Editing IPCC:AR6/WGI/Chapter-7 (section)

== 7.6 Metrics to Evaluate Emissions ==

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Emissions metrics are used to compare the relative effect of emissions of different gases over time in terms of radiative forcing, global surface temperature or other climate effects. They are introduced in ( [[IPCC:Wg1:Chapter:Chapter-1|Chapter 1]] (Box 1.3). [[IPCC:Wg1:Chapter:Chapter-8|Chapter 8]] of AR5 ( [[#Myhre--2013b|Myhre et al., 2013b]] ) comprehensively discussed different emissions metrics so this section focuses on updates since that report. [[#7.6.1|Section 7.6.1]] updates the physical assessment. [[#7.6.2|Section 7.6.2]] assesses developments in the comparison of emissions of short- and long-lived gases. Box 7.3 assesses physical aspects of emissions metric use within climate policy.

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=== 7.6.1 Physical Description of Metrics ===

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This section discusses metrics that relate emissions to physical changes in the climate system. Other metrics, for instance relating to economic costs or ‘damage’ are discussed in WGIII, Chapter 2. The same Chapter also assesses literature examining the extent to which different physical metrics are linked to cost–benefit and cost-effectiveness metrics. One metric, the 100-year global warming potentials (GWP-100), has extensively been employed in climate policy to report emissions of different GHGs on the same scale. Other physical metrics exist, and these are discussed in this section.

Emissions metrics can be quantified as the magnitude of the effect a unit mass of emission of a species has on a key measure of climate change. This section focuses on physical measures such as the radiative forcing, GSAT change, global average precipitation change, and global mean sea level rise ( [[#Myhre--2013b|Myhre et al., 2013b]] ; [[#Sterner--2014|Sterner et al., 2014]] ; [[#Shine--2015|Shine et al., 2015]] ). When used to represent a climate effect, the metrics are referred to as absolute metrics and expressed in units of ‘effect per kg’ (e.g., absolute global warming potentials, AGWP or absolute global temperature-change potentials, AGTP). More commonly, these are compared with a reference species (almost always CO <sub>2</sub> in kg (CO <sub>2</sub> )), to give a dimensionless factor (written as e.g., global warming potentials (GWP) or global temperature-change potential (GTP)). The unit mass is usually taken as a 1 kg instantaneous ‘pulse’ ( [[#Myhre--2013b|Myhre et al., 2013b]] ), but can also refer to a ‘step’ in emissions rate of 1 kg yr <sup>–1</sup> .

There is a cause–effect chain that links human activity to emissions, then from emissions to radiative forcing, climate response and climate impacts ( [[#Fuglestvedt--2003|Fuglestvedt et al., 2003]] ). Each step in the causal chain requires an inference or modelling framework that maps causes to effects. Emissions metrics map from emissions of some compound to somewhere further down the cause-and-effect chain, radiative forcing (e.g., GWP) or temperature (e.g., GTP) or other effects (such as sea level rise or socio-economic impacts). While variables later in the chain have greater policy or societal relevance, they are also subject to greater uncertainty because each step in the chain includes more modelling systems, each of which brings its own uncertainty (Figure 1.15; [[#Balcombe--2018|Balcombe et al., 2018]] ).

Since AR5, understanding of the radiative effects of emitted compounds has continued to evolve and these changes are assessed in ( [[#7.6.1.1|Section 7.6.1.1]] . Metrics relating to precipitation and sea level have also been quantified ( [[#7.6.1.2|Section 7.6.1.2]] ). Understanding of how emissions metrics are affected by the carbon cycle response to temperature has improved. This allows the carbon cycle response to temperature to be more fully included in the emissions metrics presented here ( [[#7.6.1.3|Section 7.6.1.3]] ). There have also been developments in approaches for comparing short-lived GHGs to CO <sub>2</sub> in the context of mitigation and global surface temperature change ( [[#7.6.1.4|Section 7.6.1.4]] ). Emissions metrics for selected key compounds are presented in ( [[#7.6.1.5|Section 7.6.1.5]] .

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==== 7.6.1.1 Radiative Properties andLifetimes ====

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The radiative properties and lifetimes of compounds are the fundamental component of all emissions metrics. Since AR5, there have been advances in the understanding of the radiative properties of various compounds (see Sections 7.3.1, 7.3.2 and 7.3.3), and hence their effective radiative efficiencies (ERFs per unit change in concentration). For CO <sub>2</sub> , CH <sub>4</sub> and N <sub>2</sub> O, better accounting of the spectral properties of these gases has led to re-evaluation of their stratospheric-temperature-adjusted radiative forcing (SARF) radiative efficiencies and their dependence on the background gas concentrations ( [[#7.3.2|Section 7.3.2]] ). For CO <sub>2</sub> , CH <sub>4</sub> , N <sub>2</sub> O, CFC-11 and CFC-12 the tropospheric adjustments (Sections 7.3.1 and 7.3.2) are assessed to make a non-zero contribution to ERF. There is insufficient evidence to include tropospheric adjustments for other halogenated compounds. The re-evaluated effective radiative efficiency for CO <sub>2</sub> will affect all emissions metrics relative to CO <sub>2</sub> .

The effective radiative efficiencies (including adjustments from ( [[#7.3.2|Section 7.3.2]] ) for 2019 background concentrations for CO <sub>2</sub> , CH <sub>4</sub> and N <sub>2</sub> O are assessed to be 1.33×10 <sup>–5</sup> , 3.89×10 <sup>–4</sup> and 3.19×10 <sup>–3</sup> W m <sup>–2</sup> ppb <sup>–1</sup> respectively (see Table 7.15 for uncertainties), compared to AR5 assessments of 1.37×10 <sup>–5</sup> , 3.63×10 <sup>–4</sup> and 3.00×10 <sup>–3</sup> W m <sup>–2</sup> ppb <sup>–1</sup> . For CO <sub>2</sub> , increases due to the adjustments do not quite balance the decreases due to the increasing background concentration. For CH <sub>4</sub> , increases due to the re-evaluated radiative properties more than offset the decreases due to the increasing background concentration. For N <sub>2</sub> O the addition of tropospheric adjustments increases the effective radiative efficiency. Radiative efficiencies of halogenated species have been revised slightly ( [[#7.3.2.4|Section 7.3.2.4]] ) and for CFCs include tropospheric adjustments.

