Estimation of greenhouse gas emissions from three livestock production systems in Ethiopia

2020 
Different livestock production systems contribute to globally Greenhouse gas emission (GHG) emission differently. The aim of this paper is to understand variation in emission in different production systems and it is also important for developing mitigation interventions that work for a specific production system.,In this study, the authors used the Global Livestock Environmental Assessment interactive model (GLEAM-i) to estimate the GHG emission and emission intensity and tested the effectiveness of mitigation strategies from 180 farms under three production systems in northern Ethiopia, namely, pastoral, mixed and urban production systems.,Production systems varied in terms of herd composition, livestock productivity, livestock reproductive parameters and manure management systems, which resulted in difference in total GHG emission. Methane (82.77%) was the largest contributor followed by carbon dioxide (13.40%) and nitrous oxide (3.83%). While both total carbon dioxide and methane were significantly higher (p < 0.05) in urban production system than the other systems emission intensities of cow’s milk and goat and sheep’s meat were lower in urban systems. Improvement in feed, manure management and herd parameters resulted in reduction of total GHG emission by 30, 29 and 21% in pastoral, mixed and urban production systems, respectively.,This study is a first time comparison of the GHG emission production by various production systems in northern Ethiopia. Moreover, it uses the GLEAM-i program for the first time in the ex ante settings for measuring and comparing emissions as well as for developing mitigation scenarios. By doing so, it provides information on the various livestock production system properties that contribute to the increase or decrease in GHG emission and helps in developing guidelines for low emission livestock production systems.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    10
    References
    1
    Citations
    NaN
    KQI
    []