Impacts of Sea Level Rise on Economic Growth in Developing Asia

Global sea level rise (SLR) variations have undeniably begun to make an impact on highly vulnerable economies. These impacts of SLR are a key component of the projected economic damage of climate change, an important input to climate change policies and adaptive measures. This paper considers SLR projections and its impact on the economy and includes a consolidation of various related studies. Estimated global gross domestic product (GDP) loss by 2100 ranges from 0.3% to as high as of 9.3% (Hinkel et al. 2014; Pycroft, Abrell, and Ciscar 2015). Climate change impact should be addressed at the global level through a locally focused effort where education and acceptance by all stakeholders are crucial and warranted. Further, this paper tackles several adaptive strategies as a response to SLR which include retreat, accommodation, and protection. The retreat strategy simulates that SLR causes the loss of inundated land and incurs planned relocation (migration) costs above a certain sea level. The accommodation strategy allows usage of vulnerable areas or land and limits damage by floodproofing or raising structures. Finally, the protection strategy projects that land will be protected from SLR damage by sea walls or other barriers of a certain height. On the other hand, Diaz (2016) estimates a median adaptation cost from migration at 16% of GDP under the least-cost strategy by 2050. In general, the education of and the acceptance by the concerned local community will be crucial in the successful implementation of SLR adaptation strategies, notwithstanding parallel mitigation efforts on a global scale

Integrated Assessment of Climate Catastrophes with Endogenous Uncertainty: Does the Risk of Ice Sheet Collapse Justify Precautionary Mitigation?

Greenhouse gas policies confront the trade-off between the costs of reducing emissions and the benefits of avoided climate change. The risk of uncertain and potentially irreversible catastrophes is an important issue related to the latter, and one that has not yet been well incorporated into economic models for climate change policy analysis. This paper demonstrates a multistage stochastic programming framework for catastrophe modeling with endogenous uncertainty, applied to a benchmark integrated assessment model. This study moves beyond recent catastrophe or tipping point studies with arbitrary risk, instead investigating the specific threat of the uncertain collapse of the West Antarctic Ice Sheet (WAIS), characterized in accordance with recent expert elicitations, empirical results, and physical relationships. The stochastic DICE-WAIS model introduced here informs risk management strategies that balance uncertain future climate change impacts with the costs of mitigation investments today. This work finds that accounting for the consequences of the possible WAIS collapse in a stochastic setting with endogenous uncertainty leads to more stringent climate policy recommendations (increasing the CO2 control rate by an additional 4% of global emissions and raising the social cost of carbon by $10), reflecting the need to hedge against uncertainties with downside risk as well as pursue precautionary mitigation

Integrated assessment of climate catastrophes with endogenous uncertainty: Does the risk of ice sheet collapse justify precautionary mitigation?

Greenhouse gas policies confront the trade-off between the costs of reducing emissions and the benefits of avoided climate change. The risk of uncertain and potentially irreversible catastrophes is an important issue related to the latter, and one that has not yet been well incorporated into economic models for climate change policy analysis. This paper demonstrates a multistage stochastic programming framework for catastrophe modeling with endogenous uncertainty, applied to a benchmark integrated assessment model. This study moves beyond recent catastrophe or tipping point studies with arbitrary risk, instead investigating the specific threat of the uncertain collapse of the West Antarctic Ice Sheet (WAIS), characterized in accordance with recent expert elicitations, empirical results, and physical relationships. The stochastic DICE-WAIS model introduced here informs risk management strategies that balance uncertain future climate change impacts with the costs of mitigation investments today. This work finds that accounting for the consequences of the possible WAIS collapse in a stochastic setting with endogenous uncertainty leads to more stringent climate policy recommendations (increasing the CO2 control rate by an additional 4% of global emissions and raising the social cost of carbon by $10), reflecting the need to hedge against uncertainties with downside risk as well as pursue precautionary mitigation

