon stock changes, direct and indirect nitrous oxide emissions, and nitrate-nitrogen leaching across alternative agronomic case scenarios, i.e., combinations of management practices within specific pedo-climatic conditions. The four trade-off components have been estimated by combining standard equations and emission factors from the Guidelines for National Greenhouse Gas Inventories, complemented with Grey Water Footprint accounting Guidelines and other meta-analyses. The Σommit index has been developed using a harmonised dataset of ∼1.8 million agronomic case scenarios, leveraging fuzzy logic to aggregate the trade-off components into a value ranging from 0 (bad) to 1 (good). It has been tested under three narratives reflecting stakeholders' sustainability priorities (young farmers, agrochemical companies, EU Common Agricultural Policy paying agency), using alternative weighting schemes derived from expert opinion. Adding organic matter input, intermediate N fertilisation (50–150 kg ha−1), no-tillage, winter cereal cultivation, and irrigation for summer cereals have consistently achieved higher performance across all narratives. When assigning a higher weight to soil carbon stock changes, a broader range of Σommit index values emerged, while assigning higher importance to crop yield has led to a narrower evaluation. We openly release the dataset of agronomic case scenarios, along with the scripts to replicate the methodology and an interactive dashboard to inspect the results. These resources are meant to be used by different stakeholders (e.g., policymakers, Common Agricultural Policy payment agencies, farms, agrochemical industry) as a complement to the Intergovernmental Panel on Climate Change methodology to improve current understanding and awareness of environmental trade-offs and synergies in agricultural management.

Impact of Land-Use Changes on Climate Change Mitigation Goals: The Case of Lithuania

The land-use, land-use change and forestry (LULUCF) sector is receiving increasing attention in climate change mitigation and greenhouse gas (GHG) emission offsetting. The sector itself and measures applied to mobilize this sector in order to tackle climate change are dominant in nationally determined contributions under the Paris Agreement as well as in national strategies, as in the case of Lithuania. Lithuania has set the goal of becoming a carbon-neutral country in 2050, reducing GHGs by 80% compared to 1990 and offsetting the remaining 20% through the LULUCF sector. Therefore, this paper aims at analyzing historical land-use changes in 1990–2021, as reported for the United Nations Framework Convention on Climate Change (UNFCCC) secretariat, and LULUCF’s potential to achieve climate change mitigation goals, taking into account different land-use change scenarios (business as usual, forest development, forest development + additional measures and forest land 40% + additional measures) for 2030 and 2050 in Lithuania. The scenarios are based on historical and potential future policy-based land-use changes. Projections of GHG emissions/removals for different scenarios are prepared according to the Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (2006) by the Intergovernmental Panel on Climate Change (IPCC). The results indicate that land-use changes over the period 1990–2021 remained rather stable, with some increases in forest area and grassland at the expense of cropland. The whole LULUCF sector acted as a carbon sink in most cases, forests being a key category for removal. However, reaching climate neutrality in 2050 might be challenging, as the goal to offset 20% of remaining GHG emission compared to 1990 through LULUCF would not be met in any of the scenarios analyzed, even the scenario of maximal forest-area development and additional measures. Considering the high historical GHG-removal fluctuations and the uncertainties of the sector itself, caution should be taken when relying on LULUCF’s potential to reach the set goals.

Nitrous Oxide Emissions during Cultivation and Fallow Periods from Rice Paddy Soil under Urea Fertilization

