Global diets link environmental sustainability and human health.

Agricultural activities are a substantial contributor to global greenhouse gas (GHG) emissions, accounting for about 58% of the world's anthropogenic non‐carbon dioxide GHG emissions and 14% of all anthropogenic GHG emissions, and agriculture is often viewed as a potential source of relatively low‐cost emissions reductions. We estimate the costs of GHG mitigation for 36 world agricultural regions for the 2000–2020 period, taking into account net GHG reductions, yield effects, livestock productivity effects, commodity prices, labor requirements, and capital costs where appropriate. For croplands and rice cultivation, we use biophysical, process‐based models (DAYCENT and DNDC) to capture the net GHG and yield effects of baseline and mitigation scenarios for different world regions. For the livestock sector, we use information from the literature on key mitigation options and apply the mitigation options to emission baselines compiled by EPA.

Agricultural activities are a substantial contributor to global greenhouse gas (GHG) emissions, accounting for about 58% of the world's anthropogenic non-carbon dioxide GHG emissions and 14% of all anthropogenic GHG emissions, and agriculture is often viewed as a potential source of relatively low-cost emissions reductions. We estimate the costs of GHG mitigation for 36 world agricultural regions for the 2000–2020 period, taking into account net GHG reductions, yield effects, livestock productivity effects, commodity prices, labor requirements, and capital costs where appropriate. For croplands and rice cultivation, we use biophysical, process-based models (DAYCENT and DNDC) to capture the net GHG and yield effects of baseline and mitigation scenarios for different world regions. For the livestock sector, we use information from the literature on key mitigation options and apply the mitigation options to emission baselines compiled by EPA.

Contributions of natural systems and human activity to greenhouse gas emissions

The refining industry is the third-largest source of global greenhouse gas (GHG) emissions from stationary sources, so it is at the forefront of the energy transition and net zero pathways. The dynamics of contributors in this sector such as crucial countries, leading enterprises, and key emission processes are vital to identifying key GHG emitters and supporting targeted emission reduction, yet they are still poorly understood. Here, we established a global sub-refinery GHG emission dataset in a long time series based on life cycle method. Globally, cumulative GHG emissions from refineries reached approximately 34.1 gigatons (Gt) in the period 2000-2021 with an average annual increasing rate of 0.7%, dominated by the United States, EU27&UK, and China. In 2021, the top 20 countries with the largest GHG emissions of oil refining accounted for 83.9% of global emissions from refineries, compared with 79.5% in 2000. Moreover, over the past two decades, 53.9-57.0% of total GHG emissions came from the top 20 oil refining enterprises with the largest GHG emissions in 12 of these 20 countries. Retiring or installing mitigation technologies in the top 20% of refineries with the largest GHG emissions and refineries with GHG emissions of more than 0.1 Gt will reduce the level of GHG emissions by 38.0%-100.0% in these enterprises. Specifically, low-carbon technologies installed on furnaces and boilers as well as steam methane reforming will enable substantial GHG mitigation of more than 54.0% at the refining unit level. Therefore, our results suggest that policies targeting a relatively small number of super-emission contributors could significantly reduce GHG emissions from global oil refining.

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.

Agricultural transformation towards delivering deep carbon cuts in China’s arid inland areas

Solid waste management is a cross-cutting issue that significantly influences multiple aspects of sustainable development globally. The waste sector is a major anthropogenic source of global greenhouse gas (GHG) emissions. Most global GHG assessments of waste management rely on generic data due to limitations in available data. This research used reflective inventory data for municipal solid waste (MSW) treatment systems related to the income levels of countries, resulting in more context-specific and comprehensive assessments of GHG emissions. This study aims to assess life cycle GHG emissions from the global MSW management sector for the years 2023, 2030, and 2050 and then analyses the global and regional waste management goals set by the United Nations Environment Programme (UNEP) and the European Union (EU) to identify hotspots in the MSW management systems and critical factors that influence GHG emissions from the waste sector. The study was conducted in accordance with the standards outlined in ISO 14067:2018. The results show that the average global GHG emissions from 1 tonne of MSW in 2023 based on the existing MSW management practices was approximately 89.7 kg CO2e. The major contributor was the open dumping of MSW, contributing almost 70 % of GHG emissions. The global MSW management sector emitted a total of 173.2 Mt CO2e GHG emissions in 2023. If no improvements are made to existing systems, GHG emissions from the waste sector are projected to increase to 203.4 Mt CO2e by 2030, and to 289.5 Mt CO2e by 2050. Achieving waste management goals can reduce GHG emissions by approximately 1 % to more than 160 %. The implementation of the circular economy in the waste sector has the potential to achieve net zero emissions from the global MSW management sector by 2030 and 2050. This study provides achievable MSW management targets for the world and highlights key factors to achieve carbon neutrality from the waste sector. Prioritising policies such as upgrading open dumps, standardising household-level waste separation procedures, minimising food waste, establishing national recycling targets, and promoting circular economy through a zero-waste approach could substantially reduce GHG emissions from the waste sector. These findings are important for the adoption of circular economy principles in MSW management systems to effectively support the pursuit of carbon neutrality goals.

