Social Cost Of Carbon Estimates Research Articles

Natural resource wealth in sub-Saharan Africa: A boon for public investment in renewable energy?

This paper examines the role of natural resource wealth in financing public investment in renewable energy in 25 sub-Saharan African countries over the period 1996 to 2019. Results from two step system Generalized Method of Moments (GMM) estimates reveal that natural resource wealth negatively affects public investment in renewable energy. A distinction between the types of natural resources allowed to establish that this negative effect comes exclusively from the rents of point natural resources. Furthermore, the results show that institutional quality and human capital favor public investment in renewable energy. These results are robust when using the Driscoll-Kraay estimator. In terms of policy implications, it is imperative to promote good governance of natural resource rents, especially those from point source resources. It will also be necessary to redirect these rents towards the financing of structuring projects such as renewable energies in order to promote sustainable development.

US climate policy yields water quality cobenefits in the Mississippi Basin and Gulf of Mexico

We utilize a coupled economy-agroecology-hydrology modeling framework to capture the cascading impacts of climate change mitigation policy on agriculture and the resulting water quality cobenefits. We analyze a policy that assigns a range of United States government's social cost of carbon estimates ($51, $76, and $152/ton of CO2-equivalents) to fossil fuel-based CO2 emissions. This policy raises energy costs and, importantly for agriculture, boosts the price of nitrogen fertilizer production. At the highest carbon price, US carbon emissions are reduced by about 50%, and nitrogen fertilizer prices rise by about 90%, leading to an approximate 15% reduction in fertilizer applications for corn production across the Mississippi River Basin. Corn and soybean production declines by about 7%, increasing crop prices by 6%, while nitrate leaching declines by about 10%. Simulated nitrate export to the Gulf of Mexico decreases by 8%, ultimately shrinking the average midsummer area of the Gulf of Mexico hypoxic area by 3% and hypoxic volume by 4%. We also consider the additional benefits of restored wetlands to mitigate nitrogen loading to reduce hypoxia in the Gulf of Mexico and find a targeted wetland restoration scenario approximately doubles the effect of a low to moderate social cost of carbon. Wetland restoration alone exhibited spillover effects that increased nitrate leaching in other parts of the basin which were mitigated with the inclusion of the carbon policy. We conclude that a national climate policy aimed at reducing greenhouse gas emissions in the United States would have important water quality cobenefits.

Estimating the economic value of carbon losses from wildfires using publicly available data sources: Eagle Creek Fire, Oregon 2017

BackgroundWildfires are increasingly frequent in the Western US and impose a number of costs including from the instantaneous release of carbon when vegetation burns. Carbon released into the atmosphere aggravates climate change while carbon stored in vegetation helps to mitigate climate change. The need for climate change mitigation is becoming more and more urgent as achieving the Paris climate agreement target of limiting global warming to 1.5 °C seems ever more challenging. A clear understanding of the role of different carbon sources is required for understanding the degree of progress toward meeting mitigation objectives and assessing the cost and benefits of mitigation policies.ResultsWe present an easily replicable approach to calculate the economic cost from carbon released instantaneously from wildfires at state and county level (US). Our approach is straightforward and relies exclusively on publicly available data that can be easily obtained for locations throughout the USA. We also describe how to apply social cost of carbon estimates to the carbon loss estimates to find the economic value of carbon released from wildfires. We demonstrate our approach using a case study of the 2017 Eagle Creek Fire in Oregon. Our estimated value of carbon lost for this medium-sized (19,400 ha) fire is $187.2 million (2020 dollars), which highlights the significant role that wildfires can have in terms of carbon emissions and their associated cost. The emissions from this fire were equivalent to as much as 2.3% of non-fire emissions for the state of Oregon in 2020.ConclusionsOur results demonstrate an easily replicable method for estimating the economic cost of instantaneous carbon dioxide emissions for individual wildfires. Estimates of the potential economic costs associated with carbon dioxide emissions help to provide a more complete picture of the true economic costs of wildfires, thus facilitating a more complete picture of the potential benefits of wildfire management efforts.

