A metric of mortality

 

 

A measure of the mortality cost of carbon (MCC) has been proposed by Bressler (2021), who describes it as a metric for “calculating the marginal mortality effects of emissions.” The metric “represents the number of excess deaths over some time period from one ton of additional carbon-dioxide-equivalent emissions.” Its value depends on the time period chosen for the calculation, and upon predicted changes in global average temperatures, which are themselves dependent on global emissions. The metric makes it possible to calculate, for example, the number additional of tons of carbon dioxide emitted in 2020 which would result in one excess death in the years 2020 to 2100. Such information, along with other measures, “can be useful in informing the decision-making of individuals” and organisations “in determining the social impact of the emissions generated by their activities” as well as guiding policy at higher levels.

An insight at the individual level can be provided by estimating the number of excess deaths predicted to result from one person’s lifetime carbon emissions (treated as if all emitted in 2020). This number varies from country to country, since lifetime emissions also vary with location, but it is, unsurprisingly, highest in the rich developed nations.

Bressler draws on three main sources in developing the mortality cost of carbon, The Lancet Planetary Health study (Gasparrini et al., 2017), the World Health Organization study (Hales, et al., 2014) and 2019 Climate Impact Lab study (Carleton et al. 2020). The limitations of these studies in providing the evidence needed to support the MCC are discussed in some detail, but they “came sufficiently close” to meeting the ideal criteria. The studies provided Bressler with data on the “increase in the mortality rate under different warming scenarios”. For a given increase in global temperature, more excess deaths are expected in those regions which are at present hotter than average, and some colder places will have fewer excess deaths. The effects of some factors, such as conflicts arising from climate change, have been ignored due to lack of evidence.

Figures for the MCC are given with different levels of uncertainty: a central estimate is that “reducing … emissions by 1 million metric tons of carbon dioxide in 2020 saves 226 lives …  in expectation from 2020 to 2100”. (This quantity of carbon dioxide would typically be emitted in a year by “35 commercial airliners, 216,000 passenger vehicles, and 115,000 homes in the United States.”)

While from some viewpoints it may be considered wrong ever to put a monetary value on a human life, decision makers may find themselves forced to ask how much a life is worth, and how much it costs to prevent carbon dioxide emissions. Bressler notes that some methodologies value lives in richer countries more than lives in poorer countries, and avoids this issue by using the global average value of a statistical life year, taken as “just under $12,000 in 2020.” UN projections for current world life expectancy are between 72 and 73 years (Macrotrends 2021), resulting in a life value of about $850,000.

Methods of modelling climate change and its effects are central to the study, and Bressler refers to Integrated Assessment Models (IAMs), the Social Cost of Carbon (SCC), and the Dynamic Integrated model of Climate and the Economy (DICE). Integrated Assessment Models “are used to answer central questions about climate change, from how the world could avoid 1.5C of global warming at the lowest cost, through to the implications of countries’ current pledges to cut emissions” (Carbon Brief, 2018). The Social Cost of Carbon “tries to add up all the quantifiable costs and benefits of emitting one additional tonne of CO2, in monetary terms. This value can then be used to weigh the benefits of reduced warming against the costs of cutting emissions” (Carbon Brief, 2017). The Dynamic Integrated model of Climate and the Economy is the IAM used by Bressler in his study, and he refers to two versions, DICE 2016 and DICE-EMR. An example of the use of a DICE model is given by Nordhaus (2017) in his study on the social cost of carbon, which presented “updated estimates based on a revised DICE model” and estimated that the social cost of carbon (SCC) “is $31 per ton of CO2 in 2010 US$ for the current period (2015).”

Bressler notes that integrated assessment models used to set a social cost of carbon do not adequately take into account the impacts of human mortality. He uses the results of DICE-2016 as his baseline, and modifies the model to take better account of temperature-related mortality, referring to the modified IAM as DICE-EMR (Dynamic Integrated Climate-Economy Model with an Endogenous Mortality Response). One effect is to increase the “2020 SCC from $37 to $258 … per metric ton in the baseline emissions scenario.” Another effect of “pursuing the DICE-EMR optimal emissions path” is to reduce mortality, saving “a projected 74 million lives over the course of the twenty-first century ... as the number of temperature-related excess deaths falls from 83 million in the DICE baseline emissions scenario to 9 million in the DICE-EMR optimal emissions scenario”. The lower mortality corresponds to the lower global temperatures associated with the DICE-EMR path and its higher SCC.

In a supplement to his main article (The Mortality Cost of Carbon – Supplementary Materials) Bressler addresses the effect of extending his analysis beyond 2100. The time scale is extended to 2500, and projections of cumulative excess global deaths are given. Two scenarios are described; in the first (the DICE baseline scenario) annual climate related deaths peak in 2240 at about 19 million, falling below 10 million per annum in 2500, and totalling more than 5000 million by 2500. In the second (DICE-EMR optimal) cumulative excess global deaths reach a maximum of about 100 million.

 

References

 

Bressler, R.D., 2021, The mortality cost of carbon, Nature Communications, online, accessed 22 Oct 2021

https://www.nature.com/articles/s41467-021-24487-w

Carbon Brief, 2017, Q&A: The social cost of carbon, online, accessed 29 Oct 2021

https://www.carbonbrief.org/qa-social-cost-carbon

Carbon Brief, 2018, Q&A: How ‘integrated assessment models’ are used to study climate change, online, accessed 29 Oct 2021

https://www.carbonbrief.org/qa-how-integrated-assessment-models-are-used-to-study-climate-change

Carleton, T. et al. 2020, Valuing the Global Mortality Consequences of Climate Change Accounting for Adaptation Costs and Benefits, National Bureau of Economic Research, online, accessed 28 October 2021

https://www.nber.org/papers/w27599

Gasparrini, A. et al., 2017, Projections of temperature-related excess mortality under climate change scenarios, The Lancet Planetary Health 1, e360–e367, online, accessed 28 October 2021

https://www.sciencedirect.com/science/article/pii/S2542519617301560

Hales, S. et al., 2014, Quantitative risk assessment of the effects of climate change on selected causes of death, 2030s and 2050s, World Health Organization, online, accessed 28 October 2021

https://apps.who.int/iris/bitstream/handle/10665/134014/9789241507691_eng.pdf

Macrotrends, 2021, World Life Expectancy 1950-2021, online, accessed 28 October 2021

https://www.macrotrends.net/countries/WLD/world/life-expectancy

Nordhaus, W.D., 2017, Revisiting the social cost of carbon, PNAS, online, accessed 28 October 2021

https://www.pnas.org/content/114/7/1518