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Methane emissions in Canada have both anthropogenic and natural sources. Anthropogenic emissions are estimated to be 4.1 Tg a−1 from 2010–2015 in the National Inventory Report submitted to the United Nation's Framework Convention on Climate Change (UNFCCC). Natural emissions, which are mostly due to boreal wetlands, are the largest methane source in Canada and highly uncertain, on the order of ∼ 20 Tg a−1 in biosphere process models. Aircraft studies over the last several years have provided “snapshot” emissions that conflict with inventory estimates. Here we use surface data from the Environment and Climate Change Canada (ECCC) in situ network and space-borne data from the Greenhouse Gases Observing Satellite (GOSAT) to determine 2010–2015 anthropogenic and natural methane emissions in Canada in a Bayesian inverse modelling framework. We use GEOS-Chem to simulate anthropogenic emissions comparable to the National Inventory and wetlands emissions using an ensemble of WetCHARTS v1.0 scenarios in addition to other minor natural sources. We conduct a comparative analysis of the monthly natural emissions and yearly anthropogenic emissions optimized by surface and satellite data independently. Mean 2010–2015 posterior emissions using ECCC surface data are 6.0 ± 0.4 Tg a−1 for total anthropogenic and 11.6 ± 1.2 Tg a−1 for total natural emissions. These results agree with our posterior emissions of 6.5 ± 0.7 Tg a−1 for total anthropogenic and 11.7 ± 1.2 Tg a−1 for total natural emissions using GOSAT data. The seasonal pattern of posterior natural emissions using either dataset shows slower to start emissions in the spring and a less intense peak in the summer compared to the mean of WetCHARTS scenarios. We combine ECCC and GOSAT data to characterize limitations towards sectoral and provincial-level inversions. We estimate energy + agriculture emissions to be 5.1 ± 1.0 Tg a−1, which is 59 % higher than the national inventory. We attribute 39 % higher anthropogenic emissions to Western Canada than the prior. Natural emissions are lower across Canada. Inversion results are verified against independent aircraft data and surface data, which show better agreement with posterior emissions. This study shows a readjustment of the Canadian methane budget is necessary to better match atmospheric observations with lower natural emissions partially offset by higher anthropogenic emissions.

The data on the assessment of the dynamics of forested lands of the Republic of Belarus are presented. The characteristics of the forest fund for the period 1994–2019 are presented. Based on the materials of the provisions of international treaties, documents adopted within the framework of the implementation of the UN Framework Convention on Climate Change at the international and national levels, including the Paris Agreement, the provisions of regulatory legal acts of the Republic of Belarus, the results of scientific research, information from the Ministry of Forestry, according to the data of the State Forest Cadastre, an assessment of greenhouse gases in the forest fund of the Republic of Belarus was carried out. CO2 emissions and sinks from forestry have been calculated in accordance with the IPCC Guidelines for National Greenhouse Gas Inventories using the stock-difference method. It was found that as a result of purposeful work on reforestation and reforestation over a 26-year period, a positive dynamics of the forest fund was achieved in the Republic of Belarus: the forested area increased by 919,6 thousand ha from 7360,7 thousand ha to 8280,3 thousand ha; the forest cover of the territory of the republic increased by 4,3 % and reached 39,9 %; the total standing timber stock increased by 739,5 million m3 from 1092,3 to 1831,8 million m3 (including in mature and over-mature stands — by 300,3 million m3 and amounted to 348,8 million m3); the reserve per hectare of forested land increased by 72,8 m3 and amounted to 221,2 m3/ha; the stock of mature and over-mature stands increased by an average of 52,6 m3 and reached 273,9 m3/ha.

Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States, recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5–2× greater compared to official greenhouse gas inventory (GHGI) estimates, with the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions, for the production-segment only, that agrees within error with recent syntheses of site-level field studies and allows for isolation of equipment-level contributions. We find that unintentional emissions from liquid storage tanks and other equipment leaks are the largest contributors to divergence with the GHGI. If our proposed method were adopted in the United States and other jurisdictions, inventory estimates could better guide CH4 mitigation policy priorities., Methane emissions from oil and gas systems are underestimated in official inventories. Here the authors synthesize thousands of field measurements and develop an inventory-based model for a better understanding of why this underestimation exists and how it can be fixed.

The New Zealand Government requires gross emissions of biogenic methane (CH4) to be reduced to 10% below 2017 levels by 2030. However, the amount of CH4 emissions reported in the ‘Manure Management’ category of New Zealand’s Greenhouse Gas Inventory has increased by 123% since 1990. The purpose of this research was to determine the effect of treating farm dairy effluent (FDE) with polyferric sulphate (PFS) on CH4 emissions. The effect of treating FDE with PFS on CH4 emissions was measured at four scales: (i) 1-L gas jars in the laboratory, (ii) 1.1-m-deep × 150-mm-diameter pipe microcosms in the laboratory, (iii) large 3.4-m-deep × 0.47-m-diameter pipes on-farm, and (iv) 2-m-deep × 8.4-m-diameter (100,000 L) commercial effluent storage tanks on a farm. Gas emissions were captured by repeated discrete sampling and CH4 concentrations were determined by gas chromatography. We discovered that treating FDE with PFS at an average rate of 220 mg Fe L−1 of FDE reduced CH4 emissions by up to 99% and that this effect continued for an extended period of time (up to 2 months) after treatment. The PFS treatment also reduced CO2 emissions by approximately 50% and reduced hydrogen sulphide emissions. PFS treatment resulted in a small increase in nitrous oxide (N2O) emissions, but these emissions were very low and only represented

We present an updated fuel-based oil and gas (FOG) inventory with estimates of nitrogen oxide (NOx) emissions from oil and natural gas production in the contiguous US (CONUS). We compare the FOG inventory with aircraft-derived ("top-down") emissions for NOx over footprints that account for ∼25% of US oil and natural gas production. Across CONUS, we find that the bottom-up FOG inventory combined with other anthropogenic emissions is on average within ∼10% of top-down aircraft-derived NOx emissions. We also find good agreement in the trends of NOx from drilling- and production-phase activities, as inferred by satellites and in the bottom-up inventory. Leveraging tracer-tracer relationships derived from aircraft observations, methane (CH4) and non-methane volatile organic compound (NMVOC) emissions have been added to the inventory. Our total CONUS emission estimates for 2015 of oil and natural gas are 0.45 ± 0.14 Tg NOx/yr, 15.2 ± 3.0 Tg CH4/yr, and 5.7 ± 1.7 Tg NMVOC/yr. Compared to the US National Emissions Inventory and Greenhouse Gas Inventory, FOG NOx emissions are ∼40% lower, while inferred CH4 and NMVOC emissions are up to a factor of ∼2 higher. This suggests that NMVOC/NOx emissions from oil and gas basins are ∼3 times higher than current estimates and will likely affect how air quality models represent ozone formation downwind of oil and gas fields.

