Is it getting hot in here?

This will be another graph-heavy post, but I just had to share it: Two political scientists, Patrick Egan and Megan Mullin, have investigated whether changes in local temperature affects US citizens’ views about the chance of global warming. Turns out it does, as we’ll see. But the paper itself is full of interesting graphs, which I’ll share with you here. Beware, though, that graphs are not The Truth. They can, however, be Fun.

The authors state that:

In constructing their opinions about political issues, individuals wade through a sea of information that comes from sources including political elites, the media, issue experts, interpersonal relationships, and personal experience. Research on the effects of this information has focused recently on information delivered with ideological cues, or information that elites have made at least some effort to link to an ideological agenda. The prevailing theory about these messages is that those who are interested in politics receive many more such messages than those who are not, and that politically sophisticated individuals accept these messages in a selective fashion based upon whether the cues agree with their personal ideological predispositions, while the less informed are less consistent in what new information they accept […] Less explored is another kind of information that is politically relevant but devoid of ideological content.

They set out to examine how changes in temperature affect views of a political issue such as belief in global warming. First, the money graph, as the Monkey Cage called it in the post where I found this:

Change in temperature vs. agreeing that there is solid evidence for global warming

Change in temperature vs. agreeing that there is solid evidence for global warming

What this tells you, if you see it in conjunction with the numbers provided in the paper, is that for every increase of 3 degrees Fahrenheit, people are 1 % more likely to agree that there is solid evidence for global warming. So this tells us that tangible changes have an effect. However, the effect is actually pretty small, especially compared to factors like partisanship, ideological stance (aren’t those two somewhat related?) or religiosity, as we can see in the following graph:

Effect of different variables on belief in global warming or not

Effect of different variables on belief in global warming or not

Now, we can break this even further down. Here’s a graph of the groups for whom temperature change has a greater effect then average:

Interestingly, blacks are by far those most affected by temperature changes. Just remember that this does not mean that they believe more in global warming than others, just that when temperatures get higher, they are more likely to change their attitude. Someone who believes firmly in global warming will not feel differently if the weather turns cooler, and the opposite goes for the sceptics when it gets hotter. Here is the group for whom it has lesser effect:


To prove that last point about undecision and, well, undecision, here’s a graph showing how party affiliation affects:

Party affiliation vs agreement with global warming

Party affiliation vs agreement with global warming

As you can see, Democrats generally believe more firmly in global warming than Republicans. There are two interesting things in that graph. One is that regardless of temperature change and party affiliation, about 75 % of them believe in global warming. The other finding is that those who less entrenched in party politics, i.e. those leaning towards a party rather than being members, are most affected by outside effects like temperature change when assessing claims about global warming.

We can see something similar when we look at the level of education:

Education vs assessment of global warming

Education vs assessment of global warming

What’s interesting is that the higher the education, the more sure people are of their views on the issue, to the point where post-graduates have no chance of changing opinion on the matter depending on the weather. Finally, I have to include the graph that to me is funniest, if not most valuable. The authors actually took the bother to chart beliefs about climate change against the time of screening of Al Gore’s movie An Inconvenient Truth. Here’s the result:

Belief in global warming vs screening of An Inconvenient Truth over time

Belief in global warming vs screening of An Inconvenient Truth over time

As you can see, there’s a big jump in belief in global warming just around the time the movie aired, followed by a steady, but not as large decline as it stopped running in cinemas.

All this goes to prove that we are suspect to changes in attitude and opinions based on things that are not necessarily rational. Well, rationality might be a bad term, as it’s not irrational to be persuaded by the arguments of a documentary per se, but when so many change their opinion back after a short while, something is going on here.

End of another long post. How about the annual Time’s 100 Poll getting hacked not once, but twice, to spell a message chosen by a small hacking collective who usually hang out at 4chan?


ENOVA seminar

In addition to getting my name in the paper last Thursday, I also attended a seminar by Norway’s national energy conservation advisory board ENOVA. The theme was how to identify the correct instruments for changing habits and behaviour with regards to saving energy. The whole day was devoted to a presentation by a researcher from the Dutch version of ENOVA, SenterNovem, who presented their tool for assessing the correct instrument for affecting change, the Instrument Planner.

The basic idea is that you follow a set procedure, by identifying a target group and a desirable outcome. Then, after answering a questionnaire about different aspects of your target group, the Instrument Planner gives you a list of possible policy instruments with recommendations to choose from. To be honest, I found the Instrument Planner itself to have some serious flaws, but there is some interesting insights to be had from this. I’m going to illustrate the process for you, but first I need to explain the underlying assumptions of the setup.

