Post-disaster repairs II: the case of repurposing ex-industrial landscapes in the UK

What is so special about humanitarian bureaucracy anyway? Haven't plenty of people in all sorts of different organisations come up with a great idea that nobody wants to pay for? Sure enough, the post-disaster repair problem has two juicy elements that should be of interest to any avid idealist: the challenge of selling resilience and the challenge of putting into practice what we claim to know and believe to be reasonable. This post is about what I learnt about this problem by doing something completely different: turns out it is just as hard in other sectors as it is for…well… most individual human beans.

When I left the humanitarian sector in mid-2011, I’d been going back and forth to Haiti watching the international humanitarian response unfold for 18 months. At first all I could see at home was complacency and naïve, suburban incredulity about rising food and energy prices. This seemed ridiculous: the apocalypse was obviously on its way and I had already watched it, like TV, through the windows of a 4-by-4 in Port-au-Prince. The era of affordable stuff was surely over. High time to get reacquainted with my country, do something to stave off the energy crisis and stop being the outsider speaking a different language. So, it was with this sense of impending doom and ambivalence about my fellow Britishers that I joined the Quarry Battery Company, a start-up in the UK energy sector.

The business idea was to retrofit disused quarries with an electricity storage technology – basically creating giant batteries that would give the electricity network a type of resilience: a way to buffer the volatility of electricity from wind and the inflexibility of electricity from nuclear power. And so it came to pass that I was working in Essex on an engineering project planned for Glyn Rhonwy, a cascade of former slate mine in Gwynedd – whose abandonment in the 1930s precipitated disastrous economic decline for north Wales where – yes, you’ve guessed it – again I was an English-speaking foreigner…

To set the scene, there are 3 electricity markets that traders access in the UK – one for buying long in advance, one for buying a bit ahead of time and one that operates at the last minute when you have to pull out all the stops to supply a surge in demand. Each of these markets commands different prices (like train tickets, electricity can be extortionate if you buy it at the last minute) and each is driven by different fundamentals and this means that the players in each market do different things. Roughly speaking, prices in the first market track wind speeds, not just in the UK but across Europe. Prices in the second market track how well we can predict wind speeds. But prices in the third market – potentially the highest prices – are driven by something totally different: something more like a game of poker between a few players – and I am not talking about the random luck-of-the-draw aspects of poker but the poker-faced gaming bit. This is about guessing what others will do and strategizing on the basis of some hypothetical outcomes and trade-offs.

I should add that the operations team (of 4! Dave H, Chris W, Sarah N and me) was composed entirely of scientists, engineers and geologists so, for us, this deliberative, gaming aspect of the modelling was bewildering, subjective, irrational and more difficult to sell! But guess what. We were meeting banks, private equity companies, angel investors and high net worth individuals (AKA rich people) and by and large they had the same poker approach.

• Firstly, no investor was interested just because it was a good idea. They were interested only if, for any given risk, it would make money faster or make more money than any other ideas on the table. So, we had to work out how much money the business would make over a 20 year period. This involved running these elaborate simulated scenarios that modelled wind speeds, electricity markets and growth and we ended up with what we thought was pretty convincing evidence for profit.
• BUT, it was not the evidence that convinced our investors it was conviction! We didn’t need a business model so much as a business case. What they really wanted were not just the numbers and the simulations but confidence in our competence, confidence in the stories we were telling them and corroboration from their peers, advisors and the press. If the Financial Times ran a story about battery technology, they were totally sold that day.
• AND THEN, we noticed a difference between our investor-decision-makers. One of these high net worth individuals was a bit more vocal. It turned out that he was different because he was not as rich. He understood that the investment was risky – in that the scheme might not make money – but also that this was a genuine risk to him. If it did not turn a profit, he would not just have to write off his money, he would lose his family home. This is the difference between taking a risky decision and taking a personal risk. There was another risk too. And this was a big part of the team’s motivation as entrepreneurs: the risk to the environment, the economy and our society that the electricity network would not be changed.

Many of these issues come up in the humanitarian shelter sector and in the repair dilemmas. We are often asking ourselves: do we have evidence; would we use it if we did; what does it look like; are we talking about corporate risk, my personal risk as a professional or, actually, is it your risk – you - the person who has to live with it?

And, if we are thinking about reducing risk: what about other risks?

What about the risk of doing nothing? What is the risk to electricity generators, suppliers or consumers of not adding any batteries to our electricity network? How much does it cost and who pays? What about the risk to our profit and to investors if gas prices plummet or soar? Or, after a disaster, if risk reduction focuses only on seismic risk, what about the risks of hunger, eviction or hurricanes?

