I started out with three assumptions:
> Climate change is a big deal.
> It is caused by humans.
> We can do something about it.
This book isn’t really about those assumptions, but this section is for anyone who is still unsure. The human capacity for collective denial is an amazing phenomenon to watch. If that is where you are right now, I’m not too hopeful that I can shift you.
Is climate change a big deal and caused by humans?
At the end of the day we all have to make up our own minds. I can’t go over the scientific arguments in detail here, and even if I did I’d just be one more voice for you to sift through. But I will briefly go through how I came to make up my mind.
None of us really knows for sure what climate change is going to mean for us in the coming decades. The science is hideously complex and uncertain. The media still report a full spectrum of arguments. It’s a confusing picture for the layperson. What basis can we have for knowing whether a news article, a TV program, or a book is credible?
A key question in this context is how can we work out whom to trust? I meet plenty of people who have understandably given up trusting anyone over climate change. But it is possible to do a lot better than that. This is how I make up my own mind about a report or a piece of research:
1. I look at the argument itself and see if the logic makes sense at face value.
2. I look at the competence of the source.
3. I look at the resources and information that it had at its disposal.
4. Critically, I try to understand the motivations—political, financial, and psychological. How strong was the dedication to truth? Who funded the research, and what did those funders want? Who wanted what from their careers, and what influence might this have had? What was the psychological readiness of the source to accept and report on different findings that might emerge?
These are the questions I have been asking about skeptics’ arguments. They can sometimes pass the first test, but every single one of them fails at least one of the final three.
A few years back, just before I reoriented my working life toward addressing climate change, I thought I’d better double-check that the whole thing wasn’t a storm in a teacup. I didn’t want to go to a whole lot of trouble for nothing. I knew my family was going to have to put up with my hardly earning anything for a year or two while I learned a new trade.
A good friend of mine had raved about Bjørn Lomborg’s book The Skeptical Environmentalist. “Mike,” he said, “I’ve read this book and it’s rearranged my thinking.” It’s a thick and persuasively written tome with some 2,000 academic references. It makes the claim that we can all afford to chill out about climate change and we would do better to invest the money elsewhere. Lomborg further asserts that the climate change worriers are psychologically wedded to a doom-and-gloom position on life. To me, that last point hit a nerve. It was an important challenge to address. I thought, “Perhaps he’s right! Maybe I should ask myself if this applies to me?” I didn’t want the experience of realizing in years to come that the only reason I’ve done all this stuff about climate change is because of some unhealthy personal hang-up. At the very least I felt that the mainstream scientific community should have a blisteringly clear response to Lomborg, and it was disquieting that I couldn’t readily find one.
I sat down to spend about a week with Lomborg’s work. I picked into some of his arguments in detail and before long found that even from my distant position I could see several clear misrepresentations of science. Then I found that his book had never been appropriately peer-reviewed. Then I started uncovering websites that detailed his errors literally in their hundreds, along with roasting dismissals of his arguments from scientists, statisticians, and economists alike. After that I started to read about Lomborg’s close shaves with the Danish Commission for Scientific Dishonesty. In the end it was abundantly clear to me that the whole thing was a sham.1 I came to a clear view, but it took detailed consideration of his work—far more than can be expected of the average person on the street.
Lomborg passed the first and third of my tests but failed the second and fourth. To this day Lomborg carries on and has a following. It is incredibly unhelpful for the world. I don’t know any scientists who have any time for his position at all, although some commentators treat his work with unwarranted respect in the misguided name of “balance” or perhaps just to be polite.
In the name of open-mindedness I’ve looked in detail at several other “skeptics” and had a similar experience.2
So much for the skeptics. Let’s look at the mainstream scientific community. The UN’s Intergovernmental Panel on Climate Change consists of around 2,500 scientists. The skeptics point out that there may be potential for group-think and mass hysteria. These are warnings that should be taken seriously. Furthermore, there have been occasional errors in the IPCC’s work, and even the hint of the odd deliberate misrepresentation. However, the standard of integrity that is demanded of the climate change believers is on a different plane altogether from that demanded of the skeptics. Some scientists at the University of East Anglia have been in world in headline-hitting trouble for allegedly “sexing up” their work in a way that the some of the skeptics would consider quite normal. The resulting scandal, which turned out to be about not all that much, has been hugely damaging to popular understanding of climate science.
