Marginal Abatement Cost Curve Analysis

Marginal Abatement Cost Curves (MACC) are a commonly used tool in evaluating emissions reduction technologies and a most efficient communication instrument for discussions of the abatement policies.

MACC charts are designed to be a “brief” for decision makers: they compare technologies to be considered for implementation in a simple but informative way that’s easy to comprehend quickly. MACCs are charts showing a set of technologies that would reduce emissions from economic activities, each characterized by the abatement it is expected to deliver within a particular time period (or a specific year) in the future and the marginal net cost per unit of expected abatement.

The technologies can be presented one by one or at various levels of aggregation, including by blocks of technologies within a sector, by economic sector, or even by groups of sectors.

The level of abatement, Mt CO2e, equals the difference in emissions the new technology produces compared to the technology it replaces (the abatement potential).

The cost is calculated as net of benefits and marginal over the cost of the technology being replaced.

Also, it is a unit cost calculated per unit of abatement, Euro/tCO2e which is expressed in present value terms.

The two characteristics of the MACC technologies are estimated using modeling; prior to modeling, a list of technologies should be created and the baseline defined, since both costs and abatement are calculated marginally to the baseline.

The baseline can be built differently depending on the modeling used. Within a sector-wide bottom-up or hybrid (combined bottom-up and top-down) approach, the baseline is a combination of emissions from all economic activities in the sector.

Within a technology-specific approach, a list of abatement technologies for the MACC is created first, then the baseline technology is determined for each of them.

Dissemination Note Series

Romania: Toward a Low Carbon and Climate Resilient Economy

Marginal Abatement Cost Curve Analysis

What is a Marginal Abatement Cost Curve?

Mitigation actions across the five sectors included in Romania’s MACC—power supply, energy efficiency, transport,

agriculture and forestry—will reduce emissions in the country by 37.8 Mt CO2e by the year 2050, the equivalent of a 23

percent decrease from the level projected in for the 2050 Baseline.

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Three basic modeling approaches are used to constructing MAC curves: a bottom-up individual assessment of technologies/abatement measures, a bottom-up system modeling approach, and macro-economic modeling.

In the individual technology approach, abatement costs are defined at a technology level, commonly using cost-benefit models and often involving expert opinions. In system approaches, various bottom-up (e.g., MARKAL and TREMOVE) and top-down (CGE) system models have been used to generate MAC curves in order to include interactions among technologies and policies.

MACCs can also be derived using CGE models. In a CGE model, emissions are usually modeled by using fuel as an input, using fuel emission coefficients and introducing constraints on emissions.

Each modeling type has its own benefits and deficiencies.

The MACC analysis in the Romania Green Growth study presents a cross-sectoral outlook of the benefits and costs of the green technologies/abatement measures recommended in the sectoral modeling and analysis for the time period 2015-2050.

The timeframe is driven by Romania’s EU commitments: the EU 2030 Framework for Climate and Energy and the EU Roadmap 2050. MACC is connected to the sector modeling through technology/green measure selection and through sharing the input data. The selection of sectors was based on their importance for mitigation and/or adaptation, taking availability of data and models into account. Also, only sectors with mitigation (as opposed to adaptation) measures are relevant for the MACC analysis by design.

In addition, the urban sector, which is part of the overall analysis, is absent from MACC to avoid double counting: urban measures are mainly transport and energy interventions at the urban level.

As a result, five sectors—power supply, energy efficiency, transport, forestry and agriculture—were included in Romania’s MACC, and the technologies analyzed and recommended by the sectoral assessments were evaluated.

Romania’s MACC is a combination of sectoral curves, each of which was built using the most appropriate approach for each sector.

The approach used in each sector depends on data availability, accessibility and quality, as well as on the availability of the models. For the electricity supply, the specifications of the curve (potential abatement and cost of the generation technologies per unit of abatement) were calculated using the system model TIMES/MARKAL. For the energy efficiency, a bottom-up detailed engineering model was used.

For forestry, agriculture, and transport, bottom-up Excel-based approaches were used, and the measures evaluated individually.

Methodology

Sector analysis conducted for the Romania Green Growth Assessment resulted in a selection of a list of measures that constitute a green package in each sector. The mitigation measures from this list are evaluated in the MACC analysis.

The analysis outcomes are presented in the cross-sectoral MACC chart (Figure 1). The chart includes the main options for abatement in five sectors:

power supply,energy efficiency,forestry,agriculture, transport.

