Overall atmospheric chemistry as a potential biosignature

Introduction

Astrobiology poses one major question: is Life a cosmic imperative? Why does one formulate such a question? Generally, people are familiarized with Life being a singular, isolated process. Something that arose from nowhere. An incidental phenomenon. However, Life could not have existed if energy gradients within Earth’s geochemistry do not occur [20]. As geological eras started and ended, the young, chaotic Earth tempered; but it left some vestiges of its infernal past. Places where a strong thermodynamic disequilibrium remains even today [6] [12] [20] [29]. Some scientists consider Life was initially a mechanism of energy dissipation, thus it evolved and adapted to conquer other environments. Some constraints can be made about that hypothesis, however. In the first place, solely as energy relief processes, organic chemical networks would have not jumped to lifeforms. Because entropy dissipation only favors the simplest systems. Though, the velocity of dissipation heavily relies on informational content. And the accumulation of information requires a certain degree of complexity. Read Sara Imari Walker’s review for a further explanation of this paradox [29].

One thing is clear: living beings cannot be regarded as separate processes from their media. There is complex feedback between both Life and its environment (atmospheric and geochemical)15. Recently, astrobiologists began to compare Earth’s atmosphere with other atmospheres, whether they belong to Solar System planets or Exoplanets. They contrasted not only their constituents but what kind of chemical reactions are given among them. Specifically, how they are organized within a network and what information we can infer from [11]. Here is where Network Topology enters and gives us new perspectives.

For the scope of this review, I am going to exclude the relationship between Earth's crustal components and Life. Mainly because current detection techniques applied on Exoplanets cannot identify the planetary composition just atmosphere constituents. Instead, I am going to focus on how overall atmospheric chemistry can be used as a potential biosignature.

1. Not the sole constituents but their chemistry

When scrutinizing living beings under the scope of Chemistry, as well as their origins, and the changes they exert on their habitats, we cannot conform with focusing on isolated elements. Alike Life, it is advantageous to regard them as mere parts of a whole [25] [26] [29]. Current approaches target to identify biosignature gases through classifying atmospheric composites into three categories: anthropogenic, from geochemical sinks, and biogenic [28]. Most research works focus on the detection of molecular oxygen (both O2 and O3), methane (CH4), nitrous oxide (N2O), and less frequently chloromethane (CH3Cl), dimethyl sulfide (DMS), and dimethyl disulfide (DMDS) [10] [20] [28].

One recent study used a systematic methodology to filter all stable, volatile molecules in Earth’s atmosphere (figure 1). The authors added a new criterium: gases made of famous CHONPS and built up with six or more consecutive non-Hydrogen atoms. However, most of the biogenic gases are produced in undetectable concentrations and are a consequence of exquisitely complex ecology interactions. It turns out virtually unlikely to distinguish which gas is being utilized in what interaction and for what purpose. Living beings' manufacture of gases is dependent on functional needs (either defense mechanisms, stress response, or signaling), diffusion limits, energy availability, and resource limitations. In a nutshell, they encompass the evolutionary history of each organism and cannot be predicted relying upon the knowledge of the physicochemical properties of a given planet [28].

Figure 1. Filtering of all gaseous molecules built from CHONPS and up to 6 non-hydrogen atoms. First, they should be stable but volatile under SPT conditions. Second, compounds known as biogenic are selected from the group. Third, those which are difficult to detect remotely or that require absurd biomass to reach detectable concentrations, are discarded. Finally, geophysically or otherwise generated false positives are rejected as well. Resultant molecules can be classified as those not made by Earth Life, types I and II (byproducts of energy transduction), and type III (generated by secondary metabolism). Reproduced from Seager et al [28].

Nevertheless, massive populations of few microorganisms released overwhelming amounts of certain gases. Both cyanobacteria and green microalgae emit nearly all oxygen in Earth's atmosphere. Marine phytoplankton releases huge quantities of dimethylsulfide (DMS). Also, some species of plants and algae are known to synthesize and release methyl chloride. Along with ozone (O3), these three gases are the most prominent, potential biosignatures [2] [20]. However, for we do not have the slightest clue of alien biochemistries and ecologies, new strategies are required.

Get back to elements and compounds as tiny pieces of the puzzle. While the planet is developing, temperature and chemistry of the local stellar nebula are the key determinants of gaseous constituents. Since planets and their star are formed at the same time, they mold each other. Thereafter, the lightest elements such as Helium and Hydrogen jump away from gravity forces, and the young planet begins to discharge its interior gases thanks to an early, and often chaotic, geological activity [9] [18].