The government has a number of ways to influence our behaviour, ranging from direct laws and regulations to “softer” approaches like coaching or demonstrations. Naturally, these instruments have different impact on the people to be influenced, and appeal to different parts of behaviour. For example, financial incentives help to enable behaviour by freeing up resources, but might not be a strong motivating factor in the same way using more moral instruments might. So our Dutch researcher has done a literature review on how different instruments affect different parts of what makes up behaviour, and has come up with a chart of what works and what doesn’t:

Coloured fields work, blank don't

Coloured fields work, blank don't

Notice how this is now a binary relation, meaning that if a field is blank, an instrument has no effect at all on that determinant of behaviour. We’ll come back to that shortly. This nice chart has been converted into a handy web site, where people can answer twelve questions about the target group, where each possible answer is given a value. We see the first question here:

Answers range from 0 to 3 points

Answers range from 0 to 3 points

After the twelve questions have been answered, the Instrument Planner sums up your scores:

Here the answers are summed up

Here the answers are summed up

…and comes out with a list of instruments you can choose from, rated after their effectiveness.

The final results

The final results

Now, there’s nothing wrong with a lot of this. It’s standard quantitative procedure to assign values to answers, and try to analyze the relationship between them through this. And in fact, the answers are not half bad. However, there are two major problems with this approach. The first is methodological: there are some questionable choices here. As we saw above, the first operation of the designers of the Instrument Planner was to break down motivations and determinants into binary relations. This means that from here on, there is no room for other influences. After this, they go on to assign numerical values to statements that the user of the Planner check off in the questionnaire. This is a source of possible error, since the points are simply summed up when all the questions are answered. Is “No, [the target group] is not aware of [the goal]” worth exactly three times as many points as “Yes, but [the target group] is not well informed”?

The second problem with this approach is the rhetorical effect it has. In spite of any methodological problems related to the Instrument Planner, the final result will prove almost impossible to dispute once it has been produced. Numbers and “hard facts” have a powerful grip on planner and policy makers, and any tool that promises to deliver answers to complicated relations will be used, regardless of any more theoretical issues. The question is if this is a challenge to the less directly policy oriented among us. Should we perhaps adopt a more clear-cut, less problematizing attitude towards policy recommendations in order to gain influence (because we do, after all, have ideas about what works and what doesn’t), or is that sacrificing academic integrity for power?

Youth and climate change

Yesterday, Robert Næss here at the institute and I had a column (Norwegian) in local newspaper Adresseavisa titled “Youths’ fears of climate change”, where we discuss the impact media coverage of climate changes has on how youth perceive environmental issues. We have found that there is remarkably little research into this, with only two small studies touching on the issue at all.

Using the data Robert collected at the annual Research Days last year, we find that youth actually get most of their knowledge about climate change from the media, and not from school or at home, and that what they read and see about it scares them. Most of the respondents also claim that they are conscious of their energy usage and try to limit it in their everyday actions. However, the people around them, the family and other grown-ups, are not as energy conscious. This finding is of course subject to some uncertainty, as there is reason to expect some erroneous self reporting on this issue.

If it does reflect reality, then there is reason to be both pleased and worried with these findings. It’s good that the leading generation of tomorrow is conscious of environmental issues and willing to take action to do something about it. It’s extremely important that people get good habits at an early stage, for the behaviour to stay with them for the rest of their life. On the other hand, the fact that youth are worried and anxious about what they hear about climate change is food for thought. People probably should be worried about climate change, because it’s a real threat that we have to start adressing properly very, very soon. However, if people are too worried about climate changes being inevitable and large-scale, they might adopt a fatalistic attitude towards it, and this might stand in the way of important changes in behaviour and attitudes.

If you want a closer look at the data from the small survey, my esteemed colleague Thomas Berker has put up an excellent site with graphs of all the data. Go see all the exciting little numbers and purdy picshures!

Heat and energy, adddendum

Looking back at yesterday’s post, I realize that I never made it to the second point of the post about why articles such as the one quoted might be problematic. While I made a point (that might not be so strong) about methodology, I forgot to point out the broader political implications of these attempts at quantifying economic gains from environmentally friendly policies.

The problem is that of relying too much on economic reasoning in our approach to environmental issues. While it is useful to have backing from economists in insisting that adopting energy efficient measures is a necessity, this can easily backfire. If environmentally minded people come to rely too heavily on economic arguments for going green, what happens when new data come out that show that there is actually a considerable cost to this? It will happen again, as it has been happening for many years. In fact, the economic argument is already often the main barrier to implementing many environment friendly changes, and is a fickle bedfellow.

This has, of course, nothing to do with the actual paper or the authors who wrote it, since it is both useful and of satisfying quality, but it is something to ponder.

