ISSN: 2641-2969
Annals of Environmental Science and Toxicology
Research Article       Open Access      Peer-Reviewed

Estimation of enteric methane emission factor in cattle species in Ethiopia using IPCC tier 2 methodology

Million Tadesse, Kefale Getahun* and Ulfina Galmessa

Ethiopian Institute of Agricultural Research, Holetta Research Center; P O Box 2003 Addis Ababa or 31 Holetta, Ethiopia
*Corresponding author: Kefale Getahun, Researcher, Livestock Science, Ethiopian Institute of Agricultural Research, Holetta Research Center; P O Box 2003 Addis Ababa or 31 Holetta, Ethiopia, Tel: +251913856016; E-mail: kefalegetahun@gmail.com
Received: 04 March, 2022 | Accepted: 11 March, 2022 | Published: 12 March, 2022
Keywords: Animal performance; Cattle subcategory; Emission estimation; Greenhouse gas

Cite this as

Tadesse M, Getahun K, Galmessa U (2022) Estimation of enteric methane emission factor in cattle species in Ethiopia using IPCC tier 2 methodology. Ann Environ Sci Toxicol 6(1): 013-018. DOI: 10.17352/aest.000047

Copyright

© 2022 Tadesse M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Aims: The livestock production system contributes to global climate change directly through the production of methane (CH4) from enteric fermentation, CH4 and nitrous oxide (N2O) from manure management. Enteric CH4 emission from livestock is the major contributor to greenhouse gas (GHG) emission from livestock in Ethiopia. National inventory and reporting of enteric CH4 emission in cattle species in Ethiopia are based on default emission factor (tier 1 methodology) developed by Intergovernmental Panel on Climate Change (IPCC). These enteric CH4 emissions are influenced by different factors such as livestock feed characteristics, livestock management, and livestock production and productivity. Hence, its estimation requires accurate data specific to the condition of the livestock production system in the country. The objective of this study was to estimate enteric CH4 emission from cattle species in Ethiopia.

Methodology: Enteric CH4 emission was estimated using IPCC tier 2 methods using input data collected through survey and literature data on livestock and feed characteristics in Ethiopia.

Results: Results indicated that enteric CH4 emission factors among indigenous cattle were 30.27, 18.52, 31.55, 29.82, 32.48, and 12.60 kg per head per year for matured females >2 years old, females 1-2 years, bullocks/oxen, breeding bulls >2 years old, males 1-2 years and calves <1 year’s old, respectively. Among crossbred dairy cattle, enteric CH4 emission factors were found to be 36.21, 19.98, 27.90, 25.51, 5.45 kg per head per year for matured females >2 years, females 1-2 years, matured males >2 years, males 1-2 years and calves <1 year’s age, respectively. The weighted average CH4 emission factor for indigenous cattle and crossbred dairy cattle were 26 and 30.71kg/head/year, respectively.

Conclusion: Enteric CH4 emission factors for nondairy indigenous and crossbred cattle using IPCC tier 2 methodology were lower when compared to IPCC tier 1 estimate. Our study recommends IPCC tier 2 methodology, for national enteric CH4 emission inventory and reporting for cattle species in Ethiopia. The present study was based on limited survey and published data, uncertainties may have presented with, some of production and performance data. Further research is required to estimate enteric CH4 emission using more detailed cattle production and feed characterization data.

Introduction

The livestock production system contributes to global climate change directly through the production of CH4 from enteric fermentation and manure management and N2O from manure management. Methane is the most important greenhouse gas that traps over 21 times more heat per molecule compared to carbon dioxide CO2 [1]. One of the largest biogenic (i.e., produced by a living organism) sources of CH4 is digestive fermentation from ruminant animals [2]. CH4 is emitted through methanogens under anaerobic conditions through enteric fermentation and in manure storage. In general, enteric methane production by ruminants is influenced by dietary characteristics (example daily feed intake, type of diet, and diet composition), livestock production (such as live weight, growth rate, stage of production, reproduction, and feeding situation) Hence its estimation requires accurate data specific to the condition of the country.

