Summary: As the seventh largest emitter of greenhouse gas emissions—primarily from agriculture (32%), land-use change and deforestation (28%) and fossil fuel consumption (27.7%)—Brazil plays a key role in global climate negotiations. In its Nationally Determined Contribution (NDC) to the Paris Agreement on climate change, the country has pledged to reduce its emissions by 37% in 2025 and 43% in 2030 (relative to 2005 levels). To meet these targets, the Brazilian NDC highlighted its intentions to decrease deforestation, reforest degraded land areas, expand the use of renewable energy sources, increase energy efficiency and expand the area of integrated cropland-livestock-forestry systems.

Using the MIT EPPA model, this study evaluates the costs associated with these and alternative policy instruments by 2030, as well as policy options to further reduce emissions after 2030.

The study projects that the cost of the Brazilian NDC will be just 0.7% of GDP in 2030. Further efforts to reduce carbon emissions beyond 2030 would require policy changes, since all potential emissions reductions from deforestation would be completed, and the capacity to expand renewable energy sources would be limited. Given these constraints, the study finds that an economy-wide carbon pricing system would help substantially to avoid higher compliance costs.

Large-scale economy-wide equilibrium models are widely used for assessing energy or climate policies. As different models often produce diversified outcomes for similar policies, researchers have been trying to understand reasons behind this observation, including cost assumptions for mitigation options, model structure, policy design, and timing. In this study, we focus on analyzing how updating the input-output database of a CGE model could inadvertently change the model output, which has not been carefully examined but could also be an important source that accounts for variations in simulation results of distinct models.

To answer the research question, we provide an analytical framework that elucidates how using a database with a higher energy price raises the CO₂ mitigation cost when the substitution between inputs is relatively limited in the short-run, or when the price hike is considered as temporary. We also provide a numerical example for the analysis, and propose an adjustment that could, under the same percentage reduction in emissions, address the concerns of using the input-output data with prices for fossil fuels and their consumption levels deviating from a more sustainable state.

The latest round of United Nations climate talks in Poland in December 2019 sought to get the world on track to meet the Paris Agreement’s long-term goal of keeping global warming well below two degrees Celsius (2ºC). Toward that end, negotiators from the Agreement’s nearly 200 signatory nations were asked to report on their country or region’s progress toward fulfilling its Paris pledge, or Nationally Determined Contributions (NDC). But just how accurate were those progress reports? That depends on the integrity of the underlying greenhouse gas emissions data that each country used to assess its performance toward meeting the emissions reduction targets spelled out in its NDC. The measurement, reporting and verification (MRV) of a country’s overall emissions and emissions reductions involves culling and validating emissions data from multiple sources, including firms—industrial, nonprofit and government entities—in different economic sectors. Building reliable firm-based systems for emissions MRV is no easy task, especially in developing countries where misreporting of environmental data can be significant, but a new MIT-led study in Nature Climate Change identifies challenges and opportunities to achieve that goal.

Co-authored by researchers at MIT, Tsinghua University and Wuhan University, the study focuses on China, the world’s largest carbon dioxide (CO₂) emitter. China’s climate-change mitigation strategy centers on a national emissions trading system (ETS) whose success depends upon accurate emissions reporting at the firm level. Using data obtained from two of China’s pilot regional ETS programs, one in Beijing, a highly developed major city, the other in Hubei, a less developed province, the researchers compared firms’ self-reported CO₂ emissions numbers with those verified by independent third parties. The average discrepancy in these numbers decreased significantly in Beijing, going from 17 percent in 2012 to 4 percent in 2014 and 2015 for approximately 400 firms. In Hubei, which launched its system one year later, the number of discrepancies started lower and showed a statistically-insignificant decrease (from 6% in 2014 to 5% in 2015).

The study emphasized that building effective MRV systems at firms in China and other developing countries takes time, resources and attention to detail. Among its recommendations to increase reporting accuracy and prevent manipulation or collusion is to provide external funding from governments or multilateral entities, at least in early years, to pay the independent verifiers. If firms pay for verification, government back-checks are essential to ensure reporting integrity. The study also maintains that strong law enforcement will be necessary to punish any detected incidents of collusion between verifiers and firms.