Power density is the rate of energy generation per unit of land surface area occupied by an energy system. The power density of low-carbon energy sources will play an important role in mediating the environmental consequences of energy system decarbonization as the world transitions away from high power-density fossil fuels. All else equal, lower power densities mean larger land and environmental footprints. The power density of solar and wind power remain surprisingly uncertain: estimates of realizable generation rates per unit area for wind and solar power span 0.3–47W_em⁻² and 10–120W_em⁻² respectively. We refine this range using US data from 1990–2016. We estimate wind power density from primary data, and solar power density from primary plant-level data and prior datasets on capacity density. The mean power density of 411 onshore wind power plants in 2016 was 0.50W_em⁻². Wind plants with the largest areas have the lowest power densities. Wind power capacity factors are increasing, but that increase is associated with a decrease in capacity densities, so power densities are stable or declining. If wind power expands away from the best locations and the areas of wind power plants keep increasing, it seems likely that wind’s power density will decrease as total wind generation increases. The mean 2016 power density of 1150 solar power plants was 5.4W_em⁻². Solar capacity factors and (likely) power densities are increasing with time driven, in part, by improved panel efficiencies. Wind power has a 10-fold lower power density than solar, but wind power installations directly occupy much less of the land within their boundaries. The environmental and social consequences of these divergent land occupancy patterns need further study.

We find that generating today’s US electricity demand (0.5 TW_e) with wind power would warm Continental US surface temperatures by 0.24C. Warming arises, in part, from turbines redistributing heat by mixing the boundary layer. Modeled diurnal and seasonal temperature differences are roughly consistent with recent observations of warming at wind farms, reflecting a coherent mechanistic understanding for how wind turbines alter climate. The warming effect is: small compared with projections of 21st century warming, approximately equivalent to the reduced warming achieved by decarbonizing global electricity generation, and large compared with the reduced warming achieved by decarbonizing US electricity with wind. For the same generation rate, the climatic impacts from solar photovoltaic systems are about ten times smaller than wind systems. Wind’s overall environmental impacts are surely less than fossil energy. Yet, as the energy system is decarbonized, decisions between wind and solar should be informed by estimates of their climate impacts.

Context & Scale
An industrial process for large-scale capture of atmospheric CO₂ (DAC) serves two roles. First, as a source of CO₂ for making carbon-neutral hydrocarbon fuels, enabling carbon-free energy to be converted into high-energy-density fuels. Solar fuels, for example, may be produced at high-insolation low-cost locations from DAC-CO₂ and electrolytic hydrogen using gas-to-liquids technology enabling decarbonization of difficult-to-electrify sectors such as aviation. And second, DAC with CO₂ sequestration allows carbon removal.

The feasibility of DAC has been disputed, in part, because publications have not provided sufficient engineering detail to allow independent evaluation of costs. We provide an engineering cost basis for a commercial DAC system for which all major components are either drawn from well-established commercial heritage or described in sufficient detail to allow assessment by third parties. This design reflects roughly 100 person-years of development by Carbon Engineering.

Summary
We describe a process for capturing CO₂ from the atmosphere in an industrial plant. The design captures ∼1 Mt-CO₂/year in a continuous process using an aqueous KOH sorbent coupled to a calcium caustic recovery loop. We describe the design rationale, summarize performance of the major unit operations, and provide a capital cost breakdown developed with an independent consulting engineering firm. We report results from a pilot plant that provides data on performance of the major unit operations. We summarize the energy and material balance computed using an Aspen process simulation. When CO₂ is delivered at 15 MPa, the design requires either 8.81 GJ of natural gas, or 5.25 GJ of gas and 366 kWhr of electricity, per ton of CO₂ captured. Depending on financial assumptions, energy costs, and the specific choice of inputs and outputs, the levelized cost per ton CO₂ captured from the atmosphere ranges from 94 to 232 $/t-CO₂.

Solar geoengineering is no substitute for cutting emissions, but could nevertheless help reduce the atmospheric carbon burden. In the extreme, if solar geoengineering were used to hold radiative forcing constant under RCP8.5, the carbon burden may be reduced by ~100 GTC, equivalent to 12–26% of twenty-first-century emissions at a cost of under US$0.5 per tCO₂.

Global warming potentials (GWPs) have become an essential element of climate policy and are built into legal structures that regulate greenhouse gas emissions. This is in spite of a well-known shortcoming: GWP hides trade-offs between short- and long-term policy objectives inside a single time scale of 100 or 20 years (1). The most common form, GWP₁₀₀, focuses on the climate impact of a pulse emission over 100 years, diluting near-term effects and misleadingly implying that short-lived climate pollutants exert forcings in the long-term, long after they are removed from the atmosphere (2). Meanwhile, GWP₂₀ ignores climate effects after 20 years. We propose that these time scales be ubiquitously reported as an inseparable pair, much like systolic-diastolic blood pressure and city-highway vehicle fuel economy, to make the climate effect of using one or the other time scale explicit. Policy-makers often treat a GWP as a value-neutral measure, but the time-scale choice is central to achieving specific objectives (2–4).