Currently, in Ethiopia, national inventories of CH4 emission from enteric fermentation are estimated using the Intergovernmental Panel on Climatic Change (IPCC) tier-1 methodology, which calculates CH4 emissions for each animal category by multiplying the animal population by the default emissions factor associated with the specific animal category [3]. Weight, age, sex, and feeding systems are assumed similar within the animal category. Using these estimates, it has been determined that Greenhouse Gas (GHG) emission from Ethiopian cattle accounts for 65 Mt CO2e in 2011, enteric fermentation accounting for 90% of total livestock emissions [4]. According to [3], countries using an IPCC tier-2 methodology can improve emission estimates and reduce uncertainties as this methodology considers several variables influencing enteric CH4 emissions, including weight, age, gender, feeding systems, etc. As enteric fermentation is a key source of GHG emissions in the agricultural sector in Ethiopia, adopting the IPCC Tier-2 methodology will improve our ability to determine the mitigation value of various on-farm practices. Several countries for example Canada, the United States, and Australia are already using Tier-2 methodology. The objectives of this study were to estimate enteric CH4 emissions from the Ethiopian cattle population using the IPCC Tier-2 methodology and further, to compare these values to emission factors generated by the IPCC Tier-1 methodology.

Materials and methods

Cattle performances and production practices

A survey posing questions regarding cattle management, feed, and feeding practices was prepared and administered to smallholder farmers. When available, data from producer surveys were utilized to describe the production environment and associated performances of the cattle category. Additional information was sought from personal communication with a researcher at federal and regional research institutions, as well as from district-level development workers.

The survey and published reports provided information in the following areas: average body weight, mature weight, daily weight gain, average daily milk yield, milk fat content, type of production environment (pasture vs. confinement), pregnancy rates, type and quality of feed fed for each cattle sub-category. When not provided by the survey data for example live weight for indigenous cattle (Table 1), daily weight gain (Table 2), and Digestible Energy (DE%) values of the feedstuffs were obtained from the published literature [3,5]. For crossbred dairy cattle, the live weight of the animal was obtained by taking heart girth measurements from selected dairy farms around Addis Ababa milk shade for defined IPCC sub-categories. However, for indigenous cattle average live weight was generated from data collected from published and research centers reports of different indigenous cattle breeds in Ethiopia (Table 1). DE% value of 50% for indigenous cattle on grazing and crop residue, while DE% value of 65% for crossbred dairy cattle under improved feed, supplementation with concentrate diet was used [3,5]. The average daily growth rate of growing animals for both indigenous cattle and crossbred dairy cattle was obtained from a published report (Table 2).

Emission estimates

Enteric CH4 emissions factors were calculated using IPCC Tier-2 equations [3]. In doing so, some assumptions were made:

  • Methane conversion rates (Ym), percent of gross energy intake applied to enteric CH4 emission estimates were 6.5% for both indigenous and crossbred dairy cattle [3];
  • Subcategory used were matured females >2 years, females 1-2 years, males >2 years, bullocks/oxen, males 1-2 years, and calves <1-year-old.
  • To calculate the energy for work for indigenous cattle, bullock or oxen was assumed to work for 1.37 hours per day other cattle for about 0.55 hours per day [3].

The amount of CH4 produced, also known as the Emission Factor (EF), was calculated using the Tier-2 equations and expressed as kg per head per year. For most categories, the time that cattle are in a given production environment is equal to one a year but for young animals, 180 days were used [3].

CH4 emission factor estimate for each cattle sub-category was multiplied by their proportional contribution of sub-category to the total population of that category to arrive at weighted average CH4 emission factor. The proportion of each sub-sub category to total population was derived from cattle population data from the Central Statistical Authority of Ethiopia [6] by dividing sub-category population number to total population number of that category.

The animal performances information obtained from the survey and published literature were used to estimate Gross Energy (GE) required for each cattle subcategory. Although not used in the calculation to estimate enteric CH4 emissions, feed intake was checked and compared with the weight of the animal in each subcategory by dividing the GE for each category by a default energy density of 18.45MJ/ kg, as suggested by [3].

