Greenhouse gas emissions in the state of Morelos, Mexico: A first approximation for establishing mitigation strategies

The European Union (EU) has proposed legislative revisions to achieve climate neutrality in EU by 2050. The Land Use, Land-Use Change and Forestry (LULUCF) Regulation, adopted in 2018, is being revised to ensure that accounted greenhouse gas (GHG) emissions from LULUCF are balanced by equivalent accounted removals of carbon dioxide (CO2) from the atmosphere. This study focuses on the impact of targeted tree introduction in agricultural land in Latvia, specifically afforestation of drained organic soil and implementation of agroforestry systems (riparian buffer strips), on national GHG reduction targets for the LULUCF sector. The potential contributions of selected measures were evaluated using evaluation methods including GHG emissions factors based on the Intergovernmental Panel on Climate Change (IPCC) guidelines and recent scientific studies. The study differentiated between different land use categories by GHG emissions from soil and CO2 removals in living biomass, dead wood, litter, mineral soil, and organic soil. Basic scenarios were compared with additional scenarios that included afforestation of drained organic soils and implementation of agroforestry systems. The study analysed the possibilities of achieving LULUCF sector goals for 2030, 2035, and 2050 with the selected scenarios. According to the basic scenarios, the LULUCF sector has been a continuous source of GHG emissions since 2019, partly compensated by forest management by 2040, but after 2040 forest management becomes a source of GHG emissions as well. The study shows that afforestation of organic soils currently used for agricultural production can reduce GHG emissions and ensure the achievement of national LULUCF targets for 2021-2025, with a significant decrease in GHG emissions by 3.9 million t CO2 eq. during the 2021-2025 period if compared to the basic scenario. However, the study finds that national target of net GHG removals is not achieved for 2026-2030 according to both basic and afforestation scenarios if no additional measures, e.g., establishment of the shelter belts, are implemented.

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).

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. .

Forecasting of Turkey's greenhouse gas emissions using linear and nonlinear rolling metabolic grey model based on optimization

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Abstract. To track progress towards keeping global warming well below 2 ∘C or even 1.5 ∘C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO2 emissions, CH4 emissions, N2O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF6, NF3) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (∼ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO2 eq. consisting of CO2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO2, CO2-LULUCF 5.7 ± 4.0 GtCO2, CH4 10 ± 3.1 GtCO2 eq., N2O 2.6 ± 1.6 GtCO2 eq., and F-gases 1.3 ± 0.40 GtCO2 eq. Initial estimates suggest further growth of 1.3 GtCO2 eq. in GHG emissions to reach 59 ± 6.6 GtCO2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr−1) compared to 2000–2009 (2.4 % yr−1), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

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.

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

This paper presents plans and efforts on European Union (EU) Member States (MSs) (including Norway and Iceland)-specific support for monitoring emissions and removals from land use, land use change and forestry (LULUCF) which are built on existing and forthcoming Copernicus data and services. Land use and change between land uses are mapped using at top level and appropriate sub-categories in accordance to the current the Intergovernmental Panel on Climate Change (IPCC) guidelines to allow MSs to calculate the greenhouse gas (GHG) emissions and removals. We discuss findings on (1) technical needs in Member State (MS) for meeting technical requirements of reporting the GHG emissions and removals, (2) definition and implementation of improved national and pan-European methodologies and technical solutions such as tools or software or integrated data sets meeting the needs of the LULUCF regulation including the calculation of carbon stock change and the GHG emissions and removals and (3) training and workshops for the relevant services in MSs.

