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1、Contents lists available at ScienceDirectAtmospheric Environmentjournal homepage: /locate/atmosenvAtmospheric Environment 45 (2011) 2750e2759Estimating the climate and air quality benets of aviation fuel and emissions reductionsChristopher S. Dorbian*, Philip J. Wolfe, Ian A. WaitzDe

2、partment of Aeronautics and Astronautics, Massachusetts Institute of Technology, 33-207, 77 Massachusetts Avenue, Cambridge, MA 02139, USAa r t i c l e i n f oArticle history:Received 20 July 2010 Received in revised form 12 January 2011Accepted 10 February 2011Keywords:Aviation air quality and clim

3、ate impacts Non-CO2 impactsClimate metricsa b s t r a c tIn this study we consider the implications of our current understanding of aviation climate impacts as it relates to the ratio of non-CO2 to CO2 effects from aviation. We take as inputs recent estimates from the literature of the magnitude of

4、the component aviation impacts and associated uncertainties. We then employ a simplied probabilistic impulse response function model for the climate and a range of damage functions to estimate the ratio of non-CO2 to CO2 impacts of aviation for a range of different metrics, scientic assumptions, fut

5、ure background emissions scenarios, economic growth scenarios, and discount rates. We take cost-benet analysis as our primary context and thus focus on integral metrics that can be related to damages: the global warming potential, the time-integrated change in surface temperature, and the net presen

6、t value of damages. We also present results based on an endpoint metric, the global temperature change potential. These latter results would be more appropriate for use in a cost-effec- tiveness framework (e.g., with a well-dened policy target for the anthropogenic change in surface temperature at a

7、 specied time in the future).We nd that the parameter that most inuences the ratio of non-CO2 to CO2 impacts of aviation is the discount rate, or analogously the time window used for physical metrics; both are expressions of the relative importance of long-lived versus short-lived impacts. Second to

8、 this is the inuence of the radiative forcing values that are assumed for aviation-induced cloudiness effects. Given the large uncertainties in short-lived effects from aviation, and the dominating inuence of discounting or time- windowing, we nd that the choice of metric is relatively less inuentia

9、l. We express the ratios of non- CO2 to CO2 impacts on a per unit fuel burn basis so that they can be multiplied by a social cost of carbon to estimate the additional benets of fuel burn reductions from aviation beyond those associated with CO2 alone (all else being equal). For a non-CO2 to CO2 rati

10、o based on economic damage costs, we nd a central value of 1.8 at a 3% discount rate, with a range from 0.6 to 2.5 for the upper and lower bounds of scientic and scenario-based uncertainty. Since estimating the co-benets in this way is an important requirement for cost-benet analyses, we also provid

11、e estimates of the air quality benets of aviation fuel burn reduction in a similar format. We nd the marginal damage costs of aircraft emissions below 3000 feet to be of similar magnitude to the climate costs on a per unit fuel burn basis, or an order of magnitude smaller on a per ight basis since w

12、e take no account of the air quality impacts of emissions above 3000 feet where the majority of fuel is consumed for the eet. 2011 Elsevier Ltd. All rights reserved.1. Introduction1.1. Policy contextIn the United States and several other countries it is required that cost-benet analyses of proposed

13、environmental regulations* Corresponding author. Tel.: 1 610 608 0492; fax: 1 617 258 7566.E-mail address: (C.S. Dorbian).be performed as part of the policy assessment process (see e.g., Federal Register, 1994; OMB, 2003; EPA, 2000; Federal AviationAdministration, 1998; OECD, 1995;

14、 UK HM Treasury, 2003). Providing information to support such assessments is the primary motivation for the work we report in this paper. This is consistent with current directions within the U.S government. For example, a U.S. Government Interagency Working Group recently developed social cost of c