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'''Table 7.15''' '''|''' '''Emissions metrics for selected species: global warming potential (GWP), global temperature-change potential (GTP).''' All values include carbon cycle responses as described in ( [[#7.6.1.3|Section 7.6.1.3]] . Combined GTPs (CGTPs) are shown only for species with a lifetime less than 20 years ( [[#7.6.1.4|Section 7.6.1.4]] ). Note CGTP has units of years and is applied to a change in emissions rate rather than a change in emissions amount. The radiative efficiencies are as described in ( [[#7.3.2|Section 7.3.2]] and include tropospheric adjustments where assessed to be non-zero in ( [[#7.6.1.1|Section 7.6.1.1]] . The climate response function is from Supplementary Material 7.SM.5.2. Uncertainty calculations are presented in Supplementary Tables 7.SM.8 to 7.SM.13. Chemical effects of CH <sub>4</sub> and N <sub>2</sub> O are included ( [[#7.6.1.3|Section 7.6.1.3]] ). Contributions from stratospheric ozone depletion to halogenated species metrics are not included. Supplementary Table 7.SM.7 presents the full table.

{| class="wikitable"
|-
| Species

| Lifetime

(Years)

| Radiative Efficiency (W m <sup>–2</sup> ppb <sup>–1</sup> )

| GWP-20

| GWP-100

| GWP-500

| GTP-50

| GTP-100

| CGTP-50 (years)

| CGTP-100 (years)

|-
| '''CO''' <sub>2</sub>

| Multiple

| 1.33 ± 0.16 ×10 <sup>–5</sup>

| 1.

| 1.000

| 1.000

| 1.000

| 1.000

|
|-
| '''CH''' <sub>4</sub> '''-fossil'''

| 11.8 ± 1.8

| 5.7 ± 1.4 ×10 <sup>–4</sup>

| 82.5 ± 25.8

| 29.8 ± 11

| 10.0 ± 3.8

| 13.2 ± 6.1

| 7.5 ± 2.9

| 2823 ± 1060

| 3531 ± 1385

|-
| '''CH''' <sub>4</sub> '''-non fossil'''

| 11.8 ± 1.8

| 5.7 ± 1.4 ×10 <sup>–4</sup>

| 79.7 ± 25.8

| 27.0 ± 11

| 7.2 ± 3.8

| 10.4 ± 6.1

| 4.7 ± 2.9

| 2675 ± 1057

| 3228 ± 1364

|-
| '''N''' <sub>2</sub> '''O'''

| 109 ± 10

| 2.8 ± 1.1 ×10 <sup>–3</sup>

| 273 ± 118

| 273 ± 130

| 130 ± 64

| 290 ± 140

| 233 ± 110

|
|-
| '''HFC-32'''

| 5.4 ± 1.1

| 1.1 ± 0.2 ×10 <sup>–1</sup>

| 2693 ± 842

| 771 ± 292

| 220 ± 87

| 181 ± 83

| 142 ± 51

| 78,175 ± 29,402

| 92,888 ± 36,534

|-
| '''HFC-134a'''

| 14.0 ± 2.8

| 1.67 ± 0.32 ×10 <sup>–1</sup>

| 4144 ± 1160

| 1526 ± 577

| 436 ± 173

| 733 ± 410

| 306 ± 119

| 146,670 ± 53,318

| 181,408 ± 71,365

|-
| '''CFC-11'''

| 52.0 ± 10.4

| 2.91 ± 0.65 ×10 <sup>–1</sup>

| 8321 ± 2419

| 6226 ± 2297

| 2093 ± 865

| 6351 ± 2342

| 3536 ± 1511

|
|-
| '''PFC-14'''

| 50,000

| 9.89 ± 0.19 ×10 <sup>–2</sup>

| 5301 ± 1395

| 7380 ± 2430

| 10,587 ± 3692

| 7660 ± 2464

| 9055 ± 3128

|
|}

The perturbation lifetimes of CH <sub>4</sub> (Section 6.3.1). and N <sub>2</sub> o ( [[IPCC:Wg1:Chapter:Chapter-5#5.2.3.1|Section 5.2.3.1]] ) have been slightly revised since AR5 to be 11.8 ± 1.8 years and 109 ± 10 years, respectively (Table 7.15). The lifetimes of halogenated compounds have also been slightly revised ( [[#Hodnebrog--2020a|Hodnebrog et al., 2020a]] ).

Although there has been greater understanding since AR5 of the carbon cycle responses to CO <sub>2</sub> emissions (Sections 5.4 and 5.5), there has been no new quantification of the response of the carbon cycle to an instantaneous pulse of CO <sub>2</sub> emission since [[#Joos--2013|Joos et al. (2013)]] .

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==== 7.6.1.2 Physical Indicators ====

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The basis ofall the emissions metrics is the time profile of effective radiative forcing (ERF) following the emission of a particular compound. The emissions metrics are then built up by relating the forcing to the desired physical indicators. These forcing–response relationships can either be generated from emulators (Cross-Chapter Box 7.1; [[#Tanaka--2013|Tanaka et al., 2013]] ; [[#Gasser--2017b|Gasser et al., 2017b]] ), or from analytical expressions based on parametric equations (response functions) derived from more complex models ( [[#Myhre--2013b|Myhre et al., 2013b]] ).

To illustrate the analytical approach, the ERF time evolution following a pulse of emission can be considered an absolute global forcing potential (AGFP; similar to the ‘Instantaneous Climate Impact’ of [[#Edwards--2014|Edwards and Trancik, 2014]] ). This can be transformed into an absolute global temperature-change potential (AGTP) by combining the radiative forcing with a global surface temperature response function. This temperature response is typically derived from a two-layer energy balance emulator (Supplementary Material 7.SM.5; [[#Myhre--2013b|Myhre et al., 2013b]] ). For further physical indicators further response functions are needed based on the radiative forcing or temperature, for instance. [[#Sterner--2014|Sterner et al. (2014)]] used an upwelling-diffusiveenergy balance model to derive the thermosteric component of sea level rise as response functions to radiative forcing or global surface temperature. A metric for precipitation combines both the radiative forcing (AGFP) and temperature (AGTP) responses to derive an absolute global precipitation potential (AGPP; [[#Shine--2015|Shine et al., 2015]] ). The equations relating these metrics are given in Supplementary Material 7.SM.5.