Estimation of Gross Energy (GE) intake

Average GE intake was estimated from net energy requirement for maintenance, activity, work, lactation, pregnancy, and net energy for growth for young animals using IPCC tier-2 methodology. The equation used to estimate Gross Energy intake (GE) is as follows:

GE= { ( NEm+NEa+NEwork+NEl+NEp ) REM + NEg REG } DE%/100 MathType@MTEF@5@5@+=feaaguart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=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@6497@

Where;

GE= Gross energy in megajoule, (MJ/animal/day)

NEm=net energy for maintenance

NEa= Net energy for activity

NEwork= Net energy for work

NEl= Net energy for lactation

NEp= Net energy for pregnancy

NEg=Net energy for growth of young animals

REM=Ratio of net energy available in the diet for maintenance to digestible energy consumed

REG= Ratio of net energy available in the diet for growth to digestible energy consumed

DE% = digestible energy expressed as a percentage of gross energy

Estimating enteric CH4 emission factor

Methane emission factor from enteric fermentation in cattle was calculated using estimated GE intake and methane conversion factor (Ym) as input in the following equation;

EF={ GE( Ym 100 )365 55.65 } MathType@MTEF@5@5@+=feaaguart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqcLbsaqaaaaaaaaaWdbiaadweacaWGgbGaeyypa0Jaai4EaKqbaoaalaaak8aabaqcLbsapeGaam4raiaadweajuaGdaqadaGcpaqaaKqba+qadaWcaaGcpaqaaKqzGeWdbiaadMfacaWGTbaak8aabaqcLbsapeGaaGymaiaaicdacaaIWaaaaaGccaGLOaGaayzkaaqcLbsacaaIZaGaaGOnaiaaiwdaaOWdaeaajugib8qacaaI1aGaaGynaiaac6cacaaI2aGaaGynaaaacaGG9baaaa@4DB1@

Where;

EF= Methane emission from enteric fermentation, kg CH4/animal/year

GE= Gross energy intake, MJ/head/day

Ym= Methane conversion factor, percent of gross energy in feed converted to methane [3], Ym value of 6.5% reported by [3] was used for all sub-categories.

The factor 55.65 (MJ/kg methane) is the energy content of CH4.

Comparison with IPCC tier 1

The computed enteric CH4 emission factors obtained using IPCC Tier-2 methodology were compared with IPCC tier-1 CH4 emission factors reported for other cattle in Africa [3]. The IPCC tier-1 emission factors (kg of CH4 per head per year used for comparison were: 41 kg/head for mature females grazing and bullock under stall feeding, and 49 kg/head for bull grazing [3].

Result and discussion

The result from the study (Table 3) indicated that enteric CH4 emission factors using IPCC Tier-2 approach for indigenous cattle were 30.27, 18.52, 31.55, 29.82, 32.48 and 12.60, Kg per head per year for mature females >2 years, females 1-2 years, bullocks/oxen, mature male >2 years, males 1-2 years and calves <1-year-old, respectively. For crossbred dairy cattle, enteric CH4 emission factors were found to be 36.21, 19.98, 27.90, 25.51, 5.45 kg per head per year for mature females >2 years, females 1-2 years, mature males >2 years, males 1-2 years and calves <1 year’s old, respectively. The weighted average emission factor for indigenous cattle and crossbred dairy cattle were 26.00 and 30.71 kg/head/year, respectively. Crossbred dairy cattle was higher initial body weight, higher milk yield compared with indigenous cattle leading to increased energy requirements for maintenance and for production (Table 3). However, on the base of CH4 per unit of milk yield crossbred dairy cattle emit less compared to indigenous.

