Environmental Lifecycle Assessment for Policy Decision-Making and Analysis

A key argument in the societal debate against polices to support biofuels is that production of these alternative fuels may in fact consume more energy than they generate and emit more greenhouse gases than they sequester (Fargione et al., 2008; Searchinger et al., 2008; Rajagopal and Zilberman, 2007; Farrell et al., 2006; Pimentel and Patzek, 2005). Metrics like net energy value, net carbon value and net petroleum offset are the basis for comparing the various fuels and are the source of these debates. The technique that underlies the calculation of these metrics is called lifecycle assessment or lifecycle analysis (LCA). A central aspect of LCA (described in detail in the next section) is it assumes linear technologies and produces outcomes that are numbers – how many units of energy are needed to produce a liter of ethanol fuel from a ton of corn. But as basic economics suggests, under reasonable conditions of some substitution between inputs and processes in production, this ratio is not a number but a function of prices. For instance, with energy being a ubiquitous input to production, a change in the relative price of different energy sources or with respect to other inputs will induce adjustments in the form of fuel switching, substitution between capital, energy and labor etc. This switching can occur at several levels in the production chain of a commodity. This will obviously alter the net carbon indicator for a fuel in the future. Also current LCA outcomes change only if the physical quantities of various inputs such as quantity of coal or electricity used in calculating LCA change. In other words, today LCA is capable of answering, how does a 10% decrease in the share of natural gas in the average electricity mix decrease the net carbon value of ethanol? But it is not capable of answering, if natural gas prices increase by 10% what is the impact on the net carbon value of ethanol? Obviously the latter is more intuitive and useful way of framing the question than the former from a policy standpoint. In this paper, we introduce a framework which can be used to derive LCA indicators directly as a function of underlying economic parameters and make it easier to simulate the impact of policies like pollution taxes and fuel mandates which in one way or another ultimately alter the relative price of commodities. Next we provide some background on current LCA literature. We then introduce a micro-economics based LCA that integrates prices directly into the lifecycle framework. We point out some implications of our model with simple illustrations. We finally describe directions for future work.