Coupled atmospheric chemistry, radiation, and dynamics of an exoplanet generate self-sustained oscillations.

Nonlinearity in photochemical systems is known to allow self-sustained oscillations, but they have received little attention in studies of planetary atmospheres. Here, we present a unique, self-oscillatory solution for ozone chemistry of an exoplanet from a numerical simulation using a fully coupled, three-dimensional (3D) atmospheric chemistry-radiation-dynamics model. Forced with nonvarying stellar insolation and emission flux of nitric oxide (NO), atmospheric ozone abundance oscillates by a factor of thirty over a multidecadal timescale. As such self-oscillations can only occur with biological nitrogen fixation contributing to NO emission, we propose that they are a unique class of biosignature. The resulting temporal variability in the atmospheric spectrum is potentially observable. Our results underscore the importance of revisiting the spectra of exoplanets over multidecadal timescales to characterizing the atmospheric chemistry of exoplanets and searching for exoplanet biosignatures. There are also profound implications for comparative planetology and the evolution of the atmospheres of terrestrial planets in the solar system and beyond. Fully coupled, 3D atmospheric chemistry-radiation-dynamics models can reveal new phenomena that may not exist in one-dimensional models, and hence, they are powerful tools for future planetary atmospheric research.

Forecasting the progression of human civilization on the Kardashev Scale through 2060 with a machine learning approach.

Energy has been propelling the development of human civilization for millennia. Humanity presently stands at Type 0.7276 on the Kardashev Scale, which was proposed to quantify the relationship between energy consumption and the development of civilizations. However, current predictions of human civilization remain underdeveloped and energy consumption models are oversimplified. In order to improve the precision of the prediction, we use machine learning models random forest and autoregressive integrated moving average to simulate and predict energy consumption on a global scale and the position of humanity on the Kardashev Scale through 2060. The result suggests that global energy consumption is expected to reach ~ 887 EJ in 2060, and humanity will become a Type 0.7449 civilization. Additionally, the potential energy segmentation changes before 2060 and the influence of the advent of nuclear fusion are discussed. We conclude that if energy strategies and technologies remain in the present course, it may take human civilization millennia to become a Type 1 civilization. The machine learning tool we develop significantly improves the previous projection of the Kardashev Scale, which is critical in the context of civilization development.

Nitrogen Fixation at Early Mars.

The Mars Science Laboratory (MSL) recently discovered nitrates in Gale Crater (e.g., Stern et al., 2015; Sutter et al., 2017). One possible mechanism for ancient nitrate deposition on Mars is through HNOx formation and rain out in the atmosphere, for which lightning-induced NO is likely the fundamental source. This study investigates nitrogen (N2) fixation in early Mars' atmosphere, with implications for early Mars' habitability. We consider a 1 bar atmosphere of background CO2, with abundance of N2, hydrogen, and methane varied from 1% to 10% to explore a swath of potential early Mars climates. We derive lightning-induced thermochemical equilibrium fluxes of NO and HCN by coupling the lightning-rate parametrization from the study of Romps et al. (2014) with chemical equilibrium with applications, and we use a Geant4 simulation platform to estimate the effect of solar energetic particle events. These fluxes are used as input into KINETICS, the Caltech/JPL coupled photochemistry and transport code, which models the chemistry of 50 species linked by 495 reactions to derive rain-out fluxes of HNOx and HCN. We compute equilibrium concentrations of cyanide and nitrate in a putative northern ocean at early Mars, assuming hydrothermal vent circulation and photoreduction act as the dominant loss mechanisms. We find average oceanic concentrations of ∼0.1-2 nM nitrate and ∼0.01-2 mM cyanide. HCN is critical for protein synthesis at concentrations >0.01 M (e.g., Holm and Neubeck, 2009), and our result is astrobiologically significant if secondary local concentration mechanisms occurred. Nitrates may act as high-potential electron acceptors for early metabolisms, although the minimum concentration required is unknown. Our study derives concentrations that will be useful for future laboratory studies to investigate the habitability at early Mars. The aqueous nitrate concentrations correspond to surface nitrate precipitates of ∼1-8 × 10-4 wt % that may have formed after the evaporation of surface waters, and these values roughly agree with recent MSL measurements.