Enteric CH4 emission factor obtained for females >2 years old (indigenous cattle) in the present study is similar with emission factor ranging from 27.1 to 34.1kg/head/year reported in Kenya for female cattle >2 years old but enteric CH4 emission factor for males >2 years age in the present study is lower than emission factor of 35.9 kg/year reported for male greater than 2 years old in Kenya [22]. Emission factors for indigenous cattle females of 1-2 years age class (18.52 kg CH4 /head/year) in the present study were close to the mean enteric CH4 emission factor of 23kg reported for females 1-2 years old in Kenya in cattle species [22]. Kouazounde, et al. [23] reported an average CH4 emission factor of 39kg per head for cattle from Benin, which is higher than the emission factor for mature females in the present study. Moreover, the enteric CH4 emission factor for indigenous cattle (nondairy cattle) in the present study were lower than enteric CH4 emission factors ranging from 31.70 to 106.70 kg/head/year with a weighted average of 65.13kg CH4/head/year [24] reported in South Africa for non-dairy cattle. The variation in emission factors estimated in the present study from literature reports was attributed to the difference in breed [23], feed intake and feed types [25,26], animal management, and body size [3,25].

For crossbred dairy cattle, enteric CH4 emission factors in the present study were lower than enteric CH4 emission factors ranging from 83.70 to 112.36kg CH4/head/year [24,27] reported for dairy cattle in South Africa. This might be attributed to the live weight of these cattle could be higher than that of the cattle in our study (and that voluntary intake would have been commensurately larger). A higher emission factor of 126 kg/head/year was also reported for dairy cows in Canadian dairy cattle [28] using the same IPCC Tier-2 methodology. These variabilities might be related to breed and body size differences in energy requirement for maintenance, production, and or locomotion.

The enteric CH4 emission factor of 19.98 kg/head/year for crossbred dairy cattle of 1-2 years of age in the present study was lower than the enteric CH4 emission factor of 62 kg /head/year for Canada dairy cattle [28]. A higher emission factor of 72 kg CH4 /head/year was also reported [29] for dairy heifers in Canada using IPCC Tier-2 methodology. In a similar way, a higher emission factor of 73 kg of CH4 /head/year was also reported in the United States for beef heifers, 12–23 months of age, using the same IPCC Tier-2 methodology (Inventory of US Greenhouse Gas Emissions and Sinks, 1990–2000). These lower emission factors in Ethiopian crossbred dairy cattle and heifers compared to the above reports could be attributed to lower feed intake as a result of lower body weight [25], the difference in feed characteristic [25,26], and breed and age differences [23].

Comparison of methodologies

A comparison of enteric CH4 emission factors using IPCC Tier-1 and IPCC Tier-2 methodology is given in Table 4. In general, IPCC Tier-2 estimates for enteric CH4 emissions in the present study were lower than those generated using IPCC Tier-1 methodology. For example, emission factors for mature indigenous nondairy females using IPCC Tier-2 were lower than IPCC Tier-1 by 26%. Moreover, IPCC Tier-1 estimates were 39% and 23% higher for bulls grazing and bullock when compared with the result obtained using IPCC Tier-2 methodology. In general, the lower CH4 emission factors obtained using IPCC tier-2 method compared to IPCC tier-1 values in the present study are attributed to the use of country-specific data on production, live weight, and average daily weight gain. This can be expected as IPCC Tier-1 was not based on country-specific data and may not account for differences in performances [3]. The weighted average CH4 emission factors obtained in the present study for indigenous and crossbred dairy cattle using tier-2 methodology were lower than the values generated using the IPCC tier-1 method by 15% and 36%, respectively (Table 4).

Conclusion

Enteric CH4 emission factors for nondairy indigenous and crossbred dairy cattle were lower compared to others in the literature, which is attributed to the difference in breed, feed intake and feed types, animal management, the body size difference in energy requirement for maintenance, production, and or locomotion. Moreover, the enteric CH4 emission factor for nondairy indigenous cattle in the present study using IPCC tier-2 was lower compared to IPCC tier-1 estimates. The lower enteric CH4 emission factor using IPCC tier-2 methodology compared to IPCC tier-1 estimate was attributed to the use of cattle characterization data generated in Ethiopia livestock production system. Our study recommended the use of IPCC tier-2 methodology in methane emission inventory preparation and reporting for cattle species in Ethiopia. The present results were the first attempts to estimate enteric CH4 emission using IPCC tier-2 methodology, based on limited published data on production and feed characterization data. Further research is required to improve emission factors for Ethiopian livestock production using detailed livestock and feed characterization data in IPCC tier-2 and recent advanced technologies.

