The Price of Heat

Temperature kills in a U-shape. Both extreme cold and extreme heat increase mortality, with a minimum around 20-22°C.^[1] But the curve is not symmetric — heat kills faster than cold at equivalent deviations from the optimum. A day above 35°C adds roughly 4 deaths per million people; a day below -5°C adds about 3.

The critical insight is that this curve shifts. People adapt. Houston residents tolerate 35°C because their built environment is designed for it — universal air conditioning, heat-adapted architecture, emergency protocols. Seattle residents, facing the same temperature, die at 1.8x the rate.^[1]The curve is biological. The adaptation is economic.

Climate change does not distribute its damage equally. Cold, wealthy regions — Scandinavia, Western Europe, parts of North America — see net mortality benefits. Fewer cold deaths outweigh the increase in heat deaths. These regions also have the income to adapt: better healthcare, air conditioning, building standards.

Hot, poor regions absorb nearly the entire burden. Sub-Saharan Africa faces +107 additional deaths per 100,000 by 2100. South Asia faces +85.^[1] These are the regions with the lowest per capita emissions, the least adaptation infrastructure, and the youngest populations. The gap is not just geographic. It is a measure of global injustice with arithmetic precision.

Carleton et al.^[1] use a “revealed preference” method to estimate adaptation costs — they look at what people actually spend on heating, cooling, and building design in response to climate conditions. The finding: adaptation reduces mortality by 29% at a cost of roughly 13% of total damages. The cost-benefit case is overwhelming.

But adaptation requires money. High-income countries spend approximately 3x more per capita on climate adaptation than low-income countries.^[1] An air conditioner in Accra costs roughly the same as one in Houston. But in Accra, it represents months of income. In Houston, hours. The technology exists. The distribution mechanism does not.

The social cost of carbon (SCC) is the central number in climate policy. It represents the total economic damage caused by emitting one additional ton of CO₂. Every cost-benefit analysis of climate regulation relies on it. Prior models — particularly the FUND integrated assessment model — estimated the mortality component at roughly $8 per ton.^[4]

Carleton et al.'s empirical estimate:^[1] $36.60 per ton. That is 4.5x larger than the prior standard. Mortality alone accounts for 44% of the full SCC (~$51/ton). This is not a minor revision. It implies that climate regulations have been systematically under-valued — that the damage we have been ignoring is denominated in human lives.

By 2100 under high emissions, climate-driven mortality (73-85 per 100,000)^[1] approaches the current global burden of all infectious diseases (~74 per 100,000).^[3] We organize entire health systems, international agencies, and billion-dollar research programs around infectious disease. Climate mortality of equivalent scale receives a fraction of the institutional response.

The scatter tells the story with brutal clarity: income determines who survives climate change. Accra (GDP per capita $2,200) faces +160 deaths per 100,000. Oslo ($82,000) gains 25 lives. Both face the same climate change. They face radically different mortality outcomes because adaptation requires wealth that is not equally distributed.

This is the paper's deepest implication. Climate mortality is not a problem of physics. It is a problem of economics. The atmosphere does not discriminate. The global economy does.

The paper's empirical foundation is extraordinary. Carleton et al.^[1] assembled the largest subnational vital statistics database ever compiled: 399 million deaths across 41 countries, covering 55% of the global population. They combined this with 33 high-resolution climate simulations and projected impacts across 24,378 regions.

The three-step framework: (1) aggregate economic and climate data at the local level; (2) estimate the causal relationship between temperature and mortality, controlling for income, age, and local climate adaptation; (3) project forward under multiple emissions and income growth scenarios. The approach uses a 2% discount rate, justified by historical US Treasury returns.

This paper does three things that matter. First, it replaces theoretical models with empirical estimates built on real deaths — and finds the damage is 4.5x worse than we thought.^[1] Second, it quantifies the inequality: the poorest countries will pay 4x more in lives than the richest. Third, it shows adaptation works but requires money — money that the most vulnerable countries do not have.

The policy implication is straightforward: every ton of carbon emitted has a price, and that price is paid disproportionately in the deaths of people who contributed least to the problem. The social cost of carbon is not an abstraction. It is a body count.