Cold-Temperature Capture of Carbon Dioxide with Water Coproduction from Air Using Commercial Zeolites

The increase in the global atmospheric CO2 concentration resulting from over a century of combustion of fossil fuels has been associated with significant global climate change. With the global population increase driving continued increases in fossil fuel use, humanity's primary reliance on fossil energy for the next several decades is assured. Traditional modes of carbon capture such as precombustion and postcombustion CO2 capture from large point sources can help slow the rate of increase of the atmospheric CO2 concentration, but only the direct removal of CO2 from the air, or "direct air capture" (DAC), can actually reduce the global atmospheric CO2 concentration. The past decade has seen a steep rise in the use of chemical sorbents that are cycled through sorption and desorption cycles for CO2 removal from ultradilute gases such as air. This Review provides a historical overview of the field of DAC, along with an exhaustive description of the use of chemical sorbents targeted at this application. Solvents and solid sorbents that interact strongly with CO2 are described, including basic solvents, supported amine and ammonium materials, and metal-organic frameworks (MOFs), as the primary classes of chemical sorbents. Hypothetical processes for the deployment of such sorbents are discussed, as well as the limited array of technoeconomic analyses published on DAC. Overall, it is concluded that there are many new materials that could play a role in emerging DAC technologies. However, these materials need to be further investigated and developed with a practical sorbent-air contacting process in mind if society is to make rapid progress in deploying DAC as a means of mitigating climate change.

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.