Rice cultivation serves as a significant anthropogenic source of methane (CH4) and nitrous oxide (N2O). Although N2O emissions remain relatively small compared to CH4 emissions, they are remarkably affected by nitrogen-fertilized soil conditions during rice cultivation. While numerous studies have investigated nitrous oxide emissions in response to nitrogen fertilization, existing research assessing nitrous oxide emissions based on nitrogen fertilizer levels has often been limited to cultivation periods. Therefore, there is a need for comprehensive analyses covering the entire year, including the dry periods, to address nitrous oxide emissions as an important source throughout the entire agricultural cycle. In this case study, we investigated the characteristics of N2O emissions in a central region of South Korea, where a single rice-cropping cycle occurs annually over a span of three whole years, from May 2020 to May 2023. We investigated the impact of variations in temperature and soil moisture on N2O emissions during rice cultivation and fallow periods. In this context, we attempted to discover the complex dynamics of N2O emissions by comparing longer fallow periods with the rice cultivation periods and extended non-dry periods with irrigated periods. We discovered that the greater contribution of cumulative N2O emissions during the fallow period made a much greater contribution (up to approximately 90%) to the whole-year N2O emissions than those during the rice cultivation period. During the fallow period from rice harvest to rice planting in the following year, variations in N2O emissions were associated with high-flux events after rainy periods on dry soils. This highlights the considerable influence of soil moisture content and weather conditions on N2O emissions during the fallow period. This affects high emission events, which in turn significantly impact the cumulative emissions over the entire period. We underscore that assessing N2O emissions solely based on the rice cultivation period would underestimate annual emissions. To prevent underestimation of N2O emissions, periodic gas collection throughout a year covering both rice cultivation and fallow phases is required in alignment with the monitoring of different temperature and soil moisture conditions. We captured statistical differences in cumulative N2O emissions due to nitrogen fertilization treatments across the three years. However, no significant difference was observed in the three-year average emissions among the different (one, one-and-a-half, and double) nitrogen fertilization treatments, with the exception of the control treatment (no fertilization). Based on the findings, we recommend at least three whole-year evaluations to ensure the estimation accuracy of N2O emissions under different nitrogen fertilization conditions. The findings from this study could help prepare the further revision or refinement of N2O emission factors from rice cultivation in the national greenhouse gas inventories defined by the inter-governmental panel on climate change (IPCC).

Carbon Dioxide Uptake Estimation for Spanish Cement-Based Materials.

The Intergovernmental Panel on Climate Change (IPCC), which is the United Nations body for assessing the science related to climate change, has recently recognized the natural carbonation process as a way of carbon offsetting with mortar and concrete. Accordingly, this activity could be recognized as a carbon removal process for which certification should be granted. The aim of the certification of carbon removal is to promote the development of adequate and efficient new carbon removal processes. Therefore, the main objective of this study is to provide reliable results on carbon dioxide uptake by cement-based materials in Spain. Yearly, greenhouse gas emissions are reported to the United Nations Framework Convention on Climate Change (UNFCCC) by each country, and the natural carbonation should be added up to the carbon accounting. Therefore, natural carbonation should be included in the IPCC Guidelines for National Greenhouse Gas Inventories, and such accounting information should be made available promptly to the national regulatory authorities. This paper provides the results of carbon dioxide uptake by Spanish cement-based materials from 1990 to 2020 by using an easy method of estimating the net carbon dioxide emissions (simplified method) considering the carbon dioxide released by the calcination during clinker production (process emissions). The outcome of this study reveals that there was 93,556,000 tons of carbon dioxide uptake by the mortar and concrete manufactured in Spain from 1990 to 2020.

High emissions or carbon neutral? Inclusion of “anthropogenic” forest sinks leads to underreporting of forestry emissions

Recent research has shown forest-related emissions reported in national greenhouse gas inventories are much lower than global estimates from models summarized in Intergovernmental Panel on Climate Change reports. A substantial part of this discrepancy could be explained by conceptual differences in what is counted as part of the anthropogenic forest carbon sink and the way countries report on their forest harvesting sectors. With Canada as a case study, we used published National Inventory Report and Common Reporting Format tables to isolate emissions and removals directly associated with forestry from those associated with forests more broadly. Forestry-related factors that affect CO2 emissions and removals include tree harvesting, post-harvest forest regeneration and growth, and carbon storage in long-lived harvested wood products. We found that between 2005 and 2021, forestry in Canada represented a net source of carbon (annual mean = 90.8 Mt. CO2e), and that total area logged was a significant predictor of net forestry emissions. In contrast, Canada’s NIR reported a small net carbon sink during the same time period (annual mean = −4.7 Mt. CO2e). We show this discrepancy can be explained by Canada’s GHG reporting approach that claims GHG emissions from wildfires are natural, but GHG removals from forests at the age of commercial maturity, despite being primarily natural disturbance origin, are anthropogenic. This reporting approach may lead to climate mitigation policies that are ineffectual or detrimental to reducing net carbon in the global atmosphere.

