Researchers at The Department of Energy Resources Engineering at Stanford's School of Earth, Energy & Environmental Sciences share their insight on average vs. marginal emissions, to help design interventions that could provide large environmental and health benefits.
Policymakers in the U.S are encouraging the widespread use of renewable energy to reduce pollutants, especially carbon dioxide. Understanding how much pollution is released at different times by power plants will inform policymakers on the interventions needed to reduce the damage to health and the environment.
Policy makers normally use the annual average emissions intensity – level of emissions per unit of economic activity averaged over an entire year - to calculate the emissions which missed a policy or investment-based intervention. For some interventions, using average emissions intensities does not always highlight the damages avoided. This then might cause a policymaker to think an intervention is not as effective as it could be. Thus, its implementation might not be as widely used, despite its large benefits.
Scientists tested the difference between average and marginal emissions (hourly monitoring of emissions) analysing electricity from PJM, the largest wholesale electricity market in the U.S and therefore, a large producer of emissions.
Results showed that average emissions do not allow one to see the positive effects of the interventions. However, marginal emissions give a much better indication of how well the intervention is working.
Priya Donti, a PhD student at Carnegie Mellon University and study co-author, stated that ‘The electric grid is changing rapidly, (and) emissions intensity data is often released with a large lag (which) demonstrates the importance of frequently updating this data.’
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