Reply on RC1

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).

In order to achieve target greenhouse gas (GHG) emissions, such as those proposed by each country by nationally determined contributions (NDCs), GHG emission projections are receiving attention around the world. Generally, integrated assessment models (IAMs) are used to estimate future GHG emissions considering both economic structure and final energy consumption. However, these models usually do not consider the entire supply chain, because of differences in the aims of application. In contrast, life cycle assessment (LCA) considers the entire supply chain but does not cover future environmental impacts. Therefore, this study aims to evaluate the national carbon footprint projection in Japan based on life cycle thinking and IAMs, using the advantages of each. A future input–output table was developed using the Asia-Pacific integrated model (AIM)/computable general equilibrium (CGE) model (Japan) developed by the National Institute for Environmental Studies (NIES). In this study, we collected the fundamental data using LCA databases and estimated future GHG emissions based on production-based and consumption-based approaches considering supply chains among industrial sectors. We targeted fiscal year (FY) 2030 because the Japanese government set a goal for GHG emissions in 2030 in its NDC report. Accordingly, we set three scenarios: FY2005 (business as usual (BAU)), FY2030 (BAU), and FY2030 (NDC). As a result, the carbon footprint (CFP) in FY2030 will be approximately 1097 megatons of carbon dioxide equivalent (MtCO2eq), which is 28.5% lower than in FY2005. The main driver of this reduction is a shift in energy use, such as the introduction of renewable energy. According to the results, the CFP from the consumption side, fuel combustion in the use stage, transport and postal services, and electricity influence the total CFP, while results of the production side showed the CFP of the energy and material sectors, such as iron and steel and transport, will have an impact on the total CFP. Moreover, carbon productivity will gradually increase and FY2030 (NDC) carbon productivity will be higher than the other two cases.

BackgroundThe Nationally Determined Contribution (NDC) of Thailand intends to reduce greenhouse gas (GHG) emissions by 20 to 25% from the projected business as usual level by 2030 with the deployment of renewable energy technologies and energy efficiency improvement measures in both the supply and demand sectors. However, in order to contribute towards meeting the long-term goal of the Paris Agreement to stay well below 2 °C, ambitious mitigation efforts beyond 2030 are needed. As such, it is necessary to assess the effects of imposing more stringent long-term GHG reduction targets in Thailand beyond the NDC commitment.MethodsThis paper analyses the macroeconomic effects of limiting the GHG emissions by using a computable general equilibrium (CGE) model on Thailand’s economy during 2010 to 2050. Besides the business as usual (BAU) scenario, this study assesses the macroeconomic effects of ten low to medium GHG mitigation scenarios under varying GHG reduction targets of 20 to 50%. In addition, this study also assesses three different peak emission scenarios, each targeting a GHG reduction of up to 90% by 2050, to analyze the feasibility of zero GHG emissions in Thailand to pursue efforts to hold the global temperature rise to 1.5 °C above pre-industrial levels, as considered in the Paris Agreement.ResultsAccording to the BAU scenario, the GHG emissions from the electricity, industry, and transport sectors would remain the most prominent throughout the planning period. The modeling results indicate that the medium to peak emission reduction scenarios could result in a serious GDP loss compared to the BAU scenario, and therefore, the attainment of such mitigation targets could be very challenging for Thailand. Results suggest that the development and deployment of energy-efficient and renewable energy-based technologies would play a significant role not only in minimizing the GHG emissions but also for overcoming the macroeconomic loss and lowering the price of GHG emissions.ConclusionsThe results reveal that without a transformative change in the economic structure and energy system of Thailand, the country would have to face enormous cost in reducing its GHG emissions.

