Reduce Ozone When and Where It Matters Most

Just as we were drafting this commentary, the U.S. Environmental Protection Agency (EPA) issued a new ground-level ozone rule, tightening the standard from 75 to 70 ppb. The projected human health and environmental benefits are substantial. Yet there has been significant concern about tightening the ozone standards because of compliance cost.

As it happens, our research team at the Georgia Institute of Technology recently developed a new way to help meet air quality standards that might reduce the costs of meeting the new ozone rule. Our method is not an end-of-pipe air pollution control technology. Rather, we take advantage of the fact that ozone concentrations vary substantially by day and by hour, depending on the emissions from local and regional sources as well as on atmospheric chemistry and atmospheric conditions such as temperature and mixing. Emissions from a specific hour of the day can have a disproportionately large—or minimal—impact on the pollution that forms, owing to the synergy with emissions from other hours combined with the effects of changing winds, atmospheric mixing, and sunlight.

What’s interesting about this is that for a power plant operating at full capacity, on some days and at some times the resulting human health impacts may be low, whereas on other days—even similar days at the same time—health impacts can be elevated.

Basically, our method, which we call APOM (for Air Pollution Optimization Model), targets high-impact times, reducing health impacts at a lower cost. During low-impact time periods, the operations of power plants do not need to change, minimizing the impact on electricity generation cost. During high-impact times, some generation is either shifted to power plants that will have less effect on ozone concentrations in highly populated regions at that specific time, or generation is reduced using demand management. Because this method can be used when its benefits are greatest, and because it is managed entirely through power system operations, without purchase of pollution control equipment, it can reduce ozone levels at lower cost. (See for more details and an animation.)

Why Hasn’t This Been Done Before?

Power systems use computer models to control the operations of their power plants throughout the day, determining the level at which each power plant should operate as the day progresses. Our method allows a simplified air quality impact model to be included as part of a power system’s operation model. The simplified “reduced form” air quality model is based on a very comprehensive model, called CMAQ, used by the scientific community, government agencies (including the EPA), and stakeholders worldwide to simulate and study air pollution formation and forecast air quality. CMAQ does a great job, but it is too slow and complex to run the thousands of times needed for APOM.

Using a technique developed by our team called DDM-3D, we can determine from one CMAQ simulation how air quality across a region responds to emissions from power plants and other targeted sources, without repeating CMAQ simulations for each emissions scenario. This leads to a reduced form model that responds almost exactly like CMAQ to changes in emissions, but instead of taking days to run, takes less than a second.

New Method Still Under Development

In our first demonstration of this technique, we focused on reducing health impacts in the state of Georgia by using mathematical optimization to quickly sift through a huge number of possible electricity generating patterns. By considering many ways to adjust power plant operations as the day goes on, balancing ozone impacts with power plant operation costs on an hourly basis every day, the APOM method was able to search out and find low-cost ways to improve air quality and human health.

More needs to be done before this method is ready for broad operational deployment. Also, although our case study demonstration was done for an electricity generation system, the same method could be applied to industrial sources, transportation sources, and residential sources of ozone-producing emissions.

There are examples of similar approaches that have successfully been incorporated in the operation of electricity systems. One is the use of congestion pricing. When the transmission system is congested, the operator chooses alternative (often more expensive) generating units to relieve system congestion in a given region. These prices differ in terms of time and space. Pricing air quality in the same way is now a possibility with this approach.

Facilitating a Broader Mix of Generation

The key advantage of this approach is that it can find low-cost ways to improve air quality. A second advantage is that it can be applied soon, for existing facilities. While pollution control equipment or replacement of emission sources may be the best approach, the APOM approach can be applied quickly. It can also be applied anywhere in the world. In locations with significant air quality challenges, this approach can provide benefits before pollution control technology can become widespread. A third advantage is that the APOM approach can allow different kinds of emission sources to work together, using market-based approaches, to reduce ozone levels at least cost.

The heart of the APOM approach is to find the lowest cost ways to change operations when it matters most—times when ozone concentrations would be highest. This approach can work with high-emitting sources and, in fact, could allow high-emitting sources to continue operating while contributing to meeting the new air quality standards. Because of this, reliance on the APOM approach is unlikely to be able to substitute for improved technology that will reduce emissions permanently and comprehensively. Yet, it can be an opportunity for electricity generators, industrial facilities, and other sources to remain in operation and meet emissions limits at lower costs than they have expected. ■

Valerie Thomas, Paul Kerl, Juan Moreno Cruz, Athanasios Nenes, Matthew Realff, Armistead Russell, and Joel Sokol are at the Georgia Institute of Technology; Wenxian Zhang now works at Trinity Consultants. [Ed.: Name spelling correction for Wenxian made 9/13/16.]

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