Quantity and constitution of initial atmospheres are rooted in crustal nature [6] [7] [9], which is likewise a reflection of stellar elemental ratios and metallicity. In fact, the unique set of elemental abundances within the host star casts several habitability parameters: mineralogy, internal structure, and surface composition. For instance, stars with higher levels of metallicity, id est Fe/H ratio, and enriched with other heavy elements, such as Carbon, Oxygen, Sodium, and Iron, tend to host giant gaseous. Though so correlations have not been found for terrestrial planets [10].

As an outcome of such intricate parameters, an overwhelming planetary diversity occurs. However, the ensuing of Life cannot be inferred exclusively from the occurrence of certain features. Like, for example, expressing high vulcanism, being a water world, or a Venus-like world or begetting hydrogen-rich atmosphere. Of course, all those planets are likely to be habitable to some extent, but it is not a reliable biosignature. They could be completely abiotic as well [28]. So, instead, I am going to argue why putting altogether atmospheric constituents and reactions, could tell us more about planetary dynamics and why the impact of Life goes beyond the mere presence of certain organic molecules.

2. Network Topology in a nutshell

When we first learn the basics of chemistry, we are taught to represent reactions as equations. It is logical, is the simplest form, though alternative dispositions can bring new insights. One of them is arranging sets of related chemical reactions as networks, or graphs. Id est, ordering their elements whether as nodes or linking edges. Topology is the layout of a given graph and reveals to us how nodes communicate and attach to their neighbors. All sorts of information can be inferred from this method [11].

Now, I am going to briefly outline some concepts of Network Topology. Which are useful to understand how arranging atmospheric chemical reactions as a graph, can indicate if an atmosphere belongs to an inhabited planet or not. Thus, serving as compelling biosignatures.

2.1. Bipartite graphs to integrate reactions and species

Building projection-based schemes to analyze chemical networks, where nodes represent species and edges depict reactions, or vice versa, discards a lot of useful information about the network’s topology [11] [21]. Rather, we can classify nodes into two groups. Using one color for reactions and another for involved species. While directed edges connecting them point out what species are reactants and what are products in each reaction. This allows for better integration of both elements and renders more information about the global properties of the network. Indeed, bipartite graphs spontaneously appear when modeling two different classes of objects. Following some mathematical principles, an edge cannot link two nodes of the same class [11].

Bipartite graphs are widely used in Biology and its related sciences, such as Systems Biology, Medicine, and the OMICS (genomics, metabolomics, proteomics, transcriptomics, etc.), because many biogenic networks already have aforesaid native structure. In addition to this, employing statistical artifacts that could interfere with the analysis turns out unnecessary [21].

2.2. What kind of information can be gathered from network properties

Any network possesses properties which vary hinging upon how it is arranged. Some of them describe individual nodes while others reveal network global interactions. For example, degree distribution measures total connections made by any node with others. This quantity is not fruitful when working with bigraphs because of asymmetric distributions. A better alternative is strength distribution which calculates how many paths a node has, to reach its second neighbors, id est, nodes of its same type, or color [11]. I have compiled the most relevant topological properties in table 1.

Table 1. Relevant topological properties when studying bipartite graphs for complex chemical networks [11].

Before moving to the next section, I am going to spend some time talking about the PageRank algorithm, a notably useful tool for analyzing the chemical network as a whole. It ranks how much time a random walker would spend in each node, measure which is profoundly context-dependent. Initially, all nodes are given with the same amount of time but while algorithm runs, those nodes connected to several inputs progressively retain more the walker. As well as peripheral nodes do. By contrast, nodes with more outputs receive lesser time. Interestingly, expended time also rides on nearby nodes' rank and network geometry. In addition to this, the PageRank algorithm can be executed in both forward and reverse directions, revealing which reactions are preferentially consumers or producers, as well as the species whose formation or production is favored. Surely, self-referencing nodes could trap the random walker, so the algorithm is designed to include a finite probability of teleporting the walker to a chosen node. Respecting chemical networks, it is circumscribed to the initial set of reactants in the forward rout, and by the final state of the system in the reverse direction [11].