We designed a new approach for modeling the nitrous oxide (N2O) derived from nitrogen (N) mineralization associated with loss of soil organic matter (SOM) that meets the current IPCC guidelines (GL...

The biennial report of Vietnam includes updated information on the greenhouse gas emissions for the base years which are specified by the United Nations Framework Convention on Climate Change for reporting on greenhouse gas emissions by member nations of the Intergovernmental Panel on Climate Change. The estimation of greenhouse gas emissions in general and carbon emissions in particular in the field of land use, land use change, and forestry using advanced technology to provide the input data was recommended. Remote sensing technology with transparency, multi-time characteristics, and wide coverage is useful in this area. An experiment on carbon emission estimation was carried out based on land cover change over ten years between 2002 and 2012. The results obtained by remote sensing data classification for the land cover categories achieved a reliability of 68% for the year 2002 and 67% for the year 2012. Data in relation to the land cover change, soil zoning, and ecological/climate zoning in the Vietnamese mainland, through the process of integrating, processing, and synthesizing data, and using the reported activity data and carbon emission coefficients, were input into the Agriculture and Land Use Greenhouse Gas Inventory Software for carbon emission estimations based on the quality control and quality assurance work.

A key uncertainty in quantifying dead wood carbon (C) stocks—which comprise ~8% of total forest C pools globally—is a lack of accurate dead wood C fractions (CFs) that are employed to convert dead woody biomass into C. Most C estimation protocols utilize a default dead wood CF of 50%, but live tree studies suggest this value is an over-estimate. Here, we compile and analyze a global database of dead wood CFs in trees, showing that dead wood CFs average 48.5% across forests, deviating significantly from 50%, and varying systematically among biomes, taxonomic divisions, tissue types, and decay classes. Utilizing data-driven dead wood CFs in tropical forests alone may correct systematic overestimates in dead wood C stocks of ~3.0 Pg C: an estimate approaching nearly the entire dead wood C pool in the temperate forest biome. We provide for the first time, robust empirical dead wood CFs to inform global forest C estimation., Tree mortality is increasing with climate change, which suggests that the biomass of dead wood is likely becoming more and more important to the global carbon cycle. Here, the authors perform a meta-analysis of the carbon content of dead wood and find that past estimates of total forest carbon were overestimated.

After the Paris Agreement, the Republic of Korea also has own Nationally Determined Contributions (NDCs), and forest sector has to sequestrate 22 million tons of CO₂ eq. by 2030 and to develop a national inventory and Land‐Use, Land Use Change, and Forestry (LULUCF) system. However, forest activity data have been neglected in the assessment process, because they have been partially recorded from various data sources. Therefore, this study collects available data to represent forest activity data and integrates them considering spatial availability based on Intergovernmental Panel on Climate Change (IPCC) guidelines and approaches from the Kyoto Protocol. National and private spatial data were collected, and the available data as forest activity data were selected. Subsequently, forest management records on address‐based locations were converted to spatial data by spatial joining and overlying. As a result, around 1.25 million forest management and afforestation recodes are available. Based on these records, the estimated average forest management rate considering regional distribution is 31.2% during 2013‐2017, and the estimated forest management rate reflecting average values for missing management recodes is 43.1% during 2003‐2017. This study suggests a spatial approach to develop proper calculation of forest management rate despite differences in forest management rate caused by missing data from filed activities and limitation of spatial data during overlaying analysis. Therefore, more forest data are needed to secure the future development of a national forest inventory.

Stabilizing the global climate within safe bounds will require greenhouse gas (GHG) emissions to reach net zero within a few decades. Achieving this is expected to require removal of CO2 from the atmosphere to offset some hard-to-eliminate emissions. There is, therefore, a clear need for GHG accounting protocols that quantify the mitigation impact of CO2 removal practices, such as biochar sequestration, that have the potential to be deployed at scale. Here, we have developed a GHG accounting methodology for biochar application to mineral soils using simple parameterizations and readily accessible activity data that can be applied at a range of scales including farm, supply chain, national, or global. The method is grounded in a comprehensive analysis of current empirical data, making it a robust method that can be used for many applications including national inventories and voluntary and compliance carbon markets, among others. We show that the carbon content of biochar varies with feedstock and production conditions from as low as 7% (gasification of biosolids) to 79% (pyrolysis of wood at above 600 °C). Of this initial carbon, 63–82% will remain unmineralized in soil after 100 years at the global mean annual cropland-temperature of 14.9 °C. With this method, researchers and managers can address the long-term sequestration of C through biochar that is blended with soils through assessments such as GHG inventories and life cycle analyses., In this article, we develop a simple and robust empirical model of the avoided greenhouse gas (GHG) emissions due to addition of biochar to mineral soils, suitable for use in GHG inventories or life-cycle assessments.

There are significant inter-annual fluctuations of growing stock volume changes of living trees estimated by the Lithuanian National Forest Inventory (NFI). In the current study, we compared two sources of information on forest productivity: conventional NFI data and dendrochronological data based on tree cores collected in parallel with the measurements of the fourth Lithuanian NFI cycle during 2013–2017 on the same permanent plots (total number of cores was 4967). The main finding is that the dendrochronological basal area increment data confirmed the depression of gross stand volume increment around 2006–2007 (based on Lithuanian NFI measurements in 2008–2009), followed by a steep increase during 2008–2011 (NFI from 2010–2013). The findings explain the differences between projected growing stock volume change, which have been used for forest reference level estimation according to land use, land-use change and forestry sector regulation, and the one recently provided in National Greenhouse Gas Inventory Reports. Key words: Growing stock volume change, basal area increment, forest reference level, greenhouse gas reporting

This study was conducted to suggest application of a new stem volume for the forest carbon stocks in South Korea. We recalculated stem volume using the Kozak parameter and equations based on the old stem volume (approach one) and new stem volume (approach two). Also, we calculated carbon stock and changes using the estimated stem volume and country‐specific emission factors. As a result, growing stock with approach two was higher than that with approach one, and there was a statistically significant difference (p

Understanding the environmental implications of activated carbon (AC) produced from diverse biomass feedstocks is critical for biomass screening and process optimization for sustainability. Many st...