15、arbon estimates meant to allow U.S. government agencies to incorporate the social benets of reducing CO2 emis- sions into cost-benet analyses of regulatory actions (USG Interagency Working Group on Social Cost of Carbon, 2010).1352-2310/$ e see front matter 2011 Elsevier Ltd. All rights reserved. do

16、i:10.1016/j.atmosenv.2011.02.025C.S. Dorbian et al. / Atmospheric Environment 45 (2011) 2750e275927591.2. Multi-gas approachAlthough the Kyoto Protocol targets a number of relatively long- lived greenhouse gases (GHGs) beyond CO2, most climate change discussions and abatement cost assessments have f

17、ocused on CO2. CO2 is the largest single contributor to climate change, but there are good physical and economic arguments for the inclusion of non- CO2 gases in policies to address climate change. Shorter-lived impactsdsuch as those due to methane, ozone precursors, andwith new policies and technol

18、ogies), especially because these emissions have different atmospheric lifetimes. More useful is an integration of the radiative forcing over some future time period. The GWP has been dened by the IPCC as the ratio of the time- integrated radiative forcing of a trace species relative to that of a ref

19、erence gas (typically CO2) for an emissions pulse or scenario:ZTHa x t dtx aerosolsdare believed to play a signicant role in anthropogenic climate change (IPCC, 2001; IPCC, 2007). This is true in general, but particularly for aviation where non-CO2 impacts on surface temperature may be of the same o

20、rder of magnitude as impacts due to CO2 (see, e.g., Penner, 1999; Lee et al., 2009; and others). SeveralGWPx 0ZTHarrt dt0(1)studies have shown that the costs of abating climate change are reduced when non-CO2 emissions are included in the proposed policies (see, e.g., Reilly et al., 2003; Tol, 2006,

21、 and Weyant et al., 2006). In addition, reducing aviations adverse effects on climate beyond CO2 may have signicant co-benets in terms of air quality as we describe later.An important challenge in including non-CO2 emissions in cost- benet analyses results from the fact that these emissions can have

22、 effects on the environment and human health and welfare that differ by the type, magnitude, timing, and geographic location of the impact. Further, there are different levels of scientic uncer- tainty for the different impacts and disagreement on an appropriate metric for quantifying the effects. F

23、or this reason, Forster (2006) maintain that it is premature to include non-CO2 effects from aviation in emissions trading schemes until a robust emissions based index is available in addition to a consensus across climate models on metric values. Our objectives are different. We are not proposing a

24、 single emissions-based index or multiplier value to be used. Rather we are presenting a range of indices and values for different assumptionsdwith quantication of many of the impor- tant uncertaintiesdfor use in analyses of the costs and benets of technological, operational, or policy-based mitigat

25、ion options for aviation.1.3. Ratio metricsThe use of a non-CO2 to CO2 ratio is an effort to simplify the accounting of aviation climate forcing from effects other than CO2 accumulation. Cost-benet analyses require a metric that puts emissions on a common scale, and for this we have several options

26、as described by Fuglestvedt et al. (2010) and others. Starting with aviation emissions, one can proceed along the impact pathway to changes in atmospheric concentrations, globally-averaged radiative forcing (RF), surface temperature change, and associated socio- economic damages. Note that in this p

27、aper, we use the word “damage” to describe the effect of CO2 and other species, but this effect can be either positive or negative (i.e., detrimental or bene- cial, respectively).where TH is the time horizon over which the impacts are calculated, ax is the radiative efciency due to an emission of th

28、e species of interest, x(t) is the time-dependent decay of the species in the atmosphere, and the term in the denominator represents the cor- responding quantities for the reference gas (IPCC, 2001). GWP can be computed over a range of time horizons, but IPCC practice generally consists of presentat

29、ion of GWP20, GWP100, and GWP500 corresponding to 20-, 100-, and 500-year time periods, respectively (IPCC, 2007). GWP can also be computed for a range of background scenarios, though a constant background is often assumed as the reference. In addition to the common use of GWPs by the scientic commu

