Analysis of uncertainties in the estimates of nitrous oxide and methane emissions in the UK's greenhouse gas inventory for agriculture

Milne, Alice E.; Glendining, M. J.; Bellamy, P.; Misselbrook, Tom; Gilhespy, S. L.; Casado, Mónica Rivas; Hulin, A.; Oijen, Marcel van; Whitmore, A. P.

doi:10.1016/j.atmosenv.2013.10.012

Cited by 35 publications

(23 citation statements)

References 5 publications

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“…This reduces uncertainty and is one of the important advantages of the Tier 2 over the Tier 1. The uncertainty in estimating MEF for enteric fermentation may determine that in CH 4 emissions from the livestock production sector (Milne et al, 2014). The mechanistic approach used in the IPCC Tier 2 methodology allows the enteric CH 4 production of cattle to be estimated while reducing uncertainty involving the animals, diets, and management characteristics (Ominski et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

“…For the overall feeding period of Hanwoo steers, the estimated MEF using T2 was similar to results using T2DMI, implying that the IPCC Tier method may be applied for estimating enteric CH emissions from Hanwoo in filing NIR. However, there were significant differences in estimating the MEF separately for growing and finishing periods between T2 and T2DMI, indicating that the uncertainty in estimating MEF for enteric fermentation still remains in T2 (Bannink ,van Schijndel & Dijkstra, 2011;Milne et al, 2014). The uncertainty in the MEF estimates for the IPCC Tier 2 methodology results from GE intake prediction and MCF.…”

Section: Discussionmentioning

confidence: 99%

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Estimation of methane emission factor for enteric fermentation of growing-finishing Hanwoo steers using the IPCC Tier 2 approach

Kim

Seo

2015

Preprint

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Enteric methane (CH4) production by cattle is one of the major sources of greenhouse gas (GHG) emissions in the livestock sector. In order to develop a national GHG inventory and establish a mitigation strategy for GHG emissions from livestock production, accurate estimation of enteric CH4 production by cattle is required. In this regard, the Tier 2 method in the Intergovernmental Panel on Climate Change (IPCC) guidelines is the most widely used. The objective of this study was to estimate and evaluate the CH4 emission factor (MEF; kg CH4/head/year) for enteric fermentation using the IPCC Tier 2 method in Hanwoo steers, a dominant beef production species in Korea raised in a unique feeding system (e.g., a duration of > 16 months in a feedlot). Methane emission factor for enteric fermentation was estimated using the IPCC Tier 2 method (T2) on Korea- and Hanwoo-specific data obtained from the literature. The MEF values were also estimated and compared using the IPCC Tier 1 (T1), the IPCC Tier 2 methodology with estimated gross energy GE intake based on actual dry matter intake (T2DMI), and the Japanese Tier 3 method (JT3). JT3 was chosen due to the similarity in the beef cattle production system between the two countries. Estimated MEF using T2 were 43.4, 33.9, and 36.2 kg CH4/head/year for the growing, finishing, and overall period, respectively. The overall MEF estimated using T2 was 23% lower than the estimate by T1 (47.0 kg CH4/head/year). There were significant differences in the estimated MEF for enteric fermentation of Hanwoo steers among the T2, T2DMI, and JT3 methods. JT3 estimated the highest values in all periods possibly due to overestimation of the conversion ratio of feed energy to CH4. No significant difference was found in the overall MEF of Hanwoo steers between T2 and T2DMI. However, T2DMI estimated 8% higher and 14% lower MEF than T2 for the growing and finishing period, respectively, mainly because the IPCC Tier 2 model significantly over-predicts the GE intake of Hanwoo steers at the high level of intake. The IPCC Tier 2 methodology is preferred to IPCC Tier 1 in estimating the MEF for enteric fermentation of Hanwoo steers, and the DMI model for Japanese cattle can be used to predict DMI of Hanwoo steers. In order to reduce the uncertainty of the estimates and search for a better mitigation strategy, however, development of a country-specific methodology and parameter estimates for enteric CH4 production of Hanwoo is required.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Estimation of methane emission factor for enteric fermentation of growing-finishing Hanwoo steers using the IPCC Tier 2 approach

Kim

Seo

2015

Preprint

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“…Reduction in uncertainty could be achieved via improvement in data reporting, including better accessibility of experimental and modelling data and clearer disclosure of uncertainty. The UK GHG emission inventory now includes an assessment of the uncertainty in IPCC coefficients and activity data (Milne et al, 2014). As experimental evidence on the technical abatement potential of mitigation options is expanding, meta-analysis is becoming possible for more mitigation options (see for example Akiyama et al, 2010;Qiao et al, 2015;Veneman et al, 2016).…”

