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The Political Economy of Deep Decarbonization: Tradable Energy Quotas for Energy Descent Futures
1. Introduction
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The Core
Jerome Liebling May Day Union Square Park New York City 1948
This weekend at a speech in Mumbai, Hillary Clinton said:
“If you look at the map of the United States, there’s all that red in the middle where Trump won. …I win the coast….I won the places that represent two-thirds of America’s gross domestic product. So I won the places that are optimistic, diverse, dynamic, moving forward. And his whole campaign, ‘Make America Great Again,’ was looking backwards.”
There are many ways to look at this: for one thing, by number, over 90% of the counties are Red. Yet over 50% of the population is concentrated in the cities and Blue counties. Clinton officially won the popular vote. Yet the United States has always had a geographical Electoral College system. A compromise of representation between small, weak states and strong, large states, and the rules of the 2016 campaign were no mystery or surprise. Yet that’s only the middle-sized picture.
The Big Picture is Mrs. Clinton saying she’s representing the important people, the right people – even the working people – and that 2/3rds of those people live exclusively in Blue districts on both coasts. While this is arguably true, it wasn’t always true. NYC or San Francisco have always been important, but from their founding until now, places like Dayton, St. Paul, Pittsburgh, or New Orleans were considered vital, important places, places where their own specialty happened: tires or flour, steel or shipping, lumber or mining.
What Happened? In a way the election was a referendum on “What Happened?” What happened to my community, my country, my area, and all the vital work those long-abandoned areas used to do, what happened to the massive GDP those areas used to contribute, and the answer is simple:
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How Researchers Could Miss the Real Energy Story
How Researchers Could Miss the Real Energy Story
The “standard” approach is to start from the amount of resources that we have of a particular type, for example, oil in the ground, and see how far these resources will go. Growing development of technology seems to allow increasing amounts of these resources to be extracted. Thus, limits seem to be farther and farther in the distance, especially if a person starts out with an optimistic bias. It is easy to get this optimistic bias, with all research funds going in the direction of, “What can we do to solve our energy problems?”
Approaches for forecasting future supply problems that start from the amount of resources in the ground suffer from the problem that it is hard to draw a sharp line regarding when we will run into difficulties. It is clear that at some point, there will be a problem–EROEI (Energy Return on Energy Investment) will be too low–but exactly whenis hard to pinpoint. If a person starts from an optimistic viewpoint, it is easy to assume that as long as Energy Output is greater than Energy Input for a given process, that process must be helpful for solving our energy problem.
In fact, in my opinion, the story is very different. The very thing that should be saving us–technology–has side effects that bring the whole system down.
The only way we can keep adding technology is by adding more capital goods, more specialization, and more advanced education for selected members of society. The problem, as we should know from research regarding historical economies that have collapsed, is that more complexity ultimately leads to collapse because it leads to huge wage disparity. (See Tainter; Turchin and Nefedov.)
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