30、nity, the Kyoto Protocol adopted GWP for use in a multi-gas approach. The use of GWPs has been debated in the literature (e.g., Rotmans and Den Elzen, 1992; Fuglestvedt et al., 2003; ONeill, 2000; Skodvin and Fuglestvedt, 1997; Smith and Wigley, 2000) due largely to the fact that GWP is only a direc

31、t indicator of climate change under a restrictive set of assumptions. However, the summation of globally-averaged RF from both regional and non- regional effects coincides with globally-averaged surface warming to rst-order (Cox et al., 1995; Ramaswamy and Chen, 1997). Also, the widespread use and a

32、cceptance of GWP in policymaking is another rationale for exploring its potential as a ratio for non-CO2 to CO2 climate effects of aviation.A second physical metric that is relevant to policymaking and can be used to create a non-CO2 to CO2 impact ratio is that of time- integrated temperature change

33、 (see e.g., Marais et al., 2008). Temperature change is an attractive metric in that it lies further down the cause-and-effect chain from emissions to impacts than RF and may therefore have a higher relevance and be easier to understand than RF by itself (Shine et al., 2005; Wuebbles et al., 2010).

34、Time-integrated temperature change is of particular interest for our purposes because some measure of total impacts is required for cost-benet analysis. The ratio of the time-integrated temperature change due to a non-CO2 species to that due to CO2 can be derived from a formulation that is similar t

35、o that of a GWP:ZTHDTxtdtRadiative forcing is arelatively basic measure for comparing the effects of emissions on climate in the sense that it lies early in the climate impact cause-and-effect chain. By itself, RF has strengths and weaknesses as laid out in IPCC reports (e.g. IPCC 1995, 1996, 2001,

36、2007). Two RF metrics that are useful for evaluating avia-DT ratio x 0ZTHDTrtdt0(2)tions climate impact relative to some reference gasdCO2, in par- ticulardare the Radiative Forcing Index (RFI) and the Global Warming Potential (GWP). RFI is representative of instantaneous radiative forcing, which is

37、 the total RF from aviation (or some other sector) at a point in time divided by the total RF from aviation CO2 at that same time. RFI depends on the integrated history of prior emissions. Thus, it is less useful for considering the future impacts of new emissions (which are the emissions we seek to

38、 inuencewhere DTx(t) and DTr(t) represent thetime-dependent temperaturechange due to emissions of the species of interest and a referencegas, respectively. Finally, one step beyond temperature change due to aviation emissions is a metric of economic damages due to aviation emissions. Such economic m

39、etrics are more consistent with a cost-benet analysis framework than physical metrics. Estimates for the marginal damage costs of non-CO2 species can be used to specify multiplicative factors on the marginal damage costof CO2. The ratio of marginal damage costs can be quantied as the net present val

40、ue (NPV) of climate damages due to a unit emission of a given species relative to the same quantity for a reference gas. This sort of damage cost-based index is particularly applicable to cost-benet analysis of different climate policies and is consistent with denitions of the social cost of carbon

41、used for regulatory analyses (see, e.g. EPA, 2008b).Tol et al. (2008) have shown that GWP and time-integrated temperature change metrics can be viewed as special cases of an economic metric like the NPV-based ratio of marginal damages due to non-CO2 impacts. In particular, if one assumes a nite time

42、 horizon, zero discount rate, a given (typically constant) atmo- spheric concentration scenario, and damages that are proportional to radiative forcing (or surface temperature in the case of a time- integrated temperature change metric) then the GWP is a restric- tive form of a global economic damag

43、e potential. Tol et al. (2008) also stress that none of these assumptions are valid, but nonethe- less the assumptions may lead to some useful simplications. Here we show that these simplications may indeed be useful for aviation at this time since there are other more important factors or uncertain