Although Africa contributes less than 5% to global greenhouse gas (GHG) emissions, its role in global climate action is pivotal. To date, 53 African countries have submitted their Nationally Determined Contributions (NDCs), and four have committed to a net-zero target. However, many of Africa's NDCs are vaguely expressed and without specific focus on explicit sectoral decarbonization targets. Furthermore, Africa's huge land-based carbon dioxide removal (CDR) potential remains unclear in the context of enabling net-zero (NZ) emissions within the continent. This study achieves two objectives: Under a NZ GHG emission trajectory in Africa, we uncover the implications of a targeted zero-emission electricity sector by 2030, on the energy landscape and other sustainability factors. This study also features the role of land-based biological removal methods─bioenergy carbon capture and storage (BECCS) and afforestation/reforestation (A/R)─in net zero actualization in Africa. Our results reveal a unified but disparate actualisation of the mid-century net zero emission goal across the continent, as all regions except North Africa achieve carbon neutrality. The industrial sector faces significant difficulties in transitioning and contributes substantially to positive emissions on the continent, with its share of total residual emissions reaching 49-64% by 2050. This difficulty persists even with targeted sectoral decarbonization of the electricity sector, although it is significantly reduced by the availability of BECCS as a CDR option. Under the zero-emission electricity pathway, emissions in buildings and transport sectors are reduced due to rapid electrification. A trade-off emerges in the net zero pathway concerning land allocation for negative emissions versus other land use activities. A key result shows that achieving a net zero target in Africa leads to a cumulative loss of $102 billion in fossil fuel infrastructure within the electricity sector by mid-century, which doubles when the zero-emission electricity goal is achieved.

Nexus of embodied land use and greenhouse gas emissions in global agricultural trade: A quasi-input–output analysis

The agriculture and forestry sector accounts for approximately 24% of total greenhouse gas (GHG) emissions in Australia. Over the years researchers have produced new knowledge about agricultural GHG emissions and energy use patterns and opportunities to decrease them, albeit in small-scale studies or large-scale ones with coarse resolution. Linking the multiple, diverse and rich datasets around agricultural production in Australia into one dataset that allows for an estimate of GHG emissions and energy use related to agriculture at a national scale and high resolution has not been done before. The approach we describe here is based upon a link between operational data sourced from gross margin (GM) handbooks and life cycle assessment (LCA) process data. We have collected and processed these datasets to produce a comprehensive database of typical agricultural operations covering 72 commodities grown in 42 regions across Australia. We have also created a system that estimates the GHG emission and energy use patterns of the aforementioned commodities using the best available LCA process data. To capture GHG emissions of non-domestically produced fertiliser, we queried the United Nations Commodity Trade Statistics Database (COMTRADE) to analyse the fertiliser and pesticide import patterns for Australia between 2000-2010. This analysis determined the average country energy-mix for fertiliser and pesticide manufacturing and allowed linking the associated GHG emissions to Australian agricultural production. Finally we spatialised agricultural operational data, emissions and energy use at the national scale using the latest Australian Land Use Map (2005/06). Our findings suggest that in 2005/06 greenhouse gas emissions related to Australian agricultural production equate to a total of 95.8 Mt CO-e using 75.7 GWh of energy. According to our results 29.4% of these emissions come from sources that were categorised as non-agricultural (e.g. industrial processes or energy use) in the Australian National Greenhouse Gas Inventory (NGGI) 2006. We find that the provision of transparently modeled GHG emissions and having them linked to a spatially explicit component helps identifying new opportunities for emission reduction and facilitates an assessment of their effects. For example, our findings suggest production of ethanol from corn stover and sugarcane bagasse could have avoided 4.37 Mt CO-e emissions (4.56% of total) without affecting food production.

