A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

Contributions of natural systems and human activity to greenhouse gas emissions

Abstract. To track progress towards keeping warming well below 2 °C, as agreed upon in the Paris Agreement, comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions (GHG) is required. Here we provide a dataset on anthropogenic GHG emissions 1970–2019 with a broad country and sector coverage. We build the dataset from recent releases of the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases, and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with data on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three bookkeeping models. We provide an assessment of the uncertainties in each greenhouse gas at the 90 % confidence interval (5th–95th percentile) by combining statistical analysis and comparisons of global emissions inventories with an expert judgement informed by the relevant scientific literature. We identify important data gaps: CH4 and N2O emissions could be respectively 10–20 % higher than reported in EDGAR once all emissions are accounted. F-gas emissions estimates for individual species in EDGARv5 do not align well with atmospheric measurements and the F-gas total exceeds measured concentrations by about 30 %. However, EDGAR and official national emission reports under the UNFCCC do not comprehensively cover all relevant F-gas species. Excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are larger than the sum of the reported species. GHG emissions in 2019 amounted to 59 ± 6.6 GtCO2eq: CO2 emissions from FFI were 38 ± 3.0 Gt, CO2 from LULUCF 6.6 ± 4.6 Gt, CH4 11 ± 3.3 GtCO2eq, N2O 2.4 ±1.5 GtCO2eq and F-gases 1.6 ± 0.49 GtCO2eq. Our analysis of global, anthropogenic GHG emission trends over the past five decades (1970–2019) highlights a pattern of varied, but sustained emissions growth. There is high confidence that global anthropogenic greenhouse gas emissions have increased every decade. Emission growth has been persistent across different (groups of) gases. While CO2 has accounted for almost 75 % of the emission growth since 1970 in terms of CO2eq as reported here, the combined F-gases have grown at a faster rate than other GHGs, albeit starting from low levels in 1970. Today, F-gases make a non-negligible contribution to global warming – even though CFCs and HCFCs, regulated under the Montreal Protocol and not included in our estimates, have contributed more. There is further high confidence that global anthropogenic GHG emission levels were higher in 2010-2019 than in any previous decade and GHG emission levels have grown across the most recent decade. While average annual greenhouse gas emissions growth slowed between 2010–2019 compared to 2000–2009, the absolute increase in average decadal GHG emissions from the 2000s to the 2010s has been the largest since the 1970s – and within all human history as suggested by available long-term data. We note considerably higher rates of change in GHG emissions between 2018 and 2019 than for the entire decade 2010–2019, which is numerically comparable with the period of high GHG emissions growth during the 2000s, but we place low confidence in this finding as the majority of the growth is driven by highly uncertain increases in CO2-LULUCF emissions as well as the use of preliminary data and extrapolation methodologies for these most recent years. While there is a growing number of countries today on a sustained emission reduction trajectory, our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. We conclude by highlighting that tracking progress in climate policy requires substantial investments in independent GHG emission accounting and monitoring as well as the available 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.5053056 .

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.

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)

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.

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.

