Reliable information on future greenhouse gas emissions is crucial for developing countries shaping and implementing their third nationally determined contributions (NDC 3.0). The Greenhouse Gas Abatement Cost Model (GACMO) offers an easy solution for systematically assessing mitigation actions, supporting decision-making based on robust data.

GACMO is a bottom-up modeling tool for greenhouse gas emission projections based on methodologies established by the Intergovernmental Panel on Climate Change and the Clean Development Mechanism. It calculates projected emissions, greenhouse gas reductions, and associated costs for each mitigation option, allowing users to evaluate and compare the cost-effectiveness and impact of various measures. 

GACMO can be applied both ex-ante, to inform the planning and prioritization of mitigation actions in a country’s NDC and ex-post, to monitor and track NDC implementation progress. In addition, the model is capable of generating Marginal Abatement Cost (MAC) curves, which can be used by countries to classify and rank mitigation projects according to their relative cost and abatement potential.

GACMO is a flexible tool that allows the scale of mitigation options to be adjusted up or down, depending on national circumstances or scenario requirements. The data requirements to adjust the tool to a country context are relatively easy to meet, which makes GACMO very attractive for countries with limited data availability.  The model includes a set of pre-loaded default values, so users don’t need to update them unless they have more accurate data for precise estimates. When country-specific data becomes available, it can be entered into the platform, and the values will automatically update. 

Since the creation of the tool by UNEP Copenhagen Climate Centre 20 years ago, countries have used GACMO to analyze emission trajectories, design and monitor NDCs, assess and compare the cost of climate policies and measures. Drawing on lessons from real experiences and strengthened by regular updates, GACMO stands as a valuable, versatile tool, empowering data-based decision-making for more effective NDC design and implementation.

Scenario analysis with GACMO: Namibia’s clean energy future

Using GACMO, policymakers can compare scenarios based on different policies, sets of measures, or economic conditions to identify the most effective mitigation strategies, helping set and achieve NDC targets. For example, Namibia conducted a comparative scenario analysis of its greenhouse gas emissions trajectories through 2050, assessing three pathways of different grades of ambition: a Business-as-Usual (BAU) scenario, a scenario with moderate mitigation interventions, and an ambitious net-zero pathway. 

GACMO enabled a quantification of the impacts and benefits of different policy options. Under BAU, emissions were estimated to rise steadily to about 5,200 kt CO₂e by 2050, driven by growing fossil fuel use in transport, industry, and electricity generation, and locking Namibia into fossil fuel dependence. The scenario with moderate mitigation measures, which included efficient lighting, fuel-efficient vehicles, and renewables expansion to 30% by 2030, showed emissions stabilizing at around 3,500 ktCO₂e by 2050. Under the most ambitious scenario, Namibia could reduce emissions by 87% by 2050 (to 680 ktCO₂e) through widespread solar and wind deployment, electrification of transport and industry, and green hydrogen development, significantly contributing to the country’s economy-wide greenhouse gas reduction targets, as reflected in the NDC. 

In this sense, the GACMO analysis identified a feasible path for a progressively ambitious energy sector transformation in Namibia. To support transition and to achieve such an ambitious target, Namibia would need to support the measures included in GACMO modeling by a targeted policy framework and strategic investment strategy, guiding the country toward an energy future that balances economic growth, energy security, and climate responsibility.

Energy Sector Greenhouse Gas Emissions Projections by Scenario (2020-2050)

Identifying the most efficient and cost-effective mitigation options in Samoa

Samoa used GACMO to analyze and project its greenhouse gas emissions through 2050, assessing both conditional and unconditional mitigation scenarios, in line with the country’s Second NDC Implementation Plan and Roadmap. Using 2020 as the baseline year, GACMO projected a 137% increase in emissions under a BAU scenario by 2030, compared to a 50.6% reduction from BAU projections with the implementation of identified mitigation measures. 

The waste sector emerged as the largest source of mitigation potential, through biogas production, landfill gas capture, composting, and recycling. The agriculture sector could also significantly reduce emissions primarily via nitrification inhibitors and biogas systems at pig farms, while forestry and land use interventions, such as reforestation, avoided deforestation, and agroforestry, could offer sustained long-term carbon sequestration benefits. Energy efficiency in residential and commercial buildings and transport electrification could contribute to additional, growing emission reductions over time.

GACMO also produced MAC curves, including country-specific data and comparing cost-effective measures such as LED lighting, solar streetlights, solar water heaters, and biogas systems, alongside more costly options like electric cars and ferries. Samoa plans to update the GACMO model with validated data twice a year to ensure projections and mitigation impact assessments remain up-to-date. Factoring in both the potential impact and the associated costs, Samoa can therefore prioritize the most affordable actions that deliver the greatest reductions in emissions.

Large-scale interventions in the waste, agriculture, and land-use sectors fall under the conditional scenario and are well-suited for international climate finance, as they achieve significant reductions at relatively low cost. In contrast, residential energy efficiency measures, which form part of the unconditional scenario funded through domestic resources, are smaller in scale but efficient and affordable. In this way, the GACMO-enabled breakdown supports a strategic approach to funding mitigation measures in Samoa.  

These examples demonstrate how GACMO empowers developing countries to apply a data-based approach to their climate action planning, starting from the effectiveness of their NDCs. From mitigation scenarios to cost comparisons, GACMO supports countries to set ambitious yet realistic NDC targets, prioritize impactful measures, and strengthen their climate action.