Global warming caused by greenhouse gas emissions is a threat to the survival of humans and other organisms living on Earth. The greenhouse gases released from the dairy sector of New Zealand accounted for 18.2 Mt of carbon dioxide equivalent (CO2-eq) in 2016, mainly from methane generated by enteric fermentation in the rumen of milking cows and their replacement stock. A productivity commission established by the New Zealand government in 2018 estimated that methane emissions from livestock needed to be reduced from 2016 levels by 10 to 22% by 2050 (i.e., 2.8 to 6.1 million t lower), so as to restrict future increases in global temperature to less than 2°C. In this study, we evaluated genetic effects of 8 traits included in the New Zealand national dairy breeding objective, on 3 types of methane emissions metrics: gross methane emissions per dairy cow per year (E), methane emissions per hectare (EH), and methane emissions intensity per milk protein equivalents (EI), as carbon dioxide equivalents. These effects were then aligned with recent genetic changes in these traits brought about by breeding schemes, so that the overall genetic trend for each metric into the future was estimated. The results showed that EH and EI are currently being reduced at rates of -2.31 kg of CO2-eq per hectare per cow per year (current average is 6,915 kg of CO2-eq/ha per cow per year) and -0.04 kg of CO2-eq per kg of milk protein equivalents per cow per year, respectively (current average is 9.7 kg of CO2-eq/milk protein-eq per cow per year). These improvements directly reflect increased production efficiency through selection for farm profitability. If the pastureland area in New Zealand remains the same, at the same productivity and with no increase in supplementation rates from external land sources, in 20 years gross emissions would be reduced by only 0.6%, or 89 Mt. Increased production efficiency will likely result in corresponding changes to the stocking rate, to fully utilize the pasture resource available, and might further encourage a greater rate of intensification via supplementary feeding. Both consequences of current genetic selection could negate any benefits for the national greenhouse gas inventory. New selection criteria for reduced methane production are needed to help achieve New Zealand's national methane reduction targets.

We used the Agriculture and Land Use National Greenhouse Gas Inventory Software to estimate the total greenhouse gas (GHG) emissions from the Nigerian agriculture sector in 2010. We went ahead to project future GHG emissions up to 2050. Two alternative GHG mitigation scenarios such as moderate (MS) and aggressive (AS) scenarios were developed and examined. Our results showed that total GHG emissions from Nigerian agriculture in 2010 were around 34.9 million tonnes of carbon dioxide equivalent. GHG emissions from livestock accounted for about 69.2 % of the total emissions, making it the largest source of GHG emissions in the sector. Nigeria’s agriculture GHG emissions are expected to increase by 94 % in 2050 relative to 2010 levels. Mitigation strategies in the Nigerian agriculture sector that do not compromise food security are limited. However, with the implementation of different GHG mitigation strategies in the alternative scenarios, emissions are expected to fall by around 13.2 % and 26.7 % by 2050 in the MS and AS, respectively, compared to the baseline scenario. While the mitigation potentials are significant, we argue that robust and dedicated policies are required to accelerate climate-smart agriculture in Nigeria. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13280-019-01293-9) contains supplementary material, which is available to authorised users.

This paper reports a greenhouse gas inventory of a synthetic fibre industrial plant from 2008 to 2014. Using long-term inventory data, a mathematical model was designed to forecast tCO2e emission o...

Here we provide a critical and comprehensive review of recent developments in the impact of protected cultivation on climate change and map the factors involved. Some possible ways to reduce greenhouse gas emissions are suggested and some sustainable adaptation strategies are indicated. We expand our survey of the existing research to the entire production system, including greenhouse structure, energy, electricity, growing media, and fertilizers. Technical and conceptual innovations are discussed, along with structural solutions, such as screenhouses. We believe that this work will contribute to facilitating reductions in direct and indirect emissions from the greenhouse gas inventory while simultaneously reducing the waste from protected cultivation systems. Moreover, we believe that this review will shed new light on some of these approaches and suggest new ways for cleaner production in controlled-environment systems. The transition to sustainable protected cultivation systems needs to be economically viable – innovative adaptations are required. We recommend adaptations such as maximum insulation, smart climate control, sustainable energy sources such as biogas, photovoltaics and geothermal energy, as well as new concepts for crop production to reduce the impact of protected cultivation on climate change.

We use 2010–2015 observations of atmospheric methane columns from the GOSAT satellite instrument in a global inverse analysis to improve estimates of methane emissions and their trends over the period, as well as the global concentration of tropospheric OH (the hydroxyl radical, methane's main sink) and its trend. Our inversion solves the Bayesian optimization problem analytically including closed-form characterization of errors. This allows us to (1) quantify the information content from the inversion towards optimizing methane emissions and its trends, (2) diagnose error correlations between constraints on emissions and OH concentrations, and (3) generate a large ensemble of solutions testing different assumptions in the inversion. We show how the analytical approach can be used, even when prior error standard deviation distributions are lognormal. Inversion results show large overestimates of Chinese coal emissions and Middle East oil and gas emissions in the EDGAR v4.3.2 inventory but little error in the United States where we use a new gridded version of the EPA national greenhouse gas inventory as prior estimate. Oil and gas emissions in the EDGAR v4.3.2 inventory show large differences with national totals reported to the United Nations Framework Convention on Climate Change (UNFCCC), and our inversion is generally more consistent with the UNFCCC data. The observed 2010–2015 growth in atmospheric methane is attributed mostly to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH trends is small in comparison. We find that the inversion provides strong independent constraints on global methane emissions (546 Tg a−1) and global mean OH concentrations (atmospheric methane lifetime against oxidation by tropospheric OH of 10.8±0.4 years), indicating that satellite observations of atmospheric methane could provide a proxy for OH concentrations in the future.

Agricultural industries are faced with the challenge to reduce their emissions of greenhouse gases (GHG) such as nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4). Approximately 27% of the GHG emissions generated by agriculture and 80% of the GHG emissions generated by livestock are in the form of CH4 from enteric fermentation and manure management. Two feed additives that have been shown to decrease enteric CH4 emissions are 3-nitrooxypropanol (3-NOP) and nitrate. However, data are lacking on the net impact of these CH4 mitigating additives on whole farm GHG emissions across different production systems. The objectives of this partial life cycle assessment (LCA) were: 1) to analyse the effect of 3-NOP and nitrate on whole farm GHG emissions of Australian and Canadian beef and dairy farms, and 2) to analyse the effect of different strategies of 3-NOP and nitrate feeding on whole farm GHG emissions. Two Australian dairy farms (ADF), one Australian beef farm (ABF), one Canadian dairy farm (CDF) and one Canadian beef farm (CBF) were modelled over the productive lifespans of dairy and beef herds. Australian farm GHG emissions were estimated based on the Australian National Greenhouse Gas Inventory method using the Greenhouse Accounting Framework calculators for beef and dairy. For the Canadian farms, total GHG emissions were estimated using Holos 3.0.3, a whole-farm software model. For all farms, the system boundary of the partial LCA was defined as the farm gate, including emissions associated with on-farm activities and emissions associated with production and transport of major production inputs. Both additives decreased whole farm GHG emissions; however, 3-NOP had a greater effect than nitrate. Feeding 3-NOP but not nitrate could be economical for both beef and dairy farms, depending on the cost of 3-NOP. It is concluded that 3-NOP can make an important contribution to reducing whole farm GHG emissions; however, a carbon offset method would have to be in place to incentivize its use in the livestock industries.