Section: How Much Effort To Invest In Reducing Uncertainties?mentioning

confidence: 99%

“…This paper considers mitigation uncertainties in agriculture, a sector that is implicated as a significant source of GHG emissions both nationally and globally; agriculture (not including land use change and forestry) has been estimated to account for approximately 14% of global anthropogenic emissions in 2010 (IPCC, 2014) and 17% of anthropogenic emissions in Scotland (Salisbury et al, 2015). To date, uncertainty regarding the agricultural sector has been considered in the context of an inventory of sources that identify total emissions (Milne et al, 2014). However, there has been less focus on how uncertainties influence mitigation policy that is informed by a systematic analysis of sector-specific mitigation options and their cost-effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Addressing Uncertainty in Efficient Mitigation of Agricultural Greenhouse Gas Emissions

Eory¹,

Topp²,

Butler³

et al. 2018

J Agricultural Economics

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The agricultural sector, as an important source of greenhouse gas (GHG) emissions, is under pressure to reduce its contribution to climate change. Decisions on financing and regulating agricultural GHG mitigation are often informed by costeffectiveness analysis of the potential GHG reduction in the sector. A commonly used tool for such analysis is the bottom-up marginal abatement cost curve (MACC) which assesses mitigation options and calculates their cumulative costeffective mitigation potential. MACCs are largely deterministic, typically not reflecting uncertainties in underlying input variables. We analyse the uncertainty of GHG mitigation estimates in a bottom-up MACC for agriculture, for those uncertainties capable of quantitative assessment. Our analysis identifies the sources and types of uncertainties in the cost-effectiveness analysis and estimates the statistical uncertainty of the results by propagating uncertainty through the MACC via Monte Carlo analysis. For the case of Scottish agriculture, the uncertainty of the cost-effective abatement potential from agricultural land, as expressed by the coefficient of variation, was between 9.6% and 107.3% across scenarios. This means that the probability of the actual abatement being less than half of the estimated abatement ranged from <1% (in the scenario with lowest uncertainty) to 32% (in the scenario with highest uncertainty). The main contributors to uncertainty are the adoption rate and abatement rate. While most mitigation options appear to be 'win-win' under some scenarios, many have a high probability of switching between being cost-ineffective and cost-effective.

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“…It is the acquisition of such data that is often considered the most demanding step in carrying out an inventory or an analysis of the farm. Furthermore, the quality of such data is central as this can improve the accuracy of the material balance and provide a reliable basis for subsequent actions (Milne et al, 2014;Velthof et al, 2015). Finally, the availability of data reflecting different manure management practices and its application in different countries remains limited or somewhat artificial or inconsistent thus rendering comparisons difficult between methods used in different countries affected by air and water pollution (Menzi et al, 2015b;Velthof et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Overview of Animal Manure Management for Beef, Pig, and Poultry Farms in France

Loyon

2018

Front. Sustain. Food Syst.

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Livestock manure management is the central issue for many environmental policies relating to water and air quality. However, there is little published data on the methods used in those countries affected by pollution from the livestock sector. This paper brings together the available data relating to manure management in France, specifically for pig, cattle and poultry production. An overview of livestock production and legislation is presented using data from the 2010 Agricultural Census, livestock farm surveys carried out in 2008 and other supporting documents relating to manure treatment (professional surveys, expert reports and technical publications). Cattle, pig, and poultry livestock produce around 120 million tons of manure per year not including those on pasture. This figure is made up from 60.6% solid manure, 38.8% livestock slurry (effluent) and a relatively small amount of poultry droppings. Solid manure is mainly stored in temporary field heaps. In the case of manure storage on the farm, the capacity varies from 45 days to 7.5 months depending on farm size and type of animals, time spent outside the buildings and the geographical location. Covered storage (whether rigid or natural crust) accounts for 17% of stored pig slurry, 45% of cattle slurry, and 39% of poultry slurry. Covered storage of solid manure is rarely used on pig or cattle farms whereas 27% of the solid poultry manure (including poultry droppings) is held in covered storage areas. Treatment applies to 13.6 million tons of the manure produced, mainly by methods based on composting or aerobic treatment. Nitrogen applied as slurry is mostly spread on the soil surface using splash plate tankers (83% in the case of cattle slurry, 63% for pig slurry, and 66% for poultry slurry). Incorporation within 24 h of the nitrogen spread on the soil concerns 28% of cattle, 44% of pig, and 56% of poultry manure. The most common method of manure management is storage (in building and pit) and spreading. The treatment of manure and the use of specific techniques to reduce gaseous emissions (such as frequent manure removal from buildings, storage covers, or injection) are not widely reported.

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Analysis of uncertainties in the estimates of nitrous oxide and methane emissions in the UK's greenhouse gas inventory for agriculture

Cited by 35 publications

References 5 publications

Estimation of methane emission factor for enteric fermentation of growing-finishing Hanwoo steers using the IPCC Tier 2 approach

Estimation of methane emission factor for enteric fermentation of growing-finishing Hanwoo steers using the IPCC Tier 2 approach

Addressing Uncertainty in Efficient Mitigation of Agricultural Greenhouse Gas Emissions

Overview of Animal Manure Management for Beef, Pig, and Poultry Farms in France

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