Social cost of carbon estimates have increased over time

Social cost of carbon estimates have increased over time

The Social Cost of Carbon, Abatement Costs, and Individual Climate Duties

ABSTRACT In this paper I examine the relation between Social Cost of Carbon (SCC) estimates, abatement cost analyses, and individual climate duties. I first highlight the stakes that SCC and abatement cost estimates potentially have for the content of individual duties to either pay the full or fair cost of their carbon emissions, or offset the volume of their emissions. I survey four methodological options (a minimalist approach, a precautionary approach, an averaging approach, and what I call a ‘sufficiency-bounded’ precautionary approach) for conceptualizing the terrain of individual duties in light of SCC and abatement cost estimates that are both contentious and evolving.

Climate module disparities explain inconsistent estimates of the social cost of carbon in integrated assessment models

•Uncertainties in SCC estimates are attributed to modeling choices in IAMs •The differences in climate modules explain 60%–95% of SCC variations •Non-linear climate system responses result in higher SCC estimates •Unified climate models substantially improve the consistency of SCC estimates The social cost of carbon (SCC) determines the quantifiable cost (in monetary value) of emitting CO2 and has been employed by policy makers to evaluate the benefits of climate mitigation against the costs of cutting emissions. SCC is generally estimated using integrated assessment models (IAMs), primarily the DICE, FUND, and PAGE models. However, these models often report different SCC estimates. Inconsistent SCCs can lead to over-/underestimation of the costs and benefits of emission reduction, further undermining the effectiveness of climate policies. The reasons behind such inconsistent SCCs, however, remain unclear. Here, we quantitatively decompose two core components of IAMs, climate modules and damage functions, and find that the core reason for SCC disparities lies in differences in climate modules. These differences explain 60%–95% of SCC variations. SCC estimates are more consistent when DICE/FUND/PAGE IAMs are coupled with a reduced-complexity climate module. Our study highlights the importance of considering a common modeling framework by synthesizing state-of-the-art information on climate science to provide more consistent science-based advice to policy makers. The social cost of carbon (SCC) determines the quantifiable cost (in monetary value) of emitting CO2 and has been employed by policy makers to evaluate the benefits of climate mitigation against the costs of cutting emissions. SCC is generally estimated using integrated assessment models (IAMs), primarily the DICE, FUND, and PAGE models. However, these models often report different SCC estimates. Inconsistent SCCs can lead to over-/underestimation of the costs and benefits of emission reduction, further undermining the effectiveness of climate policies. The reasons behind such inconsistent SCCs, however, remain unclear. Here, we quantitatively decompose two core components of IAMs, climate modules and damage functions, and find that the core reason for SCC disparities lies in differences in climate modules. These differences explain 60%–95% of SCC variations. SCC estimates are more consistent when DICE/FUND/PAGE IAMs are coupled with a reduced-complexity climate module. Our study highlights the importance of considering a common modeling framework by synthesizing state-of-the-art information on climate science to provide more consistent science-based advice to policy makers.

Impact of choice of inhalers for asthma care on global carbon footprint and societal costs: a long-term economic evaluation

Background While effective asthma control medications reduce the burden of asthma, a significant subgroup of these treatments, namely metered-dose inhalers (MDIs), produce substantial greenhouse gas (GHG) emissions, thus contributing to climate change. This study quantified the global climate impact (i.e. carbon dioxide equivalent [CO2e] emissions) and costs of long-term status quo asthma inhaler use versus alternative scenarios substituting MDIs with propellant-free dry powder inhalers (DPIs). Methods Three scenarios were evaluated across 10-year (2020–2030) and 50-year (2020–2070) time horizons: A (status quo inhaler use), B and C (2% and 5% year-over-year substitution of MDIs with DPIs, respectively). Global inhaler volumes and costs at baseline were sourced from IQVIA, then projected using UN and WHO trends in per capita GDP, urbanization, and asthma population growth. Inhaler spending was assumed to fall by 90% following generic entry in 2030. The carbon footprint per inhaler and health damage factors for disability-adjusted life years (DALYs) were derived from literature. The US government’s central and high-impact estimates for the social cost of carbon (SCC) were used to calculate emissions costs. Results Over 50 years, scenario A resulted in 826 million tonnes of CO2e emissions globally, with an associated SCC between 21% and 65% of the projected global spending on asthma inhalers. In comparison, CO2e emissions were reduced by 38% and 58% in Scenarios B and C, respectively, and DALYs improved by 33 and 51%. Depending on SCC estimates, Scenarios B and C increased global costs by 7.3% and 16.5%, respectively (central SCC), or decreased costs by 4.2% and 2.6% (high-impact SCC) versus Scenario A. Over 10 years, Scenario A resulted in 97 million tonnes of CO2e emissions globally, with an associated SCC between 4.4% and 12.2% of projected spending. In comparison, Scenarios B and C were associated with 12% and 24% reductions in CO2e emissions and improvements in DALYs by 11.5% and 22.7%, respectively. Conclusions Global efforts by environmental and health-policy decision-makers to substitute currently available MDIs with DPIs for asthma control would result in substantial reductions in GHG emissions with manageable costs, or potential cost savings, depending on the SCC. Policies that decrease use of MDIs warrant global attention.