The EU Renewable Energy Directive (RED) targets, implemented to achieve climate change mitigation, affect the level of agricultural production in the EU and in the rest of the world. This article presents an impact assessment of increased biomass supply under different sustainability constraints on land use and resulting total GHG emissions at global and EU level. We apply GLOBIOM, a global partial equilibrium model integrating the agricultural, livestock, bioenergy and forestry sectors based on geographically explicit modeling of supply under prescribed demand. According to the model, global greenhouse gas (GHG) emissions from agriculture and land‐use change (LUC) are anticipated to rise significantly up to 2030 due to various drivers (among others: GDP and population, diet shifts, and also bioenergy demand) despite basic sustainability criteria implemented by the RED (Reference scenario). Applying additional criteria, mainly protecting biodiversity outside the EU, overall GHG emissions can be reduced by 5% in 2030 compared to the Reference. Deforestation area decreases in this scenario slightly due to exclusion of high biodiversity forests but also due to increasing demand for energy wood that makes forests more valuable. If, however, in addition, deforestation is prevented through effective land‐use policies, global GHG emissions can be reduced by 20% (compared to the Reference scenario). We conclude that sustainability criteria applied to biofuel production and imports only, do not mitigate potential negative impacts on total GHG emissions effectively. Unsustainable biomass production in sectors not covered by the bioenergy criteria can be best avoided by targeting deforestation and biodiversity loss directly. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

China is one of the largest contributors to global greenhouse gas (GHG) emissions, and the livestock sector is a major source of non-CO2 GHG emissions. Mitigation of GHG emissions from the livestock sector is beneficial to the sustainable development of the livestock sector in China. This study investigated the provincial level of GHG emissions from the livestock sector between 2000 and 2020 in China, to determine the driving factors affecting the provincial-level GHG emissions from the livestock sector, based on the logarithmic mean Divisia index (LMDI) model, which took into account of technological progress, livestock structure, economic factor, and agricultural population. Moreover, a gray model GM (1, 1) was used to predict livestock GHG emissions in each province until 2030 in China. The results showed that the GHG of Chinese livestock sector was decreased from 195.1 million tons (MT) CO2e in 2000 to 157.2 MT CO2e in 2020. Henan, Shandong, and Hebei provinces were the main contributors to the reduction in Chinese livestock GHG emissions, with their livestock GHG emissions reduced by 60.1%, 53.5% and 45.5%, respectively, in 2020 as compared to 2000. The reduction in GHG emissions from the Chinese livestock sector can be attributed to two main factors: technological progress and the shrinking of the agricultural laborers. In contrast, the agricultural economic development model with high input and high emissions showed a negative impact on GHG emission reduction in China’s livestock sector. Furthermore, the different livestock structure in each province led to different GHG reduction effects on the livestock sector. Under the gray model GM (1,1), the GHG emissions of the livestock sector will be reduced by 33.7% in 2030 as compared with 2020 in China, and the efficiency factor will account for 76.6% of the positive effect of GHG reduction in 2030. The eastern coastal region will be the main contributor to the reduction of GHG emissions from the Chinese livestock sector in 2030. Moreover, recommendations (such as upgrading livestock management methods and promoting carbon emission mitigation industries) should be proposed for the environmentally sustainable development of the livestock sector in the future.

ABSTRACTAgriculture serves as both a source and a sink of global greenhouse gases (GHGs), with agricultural intensification continuing to contribute to GHG emissions. Climate‐smart agriculture, encompassing both nature‐ and technology‐based actions, offers promising solutions to mitigate GHG emissions. We synthesized global data, between 1990 and 2021, from the Food and Agriculture Organization (FAO) of the United Nations to analyze the impacts of agricultural activities on global GHG emissions from agricultural land, using structural equation modeling. We then obtained predictive estimates of agricultural GHG emissions for the future period of 2022–2050 using deep‐learning models. The FAO data show that, from 1990 to 2021, global livestock numbers, inorganic nitrogen (N) fertilizer use, crop residue, and irrigation area increased by 27%, 47%, 49%, and 37%, respectively. The increased livestock numbers contributed to the increases in CH4 and N2O emissions, while inorganic N fertilizer, crop residue, and irrigation mainly contributed to the increases in N2O emissions. Emissions of CO2 decreased because of a 29% reduction in net forest loss. As a result of the reduced deforestation emissions, the overall agricultural GHG emissions declined from 11.50 to 10.89 GtCO2eq from 1990 to 2021 despite the increases in livestock numbers, inorganic N fertilizer, crop residue, and irrigation. Looking ahead, our model predicts that if current agricultural trends persist, GHG emissions will rise to 11.82 ± 0.07 GtCO2eq in 2050. However, maintaining agricultural GHG emissions at the 2021 level through 2050 is possible if the rate of reduction in net forest loss is doubled. Furthermore, if the rate is tripled, agricultural GHG emissions can be limited to 9.85 ± 0.07 GtCO2eq in 2050. Our findings suggest that reductions in agricultural GHG emissions, alongside sustainable agricultural intensification and climate‐smart agricultural practices, can be achieved through parallel efforts emphasizing accelerated forest conservation.

