Dataset of 2012-2020 U.S. National- and State-Level Greenhouse Gas Emissions by Sector.

The dataset contains ∼1.1 million records of total greenhouse gases directly emitted annually by economic sectors and households in the US from 2012-2020. Data are given for 16 unique greenhouse gases by 118 aggregate sectors for each state, and as totals by these aggregate sectors as well as by 540 detailed sectors at the national level. The dataset is a product of updated sector attribution models that improve upon the National Greenhouse Gas Industry Attribution Model. This paper provides documentation of the methods used to produce these datasets and proof of validation of the dataset, along with relevant supporting tables, figures, and source code.

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

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

Using Open Foris Collect Earth in Kyrgyzstan to support greenhouse gas inventory in the land use, land use change, and forestry sector.

The Kyrgyz Republic (Kyrgyzstan) is one of the countries most vulnerable to the adverse effects of climate change in Central Asia. The land use, land use change, and forestry (LULUCF) sector is critical in climate change mitigation in Kyrgyzstan and is integral to national greenhouse gas (GHG) inventories. However, consistent, complete, and updated activity data is required for the LULUCF sector to develop a transparent GHG inventory. Collect Earth (CE), developed by the Food and Agriculture Organization of the United Nations (FAO), is a free, user-friendly, and open-source tool for collecting activity data for the LULUCF sector. CE assists countries in developing GHG inventories by providing consistent and complete land representation. This article reports an estimate of land use and land-use change dynamics in Kyrgyzstan, based on analyzing 13,414 1-hectare (ha) sampling units through an augmented visual interpretation approach using satellite imagery at the very high spatial and temporal resolution available through the Google Earth platform. The results show that in 2019, forests covered 1.36 million ha or 6.83% of the total land with a 6.23% uncertainty. This estimate was 5 to 16% higher than previous estimates, detecting an additional 63,024 to 188,164 ha of forestland that had not been reported previously. The new estimates suggest an average increase of 10.4% in the current forestlands of Kyrgyzstan.

The role of rice cultivation in changes in atmospheric methane concentration and the Global Methane Pledge.

Resumption of the increase in atmospheric methane (CH4 ) concentrations since 2007 is of global concern and may partly have resulted from emissions from rice cultivation. Estimates of CH4 emissions from rice fields and abatement potential are essential to assess the contribution of improved rice management in achieving the targets of the Global Methane Pledge agreed upon by over 100 countries at COP26. However, the contribution of CH4 emissions from rice fields to the resumed CH4 growth and the global abatement potential remains unclear. In this study, we estimated the global CH4 emissions from rice fields to be 27 ± 6 Tg CH4 year-1 in the recent decade (2008-2017) based on the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. The trend of CH4 emissions from rice cultivation showed an increase followed by no significant change and then, a stabilization over 1990-2020. Consequently, the contribution of CH4 emissions from rice fields to the renewed increase in atmospheric CH4 concentrations since 2007 was minor. We summarized the existing low-cost measures and showed that improved water and straw management could reduce one-third of global CH4 emissions from rice fields. Straw returned as biochar could reduce CH4 emissions by 12 Tg CH4 year-1 , equivalent to 10% of the total reduction of all anthropogenic emissions. We conclude that other sectors than rice cultivation must have contributed to the renewed increase in atmospheric CH4 concentrations, and that optimizing multiple mitigation measures in rice fields could contribute significantly to the abatement goal outlined in the Global Methane Pledge.

Estimating Regional Methane Emission Factors from Energy and Agricultural Sector Sources Using a Portable Measurement System: Case Study of the Denver-Julesburg Basin.

Methane (CH4), a powerful greenhouse gas (GHG), has been identified as a key target for emission reduction in the Paris agreement, but it is not currently clear where efforts should be focused to make the greatest impact. Currently, activity data and standard emission factors (EF) are used to generate GHG emission inventories. Many of the EFs are globally uniform and do not account for regional variability in industrial or agricultural practices and/or regulation. Regional EFs can be derived from top-down emissions measurements and used to make bespoke regional GHG emission inventories that account for geopolitical and social variability. However, most large-scale top-down approaches campaigns require significant investment. To address this, lower-cost driving surveys (DS) have been identified as a viable alternative to more established methods. DSs can take top-down measurements of many emission sources in a relatively short period of time, albeit with a higher uncertainty. To investigate the use of a portable measurement system, a 2260 km DS was conducted throughout the Denver-Julesburg Basin (DJB). The DJB covers an area of 8000 km2 north of Denver, CO and is densely populated with CH4 emission sources, including oil and gas (O and G) operations, agricultural operations (AGOs), lakes and reservoirs. During the DS, 157 individual CH4 emission sources were detected; 51%, 43% and 4% of sources were AGOs, O and G operations, and natural sources, respectively. Methane emissions from each source were quantified using downwind concentration and meteorological data and AGOs and O and G operations represented nearly all the CH4 emissions in the DJB, accounting for 54% and 37% of the total emission, respectively. Operations with similar emission sources were grouped together and average facility emission estimates were generated. For agricultural sources, emissions from feedlot cattle, dairy cows and sheep were estimated at 5, 31 and 1 g CH4 head-1 h-1, all of which agreed with published values taken from focused measurement campaigns. Similarly, for O and G average emissions for well pads, compressor stations and gas processing plants (0.5, 14 and 110 kg CH4 facility-1 h-1) were in reasonable agreement with emission estimates from intensive measurement campaigns. A comparison of our basin wide O and G emissions to measurements taken a decade ago show a decrease of a factor of three, which can feasibly be explained by changes to O and G regulation over the past 10 years, while emissions from AGOs have remained constant over the same time period. Our data suggest that DSs could be a low-cost alternative to traditional measurement campaigns and used to screen many emission sources within a region to derive representative regionally specific and time-sensitive EFs. The key benefit of the DS is that many regions can be screened and emission reduction targets identified where regional EFs are noticeably larger than the regional, national or global averages.

