scholarly journals SUSTAINABLE COOPERATION IN GLOBAL CLIMATE POLICY: SPECIFIC FORMULAS AND EMISSION TARGETS

2014 ◽  
Vol 05 (03) ◽  
pp. 1450006
Author(s):  
VALENTINA BOSETTI ◽  
JEFFREY FRANKEL
Keyword(s):  
Developing Countries ◽  
Integrated Assessment ◽  
State Of The Art ◽  
Global Climate ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Copenhagen Accord ◽  
Business As Usual ◽  
The U.S ◽  
Numerical Formula

We propose a framework that, building on the pledges made by governments after the Copenhagen Accord of 2009, could be used to assign allocations of emissions of greenhouse gases (GHGs), across all countries, one budget period at a time, as envisioned at the 2011 negotiations in Durban. Under this two-part plan: (i) China, India, and other developing countries accept targets at Business as Usual (BAU) in the coming budget period, the same period in which the U.S. first agrees to cuts below BAU; and (ii) all countries are asked in the future to make further cuts in accordance with a common numerical formula that each country is likely to view as fair. We use a state of the art integrated assessment model to project economic and environmental effects of the computed emission targets.

scholarly journals Addressing partial identification in climate modeling and policy analysis

2021 ◽  
Vol 118 (15) ◽  
pp. e2022886118
Author(s):  
Charles F. Manski ◽  
Alan H. Sanstad ◽  
Stephen J. DeCanio
Keyword(s):  
Integrated Assessment ◽  
Climate Model ◽  
Global Climate ◽  
Partial Identification ◽  
Integrated Assessment Model ◽  
Greenhouse Gas Mitigation ◽  
Assessment Model ◽  
Weighted Averaging ◽  
Structural Uncertainty ◽  
Data Limitations

Numerical simulations of the global climate system provide inputs to integrated assessment modeling for estimating the impacts of greenhouse gas mitigation and other policies to address global climate change. While essential tools for this purpose, computational climate models are subject to considerable uncertainty, including intermodel “structural” uncertainty. Structural uncertainty analysis has emphasized simple or weighted averaging of the outputs of multimodel ensembles, sometimes with subjective Bayesian assignment of probabilities across models. However, choosing appropriate weights is problematic. To use climate simulations in integrated assessment, we propose, instead, framing climate model uncertainty as a problem of partial identification, or “deep” uncertainty. This terminology refers to situations in which the underlying mechanisms, dynamics, or laws governing a system are not completely known and cannot be credibly modeled definitively even in the absence of data limitations in a statistical sense. We propose the min−max regret (MMR) decision criterion to account for deep climate uncertainty in integrated assessment without weighting climate model forecasts. We develop a theoretical framework for cost−benefit analysis of climate policy based on MMR, and apply it computationally with a simple integrated assessment model. We suggest avenues for further research.

scholarly journals Energy and climate change in China

2012 ◽  
Vol 17 (6) ◽  
pp. 689-713 ◽  
Author(s):  
Carlo Carraro ◽  
Emanuele Massetti
Keyword(s):  
Climate Change ◽  
Integrated Assessment ◽  
Carbon Tax ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Discounted Cost ◽  
Greenhouse Gases Emissions ◽  
Emissions Scenarios ◽  
Business As Usual ◽  
Different Levels

AbstractThis paper examines future energy and emissions scenarios in China generated by the Integrated Assessment Model WITCH. A Business-as-Usual scenario is compared with five scenarios in which greenhouse gases emissions are taxed, at different levels. The elasticity of China's emissions is estimated by pooling observations from all scenarios and comparing them with the elasticity of emissions in OECD countries. China has a higher elasticity than the OECD for a carbon tax lower than US$50 per ton of CO2-eq. For higher taxes, emissions in OECD economies are more elastic than in China. Our best guess indicates that China would need to introduce a tax equal to about US$750 per ton of CO2-eq in 2050 to achieve the Major Economies Forum goal set for mid-century. In our preferred estimates, the discounted cost of following the 2°C trajectory is equal to 5.4 per cent and to 2.7 per cent of GDP in China and the OECD, respectively.

scholarly journals The role of biomaterials for the energy transition from the lens of a national integrated assessment model

2021 ◽  
Vol 167 (3-4) ◽  
Author(s):  
Camilla C. N. de Oliveira ◽  
Gerd Angelkorte ◽  
Pedro R. R. Rochedo ◽  
Alexandre Szklo
Keyword(s):  
Integrated Assessment ◽  
Energy Transition ◽  
Integrated Assessment Model ◽  
Assessment Model

scholarly journals Evaluation of Integrated Assessment Model hindcast experiments: A case study of the GCAM 3.0 land use module

2017 ◽  
Author(s):  
Abigail C. Snyder ◽  
Robert P. Link ◽  
Katherine V. Calvin
Keyword(s):  
Integrated Assessment ◽  
Structural Changes ◽  
Spatial Scales ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Land Allocation ◽  
Time Period ◽  
Skill Scores ◽  
Performance Benchmarks

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data is available) are rarely undertaken in the Integrated Assessment Model (IAM) community. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation based measures that can be applied at different spatial scales (regional versus global) to make evaluating the large number of variable-region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observational dataset, that allow a model to be evaluated in absolute terms rather than relative to the performance of other models at similar tasks. This is key in the integrated assessment community, where there often are not multiple models conducting hindcast experiments to allow for model intercomparison. The performance benchmarks serve a second purpose, providing information about the reasons a model may perform poorly on a given measure and therefore identifying opportunities for improvement. As a case study, the measures are applied to the results of a past hindcast experiment focusing on land allocation in the Global Change Assessment Model (GCAM) version 3.0. We find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs, such as GCAM, that require global supply to equal global demand at each time period. Additionally, the deviation measures examined in this work successfully identity parametric and structural changes that may improve land allocation decisions in GCAM. Future work will involve implementing the suggested improvements to the GCAM land allocation system identified by the measures in this work, using the measures to quantify performance improvement due to these changes, and, ideally, applying these measures to other sectors of GCAM and other land allocation models.

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