In 1961, Frank Drake developed “The Drake Equation”, which calculated the number of likely civilizations in the Milky Way which would be able to communicate with Earth. Over the decades, this equation has been used in a variety of ways to estimate this number. However, almost every value input into this equation has been contested and challenged within the scientific community. This has lead to a wide range of values generated by this equation. This equation also fails to address the possibility of life spreading from planet to planet. Consequently, Caleb Scharf and Leroy Cronin developed the Origin of Life frequency equation.
This equation is fundamentally different from the Drake Equation in that it focuses its constraints on an individual planet instead of the Milky Way Galaxy as a whole. This more focused approach can help make more meaningful predictions about potentially habitable planets rather than a nebulous number that Drake’s equation generates. More specifically, this equation calculates the likely number of times a planet has undergone abiogenesis. This value is assuming that life can emerge on its own in a “chemical soup” on the planet’s surface and the emergence of life on that planet didn’t necessarily come from somewhere else (panspermia). In other words, this equation calculates the average number of “life-forming” events that could have occurred on that planet for a given period of time.
The origin of life equation is shown above, and I believe it will be helpful to break down every value in the equation. The first value is Nb, or the number of potential building blocks on a given planet. On Earth, we usually think of the building blocks of life to consist of things like protein, lips, and carbohydrates. However, for the simplicity of this model, the building blocks of life are tied to the atomic abundances of likely elements used for the creation of life. For example, if we know the estimated size and chemical composition of a planet, we can then estimate the amount of atoms in that planet that may aid or act as catalysts for life. The second value is n0, which is considered the average number of building blocks needed for each “organism”. It is worth noting however, that this value is open-ended when classifying what is or is not an “organism”. The next value is fc, and is the ”fractional availability of building blocks during time t”. This value is used to filter out building blocks on the planet which may not be unusable to developing life. For instance, certain building blocks may be buried beneath the crust of the planet and thus are likely unusable. The last value is Pa, which is the probability of a “life event” through the assembly of building blocks per set of building blocks per unit of time. This variable can take into account many of the unknowns and other factors that could prevent or help cause an abiogenic “life event”.
Overall, this “Origin of Life” equation is an interesting companion to the already well-know Drake equation. From what I have read of this equation it does not aim to offer any clear cut answers, but is a heuristic approach to analyzing the probability of life emerging on a given planet. This equation may have problems, like assuming each variable is independent of the next, but is still an interesting way to look at life’s origins. I would recommend anyone reading this to look at the paper and equation to offer their thoughts as well.
What I liked most about this, was that this equation is an alternative to the Drake Equation, and is more specific to the possibility and likelihood of life on a single planet, rather than how many planets total exist that can have life on them. It would be helpful to give more context on how this equation was developed, and what it means for the future of astrobiology.
This alternative to the Drake equation is fascinating, as I believe it is much less well known. It might be best that they are both used, as the Drake equation proposes how many civilizations are out there to communicate and the Origin of Life frequency equation calculates its probability, which are fundamentally different concepts. The factors are explained well here.
It would have been great if you had given some example values for the factors, as it's mentioned that this equation is more constrained, but there aren't any numbers included to back that up.