Roots and other residues from leys with or without red clover: Quality and effects on N2O emission factors in a partly frozen soil following autumn ploughing.

Revised IPCC guidelines assume that a constant share of N in decomposing crop residues is directly emitted as N2O (emission factor: EFN2O), and calculate the amount of nitrogen (N) in non-removable residues of temporary grasslands proportionally to the average annual herbage yield. However, EFN2O depends on the intrinsic quality of the residues and their interactions with environmental conditions. Only a few field studies on N2O emissions from grassland renewal are available, and none have simultaneously quantified the N amount and quality of non-removable residues (roots and stubble). To gain insight into the effect of non-removable residue quality on EFN2O, we studied the amount and quality of roots and stubble and their effect on EFN2O following the ploughing of three-year-old swards. The measured amount of N in non-removable residues was approximately 20, 25, and 31 kg N per 1 Mg average annual dry matter yield in grass, red clover-grass, and red clover, and 70-83% of it was below ground. However, the EFN2O of non-removable residues measured over 252 days was lower (0.24%, SE = 14% for grass and red clover-grass) than the IPCC default value (0.6%, CV: 50%) for wet regions, although within the uncertainty margin, and was significantly lower than the EFN2O of incorporated herbage, which was related to differences in EFCO2. We advocate for more specific studies that separate the effects of belowground and aboveground residues (AGR), considering the possibility of simplifying the accounting of N2O emissions from belowground residues while improving that of non-removable AGR from temporary grasslands and other green crops. We observed the accumulation of N2O in the frozen soil under snow, which was released during diurnal percolation of meltwater. N2O emissions from frozen soil accounted for 30% or more of the total emissions.

Prediction of enteric methane production and yield in dairy cattle using a Latin America and Caribbean database.

Successful mitigation efforts entail accurate estimation of on-farm emission and prediction models can be an alternative to current laborious and costly in vivo CH4 measurement techniques. This study aimed to: (1) collate a database of individual dairy cattle CH4 emission data from studies conducted in the Latin America and Caribbean (LAC) region; (2) identify key variables for predicting CH4 production (g d-1) and yield [g kg-1 of dry matter intake (DMI)]; (3) develop and cross-validate these newly-developed models; and (4) compare models' predictive ability with equations currently used to support national greenhouse gas (GHG) inventories. A total of 42 studies including 1327 individual dairy cattle records were collated. After removing outliers, the final database retained 34 studies and 610 animal records. Production and yield of CH4 were predicted by fitting mixed-effects models with a random effect of study. Evaluation of developed models and fourteen extant equations was assessed on all-data, confined, and grazing cows subsets. Feed intake was the most important predictor of CH4 production. Our best-developed CH4 production models outperformed Tier 2 equations from the Intergovernmental Panel on Climate Change (IPCC) in the all-data and grazing subsets, whereas they had similar performance for confined animals. Developed CH4 production models that include milk yield can be accurate and useful when feed intake is missing. Some extant equations had similar predictive performance to our best-developed models and can be an option for predicting CH4 production from LAC dairy cows. Extant equations were not accurate in predicting CH4 yield. The use of the newly-developed models rather than extant equations based on energy conversion factors, as applied by the IPCC, can substantially improve the accuracy of GHG inventories in LAC countries.

Emerging reporting and verification needs under the Paris Agreement: How can the research community effectively contribute?

Greenhouse gas (GHG) emission inventories represent the link between national and international political actions on climate change, and climate and environmental sciences. Inventory agencies need to include, in national GHG inventories, emission and removal estimates based on scientific data following specific reporting guidance under the United Nation Framework Convention on Climate Change (UNFCCC) and the Paris Agreement, using the methodologies defined in the Intergovernmental Panel on Climate Change (IPCC) Guidelines. Often however, research communities and inventory agencies have approached the problem of climate change from different angles and by using terminologies, metrics, rules and approaches that do not always match. This is particularly true dealing with "Land Use, Land-Use Change and Forestry" (LULUCF), the most challenging among the inventory sectors to deal with, mainly because of high level of complexity of its carbon dynamics and the difficulties in disaggregating the fluxes between those caused by natural and anthropogenic processes. In this paper, we facilitate the understanding by research communities of the current (UNFCCC) and future (under the Paris Agreement) reporting requirements, and we identify the main issues and topics that should be considered when targeting improvement of the GHG inventory. In relation to these topics, we describe where and how the research community can contribute to producing useful inputs, data, methods and solutions for inventory agencies and policy makers, on the basis of available literature. However, a greater effort by both communities is desirable for closer cooperation and collaboration, for data sharing and the understanding of respective and common aims.

