Social Cost Of Carbon Values Research Articles

An alternative approach to capture uncertainties embedded in the estimation of social cost of carbon

AbstractThe continuous increase in global surface temperature, which has been triggered by the increase in atmospheric CO2 concentration from anthropogenic activity, results in damage not only in the short term but also in the long term. This damage, called the social cost of carbon (SCC), has been widely estimated using integrated assessment models (IAMs). A large range of estimated SCC values have been observed because of uncertainties in IAMs' parameters. This study provides a comprehensive review of these uncertainties after dividing IAM modules into four categories: climate sensitivity, damage function, discount rate, and regional–sectoral validation. The review was conducted by comparing key ideas considered by various IAMs: socioeconomic conditions in relation to projected CO2 emissions, estimation of the atmospheric concentration of CO2, estimation of total radiative forcing, parameters of the temperature function, parameters of the damage function, and discount rate value. In addition, this study presents an alternative approach to capture the uncertainties embedded in the SCC estimation, using a machine learning approach. This enables a probabilistic evaluation of a specific level of SCC and improves our comprehension of the implication of the calculated SCC using IAMs. This alternative approach provides a basis for further study of SCC.This article is categorized under: Climate and Environment > Net Zero Planning and Decarbonization

A comparative analysis of the cumulative greenhouse gas emissions and financial viability of residential heating systems located in New York state

AbstractAchieving the stringent climate goals established by New York State will require significant emissions reductions across the agriculture, commercial and residential, electricity, industry and transportation sectors. This study analyzed the residential heating sector and quantified the environmental and financial impacts of four different residential heating pathways for buildings located in New York State. A conventional ultra‐low sulfur diesel pathway served as the baseline scenario against which three low‐carbon alternative pathways were compared: (1) a ‘bioheat’ scenario in which biomass‐based diesel is blended with heating oil; (2) a natural gas scenario; and (3) an electric scenario (air‐source heat pump). The low‐carbon alternative heating pathways incorporate the social cost of carbon as an internalized financial benefit from the conventional ultra‐low sulfur diesel baseline scenario. The bioheat pathway yielded the highest net present value (NPV) at $3 684 513 and the electric (air‐source heat pump) pathway had a NPV of $3 618 229. The electric and bioheat scenarios yielded the lowest and second lowest total cumulative emissions at 28545 Mt CO2e and 51 438 Mt CO2e, respectively. This study also incorporated a comprehensive sensitivity analysis to depict the impact of: NPV discount rates, fuel costs, carbon intensity values, system installation costs and social cost of carbon values. The study provides policymakers, researchers and other interested stakeholders with a comparison of the environmental and financial impacts of diverse residential heating systems. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.

Embedding nature-based solutions into the social cost of carbon.

China, the world's largest CO2 emitter, is making every effort to transition to a low-carbon economy and fulfill its part of a concerted global commitment to combating climate change. In tandem with decarbonizing energy and industries, feasible supplementary measures are urgently needed to help remove anthropogenic CO2 from the atmosphere. A burgeoning literature has emphasized the CO2 removal capability of land re-naturalization (such as afforestation and wetland restoration), thereby regarding cognate land-use conversions as Nature-based Solutions (NbS) and potential climate policy options. However, little empirical evidence exists concerning the effectiveness of different land re-naturalization pathways (such as converting wetlands to forests or agricultural lands to grasslands), and it also remains unclear how NbS alternatives (i.e., land-use conversions resulting in negative CO2 emission) and non-NbS options (i.e., land-use conversions resulting in positive CO2 emission) could affect the social cost of carbon (SCC), a conventional measurement for prescribing carbon mitigation approaches. This study aims to fill in this knowledge gap via embedding NbS into the dynamic integrated climate-economics (DICE) model to quantify their impacts on the SCC. Using the Pearl River Delta region (south China) as a case study for the temporal horizon during 2000-2020, we find that both positive and negative CO2 fluxes have been brought by different natural/semi-natural land conversions, affecting the SCC correspondingly. A total of 7 out of 17 types of land-use conversions could be identified as feasible NbS interventions, including forest restoration, forest-to-wetland, grassland-to-forest, grassland-to-wetland, grassland-to-cropland, cropland-to-forest, and cropland-to-wetland conversions, which could reduce the SCC values (comparing 2020 base-year with 2000 base-year) by 0.0132, 0.0009, 0.0033, 0.0030, 0.0001, 0.0082, and 0.0001 (USD/tCO2), respectively. While the SCC is mainly determined by energy and industrial structure, the overall effect of NbS is larger than the sum of land urbanization and non-NbS land-use conversions. Via embedding the real-world inter-dynamics of land-use conversions into the SCC quantification, this study presents a pioneer assessment of the impacts of NbS on the SCC in an integrated framework, sheds important insights into the effectiveness of NbS, and offers practical implications for policy-makers to devise comprehensive policies covering all feasible CO2 abatement options.