Green actions across these sectors will reduce emissions in the country by 37.8 Mt CO2e by year 2050, an equivalent of a 23 percent decrease in emissions from the projected 2050 Baseline level. The largest abatement share—45 percent of the total—is projected for supplying electricity.

Energy efficiency measures will provide a third of the overall abatement, agriculture and transport close to one-tenth, and forestry five percent. The net marginal cost (present value) ranges from the negative €-178 per ton CO2e abated in energy demand, to €16/tCO2e in energy supply, to €-0.1/tCO2 in forestry, to €12/tCO2e in agriculture, and to €154/tCO2e in transport.

A review by sector shows that energy efficiency measures are most beneficial —they have high abatement potential and mostly negative cost, while electricity supply interventions produce most of the abatement. Agriculture and forestry measures are cost efficient. In transport, attacking emissions and generating local co-benefits justifies the high cost of the interventions and motivates support for improved transport policies.

Electricity supply measures deliver the highest abatement, with the cost varying from the low to mid-range level. Energy efficiency interventions have a negative cost.Agriculture measures are relatively cost efficient, they also promise to provide mid-range abatement (per measure).Forestry measures are very cheap, and deliver mid-level abatement (per measure). The transport measures have very high costs and, at the same time, a very limited abatement potential per measure, however, apart from abatement, they produce local co-benefits, such as reduced pollution, lowered traffic, controlled noise, a reduced number of accidents, and improved quality of life.

Findings

Global and local data sources were use in the MACC analysis.

IPCC recommends using National Communications data for the MACCs. However, this source lacks the required level of details: it does not have interrelated abatement and cost data for the selected measures. Other sources were used, both local and global. In both agriculture and forestry, the calculations were done based on detailed sector data provided by Romanian experts specifically for this analysis. In transport, local data are not available for many of the proposed interventions because there is no experience with these measures in the country, and data from the comparator countries were used, adjusted to the country specifics. Energy analysis utilized both global and local data.

Conclusions and Recommendations

The MACC work derives from the analysis and modeling of all the relevant sectors in the Assessment. When the MACC data from all sectors is modeled in one chart, it creates a clear and simple picture that compares green measures by costs and benefits across sectors.

Green actions across the analyzed sectors will reduce emissions in the country by 38 Mt CO2e by 2050, an equivalent of a 23 percent decrease from the level projected for the Baseline in 2050. The largest contribution comes from electricity supply. Energy demand also provides a large share of abatement. The measures in both sectors are cost efficient.

Agriculture and forestry can produce mid-range level of abatement at a low unit cost. While transport measures are expensive, the local co-benefits will be high, justifying transport sector mitigation from economic viewpoint.

Figure 1. Romania Marginal Abatement Curve, cross-sectoral, 2050, Super Green scenario

Note: how to read the MACC. The height of each column shows the average cost of abating one ton of CO2 by 2050. The chart is ordered from left to right from measures with the lowest cost to the ones with the highest cost. The width of each column shows the GHG reduction potential of the measure in year 2050, when all measures are fully implemented.

Source: staff calculations and modeling

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The following measuresare outside of the scaleof this chart due to theirhigh cost per tCO2:Eco driving: €333,Low emission zones: €403,Investment in walking,cycling: €533,Smarter choises: €683

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These co-benefits often outweigh the high cost of the transport measures, justifying the latter from an economic point of view. Importantly, local co-benefits often drive mitigation decisions in transport (e.g., with urban congestion control, the policy approval driver would be not abatement, but urban growth and improved quality of life).

The World Bank’s recent transport climate change strategy advocates for the important role that local social costs of transport have in designing GHG emissions reduction for the sector.

The Romania MACC can increase the quality of decisions regarding prioritizing and scheduling the proposed abatement measures.

It shows that the scheduling of green actions should start with energy- efficiency measures because they have the lowest net cost and quickly bring benefits. Next, the forestry measures need to start early on: they have low annual cost, require no upfront investment, and their benefits, while occurring with a time lag, accumulate with time.

Measures in energy supply, vice versa, require large up-front investments, with benefits delivered years into the future, and the implementation requiring complicated and politically charged decisions; and MACC provides only one element of a complicated picture needed to make power supply decisions. In transport, the proposed measures should first be implemented where and when they can bring important social co-benefits including reduced pollution, decreased traffic congestion and accidents, and improved quality of life.

For more information and the publications of the OPERA-CLIMA Program, please visit its webpage at:

http://opera-clima.ro/en/

Romania:Climate Change and Low Carbon Green Growth Program OPERA-CLIMA

Project co-financed by the European Regional Development Fund through OPTA 2007-2013