No abstract

After COP 21, with the adoption of the Paris Agreement in December 2015, the outlook for carbon pricing policies has been widened. While the agreement does not directly establish a global carbon pricing, the provisions accounted for in Article 6 have the potential to increase international cooperation in favor of greenhouse gas (GHG) mitigation through market mechanisms. The Brazilian Nationally Determined Contribution (NDC) considers the use of such mechanisms, though the configuration of the Brazilian climate policy does not specify the economic instruments for carbon pricing. When examining the recent evolution of GHG emissions in Brazil, the already achieved reduction in deforestation sheds light on the need to address GHG mitigation in other sectors, such as industry. Therefore, this paper analyzes the impacts of carbon pricing on the Brazilian industry in terms of sectorial value added (VA), emissions intensity, international trade exposure, and the risk of carbon leakage. Results indicate that, considering a price of carbon of US$10/tCO 2 , the cost of reducing emissions from 35% to 45% (same range of the Brazilian NDC) could represent an impact of 0.3% to 3.7% on sectorial VA. However, results for emissions intensity and international trade reveal medium to high carbon leakage risks for all analyzed industrial sectors.

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This study investigates the logistics network planning in a major Brazilian petrochemical company, taking into consideration the impact of tax-related costs, in addition to transportation and inventory costs. A Mixed Integer Nonlinear Programming model that considers the most relevant costs involved in the network planning process in Brazil was developed and subsequently applied to a case study of a large Brazilian petrochemical company. Our results support anecdotal reports regarding Brazilian companies intensely using 'product tourism' to take advantage of different interstate tax rates. Product tourism occurs when a logistically unnecessary flow of goods is established to a lower tax jurisdiction (with a corresponding increase in transportation costs) so that the company obtains a reduction in the amount of the taxes due.

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES) -Finance Code 001. We would like to thank CAPES for the financial support and to the producers Alessandra Bellas Romariz de Macedo and Cláudio Massato Matsuoka for the kindness and patience in solving all doubts about the Brazilian small farming. We also thank the Association of Citriculturists and Rural Producers of Tanguá (ACIPTA).

Green fiscal reforms would contribute to climate change mitigation, increase the economic efficiency of national tax systems and provide additional public revenues. Some countries in Latin America have already taken first steps towards green fiscal reforms. This outlook article provides an overview of the major challenges for the successful implementation of such reforms and discusses how they could be overcome.

This study analyzes climate change mitigation policies focused on light-duty electric vehicles (LDEVs) in the transportation sector in Rio de Janeiro state, Brazil, in the 2016–2050 period. We use the Open Source Energy Modeling System (OSeMOSYS) to analyze scenarios that consider greater uptake of LDEVs in different time frames, implementation of a CO2 emission restriction policy, exclusion of fossil fuels from the power mix, and a combination of these policies. We find that carbon pricing, along with higher rates of LDEVs adoption, causes the highest emission reductions (up to 47%), albeit at higher costs. LDEVs become the preferred vehicle technology as soon as they reach cost parity with internal combustion engine vehicles in different scenarios. Greater LDEVs uptake, however, leads to increased electricity consumption (up to 3%), which is provided by fossil fuels when there is no emission restriction policy. If restrictions are placed on the expansion of fossil fuel power plants, fewer LDEVs are adopted (up to less than 26%) because there is not enough electricity to supply the demand. Given the state’s power mix in 2016 (58% provided by fossil fuels), investment in zero-carbon energy is necessary for mitigation policies in the transportation sector to be effective.

This paper proposes a novel approach that makes use of continuous-time Markov chains and regret functions to find an appropriate compromise in the context of multicriteria decision analysis (MCDA). This method was an innovation in the relationship between uncertainty and decision parameters, and it allows for a much more robust sensitivity analysis. The proposed approach avoids the drawbacks of arbitrary user-defined and method-specific parameters by defining transition rates that depend only upon the performances of the alternatives. This results in a flexible and easy-to-use tool that is completely transparent, reproducible, and easy to interpret. Furthermore, because it is based on Markov chains, the model allows for a seamless and innovative treatment of uncertainty. We apply the approach to an oil and gas decommissioning problem, which seeks a responsible manner in which to dismantle and deactivate production facilities. The experiments, which make use of published data on the decommissioning of the field of Brent, account for 12 criteria and illustrate the application of the proposed approach.