EU Gives Up on Climate-change Regulation! Really?

On January 22nd, the NY Times reported (here) that the European Union (EU) "…proposed an end to binding national targets for renewable energy production after 2020." The reasons given in the article were "high energy costs, declining industrial competitiveness and a recognition that the economy is unlikely to rebound strongly..." from the Financial Crisis of 2007-08. This would appear to be pretty bad news since the EU has been a world leader in addressing climate change. The NY Times concludes that "…now even Europe seems to be hitting its environmental limits."

What is confusing here is that the NY Times article goes on to say that:

Europe pressed ahead on other fronts, aiming for a cut of 40 percent in Europe’s carbon emissions by 2030, double the current target of 20 percent by 2020.

From the standpoint of climate change, the only really important point is that the EU reduce its CO2 emissions since CO2 -> + (Global Temperature). Does it really matter how they get there? More than that, from the graph above you can see that the EU has reduced CO2 emissions by 20% from the peak in 1981 to 2010. My forecast (dotted red line) predicts another 16% decrease by 2020 and a 30% decrease by 2046 (the end of the forecast). By 2050, the EU would be close to 1960 levels of CO2 emissions for almost a 45% reduction from the peak levels of the 1980s.

Environmental groups, such as Greenpeace, have been calling for more rapid and deeper decreases, asking for a 55% decrease by 2030. Partly, these demands are based on the idea that the existing reductions in CO2 emissions have been the result of policy measures. And, if that is true, then we don't want any policy reversals or backing away from hard emission targets. Targets themselves imply that policy goals are driving the reduction in CO2 emissions. But, what if policy pronouncements have nothing to do with reduction in CO2 emissions, at least in the EU?

The EU20 model that was used to produce the forecast in the graph above has no policy variables in it. This is not to say that policy variables are not important, just that policies directed at producing more green energy are not that important to the the overall economic system and it is the overall economic system that is responsible for generating CO2 emissions.

A comparison between the North American regional model (NAC20) and the EU20 model will help make the point. Without policy intervention, the NAC20 will keep producing higher and higher levels of CO2 emissions for ever. There are currently no limits to growth in the NAC20 model while there are  in the EU20 model. Growth will essentially be over in the EU20 model by 2040. The same thing will not happen in NAC20 model unless there are policy interventions or some other external forces limiting growth.

This is not to say that the environmental community should not be holding the EU to its environmental commitments. Even though the EU20 model predicts future reductions in CO2 emissions, no one knows the future and there are alternative futures for the EU, but that will have to be a subject for a future post, as will a discussion of the EU20 and NAC20 models.

NOTE: The CO2 data (CO2 emissions in kilo tons), EN.ATM.CO2E.KT in the plot above,is taken from the World Bank's World Data Bank (here) as is all the data in the EU20 and NAC20 models.

Calculating Forecasting Odds: Think Like a Stockbroker

In a Take Part article (here), Amy Luers, Director of Climate Change at the Skoll Global Threats Fund, takes on the issue of variability and forecasting. Leurs makes the argument that global temperature forecasting and stock forecasting have similar problems with statistical variability. Working with Leonard Sklar, Professor of Geology at San Francisco State University, Leurs developed the two graphs above. On the left is the Dow Jones Industrial Average (DJI, my forecast for the SP500 is here), on the right is Global Temperature (my forecast is here). The bottom left graph shows the odds of making money if you invested in any random year (1913-2010) and stayed in the stock market for up to 50 years. After about 35 years of staying invested, there is a 100% chance of making money. On the right is the same graph for global temperature. It takes a little longer, but after 45 years you have a 100% chance of finding a temperature increase. Notice that in both cases, if you look over only brief periods, the odds are closer to 50-50.

The graph above is from page 381 of Nate Silver's book The Signal and the Noise. In 2007, the notorious Scott Armstrong, Professor of Marketing at the Wharton Business School, made a $10,000 bet with Al Gore that Armstrong modestly called "The Global Warming Challenge." Armstrong and his colleague Kesten Green, an Australian Business School Lecturer,  have argued (here) that Global Temperature is too variable to forecast. The Armstrong-Gore bet was to be resolved monthly. Predicting "no-change," Armstrong argued from the data above that he had won the bet.

