Deep Carbon Footprinting^™

Deep Carbon Footprinting^™ is our new simulation-based technology that goes well beyond the usual static carbon footprinting and takes life-cycle carbon footprinting to the next level. It explicitly considers the dimension of time in every part of a product/service life cycle -- production, transportation, use, and disposal. It also looks at a broader range of biophysical phenomena, including inherent non-linearities and second-order effects, that could could contribute to the real carbon footprint. The result is a time profile of GHG emissions that exposes the dynamics in the carbon footprint of a product or service and provides significant new insights into trade-offs that can minimize the life-cycle carbon footprint.

Here are a few examples to illustrate the types of analyses that this methodology would handle:

• Consider the wood in a building or in a piece of furniture. The biogenic carbon in that wood is stored in the product as long as the product is in service. When the product (or a part of it) is disposed and landfilled, the wood might decompose aerobically or anaerobically, releasing its biogenic carbon atoms back into the atmosphere as either CO2 or methane over a short or a long period of time, during which there is continuing but diminishing carbon storage in addition to the GHG emissions. A similar analysis can apply to a piece of cotton clothing, or any other product that sequesters and then releases biogenic carbon.

• Concrete in buildings and infrastructure continually absorbs CO2 from the atmosphere through a process called carbonation. At the end of its service life, the concrete might be demolished and then either re-used as concrete aggregate or landfilled. Demolition/crushing increases the available surface area and potentially speeds up the carbonation. If we are looking at a 100-year assessment period, then the concrete would have to be credited with a certain amount of carbon sequestration, starting at 0 and ramping up over time. The carbon credit is not all the CO2 that is ultimately absorbed by the concrete in the 100 years, but a smaller amount that actually reflects the timing of all the absorption.

• On a related note, trees planted in a landscape project should not take credit for the total CO2 absorbed over the average growing period of 20 years or so. Any CO2 absorbed in the first year is a lot more valuable than any CO2 absorbed in the 20th year, so the time series of annual CO2 absorption amounts would have to be weighted appropriately based on the year of absorption and then summed together. Moreover, there are potential non-linearities in the absorption characteristics over the growing period.

• Food waste is among the most easily decomposable materials in the waste stream. Food waste generally occurs before cooking as well as after cooking. Unless it is composted properly, most of the food waste will turn into methane under anaerobic decomposition over time. Biogenic carbon released as CO2 very soon after production is climate neutral, but any biogenic carbon that is released as methane is decidedly not neutral unless it is recovered and used as fuel. Once again, the timing is important. This effect can sometimes exceed the contribution of transportation in food carbon footprints.

• Application of organic matter on a regular basis increases carbon content in soils, but at some point the system reaches a steady-state where the mineralization of organic carbon into CO2 offsets the annual accumulation of organic matter. This type of time-limted carbon sequestration can buy us time and can be very valuable while we move toward long-term emission reductions elsewhere in the economy. In addition, as organic soil amendments replace synthetic fertilizers, the slower release of nitrogen makes them less prone to producing N2O. A static carbon footprinting approach would miss most of the dynamics and trade-offs at play here.

Some of the above examples simply illustrate a more general distinction between biological/chemical and thermal processes. While thermal processes such as fuel combustion lead to CO2 emissions immediately (albeit with time delays depending on the timing of the combustion), biological processes (such as degradation of biomass or absorption of atmospheric CO2 in plants) and certain chemical processes occur over long periods of time and often with non-linear emission/sequestration characteristics. The real world is full of combinations of these different processes where the timing and non-linearities can not be ignored. Only a rigorous and flexible simulation-based methodology can provide an adequate solution.

Deep Carbon Footprinting^™ is now an integral part our suite of software tools and solutions.

 

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