The physical emissions metrics described above are functions of time since typically the physical effects reach a peak and then decrease in the period after a pulse emission as the concentrations of the emitted compound decay. The value of the metrics can therefore be strongly dependent on the time horizon of interest. All relative metrics (GWP, GTP etc.) are also affected by the time dependence of the CO <sub>2</sub> metrics in the denominator. Instantaneous or endpoint metrics quantify the change (e.g., in radiative forcing, global surface temperature, global mean sea level) at a particular time after the emission. These can be appropriate when the goal is to not exceed a fixed target such as a temperature or global mean sea level rise at a specific time. Emissions metrics can also be integrated from the time of emission. The most common of these is the absolute global warming potential (AGWP), which is the integral of the AGFP. The physical effect is then in units of forcing-years, degree-years or metre-years for forcing, temperature, or sea level rise, respectively. These can be appropriate for trying to reduce the overall damage potential when the effect depends on how long the change occurs for, not just how large the change is. The integrated metrics still depend on the time horizon, though for the shorter-lived compounds this dependence is somewhat smoothed by the integration. The integrated version of a metric is often denoted as iAGxx, although the integral of the forcing-based metric (iAGFP) is known as the AGWP. Both the endpoint and integrated absolute metrics for non-CO <sub>2</sub> species can be divided by the equivalent for CO <sub>2</sub> to give relative emissions metrics (e.g., GWP (=iGFP), GTP, iGTP).

Each step from radiative forcing to global surface temperature to sea level rise introduces longer time scales and therefore prolongs further the contributions to climate change of short-lived GHGs ( [[#Myhre--2013b|Myhre et al., 2013b]] ). Thus, short-lived GHGs become more important (relative to CO <sub>2</sub> ) for sea level rise than for temperature or radiative forcing ( [[#Zickfeld--2017|Zickfeld et al., 2017]] ). Integrated metrics include the effects of a pulse emission from the time of emission up to the time horizon, whereas endpoint metrics only include the effects that persist out to the time horizon. Because the largest effects of short-lived GHGs occur shortly after their emission and decline towards the end of the time period, short-lived GHGs have relatively higher integrated metrics than their corresponding endpoint metrics ( [[#Peters--2011|Peters et al., 2011]] ; [[#Levasseur--2016|Levasseur et al., 2016]] ).

For species perturbations that lead to a strong regional variation in forcing pattern, the regional temperature response can be different to that for CO <sub>2</sub> . Regional equivalents to the global metrics can be derived by replacing the global surface temperature response function with a regional response matrix relating forcing changes in one region to temperature changes in another (W.J. [[#Collins--2013|]] [[#Collins--2013|Collins et al., 2013]] ; [[#Aamaas--2017|Aamaas et al., 2017]] ; [[#Lund--2017|Lund et al., 2017]] ).

For the research discussed above, metrics for several physical variables can be constructed that are linear functions of radiative forcing. Similar metrics could be devised for other climate variables provided they can be related by response functions to radiative forcing or global surface temperature change. The radiative forcing does not increase linearly with emissions for any species, but the non-linearities (for instance changes in CO <sub>2</sub> radiative efficiency) are small compared to other uncertainties.

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==== 7.6.1.3 Carbon Cycle Responses and Other Indirect Contributions ====

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The effect of a compound on climate is not limited to its direct radiative forcing. Compounds can perturb the carbon cycle affecting atmospheric CO <sub>2</sub> concentrations. Chemical reactions from emitted compounds can produce or destroy other GHGs or aerosols.

Any agent that warms the surface perturbs the terrestrial and oceanic carbon fluxes (Sections 5.4.3 and 5.4.4), typically causing a net flux of CO <sub>2</sub> into the atmosphere and hence further warming. This aspect is already included in the carbon cycle models that are used to generate the radiative effects of a pulse of CO <sub>2</sub> ( [[#Joos--2013|Joos et al., 2013]] ), but was neglected for non-CO <sub>2</sub> compounds in the conventional metrics so this introduces an inconsistency and bias in the metric values ( [[#Gillett--2010|Gillett and Matthews, 2010]] ; [[#MacDougall--2015|MacDougall et al., 2015]] ; [[#Tokarska--2018|Tokarska et al., 2018]] ). A simplistic account of the carbon cycle response was tentatively included in AR5 based on a single study (W.J. [[#Collins--2013|]] [[#Collins--2013|Collins et al., 2013]] ). Since AR5 this understanding has been revised ( [[#Gasser--2017b|Gasser et al., 2017b]] ; [[#Sterner--2017|Sterner and Johansson, 2017]] ) using simple parametrized carbon cycle models to derive the change in CO <sub>2</sub> surface flux for a unit temperature pulse as an impulse response function to temperature. In W.J. [[#Collins--2013|]] [[#Collins--2013|Collins et al. (2013)]] this response function was assumed to be simply a delta function, whereas the newer studies include a more complete functional form accounting for subsequent re-uptake of CO <sub>2</sub> after the removal of the temperature increase. Accounting for re-uptake has the effect of reducing the carbon-cycle responses associated with the metrics compared to AR5, particularly at large time horizons. The increase in any metric due to the carbon cycle response can be derived from the convolution of the global surface temperature response with the CO <sub>2</sub> flux response to temperature and the equivalent metric for CO <sub>2</sub> (Equation 7.SM.5.5 in the Supplementary Material). Including this response also increases the duration of the effect of short-lived GHGs on climate ( [[#Fu--2020|Fu et al., 2020]] ). An alternative way of accounting for the carbon cycle temperature response would be to incorporate it into the temperature response function (the response functions used here and given in Supplementary Material 7.SM.5.2 do not explicitly do this). If this were done, the correction could be excluded from both the CO <sub>2</sub> and non-CO <sub>2</sub> forcing responses as, in [[#Hodnebrog--2020a|Hodnebrog et al. (2020a)]] .

