Image: the cost to society from a ton of CO₂—termed the social cost of carbon (SCC) – measures the economic and social effects of a change in climate. (from below article from UHN – University Health Network – Toronto, Canada. 2019)

Date: December 17, 2024

Source: University of California – Davis

Summary:: The social cost of carbon — an important figure global policymakers use to analyze the benefits of climate and energy policies — is too low, finds a new study.
in Science Daily

FULL STORY

The social cost of carbon — an important figure that global policymakers use to analyze the benefits of climate and energy policies — is too low, according to a study led by the University of California, Davis.

The study, published today in the journal Proceedings of the National Academy of Sciences (PNAS), shows that current estimates for the social cost of carbon, or SCC, fail to adequately represent important channels by which climate change could affect human welfare. When included, the SCC increases to just over $280 per ton of CO₂emitted in 2020 — more than double the average published in the academic literature. The study’s estimate is also larger than the U.S. Environmental Protection Agency’s central estimate of $190 per ton of CO₂.

“When people worry about climate change, they worry about the risk and uncertainty it causes,” said lead author Frances Moore, an associate professor in the Department of Environmental Science and Policy at UC Davis. “They worry about long-term, persistent accumulating effects, such as climate change acting as a drag on economic growth. They worry about impacts to very unique natural systems or cultural heritage that are just irreplaceable. Those are what keep people up at night about climate change, and those are not fully included in SCC estimates currently used for policymaking.”

Climate change and the damage done

The social cost of carbon quantifies the damage a ton of carbon dioxide has on society and the economy, including food production, human health, property damage due to natural disasters, and impacts to natural systems. Estimates of the SCC are used widely in policy analysis, particularly to value the benefits of reducing greenhouse gas emissions. The United States, Germany, Canada and several states all have official SCC estimates used for policy making.

Most current government estimates, the study said, are incomplete and likely underestimate the benefits of reducing greenhouse gas emissions. This is because they omit some important ways climate change can affect human welfare, including via economic growth or effects on unique natural systems.

The study combines evidence from both the published literature and a survey of experts to fully integrate these elements into the SCC estimate, providing the most comprehensive assessment of SCC estimates to date.

Accounting for omissions

The Social Cost of Carbon

Date: December 4, 2019Author: Mike Kurz

in Talkin Trash with UHN

The cost of carbon taxes is often lamented in the media, however what we should actually be talking about is the rapidly escalating costs that are being imposed on us as a result of human fossil fuel consumption. The cost of fossil fuel itself does not account for the costs borne by society as a result of emitting carbon dioxide into the atmosphere. While certain costs of the climate crisis are difficult or impossible to nail down (for example, what is the cost to society of a person dying of air pollution or the extinction of species?), many other costs can and have been quantified. The concept of social cost of carbon aims to quantify these costs to better understand the full cost of burning fossil fuels. So what are these costs?

SCC DIAGRAM

Public Health

The climate crisis is a major threat to public health (as I discussed in a previous blog) and is imposing many costs to our healthcare system. You can reference that blog for further details, but the main drivers of healthcare impacts are: increase in labour hours lost, increased frequency of disasters leading to acute loss of life/injuries as well as longer term mental health costs, increased cardiovascular disease associated with pollution and wildfire smoke, expanding range of disease spreading insects, malnutrition associated with reduced crop yields/higher food costs. The Lancet has recently published their latest report on the health impacts of the climate crisis.

All of these impacts stress our healthcare system and increase the cost to deliver health care to society. These public health costs are borne by society as a whole and are mere externalities for the entities that are generating the CO2 emissions.

Photos in original article:

Fossil Fuel Vehicles Cause Climate Pollution and Cardiovascular Disease.

Ticks that spread Lyme Disease are expanding their range within Canada.

Property Damage/Loss

It is projected that the climate crisis is leading to higher incidence of flood risk in North America. We have seen some evidence of this in New Brunswick, Toronto, and Canada overall. Flood damage is often not covered by insurance and damage cost may be borne by individuals, companies, or taxpayers in the case that governments compensate people for damages or pay to relocate communities.

Rising sea levels associated with the climate crisis are also expected to lead to loss of real estate value. Some estimates project the cost to the global economy of up to $14 trillion by the year 2100.

Unless a social cost of carbon is applied, these social costs are not borne by those burning the fossil fuels and emitting the CO2, but rather by society overall.

Agricultural Productivity Loss

The climate crisis is causing an average reduction of the food production capacity of the Earth. Reduction in supply leads to increased costs of food for individuals, businesses and governments. Once again, the costs of burning fossil fuels are being imposed on society rather than on the entity doing the burning.