Fugitive methane emissions from coal mining activities have been frequently talked about in the literature due to concerns about climate change. However, indirect and direct CO2 emissions m...

Forest soils represent a large carbon pool and already small changes in this pool may have an important effect on the global carbon cycle. To predict the future development of the soil organic carbon (SOC) pool, well-validated models are needed. We applied the litter and soil carbon model Yasso15 to 1838 plots of the German national forest soil inventory (NFSI) for the period between 1985 and 2014 to enables a direct comparison to the NFSI measurements. In addition, to provide data for the German Greenhouse Gas Inventory, we simulated the development of SOC with Yasso15 applying a climate projection based on the RCP8.5 scenario. The initial model-calculated SOC stocks were adjusted to the measured ones in the NFSI. On average, there were no significant differences between the simulated SOC changes (0.25 ± 0.10 Mg C ha−1 a−1) and the NFSI data (0.39 ± 0.11 Mg C ha−1 a−1). Comparing regional soil-unit-specific aggregates of the SOC changes, the correlation between both methods was significant (r2 = 0.49) although the NFSI values had a wider range and more negative values. In the majority of forest types, representing 75% of plots, both methods produced similar estimates of the SOC balance. Opposite trends were found in mountainous coniferous forests on acidic soils. These soils had lost carbon according to the NFSI (−0.89 ± 0.30 Mg C ha−1 a−1) whereas they had gained it according to Yasso15 (0.21 ± 0.10 Mg C ha−1 a−1). In oligotrophic pine forests, the NFSI indicated high SOC gains (1.36 ± 0.17 Mg C ha−1 a−1) and Yasso15 much smaller (0.29 ± 0.10 Mg C ha−1 a−1). According to our results, German forest soils are a large carbon sink. The application of the Yasso15 model supports the results of the NFSI. The sink strength differs between forest types possibly because of differences in organic matter stabilisation.

To report changes in land use, the forestry sector, and land-use change matrix (LUCM), monitoring is necessary in South Korea to adequately respond to the Post-2020 climate regime. To calculate the greenhouse gas statistics observing the principle of transparency required by the Climate Change Convention, a consistent nationwide land-use classification and LUCM are required. However, in South Korea, land-use information is available from the 5th National Forest Inventory conducted in 2006 onwards, therefore, developing methods to determine historical LUCM information, including the base year required by the Intergovernmnetal Panel on Climate Change (IPCC), is essential. To determine the optimal sampling intensity for measuring systematic land-use changes and to estimate the corresponding area of land-use categories for previously unmeasured years, seven intensities—2 × 2 km to 8 × 8 km—were tested using the areas of the 3rd and 4th aerial photographs in time series for forestland, cropland, grassland, wetland, and settlements, according to their standard deviations and estimates of uncertainty. Analyses of statistical accuracy, statistical efficiency, economic efficiency, and convenience showed that a sampling intensity of 4 × 4 km was ideal. Additionally, the categorized areas of unmeasured land-use years were calculated through linear interpolation and extrapolation. Our LUCM can be utilized for developing a national greenhouse gas inventory.

In China, research on winter heating and energy saving for residential buildings mainly focuses on urban residences rather than rural ones. According to the 2018 China Building Energy Consumption Research Report, rural residential buildings emit about 423 million tons of carbon, accounting for 21% of the country’s total carbon emissions. According to the research on China’s greenhouse gas inventory, the main sources of carbon emissions in rural areas are from cooking and the burning of fuelwood and biomass for heating in winter. In this study, the southern Shaanxi area, which is hot in summer and cold in winter, was selected as the research site, and a fire wall system was planned that combines cooking and heating facilities in residential buildings. The system uses the heat generated by cooking and the heat storage capacity of the wall, as well as the principle of thermal radiation and heat convection, to increase the indoor temperature. The advantage is that the hot air generated is mainly concentrated in the inside of the wall, which reduces the direct contact with the cold outdoor air and avoids excess heat loss. In this study, in addition to considering the influence of the cooking fire wall system on the indoor temperature, the difference in the outer wall with or without solar thermal radiation was also considered. The research results show that the use of a cooking fire wall heating system reduces the annual heat load of the building to 440.8318 KW·h, which is a reduction rate of 7.91%. When there is solar radiation on the outer wall, the annual thermal load of the building is reduced by 1104.723 kW·h, and the reduction rate is 19.84%.

Greenhouse gas emissions of the transportation sector of the Central Luzon State University were estimated for the annual projection of Carbon Dioxide emissions (CO2e). A total of 14 vehicles used by 15 colleges and departments were analyzed which contributes to the CO2e of the university. The CO2e of vehicles varied in terms of diesel consumption, kilometers traveled overall load weight, kilometer per liter coefficient, driving condition, and overall vehicle status. The total distance traveled by the 14 vehicles was 27,384.6101 km consuming a total of 3,262.71 liters of Diesel and emitting a total of 8,613.553 kg of CO2e. Greenhouse gas inventory (GHGI) was incorporated into energy policy recommendations which are projected to promote awareness in the community with the goal of reducing or offsetting CO2e.