Heat and energy cooperation

Wait, what’s that green checkmark doing here? It means I’ve joined Research Blogging, an online community of people blogging about peer-reviewed research. Whenever I write about published (or soon-to-be published) research, one of these icons will accompany the blog post. Also, a reference to the article(s) discussed will appear at the bottom of the page. This will help you as a reader understand when I’m in Serious Mode and have sound backing for my ramblings, and when I’m not. It also means that my posts will be aggregated into their wonderful science blogging page, which by the way is a great place to find other blogs about science related topics, and be part of that growing knowledge database. So cheers for that, and let’s get on with the sciency stuff:

I came over an interesting paper discussing the possibilities of industry and energy companies cooperating to put excess industry heat to use as energy and heat sources: A Swedish integrated pulp and paper mill—Energy optimisation and local heat cooperation. I’m afraid the paper is behind a paywall, so I’ll quote the abstract here:

Heat cooperation between industries and district heating companies is often economically and environmentally beneficial. In this paper, energy cooperation between an integrated Swedish pulp and paper mill and two nearby energy companies was analysed through economic optimisations. The synergies of cooperation were evaluated through optimisations with different system perspectives. Three changes of the energy system and combinations of them were analysed. The changes were process integration, extending biofuel boiler and turbine capacity and connection to a local heat market. The results show that the single most promising system change is extending biofuel and turbine capacity. Process integration within the pulp and papermill would take place through installing evaporation units that yield less excess heat but must in this particular case be combined with extended biofuel combustion capacity in order to be beneficial. Connecting to the local heat market would be beneficial for the pulp and paper mill, while the studied energy company needs to extend its biofuel capacity in order to benefit from the local heat market. Furthermore, the potential of reducing CO2 emissions through the energy cooperation is shown to be extensive; particularly if biofuel and turbine capacity is increased.

The findings are interesting, as they point towards an economically viable way to increase energy efficiency, and thus realize some benefits for society. If this could be implemented large scale, there is probably a lot to be gained in terms of savings of both energy, money and CO2 emissions. The following graph shows the CO2 cuts to be had from implementing cooperation, depending on whether you measure against standard Northern European electricity production (coal) or Swedish (hydro/nuclear):

Three different scenarios measured against two types of electricity production. The middle one is recommended by the authors, being also the cheapest one.

Three different scenarios measured against two types of electricity production. The middle one is recommended by the authors, being also the cheapest one.

Of course, all is not well. This paper suffers from the same ailment as many system modeling approaches, namely in that it assumes that the only thing standing in the way of implementation is lack of will or knowledge. However, as we here at the institute know all too well, the problem is more complex[1]. First of all, there is reason to take the methodology itself with a grain of salt. The authors model both existing and potential costs with “mixed integer linear programming”, which on closer inspection turns out to be a standard procedure for optimization within operations research[2].

Now, there’s nothing wrong with trying to establish best practice through setting up a system of parameters and examining outcomes by manipulating input data. It often forms the basis upon which political and practical discussions can take place. However, I think the method has some limitations which are seldom mentioned in the articles applying it (although I’m sure these reservations exist in the background methods training of most operations researchers). Most importantly, the underlying assumption is that implementation of the changes discussed is simply a matter of deciding on a course of action. The problem with this is of course the frequent intervention of real life. There are a million reasons why leaders of businesses and industry (or politicians, or individuals) regularly shy away from decisions that would benefit their companies, so I won’t go into that right here. To the authors’ credit, they include a paragraph on why changes to the system might not be implemented:

Cooperation between industries and energy companies is not always initiated even though it would be both economically beneficial and resource efficient. Other parameters, such as different business cycles, believed advantages of being independent and historical conflicts are examples of barriers to cooperation.

One might object that the purpose of this particular paper is not to discuss possible barriers to implementation, and One would be entirely correct. That discussion is the one that comes after this paper, and is why this is a valuable contribution to the discussion of how one can reduce energy spending and CO2 emissions, even if all the implications are not included in the paper itself.

[1] Ah, one day I hope to be able to say of a phenomenon: “this is actually not complex at all”.

[2] Although, apparently, the mixed integer approach seems to not be so straight-forward. I assume the authors have taken any computational problems into account when using the method.


Klugman, S., Karlsson, M., & Moshfegh, B. (2009). A Swedish integrated pulp and paper mill—Energy optimisation and local heat cooperation Energy Policy DOI: 10.1016/j.enpol.2008.09.097


The excellent site UbuWeb uploaded its 1000th video up today, and celebrates it with allowing video embedding in a new video player. This is a great opportunity for me to plug the site for all you art interested people[1]. Unfortunately, it seems WordPress only allows certain video formats to be embedded, so you’ll have to do with a link: Please, give it up for Guy Debord’s La Société du spectacle!

Nothing like a little Marxist postmodernism to lighten up your day.

[1] Of course you are!