3. Non-equilibrium Thermodynamics of Chemical Reaction Networks

Thermodynamic equilibrium comprises three main characteristics. One, the absence of either mass or energy macroscopic flows from or to the system. Because of, entropy variation is at its peak whilst Gibbs free energy and enthalpy are under minimum levels. Which means the energy of the system is stored as potential energy. That is the second feature: radiative, chemical, thermal, hydraulic, and mechanical energies are all held at once, without showing any clue of spontaneous transformation. And three, when isolated, the system does not undergo any shift in its average properties. When these rules cannot be applied to a system then we say that, at a given moment, it is in thermodynamic imbalance [15].

The topology of far from equilibrium networks has its own singularities and it is important to understand atmospheric reaction networks, as well as other complex chemical systems. Here, Stochastic Thermodynamics and deterministic chemical rate equations could help us to clear the landscape. Certainly, all systems tend to progress towards their minimum energy states, but their evolution over time is an interesting subject in order to understand what inequalities exist between networks in chemical equilibrium and those which are not [24].

Founded upon their behavior in the absence of time-dependent driving, two classes of Chemical Reaction Networks (CRN) have been elucidated: detailed-balance CRNs and complex-balance CRNs. Under the above-mentioned restriction, detailed balance networks are prone to reach equilibrium through curtailing Gibbs' free energy. Whereas complex-balance CRNs evolve to non-equilibrium steady states where entropy production diverges into adiabatic or non-adiabatic. Detailed-balance open CRNs could be regarded as a subclass of Complex-balance networks since non-adiabatic entropy production drives the dissipation process in both detailed-balance CRNs and complex-balance CRNs’ steady states [24].

In theoretical analyses, CRNs can be depicted either as closed or open systems. If closed, they do not react with the environment and network kinetics regulate constituents’ concentrations. To simulate driven open systems, external reservoirs known as chemostats are needed to adjust flux of species. Alternatively, such control can be obtained affixing semipermeable membranes into the reactor. Non-driven open CRNs also exist and similarly to closed networks, reaction rates shift reactants’ concentrations. Complex-balance CRNs can be represented as singular topological structures: reaction graphs, in which nodes are built from complexes, id est, clusters of chemical species that are either products or reactants in each reaction. If they are rather characterized as usual, with nodes being chemical species, they adopt whether a hypergraph or a Petri net structure [24].

3.1. Detailed-balance open Chemical Reaction Networks

To accomplish density equality of all thermodynamic extensive properties, local equilibrium and homogeneous reaction mixture must be assumed. Before introducing Gibbs free energy, entropy generation rates and flux measures must be granted. Once reactions are initiated, Gibbs free energy of the CNR turns automatically in a non-equilibrium value and it is always greater, or at least equal, than any equilibrium state adopted by the system. By adding disequilibrium concentration distribution to the equation, ΔG describes the chemical potential of the network components. Generalizing relative entropy, ΔG transforms into a mathematical tool to compare two normalized probability distribution (figure 2). Finally, the change rate of this parameter can be related to entropy rate production using open CRN and chemical work equations [15] [24].

Figure 2. Pictorial representation of the transformation between two nonequilibrium concentration distributions. The equilibrium transformation depends on the equilibrium states corresponding to the initial and final concentration distributions. For a detailed balance CRN, the equilibrium states are obtained by simply stopping the time-dependent driving and letting the system spontaneously relax to equilibrium. Reproduced from Rao et al [24].

3.2. Complex-balance open Chemical Reaction Networks

Chemosttated concentrations break conservation laws, even influencing some of them. That is why other calculations need to be established for the dynamical states. If the energy contribution of said laws is excluded from G, the corrected thermodynamic potential is obtained. As with detailed-balance CRNs, disequilibrium concentration distribution is introduced among other modifications, resulting in the corresponding equilibrium value to be compared. This reveals that reaction dynamics minimizes the transformed nonequilibrium Gibbs free energy. Each one of the chemostatted species creates an emerging cycle, violating another conservation law consequently. As well as detailed-balance CRNs, what is calculated for non-driving CRNs is chemical potential. Contrarily, for open driving systems, the determinant measure is the driving work [24].

It would be interesting to study metabolic pathways, or other biological networks, and atmospheric chemical reactions through this theoretical background. New similarities, or even differences, between both, can appear, then allowing us to better establish or discard atmospheric thermodynamic imbalances as well as its topological features as potential biosignatures. These two topics will be addressed later.

