Assessing marginal abatement cost for greenhouse gas emissions from livestock production in China and Europe - accounting for uncertainties
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Date
16//2/28/1Author
Koslowski, Frank Johannes
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Abstract
Climate change is probably the most challenging threat to mankind. International agreements
have acknowledged the fact that anthropogenic GHG emissions must be reduced
significantly to adhere to a maximum global warming of 2°C. The livestock sector plays a
key role in achieving this target as it is a significant source of GHG emissions. While the
livestock sector offers significant GHG reduction potential, it is currently neglected in
international and national mitigation efforts. Therefore, scientific research must guide
mitigation policy decisions with evidence of cost-efficient abatement potential that can be
achieved through various mitigation technologies.
Marginal Abatement Cost Curves (MACC) are an analytical tool for informing policy
makers about the cost-effectiveness (CE) of mitigation. MACCs provide a relatively clear
representation of a complicated issue based on their graphical design that prioritises various
mitigation options in terms of their CE of abatement and enables assessment of total GHG
reduction under a budget constraint. However, developing a MACC involves considerable
data collection, depends on various interdisciplinary information sources and the
methodology is subject to several limitations. These factors can result in uncertainties in
marginal abatement cost (MAC) results, the assessment of which is often neglected in
MACC literature.
This research shows the main GHG emission sources in livestock production and possible
mitigation options to reduce GHG emissions from these sources. After elaborating the
MACC methodology, advantages, disadvantages and limitation of the engineering MACC
are shown. This allows understanding the relevance of assessing and reporting uncertainty of
MACCs. Two engineering MACCs are developed that show the CE abatement potentials
available in the Chinese livestock sector and European Union 15 (EU-15) dairy sector in
2020, with emphasis on dietary mitigation options. The requirement of assessing CE of
abatement for individual mitigation options is highlighted by separate derivation of technical
and economic abatement potential for the EU-15 dairy sector. For the Chinese MACC, a
scenario analysis (SA) and for the European MACC, a Monte Carlo (MC) simulation are
utilised to show the relevance of assessing uncertainty in MACCs. To provide further
evidence, the overall range of CE estimates for eight mitigation options found in relevant
MACC literature is presented. This allows the generation of probability distribution
functions of CE for each mitigation option with kernel density estimation (KDE). The results from this study show the significance of livestock and dairy production related
GHG emissions in China and Europe, respectively. In China, baseline GHG emissions of
livestock production are projected to increase significantly, while these of the EU-15 dairy
production are predicted to decrease by 2020. It was found that enteric fermentation is the
largest GHG emission source from dairy production and should be focus of mitigation
policies. Both case studies showed mitigation options that offer abatement potential at high
CE. Priorities should be given to biomass gasification, breeding techniques and feed
supplements as tea saponins and probiotics for the Chinese livestock sector, and to animal
selection, reduced tillage and dietary probiotics for the EU-15 dairy sector. The scenario
analysis reveals that mid-term projections for the Chinese livestock sector are varying
strongly, and utilising key variables from different projections has a significant impact on
MAC results which changes the ranking of the mitigation options. The MC simulation shows
the contribution of some model inputs to the uncertainty of abatement at negative cost and a
high model output uncertainty regarding measure’s CE for most mitigation options.
However, the ranking of the mitigation options remains stable. The range of MAC estimates
for 8 mitigation options in the agricultural sector is high and variables like ‘study quality’ or
‘study location’ do not change this. The KDE was further used to rank the mitigations
options based on their probability of being reported as cost-negative and shows that
measures affecting soil N2O and carbon sequestration are reported to be more cost-efficient
as compared to measures focusing on manure management. Based on these finding, the
impact of study designs on MAC estimates and lack of communication uncertainty in MACC
literature are discussed.
Uncertainties that are underpinning MACC results can have significant impacts on CE and
abatement potentials. To increase utilisation of MACCs by knowledge users, MACC
research must prioritise assessment, quantification and report of uncertainties, compare
results within the scientific literature and publish data and assumption of the MACC
transparently.