Combating climate change requires reducing greenhouse gas (GHG) emissions from human activities and enhancing carbon dioxide removal (CDR) through blue carbon ecosystems (BCEs). Progress is measured by international reporting of national GHG inventories under the UNFCCC, following IPCC guidelines. The EU Green Deal, particularly the EU Biodiversity Strategy to 2030, recognizes BCEs’ potential by advocating for the restoration of carbon-rich habitats. However, the IPCC Wetlands Supplement is underutilized in national GHG reporting, and few countries, especially in Europe, include blue carbon in their Nationally Determined Contributions (NDCs) under the Paris Agreement. This is due to limited awareness, the non-mandatory nature of the IPCC Wetlands Supplement, and data gaps. Our research aims to advance blue carbon knowledge, promoting BCEs as nature-based solutions, and addressing key gaps and scientific uncertainties to improve quantification and reporting of blue carbon under the UNFCCC in GHG inventory reporting under the Paris Agreement. The C-BLUES project, part of the Joint EU-China Flagship Initiative on Climate Change & Biodiversity, seeks to enhance the IPCC Wetlands Supplement, increase BCE inclusion in national GHG inventories, and explore additional BCEs like natural and farmed kelp systems. We document best practices for monitoring and verifying BCE actions, model BCE sequestration capacity, and upscale GHG budgets to estimate BCE contributions to EU and Chinese inventories. We assess carbon stock changes, GHG emissions, and removals from various management interventions, and evaluate the integration of BCEs into national reporting mechanisms. We present a roadmap and invite participation with the scientific community, policy makers and the wider civil society to generate knowledge, raise awareness of BCEs and build capacity for BC research, as well as provide guidance on voluntary reporting on BCE.

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Since the Paris Agreement in COP21, many countries around the world, including Ghana and Thailand, have established a Nationally Determined Contribution (NDC) to reduce greenhouse gas (GHG) emissions, with first update recently in COP26. With Ghana’s ongoing effort at COP26 to change its baseline to 2019, this study established a detailed Ghana vehicle ownership model with necessary transport parameters to construct an energy demand model to provide insight for reducing GHG emission contributions from road transport through biofuel (both bioethanol and biodiesel) potential by recourse to a Low Emission Analysis Platform (LEAP), with two scenarios of development from Thailand’s best practice for policy recommendation, which are alternative (ALT), with up to E20/B20, and extreme (EXT), with up to E85/B50, for new vehicles. In each case, energy demand and GHG emissions were analyzed from detailed data on Ghana’s transport sector to show potential benefit from biofuel usages. From Ghana’s transport sector contribution to NDC, 8.4% and 11.1% of GHG emission reduction in 2030 can be achieved with a 0.13% and 0.27% additional arable land requirement from ALT and EXT scenarios. Policy recommendation and implication were also discussed.

Urban water cycle systems(UWCS), including water treatment facilities, distribution facilities, sewers, and wastewater treatment facilities, are energy intensive and significant source of greenhouse gas (GHG) emissions, making the reduction of GHG emissions and the transition to eco-friendly energy essential. This study identifies specific GHG emission sources at each stage of the UWCS and proposes detailed methods to achieve a 40% reduction in GHG emissions, implement RE100, and attain Net Zero by employing insets and offsets. This study develops scenarios for insets and offsets based on the baseline process of the UWCS, and investigates potential pathways to reduce GHG emissions by quantifying emissions from each process. Internal insets, which are self-implemented and technical measures, are prioritized, while external offsets are applied to compensate for the remaining emissions. Internal insets include the application of anaerobic digesters and combined heat and power(CHP), improvements in energy efficiency of equipment, reduction in water pipe leakage, implementation of water footprint labeling, and installation of on-site photovoltaic system. External offsets comprise renewable energy certificates(REC), power purchase agreements(PPA), green hydrogen fuel for vehicles, natural sequestration improvement, and emission trading system. GHG emissions at each stage within the UWCS are quantified using modeling software. Based on these results, the effectiveness of insets and offsets in achieving a 40% GHG emissions reduction, Net Zero, and RE100 goal is analyzed. The baseline total GHG emissions for the UWCS are estimated at 4,732.8 tCO2eq/yr, of which 56.8% is identified as targets for internal insets, and the remaining 43.2% is reduced through external offsets. A 40% GHG reduction can be achieved through internal insets, and Net Zero can be attained by incorporating additionally applying external offsets. The total power demand of UWCS facilities and equipment is calculated as 572.8 kW. Renewable energy is generated through anaerobic digesters and CHP(116.1kW) as well as on-site PV(395.0 kW), while RE100 compliance is achieved by securing an aditional 61.7 kW through REC/PPA. Achieving Net Zero and RE100 requires prioritizing strategies for insets, offsets and efficient resource allocation. For this, the technical feasibility and self-implementation potential of reduction efforts and the external conditions for offsets, should be carefully reviewed to optimize implementation strategies. GHG reduction and renewable energy utilization in the UWCS are key priorities for addressing the climate crisis and achieving sustainable water resource management, requiring technological innovation and institutional support. The comprehensive and systematic application of GHG insets and offsets is the optimal approach to achieving these goals. Furthermore, modeling software serves as a key tool for quantifying GHG emissions and formulating concrete, viable GHG reduction strategies. In addition to the technical and institutional approaches proposed in this study, achieving Net Zero and implementing RE100 requires the integrated consideration of economic factors in the future.

