So you accept that CO₂ from human activities is a major cause of climate change. What are you going to do about it? Buy a hybrid car? Install a PV system? Buy fresh produce with less food miles? Vote for smokeless nuclear power?
But how do you know that your actions and choices are really going to reduce your carbon footprint? Well - doesn’t the hybrid have just half the fuel consumption of a comparable all-petrol car? Don’t the PV panels eliminate your coal-fired electricity consumption? Don’t those low-food-mile vegies reduce transport-to-market fuel? Doesn’t a nuclear power station guarantee clear skies?
Maybe, and maybe not. The fact is we don’t really know. And we need to find out: soon.
Carbon taxes and emissions trading schemes are intended to shift our preferences towards lower carbon use. But we don’t know exactly, or even approximately, whether our new choices do in fact mean we are reducing our carbon use.
The methodology for finding answers to these questions has been known for decades. It is variously known as net energy analysis (NEA) or energy return on energy invested (EROEI).
The problem is that to be useful, the methodology requires data that is tedious – and therefore expensive – to gather and complex to compute. And nobody has ever done it comprehensively, in Australia or anywhere else.
Certainly, some data has been gathered. This is mainly process energy that relates directly to some stage of a product’s development or use, such as the number of megajoules required to smelt a tonne of steel, aluminium or silicon, or to kiln bricks or concrete, or to transport products from A to B.
Craig Jones and colleagues, at the University of Bath, UK, have compiled an inventory of process and embodied carbon and energy (ICE) that is a valuable contribution. So what’s missing?
To be meaningful, the data needs to be a comprehensive account of the energy used along the whole value-chain and the whole life-cycle for each and every good or service we use. By value-chain, we mean all the steps from research and development to design to production. And life-cycle means “cradle to grave” – the acquisition, installation, maintenance, repair, decommissioning and environmentally acceptable disposal of a good.
It gets quite complicated. We don’t just have to count the more-obvious megajoules or kilowatt-hours or litres of fuel at each stage, but also the energy that is involved with each stage. The energy involved directly in smelting iron, aluminium or silicon is fairly obvious, but what about, say, the energy involved in the design of that hybrid car or the energy involved in the exploration for uranium?
It’s not just the electricity to power the lights, computer and air-conditioning in the design lab, but also the energy to make the lights, computer and air-conditioner, the energy to make the laboratory, the car the designer drives to work, her house, food … get the idea?
It’s both tedious to collect and becomes complicated to analyse, apportioning fractions of all these embodied-energy and energy consuming products and actions to each particular output.
To be complete, the straightforward process–energy analysis needs to be replaced by an input/output matrix that can account for all the fractions along the value chain.
This was done fairly comprehensively in the USA about 35 years ago, but was never fully validated then or updated since. It was done around the time of the 1973 OPEC oil crisis and subsequent decreases in fossil fuel costs reduced the enthusiasm for the project – until recently.
If you are surprised by this statement, the comprehensive reference list to the Sydney University’s ISA Consultants 2006 Report and Murphy and Hall shows how little work has been done in recent years.
So, do we have to wait for some yet-to-be-formed group of researchers to go through the usual cycle of applying for grants, conducting research, publishing results and public validation before we can exercise our carbon-related choices with confidence? Maybe not. There may be another way. It’s called the average energy intensity method (AEI).
The AEI method recognises that the “matrix” is complex – indeed, all-pervading – and notes we have already developed a comprehensive system that accounts for all effort along the value-chain. That system is called money! As Murphy and Hall say: “Quite simply, economic production is a work process and work requires energy.”
The above diagram from the US Energy Information Agency is typical. The energy intensity is derived from the GNP divided by the national (or global) energy consumption: dollars per megajoule.
At its simplest, this system implies that (subsidies aside) no matter how we spend a dollar – whether for a good or a service, silicon, steel or uranium – the energy involved (which is at least 90% carbon-based) in spending that dollar is the same.
There are some objections to the AEI methodology. But as Murphy and Hall have shown, it seems to be a pretty robust proxy method, particularly if full life-cycle costing (including subsidies, insurances and environmentally acceptable disposal) are included.
If it is, then the implications are clear:
- If something’s life-cycle cost is more, then it involves more carbon than something that costs less.
- Smokestack-less energy sources – such as solar, wind and nuclear will only reduce carbon use if their life-cycle cost is less than fossil-fueled systems.
- Overall, in the short to medium term, carbon use will not reduce if we spend the dividend from an improved national average energy intensity.
- Nations can improve their AEIs by “off-shoring” production of goods if the value of their tradable services can be maintained. But they shouldn’t then blame China for being a carbon-hog – if its goods are cheaper then they use less carbon than if they were made in the purchasing country.
- There’s no such thing as a (carbon) free lunch.
In the absence of a globally-enforced emissions trading scheme or a global input/output net energy analysis, we are likely to make many wrong choices regarding carbon abatement. No claims to superior carbon-efficiency by any vendors of goods and services are credible while it is possible to shift the carbon use to another part of the value-chain or life-cycle.
In the meantime, a precautionary strategy would be to treat money as a proxy for energy use (which is presently mainly carbon-based) as it seems highly correlated and already globally exchanged. This correlation, incidentally, makes a strong case for China floating its currency.