Determination of the carbon footprint of all Galician production and consumption activities: Lessons learnt and guidelines for policymakers.

Galicia is an Autonomous Community located in the north-west of Spain. As a starting point to implement mitigation and adaptation measures to climate change, a regional greenhouse gas (GHG) inventory is needed. So far, the only regional GHG inventories available are limited to the territorial emissions of those production activities which are expected to cause major environmental degradation. An alternative approach has been followed here to quantify all the on-site (direct) and embodied (indirect) GHG emissions related to all Galician production and consumption activities. The carbon footprint (CF) was calculated following the territorial life cycle assessment (LCA) methodology for data collection, that combines bottom-up and top-down approaches. The most up-to-date statistical data and life cycle inventories available were used to compute all GHG emissions. This case study represents a leap of scale when compared to existing studies, thus addressing the issue of double counting, which arises when considering all the production activities of a large region. The CF of the consumption activities in Galicia is 17.8 ktCO2e/year, with 88% allocated to Galician inhabitants and 12% to tourist consumption. The proposed methodology also identifies the main important contributors to GHG emissions and shows where regional reduction efforts should be made. The major contributor to the CF of inhabitants is housing (32%), followed by food consumption (29%). Within the CF of tourist consumption, the share of transport is highest (59%), followed by housing (26%). The CF of Galician production reaches 34.9 MtCO2e/y, and its major contributor is electricity production (21%), followed by food manufacturing (19%). Our results have been compared to those reported for other regions, actions aimed at reducing GHG emissions have been proposed, and data gaps and limitations identified.

Leachate treatment in landfills is a significant N2O source.

The importance of methane (CH4) emissions from landfills has been extensively documented, while the nitrous oxide (N2O) emissions from landfills are considered negligible. In this study, three landfills were selected to measure CH4 and N2O emissions using the static chamber method. Dongbu (DB) and Dongfu (DF) landfills, both located in Xiamen city, Fujian Province, were classified as sanitary. The former started to receive solid waste from Xiamen city in 2009, and the latter was closed in 2009. Nanjing (NJ) landfill, located in Nanjing county, Fujian Province, was classified as managed. Results showed that for the landfill reservoirs, CH4 emissions were significant, while N2O emissions occurred mainly in operating areas (on average, 16.3 and 19.0mgN2Om-2h-1 for DB and NJ landfills, respectively) and made a negligible contribution to the total greenhouse gas emissions in term of CO2 equivalent. However, significant N2O emissions were observed in the leachate treatment systems of sanitary landfills and contributed 72.8% and 45.6% of total emissions in term of CO2 equivalent in DB and DF landfills, respectively. The N2O emission factor (EF) of the leachate treatment systems was in the range of 8.9-11.9% of the removed nitrogen. The total N2O emissions from the leachate treatment systems of landfills in Xiamen city were estimated to be as high as 8.55gN2O-Ncapita-1yr-1. These results indicated that N2O emissions from leachate treatment systems of sanitary landfills were not negligible and should be included in national and/or local inventories of greenhouse gas emissions.

Scaling methane emissions in ruminants and global estimates in wild populations.

Methane (CH4) emissions by human activities have more than doubled since the 1700s, and they contribute to global warming. One of the sources of CH4 is produced by incomplete oxidation of feed in the ruminant's gut. Domestic ruminants produce most of the emissions from animal sources, but emissions by wild ruminants have been poorly estimated. This study (i) scales CH4 against body mass in 503 experiments in ruminants fed herbage, and assesses the effect of different sources of variation, using published and new data; and (ii) it uses these models to produce global estimates of CH4 emissions from wild ruminants. The incorporation of phylogeny, diet and technique of measuring in to a model that scales log10 CH4gd-1 against log10 body mass (kg), reduces the slope, from 1.075 to 0.868, making it not significantly steeper than the scaling coefficient of metabolic requirements to body mass. Scaling models that include dry matter intake (DMI) and dietary fiber indicate that although both increase CH4, dietary fiber depresses CH4 as the levels of DMI increases. Cattle produces more CH4 per unit of DMI than red deer, sheep or goat, and there are no significant differences between CH4 produced by red deer and sheep. The average estimates of global emissions from wild ruminants calculated using different models are smaller (1.094-2.687Tgy-1) than those presented in the reports of the Intergovernmental Panel on Climate Change (15Tgyr-1). Potential causes to explain such discrepancy are the uncertainty on the world's wild ruminant population size, and the use of methane output from cattle, a high methane producer, as representative methane output of wild ruminants. The main limitation researchers' face in calculating accurate global CH4 emissions from wild ungulates is a lack of reliable information on their population sizes.