National Academy of Sciences

David Keith, Debra Weisenstein, John Dykema, and Frank Keutsch. 12/12/2016. “Stratospheric Solar Geoengineering without Ozone Loss.” Proceedings of the National Academy of Sciences. Publisher's VersionAbstract

Injecting sulfate aerosol into the stratosphere, the most frequently analyzed proposal for solar geoengineering, may reduce some climate risks, but it would also entail new risks, including ozone loss and heating of the lower tropical stratosphere, which, in turn, would increase water vapor concentration causing additional ozone loss and surface warming. We propose a method for stratospheric aerosol climate modification that uses a solid aerosol composed of alkaline metal salts that will convert hydrogen halides and nitric and sulfuric acids into stable salts to enable stratospheric geoengineering while reducing or reversing ozone depletion. Rather than minimizing reactive effects by reducing surface area using high refractive index materials, this method tailors the chemical reactivity. Specifically, we calculate that injection of calcite (CaCO3) aerosol particles might reduce net radiative forcing while simultaneously increasing column ozone toward its preanthropogenic baseline. A radiative forcing of −1 W⋅m−2, for example, might be achieved with a simultaneous 3.8% increase in column ozone using 2.1 Tg⋅y−1 of 275-nm radius calcite aerosol. Moreover, the radiative heating of the lower stratosphere would be roughly 10-fold less than if that same radiative forcing had been produced using sulfate aerosol. Although solar geoengineering cannot substitute for emissions cuts, it may supplement them by reducing some of the risks of climate change. Further research on this and similar methods could lead to reductions in risks and improved efficacy of solar geoengineering methods.

Lee Miller and Axel Kleidon. 2016. “Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low generation limits.” Proceedings of the National Academy of Sciences. Publisher's VersionAbstract

Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power limits that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 We m−2) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 We m−2) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power use can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 We m−2 of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power.

Lee Miller, Nathaniel A. Brunsell, David B. Mechem, Fabian Gans, Andrew J. Monaghan, Robert Vautard, David Keith, and Axel Kleidon. 2015. “Two methods for estimating limits to large-scale wind power generation.” Proceedings of the National Academy of Sciences of the United States, 112, Pp. 11169–11174. Publisher's Version miller_et_al._-_2015_-_two_methods_for_estimating_limits_to_large-scale_w.pdf