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Climate and economic storms of our grandchildren

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Abstract

The evidence continues to mount. As our industrial economy continues to dump large amounts of carbon into the atmosphere, we are affecting the atmospheric chemistry of the global climate. This has led prominent physicist and climate scientist James Hansen to reach the “startling conclusion” that the continued exploitation of fossil fuels threatens not only the planet, but also the survival of humanity itself. At the same time, however, the evidence also suggests that the lagging rate of energy productivity is among the critical reasons for both a slumping economy and an imperiled climate. Hansen further suggests the backbone of a strategy to ensure a “global phaseout” of all fossil fuels is to encourage “a rising price on carbon.” This paper suggests we can achieve the same result in a less costly manner through cost-effective energy efficiency programs and standards. This action will require a smaller carbon charge even as we strengthen the robustness of the larger economy.

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Notes

  1. The original data is provided through 2009 with supplement data used by the author to extend the dataset to 2012. Also note that, especially in the first two sections of the narrative, this paper uses carbon rather than carbon dioxide (CO2) as an emission metric. For those who want to convert from carbon to CO2, use the ratio of their atomic weights. The atomic weight of carbon is 12 atomic mass units. The weight of CO2 is 44 because it also includes two oxygen atoms which weigh 16 atomic mass units each. Hence, 1 t of carbon equals 44/12 = 11/3, or about 3.67 t of CO2.

  2. Physicist Reiner Kümmel (2011, section 1.7) notes that an irrefutable law of physics is behind all this. It says “energy conversion is coupled to entropy production, and entropy production is coupled with emissions of particles and heat. Large quantities of emissions and particles change the molecular composition of our biosphere.”

  3. In economic parlance, the world is essentially divided into producers and consumers. Thus, any entity, agent, firm, or household that buys a particular good or service is, in that moment, a consumer. Consumer behavior, in this case then, refers to any segment of the economy that consumes energy or services—whether an industry, a school system, or an industry.

  4. See, for example, the Annual Energy Review 2011 (Energy Information Administration 2012).

  5. As Kümmel (2011) notes, the conversion of exergy into anergy is the entropy process.

  6. For a more complete discussion of these distinctions, see Laitner (2013) and especially Ayres and Warr (2009) and Kümmel (2011).

  7. Economic data are undergoing constant revision so that the GDP value here may vary from estimates first generated a year ago. Despite these minor differences, the results discussed here still hold in scope and magnitude.

    This assumes, of course, that the opportunity costs favor investments in energy or exergy efficiency over other factors of production. With the cost of efficiency generally lower than the cost of new energy supply, this seems to be the case (Laitner et al. 2012). Moreover, since exergy efficiency is a critical if special case of productivity, this logically makes sense as well.

  8. While this figure relies on projections from Moody's analytics, the trend is seen in other forecasts—whether OECD (2013), or Woods and Poole (2013).

  9. There is nothing magical about these three 30-year periods. They offer a convenient way to highlight and summarize, and therefore explain key trends. Once we understand the significant points, we can review more of the year-by-year and more of the detailed data for insights to positively shape the nation's energy and economic policies.

  10. The inadequate collection of data tracking energy as work, or exergy, forces us to turn to the more conventional EIA accounting at this point, even as we keep in mind that the complete accounting and conversion of exergy into useful work is the central idea behind this analysis. Also, greater rates of standard energy efficiency, by definition, will necessarily move us toward the kind of outcomes associated with greater rates of exergy efficiency.

  11. Without providing an exhaustive literature review here, we can cite a variety of other studies suggesting large-scale investments that can positively impact the US economy. Among many others, see for example, AEF (2009), APS (2008), Carlsmith et al. (1990), Cleetus et al. (2009), Hanson et al. (2003), InterAcademy Council (2007), Interlaboratory Working Group (2000), Laitner (2009a, b), Lovins, Amory, and the Rocky Mountain Institute (2011), McKinsey (2009), and Von Weizäcker (2009). Perhaps not immediately obvious but these and other studies suggest that the marginal returns associated with greater levels of resource efficiency than for conventional energy supply.