44、ties that inuence the value of the non-CO2 to CO2 ratio compared to the relatively smaller differences among metrics.Tol et al. (2008) also compare an endpoint metric such as the global temperature change potential to these integral metrics and conclude that the GTP is most appropriate for a cost-ef

45、fectiveness- based framework where there is a predened policy target (e.g., a maximum anthropogenic change in surface temperature at a given point in time, like 2 o Celsius in 2050). Although we are mainly interested in cost-benet analysis and hence on damage and surrogate metrics for it (e.g., GWP

46、and integrated temperature change ratios), we also include computations of GTP-based ratios for comparison. We adopt the formulation of GTP rst introduced by Shine et al. (2005):general reduced as one includes more of the relevant physical and economiceffects. Forexample, ifoneisevaluatingpoliciesin

47、tended to mitigate socioeconomic damages, then a metric that estimates these damages is in general better than one that stops short at some other place along the impact pathway. This is the reason that many economists and government organizations responsible for environ- mental policy making recomme

48、nd the use of metrics (with quanti- ed uncertainty) that directly estimate the socioeconomic damages (see e.g., EPA, 2000). Further, in comparing two mitigation options manyof the uncertaintiesintheimpactestimates arecommon tothe two mitigation options andtherefore donot contribute torst order to th

49、e uncertainty in estimating the difference between the impacts of the two options. It is the uncertainty in predicting the difference that is relevant for making the choice between the two options, not the uncertainty in the baseline impacts. In short, in many cases the “delta” can be predicted with

50、 higher condence than the baseline effect. This can be addressed rigorously when performing a policy analysis using paired Monte Carlo simulations with some common uncertainties as demonstrated by Mahashabde et al. (2010).1.4. Objectives and overall approachOur goal in this work is to provide estima

51、tes of aviation-specic ratios representing the impacts of non-CO2 species relative to the impact of CO2. These ratios may be applied to user-specied social cost of carbon values (SCC) within cost-benet analyses to estimate the monetized benets of reducing CO2 and non-CO2 emissions from aircraft; Sec

52、tion 2.1 provides further justication for this. The purpose is not to propose a single ratio for non-CO2 to CO2 impacts from aviation, but rather to articulate the inuence of metric choice, current scientic uncertainties, and value-based judgments (e.g. discount rate or time period used for a physic

53、al metric) on the ratio. The view we take throughout is to focus on globally-averaged quantitiesda view which itself has some shortcomings when appliedGTP xDTxTH(3)to aviation given the regionalized impacts of NOx, contrails, andr DT THwhere DTx(t) and DTr(t) represent the temperature change in the

54、year TH years after the emission of the species of interest anda reference gas, respectively. The GTP differs from the temperature change ratio introduced in Eq. (2) in that it is an endpoint metric and not an integral metric.The different metrics discussed above have some common features. For examp

55、le, each metric can be used to describe different emissions scenarios, with pulse, sustained, and specic aviation scenarios being the most common. Additionally, all of the metrics have common types of uncertainty underlying them: structural uncertainty, the degree to which the metric represents the

56、real world; scenario uncertainty, the degree to which the metric addresses or is sensitive to different projections of future world behavior (background emissions and economic growth); value- based uncertainty, the degree to which short or long-lived effects are weighted; and scientic uncertainty, u

57、ncertainties in knowl- edge of the underlying physical processes affecting the climate.We conclude this section on metrics by noting that the role that metric uncertainty plays in making choices among mitigation options is sometimes misinterpreted. The further along the impact pathway one goes from

58、emissions to damages, the greater the uncertainty in the metric because more physical and economic effects must be estimated. It is sometimes stated that metrics that evaluatesocioeconomicdamagesaretoouncertaintobeuseful(see,e.g. Wuebbles et al., 2010). However, what matters is not the uncertainty in the estimate given by a metric, but the uncertainty in the decision that is made using that estimate (e.g. among policy or technology mitigation options). The uncertainty in the decision is inaviation-induced