Research Highlights: The estimation of soil and litter carbon stocks by the Land Use, Land-Use Changes, and Forestry (LULUCF) sectors has the potential to improve reports on national greenhouse gas (GHG) inventories. Background and Objectives: Forests are carbon sinks in the LULUCF sectors and therefore can be a comparatively cost-effective means and method of GHG mitigation. Materials and Methods: This study was conducted to assess soil at 0&ndash, 30 cm and litter carbon stocks using the National Forest Inventory (NFI) data and random forest (RF) models, mapping their carbon stocks. The three main types of forest in South Kora were studied, namely, coniferous, deciduous, and mixed. Results: The litter carbon stocks (t C ha&minus, 1) were 4.63 &plusmn, 0.18 for coniferous, 3.98 &plusmn, 0.15 for mixed, and 3.28 &plusmn, 0.13 for deciduous. The soil carbon stocks (t C ha&minus, 1) were 44.11 &plusmn, 1.54 for deciduous, 35.75 &plusmn, 1.60 for mixed, and 33.96 &plusmn, 1.62 for coniferous. Coniferous forests had higher litter carbon stocks while deciduous forests contained higher soil carbon stocks. The carbon storage in the soil and litter layer increased as the forest grew older, however, a significant difference was found in several age classes. For mapping the soil and litter carbon stocks, we used four random forest models, namely RF1 to RF4, and the best performing model was RF2 (root mean square error (RMSE) (t C ha&minus, 1) = 1.67 in soil carbon stocks, 1.49 in soil and litter carbon stocks). Our study indicated that elevation, accessibility class, slope, diameter at breast height, height, and growing stock are important predictors of carbon stock. Soil and litter carbon stock maps were produced using the RF2 models. Almost all prediction values were appropriated to soil and litter carbon stocks. Conclusions: Estimating and mapping the carbon stocks in the soil and litter layer using the NFI data and random forest models could be used in future national GHG inventory reports. Additionally, the data and models can estimate all carbon pools to achieve an accurate and complete national GHG inventory report.

Greenhouse gas (GHG) inventory has played a fundamental role in providing scientific political-making evidence in mitigation. For a particular case study, Japan offers a positive performance in reducing GHG emissions since an early age, and the GHG Inventory Office of Japan was established in 2002 and is making efforts on publishing both “National GHGs Inventory Report of Japan” and “GHGs Emissions Data of Japan” annually. This paper covers local Japanese inventory development from a global range to a domestic level and offers its general reporting criteria nationwide. Furthermore, through a case study of recalculating 2010 Saga Prefecture’s GHG emission, local inventory methodology is investigated in six GHGs (including CO2, CH4, N2O, HFC, PFC, and SF6) and forestry sectors. In this section, recalculating methodologies, especially regarding calculated fields and basic formulations categorized by GHG types, are introduced in detail. Then, it provides limitations and improvements of the inventory reformation. Further, future research directions are discussed as well. This research exhibits an inventory method at the local scale and offers its improvements by the author to provide some experiences and lessons for the research and mitigation policy-making practices in other parts of the world.

Global economic development has highlighted the issue of climate change, which is one of the most important environmental issues plaguing human beings. It is widely agreed that excessive greenhouse gas (GHG) emissions are important factors contributing to global warming. Many countries have formulated corresponding GHG emission reduction plans to deal with climate change issues. An important GHG emission source is released from sewage-sludge treatment systems. However, there has not been a comprehensive quantitative GHG emissions evaluation system in the case of sewage-sludge treatment systems, due to multiple emission sources, complex processes, and different standards. In previous studies, the Guidelines for National Greenhouse Gas Inventories (Intergovernmental Panel on Climate Change, IPCC, 2006) and Chinese Greenhouse Gas Inventory (National Center for Climate Change Strategy and International Cooperation, NCSC, 2005) were widely applied to estimate GHG emissions from sewage-sludge treatment. However, IPCC does not consider CO2 emissions from sewage treatment, and NCSC does not consider CO2 emissions from the sewage treatment and N2O emissions from sludge treatment. Therefore, the following have been conducted in this study: (1) A GHG estimation model basing on Life Cycle Thinking (LCT) was constructed, and the research objects were CH4, N2O, and CO2 that were produced by the sewage-sludge treatment system. The estimation model of CO2 and N2O, which were ignored in the IPCC report, were analyzed and discussed. The models of the GHG emission estimation were summarized and improved in the urban sewage-sludge treatment system under the different sewage-sludge treatment process scenarios. (2) The GHG emission load of major urban sewage-sludge treatment processes was analyzed, and the level and key links of environmental impacts generated by different processes were identified. This helps to understand and compare the environmental impacts of different treatment processes and provides suggestions for the sustainable development of wastewater treatment processes. (3) The GHG emission characteristics of nine scenarios of different sewage-sludge treatment processes were analyzed, and the environmental impacts caused by energy consumption and chemicals consumption were studied. Consequently, the sewage-sludge treatment process under low carbonization and low environment impact were proposed.

Fertilized agricultural soils serve as a primary source of anthropogenic N2O emissions. In South Africa, there is a paucity of data on N2O emissions from fertilized, irrigated dairy-pasture systems and emission factors (EF) associated with the amount of N applied. A first study aiming to quantify direct N2O emissions and associated EFs of intensive pasture-based dairy systems in sub-Sahara Africa was conducted in South Africa. Field trials were conducted to evaluate fertilizer rates (0, 220, 440, 660, and 880 kg N ha&minus, 1 year&minus, 1) on N2O emissions from irrigated kikuyu&ndash, perennial ryegrass (Pennisetum clandestinum&ndash, Lolium perenne) pastures. The static chamber method was used to collect weekly N2O samples for one year. The highest daily N2O fluxes occurred in spring (0.99 kg ha&minus, 1 day&minus, 1) and summer (1.52 kg ha&minus, 1). Accumulated N2O emissions ranged between 2.45 and 15.5 kg N2O-N ha&minus, 1 and EFs for mineral fertilizers applied had an average of 0.9%. Nitrogen in yielded herbage varied between 582 and 900 kg N ha&minus, 1. There was no positive effect on growth of pasture herbage from adding N at high rates. The relationship between N balance and annual N2O emissions was exponential, which indicated that excessive fertilization of N will add directly to N2O emissions from the pastures. Results from this study could update South Africa&rsquo, s greenhouse gas inventory more accurately to facilitate Tier 3 estimates.

We estimate methane emissions from U.S. local distribution natural gas (NG) pipes using data collected from an advanced mobile leak detection (AMLD) platform. We estimate that there are 630,000 leaks in U.S. distribution mains, resulting in methane emissions of 0.69 Tg/year (95% cr int: 0.25, 1.23). Total emissions are calculated as the product of activity factors and emissions factors. Our analysis leveraged data on >4000 leak indications found using AMLD, combined with utility pipeline GIS information, to allow us to estimate activity factors. We derive emissions factors from AMLD emission rate estimates and correct these emissions factors based on data from in-field studies assessing AMLD emissions estimates. Finally, we quantify uncertainty in both emissions factors and activity factors and propagate the uncertainty to our total emissions estimate. In modeling leak frequency, we find a clear interaction between pipeline material and age with the leakiness of all material types increasing with age. Our national methane emissions estimate is approximately 5× greater (95% cr int: 1.7×, 8.7×) than the U.S. Environmental Protection Agency's current greenhouse gas inventory estimate for pipeline mains in local distribution systems due to both a larger estimated number of leaks and better characterization of the upper tail of the skewed distribution of emission rates.

