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.
- This presentation describes the method and applications of EASIUR and APSCA.
- Please refer to Getting APSCA and EASIUR for using EASIUR pragmatically as well as getting it in the HDF5 format.
- EASIUR User's Guide (Updated: 5/21/2015), EASIUR Tutorial (Updated: 5/21/2015) (These two documents are not updated yet for some changes made in EASIUR provided below. Please refer to two papers in the publication page.)
- EASIUR marginal social costs [2010 USD/metric ton] are provided in four formats (Updated: 8/21/2015):
- Comparion of EASIUR to AP2: EASIUR is compared to AP2, an updated version of APEEP (Updated: 1/22/2016).
- EASIUR also estimates intake fraction [ppm]. Let us know if needed.
- Center for Climate and Energy
This work was supported by the center for Climate and Energy Decision Making (SES-0949710) through a cooperative agreement between the National Science Foundation and Carnegie Mellon University.
- Center for Atmospheric Particle studies <http://www.cmu.edu/particulate-matter/>