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JavaScript appears to be disabled on this computer. Please click here to see any active alerts. Greenhouse gases GHGs warm the Earth by absorbing energy and slowing the rate at which the energy escapes to space; they act like a blanket insulating the Earth. Different GHGs can have different effects on the Earth's warming. Two key ways in which these gases differ from each other are their ability to absorb energy their "radiative efficiency" , and how long they stay in the atmosphere also known as their "lifetime".
Specifically, it is a measure of how much energy the emissions of 1 ton of a gas will absorb over a given period of time, relative to the emissions of 1 ton of carbon dioxide CO 2. The time period usually used for GWPs is years. Lauder, A. Offsetting methane emissions—An alternative to emission equivalence metrics. Control 12 , — Tol, R. A unifying framework for metrics for aggregating the climate effect of different emissions.
Collins, W. Increased importance of methane reduction for a 1. Cambridge University Press, Cambridge, Google Scholar. Forster, P. Allen, M. A solution to the misrepresentations of CO2-equivalent emissions of short-lived climate pollutants under ambitious mitigation. Climate implications of GWP-based reductions in greenhouse gas emissions. Tanaka, K. The Paris Agreement zero-emissions goal is not always consistent with the 1.
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Solomon, S. Irreversible climate change due to carbon dioxide emissions. Natl Acad. Lowe, J. The impact of Earth system feedbacks on carbon budgets and climate response. A , Global and regional temperature-change potentials for near-term climate forcers. Persistence of climate changes due to a range of greenhouse gases.
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Held, I. Probing the fast and slow components of global warming by returning abruptly to preindustrial forcing. A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions.
Geoffroy, O. Transient climate response in a two-layer energy-balance model. Model structure in observational constraints on transient climate response. Change , — The simplicity of the calculation of the GWP is one of the reasons that the use of the metric is so widespread. In this paper, we focus on the choice of time horizon in the GWP as a key choice that can reflect decision-maker values, but for which additional clarity regarding the implications of the time horizon could be useful.
We also investigate the extent to which the choice of time horizon can incorporate many of the complexities of assessing the impacts described in the previous paragraph. The year time horizon of the GWP GWP is the time horizon most commonly used in many venues, for example in trading regimes such as under the Kyoto Protocol, perhaps in part because it was the middle value of the three time horizons 20, , and years analyzed in the IPCC First Assessment Report.
However, the year time horizon has been described by some as arbitrary Rodhe, Recently, some researchers and NGOs have been promoting more emphasis on shorter time horizons, such as 20 years, which would highlight the role of short-lived climate forcers such as CH 4 Howarth et al. These studies each have different nuances regarding their recommendations — for example, Ocko et al. In contrast, some governments have suggested the use of the year global temperature change potential GTP based on the greater physical relevance of temperature in comparison to forcing, in effect downplaying the role of the same short-lived climate forcers Chang-Ke et al.
Therefore, the question of timescale remains unsettled and an area of active debate. We argue that more focus on quantitative justifications for timescales within the GWP structure would be of value, as differentiated from qualitative justifications such as a need for urgency to avoid tipping points as in Howarth et al.
While we argue that quantitative justifications for choosing appropriate GWP timescales are rare, as reflected by the judgment of the IPCC authors that no scientific arguments exist for selecting given timescales, there is a rich literature addressing many aspects of climate metrics. Deuber et al. Mallapragada and Mignone present a similar framework and also note that metrics can consider a single pulse of a stream of pulses over multiple years. Several authors have recognized that under certain simplifying assumptions, the GWP is equivalent to the integrated GTP, and therefore any timescale arguments that apply to analyses of one metric would also apply to the other Shine et al.
Boucher uses an uncertainty analysis similar to that used in this paper to estimate the GDP of methane. Fuglestvedt et al. De Cara , in an unpublished manuscript, also calculated the relationship between discount rates and time horizon, though they assumed linear damages.
An alternate approach is to evaluate metrics within the context of an integrated assessment model IAM. There are several examples of such an approach. Van den Berg et al. The analysis estimated optimal costs to meet a 3.
A key caveat here, as with many such analyses including the present Sarofim and Giordano paper , is that the structure of the test can drive the evaluation result: in the case of van den Berg et al. This is in large part because marginal abatement curves for CH 4 within these models have low-cost options likely representing mitigation options such as landfill gas to energy projects and oil and gas leakage reduction and high-cost options reductions of enteric fermentation emissions from livestock but few moderate-cost options.