Including the carbon cycle response for non-CO <sub>2</sub> treats CO <sub>2</sub> and non-CO <sub>2</sub> compounds consistently and therefore we assess that its inclusion more accurately represents the climate effects of non-CO <sub>2</sub> species. There is ''high confidence'' in the methodology of using carbon cycle models for calculating the carbon cycle response. The magnitude of the carbon cycle response contributions to the emissions metrics varies by a factor of two between [[#Sterner--2017|Sterner and Johansson (2017)]] and [[#Gasser--2017b|Gasser et al. (2017b)]] . The central values are taken from [[#Gasser--2017b|Gasser et al. (2017b)]] as the OSCAR 2.2 model used is based on parameters derived from CMIP5 models, and the climate–carbon feedback magnitude is therefore similar to the CMIP5 multi-model mean ( [[#Arora--2013|Arora et al., 2013]] ; [[#Lade--2018|Lade et al., 2018]] ). As values have only been calculated in two simple parametrized carbon cycle models the uncertainty is assessed to be ±100%. Due to there being few studies and a factor of two difference between them, there is ''low confidence'' that the magnitude of the carbon cycle response is within the higher end of this uncertainty range, but ''high confidence'' that the sign is positive. Carbon cycle responses are included in all the metrics presented in Table 7.15 and Supplementary Table 7.SM.7. The carbon cycle contribution is lower than in AR5, but there is ''high confidence'' in the need for its inclusion and the method by which it is quantified.

Emissions of non-CO <sub>2</sub> species can affect the carbon cycle in other ways: emissions of ozone precursors can reduce the carbon uptake by plants (W.J. [[#Collins--2013|]] [[#Collins--2013|Collins et al., 2013]] ); emissions of reactive nitrogen species can fertilize plants and hence increase the carbon uptake ( [[#Zaehle--2015|Zaehle et al., 2015]] ); and emissions of aerosols or their precursors can affect the utilisation of light by plants ( [[#Cohan--2002|Cohan et al., 2002]] ; [[#Mercado--2009|Mercado et al., 2009]] ; [[#Mahowald--2017|Mahowald et al., 2017]] ; see Section 6.4.4 for further discussion). There is ''robust evidence'' that these processes occur and are important, but ''insufficient evidence'' to determine the magnitude of their contributions to emissions metrics. Ideally, emissions metrics should include all indirect effects to be consistent, but limits to our knowledge restrict how much can be included in practice.

Indirect contributions from chemical production or destruction of other GHGs are quantified in ( [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] (Section 6.4). For methane (CH <sub>4</sub> ), AR5 ( [[#Myhre--2013b|Myhre et al., 2013b]] ) assessed that the contributions from effects on ozone and stratospheric water vapour add 50% ± 30% and 15% ± 11% to the emissions-based ERF, which were equivalent to 1.8 ± 0.7 ×10 <sup>–4</sup> and 0.5 ± 0.4 ×10 <sup>–4</sup> W m <sup>–2</sup> ppb (CH <sub>4</sub> ) <sup>–1</sup> . In AR6 the radiative efficiency formulation is preferred as it is independent of the assumed radiative efficiency for methane. The assessed contributions to the radiative efficiency for methane due to ozone are 1.4 ± 0.7 ×10 <sup>–4</sup> W m <sup>–2</sup> ppb (CH <sub>4</sub> ) <sup>–1</sup> , based on 0.14 W m <sup>–2</sup> forcing from a 1023 ppb (1850–2014) methane change ( [[#Thornhill--2021b|Thornhill et al., 2021b]] ). The contribution from stratospheric water vapour is 0.4 ± 0.4 ×10 <sup>–4</sup> W m <sup>–2</sup> ppb (CH <sub>4</sub> ) <sup>–1</sup> , based on 0.05 W m <sup>–2</sup> forcing from a 1137 ppb (1750–2019) methane change ( [[#7.3.2.6|Section 7.3.2.6]] ). Nitrous oxide (N <sub>2</sub> O) depletes upper stratospheric ozone (a positive forcing) and reduces the methane lifetime. In AR5 the methane lifetime effect was assessed to reduce methane concentrations by 0.36 ppb per ppb increase in N <sub>2</sub> O, with no assessment of the effective radiative forcing from ozone. This is now increased to –1.7 ppb methane per ppb N <sub>2</sub> O (based on a methane lifetime decrease of 4% ± 4% for a 55 ppb increase in N <sub>2</sub> O ( [[#Thornhill--2021b|Thornhill et al., 2021b]] ) and a radiative efficiency of 5.5 ± 0.4 ×10 <sup>–4</sup> W m <sup>–2</sup> ppb (N <sub>2</sub> O) <sup>–1</sup> through ozone ( [[#Thornhill--2021b|Thornhill et al., 2021b]] )). In summary, GWPs and GTPs for methane and nitrous oxide are slightly lower than in AR5 ( ''medium confidence'' ) due to revisions in their lifetimes and updates to their indirect chemical effects.

Methane can also affect the oxidation pathways of aerosol formation ( [[#Shindell--2009|Shindell et al., 2009]] ) but the available literature is insufficient to make a robust assessment of this. Hydrocarbon and molecular hydrogen oxidation also leads to tropospheric ozone production and change in methane lifetime ( [[#Collins--2002|Collins et al., 2002]] ; [[#Hodnebrog--2018|Hodnebrog et al., 2018]] ). For reactive species the emissions metrics can depend on where the emissions occur, and the season of emission ( [[#Aamaas--2016|Aamaas et al., 2016]] ; [[#Lund--2017|Lund et al., 2017]] ; [[#Persad--2018|Persad and Caldeira, 2018]] ). The AR5 included a contribution to the emissions metrics for ozone-depleting substances (ODSs) from the loss of stratospheric ozone. The assessment of ERFs from ODSs in ( [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] (Section 6.4.2) suggests the quantification of these terms may be more uncertain than the formulation in AR5 so these are not included here.