Abstract. A key goal of the Paris Agreement (PA) is to reach net-zero greenhouse gas (GHG) emissions by 2050 globally, which requires mitigation efforts from all countries. Africa's rapidly growing population and gross domestic product (GDP) make this continent important for GHG emission trends. In this paper, we study the emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in Africa over 3 decades (1990–2018). We compare bottom-up (BU) approaches, including United Nations Convention Framework on Climate Change (UNFCCC) national inventories, FAO, PRIMAP-hist, process-based ecosystem models for CO2 fluxes in the land use, land use change and forestry (LULUCF) sector and global atmospheric inversions. For inversions, we applied different methods to separate anthropogenic CH4 emissions. The BU inventories show that, over the decade 2010–2018, fewer than 10 countries represented more than 75 % of African fossil CO2 emissions. With a mean of 1373 Mt CO2 yr−1, total African fossil CO2 emissions over 2010–2018 represent only 4 % of global fossil emissions. However, these emissions grew by +34 % from 1990–1999 to 2000–2009 and by +31 % from 2000–2009 to 2010–2018, which represents more than a doubling in 30 years. This growth rate is more than 2 times faster than the global growth rate of fossil CO2 emissions. The anthropogenic emissions of CH4 grew by 5 % from 1990–1999 to 2000–2009 and by 14.8 % from 2000–2009 to 2010–2018. The N2O emissions grew by 19.5 % from 1990–1999 to 2000–2009 and by 20.8 % from 2000–2009 to 2010–2018. When using the mean of the estimates from UNFCCC reports (including the land use sector) with corrections from outliers, Africa was a mean source of greenhouse gases of 262221863239 Mt CO2 eq. yr−1 from all BU estimates (the subscript and superscript indicate min–max range uncertainties) and of +263717615873 Mt CO2 eq. yr−1 from top-down (TD) methods during their overlap period from 2001 to 2017. Although the mean values are consistent, the range of TD estimates is larger than the one of the BU estimates, indicating that sparse atmospheric observations and transport model errors do not allow us to use inversions to reduce the uncertainty in BU estimates. The main source of uncertainty comes from CO2 fluxes in the LULUCF sector, for which the spread across inversions is larger than 50 %, especially in central Africa. Moreover, estimates from national UNFCCC communications differ widely depending on whether the large sinks in a few countries are corrected to more plausible values using more recent national sources following the methodology of Grassi et al. (2022). The medians of CH4 emissions from inversions based on satellite retrievals and surface station networks are consistent with each other within 2 % at the continental scale. The inversion ensemble also provides consistent estimates of anthropogenic CH4 emissions with BU inventories such as PRIMAP-hist. For N2O, inversions systematically show higher emissions than inventories, on average about 4.5 times more than PRIMAP-hist, either because natural N2O sources cannot be separated accurately from anthropogenic ones in inversions or because BU estimates ignore indirect emissions and underestimate emission factors. Future improvements can be expected thanks to a denser network of monitoring atmospheric concentrations. This study helps to introduce methods to enhance the scope of use of various published datasets and allows us to compute budgets thanks to recombinations of those data products. Our results allow us to understand uncertainty and trends in emissions and removals in a region of the world where few observations exist and where most inventories are based on default IPCC guideline values. The results can therefore serve as a support tool for the Global Stocktake (GST) of the Paris Agreement. The referenced datasets related to the figures are available at https://doi.org/10.5281/zenodo.7347077 (Mostefaoui et al., 2022).