It’s worth bearing in mind that it would also be possible to criticize the IPCC for its caution. Does it offer a sufficient platform for the airing of discomfort about poorly understood scientific risks? Does the level of deliberation and the need for consensus among such a wide community, some members of which have clearly been under political pressure to play things down, result in an undercooked estimation of the risks? We can’t know for sure. We do know that the extent of scientific consensus is almost unanimous in affirming the first two of my assumptions.
Finally I want to note a trend that I have also picked up on among the people I know. The more scientifically minded they are and the more they have thought about the issues, the more worried they tend to be that even though we might almost all be fine, it is also just as likely that we’ll end up frying in our billions. I talk to a lot of academics, mainly physical scientists and social scientists. In the last few weeks I’ve started conducting my own informal opinion poll by asking any senior academic that I meet to estimate the percentage of people in their department who think that “climate change is a big deal and is caused by humans.” So far I have yet to have anyone give me a figure under 99 percent. It is an amazing phenomenon that people within the academic community, those with the most realistic and mature understanding of how the academic process works and of how scientific knowledge evolves, are so clear about my first two assumptions while the wider public remains so obstinately doubtful.
Can we do something about it?
People ask me sometimes why they should bother when, even if everyone in their country cut the carbon, it would make such a small impact on world emissions. Sometimes I hear businesspeople trying out the argument that their hands are tied until governments act or until their end consumers care more. Governments say they can’t move ahead of popular opinion. I hear Chinese people saying that the developed world started it and is more carbon hungry, so they should start the cuts, whereas in the U.K. I hear people saying we’re just a pinprick in comparison with the U.S. or the emerging Chinese middle classes.
The UN climate negotiations in Copenhagen and elsewhere have surely taught us that it isn’t enough to hope that world leaders will sort things out on their own. So the question is, Where does leadership come from? My answer is that it can come from anywhere, and we need it to come from everywhere at once. If the Chinese middle class wants a Western lifestyle, then Western lifestyles had better become lower carbon. Who can start that off? Anyone can. Anyone who finds a way of enjoying life more for less carbon is setting a standard for others. Anyone who chooses a lower-carbon food is helping the supermarkets to emphasize that product. Any supermarket that improves and promotes its lower-carbon range is helping its customers to enjoy low-carbon food. All of this helps the political parties to move into a low-carbon position.
If you can find a way of being happier but with a smaller footprint, you are a leader.
The cost efficiency of selected carbon-saving options
The list I give below isn’t complete, but I have included it to illustrate that it is essential to pick our battles. Taking the U.K. as an example, some of the least cost-effective options on this list are receiving major government funding, while some of the best-looking options haven’t yet had serious attention. There could be other well-founded reasons for this, but they aren’t yet obvious to me.
It can be frustrating to see public money wasted on red herrings, apparently because the analysis simply hasn’t been done. Quantified carbon and cost analysis may not be the whole story, but it is an essential part of it.
All the figures below are net costs or profits over the lifetime of the measure. They are based on a financial discount rate of 10 percent (see Photovoltaic panels). In other words, if you are promised a savings of $1,000 but have to wait a year for it, I’ve only called it $900. If you have to wait 2 years, I’ve called it $810, and so on.
> Putting 270 mm (10-inch) attic insulation in homes that haven’t got any
$105 net profit per ton saved. $2.80 for every $1 invested.
> Investing in offshore and onshore wind farms
Just above zero. Payback in 15 years (would be 8 years if we ignore discount rates). Lifetimes of the farms vary.
> Slowing down from 70 miles per hour to 60 miles per hour on the highway
Variable, but typically cost neutral even when the value of the driver’s time is included. No investment costs (see Driving 1 mile).
