Computer Models Predict the Effects of Greenhouse Gasses, But To What End?
I’m reading Beyond the Limits by Donella Meadows et. al. and learning all about the computer models these folks have used to predict the consequences of things like exponential population growth on a planet with finite resources. This is brilliant work, and wonderfully thought provoking, but I wonder about its practical application. After all, the world doesn’t have a governing body that will take a certain set of actions according to the output of the model.
Our scientists tell us in no uncertain terms the consequences of what we’re doing with greenhouse gasses, but we come home from our climate change meetings with no agreements to lift a finger to do anything about this. China is building a new coal-fired power plant at the rate of one a week. The best computer model in the world is no match for a large powerful government with an army of 200 million soldiers that is determined to build 50 new electrical plants next year.
“China is building a new coal-fired power plant at the rate of one a week.” Although that is not news, it is disturbing. China is also building nuclear plants, is planning more, and has a number in operation, which will reduce its dependence on coal. China is also doing doing R & D on nuclear power, which is good and for which they should be commended. However, if we don’t get on the ball, we will end up buying advanced nuclear technology from China and it will be our own fault.
While it’s true that there’s no overarching government body empowered to deal with climate change that really isn’t the issue. If you take a step back and think about it governments by their nature are late adopters of the viewpoints of their citizens. Even in the west, where representative governments hold sway, action not only on climate/energy but on any topic gets diluted by the lag between effect-awareness-political pressure-political action-implementation-new effect.
Business and industry tend to be more efficient in this loop for a variety of reasons. They then become the first consumers of the kind of data generated by universities and scientists. In this case climate modeling is already having the substantial practical impacts asked after in this article. Principally in the insurance and agro sectors where water resources and extreme weather become market forces and get voiced by industry lobbyists.
Separately from the link between data and direct action, we should also consider the link between data and indirect action, i.e.. data as a marketing force. This is far harder to quantify but it’s very difficult to imagine there is a causal link. Consider by way of example the causal link between NASA funding and the number of students who declare as engineering majors to universities. There was and continues to be a dramatic correlation between the two although it’s very very difficult to track any specific examples in micro-scale. So too the impacts of further climate modeling on entrepreneurs, investors and students are difficult to see in micro-form but clearly there is a link.
Last, government isn’t absent from the feedback generated by this modeling. DOD is making substantial adjustments to their strategic deployments and conflict scenarios based on water availability and climate-based military conflicts. Bureaucratic and political forces still make the issue a hot-button, but the practical boots-on-the-ground types seem to be taking a great deal of notice.
China also has 5 universities working in parallel on DCFC (Direct Carbon Fuel Cell) which converts carbon/coal directly to electricity and at the very least could halve the emissions from power generation from coal; the DCFC is more than double the efficiency of a coal fired power station. It also provides carbon capture as an integral part of the technology, so the waste CO2 is ready for storage, or better still reuse or recycle it, there are much better things we can do with CO2 than just dump/landfill it.
It’s certainly a worth-while project, but it remains to be seen whether it will be successful. Perhaps we here in the U.S. should also be working on it.