Given the Luers-Sklar data, we understand why Armstrong made this bet and we also understand why Al Gore never took the bet. Five years is far too short a time to determine whether temperature has increased or whether, for that matter, the stock market has made money. Having published "Principles of Forecasting, [...a book that...] should be considered canonical to anybody who is seriously interested in the field [...of forecasting]" (these are Silver's words), Prof. Armstrong should have known better.

The basic problem with Prof. Armstrong, his "Global Warming Challenge" and his forecasting principles (I have commented on the principles here) is summed up by a quote from Nelson Mandela "Where you stand depends on where you sit" and Prof. Armstrong sits in the business school and is paid to market business activity as having little impact on the environment. All the forecasting principles and outrageous bets in the world will not cover up this canonical conflict.

Peak Oil Forecast and Global Warming

Peak Oil is the point where the rate of petroleum extraction starts declining because the resource is being exhausted.  US domestic Peak Oil production was reached in 1970. World oil production may have peaked in 2011, but it is too early to establish that as fact. In this post, I will forecast World oil production using the WL20 model to see whether the model thinks the World system has reached Peak Oil.

If you've "peaked" at the graphic above you probably can determine that the answer will be "Yes"! However, there's much more at stake here than the simple conclusion, however controversial, that we have reached Peak Oil.

After seeing my Global Warming forecast (here), one of my readers wondered whether anyone had combined Peak Oil models and Global Warming models. He reasoned, correctly, that the  WL20 model was capable of exploring the link between Peak Oil and Global Warming. This post will explore that relationship.

The underlying theoretical model linking Peak Oil and Global Warming is pretty simple: (Oil Production) -> (CO2 Emissions) -> (Global Warming). You might disagree with this linear causal model, but assume for the moment that it is correct. Then, anything that reduces oil production, like Peak Oil, will reduce Global Warming. My Global Warming forecast (here) shows Global temperature peaking sometime between 2040 and 2060. My Peak Oil Forecast above shows that oil production has reached its peak and is likely to collapse entirely around 2040. The result would seem to confirm the simple theoretical model, but how are these two forecasts related within the WL20 model?

The WL20 model model is a state-space model with three state variables (these state variables were not imposed on the model a priori but were the result of the statistical analysis): the first state variable measures overall growth in the World system; the second state variable measures declining biodiversity; and, the third state variable measures increasing resource constraints in the commodity markets related to the Ecological Footprint. The three state variables are interrelated: increasing biodiversity is related to declining global temperature while  increased resource extraction through commodity markets and overall economic growth are related to positive increases in global temperature.

The early peak in oil production is just one of a number of negative feedback loops within the model. The negative feedback loops limit overall growth in the World system around 2040 (see the WL20 state-variable forecast here). Global temperature takes a few more decades to peak after that, but it is really the end of overall growth, not just Peak Oil, that eventually limits global temperature growth, at least in the WL20 model.

There seem to be very few studies that have pursued the link between Peak Oil and Global Warming possibly because there are many alternative, high-carbon sources of energy (tar sands and synfuel from coal being two examples) that could be substituted for oil. Others, such as Amory Lovins (here) have argued that "Efficiency is cheaper than fuel" and will, for economic reasons, eventually limit emissions along with cheaper green energy. The WL20 model is capable of making projections of economic efficiency, a topic I will have to return to in a future post. The difficulty with the "substitution" argument is the important extent to which the entire World system is built on the oil economy. Even though we switched from a coal- to an oil-based economy in the 20th Century, it's not clear that the next energy conversion will be that easy given the larger scale of the present World system.

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The prediction of Peak Oil was initially made by M. King Hubbert, a Shell geoscientist who died in 1989. The Hubbert curve or Hubbert peak for the World system is displayed above (from this source). His forecast, based on logistic curve modeling, predicted that the peak in World oil production would occur in the year 2000. It serves as a warning that no forecasting model can really see into the future. The models are simply attempts to explore the future implications of the data and models available when the forecast was made.