  12. Also worth pointing out is the increasing discussion of GDP as a weak measure of social and economic well-being, a criticism with which I agree. See, for example, Daly and Cobb (1989), Kubiszewski et al. (2013), and Stiglitz et al. (2009). At the same time, however, this paper focuses on increasing energy or exergy efficiency as means to boost overall economic well-being while reducing both energy consumption and energy-related carbon emissions.

  13. Here, we might discuss the methodology used to adjust GDP in this exercise. The relationship is drawn from a series of GDP outcomes provided by Laitner (2013). Since this is a heuristic exercise to explore the possibilities of different positive outcomes based on greater levels of energy efficiency, rather than a hard economic assessment of policy scenarios, we adapt the data to fit a curve which says that GDP = 62,015 * (kBtu/$GDP)−0.772. What this relationship says that a dollar of GDP is supported by the conversion of high-quality of energy into useful work. Admittedly, this exercise provides only an indication of what is physically possible; it does not say what are the actual prices, policies, investments, and behavioral or cultural shifts necessary to achieve a specific outcome. Consistent with the philosophy of Stanford University's Energy Modeling Forum (Huntington et al. 1982), we are modeling for insights rather than exact numbers—or in this case, evaluating reasonable differences between scenario assumptions as we explore possible benefits to the US economy. Still, the results of this thought experiment are highly consistent with a more rigorous modeling assessment of different long-term, deep reduction scenarios provided by Laitner (2009b), and described in Sect. 3 that follows.

  14. Externalities are the incidental—often not inconsequential—effects that the transactions or activities of one party have on another party, or the impact from a decision to produce and consume by one group of actors may have on others outside that market decision. The tendency is to think of negative environmental impacts that might follow from a decision to production or consume electricity, for example. But the consequences can be both negative and positive, and they often have both social and economic consequence beyond environmental concerns. For a more complete discussion of pervasive externalities see Daly and Cobb (1989), among others.

  15. By way of comparison, a $100/MtC would raise the price of gasoline by about $0.24 per gallon. Hence, a carbon charge of $93/MtC would be about 22 cents per gallon equivalent.

  16. The ten categories of products included refrigerators, clothes washers, dishwashers, residential and commercial heat pumps and air conditioners, toilets, general service light bulbs, incandescent reflector lamps, fluorescent lamp ballasts, and refrigerator vending machines.

  17. This will effectively increase the 2011 Corporate Average Fuel Economy requirement for new cars from 27.6 miles per gallon to just over 50 miles per gallon.

  18. DEEPER is the Dynamic Energy Efficiency Policy Evaluation Routine, a 15-sector quasi-dynamic input–output model that has been widely used for various state and national energy and climate policy assessments. For more background on the DEEPER Model, see the Appendix in Laitner (2009b). Note that while the reporting of the carbon price previously was expressed as dollars per metric ton of carbon, the DEEPER modeling system references the carbon price as dollars per metric ton of carbon dioxide or CO2. See note 1 for a further explanation of the difference between carbon and carbon dioxide.

  19. Hansen and others are critical of the Waxman–Markey bill because of its complexities, among other things. At almost 1,000 pages, that is a fair comment. As we shall see, however, it has so many cost-saving provisions that it turns out cheaper and better for the economy on the whole. Ideally, it could be streamlined while maintaining the larger objectives.

  20. In this case, for example, the assumption is that the implicit discount rate for consumers falls from 30 to 20 % over times. The changing preference—in effect suggesting that while consumers today might want a technology that, on average, pays for itself with energy bill savings over a 3.3-year period (or 1/0.30), but tomorrow (or sometime in the future and in response to growing concerns about the climate or worries about rising energy prices) may be happy with a technology that have a 5-year payback (or 1/0.20).

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  1. Economic and Human Dimensions Research Associates, 5751 N. Kolb Road, Unit 40108, Tucson, AZ, 85750, USA

    John A. “Skip” Laitner

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Laitner, J.A.“. Climate and economic storms of our grandchildren. J Environ Stud Sci 4, 99–109 (2014). https://doi.org/10.1007/s13412-013-0152-x

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