As policymakers seek to reduce carbon dioxide and other pollutants through increases in renewable energy, improving energy efficiency or electrifying transportation, a key question arises: Which interventions provide the largest benefits to avoid the negative health effects of air pollution?
As policymakers seek to reduce carbon dioxide and other pollutants through increases in renewable energy, improving energy efficiency or electrifying transportation, a key question arises: Which interventions provide the largest benefits to avoid the negative health effects of air pollution?
To address this question, it is important to understand how much pollution is released at different times by power plants on the electricity system. The amount of pollution that is produced per unit of energy on the electric grid is measured by what is known as emissions intensity. Traditionally, policymakers and energy modelers have used annual average emissions intensities – averaged across all power plants over an entire year – to estimate the emissions avoided by a power system intervention. However, doing so misses the fact that many interventions affect only a certain set of power plants, and that these effects may vary by time of day or year.
By using marginal emissions that are collected on an hourly basis and account for location, policymakers may be able to glean important information that would otherwise be missed, according to new research. This approach may help decision-makers more clearly understand the impacts of different policy and investment options.
Read more at Stanford's School of Earth, Energy & Environmental Sciences
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