Waste heat utilization is shown to have the potential to decrease greenhouse gas emissions globally. The purpose of this case study is to illustrate how the utilization of waste heat to decrease municipal boundary greenhouse gas emissions may increase such emissions within wider boundaries. The case study assesses the utilization of waste heat generated by a data center. In this paper, we analyze the implications within Scopes 1-3 of the Greenhouse Gas Protocol together with attributional and consequential life cycle assessment principals. Only Scope 1 showed negative greenhouse gas emission implications. In order to achieve negative Scope 2 emissions, approximately half of the waste heat would need to be utilized, which is the purpose of further site development. In order for negative Scope 3 emission implications, electricity production changes are needed or local municipal replaceable greenhouse gas emissions would need to be much higher.

Using results from a nationally representative measurement campaign at 180 gathering compressor stations conducted with nine industry partners, this study estimated emissions for the U.S. gathering sector, where sector-specific emission factors have not been previously available. The study drew from a partner station population of 1705 stations-a significantly larger pool than was available for prior studies. Data indicated that whole gas emission rates from components on gathering stations were comparable to or higher than emission factors utilized by the EPA's greenhouse gas reporting program (GHGRP) but less than emission factors used for similar components on transmission compressor stations. Field data also indicated that the national population of stations likely has a higher fraction of smaller stations, operating at lower throughput per station, than the data used to develop the per-station emission factor used in EPA's greenhouse gas inventory (GHGI). This was the first national study to incorporate extensive activity data reported to the GHGRP, including 319 basin-level reports, covering 15,895 reported compressors. Combining study emission data with 2017 GHGRP activity data, the study indicated statistically lower national emissions of 1290 [1246-1342] Gg methane per year or 66% [64-69%] of current GHGI estimates, despite estimating 17% [12-22%] more stations than the 2017 GHGI (95% confidence interval). Finally, we propose a replicable method that uses GHGRP activity data to annually update GHGI gathering and boost sector emissions.

Background Reducing net greenhouse gas emissions through conserving existing forest carbon stocks and encouraging additional uptake of carbon in existing and new forests have become important climate change mitigation tools. The contribution of harvested wood products (HWPs) to increasing carbon uptake has been recognised and approaches to quantifying this pool developed. In New Zealand, harvesting has more than doubled since 1990 while log exports have increased by a factor of 11 due to past afforestation and comparatively little expansion in domestic processing. This paper documents New Zealand’s application of the IPCC approaches for reporting contributions of the HWP pool to net emissions, in order to meet international greenhouse gas inventory reporting requirements. We examine the implications of the different approaches and assumptions used in calculating the HWP contribution and highlight model limitations. Results Choice of system boundary has a large impact for a country with a small domestic market and significant HWP exports. Under the Production approach used for New Zealand’s greenhouse gas inventory reporting, stock changes in planted forests and in HWPs both rank highly as key categories. The contribution from HWPs is even greater under the Atmospheric Flow approach, because emissions from exported HWPs are not included. Conversely the Stock Change approach minimises the contribution of HWPs because the domestic market is small. The use of country-specific data to backfill the time series from 1900 to 1960 has little impact but using country-specific parameters in place of IPCC defaults results in a smaller HWP sink for New Zealand. This is because of the dominance of plantation forestry based on a softwood mainly used in relatively short-lived products. Conclusions The NZ HWP Model currently meets international inventory reporting requirements. Further disaggregation of the semi-finished HWP end uses both within New Zealand and in export markets is required to improve accuracy. Product end-uses and lifespans need to be continually assessed to capture changes. More extensive analyses that include the benefits of avoided emissions through product substitution and life cycle emissions from the forestry sector are required to fully assess the contribution of forests and forest products to climate change mitigation and a low emissions future.

Globally, animal excreta (dung and urine) deposition onto grazed pastures represents more than half of anthropogenic nitrous oxide (N2O) emissions. To account for these emissions, New Zealand currently employs urine and dung emission factor (EF3) values of 1.0% and 0.25%, respectively, for all livestock. These values are primarily based on field studies conducted on fertile, flatland pastures predominantly used for dairy cattle production but do not consider emissions from hill land pastures primarily used for sheep, deer and non-dairy cattle. The objective of this study was to determine the most suitable urine and dung EF3 values for dairy cattle, non-dairy cattle, and sheep grazing pastures on different slopes based on a meta-analysis of New Zealand EF3 studies. As none of the studies included deer excreta, deer EF3 values were estimated from cattle and sheep values. The analysis revealed that a single dung EF3 value should be maintained, although the value should be reduced from 0.25% to 0.12%. Furthermore, urine EF3 should be disaggregated by livestock type (cattle > sheep) and topography (flatland and low sloping hill country > medium and steep sloping hill country), with EF3 values ranging from 0.08% (sheep urine on medium and steep slopes) to 0.98% (dairy cattle on flatland and low slopes). While the mechanism(s) causing differences in urine EF3 values for sheep and cattle are unknown, the 'slope effect' on urine EF3 is partly due to differences in soil chemical and physical characteristics, which influence soil microbial processes on the different slope classes. The revised EF3 values were used in an updated New Zealand inventory approach, resulting in 30% lower national N2O emissions for 2017 compared to using the current EF3 values. We recommend using the revised EF3 values in New Zealand's national greenhouse gas inventory to more accurately capture N2O emissions from livestock grazing.

Atmospheric concentrations of CH4 have tripled since the Industrial Revolution. One culprit of this increase is animal agriculture, contributing 8 to 10% of global greenhouse gas emissions primarily in the form of CH4. According to US Environmental Protection Agency greenhouse gas inventory estimates, the majority of the manure emissions are from manure management on dairy farms (53%). Most of these manure emissions are generated from liquid manure in anaerobic lagoons. Thus, accurate estimates of the emissions from these lagoons are essential for developing management strategies to reduce CH4 emissions. Emissions of methane from two manure lagoons, one in Southern California and the other in Central California, were estimated by fitting results from a state-of-the-art dispersion model to CH4 concentrations measured with a mobile monitor. The sampling was conducted by stationing the mobile monitors at several locations (29-42) around the lagoons for time intervals ranging from 10 to 15 minutes. A sonic an...