Damage Functions and the Social Cost of Carbon: Addressing Uncertainty in Estimating the Economic Consequences of Mitigating Climate Change.

Mitigating the effects of human-induced climate change requires the reduction of greenhouse gases. Policymakers must balance the need for mitigation with the need to sustain and develop the economy. To make informed decisions regarding mitigation strategies, policymakers rely on estimates of the social cost of carbon (SCC), which represents the marginal damage from increased emissions; the SCC must be greater than the marginal abatement cost for mitigation to be economically desirable. To determine the SCC, damage functions translate projections of carbon and temperature into economic losses. We examine the impact that four damage functions commonly employed in the literature have on the SCC. Rather than using an economic growth model, we convert the CO2 pathways from the Representative Concentration Pathways (RCPs) into temperature projections using a three-layer, energy balance model and subsequently estimate damages under each RCP using the damage functions. We estimate marginal damages for 2020-2100, finding significant variability in SCC estimates between damage functions. Despite the uncertainty in choosing a specific damage function, comparing the SCC estimates to estimates of marginal abatement costs from the Shared Socioeconomic Pathways (SSPs) indicates that reducing emissions beyond RCP6.0 is economically beneficial under all scenarios. Reducing emissions beyond RCP4.5 is also likely to be economically desirable under certain damage functions and SSP scenarios. However, future work must resolve the uncertainty surrounding the form of damage function and the SSP estimates of marginal abatement costs to better estimate the economic impacts of climate change and the benefits of mitigating it.

Estimates of country level temperature-related mortality damage functions

Many studies project that climate change is expected to cause a significant number of excess deaths. Yet, in integrated assessment models that determine the social cost of carbon (SCC), human mortality impacts do not reflect the latest scientific understanding. We address this issue by estimating country-level mortality damage functions for temperature-related mortality with global spatial coverage. We rely on projections from the most comprehensive published study in the epidemiology literature of future temperature impacts on mortality (Gasparrini et al. in Lancet Planet Health 1:e360–e367, 2017), which estimated changes in heat- and cold-related mortality for 23 countries over the twenty-first century. We model variation in these mortality projections as a function of baseline climate, future temperature change, and income variables and then project future changes in mortality for every country. We find significant spatial heterogeneity in projected mortality impacts, with hotter and poorer places more adversely affected than colder and richer places. In the absence of income-based adaptation, the global mortality rate in 2080–2099 is expected to increase by 1.8% [95% CI 0.8–2.8%] under a lower-emissions RCP 4.5 scenario and by 6.2% [95% CI 2.5–10.0%] in the very high-emissions RCP 8.5 scenario relative to 2001–2020. When the reduced sensitivity to heat associated with rising incomes, such as greater ability to invest in air conditioning, is accounted for, the expected end-of-century increase in the global mortality rate is 1.1% [95% CI 0.4–1.9%] in RCP 4.5 and 4.2% [95% CI 1.8–6.7%] in RCP 8.5. In addition, we compare recent estimates of climate-change induced excess mortality from diarrheal disease, malaria and dengue fever in 2030 and 2050 with current estimates used in SCC calculations and show these are likely underestimated in current SCC estimates, but are also small compared to more direct temperature effects.

