Assessing the Greenhouse Gas Mitigation Effect of Removing Bovine Trypanosomiasis in Eastern Africa

MacLeod, Michael; Eory, Vera; Wint, William; Shaw, Alexandra; Gerber, Pierre; Cecchi, Giuliano; Mattioli, Raffaele C.; Sykes, Alasdair; Robinson, Timothy P.

doi:10.3390/su10051633

Cited by 16 publications

(5 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Approaches differ regionally, with more focus on direct, technical options in Developed Countries, and improved efficiency in developing countries (Caro Torres et al 2016;Mottet et al 2017b;MacLeod et al 2018;Frank et al 2018). A recent assessment finds greatest economic (up to USD100 tCO 2 -eq -1 ) potential (using the IPCC AR4 GWP100 value for CH 4 ) for 2020-2050 in Asia and the Pacific (32.9 MtCO 2 -eq yr -1 ) followed by Developed Countries (25.5 MtCO 2 -eq yr -1 ) (Roe et al 2021).…”

Section: Enteric Fermentationmentioning

confidence: 99%

Agriculture, Forestry and Other Land Uses (AFOLU)

2023

Climate Change 2022 - Mitigation of Climate Change

View full text Add to dashboard Cite

Chapter 7 Agriculture, Forestry and Other Land Uses (AFOLU) CH 4 MtCH 4 yr -1 157.0 ± 47.1 c 207.5 ± 62.2 364.4 ± 109.3 -iGtCO 2 -eq yr -1 4.2 ± 1.3 g 5.9 ± 1.8 10.2 ± 3.0 41%N 2 O MtN 2 O yr -1 6.6 ± 4.0 c 2.8 ± 1.7 9.4 ± 5.6GtCO 2 -eq yr -1 1.8 ± 1.1 g 0.8 ± 0.5 2.6 ± 1.5 69% Total jGtCO 2 -eq yr -111.9 ± 4.4 (CO 2 component based on book-keeping models, managed soils and pasture) 44 ± 3.4 55.9 ± 6.1 21% a Estimates are given until 2019 as this is the latest date when data are available for all gases, consistent with Chapter 2, this report. Positive fluxes are emission from land to the atmosphere. Negative fluxes are removals. b Net anthropogenic flux of CO 2 are due to land-use change such as deforestation and afforestation and land management, including wood harvest and regrowth, peatland drainage and fires, cropland and grassland management. Average of three bookkeeping models (Hansis et al. 2015; Houghton and Nassikas 2017; Gasser et al. 2020), complemented by data on peatland drainage and fires from FAOSTAT (Prosperi et al. 2020) and GFED4s (van der Werf et al. 2017). Bookkeeping based CO 2 -LULUCF emissions (5.7±4.0) are consistent with AR6 WGI and Chapter 2 of this report. The value of 5.9(±4.1) includes CO 2 emissions from urea application to managed soils and pasture. Comparisons with other estimates are discussed in 7.2.2. Based on NGHGIs and FAOSTAT, the range is 0 to 0.8 GtCO 2 yr -1 . c CH 4 and N 2 O emission estimates and assessed uncertainty of 30 and 60% respectively, are based on Emissions Database for Global Atmospheric Research (EDGAR) data (Crippa et al. 2021) in accordance with Chapter 2, this report (Sections 2.2.1.3 and 2.2.1.4). Both FAOSTAT (Tubiello 2019; USEPA 2019; FAO 2021a) and the USA EPA (USEPA 2019) also provide data on agricultural non-CO 2 emissions, however, mean global CH 4 and N 2 O values considering the three databases are within the uncertainty bounds of EDGAR. EDGAR only considers agricultural and not overall AFOLU non-CO 2 emissions. Agriculture is estimated to account for approximately 89 and 96% of total AFOLU CH 4 and N 2 O emissions respectively. See Section 7.2.3 for further discussion.d Total non-AFOLU emissions are the sum of total CO 2 -eq emissions values for energy, industrial sources, waste and other emissions with data from the Global Carbon Project for CO 2 , including international aviation and shipping, and from the PRIMAP database for CH 4 and N 2 O averaged over 2007-2014, as that was the period for which data were available. e The modelled CO 2 estimates include natural processes in vegetation and soils and how they respond to both natural climate variability and to human-induced environmental changes, for example, the response of vegetation and soils to environmental changes such as increasing atmospheric CO 2 concentration, nitrogen deposition, and climate change (indirect anthropogenic effects) on both managed and unmanaged lands. The estimate shown represents the average from 17 Dynamic Global Vegetation Models with 1SD uncertainty (Friedlingstei...

show abstract

Section: Enteric Fermentationmentioning

confidence: 99%

Agriculture, Forestry and Other Land Uses (AFOLU)

2023

Climate Change 2022 - Mitigation of Climate Change

View full text Add to dashboard Cite

show abstract

“…Improving the health status of animals is one option to maintain high production efficiency of livestock and in this way keep the emission intensity at the minimal level. In their paper, MacLeod et al [19] apply the FAO livestock model GLEAM to quantify the greenhouse gas emissions from East African cattle production systems and the effects of an endemic disease trypanosomiasis on the emissions. The authors found that removing that disease could lead to a reduction in the emissions intensity per unit of protein produced, as a result of increases in milk yields and higher cow fertility rates.…”

mentioning

confidence: 99%

Achieving Environmentally Sustainable Livestock Production

Leinonen

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…A retrospective abattoir study of the liver fluke, Fasciola hepatica in beef cattle revealed a 4% reduction in daily live weight gain (LWG), an extra 11 days to slaughter and an increase in associated emissions intensity of 2% [ 32 ]. Similarly, using a hybrid modelling approach [ 33 ] estimated that the removal of trypanosomiasis, a disease caused by a tsetse fly transmitted protozoan parasite, from East African cattle would result in a reduction in emissions intensity between 0 and 8%, driven largely by increases in milk yield and fertility rates.…”

Section: Current Evidence On the Impacts Of Animal Health Conditions ...mentioning

confidence: 99%

Improve animal health to reduce livestock emissions: quantifying an open goal

Kyriazakis,

Arndt,

Aubry

et al. 2024

Proc. R. Soc. B.

View full text Add to dashboard Cite

Greenhouse gas (GHG) emissions from livestock production must be urgently tackled to substantially reduce their contribution to global warming. Simply reducing livestock numbers to this end risks impacting negatively on food security, rural livelihoods and climate change adaptation. We argue that significant mitigation of livestock emissions can be delivered immediately by improving animal health and hence production efficiency, but this route is not prioritized because its benefits, although intuitive, are poorly quantified. Rigorous methodology must be developed to estimate emissions from animal disease and hence achievable benefits from improved health through interventions. If, as expected, climate change is to affect the distribution and severity of health conditions, such quantification becomes of even greater importance. We have therefore developed a framework and identified data sources for robust quantification of the relationship between animal health and greenhouse gas emissions, which could be applied to drive and account for positive action. This will not only help mitigate climate change but at the same time promote cost-effective food production and enhanced animal welfare, a rare win–win in the search for a sustainable planetary future.

show abstract

Assessing the Greenhouse Gas Mitigation Effect of Removing Bovine Trypanosomiasis in Eastern Africa

Cited by 16 publications

References 31 publications

Agriculture, Forestry and Other Land Uses (AFOLU)

Agriculture, Forestry and Other Land Uses (AFOLU)

Achieving Environmentally Sustainable Livestock Production

Improve animal health to reduce livestock emissions: quantifying an open goal

Contact Info

Product

Resources

About