Ecosystem Services

The natural environment supports human civilization in many ways: provisioning food and water, regulating climate and disease, supporting nutrient cycles and oxygen production, and providing recreational benefits. Some examples of ecosystem services include pollination of crops by bees, filtration of water through natural watersheds, natural predators reducing numbers of prey animals, carbon sequestration in plants, etc. Many of these ecosystem benefits are often taken for granted in economic analysis. In a heating world, some of these benefits are becoming more and more strained. A social cost of carbon analysis accounts for the decline in these ecosystem services.

Social Cost of Carbon

So what do all of these costs add up to? What cost are we imposing on society for every ton of CO2 we emit? There have been several studies that attempted to quantify the cost, but I found the most detailed to be the US Government Interagency Working Group on Social Cost of Greenhouse Gases. You can read the full methodology in their technical document, but the key result is shown in the table ES-1 of the executive summary. I converted the results to 2019 Canadian dollars and used a 3% discount rate which is typical for government agencies and I removed years that have already elapsed to yield the table below:

As you can see, the social cost of carbon in 2020 under the “average” impact scenario is already significantly higher than the highest level of carbon tax scheduled to be imposed in Canada, which will reach $50 per ton by 2022. The scenarios are based on three different peer reviewed climate impact models explained in the technical document. The “average” scenario assumes no extreme tipping points are reached. Generally, projections have been too conservative and have underestimated the impacts of the climate crisis. Therefore, it may be wiser to consider the high impact scenario, which assumes the 95th percentile for the cost of climate heating. Although these models were produced by the US Government, the Canadian Government has used the same models to estimate the social cost of carbon so I believe the analysis is relevant to Canada.

With impacts as severe as those shown, it starts to make sense when organizations such as the Ecofiscal Commission say that we will need a carbon tax of $210 to reach our 2030 Paris climate targets. Interestingly, documents are now being uncovered that show Canadian oil company Imperial Oil has known for decadesthat carbon pricing of this magnitude would be necessary to combat the effects of climate change. Their 1991 recommendation of a carbon price of $88.50/ton (converted to 2019 dollars) to “stabilize CO2 emissions” is shockingly close to the social cost of carbon identified in the average impact scenario in the table above. Unfortunately, oil companies typically buried their own climate research and chose to promote denialism instead.

Carbon Pricing in the $80-200/ton range would look like a good deal if it enables us to avoid the worst climate impacts per the table above. So next time the topic of carbon pricing comes up, try not to recoil in terror at the added cost to gasoline and instead think about the significantly larger costs we are trying to avoid.

The societal costs of CO2 emissions are starting to become more and more apparent to governments around the world. Much higher carbon pricing will most likely be coming. Organizations that have a high carbon footprint, including hospitals, need to plan to curtail their fossil fuel consumption to mitigate this oncoming risk.

Through our energy management program, UHN reduced our fossil fuel emissions by almost 20% between 2010 and 2018 despite adding over 600,000 square feet of floor space. We plan to do everything in our power to reach our 2030 targets of a 45% reduction from 2010 levels. This target is based on reductions recommended by the IPCC SR1.5 report.

Article Abstract

Estimating the cost to society from a ton of CO₂—termed the social cost of carbon (SCC)—requires connecting a model of the climate system with a representation of the economic and social effects of changes in climate, and the aggregation of diverse, uncertain impacts across both time and space. A growing literature has examined the effect of fundamental structural elements of the models supporting SCC calculations. This work has accumulated in a piecemeal fashion, leaving their relative importance unclear. Here, we perform a comprehensive synthesis of the evidence on the SCC, combining 1,823 estimates of the SCC from 147 studies with a survey of authors of these studies. The distribution of published 2020 SCC values is wide and substantially right-skewed, showing evidence of a heavy right tail (truncated mean of $132). ANOVA reveals important roles for the inclusion of persistent damages, the representation of the Earth system, and distributional weighting. However, our survey reveals that experts believe the literature underestimates the SCC due to an undersampling of model structures, incomplete characterization of damages, and high discount rates. To address this imbalance, we train a random forest model on variation in the literature and use it to generate a synthetic SCC distribution that more closely matches expert assessments of appropriate model structure and discounting. This synthetic distribution has a mean of $283 per ton CO₂ for a 2020 pulse year (5% to 95% range: $32 to $874), higher than most official government estimates, including a 2023 update from the U.S. EPA.

Anthropogenic climate change affects the welfare of people around the world and will continue to do so for centuries into the future. Because these costs are largely not incorporated into energy, land-use, and other economic decisions, climate change has been termed “the greatest and widest-ranging market failure ever seen” (1, p. i). Incorporating climate costs into the prices of economic activities that emit greenhouse gases, either directly through carbon pricing or indirectly through emission regulation or subsidies of cleaner alternatives, is essential for averting the worst climate outcomes. Quantifying these costs is extremely challenging as it involves projecting and valuing the effects of climate change in all countries and sectors far into the future, an exercise that is rife with uncertainties and contestation.