3.3. Energy inputs of your average terrestrial atmosphere

All atmospheres are in thermodynamic disequilibrium to some extent, thanks to a bunch of energy sources stemming from both surrounding celestial bodies and internal geological forces. As I mentioned above, volcanic gases play an important role, but so do internal heat, tidal energy of the planet’s moons, and Host star’s ultraviolet radiation [2] [12]. Photochemistry and derived interactions provoke a set of mechanisms of destruction, which are important when measuring the concentrations of certain gases [12]. All these factors besides crustal imbalances that are found both in Jovian planets as well as within terrestrial ones [22]. For instance, Earth’s solid surface undergoes oxidative weathering which provides some oxygen abundance to the atmosphere. Moreover, hydrogen protons (H+) scaping to space from the exosphere outer layers provokes alterations in the planet’s Gibbs free energy [2] [12].

Planetary atmospheres receive energy hinging upon whether they are from giant gaseous or rocky planets, tending to be highly reducing or oxidizing, respectively [22]. Oceans also contribute to thermodynamic and/or REDOX atmospheric imbalances by containing dissolved oxidants from the crust and acting as environments for certain reactions [12] [30].

4. What are the hallmarks of a complex chemical network?

Before discussing anything, we need to establish what a complex physicochemical system is. Dark nebulae, neutron star’s cores, and lifeforms are all complex systems.; formed and sustained by tangled chemistries. We can agree all three are entirely different from each other, but once we regard them as reaction networks, similarities start to emerge. First, having many components causes all kinds of stochastic effects, or noise, to come up. They are intrinsically linked to ‘unimportant’ interactions between elements of the system. Id est are inherent from their complexity. Of course, not noisy interactions also exist, which present a non-linear distribution. Whether exponential or power laws [11].

As a result, we obtain an emerging behavior, in which isolated components cannot explain the new interactions and the drastic alteration in the overall state of the system. The chemical network could be fragmented into subsystems or modules. Or it could aggregate with similar systems, also yielding modules and establishing hierarchies among nodes and subnetworks [11]. It is known autocatalytic sets crystallize if there are enough of them in proximity. We call these phenomena like phase transitions, or criticality because subtle interactions between noisy elements of the system gradually have less influence on the overall state until network properties suddenly change. In the case of Life, said criticality leads to a highly dynamic, power-law distribution. With most of its nodes displaying few edges and the resting nodes acting as hubs with many edges. Furthermore, the network shows self-similarity and a high degree of cooperativeness. Other features such as “learning” from feedback with its environment and circumstances to adapt are also found within biological networks [29].

The second outcome of criticality is the frequent incidence of catastrophic events since short distance interactions lead to long-range responses [29]. This allows Life to coordinate values of its topological parameters with the landscape, acquiring complex exponents in its power-law function. Those exponents dictate both punctuated equilibrium and Cantor functions in evolutionary processes. Respectively, they are non-gradual transition from stasis to change, and progressions not continuous in all their domains. Also, power-law proportionality is observed in population density as well as in metabolic rates [1].

Power-law behaviors and evolution are clear hallmarks of both Life and Earth’s atmosphere, but indeed they are not the only ones [11] [29]. For this purpose, Jolley [11] simulated two different complex chemical networks: dark clouds and Escherichia coli’s metabolism. Even manifesting greatly complex chemistry, non-biological networks tend to reach equilibrium at a certain point. Dark clouds, for example, get this state a little bit time before they collapse in protostar structures. While living systems had to keep themselves dynamic and reconfigure their metabolic fluxes through enzymatic regulation. Which can be found out as contradictory since both systems show a marked distinction between their species. Some of them are more important as reactants, exhibiting poor formation rates, and others are biased products, with little or no degradation rates and high formation ones. Within interstellar dust clouds, He, He+, and electrons are depleted as they react with each other and the outcomes are H, H2, and CO which gradually nucleate until inner gravity forces overcome turbulence. In bacterial metabolism, raw materials are mainly ATP and NADPH, and skewed products are ADP, NADP+, and CO2. However, the reactants are constantly replenished and the products reflux into the pathway. Evolutionary pressure exerted on metabolic routs could explain that divergence [11].

Kinetics enters indirectly through chosen reactions, rather they are kinetically feasible under the conditions within dark nebulae, or there is an enzyme to catalyze it, linking thermodynamically unfavorable reactions to advantageous processes. Though, topological analyses which somehow include Kinetics as an active variable will uncover more information about complex chemical systems in general and how Life differs from its abiotic counterparts [11] [29].