Oxidation of methane leads ultimately to the net production of atmospheric CO <sub>2</sub> ( [[#Boucher--2009|Boucher et al., 2009]] ). This yield is less than 100% (on a molar basis) due to uptake by soils and some of the reaction products (mainly formaldehyde) being directly removed from the atmosphere before being completely oxidized. Estimates of the yield are 61% ( [[#Boucher--2009|Boucher et al., 2009]] ) and 88% ( [[#Shindell--2017|Shindell et al., 2017]] ), so the assessed range is 50–100% with a central value of 75% ( ''low confidence'' ) ''.'' For methane and hydrocarbons from fossil sources, this will lead to additional fossil CO <sub>2</sub> in the atmosphere whereas for biogenic sources of methane or hydrocarbons, this replaces CO <sub>2</sub> that has been recently removed from the atmosphere. Since the ratio of molar masses is 2.75, 1 kg of methane generates 2.1 ± 0.7 kgCO <sub>2</sub> for a 75% yield. For biogenic methane the soil uptake and removal of partially oxidized products is equivalent to a sink of atmospheric CO <sub>2</sub> of 0.7 ± 0.7 kg per kg methane. The contributions of this oxidation effect to the methane metric values allow for the time delay in the oxidation of methane. Methane from fossil fuel sources has therefore slightly higher emissions metric values than those from biogenic sources ( ''high confidence'' ). The CO <sub>2</sub> can already be included in carbon emissions totals ( [[#Muñoz--2016|Muñoz and Schmidt, 2016]] ) so care needs to be taken when applying the fossil correction to avoid double counting.

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==== 7.6.1.4 Comparing Long-lived with Short-lived Greenhouse Gases ====

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Since AR5 there have been developments in how to account for the different behaviours of short-lived and long-lived compounds. Pulse-based emissions metrics for short-lived GHGs with lifetimes less than 20 years are very sensitive to the choice of time horizon (e.g., [[#Pierrehumbert--2014|Pierrehumbert, 2014]] ). Global surface temperature changes following a pulse of CO <sub>2</sub> emission are roughly constant in time (the principle behind TCRE; [[IPCC:Wg1:Chapter:Chapter-5#5.5.1|Section 5.5.1]] and Figure 7.21b) whereas the temperature change following a pulse of short-lived GHG emission declines with time. In contrast to a one-off pulse, a step change in short-lived GHG emissions that is maintained indefinitely causes a concentration increase that eventually equilibrates to a steady state in a way that is more comparable to a pulse of CO <sub>2</sub> . Similarly the resulting change in global surface temperature from a step change in short-lived GHGs (Figure 7.21a) after a few decades increases only slowly (due to accumulation of heat in the deep ocean) and hence its effects are more similar to a pulse of CO <sub>2</sub> ( [[#Smith--2012|Smith et al., 2012]] ; [[#Lauder--2013|Lauder et al., 2013]] ; [[#Allen--2016|Allen et al., 2016]] , 2018b). The different time dependence of short-lived and long-lived compounds can be accounted for exactly with the CO <sub>2</sub> forcing equivalent metric ( [[#Wigley--1998|Wigley, 1998]] ; [[#Allen--2018b|Allen et al., 2018b]] ; [[#Jenkins--2018|Jenkins et al., 2018]] ) that produces a CO <sub>2</sub> emissions time profile such that the radiative forcing matches the time evolution of that from the non-CO <sub>2</sub> emissions. But other metric approaches can approximate this exact approach.

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[[File:4392da8f1bc131e9b8e504983581c657 IPCC_AR6_WGI_Figure_7_21.png]]

'''Figure 7.21''' '''|''' '''Emissions metrics for two short-lived greenhouse gases: HFC-32 and methane (CH''' <sub>4</sub> '''; lifetimes of 5.4 and 11.8 years).''' The temperature response function comes from Supplementary Material 7.SM.5.2. Values for non-CO <sub>2</sub> species include the carbon cycle response ( [[#7.6.1.3|Section 7.6.1.3]] ). Results for HFC-32 have been divided by 100 to show on the same scale. '''(a)''' Temperature response to a step change in short-lived greenhouse gas emissions. '''(b)''' Temperature response to a pulse CO <sub>2</sub> emission. '''(c)''' Conventional GTP metrics (pulse vs pulse). '''(d)''' Combined GTP metric (step versus pulse). Further details on data sources and processing are available in the chapter data table (Table 7.SM.14).

The similarity in behaviour of step changes in short-lived GHG emissions and pulses of CO <sub>2</sub> emissions has recently been used to formulate new emissions metric concepts ( [[#Collins--2020|Collins et al., 2020]] ). For short-lived GHGs, these new concepts use a step change in the rate of emissions, in contrast to an instantaneous pulse in a given year that is typically used (e.g., [[#Myhre--2013b|Myhre et al., 2013b]] ). Metrics for step emissions changes are denoted here by a superscript ‘ <sup>S</sup> ’ (e.g., ''AGT'' ''P'' <sup>S</sup> X is the absolute global surface temperature-change potential from a unit step change in emissions of species “ ''X'' ”). These can be derived by integrating the more standard pulse emission changes up to the time horizon. The response to a step emissions change is therefore equivalent to the integrated response to a pulse emission ( ''AGT'' ''P'' <sup>S</sup> X = ''iAGT'' ''P'' X ); and the radiative forcing response to a step emissions change ''AGF'' ''P'' <sup>S</sup> X is equivalent to the integrated forcing response ''iAGF'' ''P'' X which is the AGWP. The step metric for short-lived GHGs can then be compared with the pulse metric for CO <sub>2</sub> in a ratio ''AGT'' ''P'' <sup>S</sup> X / ''AGT'' ''P'' CO 2 ( [[#Collins--2020|Collins et al., 2020]] ). This is referred to as a combined GTP (CGTP) in [[#Collins--2020|Collins et al. (2020)]] , and has units of years (the standard GTP is dimensionless). This CGTP shows less variation with time than the standard GTP (comparing Figure 7.21c with Figure 7.21d) and provides a scaling for comparing a change in emissions rate (in kg yr <sup>–1</sup> ) of short-lived GHGs with a pulse emission or change in cumulative CO <sub>2</sub> emissions (in kg). Cumulative CO <sub>2</sub> equivalent emissions are given by CGTP × emissions rate of short-lived GHGs. The CGTP can be calculated for any species, but it is least dependent on the chosen time horizon for species with lifetimes less than half the time horizon of the metric ( [[#Collins--2020|Collins et al., 2020]] ). Pulse-step metrics can therefore be useful where time dependence of pulse metrics, like GWP or GTP, complicates their use (see Box 7.3).

