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 partially driven by economical or environmental positions. Finally, several case studies and discussions are presented showing the advantages of the exposed methods.
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Notes
- 1.
Expressed as equivalent CO2 in tonnes that a measure m could potentially abate.
Abbreviations
- Acronyms :
-
Meaning
- ΔB m :
-
Economic benefit generated by the energy savings for a measure m
- ΔC m :
-
Associated net present value associated to a measure m
- ΔE m :
-
GHG abatement potential associated to a measure m
- \(BOM^{\alpha } \left( {\mu_{1} ,\mu_{2} } \right)\left( m \right)\) :
-
Balanced ordering method for methods \(\mu_{1}\) and \(\mu_{2}\), and a balance \(\alpha\)
- Cost m :
-
Total cost of the measure m (Cost m = ΔC m —ΔB m )
- ENV :
-
Environmentalist benchmark
- GHG :
-
Greenhouse gases
- GM(ε) :
-
Gain maximizing method being ε a very small value
- GM(1) :
-
Gain maximizing method being ε = 1
- GM m :
-
Gain value for a measure m
- GRE :
-
Greedy benchmark
- EMAC :
-
Extended MACC method
- EMAC m :
-
Extended MACM value for a measure m
- MACC :
-
Marginal abatement costs curve
- MAC m :
-
Marginal cost of abating a tonne of CO2 for a measure m
- m :
-
Measure
- NPV :
-
Net present value
- sign(x) :
-
Sign of x
- \(\tau_{MAC}\) :
-
Set of ordered measures applying method MACC
- \(\tau_{Ward}\) :
-
Set of ordered measures applying method Ward
- \(\tau_{Taylor}\) :
-
Set of ordered measures applying method Taylor
- \(\tau_{GM(\epsilon)}\) :
-
Set of ordered measures applying method GM(ε) being ε a very small value
- \(\tau_{GM(1)}\) :
-
Set of ordered measures applying method GM(ε) being ε = 1
- \(\tau_{EMAC}\) :
-
Set of ordered measures applying method. EMAC
- \(K\left( {\tau_{{\mu_{1} }} ,\tau_{{\mu_{2} }} } \right)\) :
-
Kendall tau distance between methods \(\mu_{1}\) and \(\mu_{2}\)
References
Ackerman, F., & Bueno, R. (2011). Use of McKinsey abatement cost curves for climate economics modelling. Somerville, MA: Stockholm Environment Institute.
Balsalobre Lorente, D., Álvarez-Herránz, A., & Baños Torres, J. (2016). La innovación y la sustitución energética como medidas de corrección medioambiental en países de la OCDE. Estudios de Economía Aplicada, 34(1), 1–26.
Behrentz, E. (2014). Productos analíticos para apoyar la toma de decisiones sobre acciones de mitigación a nivel sectorial: Curvas de abatimiento para Colombia, Bogotá. Colombia: Universidad de los Andes.
Bockel, L., Sutter, P., Touchemoulin, O., & Jönsson, M. (2012). Using marginal abatement cost curves to realize the economic appraisal of climate smart agriculture policy options. Methodology, 3(1), s.l. Food and Agriculture Organization of the United nations (FAO).
Cantos, J. M., & Balsalobre Lorente, D. (2011). Las energías renovables en la Curva de Kuznets Ambiental: Una aplicación para España. Estudios de Economia Aplicada, 29(2), 1–32.
Cantos, J. M., & Balsalobre Lorente, D. (2013). Incidencia del gasto público en I + D + i energético sobre la corrección medioambiental en España*. Estucios de Economia Aplicada, 31(1), 1–34.
Contreras, R. F. (2016). Analysis and comparison of energy saving measures through marginal abatement cost curves. En: Project Management and Engineering Research. s.l. Springer International Publishing, pp. 203–214.
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. Chichester, UK: Wiley.
Goldberg, D. E., & Holland, J. H. (1988). Genetic algorithms and machine learning. Machine Learning, 3(3), 95–99.