On the other hand, transitivity features revealed both dark clouds and metabolism are not randomized networks since they bias some motifs while actively avoiding others (anti-motifs). Detailed descriptions are summarized in table 2. Regarding strength gave to each node, both systems share an exponential scaling distribution. Id est, showing the same large-scale ordering [11].

Table 2. Comparison of bipartite transitivity motifs occurrence in two complex chemical networks: dark nebulae and E coli’s metabolism. Quadrilateral motifs are reproduced from Jolley and Craig [11].

Finally, about the PageRank algorithm, Jolley’s analysis found a remarkable asymmetry within dark nebulae chemical networks, which favored reverse direction. Reactant He+, a powerful oxidizing agent, is involved just in one reaction, yielding high ranked nodes and therefore, contributing to the overall connectivity of the network. By contrast, Life displayed more balance between forward and reverse directions for almost all its nodes. Trait thought to help to maintain dynamism in the system [11].

We must notice Earth’s atmosphere chemistry shares many of these characteristics, indicating emergency and power-law behaviors cut across all layers of Life: geochemistry at the bottom; metabolic pathways; gene regulatory networks; cell signaling; neuronal networks; ecology; and atmospheric reactions at the top [22]. In other words, the concept of Life could comprise a hierarchy of interacting networks. Though some of the foregoing topological features are underlying from non-equilibrium thermodynamics, as I discussed above.

Whether they are complex or not, when systems are studied initial and final states must be defined. In most physical systems, a straightforward path appears. There is only one way to go from whatever the initial conditions were, to the unique final state. If we modify those initial conditions, so does the final state and a new path is “created”. Life does not work in the same manner. Even with equal initial conditions, the same compounds, concentrations, and energy inputs, lifeforms could still display a bunch of paths to reach different final states, frequently hinging upon incomprehensible parameters [29]. This could constitute another interesting and maybe decisive, trait of Life networks. Yet we do not know if it is the case of our atmosphere. Neither if Life is able to shape it at this level.

5. Gaps between biotic and abiotic atmospheres

Atmospheres belonging to “death” worlds are structured significantly different than Earth’s, which is the only planet known to sustain life [30]. We can explore their divergences regarding them either as chemical networks [11] or as far from equilibrium REDOX systems [2] [12] [24] [30]. Each one has its own constraints and sheds new light on this topic. How unlike are biological atmospheres from inorganic ones?

5.1. As chemical networks

I have mentioned before Earth’s atmospheric chemistry shares many features of biotic networks. Now I am going to list them. Three of the are the most outstanding and profitable as biosignatures: power-law behavior, self-similarity, marked hierarchy (modularity), and scale-free ordering [11] [22] [29]. On the other hand, lifeless worlds show randomized chemical networks among their constituents, with most of the species homogeneously connected [11] [29]. Earth's atmosphere is also a complex chemical network, though large statistical analyses are required to discern between those topological features distinctive of the different planetary types and those that Life produces [11] [22] [29].

5.2. As far-from-equilibrium REDOX systems

In 1965, Lovelock [19] scrutinized Exoplanet atmospheres and came to an intriguing realization. How long-term coexistence of incompatible species, such as methane (CH4) and oxygen (O2), was possible only on Earth but in other worlds? His idea was somewhat wrong as I will discuss later, and subsequent calculations lessened the expectations about his hypothesis because of contradictory results. However, studying REDOX imbalances present in atmospheres is regaining interest since the current methods are grown in accuracy and reproducibility, and several technical constraints have been overcome. Besides, it could be generalized since it does not rely on a given metabolism or a couple of atmospheric gases. Atmosphere disequilibria emerge then as a compelling spotlight about the turnovers Life pushes on its habitats. Not lone at the local level but also planetary scales [12–15] [26].