For a stable global warming from non-CO <sub>2</sub> climate agents (gas or aerosol) their effective radiative forcing needs to gradually decrease ( [[#Tanaka--2018|Tanaka and O’Neill, 2018]] ). [[#Cain--2019|Cain et al. (2019)]] find this decrease to be around 0.3% yr <sup>–1</sup> for the climate response function in AR5 ( [[#Myhre--2013b|Myhre et al., 2013b]] ). To account for this, a quantity referred to as GWP* has been defined that combines emissions (pulse) and changes in emissions levels (step) approaches ( [[#Cain--2019|Cain et al., 2019]] ; [[#Smith--2021|Smith et al., 2021]] ). <sup>[[#footnote-000|2]]</sup> The emissions component accounts for the need for emissions to decrease to deliver a stable warming. The step (sometimes referred to as flow or rate) term in GWP* accounts for the change in global surface temperature that arises from a change in short-lived GHG emissions rate, as in CGTP, but here approximated by the change in emissions over the previous 20 years.

Cumulative CO <sub>2</sub> emissions and GWP*-based cumulative CO <sub>2</sub> equivalent GHG emissions multiplied by TCRE closely approximate the global warming associated with emissions time series (of CO <sub>2</sub> and GHG, respectively) from the start of the time series ( [[#Lynch--2020|Lynch et al., 2020]] ). Both the CGTP and GWP* convert short-lived GHG emissions rate changes into cumulative CO <sub>2</sub> equivalent emissions, hence scaling these by TCRE gives a direct conversion from short-lived GHG emissions to global surface temperature change. By comparison expressing methane emissions as CO <sub>2</sub> equivalent emissions using GWP-100 overstates the effect of constant methane emissions on global surface temperature by a factor of 3–4 ( [[#Lynch--2020|Lynch et al., 2020]] , their Figure 5), while understating the effect of any new methane emission source by a factor of 4–5 over the 20 years following the introduction of the new source ( [[#Lynch--2020|Lynch et al., 2020]] , their Figure 4).

Figure 7.22 explores how cumulative CO <sub>2</sub> equivalent emissions estimated for methane vary under different emissions metric choices and how estimates of the global surface air temperature (GSAT) change deduced from these cumulative emissions compare to the actual temperature response computed with the two-layer emulator. Note that GWP and GTP metrics were not designed for use under a cumulative carbon dioxide equivalent emissions framework ( [[#Shine--1990|Shine et al., 1990]] , 2005), even if they sometimes are (e.g., [[#Cui--2017|Cui et al., 2017]] ; [[#Howard--2018|Howard et al., 2018]] ) and analysing them in this way can give useful insights into their physical properties. Using these standard metrics under such frameworks, the cumulative CO <sub>2</sub> equivalent emissions associated with methane emissions would continue to rise if methane emissions were substantially reduced but remained above zero. In reality, a decline in methane emissions to a smaller but still positive value could cause a declining warming. GSAT changes estimated with cumulative CO <sub>2</sub> equivalent emissions computed with GWP-20 matches the warming trend for a few decades but quickly overestimates the response. Cumulative emissions using GWP-100 perform well when emissions are increasing but not when they are stable or decreasing. Cumulative emissions using GTP-100 consistently underestimate the warming. Cumulative emissions using either CGTP or GWP* approaches can more closely match the GSAT evolution ( [[#Allen--2018b|Allen et al., 2018b]] ; [[#Cain--2019|Cain et al., 2019]] ; [[#Collins--2020|Collins et al., 2020]] ; [[#Lynch--2020|Lynch et al., 2020]] ).

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[[File:edc4d79264e4f65065419bb746d8b187 IPCC_AR6_WGI_Figure_7_22.png]]

'''Figure 7.22''' '''|''' '''Explores how cumulative carbon dioxide equivalent emissions estimated for methane vary under different emissions metric choices and how estimates of the global surface air temperature (GSAT) change deduced from these cumulative emissions compare to the actual temperature response computed with the two-layer emulator (solid black lines).''' Panels '''(a)''' and '''(b)''' show the SSP4-6.0 and SSP1-2.6 scenarios respectively. The panels show annual methane emissions as the dotted lines (left axis) from 1750 to 2100. The solid lines can be read as either estimates of GSAT change or estimates of the cumulative carbon dioxide equivalent emissions. This is because they are related by a constant factor, the TCRE. Thus, values can be read using either of the right-hand axes. Emissions metric values are taken from Table 7.15. The GWP* calculation is given in ( [[#7.6.1.4|Section 7.6.1.4]] . The two-layer emulator has been calibrated to the central values of the Report’s assessment (see Supplementary Material 7.SM.5.2). Further details on data sources and processing are available in the chapter data table (Table 7.SM.14).

In summary, new emissions metric approaches such as GWP* and CGTP are designed to relate emissions changes in short-lived GHGs to emissions of CO <sub>2</sub> as they better account for the different physical behaviours of short- and long-lived gases. Through scaling the corresponding cumulative CO <sub>2</sub> equivalent emissions by the TCRE, the GSAT response from emissions over time of an aggregated set of gases can be estimated. Using either these new approaches, or treating short- and long-lived GHG emissions pathways separately, can improve the quantification of the contribution of emissions to global warming within a cumulative emissions framework, compared to approaches that aggregate emissions of GHGs using standard CO <sub>2</sub> equivalent emissions metrics. As discussed in Box 7.3, there is ''high confidence'' that multi-gas emissions pathways with the same time-dependence of aggregated CO <sub>2</sub> equivalent emissions estimated from standard approaches, such as weighting emissions by their GWP-100 values, rarely lead to the same estimated temperature outcomes.

