A new approach for improving emission factors for enteric methane emissions of cattle in smallholder systems of East Africa – Results for Nyando, Western Kenya

Goopy, John P.; Onyango, Alice A.; Dickhoefer, Uta; Butterbach‐Bahl, Klaus

doi:10.1016/j.agsy.2017.12.004

Cited by 60 publications

(95 citation statements)

References 23 publications

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“…The importance of the dung C/N ratio for CH 4 emissions from dung patches was also highlighted by Pelster et al (). However, based on our data, total CH 4 emissions from dung patches would amount to <100 g CH 4 head −1 yr −1 , which is small compared to annual CH 4 emissions from enteric fermentation in 1‐ to 2‐year old steers of 30 kg CH 4 head −1 yr −1 in a study in Kenya (Goopy et al, ).…”

Section: Discussionmentioning

confidence: 56%

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Zhu

Merbold

Pelster

et al. 2018

Global Biogeochemical Cycles

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To improve estimates of agricultural greenhouse gas emissions in sub‐Saharan Africa, we measured over six individual periods of 25–29 days fluxes of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) with subdaily time resolution from dung patches of different quality (C/N ratio: 23–41) and quantity (0.5 and 1.0 kg) on a Kenyan rangeland during dry and wet seasons. Methane emissions peaked following dung application, whereas N2O and CO2 fluxes from dung patches were similar to fluxes from rangeland soils receiving no N additions. Greenhouse gas emissions scaled linearly with dung quantity during both seasons. Dung with a low (23) C/N ratio produced up to 10 times more CH4 than dung with a high (41) C/N ratio. Overall, CH4 emission factors (EFs) ranged from 0.001 to 0.042%, lower than those derived in temperate regions. Cumulative CO2 and N2O emissions were similar for all treatments across the different seasons. The N2O EF ranged from 0 to 0.01%, less than 1% of the Intergovernmental Panel on Climate Change Tier 1 default EF (2%) for N2O emissions from dung and urine patches, likely because of the low dung N content (9.7–16.5 g N kg−1 dry matter). However, these results were consistent with the updated cattle dung EF (0.2%) developed for Kenya in 2016/2017 (EF database ID# 422665). In view of the wide range of climates, soils, and management practices across sub‐Saharan Africa, development of robust GHG EFs from dung patches for SSA requires additional studies.

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Section: Discussionmentioning

confidence: 56%

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Zhu

Merbold

Pelster

et al. 2018

Global Biogeochemical Cycles

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“…Although several changes to improve the precision of measurement were made in the study, including better scheduling of LW measurement and the assessment of milk energy composition, in many respects, the present study was limited by the same factors as the Nyando study (Goopy et al 2018). The energy value of tissue is highly variable, depending on its A There were no young males in the upper midlands zone during the short rains; thus, the emission factor was calculated by multiplying the daily CH 4 production (DMP) by 274 days (3 seasons) instead of 365 days (4 seasons).…”

Section: Discussionmentioning

confidence: 99%

“…As such, findings cannot be extrapolated to a national or even regional level without further corroboration; there is a strong need for further region-specific livestock and feed data to facilitate the development of Tier II enteric CH 4 EFs on a wider scale. In the present study, we hypothesised that the (Tier II) EFs we derived in Nandi County would not be different from those derived from the study in Nyando (Goopy et al 2018), as both regions have broadly comparable livestock systems characterised by small land areas, low numbers of livestock per household and low farm inputs, and are located in the western highlands of Kenya.…”

Section: Introductionmentioning

confidence: 99%

“…Animal performance and production data Data collection followed the protocol described in Goopy et al (2018), but briefly, animal performance and production data from measurements of 1143 cattle in the three AEZs formed the basis of the present study and all cattle present in each household during the survey were included. During the second household visit (the first having been to identify participants), animals were identified using ear tags (Allflex Europe SA, Vitre, France) with unique numbers.…”

Section: Animal Feeding/grazing Managementmentioning

confidence: 99%

“…Energy expenditure was calculated using equations from Goopy et al (2018), which, in turn, were derived from equations published in 'Nutrient Requirements of Domestic Ruminants' (Touchberry and Lush 1950). Animal data were analysed by group based on age and sex; females (>2 years), males (>2 years), heifers (1-2 years), young males (1-2 years) and calves (<1 year).…”

Section: Metabolisable Energy-requirement (Mer) Estimationmentioning

confidence: 99%

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Improved region-specific emission factors for enteric methane emissions from cattle in smallholder mixed crop: livestock systems of Nandi County, Kenya

et al. 2019

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Abstract. National greenhouse-gas (GHG) inventories in most developing countries, and in countries in Sub-Saharan Africa in particular, use default (Tier I) GHG emission factors (EFs) provided by the Intergovernmental Panel on Climate Change (IPCC) to estimate enteric methane (CH 4 ) emissions from livestock. Because these EFs are based on data primarily from developed countries, there is a high degree of uncertainty associated with CH 4 emission estimates from African livestock systems. Accurate Tier II GHG emission reporting from developing countries becomes particularly important following the Paris Climate agreement made at COP21, which encourages countries to mitigate GHG emissions from agricultural sources. In light of this, the present study provides improved enteric CH 4 emission estimates for cattle in Nandi County, Western Kenya, representing a common livestock production system found in East Africa. Using the data from measurements of liveweight and liveweight change, milk production and locomotion collected from 1143 cattle in 127 households across 36 villages over three major agro-ecological zones covering a full year, we estimated total metabolic energy requirements. From this and assessments of digestibility from seasonally available feeds, we estimated feed intake and used this to calculate daily CH 4 production by season, and, subsequently, created new EFs. Mean EFs were 50.6, 45.5, 28.5, 33.2 and 29.0 kg CH 4 /head.year for females (>2 years), males (>2 years), heifers (1-2 years), young males (1-2 years) and calves (<1 year) respectively, and were lower than the IPCC Tier I estimates for unspecified African adult cattle, but higher for calves and young males. Thus, using IPCC Tier 1 EFs may overestimate current enteric CH 4 emissions in some African livestock systems.

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Estimating Greenhouse Gas Emissions in the Pacific Island Countries

Mani

2020

Advances in Global Change Research

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A new approach for improving emission factors for enteric methane emissions of cattle in smallholder systems of East Africa – Results for Nyando, Western Kenya

Cited by 60 publications

References 23 publications

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya

Improved region-specific emission factors for enteric methane emissions from cattle in smallholder mixed crop: livestock systems of Nandi County, Kenya

Estimating Greenhouse Gas Emissions in the Pacific Island Countries

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