The fundamental statement of this hypothesis argues that strong reducing and oxidizing agents do not co-occur during large periods unless they are resupplied regularly as byproducts from metabolic processes. Two REDOX couples have been proposed: CH4–O2 and N2–O2 [2] [12–15] [19]. The first was delayed because of ablating micrometeorites from dust-rich systems and geological, abiotic sinks submit as false positives [2] [12] [30]. The later raises from atmospheric abundances of nitrogen and oxygen and is deficient if we do not consider oceans into the equation. Because Earth’s Gibbs free energy excess is not statistically significant if contrasted to other Solar System planets, it barely scores 1.5 J/mol. However, when liquid water from oceans is included, ΔG multiplies and equals 2326 J/mol [12] [25]. Equation 1 is a simplification of the real calculations [12] and describes how thermodynamic disequilibria of atmospheric gases were worked out:

Figure 3. Ocean-atmosphere REDOX / thermodynamic disequilibrium over two early Earth’s geological eras: Archean (left) and Proterozoic (right). N2-CO2-CH4-H2O imbalance dominates the Archean period thanks to the long biomass of methanogenic bacteria and the absence of CO. This first disequilibrium was smaller than that generated by oxygenic photosynthetic organisms, such as cyanobacteria. N2-O2-H2O REDOX instability yields more Gibbs free energy. It was boosted after the Proterozoic, during the Phanerozoic, because of phototrophs’ spreading across Earth’s surface. Source: author’s own elaboration [3] [13] [14] [23].

Abiotically, lightning destroys N2 and O2, leaving nitrates and nitrites dissolved in ocean water. The reverse process, N2 sparing again into the atmosphere, is unable to counteract depletion, so there are low concentrations of both gases (equation 2). Conversely, when this non-biological ocean-atmosphere system interacts with living beings, it becomes highly dynamic through nitrogen and oxygen fluxes. Photosynthetic organisms replenish both: oxygen is its main byproduct while the organic matter consumed by bacteria, when denitrifying nitrates, is firstly produced by plants, algae, and cyanobacteria. Setting up then the nitrogen cycle: N2, NO2, NO3 (figure 3). It should be noticed that huge biomasses are necessary for these phenomena to take place and, more importantly, to ensure detectable concentrations [2] [12–15] [19] [30].

Photosynthesis also causes two more thermodynamic imbalances that are greater than the ocean-atmosphere system per se: ferric ions and organic carbon. However, they belong to crustal dynamics, then they do not fall into the limits of remote detection methods [12] [15].

Yet one would expect alien biospheres to produce extensive REDOX asymmetries as well we should be careful about assuming REDOX imbalance as a straightforward biosignature30. That is because abiotic mechanisms with poor fluxes and slow kinetics could hold considerable atmospheric chemical disequilibrium likewise. Constituents concentration and pressure-temperature conditions must not be forgotten when executing the calculations. Factors like molecular abundances and ocean volume should be included to better accuracy. However, ocean pH and salinity can be neglected [12–14] [30].

a. An atmosphere modeled by early Life

Probably, N2–O2–H2O imbalance is a byproduct of an oxygenic-dominated biosphere. Main energy suppliers (algae, cyanobacteria, and plants) perform photosynthesis and discharge large amounts of O2 into our atmosphere [2] [12]. But what imbalance would emerge from an anoxic Earth? Before the apparition and spreading of photosynthetic organisms during Proterozoic and Phanerozoic, our world was dominated by Archaea, whose main output was methane gas (CH4). Besides naturally occurring abiotic sinks. Also, in the early stages of Earth’s geological history, the so-called Hadean era, the aggressive vulcanism prompted big amounts of carbon dioxide (CO2) [5–8] (figure 4). Geochemical sinks outgassing, similarly, provided nitrogen. Liquid water, CO2, CH4, and N2 would not have coexisted without methanogenic bacteria, at least not in thermodynamic equilibrium (figure 3). Under inorganic conditions, all four molecules would react and yield ammonium and bicarbonate (equation 3), gradually diminishing atmospheric methane [3] [4] [13] [14] [23].

Figure 4. Releasing and maintaining of atmospheric CO2 in the Hadean. When high gravitational potential energy points out within mantle, subduction between two adjacent tectonic plates occurs. Leaking mantle’s materials into crust thus ensuing vulcanism. Some of them are the named greenhouse gasses: H2O, CO2, SO, NO, etc. Water and carbon dioxide creates an intricate cycle through the ocean-atmosphere-crust system. When in the atmosphere, they arrest ultraviolet radiation from the sun and heat the atmosphere. The temperature rises and allows the presence of liquid water on the planet’s surface. As heating progress, oceans start to evaporate. The steam focus in clouds and, when enough density is reached, they drag down atmospheric H2O and CO2. Carbon dioxide dissolves in carbonates (HCO2—) and along the water, returns into the lithosphere and the cycle initiates again [5–8].

