Marginal Abatement Cost Curves (MACC): Unsolved Issues, Anomalies, and Alternative Proposals
Jose Luis Ponz-Tienda, Andrea Victoria Prada-Hernandez, Alejandro Salcedo-Bernal and Daniel Balsalobre-Lorente
Abstract Policy makers proposed the MACC as an instrument to rank possible mitigation measures available in a market. This tool orders measures according to their cost-efficiency, taking into account only two variables: costs and emissions reductions. Although this tool has been used in relevant settings like the first treaty of the United Nations Framework Convention on Climate Change (UNFCCC), it has shown mathematical failures that might produce unreliable rankings. This chapter presents existing alternatives to the use of traditional MACC for ranking GHG abatement measures: (1) Taylor’s method by the application of the dominance concept. (2) Ward’s method directly related to the net benefit of each measure. (3) The GM method, which supports an environmentalist attitude and performs a direct comparison of measures with negative and positive costs. (4) An extension of traditional MACC (EMAC method), that considers the economically driven point of view of the decision maker, weighting the negative cost options according to its economic savings over its reduction potential. (5) And the BOM method, consisting of a linear-weighted combination of two discretional seed methods, allowing decision makers to take into account the goodness of multiple methods in order to create new rankings adjustable to a specific GHG policy, whether it is fully or
J.L. Ponz-Tienda (H)
Civil and Environmental Department, Universidad de Los Andes,
Bogota, Colombia
e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it
A.V. Prada-Hernandez
School of Public Policy, University of Maryland, College Park, MD, USA e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it
A. Salcedo-Bernal
Department of Systems and Computing Engineering, Universidad de Los Andes, Bogota, Colombia
e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it D. Balsalobre-Lorente
Department of Political Economy and Public Finance Economic and Business Statistics and Economic Policy, University of Castilla-La Mancha,
Ciudad Real, Spain
e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it © Springer International Publishing AG 2017
R. Alvarez Fernandez et al. (eds.), Carbon Footprint and the Industrial Life Cycle, Green Energy and Technology, DOI 10.1007/978-3-319-54984-2_12
partially driven by economical or environmental positions. Finally, several case studies and discussions are presented showing the advantages of the exposed methods.
Notations
The following concepts, symbols and acronyms are used in this article
Acronyms Meaning
ABm Economic benefit generated by the energy savings for a
measure m
ACm Associated net present value associated to a measure m
AEm GHG abatement potential associated to a measure m
BOMa(pJ, p2)(m) Balanced ordering method for methods pJ and p2, and a balance a
Costm Total cost of the measure m (Costm = ACm—ABm)
ENV Environmentalist benchmark
GHG Greenhouse gases
GM(e) Gain maximizing method being e a very small value
GM(1) Gain maximizing method being e = J
GMm Gain value for a measure m
GRE Greedy benchmark
EMAC Extended MACC method
EMACm Extended MACM value for a measure m
MACC Marginal abatement costs curve
MACm Marginal cost of abating a tonne of CO2 for a measure m
m Measure
NPV Net present value
sign(x) Sign of x
sMAC Set of ordered measures applying method MACC
sWard Set of ordered measures applying method Ward
sTayior Set of ordered measures applying method Taylor
TGM(e) Set of ordered measures applying method GM(e) being e a very
small value
sgM(J) Set of ordered measures applying method GM(e) being e = J
sEMAC Set of ordered measures applying method. EMAC
K (Spi, xl2) Kendall tau distance between methods pJ and p2