Huang, S. K., Kuo, L., & Chou, K. L. (2016). The applicability of marginal abatement cost approach: A comprehensive review. Journal of Cleaner Production, Volumen, 127, 59–71.
Jackson, T. (1991). Least-cost greenhouse planning supply curves for global warming abatement. Energy Policy, 19(1), 35–46.
Kendall, M. G. (1948). Rank correlation methods. London: Charles Griffen & Company.
Kesicki, F. (2012). Intertemporal issues and marginal abatement costs in the UK transport sector. Transportation Research Part D: Transport and environment, 17(5), 418–426.
Kesicki, F. (2013). What are the key drivers of MAC curves? A partial-equilibrium modelling approach for the UK. Energy Policy, 58, 142–151.
Kesicki, F., & Ekins, P. (2012). Marginal abatement cost curves: A call for caution. Climate Policy, 12(2), 219–236.
Kesicki, F., & Strachan, N. (2011). Marginal abatement cost (MAC) curves: Confronting theory and practice. Environmental Science & Policy, 14(8), 1195–1204.
Kok, R., & Annema, J. A. (2010). The curious case of selecting and ranking GHG mitigation measures in transport. In ETC 2010, European Transport Conference. Glasgow, UK, Association for European Transport (AET).
Levihn, F. (2016). On the problem of optimizing through least cost per unit, when costs are negative: Implications for cost curves and the definition of economic efficiency. Energy, 114, 1155–1163.
Moran, D., et al. (2008). UK marginal abatement cost curves for the agriculture and land use, land-use change and forestry sectors out to 2022, with qualitative analysis of options to 2050, s.l. s.n.
Moran, D., et al. (2010). Developing carbon budgets for UK agriculture, land-use, land-use change and forestry out to 2022. Climatic Change, 105(3–4), 529–553.
Morthorst, P. E. (1994). Constructing CO2 reduction cost curves; the case of Denmark. Energy Policy, 22(11), 964–970.
Paulson, W. E. (1948). Characteristics of the marginal cost curve. Journal of Farm Economics, 30(3), 467–499.
Ponz-Tienda, J. L., Prada-Hernández, A. V., & Salcedo-Bernal, A. (2016). The problem of ranking CO2 abatement measures: A methodological proposal. Sustainable Cities and Society, 26, 306–317.
Prada-Hernández, A., Vargas, H., Ozuna, A. & Ponz-Tienda, J. L. (2015). Marginal abatement costs curve (MACC) for carbon emissions reduction from Buildings: An implementation for office buildings in Colombia. International Journal of Civil and Structural Engineering–IJCSE, 2(1).
Taylor, S. (2012). The ranking of negative-cost emissions reduction measures. Energy Policy, 48, 430–438.
Van Odijk, S., et al. (2012). Utilizing marginal abatement cost curves (MAC curves) to strategically plan CO2 reduction possibilities for the water sector: The case of watercycle organisation Waternet. s.l., s.n., pp. 13–18.
Vogt-Schilb, A., & Hallegatte, S. (2014). Marginal Abatement cost curves and the optimal timing of mitigation measures. Energy Policy, 66, 645–653.
Wallis, M. (1992a). Greenhouse ranking of gas-fuelling. Energy Policy, 20(2), 174–176.
Wallis, M. K. (1992b). Forum ranking of greenhouse gas abatement measures. Energy Policy, 20(12), 1130–1133.
Ward, D. J. (2014). The failure of marginal abatement cost curves in optimising a transition to a low carbon energy supply. Energy Policy, 73, 820–822.
Acknowledgements
The authors would like to thank the research group of Construction Engineering and Management (IN2geco) of Universidad de Los Andes.
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Ponz-Tienda, J.L., Prada-Hernández, A.V., Salcedo-Bernal, A., Balsalobre-Lorente, D. (2017). Marginal Abatement Cost Curves (MACC): Unsolved Issues, Anomalies, and Alternative Proposals. In: Álvarez Fernández, R., Zubelzu, S., Martínez, R. (eds) Carbon Footprint and the Industrial Life Cycle. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-54984-2_12
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