EASIUR: Marginal Social Costs of Emissions in the United States

The Estimating Air pollution Social Impact Using Regression (EASIUR) model is an easy-to-use tool estimating the social cost (or public health cost) of emissions in the United States. The EASIUR model was derived using regression on a large dataset created by CAMx, a state-of-the-art chemical transport model. The EASIUR closely reproduce the social costs of emissions predicted by full CAMx simulations but without the high computational costs.

EASIUR's marginal social costs

Figure: Marginal social costs at the point of ground-level emissions estimated by EASIUR
(Value of statistical life: $8.6M in 2010 USD, Relative risk: 1.06)