> Pay farmers to keep their forests via the Amazon Fund or similar
$4.5 per ton, plus biodiversity benefits (see Deforestation).
> Funding family planning in the developing world
$6 per ton according to the Optimum Population Trust (see Having a child).
> Upgrading attic insulation to 270 mm (10 inches) where 50 mm (2 inches) currently exists
$7.5 per ton. This figure is the total cost, which is shared between government and homeowner.
> U.K. government investing 24p (36 cents) per unit to a feed-in tariff for micro wind turbines
£250 ($375) per ton saved, assuming that this replaces electricity from coal, and ignoring the embodied energy in the panels themselves (see Wind turbine).
> U.K. government investing 36.5p (55 cents) per unit to a feed-in tariff for micro-photovoltaic panels
£360 ($540) per ton saved, assuming that this replaces electricity from coal, and ignoring the embodied energy in the panels themselves (see Solar panel).
> Building to U.K. code for sustainable homes level 6 (carbon neutral) instead of to current U.K. building regulations
Almost certainly very expensive (see A house).
I hope I have already made the point clearly enough that carbon footprinting is a long way from being an exact process, whatever anyone ever tells you or whatever numbers you might see written on the side of products in some stores. All my numbers are best estimates and nothing more, even though I have reached them as carefully as I can.
I have tried to be as transparent as I can within the practical constraints of the book and my resources. Occasionally the sources are confidential to clients of mine, but more often it is simply too laborious to document every last detail. Nevertheless, there is a reasonable degree of transparency most of the time, and here is a summary of my approach.
I have used a variety of different methods and sources. I have drawn on a range of publicly available data sets and models, from life-cycle studies and reports, and from studies I have carried out myself for businesses across different industries. I have used models that we are developing all the time in my company, Small World Consulting.
Often I’ve arrived at numbers from a couple of different routes to check that the results agree with each other. I’ve tried to put notes and references in the text wherever possible. Occasionally, frankly, it has been more a case of putting my finger in the air and guessing, but when that has been the case I’ve tried to make it clear.
Here are some of the main sources I have used.
Publicly available data sets drawn from process life-cycle analyses
Process-based life-cycle analysis is the most common approach to carbon footprinting. It is often referred to as “bottom-up” because you start off down on your hands and knees, identifying one by one all the processes that have had to happen in order for, say, a product to be created. Then you add up the emissions from each process, and that’s the footprint of the product. Simple! Except that it isn’t. Not at all. It’s back-breaking work, and since the number of processes you really need to count up is always infinite, the job is never quite complete, so you end up with an underestimate. In fact the leaks are often shocking, 50 percent or more. To make matters worse, these problems are popularly overlooked, even in the development of U.K. government–backed and –funded guidelines, such as the PAS 2050 standard (which was published despite a government-commissioned study that concluded that the draft methodology wasn’t fit for some of its key intended purposes3).
For all the problems, and despite being hard work, process life-cycle analysis is still an essential source of detailed information that can’t be gathered any other way. Here are some of the key sources of this type that I’ve used, each of which is referenced in the main text:
> The U.K. government’s Department for Environment, Food and Rural Affairs (Defra) publishes emissions factors for a range of fuels, electricity sources, transport modes, utilities, and waste. These are mostly U.K. specific and don’t take account of full supply chains. I use them where I can but supplement with additions for the missing supply chains. The carbon intensity of electricity in the United States varies from state to state, but it averages out to about 10 percent higher than the U.K. figure, so I have applied that adjustment to all electricity calculations that were originally carried out for the U.K. In Canada the electricity mix is considerably less reliant on fossil fuels than in the U.K. or the U.S., but both for simplicity and because the U.S. and Canada grids are linked, it is spurious to think that turning a light bulb on in Canada has a lower impact than doing so in the United States.
> The University of Bath produces the Inventory of Carbon and Energy, a publicly available data set of carbon emissions factors for hundreds of materials, mainly relating to the construction industry, up to the factory gate.
