Life cycle analysis of emissions from various forms of energy converted to electricity


There was a recent discussion regarding the life cycle analysis of various forms of energy, principally to be converted to electricity. Given that everything I know about sustainability and life cycle analysis suggests is it is a very complicated business, I decided to dig into this a bit. (See also.) The discussion only considers a few major scholarly references, notably Stanford’s Mark Jacobson, who I’ve written a lot about on these pages, his colleague, Mark Delucchi, and then critics of their work, Barry Brook, Charles Barton, and Howard Hayden.

This is not a summary. While I have read the references below, I have not analyzed them.

I do have some impressions. Even if my impressions amount to what is essentially a meta-analysis (“LCA”), the point estimates of life cycle emissions are all over the place, possibly due to different methods and assumptions. If that sounds demeaning, it is not. The same kind of scatter can be found in most meta-analyses of medical treatments and procedures. Consider, for example, the studies leading to the settings of the “normal” range for diastolic blood pressure when diagnosing hypertension, even if there are large cohort studies as well, namely, Sesso, et al, “Systolic and diastolic blood pressure, pulse pressure, and mean arterial pressure as predictors of cardiovascular disease risk in men“. The point is that sometimes decisions need to be made, and the guidance of a meta-analysis is all we’ve got. But, if done, it needs to be done with great care and choice. And it needn’t remain that way.

In particular, if informed policy is the goal, empirical measurements of greenhouse gas emissions and their allocation to activities ought to be much better done and accounted for. What’s being used in the above are a bunch of bounds and guestimates from either ab initio calculations (which can go very wrong with engineered systems), self-reporting from those emitting, or inferences based upon economic activity. A hidden benefit of a Carbon Tax (or “fee-and-dividend scheme”, for those afraid of Tea Partyers) is that this kind of accounting might begin to be possible. Detailed time and spatial series of emissions at global scale down to neighborhoods ought to be possible, but that is an enormous undertaking.

But, also, the Hatch analysis says nuclear power has a LCA GHG emissions almost twice that of wind turbines.

The World Nuclear Organization (2015) summarizes (based upon reports from three countries) that nuclear has half the life cycle GHG emissions of solar, and (except for Finland) roughly the same as wind. But it has double the life cycle GHG emissions of hydropower. NREL concludes life cycle emissions from nuclear and wind are comparable, as are those for concentrating solar power, but solar PV are greater (but significantly less than methane).

For China, Aden, Marty, and Muller found onshore wind turbines to have LCA emissions greater than nuclear, with MOX and reprocessing considered, and much greater if they were not. Offshore wind turbines has less LCA emissions (which seems strange to me). They found concentrated solar to be in the ballpark, with solar PV 4x bigger. Hydropower again wins.

Weisser gives comparable results to the other findings, except that his assessment of LCA emissions for solar PV are less, but still 3x higher than the nuclear-wind LCAs. Weisser also cautions that hydropower may not yield the low LCA emissions estimates often touted for it, as these sometimes neglect flooding of new land, with decomposition and emissions, as well as ecosystem changes which produces higher lifetime contributions.

Sovacool looks at the LCA emissions for nuclear energy exclusively, reviewing a large number of articles and summarizing them.

Like I said, I’m not trying to summarize anything. But a significant point is that one doesn’t have to assume a limited nuclear war to arrive at a rationalized conclusion that nuclear power has life cycle GHG emissions in excess of wind and solar. Also, the ranges of reported per unit energy emissions should be considered in comparisons. For some reason, some of the reports on ranges from nuclear power LCA are huge. Sovacool provides some explanation for why.

About hypergeometric

See http://www.linkedin.com/in/deepdevelopment/ and http://667-per-cm.net
This entry was posted in adaptation, anemic data, Anthropocene, biofuels, bridge to nowhere, carbon dioxide, carbon dioxide sequestration, Carbon Worshipers, citizenship, civilization, clean disruption, climate, climate change, climate disruption, complex systems, corporate litigation on damage from fossil fuel emissions, corporate supply chains, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, economics, efficiency, energy, energy reduction, energy utilities, engineering, environment, evidence, forecasting, fossil fuel divestment, fossil fuels, global warming, Hyper Anthropocene, investment in wind and solar energy, IPCC, James Hansen, Life Cycle Assessment, Mark Jacobson, methane, natural gas, nuclear power, nuclear weapons, pipelines, Sankey diagram, solar energy, solar power, SolarPV.tv, Tea Party, transparency, wind energy, wind power, zero carbon. Bookmark the permalink.

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