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Benavides, C., Diaz, M., O' Ryan, R., Gwinner, S., & Sierra, E. (2021). Methodology to analyse the impact of an emissions trading system in Chile. Clim. Policy, 21(8), 1099–1110.
Abstract: In the context of updating the 2015 Nationally Determined Contribution (NDC), the government of Chile has updated its estimates of compliance costs for a series of mitigation actions with an emphasis on the energy sector as the main source of its greenhouse gas emissions. Using the information developed in this process, we assess the impact on compliance costs of increasing the flexibility for sources by introducing different emissions trading schemes. For this we develop a detailed optimization model that represents the operational and investment decisions that could be taken by the energy generation, industrial and mining sectors if an Emissions Trading System (ETS) was implemented. An ETS with two cap and trade options is analysed together with an offset mechanism for sources not included in the ETS. Also, two policy goals are considered: a stringent 76% sectoral reduction goal in 2050 similar to Chile's current strict NDC, and a more lax 46% goal similar to Chile's initial 2015 NDC proposal. The results show that (i) cost reductions from increased flexibility for Chile's current strict NDC are significant, and that offsets can play an important role; (ii) the stringency of the reduction goal affects the magnitude of the cost savings related to flexibility and, surprisingly, total abatement costs are negative (i.e. there are benefits) for the 46% reduction goal. In this latter case, the most significant cost reductions result from compelling firms to comply with their allowances in each sector, not increased flexibility. These results highlight the policy relevance of case by case analysis using a modelling approach similar to the one we develop here. Key policy insights ETS implementation can help Chile meet its mitigation commitment for 2050. The compliance costs can vary significantly depending on the flexibility implemented in the emissions trading schemes. Optimization models can help decision-makers define the attributes of an ETS, such as the sectors that should participate, the cap, and the percentage of offsets. The proposed methodology also highlights and quantifies the offsets that can be acquired from sectors that are not part of an ETS, such as forestry, agriculture, and the waste sector. The possibility to acquire of offsets could reduce significantly the cost for industries that participate of an ETS.
O' Ryan, R., Benavides, C., Diaz, M., San Martin, J. P., & Mallea, J. (2019). Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile. Clim. Policy, 19(3), 299–314.
Abstract: In this paper, initial steps are presented toward characterizing, quantifying, incorporating and communicating uncertainty applying a probabilistic analysis to countrywide emission baseline forecasts, using Chile as a case study. Most GHG emission forecasts used by regulators are based on bottom-up deterministic approaches. Uncertainty is usually incorporated through sensitivity analysis and/or use of different scenarios. However, much of the available information on uncertainty is not systematically included. The deterministic approach also gives a wide range of variation in values without a clear sense of probability of the expected emissions, making it difficult to establish both the mitigation contributions and the subsequent policy prescriptions for the future. To improve on this practice, we have systematically included uncertainty into a bottom-up approach, incorporating it in key variables that affect expected GHG emissions, using readily available information, and establishing expected baseline emissions trajectories rather than scenarios. The resulting emission trajectories make explicit the probability percentiles, reflecting uncertainties as well as possible using readily available information in a manner that is relevant to the decision making process. Additionally, for the case of Chile, contradictory deterministic results are eliminated, and it is shown that, whereas under a deterministic approach Chile's mitigation ambition does not seem high, the probabilistic approach suggests this is not necessarily the case. It is concluded that using a probabilistic approach allows a better characterization of uncertainty using existing data and modelling capacities that are usually weak in developing country contexts. Key policy insights Probabilistic analysis allows incorporating uncertainty systematically into key variables for baseline greenhouse gas emission scenario projections. By using probabilistic analysis, the policymaker can be better informed as to future emission trajectories. Probabilistic analysis can be done with readily available data and expertise, using the usual models preferred by policymakers, even in developing country contexts.