The relative absence of carbon monoxide is one essential requirement for this setting to work since CO–CH4 is abiotically biased. Lifeless Earth carried out a comparably REDOX imbalance arose from hydrogen (H2) as the reducing agent and carbon dioxide (CO2) as the oxidant, along with vapor water and CO. Also, many Archaea exploit CO as simple-to-degrade energy and carbon source. Hence, methane’s photochemistry and carbon monoxide’s high concentrations can be used to avoid false positives [2–4] [14] [23].

N2–CO2–CH4–H2O Archean disequilibria were smaller than N2–O2–H2O, reaching 234 J/mol at its maximum, even if the reaction above (equation 3) provides roughly 170 J/mol. With the apparition and spawning of first photosynthetic organisms, in the Proterozoic, Earth’s available Gibbs free energy augmented considerably. The second and final boost was reached while the Phanerozoic. These findings enforce speculations about biological free energy dissipation through planetary evolution [4] [14] [23] [30].

Interestingly, if Archean microorganisms were chemotrophic rather than organotrophic, the aforesaid REDOX asymmetry would have been dropped off the default abiotic disequilibrium. So would do ferroxidixing phototrophs (equation 4). Although these lower earnings, both cases keep dynamic and do not tend to chemical equilibrium [3] [13] [14].

Whether we are evaluating oxygenic or anoxic ambiances, the thermodynamic imbalance is closely linked to kinetic metrics. They comprise directional fluxes of reactions and timescales. When bizarre biomasses are required to achieve expected free energy variations, or if abiotic processes' yields approximate to that of biogenic minimal driving forces, Life probability severely decreases [14] [23] [27].

Also, regarding carbon monoxide as an absolute antibiosignature is arguable. We must determine beforehand if the biosphere is whether oxidizing or reducing. In the latter case, metabolism might by-produce significant levels of CO along with O2, and consequently O3, because of hybrid photosynthetic ecosystems (figure 5). Even when H2 is a negligible volcanic input. Also, having an M dwarf as host star biases the buildup of carbon monoxide [27], though other studies have been demonstrated that nearly all low-mass stars are unable to flare minimal rates to enrich an atmosphere with molecular oxygen [17]. Therefore, context is key when analyzing REDOX disequilibria as a potential biosignature.

Figure 5. Schematic depiction of a CH4-CO coupled ecosphere-atmosphere model structure. They ran a simulation mixing biological sources of CO (biomass burning and photooxidation of oceanic organic matter), molecular flux limitations imposed by the ocean-atmosphere interface, and photochemistry around late-type stars. Thus, arranging a putative inhabited planet with coetaneous high levels of CO2, CH4, CO, and even O2. Reproduced from Schwieterman et al [27].

6. Atmospheric seasonality

Earth’s obliquity plays a fundamental role in determining the amount of solar radiation at which the biosphere is exposed seasonally. Living beings respond to temperature changes by adjusting releasing rates, gas solubility, precipitation patterns, density stratification, and nutrient recycling. Then shifting the concentrations of most atmospheric constituents separately from the nature of metabolisms implied. These outputs ultimately draw periodic patterns that may be observed remotely [20].

Recording and examining those intermittences could become a powerful tool when characterizing inhabited and lifeless worlds. Seasonality fluctuations also can help to avert the above describe ambiguities and provide some context about planetary dynamics. For instance, if an atmosphere receives scarce quantities of oxygen from both biotic and abiotic sources (similarly to mid-Proterozoic) while showing temporal changes in the strength of ozone UV bands, then we can infer the presence of Life. It is not absurd to deem atmospheric seasonality as a current rebound of biospheres to wavering insolation [20].

Future approaches

Could Life be shaping Solar System’s topology as it does with Earth’s atmosphere and crust? Or is Life a result of the network interactions of the Solar System? For example, one might ask if Earth’s atmosphere is poor in nitrogen because of Jupiter, its giant, gaseous neighbor [18]. Composition of the interstellar medium from which our Solar System was formed exerted a great influence in crustal and atmospheric relative abundances of all planets and moons of the planetary system; and the constitution and size of Sun itself [6] [18]. However, specific interactions between protostellar and protoplanetary clusters also played an important role [18] [22]. We could do a topological study of those interactions in order to answer questions such as: how and why planetary distribution affects the presence of a biosphere on Earth. Still, we must consider technological obstacles to setting up such kind of computational simulation.

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