Over at Dot Earth Robert Bertollini of the World Health Organization (WHO) asserts that the discussion about the Global Humanitarian Forum’s report has missed what matters most:
It is also a bit misleading that the ensuing debate over the GHF report has been portrayed as an argument over disaster statistics. In fact 95% of their headline figure is estimated to be from gradual effects on existing endemic health problems – malaria, diarrhoea and malnutrition. Arguments over attribution of disaster impacts clearly miss the main point.
I focused my critique on the disaster impacts because it seems common wisdom that the attribution of malaria, diarrhea and malnutrition deaths to greenhouse gas emissions needs no further critique. I was wrong about the common wisdom.
The attribution of health impacts to greenhouse gas emissions relies on work done by the WHO. Here is how the WHO describes its own analyses:
In 2002 the WHO explained (at p. 26 in this PDF):
Climate exhibits natural variability, and its effects on health are mediated by many other determinants. There are currently insufficient high-quality, long-term data on climate-sensitive diseases to provide a direct measurement of the health impact of anthropogenic climate change, particularly in the most vulnerable populations. Quantitative modelling is therefore the only practical route for estimating the health impacts of climate change.
And by quantitative modeling, they mean a model with assumptions included for the effects of GHG-driven climate change. To be clear, these assumptions are not based on observations or measurements. What they are based on I do not know, but we do know that it is not the actual data record of deaths and their correlates. As WHO admits, the magnitude of the effects is not determined directly or empirically.
In 2003 McMichael et al. published a chapter for WHO surveying this topic in which they admitted that they were engaged in what might be generously called speculative work (here in PDF):
Empirical observation of the health consequences of long-term climate change, followed by formulation, testing and then modification of hypotheses would therefore require long timeseries (probably several decades) of careful monitoring. While this process may accord with the canons of empirical science, it would not provide the timely information needed to inform current policy decisions on GHG emission abatement, so as to offset possible health consequences in the future.
In other words, the policy process needs numbers and cannot afford to follow the “canons of empirical science.” So full speed ahead.
The 2002 WHO report concluded that:
[GHG-driven] Climate change was estimated to be responsible in 2000 for approximately 2.4% of worldwide diarrhoea, 6% of malaria in some middle income countries and 7% of dengue fever in some industrialized countries.
For the exact same diseases the GHF report issued last week assumes that greenhouse gas emissions are responsible for the following proportions of deaths (in 2010, from p. 90):
Diarrhea 4-5%
Malaria 4%
Dengue fever 4-5%
[UPDATE: In the comments, eagle-eyed Mark Bahner observes that the absolute numbers of deaths in the GHF report are exactly twice the number from the 2003 WHO report. Why? Mark hypothesizes that the GHF applied the Munich Re disaster "adjustment" to the health effects losses. If so, then wow. But when you are non-empirical, I guess you can do that sort of thing.]
Should we conclude that the effect of greenhouse gas emissions on malaria deaths has decreased by 33% from 2000 to 2010 (from 6% to 4%, and apparently has spread from some middle income countries)? Or that the effects of greenhouse gas emissions on diarrhea deaths have increased by more than 100% in only 10 years?
More pointedly, how would anyone counter a claim from a critic who says that the actual number is zero? Or even that greenhouse gas emissions have led to a net reduction in deaths?
The answer is that you can’t counter these claims because there is no data on which to adjudicate them. We can rely on hunches, feelings, divine inspiration, goat entrails, or whatever, but you cannot appeal to the actual data record to differentiate these claims. So when people argue about them they are instead arguing about feelings and wishes, which does not make for a good basis for science.
And that is the problem with non-empirical science. It is not science. It might charitably be called educated guesswork or less charitably by a few other terms.
So is it possible that greenhouse gas emissions have already led to an increase in deaths? Sure. It is also possible that greenhouse gas emissions have led to a decrease in deaths or no effect at all.
How will we know the difference? For that we’ll need some empirical science.