Nitrous oxide (N2O) emission factors (EFs) were calculated from measurements of emissions from livestock manures applied to UK arable crops and grassland as part of a wider research programme to reduce uncertainty in the UK national agricultural N2O inventory and to enhance regional inventory reporting through increased understanding of processes and factors controlling emissions. Field studies were undertaken between 2011 and 2013 at 3 arable and 3 grassland sites in the UK. Nitrous oxide emissions were measured following the autumn and spring application of different manures (pig slurry, cattle slurry, cattle farmyard manure (FYM), pig FYM, poultry layer manure, and broiler litter) at typical rates, using representative manure application and soil incorporation methods. In addition, ammonia emissions and nitrate leaching losses (1 site on a light sandy soil) were measured to calculate indirect N2O losses. IPCC comparable, direct N2O EFs ranged from −0.05 to 2.30% of total nitrogen applied, with the variability driven by a range of factors including differences in manure composition, application method, incorporation and climatic conditions. When data from the autumn applications were pooled, the mean N2O EF from poultry manure (1.52%) was found to be greater (P < 0.001) than from FYM (0.37%) and slurry (0.72%), with no difference found (P = 0.784) in the EF for bandspread compared with surface broadcast slurry application, and no effect (P = 0.328) of the nitrification inhibitor, Dicyandiamide (DCD). For the spring applications, the mean N2O EF for bandspread slurry (0.56%) was greater (P = 0.028) than from surface broadcast slurry (0.31%), but there were no differences (P = 0.212) in the mean N2O EFs from poultry manure (0.52%), slurry (0.44%), and FYM (0.22%). The study did confirm, however, that DCD reduced N2O emissions from slurries applied in the spring by 45%. EF data from this project have been used in the derivation of robust Tier 2 country specific EFs for inclusion in the UK national agriculture greenhouse gas inventory.

Excessive GHG emissions from human activities lead to climate warming, and sewage treatment plants are one of the sources of GHG emissions. The number of sewage treatment plants in my country is increasing year by year, and they emit a large amount of GHG, it is necessary to evaluate their emissions and seek ways to reduce emissions. According to the “Greenhouse Gas Inventory Protocol-Corporate Accounting and Reporting Standards”, taking a sewage treatment plant in a northern city as an example, the GHG emission classification of its operation control range, selection of evaluation methods and emission factors, assessment of GHG emissions, analysis of GHG emissions Constitution, propose ecological treatment technology, recycling CH4 and other emission reduction measures.

Nitrous oxide (N2O) emissions from dairy-grazing pastures can be dominated by large emissions from small areas (‘hotspots’) frequently used by grazing dairy cattle (i.e., water troughs and gateways). N2O emissions from these hotspots are quantified by investigating whether N2O emissions and emission factors (% of applied N emitted as N2O, EF3) from potential hotspots are different from non-hotspots. To better characterise N2O emissions from hotspots and non-hotspots of farms to understand their contributions to national agricultural greenhouse gas inventory calculations, a series of measurements were conducted during winter and spring on two NZ typical dairy farms with contrasting soil drainage (poorly versus well drained). Before measurements were taken, the soils either received a cow urine application or remained untreated. The results showed that changes in water-filled pore space (WFPS) and mineral N around water troughs and gateways, due to additional stock movements and disproportionate excreta-N deposition during previous grazing events, affected both background and total N2O emissions. But there was little impact on EF3 values (calculated using IPCC guidelines) from deposited urine between hotspot and pasture areas. These results suggest the same EF3 values can be used for both to calculate emissions from urine deposited on grazed pastures. However, these results raise concerns about higher background emission in hotspots subtracted from measured emissions from urine-N deposition in calculating EF3 values and discounting the effects of disproportionate N inputs in intensive agriculture on increased background emissions (legacy effect). This IPCC inventory method does not account for the legacy effect of N loading prior to the measurements which may underestimate the emissions. Thus, an allowance for higher hotspot background emissions could be included in the Inventory to accurately estimate total emissions from agriculture.

The Republic of Korea is trying to reduce greenhouse gas emissions by 37% from business-as-usual levels by 2030. Reliable greenhouse gas inventory is prerequisite to making effective greenhouse gas reduction plans. Currently, Intergovernmental Panels on Climate Change default emission factors were used in biological treatment of the solid waste sector without any consideration of the biological treatment process in the Republic of Korea. In this study, greenhouse gas emissions from biological treatment facilities of food waste have been monitored in order to develop country-specific emission factors in the Republic of Korea. Greenhouse gas emissions were monitored in two composting facilities and one anaerobic digestion facility. All study sites possess a local exhaust ventilation system and odour treatment system. Continuous greenhouse gas monitoring has been conducted on gathered gases using a non-dispersive infrared detector before entering odour treatment systems. At composting facilities, the emission factors of CH4 and N2O were 0.17–0.19 g-CH4 kg-waste−1 and 0.10–0.13 g-N2O kg-waste−1, respectively. Especially, the emission factors of CH4 in composting facilities showed significantly low values compared with other countries owing to the air blowing by a pump at the studied sites. At anaerobic digestion facilities, the emission factors of CH4 and N2O were 1.03 g-CH4 kg-waste−1 and 0.53 g-N2O kg-waste−1. The emission factors estimated in this study showed a significant difference from the Intergovernmental Panels on Climate Change default value. Therefore, it is recommended to develop a country-specific emission factor in order to reflect the different processes of biological treatment of solid waste.

Background There has been growing interest in the development of waste-specific decay factors for estimation of greenhouse gas emissions from landfills in national greenhouse gas inventories. Although engineered wood products (EWPs) and paper represent a substantial component of the solid waste stream, there is limited information available on their carbon dynamics in landfills. The objective of this study was to determine the extent of carbon loss for EWPs and paper products commonly used in Australia. Experiments were conducted under laboratory conditions designed to simulate optimal anaerobic biodegradation in a landfill. Results Methane generation rates over incubations of 307–677 days ranged from zero for medium-density fibreboard (MDF) to 326 mL CH4 g−1 for copy paper. Carbon losses for particleboard and MDF ranged from 0.7 to 1.6%, consistent with previous estimates. Carbon loss for the exterior wall panel product (2.8%) was consistent with the expected value for blackbutt, the main wood type used in its manufacture. Carbon loss for bamboo (11.4%) was significantly higher than for EWPs. Carbon losses for the three types of copy paper tested ranged from 72.4 to 82.5%, and were significantly higher than for cardboard (27.3–43.8%). Cardboard that had been buried in landfill for 20 years had a carbon loss of 27.3%—indicating that environmental conditions in the landfill did not support complete decomposition of the available carbon. Thus carbon losses for paper products as measured in bioreactors clearly overestimate those in actual landfills. Carbon losses, as estimated by gas generation, were on average lower than those derived by mass balance. The low carbon loss for particleboard and MDF is consistent with carbon loss for Australian wood types described in previous studies. A factor for carbon loss for combined EWPs and wood in landfills in Australia of 1.3% and for paper of 48% is proposed. Conclusions The new suggested combined decay factor for wood and EWPs represents a significant reduction from the current factor used in the Australian greenhouse gas inventory; whereas the suggested decay factor for paper is similar to the current decay factor. Our results improve current understanding of the carbon dynamics of harvested wood products, and allow more refined estimates of methane emissions from landfills. Electronic supplementary material The online version of this article (10.1186/s13021-018-0115-3) contains supplementary material, which is available to authorized users.