Cutting through the noise on negative emissions

Cutting through the noise on negative emissions

Benefits and costs of incentive-based forest conservation in the Peruvian Amazon

A growing literature focuses on evaluating the effectiveness of forest conservation policies, but few studies explore where and under which conditions programs produce net positive benefits. Quantifying the costs and benefits of conservation policy instruments contributes to making impact evaluation more relevant for policy makers and can help to improve program design. Here we analyze the costs and benefits of deforestation avoided by the Peruvian Programa Bosques between 2011 and 2015. Our approach builds on an ex post counterfactual-based impact evaluation and considers spatial heterogeneity in conservation opportunity costs as well as uncertainty across a wide range of parameters. We rely on existing social cost of carbon estimates to value benefits and calculate implementation and administration costs from primary and secondary sources. Our estimates suggest that deforestation was avoided at a negative net future value of US$ 13.7 Million in 2015. Poor conservation performance is mainly due to high implementation and administration costs (~67% of total budget). Nevertheless, participating communities benefited from an estimated net transfer of US$ 7.7 Million. Our result emphasizes the need to boost impact, secure the permanence of the avoided deforestation, and minimize program implementation costs, while paying carefully attention to distributional outcomes.

A near-term to net zero alternative to the social cost of carbon for setting carbon prices

The social cost of carbon (SCC) is commonly described and used as the optimal CO2 price. However, the wide range of SCC estimates provides limited practical assistance to policymakers setting specific CO2 prices. Here we describe an alternate near-term to net zero (NT2NZ) approach, estimating CO2 prices needed in the near term for consistency with a net-zero CO2 emissions target. This approach dovetails with the emissions-target-focused approach that frames climate policy discussions around the world, avoids uncertainties in estimates of climate damages and long-term decarbonization costs, offers transparency about sensitivities and enables the consideration of CO2 prices alongside a portfolio of policies. We estimate illustrative NT2NZ CO2 prices for the United States; for a 2050 net-zero CO2 emission target, prices are US$34 to US$64 per metric ton in 2025 and US$77 to US$124 in 2030. These results are most influenced by assumptions about complementary policies and oil prices. Wide-ranging estimates of the social cost of carbon limit its usefulness in setting carbon prices. Near-term to net zero is an alternative modelling approach that focuses on the prices, combined with other policies, needed to set an economy on a pathway consistent with a net-zero emissions target.

Can you trust a model whose output keeps changing? Interpreting changes in the social cost of carbon produced by the DICE model

The social cost of carbon (SCC) measures the present value of the economic damages caused by emitting one marginal ton of carbon dioxide into the atmosphere. It plays a crucial role in climate policy analysis, where it is used to suggest optimal carbon prices or quantify the benefits of actions that reduce emissions. One prominent framework used to estimate the SCC is the Dynamic Integrated Climate-Economy (DICE) model. As updated versions of DICE have been introduced, its SCC estimates have changed, sometimes by amounts that would appear significant. For example, the SCC in 2020 produced by DICE rose 54% from its 2013R version to its 2016R2 version. We address two important questions. First, what changes to DICE explain this increase in its SCC? Second, how surprising is the magnitude of this increase, relative to the uncertainty present in DICE’s input parameters? We find that changes in scientific parameters and updated initial conditions due to near-term forecasting errors accounted for the largest shares of the SCC increase. The later SCC estimate falls within the 80% probability interval produced using the earlier model with uncertainty. Therefore, the 54% increase should not be considered surprising or dispositive regarding the quality of DICE itself.

Climate sensitivity, agricultural productivity and the social cost of carbon in FUND

We explore the implications of recent empirical findings about CO2 fertilization and climate sensitivity on the social cost of carbon (SCC) in the FUND model. New compilations of satellite and experimental evidence suggest larger agricultural productivity gains due to CO2 growth are being experienced than are reflected in FUND parameterization. We also discuss recent studies applying empirical constraints to the probability distribution of equilibrium climate sensitivity and we argue that previous Monte Carlo analyses in IAMs have not adequately reflected the findings of this literature. Updating the distributions of these parameters under varying discount rates is influential on SCC estimates. The lower bound of the social cost of carbon is likely negative and the upper bound is much lower than previously claimed, at least through the mid-twenty-first century. Also the choice of discount rate becomes much less important under the updated parameter distributions.

Estimating the Present Value of Carbon Sequestration in U.S. Forests, 2015–2050, for Evaluating Federal Climate Change Mitigation Policies

AbstractWe demonstrate an application evaluating carbon sequestration benefits from federal policy alternatives. Using detailed forest inventory data, we projected carbon sequestration outcomes in the coterminous 48 states for a baseline scenario and three policy scenarios through 2050. Alternatives included (1) reducing deforestation from development, (2) afforestation in the eastern United States and reforestation in the western United States, and (3) reducing stand-replacing wildfires. We used social cost of carbon estimates to evaluate the present value of carbon sequestration benefits gained with each policy. Results suggest that afforestation and reforestation would provide the greatest marginal increase in carbon benefit, far exceeding policy cost.