The external costs of carbon dioxide (CO₂) emissions are summarized by the “social cost of carbon” (SCC): the present value of all future impacts from an additional metric ton of CO₂emissions. The SCC is key for understanding the benefits of emissions-reduction policies and is used for climate and energy policy analysis in the United States, Europe, and numerous other countries and subnational jurisdictions around the world as well as by companies and other institutions (2, 3). Integrated assessment models (IAMs) commonly used to calculate the SCC have been criticized on various grounds, including inaccurate climate and carbon-cycle modeling, ignoring irreversibilities and tipping points in the climate system, failing to adequately model uncertainty or the potential for catastrophic outcomes, and relying on dated science in the representation of climate impacts (4–8).

The continuing importance of the SCC as a tool for climate policy analysis (2) and recognition of failings in IAMs currently used to calculate it has led to a surge of research seeking to improve, expand, and update the estimates. Major strands of this literature include: improving modeling of Earth system dynamics (9–12); disentangling preferences over risk and time using more complex utility functions (13–15); representing tipping points in the climate system (thresholds where reinforcing feedbacks can amplify initial small perturbations to Earth system components to produce much large changes in climate) and associated uncertainties in damages (16–19); addressing model uncertainty, ambiguity, and learning of new information (20–24); allowing climate damages to affect the growth rate rather than just the level of economic output (11, 25–27); calibrating aggregate climate damages on recent economic and scientific evidence (20, 28, 29); modeling the distribution of climate damages and incorporating inequality aversion or distributional weighting (30–32); and explicitly representing climate damages to nonmarket goods, such as natural systems or cultural heritage, which are imperfectly substitutable with market-traded goods (33–36). (SI Appendix, section S3 contains more detailed discussion of the different model structures discussed in this paper and examples of papers integrating them into SCC estimates.)

Although this literature is now substantial, it has accumulated piecemeal. The vast majority of papers make one or two structural adjustments to a simpler IAM and report how these alter SCC values, often with an exploration of associated parametric uncertainty. The collective implications of the full suite of issues addressed by this literature have not been assessed. Previous syntheses have quantified the distribution of SCC estimates and explored a limited set of covariates, such as publication year and discounting (37, 38), as well as the possible role of publication bias (39). Previous modeling studies have made multiple simultaneous changes to individual IAMs (12, 40), or have undertaken systematic IAM intercomparisons and evaluations (41, 42), albeit focusing on a limited number of IAMs with comparable model structures. Previous expert surveys have either imposed very specific structure or none at all (43–45), or have focused on carbon prices (46). Thus, prior studies only illuminate the role of a subset of mechanisms and structural models.

This paper provides the most comprehensive assessment to date of SCC estimates, including how elements of model structure shape the SCC. It builds on two complementary approaches. First, we perform an analysis of SCC values published in the peer-reviewed literature between 2000 and 2020. After reviewing over 2,800 abstracts, we identified 1,823 estimates (or distributions of estimates) published in 147 studies. We recorded SCC estimates and, where reported, the distribution of parametric uncertainty, along with 31 covariates capturing details of the estimate itself (e.g., SCC year, discounting scheme, and socioeconomic and emissions scenarios), important elements of model structure (e.g., growth-rate damages, distributional weighting, and representation of the utility function), and sources of parametric variation (e.g., distributions over productivity growth, climate sensitivity, discount rates, and damage-function parameters). Second, to help place the literature distribution in a broader context, we conduct an expert survey of the authors of the SCC papers in our analysis. We elicit expert estimates of both the distribution of published SCC values in the peer-reviewed literature and their best estimate of the SCC distribution, all things considered. We also ask experts to break down the wedge between these two SCC estimates into component parts, generating information on what experts perceive as potentially missing from or underrepresented in the literature. Furthermore, we elicit experts’ views on the degree to which various model structures that have been explored in the literature improve SCC estimates relative to estimates that exclude them, using this quality assessment to inform our final synthetic SCC estimate.

Our study therefore contains two complementary data-generating processes: a meta-analysis, which collects much richer data on published SCC estimates and their determinants than previous studies, and an expert survey. We combine these lines of evidence to produce a synthetic SCC distribution using a random forest model (a form of machine learning) trained on variation in the literature but sampled to more closely match experts’ assessment of model structures and discounting parameters. The resulting SCC distribution essentially amounts to a structured reweighting of published SCC estimates to better match expert-elicited model structure and discounting. Additional details on the literature review, coding of values, data cleaning and processing, expert survey, and construction of the synthetic SCC are provided in SI Appendix, section S2.

References

N. Stern, The Economics of Climate Change: The Stern Review (Cambridge University Press, Cambridge, UK, 2006).

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