And what about risk in the aggregate? Why build one big battery when you could just rely on people buying their own personal batteries to do the same job? Who wins and who loses if you stop sharing and spreading the risk? Or, in the shelter sector, if you use resources to build 10 new, perfect houses instead of repairing 100 damaged ones, what is the reduction of risk in the aggregate? What if it turns out those houses that could have been repaired were inhabited by the worst off? With expensive, imported timber-frame shelters, are we doing “heart surgery” when what is needed is the shelter equivalent of oral rehydration salts?

Confusing ain’t it….

Critical techno-policy in Japan

When we use the word 'critical' in engineering we usually mean thresholds not theories. Neat boundaries rather than full-on discourse analysis. And I, for one, am all for these clear thresholds because they mean we can get on and DO stuff. This post is about one such line in the sand, now etched into 500km of Japan's coastline. It’s a brief reflection on decision-making and tsunami risk from my experience with the EEFIT mission to Japan in June. The general questions it raises fall into what I want to call the 'techno-political domain'. This is the term Austin Zeiderman uses when he talks about risk as 'a technique for governing the future of cities and urban life' and it’s helpful here. I’ll start with the decision and its consequences and then work back through the evidence. Decisions Japan has three levels of government: national, prefectural and municipal. The national government made a decision that future protection from tsunamis along the coastal stretch hit by the 2011 event should be based on two levels of risk: Level 1 based on a 1 in 100 year event and Level 2 based on a 1 in 1000 year event. This doesn't mean that a Level 1 tsunami will definitely, regularly or only happen once in a hundred years. It means that there is theoretically a 1% chance that a tsunami worse than Level 1 could happen in any given year. (Or a 0.1% chance for a tsunami worse than Level 2).

Consequences in Practice Once this threshold was set at a national level, the prefectural authorities modelled and mapped the zones that would be inundated by Level 1 and Level 2 tsunamis. Consultants were engaged to run numerical simulations based on a standardised tsunami model, sea walls were designed to resist a Level 1 event and any coastal strip between the height of the sea wall and the run-up (the line reached by the tsunami on land) of a Level 2 tsunami (less 2 metres) was demarcated as a zone where building would be prohibited. Responsibility for protecting different stretches of coast and nearby infrastructure was already clearly divided between a number of national ministries and the prefectures, so the (PHENOMENAL) clean-up operation and construction of sea defences began, while the municipal authorities were handed the risk map to use as the basis of their urban planning.

The only glitch seems to be that not everyone wanted massive sea walls: many of the coastal communities rely on fishing or tourism, both of which would be decimated by the new infrastructure. But if local people, backed or not by their municipalities, dug their heels in, the flow of national funds and the reconstruction would grind to a halt... One settlement did have some success calling on the prefecture to re-run the simulation without the protective wall but, if your town is the only section of the coast without a wall (which is what was seems to have been modelled), the tsunami is funnelled through a little gap and the simulated run-up is even worse! So, there was no opting out.

Evidence But what was the evidence base for the decision on risk? There is archaeological and historical evidence about tsunami inundation; plenty of data on earthquakes and models explaining their mechanisms and potential for generating tsunamis in Japan and elsewhere; damage assessments from various geo-hazards in Japan; and detailed survey data mapping the sea floor and land heights. This all fed into the tsunami simulations - the technical bit of the ‘techno-political domain’.

From our brief, translated conversations with coastal dwellers, what seemed to be missing was any way of discussing at a local level:

• the uncertainties inherent in the models;
• the other risks faced by remote communities where people - including the ever increasing proportion of elderly residents - had ways of escaping tsunamis but not their dependence on an economy based on one or two capricious or precarious activities; and
• the fundamental reasons for drawing the lines based on convenient, but apparently arbitrary, round numbers like 100 and 1000... This is the political bit of the ‘techno-political domain’.

Building codes everywhere develop incrementally, as they are reviewed by officials, experts and interest groups with varying degrees of transparency and clarity. What is amazing is how many technical people seem to accept these numbers as sacrosanct once they are written: the history of the negotiations forgotten or unclear. Perhaps that’s for the best: maverick, free-style engineers throwing caution and thresholds to the wind might be a very bad thing. But what role should engineers play getting from risk information to risk-informed policy decisions? Would it help us to communicate evidence and listen to people – the householders who have to live with the risks – if we remembered that thresholds for acceptable risks are based on deliberation not calculation?

Why should we care? Because all around us, these thresholds of risk are being defined on our behalf, from public health to energy policy to mortgage lending. They shape where money goes. They affect the evolution of our cities and the way we live: our homes, our jobs, our families and our infrastructure. But it's hard to know how these thresholds will affect us, where they've come from and how we can engage in changing them. And that’s in the countries where we live and vote...

Many thanks to our generous and insightful hosts for allowing us an incredible glimpse of Japan.