> The Association of European Plastics Manufacturers (APME) publishes data sets of emissions factors for a wide range of plastics based, not surprisingly, on European manufacture.
> The U.K.’s Market Transformation Programme has a wide range of data on the carbon intensity of common appliances.
> I have drawn on a further wide range of life-cycle analysis studies from all kinds of sources. This is tricky because they all draw their boundaries in slightly different ways and use slightly different assumptions. At its best this has involved me in picking through high-quality academic studies. At its worst it has degenerated into “Google footprinting”: scrounging around the web, digging for numbers. When I’ve sunk to these depths, I’ve let you know.
Environmental input–output analysis
This is a neat alternative and complement to process life-cycle analysis. It’s not as popular, perhaps because it’s a bit harder to get your head around, but it’s at least as robust as anything else in the murky world of carbon footprinting. It is sometimes called a “top-down” approach because it starts by looking at the whole economy from a height. It uses macroeconomic modeling to understand the way in which the activities of one industry trigger activities and emissions in every other industry. Input–output’s key “trick” is a piece of funky math (for which a man called Wassily Leontief got a Nobel Prize) that succeeds in the capturing the endless ripple effects in a way that is 100 percent complete. It has the further advantage that if you know how much you spend on something, you can get an instant crude estimate of its carbon footprint. It’s like a magic trick. And just like all the best magic it is also a bit too good to be true: the downside of input–output analysis is that the results can be ridiculously generic.
Input–output analysis is powerful tool both because it doesn’t “leak” and because once the model has been built, it is often easy to use. The basic technique is well established. The specific model I’ve used is one we developed at Small World Consulting with Lancaster University. It draws mainly on data from the U.K.’s Office of National Statistics. Our model is based on a 2007 picture of the U.K. economy; it deals with all the greenhouse gases and employs an emissions weighting factor for high-altitude emissions. The model relies on the key assumption that North American industry has similar carbon intensity per unit of physical output as U.K. industry. This seems reasonable most of the time. A further weakness, which I refer to from time to time and sometimes adjust for, is that it treats imports as though they had the same carbon intensity as domestic production, whereas in reality they are usually more carbon intensive.
Most of the time I have used a combination of process-based and input–output approaches to get my numbers. At their best, process-based methods can be more precise, but input–output analysis is often able to get at places that process life-cycle analysis is unable to reach. Putting the two methods together is sometimes called a hybrid approach, and the result is a bit like looking through both a microscope and a telescope at the same time. They each show you different things, and between them, if the lenses are clean, you might end up with a passable understanding of whatever it is you are looking at.
Booths supermarkets’ greenhouse gas footprint model
Over the last three years my company has been mapping out the carbon footprint of the Booths group of U.K. supermarkets and its supply chains. The model we now have draws on a great many life-cycle studies of foods up to the farm gate, often using those funded by Defra. Reports and agricultural models from Cranfield University deserve a mention because I’ve used them extensively even though they are not uncontentious. Also well worth a mention are five reports produced by the Food Climate Research Network. The Booths model includes transport, processing, packaging refrigeration, and the supermarket chain’s other operations. All of these components are attributed to products, broken down into 75 categories. The model goes into a lot of detail, but that doesn’t make it accurate. Human understanding of emissions from agriculture is still poor. The model is simply the best picture we have managed to achieve so far. Its purpose is purely practical, and we think it is now good enough to work from, enabling actions to be reasonably well targeted on the hotspots. It is, I think, the most comprehensive model of the climate impacts of supermarket food in the public domain.
Direct greenhouse gas (GHG) emissions per GDP and per person for 60 countries
Note that these figures do not take account of embodied emissions of imported or exported products, or of international transport. They are simply estimates of the emissions that actually arise from each country.
SOURCE: derived from factsheets within Höhne, N., D. Phylipsen, and S. Moltmann (2007) Factors Underpinning Future Action: 2007 Update. A report by Ecofys for the Department for Environment, Food and Rural Affairs. Ecofys GmbH, Cologne. Available at www.fiacc.net/data/fufa2.pdf.