Life Cycle Assessment (LCA) is a comprehensive method for evaluating building sustainability. However, most studies have relied on generic or national LCA databases, overlooking the systematic consideration of future scenarios and sectoral developments due to data and tool constraints. Moreover, there's a gap in providing a standardized workflow for such evaluations and understanding their impact on the greenhouse gas (GHG) emissions of buildings on a national level. Addressing these gaps, our study incorporates scenarios from two Integrated Assessment Models (IAMs), considering the future developments of the electricity, cement, and steel sectors, to assess embodied GHG emissions of Swiss residential buildings from 2015 to 2055. Our findings reveal that incorporating these future considerations can lead up to a 25% GHG emissions reduction by 2055 compared to 2015, primarily due to GHG emission reductions in concrete and brick as a result of these considerations. This is much less than the emissions reduction potential of some specific construction materials and far from the goal of net zero. It also underscores the importance of exploring alternative strategies for net-zero GHG emissions at the building stock level. Consequently, we present reproducible workflows using open-source tools and future versions of the Swiss national building LCA databases, offering a blueprint for similar future studies in other countries.

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.

Agriculture is an important contributor to greenhouse gas (GHG) emissions. While the development of agricultural GHG emissions on national and global scales is well studied for the last three to six decades, little is known about their trajectory and drivers over longer periods. In this article, we address this research gap by calculating and analyzing GHG emissions related to agriculture in Austria from 1830 to 2018. We calculate territorial emissions on an annual basis and include all GHG emissions from the processes directly involved in agricultural production. Based on this time series, we quantify the relative importance of major drivers of changes in GHG emissions across time and agricultural product categories, applying a structural decomposition analysis. We find that agricultural GHG emissions in Austria increased by 69 % over the total study period, from 4.6 Mt. CO2e/yr in 1830 to 7.7 Mt. CO2e/yr in 2018. While emissions increased only moderately from 1830 to 1945 (+22 % overall), with strong fluctuations between 1914 and 1945, they doubled from 1945 to 1985. In the most recent period from 1985 to 2018, emissions fell by one third, with decreases leveling off over time. Our decomposition analysis reveals that increases in agricultural production per capita most importantly contributed to the high growth in GHG emissions from 1945 to 1985. Conversely, decreasing emission intensities of products and a more climate friendly product mix were key drivers in the emissions reduction observed after 1985. We also contribute to the discussion around the global warming potential star (GWP*), by calculating GHG emissions based on this alternative metric, and contextualize our data within total socio-economic GHG emission trends. By providing insights into the historical trends and drivers of agricultural GHG emissions, our findings enhance the understanding of their long-term historical dynamics and adds to the knowledge base for future mitigation efforts.

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

Transparency requirements under the Paris Agreement and their (un)likely impact on strengthening the ambition of nationally determined contributions (NDCs)