Methane Emission from Enteric Fermentation: Methanogenesis and Fermentation

2015 ◽  
pp. 171-186
Author(s):  
Arianna Buccioni ◽  
Alice Cappucci ◽  
Marcello Mele
Keyword(s):  
Methane Emission ◽  
Enteric Fermentation

scholarly journals Methane emission factors for enteric fermentation in beef cattle using IPCC Tier-2 method in Indonesia

2016 ◽  
Vol 21 (2) ◽  
pp. 101 ◽  
Author(s):  
Yeni Widiawati ◽  
M.N. Rofiq ◽  
B. Tiesnamurti
Keyword(s):  
Beef Cattle ◽  
Methane Emission ◽  
Energy Content ◽  
Emission Factors ◽  
Tier 2 ◽  
Cattle Population ◽  
Enteric Fermentation ◽  
Agriculture Sector ◽  
Enteric Methane ◽  
Country Specific

<p class="abstrak2">Methane emission from enteric is a sub-category considered under the Agriculture sector greenhouse gas emissions by UNFCCC, thus Indonesia developed calculation on enteric CH<sub>4</sub> EF for ruminant using Tier-2 method as country-specific emission factors (EF). Indonesia has huge amount of beef cattle population, which contributes significant amount to national enteric methane emission. The aim of this study was to estimate enteric methane EF for beef cattle in Indonesia using IPCC Tier-2 method.  The EF generated from this study is then used to estimate the methane emitted from beef cattle. Data on beef cattle population was obtained from BPS, data on energy content of feed, feed intake and digestibility were compiled from laboratory analysis and published paper. Equations were adopted and followed the instruction of IPCC 2006. Local cattle has different CH<sub>4</sub> EF among each sub-category, which are  ranging from 18.18 to 55.89 Kg head-1 yr-1, with the average of 36.75  head-1 yr-1. Imported beef cattle has lower  CH<sub>4</sub> EF (25.49 kg head-1 yr-1) than the average for local beef cattle. Overall, the national CH<sub>4</sub> EF of beef cattle calculated by using IPCC Tier-2 method in Indonesia is 33.14 head-1 yr-1. The value is lower than default EF from IPCC for Asia country (47 kg head-1 yr-1). The conclusion is enteric CH<sub>4</sub> EF for beef cattle in Indonesia calculated using Tier-2 method shows the real livestock system in Indonesia condition. Further research needed to be addressed are calculation of EFs for various breeds and feeding systems, since large variations of breeds and types of feed among provinces in Indonesia.</p>

scholarly journals Status of Methane Gas Emission from Paddy Fields in Nepal

2016 ◽  
Vol 4 ◽  
pp. 142-148
Author(s):  
Madhab Joshi
Keyword(s):  
Methane Emission ◽  
Agricultural Development ◽  
Agricultural Research ◽  
National Level ◽  
Secondary Data ◽  
Paddy Fields ◽  
Mitigation Measures ◽  
Gas Emission ◽  
Enteric Fermentation ◽  
Methane Gas

Annual methane emission from paddy fields in Nepal has been estimated based on the published secondary data for 11 years from 2000-2010. Available data were collected from the Ministry of Agricultural Development (MoAD), Department of Agriculture (DoA) and Nepal Agricultural Research Council (NARC). Green house gas emission (GHG) was estimated by using IPCC 2006 guidelines. Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes including the source categories such as enteric fermentation in domestic livestock, livestock manure management, rice cultivation, and agricultural soil management. Diverse traditional agriculture systems, unique diversities in land types and unavailability of required disaggregated data at the national level as defined by the emission factor data base (EFDB) of the IPCC 2006, were the problem encountered while calculating the emission status in this study. Annual methane (CH4) emission from paddy fields ranged from 111.57 to 133.07 Gg over years 2000 to 2010 but it was found lowest ( 111.57 Gg) in the year 2002 and highest (133.07 Gg) in the year2003. In the year 2010, methane emission from paddy cultivation represented about 17.48 % of cumulative methane emission both from livestock sector and paddy fields throughout Nepal. Also, some relevant policies and potential strategies towards mitigation measures of methane gas emission from paddy fields for the future in Nepal are highlighted.Agronomy Journal of Nepal (Agron JN), Vol.4, Page: 142-148, 2016

Methane emission factors and carbon fluxes from enteric fermentation in cattle of Nepal Himalaya

2020 ◽  
Vol 746 ◽  
pp. 141184
Author(s):  
Sudeep Thakuri ◽  
Preshika Baskota ◽  
Singh Bahadur Khatri ◽  
Anandita Dhakal ◽  
Pashupati Chaudhary ◽  
...  
Keyword(s):  
Methane Emission ◽  
Carbon Fluxes ◽  
Emission Factors ◽  
Enteric Fermentation ◽  
Nepal Himalaya