The social cost of carbon revisited

An estimate of the social cost of carbon (SCC) is crucial to climate policy. But how should we estimate the SCC? A common approach uses an integrated assessment model (IAM) to simulate time paths for the atmospheric CO2 concentration, its impact on temperature, and resulting reductions in GDP. I have argued that IAMs have deficiencies that make them poorly suited for this job, but what is the alternative? I present an approach to estimating an average SCC, which I argue can be a useful guide for policy. I rely on a survey of experts to elicit opinions regarding (1) probabilities of alternative economic outcomes of climate change, but not the causes of those outcomes; and (2) the reduction in emissions required to avert an extreme outcome, i.e., a large climate-induced reduction in GDP. The average SCC is the ratio of the present value of lost GDP from an extreme outcome to the total emission reduction needed to avert that outcome. I discuss the survey instrument, explain how experts were identified, and present results. I obtain SCC estimates of $200/mt or higher, but the variation across experts is large. Trimming outliers and focusing on experts who expressed a high degree of confidence in their answers yields lower SCCs, $80 to $100/mt, but still well above the IAM-based estimates used by the U.S. government.

Social cost of carbon pricing of power sector CO2: accounting for leakage and other social implications from subnational policies

In environments where climate policy has partial coverage or unequal participation, carbon dioxide (CO2) emissions or economic activity may shift to locations and sectors where emissions are unregulated. This is referred to as leakage. Leakage can offset or augment emissions reductions associated with a policy, which has important environmental and economic implications. Although leakage has been studied at national levels, analysis of leakage for subnational policies is limited. This is despite greater market integration and many existing state and regional environmental regulations in the US. This study explores leakage potential, net emissions changes, and other social implications in the US energy system with regionally differentiated pricing of power sector CO2 emissions. We undertake an economic analysis using EPRI’s US-REGEN model, where power sector CO2 emissions are priced in individual US regions with a range of social cost of carbon (SCC) values. SCC estimates are being considered by policy-makers for valuing potential societal damages from CO2 emissions. In this study, we evaluate the emissions implications within the SCC pricing region, within the power sector outside the SCC region, and outside the power sector (i.e. in the rest of the energy system). Results indicate that CO2 leakage is possible within and outside the electric sector, ranging from negative 70% to over 80% in our scenarios, with primarily positive leakage outcomes. Typically ignored in policy analysis, leakage would affect CO2 reduction benefits. We also observe other potential societal effects within and across regions, such as higher electricity prices, changes in power sector investments, and overall consumption losses. Efforts to reduce leakage, such as constraining power imports into the SCC pricing region likely reduce leakage, but could also result in lower net emissions reductions, as well as larger price increases. Thus, it is important to look beyond leakage and consider a broader set of environmental and economic metrics. Leakage rates, net emissions outcomes, electricity price changes, fuel market effects, and macroeconomic costs vary by region of the country, time, policy stringency, policy design (e.g. leakage mitigation provisions), policy environment in neighboring regions, and price responsiveness of demand.

What's the damage from climate change?

Improved damage models put social cost of carbon estimates on a firmer footing

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.

An economic analysis of policies for promoting economically efficient water heater systems operating under seasonal climatic conditions

This article reports on an economic cost-effective analysis of water heating systems including solar water heating systems. This study finds that in situations where there is a winter, or a rainy season, the choice of the source of energy for the solar water heating systems’ back-up during this period is critical for its overall cost-effectiveness. It is found that in the conditions of North Cyprus, an solar water heating systems with electricity back-up is far superior to using electricity alone; however, it is inferior to heating water with either a liquefied petroleum gas water heater alone or an solar water heating systems with an liquefied petroleum gas back-up. Policies to promote water heating systems that reduce the use of electricity should not encourage the installation of solar water heating systems with electricity back-up. An liquefied petroleum gas water heater or an solar water heating systems with an liquefied petroleum gas back-up are economically more cost-effective, with or without the inclusion of the social cost of carbon estimates.