Global and regional trends in greenhouse gas emissions from rice production, trade, and consumption

Agricultural activities are major contributors to global greenhouse gas (GHG) emissions, with methane (CH4) and nitrous oxide (N2O) emissions accounting for 40% and 60% of total agricultural emissions, respectively. Therefore, developing effective emission reduction pathways in agriculture is crucial for achieving carbon budget balance. This article synthesizes the impact of farmland management practices on GHG emissions, evaluates prevalent accounting methods and their applicable scenarios, and proposes mitigation strategies based on systematic analysis. The present review (2000–2025) indicates that fertilizer management dominates research focus (accounting for over 50%), followed by water management (approximately 18%) and tillage practices (approximately 14%). Critically, the effects of these practices extend beyond GHG emissions, necessitating concurrent consideration of crop yields, soil health, and ecosystem resilience. Therefore, it is necessary to conduct joint research by integrating multiple approaches such as water-saving irrigation, conservation tillage and intercropping of leguminous crops, so as to enhance productivity and soil quality while reducing emissions. The GHG accounting framework and three primary accounting methods (In situ measurement, Satellite remote sensing, and Model simulation) each exhibit distinct advantages and limitations, requiring scenario-specific selection. Further refinement of these methodologies is imperative to optimize agricultural practices and achieve meaningful GHG reductions.

Advanced wastewater treatment processes and novel technologies are adopted to improve nutrient removal from wastewater so as to meet stringent discharge standards. Municipal wastewater treatment plants are one of the major contributors to the increase in the global greenhouse gas (GHG) emissions and therefore it is necessary to carry out intensive studies on quantification, assessment and characterization of GHG emissions in wastewater treatment plants, on the life cycle assessment from GHG emission prospective, and on the GHG mitigation strategies. Greenhouse Gas Emission and Mitigation in Municipal Wastewater Treatment Plants summarises the recent development in studies of greenhouse gases’ (CH4 and N2O) generation and emission in municipal wastewater treatment plants. It introduces the concepts of direct emission and indirect emission, and the mechanisms of GHG generations in wastewater treatment plants’ processing units. The book explicitly describes the techniques used to quantify direct GHG emissions in wastewater treatment plants and the protocol used by the Intergovernmental Panel on Climate Change (IPCC) to estimate GHG emission due to wastewater treatment in the national GHG inventory. Finally, the book explains the life cycle assessment (LCA) methodology on GHG emissions in consideration of the energy and chemical usage in municipal wastewater treatment plants. In addition, the strategies to mitigate GHG emissions are discussed. The book provides an overview for researchers, students, water professionals and policy makers on GHG emission and mitigation in municipal wastewater treatment plants and industrial wastewater treatment processes. It is a valuable resource for undergraduate and postgraduate students in the water, climate, and energy areas; for researchers in the relevant areas; and for professional reference by water professionals, government policy makers, and research institutes. ISBN: 9781780406305 (Print) ISBN: 9781780406312 (eBook) ISBN: 9781780409054 (ePUB)

Agriculture is responsible for a large share of global greenhouse gas (GHG) emissions, especially for methane and nitrous oxide emissions. Applying a bio-economic whole-farm model, we assessed five GHG mitigation options on their economic suitability to reduce emissions from grassland-based suckler cow farms. Among the assessed options, only compensation by agroforestry systems and the choice of an adequate production system showed the potential to significantly reduce emissions. If an adequate production system is chosen, GHG emissions per kilogram of meat can be reduced by up to 18% – from 21.9 to 18 kg CO2-eq./kg of meat – while total gross margin can be increased by up to 14%. Through the application of an agroforestry system, GHG emissions in all systems can be further reduced to 7.5 kg CO2-eq./kg meat – equating to a reduction of GHG emissions of 48% to 66% – at costs between 0.03 CHF/kg meat and 0.38 CHF/kg meat depending on the production system and the state of the system before the reduction. In contrast, the addition of lipids to the diet or a cover to the slurry tank has neither the potential to reduce GHG emissions significantly nor are they cost-effective enough to be implemented. Nitrification inhibitors can reduce GHG emissions up to 10%, but costs for this reduction are much higher than for agroforestry systems. The application of agroforestry systems to suckler farming in Switzerland therefore seems to be an adequate option to reduce GHG emission significantly for a relatively low price.

Advance in a terrestrial biogeochemical model—DNDC model