Development of prediction models for quantification of total methane emission from enteric fermentation of young Holstein cattle at various ages

2014 ◽  
Vol 183 ◽  
pp. 160-166 ◽  
Author(s):  
Haopeng Jiao ◽  
Tianhai Yan ◽  
David A. Wills ◽  
Alistair F. Carson ◽  
David A. McDowell
Keyword(s):  
Methane Emission ◽  
Prediction Models ◽  
Holstein Cattle ◽  
Enteric Fermentation

scholarly journals Assessment of methane emissions from Danish livestock production practices using a tracer gas dispersion method

2020 ◽  
Author(s):  
Nathalia dos Reis Vechi ◽  
Antonio Delre ◽  
Charlotte Scheutz
Keyword(s):  
Remote Sensing ◽  
Methane Emission ◽  
Dairy Farms ◽  
Livestock Production ◽  
Methane Emissions ◽  
Anthropogenic Sources ◽  
Tracer Gas ◽  
Dispersion Method ◽  
Enteric Fermentation ◽  
Gas Dispersion

&lt;p&gt;One of the largest methane anthropogenic sources worldwide is livestock production. In Denmark, this contribution reached 81.1% of total anthropogenic methane, divided into both enteric fermentation and manure management emissions (Nielsen et al., 2019). Numerous factors can influence methane emissions from livestock production. The development of strategies to measure and monitor this anthropogenic activity allows the identification of efficient mitigation actions. The dynamic tracer gas dispersion method (TDM) is a ground-based remote sensing method, which combines a controlled release of tracer gas from the target source with concentration measurements downwind of the same source. TDM has been compared to other remote sensing techniques and widely applied for methane quantification from many facilities (Samuelsson et al., 2018). Previous studies found that this method is very likely to reached up to only 20% of error (Fredenslund et al., 2019). For livestock methane quantification, TDM has been used before releasing a strong greenhouse gas (SF&lt;sub&gt;6&lt;/sub&gt;) with mostly stationary point sampling setup. The aim is to verify the suitability of the method for these facilities and identify the differences between farming approaches. Furthermore, the comparison of the measured emissions with inventory estimation could show the accuracy of the later.&lt;/p&gt;&lt;p&gt;This study uses acetylene as tracer gas and measurements performed with a fast responding and highly sensitive gas analyzer by Picarro. On this project, emissions from six livestock facilities (dairy cows and swine production) were investigated along one year.&lt;/p&gt;&lt;p&gt;Dairy farms were the largest methane emitters per head (Around 40 gCH&lt;sub&gt;4&lt;/sub&gt;/head/h). Results show that management practices might cause different methane emissions from dairy farms. Similar result was observed analyzing emissions from pig facilities (Around 6 gCH&lt;sub&gt;4&lt;/sub&gt;/head/h), with an influence of animal life stage. The sow&amp;#8217;s farm had the highest methane emission factor when compared to fattening pigs, while manure acidification treatment might have a positive impact on reducing methane emission.&lt;/p&gt;&lt;p&gt;The successful application in this study of the TDM showed that this method is a valuable tool to support Danish farming strategies to meet ambitious GHG emission reduction targets.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Fredenslund, A. M., Rees-White, T. C., Beaven, R. P., Delre, A., Finlayson, A., Helmore, J., &amp;#8230; Scheutz, C. (2019). Validation and error assessment of the mobile tracer gas dispersion method for measurement of fugitive emissions from area sources. Waste Management, 83, 68&amp;#8211;78.&lt;/p&gt;&lt;p&gt;Nielsen, O.-K., Plejdrup, M. S., Winther, M., Nielsen, M., Gyldenk&amp;#230;rne, S., Mikkelsen, M. H., &amp;#8230; Hansen, M. G. (2019). Denmark&amp;#8217;s National Inventory Report 2019 (Emission I).&lt;/p&gt;&lt;p&gt;Samuelsson, J., Delre, A., Tumlin, S., Hadi, S., Offerle, B., &amp; Scheutz, C. (2018). Optical technologies applied alongside on-site and remote approaches for climate gas emission quantification at a wastewater treatment plant. Water Research, 131, 299&amp;#8211;309.&lt;/p&gt;

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

2015 ◽  
Author(s):  
Namchul Jo ◽  
Jongnam Kim ◽  
Seongwon Seo
Keyword(s):  
Methane Emission ◽  
Emission Factor ◽  
Ghg Emissions ◽  
Mitigation Strategy ◽  
Accurate Estimation ◽  
Parameter Estimates ◽  
Tier 2 ◽  
Enteric Fermentation ◽  
Significant Difference ◽  
Tier 1

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.

Sign in / Sign up

Export Citation Format

Share Document