A comparison of Tier 1, 2, and 3 methods for quantifying nitrous oxide emissions from soils amended with biosolids

Municipal biosolids are a nitrogen (N)-rich agricultural fertilizer which may emit nitrous oxide (N2O) after rainfall events. Due to sparse empirical data, there is a lack of biosolids-specific N2O emission factors to determine how land-applied biosolids contribute to the national greenhouse gas inventory. This study estimated N2O emissions from biosolids-amended land in Canada using Tier 1, Tier 2 (Canadian), and Tier 3 (Denitrification and Decomposition model [DNDC]) methodologies recommended by the Intergovernmental Panel on Climate Change (IPCC). Field data was from replicated plots at 8 site-years between 2017 and 2019 in the provinces of Quebec, Nova Scotia and Alberta, Canada, representing three distinct ecozones. Municipal biosolids were the major N source for the crop, applied as mesophilic anaerobically digested biosolids, composted biosolids, or alkaline-stabilized biosolids alone or combined with an equal amount of urea-N fertilizer to meet the crop N requirements. Fluxes of N2O were measured during the growing season with manual chambers and compared to N2O emissions estimated using the IPCC methods. In all site-years, the mean emission of N2O in the growing season was greater with digested biosolids than other biosolids sources or urea fertilizer alone. The emissions of N2O in the growing season were similar with composted or alkaline-stabilized biosolids, and no greater than the unfertilized control. The best estimates of N2O emissions, relative to measured values, were with the Tier 3 > adapted Tier 2 with biosolids-specific correction factors > standard Tier 2 = Tier 1 methods of the IPCC, according to the root mean square error statistic. The Tier 3 IPCC method was the best estimator of N2O emissions in the Canadian ecozones evaluated in this study. These results will be used to improve methods for estimating N2O emissions from agricultural soils amended with biosolids and to generate more accurate GHG inventories.

A Greenhouse Gas Budget for Mexico During 2000–2019

AbstractApplication of the best available science to improve quantification of greenhouse gas (GHG) emissions at regional and national scales is key to climate action. Here, we present a two‐decade (2000–2019) GHG (CO2, CH4, and N2O) budget for Mexico derived from multiple products. Data from the National GHG Inventory, global observations, and the scientific literature were compared to identify knowledge gaps on GHG flux dynamics and discrepancies among estimates. Total mean annual GHG emissions were estimated at 695–910 TgCO2‐eq year−1 over these two decades, with 70% of the emissions attributable to CO2, 23% to CH4, and 5% to N2O (2% to other gases). When divided by sectors, we found agreement across emission estimates from various sources for fossil fuels, cattle, agriculture, and waste for all GHGs. However, considerable discrepancies were identified in the fluxes from terrestrial ecosystems. The disagreement was particularly large for the land CO2 sink, where net biome production estimations from the national inventory were double those from any other observational product. Extensive knowledge gaps exist, mainly related to aquatic systems (e.g., outgassing in rivers) and the lateral fluxes (e.g., wood trade). In addition, limited information is available on CH4 emissions from wetlands and soil CH4 consumption. We expect these results to guide future research to reduce estimation uncertainties and fill the information gaps across Mexico.

Using Atmospheric Inverse Modelling of Methane Budgets with Copernicus Land Water and Wetness Data to Detect Land Use-Related Emissions

Climate change mitigation requires countries to report their annual greenhouse gas (GHG) emissions and sinks, including those from land use, land use change, and forestry (LULUCF). In Finland, the LULUCF sector plays a crucial role in achieving net-zero GHG emissions, as the sector is expected to be a net sink. However, accurate estimates of LULUCF-related GHG emissions, such as methane (CH4), remain challenging. We estimated LULUCF-related CH4 emissions in Finland in 2013–2020 by combining national land cover and remote-sensed surface wetness data with CH4 emissions estimated by an inversion model. According to our inversion model, most of Finland’s CH4 emissions were attributed to natural sources such as open pristine peatlands. However, our research indicated that forests with thin tree cover surrounding open peatlands may also be a significant source of CH4. Unlike open pristine peatlands and pristine peatlands with thin tree cover, surrounding transient forests are included in the Finnish GHG inventory if they meet the criteria used for forest land. The current Finnish national GHG inventory may therefore underestimate CH4 emissions from forested organic soils surrounding open peatlands, although more precise methods and data are needed to verify this. Given the potential impact on net GHG emissions, CH4 emissions from transitional forests on organic soils should be further investigated. Furthermore, the results demonstrate the potential of combining atmospheric inversion modelling of GHGs with diverse data sources and highlight the need for methods to more easily combine atmospheric inversions with national GHG inventories.