 A key goal of the Paris Agreement (PA) is to reach net-zero greenhouse gas (GHG) emissions by 2050 globally, which requires mitigation efforts from all countries. Africa’s rapidly growing population and gross domestic product (GDP) make this continent important for GHG emission trends. In this project we study the emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in Africa over 3 decades. We compare bottom-up (BU) approaches, including United Nations Convention Framework on Climate Change (UNFCCC) national inventories, FAO, PRIMAP-hist, process-based ecosystem models for CO2 fluxes in the land use, land use change and forestry (LULUCF) sector and global atmospheric inversions. For inversions, we applied different methods to separate anthropogenic CH4 emissions. The BU inventories show that, over the decade 2010–2018, fewer than 10 countries represented more than 75 % of African fossil CO2 emissions. With a mean of 1373 Mt CO2 yr−1, total African fossil CO2 emissions over 2010–2018 represent only 4 % of global fossil emissions. However, these emissions grew by +34% from 1990–1999 to 2000–2009 and by +31% from 2000–2009 to 2010–2018, which represents more than a doubling in 30 years. This growth rate is more than 2 times faster than the global growth rate of fossil CO2 emissions. The anthropogenic emissions of CH4 grew by 5 % from 1990–1999 to 2000–2009 and by 14.8 % from 2000–2009 to 2010–2018. The N2O emissions grew by 19.5 % from 1990–1999 to 2000–2009 and by 20.8 % from 2000–2009 to 2010–2018. When using the mean of the estimates from UNFCCC reports (including the land use sector) with corrections from outliers, Africa was a mean source of greenhouse gases of 2622 (min: 2186, max: 3239) Mt CO2 eq. yr−1 from all BU estimates (the min–max  indicate range uncertainties) and of +2637 (min: 1761, max: 5873) Mt CO2 eq. yr−1 from top-down (TD) methods during their overlap period from 2001 to 2017. Although the mean values are consistent, the range of TD estimates is larger than the one of the BU estimates, indicating that sparse atmospheric observations and transport model errors do not allow us to use inversions to reduce the uncertainty in BU estimates. The main source of uncertainty comes from CO2 fluxes in the LULUCF sector, for which the spread across inversions is larger than 50 %, especially in central Africa. Moreover, estimates from national UNFCCC communications differ widely depending on whether the large sinks in a few countries are corrected to more plausible values using more recent national sources following the methodology of Grassi et al. (2022). The medians of CH4 emissions from inversions based on satellite retrievals and surface station networks are consistent with each other within 2 % at the continental scale. The inversion ensemble also provides consistent estimates of anthropogenic CH4 emissions with BU inventories such as PRIMAP-hist. For N2O, inversions systematically show higher emissions than inventories, either because natural N2O sources cannot be separated accurately from anthropogenic ones in inversions or because BU estimates ignore indirect emissions and underestimate emission factors. 

Accurate estimation of national greenhouse gas (GHG) emissions is very important for mitigation action of climate change. The IPCC (Intergovernmental Panel on Climate Change) guidelines have been used for calculating emissions from the energy, industrial processes, agriculture, and LULUCF (Land Use, Land-Use Change and Forestry), and waste sectors in national country. Assessment of national GHG emissions from the agriculture sector has been conducted using the 2000 Good Practice Guidance and 2006 IPCC Guidelines. In 2019, refined guidelines, such as the 2019 Refinement to the 2006 IPCC Guidelines were published. We conducted to this study to investigate application of the new guidelines which including calculation equation, emission factor, fractions and so on to compare of the old one.<BR> Some emission factors and fractions were changed to disaggregated ones considering climate zone and fertilizer type. Also, the default cultivation period of rice was provided for the fist time in the guideline and that was 112 days in the East Asia region. The nitrous oxide emission factor for flooded rice fields was changed from 0.003 to 0.005 kg N₂O-N (kg N)<SUP>-1</SUP> when applied to single and multiple drainage of rice paddies. In addition to fraction of N loss through leaching and runoff, fraction of synthetic fertilizer N and organic N fertilizer that volatilize as NH₃ and NO<SUB>x</SUB> were changed. When the changed parameters including emission factors, were applied to estimation of national GHG inventory of the agricultural sector, total emissions were reduced by 1,132 Gg CO₂-eq.

