Virtually all current carbon footprinting efforts ignore the dimension of time. This implicitly assumes that greenhouse gases emitted in the past, emitted today, or emitted in the future, all have the same global warming potential. This, of course, is not a valid assumption. If we have to emit a fixed amount of greenhouse gases, it would be better from a climate perspective to defer the emissions to a later date, or spread out the emissions over a period of time, than to emit the entire amount today. Similarly, if we have to offset a certain amount of greenhouse gases, it would be better for the offsetting process (whether it is in the form of carbon sequestration, energy efficiency, or some other CDM project) to become fully effective today rather than ramp up over a period of time.
An interesting timing issue comes up when emissions generated over a period of time must be offset by a process that also removes carbon or reduces emissions over a period of time. Depending on which process occurs faster, the offsetting may be more or less effective at the end. David Douglas, VP of Eco Responsibility at Sun Microsystems, provides a nice analysis using Dell's Plant a Tree for Me program as an example. The critical issue is the stock of CO2 that is in the atmosphere as a function of time, which would be very amenable to modeling with system dynamics tools. David suggests that an NPV calculation for carbon might be useful. I agree that we do need a measure that adequately captures the time dimension. Imagine a hypothetical product that takes a long time to produce (with components and finished products sitting for long periods in warehouses, moving through slow transport links, etc.) and/or takes a long time to consume. The emissions produced in the life cycle of the product would occur at various points in time, and the time-adjusted total carbon footprint would be more than just a sum of the separate emissions.
Even without getting into offsets, just quantifying a proper global warming potential will require improved methodology -- essentially a dynamic LCA. Academically, this is not a well developed topic, and as far as I know, there are no commercial solutions that address this problem. You can find a short discussion of this in the book The Computational Structure of Life Cycle Assessment, by Heijungs and Suh.
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