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==== 7.6.1.5 Emissions Metrics by Compounds ====

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Emissions metrics for selected compounds are presented in Table 7.15, with further compounds presented in the Supplementary Material, Table 7.SM.7. The evolution of the CO <sub>2</sub> concentrations in response to a pulse emission is as in AR5 ( [[#Joos--2013|Joos et al., 2013]] ; [[#Myhre--2013b|Myhre et al., 2013b]] ), the perturbation lifetimes for CH <sub>4</sub> and N <sub>2</sub> O are from ( [[#7.6.1.1|Section 7.6.1.1]] . The lifetimes and radiative efficiencies for halogenated compounds are taken from [[#Hodnebrog--2020a|Hodnebrog et al. (2020a)]] . Combined metrics (CGTPs) are presented for compounds with lifetimes less than 20 years. Note that CGTP has units of years and is applied to a change in emissions rate rather than a change in emissions amount. Changes since AR5 are due to changes in radiative properties and lifetimes ( [[#7.6.1.1|Section 7.6.1.1]] ), and indirect contributions ( [[#7.6.1.3|Section 7.6.1.3]] ). Table 7.15 also gives overall emissions uncertainties in the emissions metrics due to uncertainties in radiative efficiencies, lifetimes and the climate response function (Supplementary Material, Tables 7.SM.8 to 7.SM.13).

Following their introduction in AR5 the assessed metrics now routinely include the carbon cycle response for non-CO <sub>2</sub> gases ( [[#7.6.1.3|Section 7.6.1.3]] ). As assessed in this earlier section, the carbon cycle contribution is lower than in AR5. Contributions to CO <sub>2</sub> formation are included for methane depending on whether or not the source originates from fossil carbon, thus methane from fossil fuel sources has slightly higher emissions metric values than that from non-fossil sources.

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'''Box 7.3 | Physical Considerations in Emissions Metric Choice'''

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Following AR5, this Report does not recommend an emissions metric because the appropriateness of the choice depends on the purposes for which gases or forcing agents are being compared. Emissions metrics can facilitate the comparison of effects of emissions in support of policy goals. They do not define policy goals or targets but can support the evaluation and implementation of choices within multi-component policies (e.g., they can help prioritize which emissions to abate). The choice of metric will depend on which aspects of climate change are most important to a particular application or stakeholder and over which time horizons. Different international and national climate policy goals may lead to different conclusions about what is the most suitable emissions metric ( [[#Myhre--2013b|Myhre et al., 2013b]] ).

Global warming potentials (GWP) and global temperature-change potentials (GTP) give the relative effect of pulse emissions, that is, how much more energy is trapped (GWP) or how much warmer (GTP) the climate would be when unit emissions of different compounds are compared ( [[#7.6.1.2|Section 7.6.1.2]] ). Consequently, these metrics provide information on how much energy accumulation (GWP) or how much global warming (GTP) could be avoided (over a given time period, or at a given future point in time) by avoiding the emission of a unit of a short-lived greenhouse gas compared to avoiding a unit of CO <sub>2</sub> . By contrast, the new metric approaches of combined GTP (CGTP) and GWP* closely approximate the additional effect on climate from a time series of short-lived GHG emissions, and can be used to compare this to the effect on temperature from the emission or removal of a unit of CO <sub>2</sub> [[#7.6.1.4|Section 7.6.1.4]] ; [[#Allen--2018b|Allen et al., 2018b]] ; [[#Collins--2020|Collins et al., 2020]] ).

Box 7.3

If global surface temperature stabilization goals are considered, cumulative CO <sub>2</sub> equivalent emissions computed with the GWP-100 emissions metric would continue to rise when short-lived GHG emissions are reduced but remain above zero (Figure 7.22b). Such a rise would not match the expected global surface temperature stabilization or potential decline in warming that comes from a reduction in emissions of short-lived greenhouse gases ( [[#Pierrehumbert--2014|Pierrehumbert, 2014]] ; [[#Allen--2018b|Allen et al., 2018b]] ; [[#Cain--2019|Cain et al., 2019]] ; [[#Collins--2020|Collins et al., 2020]] ; [[#Lynch--2020|Lynch et al., 2020]] , 2021). This is relevant to net zero GHG emissions goals ( [[#7.6.2|Section 7.6.2]] and Box 1.4).

When individual gases are treated separately in climate model emulators (Cross-Chapter Box 7.1), or weighted and aggregated using an emissions metric approach (such as CGTP or GWP*) which translate the distinct behaviour from cumulative emissions of short-lived gases, ambiguity in the future warming trajectory of a given emissions scenario can be substantially reduced ( [[#Cain--2019|Cain et al., 2019]] ; [[#Denison--2019|Denison et al., 2019]] ; [[#Collins--2020|Collins et al., 2020]] ; [[#Lynch--2021|Lynch et al., 2021]] ). The degree of ambiguity varies with the emissions scenario. For mitigation pathways that limit warming to 2°C with an even chance, the ambiguity arising from using GWP-100 as sole constraint on emissions of a mix of greenhouse gases (without considering their economic implications or feasibility) could be as much as 0.17°C, which represents about one-fifth of the remaining global warming in those pathways ( [[#Denison--2019|Denison et al., 2019]] ). If the evolution of the individual GHGs is not known, this can make it difficult to evaluate how a given global multi-gas emissions pathway specified only in CO <sub>2</sub> equivalent emissions would achieve (or not) global surface temperature goals. This is potentially an issue as Nationally Determined Contributions frequently make commitments in terms of GWP-100-based CO <sub>2</sub> equivalent emissions at 2030 without specifying individual gases ( [[#Denison--2019|Denison et al., 2019]] ). Clear and transparent representation of the global warming implications of future emissions pathways including Nationally Determined Contributions could be achieved either by their detailing pathways for multiple gases or by detailing a pathway of cumulative carbon dioxide equivalent emissions approach aggregated across GHGs evaluated by either GWP* or CGTP metric approaches ( [[#Cain--2019|Cain et al., 2019]] ; [[#Collins--2020|Collins et al., 2020]] ; [[#Lynch--2021|Lynch et al., 2021]] ). It should be noted that although the Paris Agreement Rulebook asks countries to report emissions of individual GHGs separately for the global stocktake (Decision 18/CMA.1, annex, paragraph 38), which can allow the current effects of their emissions on global surface temperature to be accurately estimated, estimates of future warming are potentially ambiguous where emissions are aggregated using GWP-100 or other pulse metrics.

