Three Wider Scientific and Economic Implications

The new scientific method presented in Systems Energy Assessment (SEA) allows economic systems to be studied by physical science methods,

so that our accounting method can match nature’s.

The first major practical finding is that the total energy demands of businesses have been undercounted, with the standard LCA method commonly fining only ~80%.   It does not count the outsourced energy uses for the scattered services businesses hire to operate, or their environmental impacts.

  1. Realistic Life Cycle Financial Accounting & business balance sheets
  2. Discovering how much of nature’s systems are hidden from view
  3. Study of complex systems as both natural objects and abstract concepts

These three main wider scientific implications of the method are found on the SEA resource page with other notes and resources. Each of which would take more explaining, but might also be helpful for suggest the intriguing challenges for learning how to apply science to the task of making the earth work for us, and us to work for the earth at the same time.

1. Realistic Life Cycle Financial Accounting & business balance sheets

Having more accurate ways to estimate the resource demands of businesses provides more accurate ways to estimate a business’s exposure to environmental hazards too, such as the need to change resources as we deplete them and the costs of climate change attributable to business operations. That allows the financial cost to the future be more accurately estimated, and included as costs of business operations.

For example, some of the direct financial costs to the future for developing unsustainable businesses and cities and populations could then be shown on “life cycle balance sheets”, for comparing chosen investment strategies and to put on annual business reports for investors to think about.

One of the earliest applications of that would likely be for assessing the global mitigation costs for climate change and energy resource depletion, as a way to establish a “true discount rate” for using investment funds in ways that become ever more unprofitable in the future. It seems likely, for example, that the point at which investors started choosing directions of development with increasingly negative returns for the future could have been a half century ago or longer.

The intent, of course would be to provide information to steer the world economy toward recovering from never before having accounted for any future liabilities at all, and now still following a plan for using up everything affordable on earth essentially as fast as the economy could find a use for it.

2. Discovering how much of nature’s working systems are hidden from view.

A second wider implication is for measuring the resource capacity of the earth, as for MDG’s and other purposes. We’re likely to find the same kind of modeling error as for the energy needs of businesses.

Our models of business energy operating needs have been overlooking the energy needed by the self-managing parts of businesses, and often overlooking 80% of the real total. So our estimates of the natural capital of the earth available to be used for economic development is likely to be similarly underestimating the needs nature’s ecologies, on the order of 80% perhaps.

This is a very important point for plans to monetize all natural resources for creating markets for trading consumption allowances for them. Based on available information, the estimates may be way off. Most of the information needed for that will be naturally hidden from view.

The problem is a persistent conceptual error in describing how natural systems work from what we see, to the point of our often not acknowledging even the existence of natural systems at all. Because they work by themselves and we often just don’t see them at all.

People have habitually defined the systems they observe around them as working by information readily available “believing that what you see is what is there”. That fundamental subjective bias of observers is quite natural, but a mistake to trust and will never go away.

The workings of the self-managing parts of both businesses and nature are located internal to their processes and so at first are quite largely hidden from view. We’ll always remain in the dark about how nature “really” works, and always need ways of avoiding excessive interference none the less.

It’s a tricky problem to solve. As far as we’re concerned most natural systems will always just operate “in the dark”, like whatever goes on inside a plant or within ourselves.   As a result information models for natural systems always start from very incomplete information, and need to be first used for trying to discover what kinds of missing information there are and when missing information will become important to search for as things change.

For SEA a way to compare local and global data gave a good estimate of the scale of missing information about their energy use. That method may not be possible for other system properties or for other kinds of systems.

3. Study of complex systems as both natural objects and abstract concepts

The third wider implication follows from the expansion of the scientific method that SEA provides, the ability of science to refer to “self-defined natural systems” as subjects of science and not be limited to only “data” as it is at present. Being able to identify and refer to some of nature’s units of organization, and not only our numerical measurements, could become a big change.

The systems that sciences now study are “theoretical”, generally information systems constructed by scientists, displaying invented relationships between our measurements to fit a mathematical logic for it. That only very informally describes to the working logic of nature’s complex systems.

So SEA advances the direct study and exploration of the naturally occurring organization and workings of environmental systems, expanding on to the work started in fields like network theory and the naturalist and empirical study of natural systems generally.

SEA shows how to define environmental systems that work as cells of organization in their environments such as businesses and other things, by locating their functional boundary for studying their systemic use of energy. This topic is also addressed in several places in the SEA research paper, and one might look for them when that becomes of interest.

These notes and others are also on the SEA resource site

 

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