Are Some Global Warming Policies Deadlier than Global Warming?

Partly to reduce the perceived impacts of global warming, which are expected to strike developing nations the hardest, the United States and the European Union are subsidizing and mandating production and use of biofuels in order to displace fossil fuels (Jordan et al., 2007; Searchinger et al.,2008; Robertson et al., 2008; Tyner, 2008). However, these policies have been questioned on the grounds whether (a) biofuels actually reduce net energy consumption from non-renewable sources (Patzek and Pimentel, 2005a, 2005b; Wang, 2005; Wesseler, 2007;) and net greenhouse gas emissions (Searchinger et al., 2008; Scharlemann and Laurance, 2008; Fargione et al., 2008; Hertel et al., 2020) and (b) their environmental consequences for land, water, and wildlife resources are positive (Robertson et al., 2008; Scharlemann and Laurance, 2008; Service, 2009; Fargione et al., 2009). In addition, several analyses indicate that increased production of biofuels has contributed to higher food prices, which, in turn, has increased hunger and poverty in developing countries (Pimentel and Patzek, 2006; FAO, 2008, 2009; Godfray et al., 2010; De Hoyos and Medvedev, 2009; World Bank, 2009). Since hunger and poverty are major contributors to death and disease around the world (WHO, 2002, 2009), Goklany (2011) argues that the artificially induced increase in biofuel demand would add to the global burden of death and disease. He then sets out to estimate order-of-magnitude increases in death and disease due to increased biofuel production.

Methodology
The methodology used by Goklany (2011) is as follows:
1. Obtain estimates of the increase in the current headcount for absolute poverty in the developing world due to increased biofuel production.
2. Develop the relationships (or "coefficients of proportionality") between the poverty headcount on the one hand, and the global burden of death and disease attributable to "diseases of poverty" on the other hand. The headcount and the burdens of death and disease should be for the same time period.
3. Apply the coefficients developed in step 2 to the increase in poverty from step 1 to estimate the increases in death and disease from the increase in biofuel production.

Step 1. Based on a search of the existing literature, Goklany identified only two studies-De Hoyos and Medvedev (2009) and Cororaton et al. (2010)-that provided estimates of increases in poverty induced by greater biofuel production in both rural and urban populations for a large segment of the developing world's population, while also accounting for adjustments by consumers, producers, economies and governments to reduce hunger and poverty. Both analyses covered 90% of the developing world's population. Both indicate that higher biofuel production increases global poverty, even after first order adjustments have been made.

Both studies used the same suite of World Bank models to estimate the effects of additional biofuel production on the poverty headcount. Both estimated the increases in poverty headcounts as the difference in poverty levels between pairs of scenarios, with one scenario assuming a higher level of biofuel production and the other being a baseline scenario with a lower biofuel production level.

Cororaton et al.'s baseline scenario assumed growth in global biofuel production from 2004 through 2020. Thus, they underestimate the contribution of total biofuel production to the poverty headcount. De Hoyos and Medvedev's baseline scenario assumed that biofuel production at the actual 2004 level. They calculated the increase in poverty over the baseline scenario for a scenario in which biofuel production increased after 2004 along its historical path through 2007, and then increased further through 2010 in response to then-existing biofuel mandates and production trends. Therefore, this latter study should give a more accurate estimate of the increase in poverty due to biofuel subsidies and mandates, although it too would be an underestimate since it assumes 2004 production levels as part of the baseline. Despite the latter shortcoming, Goklany used the De Hoyos and Medvedev estimate, after adjusting it upward to account for the incomplete coverage of the world's population. Based on this, Goklany estimated that the poverty headcount increased by 36 million people in 2010 due to an increase in biofuel production over the 2004 level.

Step 2. In order to estimate the coefficients of proportionality between the poverty headcount, and death and disease in developing countries due to poverty-dominated diseases, Goklany used estimates of (a) cumulative burden of deaths and disease from poverty-dominated health risks from the World Health Organization (2009) analysis of global health risks for 2004, and (b) the World Bank's poverty headcount for that year (Chen and Ravallion, 2007) adjusted to be consistent with the more recent World Bank (2009) data and estimation methodology (Chen and Ravallion, 2008).

In order to identify diseases of poverty, Goklany calculated for each risk factor, the ratio of its burden of disease per capita for low-income countries compared to that of lower-middle-income countries. In order to develop a conservative (lower bound) estimate for the effect of biofuel production on death and disease, it was assumed that if the ratio exceeded 5, then the risk factor was poverty dominated. Six risk factors met this criterion: global warming; underweight (largely synonymous with chronic hunger); zinc deficiency; Vitamin A deficiency; unsafe sex; and unsafe water, sanitation and hygiene. These six factors accounted for 7.7 million deaths and 268 million lost DALYs (Disability-Adjusted Life Years) worldwide for 2004. Of these, more than 99.3% of the deaths and lost DALYs were in developing countries.

Using a less restrictive criterion for the ratio of 2 would have added four more risk factors to the above list, namely: unmet contraceptive needs, indoor smoke from solid fuels, sub-optimal breast feeding and iron deficiency. Many consider these to be poverty-related (Brundtland, 2003). Including these in the list would increase their cumulative toll of poverty-dominated risks in 2004 to 11.3 million deaths and 384 million lost DALYs. However, to err on the side of conservatism, the more restrictive definition of "poverty-dominated" was used.

Regarding the poverty headcount in 2004, Goklany re-estimated the World Bank's headcount estimates for 2004 so that it was consistent with the data and methods used by De Hoyos and Medvedev (2009), which are also consistent with World Bank (2009), to estimate the increase in headcount due to additional biofuel production. Based on this, the 2004 headcount was estimated at 1,454 million. Thus, assuming proportionality between mortality and lost DALYs from poverty and the headcount, there are 5,270 deaths and 183,000 lost DALYs per million people living in absolute poverty in developing countries.

Step 3. Combining the estimates derived in Steps 1 and 2, Goklany (2011) estimated that the increase in the poverty headcount due to higher biofuel production between 2010 and 2004 implies 192,000 additional deaths and 6.7 million additional lost DALYs in 2010 alone.

Other Conclusions. 1. Biofuel policies are retarding humanity's age-old battle against poverty. 2. Since according to the World Health Organization's latest estimates, 141,000 deaths and 5.4 million lost DALYs in 2004 could be attributed to global warming (WHO 2009), biofuel policies may currently be deadlier than global warming, especially since the inertia of the climate system means little or no reduction in these numbers from any slowing of global warming due to any increase in biofuel production from 2004 to 2010.

Additional References
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Cororaton, C.B., Timilsina, G., and Mevel, S. 2010. Impacts of Large Scale Expansion of Biofuels on Global Poverty and Income Distribution. IATRC Public Trade Policy Research and Analysis Symposium, Global Warming in World Agriculture: Mitigation, Adaptation, Trade and Food Security, Universität Hohenheim, Stuttgart, Germany, June 27 -29, 2010.

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