Although there is significant history of using single-basket approaches, supported by emissions metrics such as GWP-100, in climate policies such as the Kyoto Protocol, multi-basket approaches also have many precedents in environmental management, including the Montreal Protocol ( [[#Daniel--2012|Daniel et al., 2012]] ). Further assessment of the performance of physical and economics-based metrics in the context of climate change mitigation is provided in the contribution of Working Group III to AR6.

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=== 7.6.2 Applications of Emissions Metrics ===

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One prominent use of emissions metrics is for comparison of efforts measured against climate change goals or targets. One of the most commonly discussed goals is in Article 2 of the Paris Agreement which aims to limit the risks and impacts of climate change by setting temperature goals. In addition, the Paris Agreement has important provisions which relate to how the goals are to be achieved, including making emissions reductions in a manner that does not threaten food production (Article 2), an early emissions peaking target, and the aim to ‘achieve a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century’ (Article 4). Article 4 also contains important context regarding international equity, sustainable development, and poverty reduction. Furthermore, the United Nations Framework Convention on Climate Change (UNFCCC) sets out as its ultimate objective, the ‘stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system.’

How the interpretation of the Paris Agreement and the meaning of ‘net zero’ emissions, reflects on the appropriate choice of metric is an active area of research ( [[#Schleussner--2016|Schleussner et al., 2016]] , 2019; [[#Fuglestvedt--2018|Fuglestvedt et al., 2018]] ; [[#Collins--2020|Collins et al., 2020]] ). Several possible scientific interpretations of the Article 2 and 4 goals can be devised, and these, along with emissions metric choice, have implications both for when a balance in GHG emissions, net zero CO <sub>2</sub> emissions or net zero GHG emissions are achieved, and for their meaning in terms of temperature outcome ( [[#Fuglestvedt--2018|Fuglestvedt et al., 2018]] ; [[#Rogelj--2018|Rogelj et al., 2018]] ; [[#Wigley--2018|Wigley, 2018]] ). In AR6 net zero GHG emissions is defined as the condition in which metric-weighted anthropogenic GHG emissions are balanced by metric-weighted anthropogenic GHG removals over a specified period (see Box 1.4 and Appendix VII: Glossary). The quantification of net zero GHG emissions depends on the GHG emissions metric chosen to compare emissions and removals of different gases, as well as the time horizon chosen for that metric. As the choice of emissions metric affects the quantification of net zero GHG emissions, it therefore affects the resulting temperature outcome after net zero emissions are achieved ( [[#Lauder--2013|Lauder et al., 2013]] ; [[#Rogelj--2015|Rogelj et al., 2015]] ; [[#Fuglestvedt--2018|Fuglestvedt et al., 2018]] ; [[#Schleussner--2019|Schleussner et al., 2019]] ). [[#Schleussner--2019|Schleussner et al. (2019)]] note that declining temperatures may be a desirable outcome of net zero. [[#Rogelj--2019|Rogelj and Schleussner (2019)]] also point out that the use of physical metrics raises questions of equity and fairness between developed and developing countries.

Based on SR1.5 ( [[#Allen--2018a|Allen et al., 2018a]] ), there is ''high confidence'' that achieving net zero CO <sub>2</sub> emissions and declining non-CO <sub>2</sub> radiative forcing would halt human-induced warming. Based on ( [[#Bowerman--2013|Bowerman et al., 2013]] ; [[#Pierrehumbert--2014|Pierrehumbert, 2014]] ; [[#Fuglestvedt--2018|Fuglestvedt et al., 2018]] ; [[#Tanaka--2018|Tanaka and O’Neill, 2018]] ; [[#Schleussner--2019|Schleussner et al., 2019]] ) there is also ''high confidence'' that reaching net zero GHG emissions as quantified by GWP-100 typically leads to reductions from peak global surface temperature after net zero GHGs emissions are achieved, depending on the relative sequencing of mitigation of short-lived and long-lived species. If both short- and long-lived species are mitigated together, then temperatures peak and decline. If mitigation of short-lived species occurs much earlier than that of long-lived species, then temperatures stabilize very near peak values, rather than decline. Temperature targets can be met even with positive net GHG emissions based on GWP-100 ( [[#Tanaka--2018|Tanaka and O’Neill, 2018]] ). As demonstrated by [[#Allen--2018b|Allen et al. (2018b)]] , [[#Cain--2019|Cain et al. (2019)]] , [[#Schleussner--2019|Schleussner et al. (2019)]] and [[#Collins--2020|Collins et al. (2020)]] reaching net zero GHG emissions when quantified using the new emissions metric approaches such as CGTP or GWP* would lead to an approximately similar temperature evolution as achieving net zero CO <sub>2</sub> . Hence, net zero CO <sub>2</sub> and net zero GHG, quantified using these new approaches, would both lead to approximately stable contributions to temperature change after net zero emissions are achieved ( ''high confidence'' ).

Comparisons with emissions or global surface temperature stabilization goals are not the only role for emissions metrics. Other important roles include those in pricing approaches where policymakers choose to compare short-lived and long-lived climate forcers (e.g., [[#Manne--2001|Manne and Richels, 2001]] ), and in life cycle analyses (e.g., [[#Hellweg--2014|Hellweg and Milà i Canals, 2014]] ). Several papers have reviewed the issue of metric choice for life cycle analyses, noting that analysts should be aware of the challenges and value judgements inherent in attempting to aggregate the effects of forcing agents with different time scales onto a common scale (e.g., [[#Mallapragada--2017|Mallapragada and Mignone, 2017]] ) and recommend aligning metric choice with policy goals as well as testing sensitivities of results to metric choice ( [[#Cherubini--2016|Cherubini et al., 2016]] ). Furthermore, life cycle analyses approaches which are sensitive to choice of emissions metric benefit from careful communication of the reasons for the sensitivity ( [[#Levasseur--2016|Levasseur et al., 2016]] ).

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