Comparative Analysis of Carbon Capture and Storage Finance Gaps and the Social Cost of Carbon

This paper evaluates how changes in economic market and policy conditions, including the establishment of a per-unit tax on unabated emissions of carbon dioxide (CO2) set equal to estimates of the social cost of carbon (SCC), influence the economics of carbon capture and storage (CCS) for two hypothetical power generation facilities located in the United States. Data are provided from modified versions of models and resources created and managed by the National Energy Technology Laboratory. Changes in economic market and policy conditions are evaluated over a series of scenarios in which differences in the levelized cost of electricity (LCOE) provide estimates of the financial gap necessary to overcome for CCS to be considered the cost-minimizing choice for each power generation facility type considered. Results suggest that for the coal and natural gas power generation facilities considered, a per-unit tax set equal to an SCC exceeding $123 per metric ton of CO2 (/tCO2) emitted (2018 dollars) and $167/tCO2 emitted, respectively, in combination with current Section 45Q tax credits, yields investment in CCS as the cost-minimizing choice; SCC values as low as $58/tCO2 and $98/tCO2 can make CCS the cost-minimizing choice with additional support policies (e.g., free transportation and storage options).

Low-carbon options for the French power sector: What role for renewables, nuclear energy and carbon capture and storage?

In the wake of the Paris agreement, France has set a target of zero net greenhouse gas emissions by 2050. This target can only be achieved by rapidly decreasing the proportion of fossil fuels and accelerating the deployment of low-carbon technologies. We develop a detailed model of the power sector to investigate the role of different low- and negative-emission technologies in the French electricity mix and we identify the impact of the relative cost of these technologies for various values of the social cost of carbon (SCC). We show that for a wide range of SCC values (from 0 to €500/tCO2), the optimal power mix consists of roughly 75% of renewable power. For a SCC value of €100/tCO2, the power sector becomes nearly carbon neutral while for €200/tCO2 and more it provides negative emissions. The availability of negative emission technologies can decrease the system cost by up to 18% and can create up to 20MtCO2/year of negative emissions, while the availability of new nuclear power stations is much less important. This study demonstrates the importance of an effective SCC value (as a tax for positive emissions and remuneration for negative emissions) in reaching carbon neutrality at moderate cost. Negative emissions may represent an important carbon market which could attract investments if supported by public policies.

Low-carbon Options for the French Power Sector: What Role for Renewables, Nuclear Energy and Carbon Capture and Storage?

In the wake of the Paris agreement, France has set a zero net greenhouse gas emission target by 2050. This target can only be achieved by rapidly decreasing the share of fossil fuels and accelerating the deployment of low-carbon technologies. We develop a detailed model of the power sector to investigate the role of different low emission and negative emission technologies in the French electricity mix and we identify the impact of the relative cost of these technologies for various values of the social cost of carbon (SCC). We show that for a wide range of SCC values (from 0 to 500€/tCO2), the optimal power mix consists of roughly 75% of renewable power. For a SCC value of 100€/tCO2, the power sector becomes nearly carbon neutral while for 200€/tCO2 and more, it provides negative emissions. The availability of negative emission technologies can decrease the system cost by up to 18% and can create up to 20MtCO2/year of negative emissions, while the availability of new nuclear is much less important. This study demonstrates the importance of an effective SCC value (as a tax for positive emissions and remuneration for negative emissions) to reach carbon neutrality for moderate costs. Negative emissions may represent an important carbon market which can attract investments if supported by public policies.