The land sector is expected to contribute to strategies aimed at mitigating global temperature increases and this necessitates an improved understanding of human actions on land sector emissions and removals. Current Intergovernmental Panel on Climate Change guidelines for the land sector of national greenhouse gas inventories are based on the assumption that all emissions and removals in managed lands are caused by humans. In Canada, however, natural disturbances in managed forests can result in large and highly variable emissions and subsequent removals that mask the impacts of management activities. Here we describe methods to isolate and quantify the impacts of management on trends in estimated anthropogenic emissions and removals in Canada’s managed forest by partitioning fluxes from two land components: fluxes from lands dominated by natural disturbance effects and fluxes from the remaining managed forests. The sum of the flux estimates of the two land components is equal to net emissions and removals in managed forest lands. Separating highly variable natural disturbance fluxes from the remaining fluxes in managed forest lands increases the understanding of how human activities impact flux trends. Comparing these anthropogenic emissions and removals with those from natural disturbances quantifies their relative contributions to global atmospheric CO2 concentrations.

We use observations of boundary layer methane from the SEAC 4 RS aircraft campaign over the Southeast US in August–September 2013 to estimate methane emissions in that region through an inverse analysis with up to 0.25 ∘ × 0.3125 ∘ ( 25×25 km2 ) resolution and with full error characterization. The Southeast US is a major source region for methane including large contributions from oil and gas production and wetlands. Our inversion uses state-of-the-art emission inventories as prior estimates, including a gridded version of the anthropogenic EPA Greenhouse Gas Inventory and the mean of the WetCHARTs ensemble for wetlands. Inversion results are independently verified by comparison with surface ( NOAA∕ESRL ) and column (TCCON) methane observations. Our posterior estimates for the Southeast US are 12.8±0.9 Tg a−1 for anthropogenic sources (no significant change from the gridded EPA inventory) and 9.4±0.8 Tg a−1 for wetlands (27 % decrease from the mean in the WetCHARTs ensemble). The largest source of error in the WetCHARTs wetlands ensemble is the land cover map specification of wetland areal extent. Our results support the accuracy of the EPA anthropogenic inventory on a regional scale but there are significant local discrepancies for oil and gas production fields, suggesting that emission factors are more variable than assumed in the EPA inventory.

Large volumes of engineered wood products (EWPs) and paper are routinely placed in landfills in Australia, where they are assumed to decay. However, the extent of decay for EWPs is not well-known. This study reports carbon loss from EWPs and paper buried in landfills in Sydney, Brisbane and Cairns in Australia, located in temperate, subtropical and tropical climates, respectively. The influence of pulp type (mechanical and chemical) and landfill type (municipal solid waste - MSW and construction and demolition - CD) on decay levels were investigated. Carbon loss for EWPs ranged from 0.6 to 9.0%; though there is some uncertainty in these values due to limitations associated with sourcing appropriate controls. Carbon loss for paper products ranged from 0 to 58.9%. Papers produced from predominantly mechanical pulps generally had lower levels of decay than those produced via chemical or partly chemical processes. Typically, decay levels for paper products were highest for the tropical Cairns landfill, suggesting that climate may be a significant factor to be considered when estimating emissions from paper in landfills. For EWPs, regardless of the landfill type and climate, carbon losses were low, confirming results from previous laboratory studies. Lower carbon losses were observed for EWP and paper excavated from the Sydney CD landfill, compared with the Sydney MSW landfill, confirming the hypothesis that conditions in CD landfills are less favourable for decay. These results have implications for greenhouse gas inventory estimations, as carbon losses for EWPs were lower than the commonly assumed values of 23% (US EPA) and 50% (Intergovernmental Panel on Climate Change). For paper types, we suggest that separate decay factors should be used for papers dominated by mechanical pulp and those produced from mostly chemical pulps, and also for papers buried in tropical or more temperate climates.

Over the next 10 to 30 years methane emissions from landfills in Germany will continue to represent a major source of greenhouse-gas emissions in the waste sector. Methane emissions have been estimated for the National Inventory Report on the German Greenhouse Gas Inventory (NIR) using the First Order Decay (FOD) method and the IPCC Guidelines for National Greenhouse Gas Inventories. Both national data and default factors (standard values) provided by the IPCC were used in calculating the estimations. A review of the methodological basis and input data used to determine methane formation in landfills indicates that the previous approaches adopted in the NIR reports led to methane formation rates that clearly exceeded actual emissions from German landfills. Both the state of knowledge and the results of investigations focussed on landfill gas production and emissions from numerous German municipal solid waste landfills confirm the latter. To obtain a more accurate description of the methane generation potential and methane generation in landfills, DOC parameters, fraction of degradable organic carbon (DOCf), half-life and methane correction factor (MCF) can be adapted for the individual organic fractions of waste. When the adapted values for use in the estimation of methane emissions of German landfills are applied, the results yielded are in a range of approx. 50ϼompared to the estimated values reported in the German NIR to date.

Direct agricultural N2O emissions in Germany have so far been estimated using the default Tier 1 emission factor of 1% (0.3–3%) in accordance with the IPCC’s default methodology. Since direct N2O emissions is a “key category” in the German National Greenhouse Gas Inventory, the IPCC recommends the use of country-specific emission factors or models. With the aim of deriving country-specific and stratified N2O emission factors, a meta-analysis was conducted using data collected from 71 individual studies comprising 676 separate emission measurements taken at 43 locations across Germany. A Bayesian generalised linear mixed-effects modelling approach was used to model N2O fluxes and derive emission factors. In contrast to what is suggested by the 2019 Refinement to the 2006 IPCC Guidelines, the model results did not support a distinction being made between emission factors for synthetic and organic fertilisers. Instead, a model based on four environmental zones roughly representing the north-west, north-east, south-east and south-west parts of the country was developed. It was used to derive district-wise emission factors for direct N2O emissions and revealed that northern districts had relatively lower emission factors than southern districts. The district-wise emission factors ranged from 0.38% to 0.92%. The national implied emission factor for direct N2O emissions from managed agricultural soils was 0.62% (0.43–0.85%). Accordingly, the estimate of German national GHG emissions from agriculture in 2015 is 8.59% (calculated with global warming potentials from IPCC’s fifth assessment report) lower than the estimate reported in the 2021 inventory submission to UNFCCC.