“For the simplicity on this side of complexity, I wouldn’t give you a fig. But for the simplicity on the other side of complexity, for that I would give you anything I have.”
- Supreme Court Justice, Oliver Wendell Homes
It has been noted that one of the key hidden drivers underlying the climate and biodiversity crisis, indeed one of the key underlying drivers of all of mankind’s greatest problems, is our inability to deal with the increasing complexity of the world.
Climate change’s paradigmatic effect on just about every aspect of human life, and the many indirect pathways between causes and effects requires complex cognition to process and understand, and climate change awareness has a positive correlation with intelligence, even after controlling for socio-economic factors.
And yet Commons’ model of hierarchical complexity estimates that only 20% of the adult human population have systematic cognition or above – i.e. the ability to coordinate multiple formal rules and see how they form a system. If true, this means that fully 80% of the human population are unable, without help, to recognise or identify even the most simple feedback loops. Perhaps this goes some way to explaining why we find such general levels of apathy and misunderstanding about climate change, and a widespread inability to see how even 1.5% of warming will tear apart societies and result in the deaths of millions of people.
What is perhaps more worrying is that even for those who have grasped the severity of the problem, many of the well-intentioned green solutions proposed and enacted have been produced by the same level of thinking which got us into the problem in the first place. i.e. they fail to take into account the complexity of the problem and therefore result in counter-productive unintended consequences, wasting valuable time and resources in the process.
A classic example of this was a 2001 policy from the UK’s Labour Party who introduced a new system of car tax aimed at incentivising the use of lower emissions vehicles. In practice, the policy resulted in millions of people switching from petrol to diesel cars on the basis that diesel cars emit slightly less CO2 per km driven. However, this failed to take into account the fact that they produce far higher levels of other harmful pollutants such as NO2, resulting in significantly worse local air pollution. The resulting fall in air quality in UK cities has, according to some experts, been associated with thousands of premature deaths per year, eventually prompting a reversal in the policy and the banning of diesel cars in many urban areas. How many cars were prematurely scrapped on both sides of this merry-go round, and the emissions involved in producing and shipping all these new vehicles seems to have been left out of the analysis.
This is a classic example of insufficiently complex thinking in tackling a complex problem. Given how complex value chains have become, climate literacy requires us to look at multiple metrics across full value chain as well as intersecting value chains, particularly when legislating at the national level. The policy seems to have relied on one metric - CO2 per km - while remaining utterly blind to any other factors at play or the ways in which these factors interrelate.
We simply don’t have the time, or resources, for any more false moves. We urgently need to increase our ability to model and understand complex systems when designing and implementing climate solutions.
One way we can do this is by adopting a more sophisticated approach to weighing up the costs and benefits of a given “green” solution. If you’re a policy maker, an entrepreneur, or just a concerned and committed individual – welcome to TOADS, five hidden climate costs which often get missed in mainstream value chain analysis. The five TOADS costs are:
⁃ Does the green solution rely on a future act of rectification or re-balancing? If so, it may fail on the basis that a sin committed today can not be offset tomorrow. Because of the non-linear and accelerating nature of climate breakdown, the impacts from a day of global warming resulting from a greenhouse gas emission today can never be accounted for by a tonne of greenhouse gas sequestered tomorrow.
⁃ Does the green solution accelerate or bring forward in time climatic or environmental stressors? The impacts of extraction, production and consumption today are greater than the impact they would have tomorrow. The later we push back these impacts, the better. This is not an invitation to discuss economies of scale but a reminder that climate stressors compound and cascade and planetary boundaries have thresholds and tipping points.
⁃ Is the green solution iterative such that over time, with increasing investment, the technology will evolve to become more resource-efficient in a way that might justify inefficiencies and impacts in earlier iterations? Prove it.
Is the green solution the best place to use finite resources? Green solutions all rely on and compete for finite resources, whether they be mineral, materials, water, space or air. Not to mention financial capital and increasingly, consumer attention and sentiment. If our planet only has the resources to produce X number of batteries or solar panels (for example) but we have demand (now or over time) for a multiple of X, then where (and when…) should we “spend” these resources?
Is this green solution really “greener” than existing solutions designed to satisfy the same consumer need or want? I.e. what would a consumer buy (if anything…) in the absence of the green solution? Is the Green Solution truly “greener” than the alternative? Prove it.
If the green solution replaces and results in the disposal of an existing product, what is the environmental or climate impact resulting from such disposal, and its replacement?
How does a particular green solution (including all aspects of its value chain and the development of new infrastructure) compare to an existing technology when you account for the sunk costs (environmental impact, damage and stressors) already incurred in respect of the old technology?
One example which illuminates the needs for TOADS analysis are electric scooters and bicycles. Electric scooters and bicycles have been popping up on streets in cities all over the world over the past few years. The green logic is fairly straightforward - traveling by electric scooter is more sustainable than traveling by car so if you make them accessible and cheap then people will drive less.
But a TOADS analysis reveals that the truth is not nearly as simple. For example, how many people are really replacing car or taxi rides with scooter rides, and how many are simply taking the scooter instead of walking? If some people truly are getting rid of their cars to use scooters then what’s the time interval between starting to use the scooters and the point at which I sell my car? How much revenue and investment are scooters diverting from public transport, and how would that money have been invested? What’s the environmental cost of producing and managing all these scooters and how does that compare to (already built) public transportation alternatives? Would the rare earth materials used to build all those batteries have been better used on something else e.g. local energy production and storage?
None of this is meant to deter climate action. No doubt electric scooters and bicycles do have a place in the sustainable future that we all want. But a good deal more thought and consideration would be welcome before surging ahead with solutions which have complex effects on biological, social and economic systems.
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