Greenhouse gas (GHG) emissions from post-consumer waste and wastewater are a small contributor (about 3%) to total global anthropogenic GHG emissions. Emissions for 2004-2005 totalled 1.4 Gt CO2-eq year(-1) relative to total emissions from all sectors of 49 Gt CO2-eq year(-1) [including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and F-gases normalized according to their 100-year global warming potentials (GWP)]. The CH4 from landfills and wastewater collectively accounted for about 90% of waste sector emissions, or about 18% of global anthropogenic methane emissions (which were about 14% of the global total in 2004). Wastewater N2O and CO2 from the incineration of waste containing fossil carbon (plastics; synthetic textiles) are minor sources. Due to the wide range of mature technologies that can mitigate GHG emissions from waste and provide public health, environmental protection, and sustainable development co-benefits, existing waste management practices can provide effective mitigation of GHG emissions from this sector. Current mitigation technologies include landfill gas recovery, improved landfill practices, and engineered wastewater management. In addition, significant GHG generation is avoided through controlled composting, state-of-the-art incineration, and expanded sanitation coverage. Reduced waste generation and the exploitation of energy from waste (landfill gas, incineration, anaerobic digester biogas) produce an indirect reduction of GHG emissions through the conservation of raw materials, improved energy and resource efficiency, and fossil fuel avoidance. Flexible strategies and financial incentives can expand waste management options to achieve GHG mitigation goals; local technology decisions are influenced by a variety of factors such as waste quantity and characteristics, cost and financing issues, infrastructure requirements including available land area, collection and transport considerations, and regulatory constraints. Existing studies on mitigation potentials and costs for the waste sector tend to focus on landfill CH4 as the baseline. The commercial recovery of landfill CH4 as a source of renewable energy has been practised at full scale since 1975 and currently exceeds 105 Mt CO2-eq year(-1). Although landfill CH4 emissions from developed countries have been largely stabilized, emissions from developing countries are increasing as more controlled (anaerobic) landfilling practices are implemented; these emissions could be reduced by accelerating the introduction of engineered gas recovery, increasing rates of waste minimization and recycling, and implementing alternative waste management strategies provided they are affordable, effective, and sustainable. Aided by Kyoto mechanisms such as the Clean Development Mechanism (CDM) and Joint Implementation (JI), the total global economic mitigation potential for reducing waste sector emissions in 2030 is estimated to be > 1000 Mt CO2-eq (or 70% of estimated emissions) at costs below 100 US$ t(-1) CO2-eq year(-1). An estimated 20-30% of projected emissions for 2030 can be reduced at negative cost and 30-50% at costs < 20 US$ t(-) CO2-eq year(-1). As landfills produce CH4 for several decades, incineration and composting are complementary mitigation measures to landfill gas recovery in the short- to medium-term--at the present time, there are > 130 Mt waste year(-1) incinerated at more than 600 plants. Current uncertainties with respect to emissions and mitigation potentials could be reduced by more consistent national definitions, coordinated international data collection, standardized data analysis, field validation of models, and consistent application of life-cycle assessment tools inclusive of fossil fuel offsets.

The Best Graduate Medical Education Articles From 2021-in Our (Humble) Opinions.

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.

Studies on the contribution of milk production to global greenhouse gas (GHG) emissions are rare (FAO 2010) and often based on crude data which do not appropriately reflect the heterogeneity of farming systems. This article estimates GHG emissions from milk production in different dairy regions of the world based on a harmonised farm data and assesses the contribution of milk production to global GHG emissions. The methodology comprises three elements: (1) the International Farm Comparison Network (IFCN) concept of typical farms and the related globally standardised dairy model farms representing 45 dairy regions in 38 countries; (2) a partial life cycle assessment model for estimating GHG emissions of the typical dairy farms; and (3) standard regression analysis to estimate GHG emissions from milk production in countries for which no typical farms are available in the IFCN database. Across the 117 typical farms in the 38 countries analysed, the average emission rate is 1.50 kg CO(2) equivalents (CO(2)-eq.)/kg milk. The contribution of milk production to the global anthropogenic emissions is estimated at 1.3 Gt CO(2)-eq./year, accounting for 2.65% of total global anthropogenic emissions (49 Gt; IPCC, Synthesis Report for Policy Maker, Valencia, Spain, 2007). We emphasise that our estimates of the contribution of milk production to global GHG emissions are subject to uncertainty. Part of the uncertainty stems from the choice of the appropriate methods for estimating emissions at the level of the individual animal.

BackgroundFood production accounts for 30% of global greenhouse gas (GHG) emissions. Less environmentally sustainable diets are also often more processed, energy-dense and nutrient-poor. To date, the environmental impact of diets have mostly been based on a limited number of broad food groups.ObjectivesWe link GHG emissions to over 3000 foods, assessing associations between individuals’ GHG emissions, their nutrient requirements and their demographic characteristics. We also identify additional information required in dietary assessment to generate more accurate environmental impact data for individual-level diets.MethodsGHG emissions of individual foods, including process stages prior to retail, were added to the UK Composition Of Foods Integrated Dataset (COFID) composition tables and linked to automated online dietary assessment for 212 adults over three 24-hour periods. Variations in GHG emissions were explored by dietary pattern, demographic characteristics and World Health Organization Recommended Nutrient Intakes (RNIs).ResultsGHG emissions estimates were linked to 98% (n = 3233) of food items. Meat explained 32% of diet-related GHG emissions; 15% from drinks; 14% from dairy; and 8% from cakes, biscuits and confectionery. Non-vegetarian diets had GHG emissions 59% (95% CI 18%, 115%) higher than vegetarian. Men had 41% (20%, 64%) higher GHG emissions than women. Individuals meeting RNIs for saturated fats, carbohydrates and sodium had lower GHG emissions compared to those exceeding the RNI.DiscussionPolicies encouraging sustainable diets should focus on plant-based diets. Substituting tea, coffee and alcohol with more sustainable alternatives, whilst reducing less nutritious sweet snacks, presents further opportunities. Healthier diets had lower GHG emissions, demonstrating consistency between planetary and personal health. Further detail could be gained from incorporating brand, production methods, post-retail emissions, country of origin, and additional environmental impact indicators.

