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EMISSIONS GAP REPORT 2018 – BRIDGING THE GAP: THE ROLE OF NON-STATE AND SUBNATIONAL ACTORS


while other single initiative studies evaluate emissions savings relative to business-as-usual scenarios for the actor group, rather than comparing to a global scenario. Only some studies report a range of results that take into consideration assumptions such as a lower and upper range of results (We Mean Business, 2016; Graichen et al. 2017; Kuramochi et al., 2017; Roelfsema, 2017 and Data-Driven Yale, NewClimate Institute and PBL, 2018), and even fewer conduct sensitivity analysis.


Some reports, such as the U.S. Climate Alliance (2017) report analyzing 15 regions’ contributions to GHG reductions or the Nordic Council of Ministers’ report (Nordic Council of Ministers 2017), do not provide an aggregate quantified assessment of impact. They are therefore not included in table 5.2.


Studies included in table 5.2 all assume various baseline scenarios against which they assess additional impact of NSAs. These baseline scenarios range from study- specific “business as usual” or no-action scenarios, to “current policy scenarios” that take into account a range of existing government policies and pledges, to an “NDC scenario” that assumes that countries implement their NDCs under the Paris Agreement (table 5.2; Hsu et al., forthcoming). Consequently, it is challenging to compare the estimated impact across studies, although meta-analysis of methodologies applied in each study demonstrate similar approaches, including the use of the Greenhouse Gas Protocol standard for distinguishing between direct and indirect emissions (Hsu et al., forthcoming). Specifications of baseline scenarios by which to compare additional NSA contributions are also increasingly converging to common terminology and methods.


A major question with respect to NSA climate mitigation contribution is the extent to which they lead to emission reductions that are not accounted for in current national policies or in the NDCs. A limited number of the available studies assess NSA mitigation impact relative to global current policy and NDCs based on an assessment of overlap scenarios (see table 5.2). These quantitative assessments of overlap determine the ambition level of NSA commitments vis-à-vis current policy scenarios and NDC scenarios by comparing the rate of emissions decline in actors’ targets (Kuramochi et al., 2017). For instance, if a city’s emission reduction target results in a steeper rate of decline in overall emissions compared to a national government’s NDC, a common assumption is to consider the emissions reductions that are beyond what a national actor has pledged as “additional” reductions.


One analysis focused on the United States of America (Kuramochi et al., 2017), found that 17 states and 54 cities with recorded GHG mitigation commitments comprising 40 percent of national U.S. emissions were found to have the potential to meet almost half of the country’s NDC by 2025. Another study that quantified nearly 6,000 subnational and over 2,000 business commitments determined that emissions would be 0.2-0.7 GtCO2


(Data-DrivenYale, NewClimate Institute, and PBL, 2018, Figure 5.4).


e, as indicated in Table 5.2) compared to the full implementation of the unconditional NDCs.


Figures 5.4a and 5.4b illustrates the wide range of potential emission reductions estimated in various studies. The figure includes the studies from table 5.2 that have clear and comparable baseline scenario definitions by which to assess the magnitude of additional impact. An assessment of each of the studies’ baseline estimates was made to ensure their comparable to the Emissions Gap Report scenario values for 2030. Figure 5.4a includes estimates from studies that aggregate from a bottom-up method of pledged 2030 commitments made by individual actors. As this figure illustrates, the pledged 2030 contribution by NSAs, if fully realized, is estimated to lead to limited additional emission reductions (ranging from 3-700 MtCO2


Figure 5.4b includes estimates of scaled-up potential emission reductions based on an assessment of single initiative goals and multiple initiatives’ goals. These studies assume that all actors participating within their initiative fully implement and achieve the larger goal of an initiative and therefore represent “scaled-up” potential that is larger than the estimates in figure 5.4a. The studies behind the estimates in figure 5.4b apply a range of assumptions on how actions are expanded, from assuming that all members within a network will adopt an ICI’s ambitious emission reduction goal, to that membership will grow to a certain number of actors and cover a certain number of additional sectors.


The figure indicates that NSAs have the potential to contribute significantly to bridging the 2030 emissions gap, but that realizing this potential requires commitments and action that go far beyond current recorded and quantified individual actor pledges as well as single initiatives.


5.4.2 Tracking progress and results of non-state and subnational actors


Data limitations and gaps


As the previous sections illustrate, limited availability, consistency and comparability of data pose significant challenges to evaluating the potential NSA impact on climate mitigation and their other benefits. For instance, Bansard et al. (2016) found in their evaluation of cities participating in the C40 Cities for Climate Leadership Network that out of around 40 members evaluated, nine different base years with seven different target years were found, making an evaluation and comparison of targets and level of ambition difficult.


e/year lower in 2030 than with NDCs alone


Although Non-State Actor Zone for Climate Action (NAZCA) acts as an umbrella for various NSA climate action repositories, no comprehensive database of NSA actions exists, with each NSA adopting various criteria for inclusion that are often unclear or opaque (Widerberg and Stripple, 2016). The reported data are often not suited to calculating emissions impact, estimating overlap, or comparing NSA mitigation potential to the emissions scenarios of other actors, such as national governments.


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