Country-level social cost of carbon

The social cost of carbon (SCC) is a commonly employed metric of the expected economic damages from carbon dioxide (CO2) emissions. Although useful in an optimal policy context, a world-level approach obscures the heterogeneous geography of climate damage and vast differences in country-level contributions to the global SCC, as well as climate and socio-economic uncertainties, which are larger at the regional level. Here we estimate country-level contributions to the SCC using recent climate model projections, empirical climate-driven economic damage estimations and socio-economic projections. Central specifications show high global SCC values (median, US$417 per tonne of CO2 (tCO2); 66% confidence intervals, US$177–805 per tCO2) and a country-level SCC that is unequally distributed. However, the relative ranking of countries is robust to different specifications: countries that incur large fractions of the global cost consistently include India, China, Saudi Arabia and the United States.

Quantifying the economic risks of climate change

This Review assesses climate change damage functions, which relate climate variables to economic losses, and how integrated information from impacts, adaptation and vulnerability research could be used to improve estimates of economic risk. Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost–benefit integrated assessment models, with guidance for future work.

Evaluating the Key Drivers of the US Government's Social Cost of Carbon: A Model Diagnostic and Inter-Comparison Study of Climate Impacts in DICE, FUND, and PAGE

The social cost of carbon (SCC) is a monetary estimate of the climate change damages to society from an additional emission of carbon dioxide (CO2). US agencies are now required to apply the SCC to assess the potential benefits of CO2 reductions in federal regulations, including rules and proposals affecting appliances, transportation, industry, and power generation. This paper presents the first in-depth model diagnostic and inter-comparison examination of the three integrated assessment models used to estimate the SCC – DICE, FUND, and PAGE – to reveal how they uniquely determine damages from climate change. Specifically, we reviewed the source code, published documentation, and underlying literature of each of the three models, and then performed controlled experiments to diagnose the contribution of particular sectors, regions, and other model assumptions (parametric and structural) to the resulting cost. We find that DICE and PAGE project substantially higher climate damages, and therefore higher SCC values, than FUND, which includes the potential for net benefits in the near-term. Despite the fact that FUND is highly-disaggregated sectorally and regionally, 95% of its SCC can be explained by a few damage function parameters related to cooling, agriculture, avoided heating, and water resources, particularly those for China. The DICE SCC can only be decomposed into sea level rise damages and an aggregation of all other damages, with the latter category being the dominant SCC driver. The PAGE SCC is mostly driven by non-economic damages, with all costs distributed globally though greatest in the US and least in the former Soviet Union. In all three models, impacts from sea level rise contribute less than one-tenth of the SCC. This study's diagnostic analysis improves public understanding of the SCC, informs future SCC estimation, and sets research priorities for climate impacts modeling.

Climate Impacts on Economic Growth as Drivers of Uncertainty in the Social Cost of Carbon

One of the central ways that the costs of global warming are incorporated into U.S. law is in cost-benefit analysis of federal regulations. In 2010, to standardize analyses, an Interagency Working Group (IAWG) established a central estimate of the social cost of carbon (SCC) of $21/tCO2 drawn from three commonly-used models of climate change and the global economy. These models produced a relatively narrow distribution of SCC values, consistent with previous studies. We use one of the IAWG models, DICE, to explore which assumptions produce this apparent robustness. SCC values are constrained by a shared feature of model behavior: though climate damages become large as a fraction of economic output, they do not significantly alter economic trajectories. This persistent growth is inconsistent with the widely held belief that climate change may have strongly detrimental effects to human society. The discrepancy suggests that the models may not capture the full range of possible consequences of climate change. We examine one possibility untested by any previous study, that climate change may directly affect productivity, and find that even a modest impact of this type increases SCC estimates by many orders of magnitude. Our results imply that the SCC is far more uncertain than shown in previous modeling exercises and highly sensitive to assumptions. Understanding the societal impact of climate change requires understanding not only the magnitude of losses at any given time but also how those losses may affect future economic growth.

Developing a Social Cost of Carbon for US Regulatory Analysis: A Methodology and Interpretation

The US government recently developed a range of values representing the monetized global damages associated with an incremental increase in carbon dioxide (CO2) emissions, commonly referred to as the social cost of carbon (SCC). These values are currently used in benefit–cost analyses to assess potential federal regulations. For 2010, the central value of the SCC is $21 per ton of CO2 emissions, with sensitivity analyses to be conducted at $5, $35, and $65 per ton of CO2 (2007 dollars). This article summarizes the methodology and interagency process used to develop these SCC values, offers our own commentary on how the SCC can be used to inform regulatory decisions, and identifies priorities for further research.