Abstract. While the Emissions Database for Global Atmospheric Research (EDGAR) focuses on global estimates for the full set of anthropogenic activities, the Land Use, Land-Use Change and Forestry (LULUCF) sector might be the most diverse and most challenging to cover consistently for all countries of the world. Parties to United Nations Framework Convention on Climate Change (UNFCCC) are required to provide periodic estimates of greenhouse gas (GHG) emissions, following the latest approved methodological guidance by the International Panel on Climate Change (IPCC). The current study aims to consistently estimate the carbon (C) stock changes from living forest biomass for all countries of the world, in order to complete the LULUCF sector in EDGAR. In order to derive comparable estimates for developing and developed countries, it is crucial to use a single methodology with global applicability. Data for developing countries are generally poor, such that only the Tier 1 methods from either the IPCC Good Practice Guide for Land Use, Land-Use Change and Forestry (GPG-LULUCF) 2003 or the IPCC 2006 Guidelines can be applied to these countries. For this purpose, we applied the IPCC Tier 1 method at global level following both IPCC GPG-LULUCF 2003 and IPCC 2006, using spatially coarse activity data (i.e. area, obtained combining two different global forest maps: the Global Land Cover map and the eco-zones subdivision of the Global Ecological Zone (GEZ) map) in combination with the IPCC default C stocks and C stock change factors. Results for the C stock changes were calculated separately for gains, harvest, fires (Global Fire Emissions Database version 3, GFEDv.3) and net deforestation for the years 1990, 2000, 2005 and 2010. At the global level, results obtained with the two sets of IPCC guidance differed by about 40 %, due to different assumptions and default factors. The IPCC Tier 1 method unavoidably introduced high uncertainties due to the "globalization" of parameters. When the results using IPCC 2006 for Annex I Parties are compared to other international datasets such as (UNFCCC, Food and Agriculture Organization of the United Nations (FAO)) or scientific publications, a significant overestimation of the sink emerges. For developing countries, we conclude that C stock change in forest remaining forest can hardly be estimated with the Tier 1 method especially for calculating the C losses, mainly because wood removal data are not separately available on harvesting or deforestation. Overall, confronting the IPCC GPG-LULUCF 2003 and IPCC 2006 methodologies, we conclude that IPCC 2006 suits best the needs of EDGAR and provide a consistent global picture of C stock changes from living forest biomass independent of country estimates.

In a rare empirical approach, and considering the uniqueness of the Nordic economy, this study examines the differential effect of domestic material utilization, i.e., biomass, fossil fuel, metallic ores, and non-metallic ores on the sectoral greenhouse gas (GHG) emission, i.e., industrial, agricultural, land use, land use change and forestry (LULCF), waste management, and energy GHG emissions in the period 1990–2020. By applying competent econometric tools that accounts for potential estimation bias, the result revealed that metallic ore consumption among the Nordic countries is detrimental to the region’s environmental sustainability, more so to the region’s greening circular economy drive. This is because metallic ore utilization spurs industrial, agricultural, LULCF, waste management, and energy GHG emissions. Similarly, biomass material consumption spurs GHG emissions arising from the LULCF, waste management, and energy sector activities while fossil fuel materials spur LULCF and energy GHG emissions. However, non-metallic ores consumption provides a desirable outcome as it mitigates GHG emission with respective elasticities of ~0.06, ~0.01, and ~0.05, in the industrial, agricultural, and waste management sector activities while biomass also plays a statistically significant role of reducing agricultural GHG emission by ~0.02% when there is a percent increase in the consumption of biomass. Important policy measures are put forward following the interesting revelation from the investigation.

Pemanasan global telah menyita perhatian dunia bahkan akan semakin bertambah besar dimasa yang akan datang mengingat akibat yang ditimbulkannya UNO, melalui program lingkungan UNEP (United Nations Environment Programme) dan Organisasi Meteorologi Dunia (World Meteorological Organization, WMO) membentuk The Intergovernmental Panel on Climate Change (IPCC) pada 1988 untuk meneliti dan menganalisa isu-isu ilmu pengetahuan yang muncul. Makalah ini akan membahas tentang emisi GRK dari empat industri yaitu baja, aluminium, semen dan kimia.Guna mengantisipasi meningkatnya emisi GRK maka keempat industri ini perlu melakukan kerjasama. Model kerjasama apa yang paling tepat juga akan dibahas pada makalah ini.Selanjutnya alternatif solusi yang bisa. Ada beberapa emisi GRK dari sektor industri, mulai dari industri kimia, baja, semen dan alumunium. Dalam Protocol Kyoto, tersedia tiga mekanisme fleksibel dalam upaya pencapaian target penurunan emisi GRK, yaitu Emissions Trading (ET) atau perdagangan emisi antar negara maju, Joint Implementation (JI) atau pelaksanaan penurunan emisi secara bersama sama antar negara maju, dan Clean Development Mechanism (CDM) atau kerjasama antara negara maju dan negara berkembang. Studi ini menyimpulkan bahwa salah satu cara yang strategis untuk melindungi atmosfir adalah dengan cara mengontrol penggunaan sumber daya alam melalui emisi GRK.