UNDERSTANDING THE SOCIAL COST OF CARBON: A MODEL DIAGNOSTIC AND INTER-COMPARISON STUDY

The social cost of carbon (SCC) is a monetary estimate of global climate change damages to society from an additional unit of carbon dioxide (CO2) emissions. SCCs are used to estimate the benefits of CO2 reductions from policies. However, little is known about the modeling underlying the values or the implied societal risks, making SCC estimates difficult to interpret and assess. This study performs the first in-depth examination of SCC modeling using controlled diagnostic experiments that yield detailed intermediate results, allow for direct comparison of individual components of the models, and facilitate evaluation of the individual model SCCs. Specifically, we analyze DICE, FUND, and PAGE and the multimodel approach used by the US Government. Through our component assessments, we trace SCC differences back to intermediate variables and specific features. We find significant variation in component-level behavior between models driven by model-specific structural and implementation elements, some resulting in artificial differences in results. These elements combine to produce model-specific tendencies in climate and damage responses that contribute to differences observed in SCC outcomes — producing PAGE SCC distributions with longer and fatter right tails and higher averages, followed by DICE with more compact distributions and lower averages, and FUND with distributions that include net benefits and the lowest averages. Overall, our analyses reveal fundamental model behavior relevant to many disciplines of climate research, and identify issues with the models, as well as the overall multimodel approach, that need further consideration. With the growing prominence of SCCs in decision-making, ranging from the local-level to international, improved transparency and technical understanding is essential for informed decisions. </jats:p

The Role of Natural Gas in the EU Decarbonisation Path

Over the last decade decarbonisation has become a key priority for the EU. However, on the contrary of renewable energy or energy efficiency, the role of gas in this process has never been clearly defined. This uncertainty opens a wide debate on the future role of gas in the EU energy system, particularly vis-à-vis the progressively stronger role of renewables in the EU energy mix. This paper tackles this issue with the aim to explore what role gas might play in making the EU decarbonisation path more balanced and secure up to 2030 and beyond

Assessing SDGs: A New Methodology to Measure Sustainability

The FEEM project APPS – Assessment, Projections and Policy of Sustainable Development Goals – focuses on the quantitative assessment of the seventeen Sustainable Development Goals (SDGs), adopted by the United Nations at the end of September 2015. The project consists of two phases. The first, retrospective, computes indicators for all SDGs in 139 countries and then derives a composite multi-dimensional index and a worldwide ranking of current sustainability. This allows informing on strengths and weaknesses of today socio-economic development, as well as environmental criticalities, all around the world. The second phase, prospective, aims at evaluating the future trends of sustainability in the world by 2030. The assessment of the SDGs is carried out by means of an extended version of the recursive-dynamic computable general equilibrium ICES macro-economic model that includes social and environmental indicators. The final goal is to highlight future challenges left unsolved in next 15 years of socio-economic development and analyze costs and benefits of specific policies to support the achievement of proposed targets. This paper presents the methodology and the results of the retrospective assessment. Five main steps are described: i) screening of indicators eligible to address the UN SDGs; ii) data collection from relevant sources; iii) organization in the three pillars of sustainability (economy, society, environment); iv) normalization to a common metrics; v) aggregation of the 25 indicators in composite indices by pillars as well as in the multi-dimensional index. The final ranking summarizes countries’ sustainability performance. As expected, Middle-North European countries are at top of the ranking (Sweden, Norway and Switzerland the first three), with the most industrialized European countries such as Germany and UK, however, penalized by insufficient environmental performance. Other highly developed countries are between 24th (Canada) and 52nd place (United States). The emerging nations are scattered in our sustainability ranking. Brazil (43rd) and Russia (45th) precede China (80th) and India (102nd), the latter two especially penalized because of their social complexity. The worst performances, in terms of overall sustainability, are in Sub-Saharan Africa (Comoros, the Central African Republic and Chad occupy the last places in the ranking)