Acknowledgment is granted to the experts and farmers for their valuable time during the survey work.

Conflict of interests

The authors declared that no potential conflict of interest is reported regarding the subject matter of this manuscript either for financial, commercial, or intellectual purposes.

Authors’ contribution

Both authors contributed their time in the idea generation, proposal writing, data collection, data analysis, data interpretation, and manuscript drafting (writing) and, approved for submission.

  1. EPA (United States Environmental Protection Agency) (2003) Report on the environment 172. Link: https://bit.ly/34yfVko
  2. Alan D (2008) Strategies to Reduce Greenhouse Gas Emissions through feeding and grazing management. Swift Current Research Centre EMBO Rep 9: 508–511.
  3. IPCC (International Panel for Climate Change) (2006) Guideline for National Green House Gas Inventory, Agriculture, forestry and other land use, Chapter 10 emissions from Livestock and manure management. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004. Link: https://bit.ly/3hXsWaa
  4. CRGE (Ethiopia’s Climate Resilience Green Economy) (2011) Green Economy Strategy. Federal Republic of Ethiopia, Addis Ababa, Ethiopia. Link: https://bit.ly/3HWNhao
  5. Seyoum B, Zinash S, Dereje F (2007) Chemical Composition and Nutritive Values of Ethiopian Feeds. Research Report 73, EIAR, Addis Ababa, Ethiopia.
  6. CSA (Central Statistical Authority) (2013) Agricultural sample survey 2010/11. Report on livestock and livestock characteristics. Central Statistical Authority. 2. Link: https://stanford.io/3hVFgrL
  7. FAO (Food and Agricultural Organization of United Nations) (2002) data 2002 Rome, Italy.
  8. Hailemariam M (1994) Genetic Analysis of Boran, Friesian and Crossbred Cattle in Ethiopia. Ph.D. thesis. Swedish University of Agricultural Sciences. Upsala, Sweden 84-117. Link: https://bit.ly/3CxEfiS
  9. DAGRIS (Domestic Animal Genetic Resources Information System) (2006) Domestic Animal Genetic Resources Information System (DAGRIS). (eds. J.E.O. Rege, W. Ayalew, E. Getahun, O. Hanotte and T. Dessie). International Livestock Research Institute, Addis Ababa, Ethiopia. Link: https://bit.ly/3CxEc6G
  10. DAGRIS (Domestic Animal Genetic Resources Information System) (2007) International Livestock Research Institute (ILRI). Addis Ababa, Ethiopia. Link: https://bit.ly/3I2FA2k
  11. Banjaw K, Haile-Mariam M (1994) Productivity of Boran cattle and their Friesian crosses at Abernosa ranch Rift Valley of Ethiopia. II. Growth performance. Trop Anim Health Prod 26: 49-57. Link: https://bit.ly/3pW1tds
  12. Beyene K (1992) Estimation of additive and non-additive genetic effects for growth, milk yield and reproduction traits of crossbred (Bos-taurus * Bos-indicus) cattle in the wet and dry environment in Ethiopia. PHD. Thesis, Cornel University. Ithaca, NY 253. Link: https://bit.ly/36adqVM
  13. Demeke S, Neser FWC, Schoeman SJ (2003) Early growth performance of Bos Taurus x Bos indicus crosses in Ethiopia. Evaluation of different crossbreeding Models. Journal of Animal Breeding and Genetics 120: 39-50. Link: https://bit.ly/3tR60yW
  14. Demeke S, Neser FWC, Schoeman SJ (2004) Estimation of genetic parameters for Boran, Friesian, and crosses of Friesian and Jersey with Boran in the Tropical high lands of Ethiopia. Milk production traits and cow weight. Journal of Animal Breeding and Genetics 121: 163-175. Link: https://bit.ly/3HXTWkt