Livestock and greenhouse gas emissions: The importance of getting the numbers right

Over the last three decades, socio-economic, demographic and technological transitions have been witnessed throughout the world, modifying both sectorial and geographical distributions of greenhouse gas (GHG) emissions. Understanding these trends is central to the design of current and future climate change mitigation policies, requiring up-to-date methodologically robust emission inventories such as the Emissions Database for Global Atmospheric Research (EDGAR), the European Commission’s in-house, independent global emission inventory. EDGAR is a key tool to track the evolution of GHG emissions and contributes to quantifying the global carbon budget, providing independent and systematically calculated emissions for all countries.According to the results of the EDGAR v.5.0 release, total anthropogenic global greenhouse gas emissions (excluding land use, land use change and forestry) were estimated at 49.1 Gt CO2eq in 2015, 50 % higher than in 1990, despite a monotonic decrease in GHG emissions per unit of economic output. Between 1990 and 2015, emissions from developed countries fell by 9%, while emissions from low to medium income countries increased by 130%, predominantly from 2000 onwards. The 27 Member States of the European Union and the United Kingdom led the pathway for emission reductions in industrialised economies whilst, in developing countries, the rise in emissions was driven by higher emissions in China, India, Brazil and nations in the South-East Asian region. This diversity of patterns shows how different patterns for GHG emissions are and the need for identifying regionally tailored emission reduction measures.

Intended nationally determined contributions (INDCs) are a new strategy for mitigating climate change. Many international organizations and scholars have assessed the possibility of holding the increase in global average temperature to well below 2°C based on INDCs. Although the conclusions of these assessments are consistent, there are still large differences among the assessment results. For example, the global greenhouse gas emissions in 2030 estimated by INDCs are between 47.1–66.5 GtCO2 eq, and the temperature increase at the end of the 21st century estimated by INDCs is between 2.4–4.0°C; the inconsistency represented by these ranges is not conducive to an accurate assessment of the contributions of the current INDCs to global warming mitigation or to the further development of emissions reduction programs. By summarizing the existing studies, we found that the main reasons for the differences in estimates of global greenhouse gas emissions in 2030 made using INDCs are as follows: (1) The studies interpreted INDCs differently, which is attributable to three reasons: The studies (a) made different assumptions for the unquantifiable INDCs; (b) ignored or used different methods to estimate the emissions not covered by INDCs; and (c) used different amounts of INDCs because the studies were performed at different times. (2) The studies used different databases that include different greenhouse gases, accounting methods and data sources to estimate historical greenhouse gas emissions. (3) The studies used different methods for estimating greenhouse gas emissions and removals related to land use, land-use change and forestry (LULUCF). (4) The studies used different values of the global warming potential. Additionally, the main reasons for the differences in the predictions of the temperature increase at the end of the 21st century based on INDCs are as follows: (1) Differences in the estimations of greenhouse gas emissions in 2030 based on INDCs and (2) different methods of extrapolating global greenhouse gas emissions to 2100. There are three main extrapolation methods: one is to maintain the net present value of the carbon price in 2030 and then extrapolate the greenhouse gas emissions to 2100; another is to maintain the decarbonization rate of a certain period of history and then extrapolate the greenhouse gas emissions to 2100; the third is to match the emissions reduction scenario with the current INDC emissions reduction scenario from the IPCC AR5 scenario database and then use the matching emissions reduction scenario as the current INDC emissions reduction scenario. The use of different methods of extrapolating carbon emissions is one of the main reasons for the differences in the prediction results. (3) Differences in the methods for predicting the effects of greenhouse gas emissions on temperature. Statistical methods and simulation methods are the two main prediction methods; they use different calculation methods, which led to the difference in the prediction results. Therefore, the following points are worth noting: (1) Most importantly, to the extent possible, countries should submit absolute emissions reduction targets as much as possible; nonquantifiable INDCs without detailed methods descriptions and data introductions should not be submitted; (2) authorities should recommend certain data sets that are the most suitable for INDC accounting; (3) a global warming potential should be designated to avoid differences in greenhouse gas estimates due to the use of different criteria; and (4) to the extent possible, future research should adopt simulation methods for predicting the impact of global greenhouse gas emissions on temperature.

The role of ‘indirect’ greenhouse gas emissions in tourism: Assessing the hidden carbon impacts from a holiday package tour