The Influence of the Specification of Climate Change Damages on the Social Cost of Carbon

Abstract Drawing upon climate change damage specifications previously proposed in the literature that the authors have calibrated to a common level of damages at 2.5°C, the authors examine the effect upon the social cost of carbon (SCC) of varying damage specifications in a DICE-like integrated assessment model. They find that SCC estimates are highly sensitive to uncertainty in extrapolating damages to high temperatures at moderate-to-high levels of risk aversion, but only modestly so at low levels of risk aversion. While in the absence of risk aversion, all of the SCC estimates but one agree within a factor of two, with a moderate level of risk aversion included, the differences among estimates grow greatly. For example, one composite damage specification, combining elements of different literature-derived specifications and roughly taking into account calibration uncertainty, yields SCC values 32% higher than the standard quadratic DICE damage function in the absence of risk aversion. With a coefficient of relative risk aversion of 1.4, however, the same uncertain specification yields SCC values almost triple those of the standard function. The authors conclude that failure to consider damages uncertainty and risk aversion jointly can lead to significant underestimation of the SCC.

Using the social cost of carbon in regulatory deliberations

AbstractThis paper reviews the use of social cost of carbon (SCC) values in regulatory deliberations, using practical examples to reveal potential insights. The paper reports on how the inferred choice of input assumptions, and the method used to pick SCC estimates, affects both the size of SCC values and the uncertainty ranges, and that these implicitly influence policy outcomes. The paper also reviews applications of the SCC in the UK. This reveals the following: (1) There is a potential trade‐off between the use of single SCC estimates to ensure consistency, versus use of a range to reflect uncertainty. (2) SCC values are more influential in some sectors than others, which can make it challenging to introduce consistent policies. (3) In some cases the SCC can act as a switching value on major (nonclimate) policy decisions. (4) SCC literature estimates have changed over time, often dramatically. These changes are difficult to implement and policy makers seem to prefer more stable values, even if this means changing input assumptions or methods. (5) For the analysis of climate policy, the decision framework in which SCC values are used makes a large difference to the outcome. (6) There are complex issues and potential inconsistencies involved in applying global SCC values to national decision frameworks comparing costs and benefits. All of these issues caution against a narrow and over‐simplistic application of SCC values in regulatory deliberations. Nonetheless, with appropriate caution and caveats, the paper reports that SCC values can have a role in helping to inform policy. WIREs Clim Change 2011, 2:886–901. doi: 10.1002/wcc.140This article is categorized under: Climate Economics > Economics and Climate Change

The Influence of the Specification of Climate Change Damages on the Social Cost of Carbon

Drawing upon climate change damage functions previously proposed in the literature that we have calibrated to a common level of damages at 2.5 C, we examine the effect upon the social cost of carbon (SCC) of varying the specification of damages in a DICE-like integrated assessment model. In the absence of risk aversion, all of the SCC estimates but one agree within a factor of two. The effect of varying calibration damages is mildly sublinear. With a moderate level of risk aversion included, however, the differences among estimates grow greatly. By combining elements of different damage specifications and roughly taking into account uncertainty in calibration, we have constructed a composite damage function that attempts to approximate the range of uncertainty in climate change damages. In the absence of risk aversion, SCC values calculated with this function are in agreement with the standard quadratic DICE damage function; with a coefficient of relative risk aversion of 1.4, this damage function yields SCC values more than triple those of the standard function.

Estimating the Social Cost of Carbon for Use in U.S. Federal Rulemakings: A Summary and Interpretation

The United States Government recently concluded a year-long process to develop a range of values representing the monetized damages associated with an incremental increase in carbon dioxide (CO2) emissions, commonly referred to as the social cost of carbon (SCC). These values are currently used in benefit-cost analyses to assess potential federal regulations. For 2010, the central value of the SCC is $21 per ton of CO2 emissions and sensitivity analyses are to be conducted at $5, $35, and $65 (2007$). This paper summarizes the methodology and process used to develop the SCC values, complemented with our own commentary about how the SCC can be used to inform regulatory decisions and areas where further research would be particularly useful.