  15. Abera H, Abegaz S, Mekasha Y (2011) Genetic parameter estimates of pre-weaning weight of Horro (Zebu) and their crosses with Holstein Friesian and Jersey cattle breeds in Ethiopia. International Journal of Livestock Production 2: 84-91. Link: https://bit.ly/3tSTrn3
  16. Kiwuwa GH, Trail JCM, Kurtu MY, Worku G, Anderson F, Durkin J (1983) Crossbred dairy cattle productivity in Arsi Region, Ethiopia. ILCA Research Report 11, International Livestock Centre for Africa 1-29. Link: https://bit.ly/3ME9TQu
  17. Moges D, Baars R (1998) Long-term evaluation of milk production and reproductive performance of dairy cattle at Alemaya. In: Proc. of 6th Annual Conference of Ethiopian Society of Animal Production (ESAP) 176-183. Link: https://bit.ly/3J9N595
  18. Epsten (1971) The origin of the domestic Animals of Africa. Africana publishing corporation, New York, USA. Link: https://bit.ly/3I2fFIb
  19. WARC (Werer Agricultural Research Center). Annual Livestock research review report, 2018, Addis Ababa, Ethiopia.
  20. Trail JCM, Gregory KE (1981) Characterization of Boran and Sahiwal breeds of cattle for economic characters. Journal of Animal Science 52: 1286-1293. Link: https://bit.ly/3HZyawN
  21. Goshu M (1983) Preliminary Evaluation of Holstein Breeds and their Half breed for milk production. Ethiopian Journal of Agricultural Science 5: 43-49. Link: https://bit.ly/3vZcjn0
  22. Goopya JP, Onyangoa AA, Dickhoefer U, Butterbach-Bahla K (2018) A new approach for improving emission factors for enteric methane emissions of cattle in smallholder systems of East Africa. Agricultural Systems 161: 72-80. Link: https://bit.ly/3t3L60D
  23. Kouazounde JB, Gbenou JD, Babatounde S, Srivastava N, Eggleston SH, et al. (2015) Development of methane emission factors for enteric fermentation in cattle from Benin using IPCC Tier 2 methodology. Animal 9: 526–533. Link: https://bit.ly/37oL7np
  24. Moeletsi ME, Tongwane MI, Mdlambuzi T, Grootboom L, Mliswa VK, et al. (2015) Improvement of the Greenhouse Gas Emissions Inventory for the Agricultural Sector; DFID: Pretoria, Southern Africa.
  25. Frank OM, Michael R, John C, Pat O, Owen C, et al. (2000) Climate Change Emissions of Greenhouse Gases from Agriculture and Strategies for their Reduction (2000-LS-5.1.1) Synthesis Report. UCD School of Agriculture, Food Science and Veterinary Medicine Teagasc, Johnstown Castle Research Centre, Co. Wexford, Ireland.
  26. Moss A, Jouany JP, Newbold J (2000) Methane production by ruminants: its contribution to global warming. Annales de zootechnie INRA/EDP Sciences 49: 231-253. Link: https://bit.ly/3pWHUC1
  27. Moeletsi ME, Tongwane MI, Tsubo M (2017) Enteric Methane Emissions Estimate for Livestock in South Africa for 1990–2014. Atmosphere 8: 69. Link: https://bit.ly/3KB0hUR
  28. Kebreab EK, Wagner-Riddle C, France F (2006) Methane and Nitrous Oxide emission from Canadian Animal Agriculture. Can. Journal of Animal Science 86: 135-158. Link: https://bit.ly/3CzyuRS
  29. AARFD (Alberta Agriculture, Food and Rural Development) (2003) Development of farm-level greenhouse gas assessment: Identification of knowledge gaps and development of a science plan. AARI Project Number 2001J204 203.