Therefore, for even a moderate carbon price, all the low-cost options will be enacted regardless of GWP, and no matter what the GWP, few high-cost options will be enacted. Such analyses may not fully consider nonmarket barriers or distributional effects for which changes in the GWP could be important. However, a number of authors have argued that pulse-based metrics such as the GWP are not well-suited to achieve stabilization goals Sarofim et al. However, any pulse-based approach faces at least two major challenges related to stabilization scenarios.
The first is that as a temperature target is approached, a dynamic approach will shift from favoring long-lived gas mitigation to favoring short-lived gases. While this shift may be optimal for meeting a target in a single year, it will be suboptimal for any year after that year. The second challenge is that once stabilization has been achieved, any trading between emission pulses of carbon dioxide and a shorter-lived gas will cause a deviation from stabilization.
For example, trading a reduction in methane emissions for a pulse of CO 2 emissions will lead to a near-term decrease in temperature, but also a long-term increase in temperature above the original stabilization level. One solution to the problem is a physically based one. Allen et al.
This resolves the issue of trading off what is effectively a permanent temperature change against a transient one. However, the challenge becomes one of implementation, as current policy structures are not designed for addressing indefinite sustained mitigation.
A second solution is a dynamically updating global cost potential approach that optimizes shadow prices of different gases given a stabilization constraint Tol et al.
Alternatively, a number of researchers Daniel et al. Such a separation recognizes the value of the cumulative carbon concept in setting GHG mitigation policy Zickfeld et al.
In economic terms, a temperature-based target is equivalent to the assumption of infinite damage beyond that threshold temperature and zero damages below that threshold Tol et al. This paper provides a needed quantification and analysis of the implications of different GWP time horizons.
We follow the lead of economists who have proposed that the appropriate comparison for different options for GHG emissions policies is between the net present discounted marginal damages Schmalensee, ; Deuber et al. However, instead of proposing a switch to a GDP metric, we take the structure of the GWP as a given due to the simplicity of calculation and the widespread historic acceptance of its use.
While other analysts have used similar approaches Fuglestvedt et al. The paper focuses on CO 2 and CH 4 as the two most important historical anthropogenic contributors to current warming, but the methodology is applicable to emissions of other gases, and sensitivity analyses consider N 2 O and some fluorinated gases. The general approach taken in this paper is to calculate the impact of a pulse of emissions of either CO 2 or CH 4 in the first year of simulation on a series of climatic variables.
The first step is to calculate the perturbation of atmospheric concentrations over a baseline scenario. The concentration perturbation is transformed into a change in the global radiative forcing balance. The radiative forcing perturbation over time is used to calculate the impact on temperature and then damages due to that temperature change. Discount rates are then applied to these impacts to determine the net present value of the impacts.
The details of these calculations are described here. The perturbation due to a pulse of CH 4 is calculated by the use of a In this paper, a pulse of This approach parallels the standard IPCC approach; however, various papers have noted that the lifetime of CO 2 presented in the IPCC includes climate carbon feedbacks, whereas the lifetime of CH 4 does not, which is a potential inconsistency Gasser et al.
The discussion in Sect. The perturbation of radiative forcing from additional GHG concentrations is based on the equations in Table 8. CH 4 forcing is adjusted by a factor of 1. N 2 O forcing is adjusted by a factor of 0. Baseline radiative forcing is derived from the RCP scenario database. It should be noted that the IPCC equations were designed for marginal emissions changes; therefore, using this approach to calculate temperatures resulting from the background RCPs and the additional emissions pulses introduces a potential uncertainty.
In order to calculate future temperatures, we also account for the present-day radiative forcing imbalance. Medhaug et al. We use the mean 0. The sum of the coefficients of the equations in the IPCC temperature impulse response functions 1. As a sensitivity analysis, the coefficients were scaled to yield climate sensitivities of 1.
Damages as a percent of GDP were calculated by multiplying a constant by the square of the temperature change since the baseline period. Hsiang et al. For the sensitivity analysis, damage exponents of 1.
Other formulations of the damage function have been considered in the literature. The first alternative is explicit calculation of damages within integrated assessment models.
Another alternative is to include a higher-power term in addition to the square exponent so that at low temperatures damages rise quadratically, but at high temperatures damages accelerate Weitzman,
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