The question of whether post project sustainability was being measured was based on the first tranche of projects and on the sustainability analysis in which they were included. Most of the documents cited in the sustainability analysis were either terminal or impact evaluations focused on efficiency (GEF IEO, 2019a), and most of the documents and report analysis focused on estimated sustainability. Of the 53 “postcompletion verification reports,” as they are referred to in the review (GEF IEO, 2019a, p. 62), we found only 4% to contain adequate information to support the analysis of sustainability. Our wider search for publicly available post project evaluations, which would have constituted an evidence base for sustained outcomes and environmental stress reduction and adoption cited in the GEF IEO 2019 analysis, did not identify any post project evaluations. We were unable to replicate the finding that “84% of these projects that were rated as sustainable at closure also had satisfactory postcompletion outcomes. . . . Most projects with satisfactory outcome ratings at completion continued to have satisfactory outcome ratings at postcompletion” (GEF IEO, 2019a, p. 3) or to compare the CCM subset of projects with this conclusion. The report stated that “the analysis of the 53 selected projects is based on 61 field verification reports. For 81 percent of the projects, the field verification was conducted at least four years after implementation completion [emphasis added].” However, we found no publicly accessible documentation that could be used to confirm the approach to field verification for 8 of the 17 projects.
Similarly, the available documentation for the projects lacked the most typical post project hallmarks, such as methods of post project data collection, comparisons of changes from final to post project outcomes and impacts at least 2 years post closure, and tracing contribution of the project at the funded sites to the changes. Documentation focused on a rating of estimated sustainability with repeated references to only the terminal evaluations and closure reports. In summary, of the 17 projects selected for review in the first tranche, 14 had data consisting of terminal evaluations, and none was 2–20 years post closure. We did not find publicly available evidence to support measurement of post project sustainability other than statements that such evidence was gathered in a handful of cases. Of the pool of 17 projects, only two (both from India) made any reference to post project data regarding the sectors of activity in subsequent years. However, these two were terminal evaluations within a country portfolio review and could not be substantiated with publicly accessible data.
We then screened the first tranche of projects using the Valuing Voices evaluability checklist (Zivetz et al., 2017b):
High-quality project data at least at terminal evaluation, with verifiable data at exit: Of 14 projects rated for sustainability, only six were rated likely to be sustained and outcome and impact data were scant.
Clear ex-post methodology, sufficient samples: None of the evaluations available was a post project evaluation of sustainability or long-term impact. Although most projects fell within the evaluable 2–20 years post project (the projects had been closed 4–20 years), none had proof of return evaluation. There were no clear post project sampling frames, data collection processes including identification of beneficiaries/informants, site selection, isolating legacy effects of the institution or other concurrent projects, or analytic methods.
Transparent benchmarks based on terminal, midterm, and/or baseline data on changes to outcomes or impacts: M&E documents show measurable targets and indicators, baseline vs. terminal evaluations with methods that are comparable to methods used in the post project period: For some of the 17 projects, project inception documents and terminal evaluations were available; in other cases, GEF evaluation reviews were available. Two had measurable environmental indicators that compared baseline to final, but none were after project closure.
Substantiated contribution vs. attribution of impacts: Examples of substantiated contribution were not identified.
Evaluation reports revealed several instances for which we could not confirm attribution. For example, evaluation of the project Development of High Rate BioMethanation Processes as Means of Reducing Greenhouse Gas Emissions (GEF ID 370), which closed in 2005, referenced the following subsequent market information:
As of Nov 2012, capacity installed from waste-to-energy projects running across the country for grid connected and captive power are 93.68MW and 110.74 MW respectively [versus 3.79KW from 8 sub-projects and 1-5 MW projects]. . . . The technologies demonstrated by the 16 sub-projects covered under the project have seen wide-scale replication throughout the country. . . . An installed capacity of 201.03MW within WTE [waste to energy] projects and the 50% of this is attributed to the GEF project. (GEF IEO, 2013, vol. 2, p. 64)
Claims of “the technical institutes strengthened as a result of the project were not fully effective at the time of project completion but are now actively engaged in the promotion of various biomethanation technologies” are unsubstantiated in publicly available information; as a result, the ex-post methods of contribution/attribution data are not clear. Another project in India, Optimizing Development of Small Hydel [hydroelectric] Resources in Hilly Areas (GEF ID 386), projected that later investments in the government’s 5-year plans would happen, and the resulting hydropower production would be attributable to the original project (GEF IEO, 2013); again, this attributional analysis was not documented. Analysis of a third project in India, Coal Bed Methane Capture and Commercial Utilization (GEF ID 325), which closed in 2008, claimed results that could not be reproduced: “Notable progress has been made through replication of projects, knowledge sharing, and policy development” and “expertise was built” (GEF IEO, 2013, Vol. 2, p. 90). Further claims that the project contributed to “the total coal bed methane production in the country and has increased to 0.32 mmscmd [million metric standard cubic meters per day], which is expected to rise to 7.4 mmscmd by the end of 2014” is without proof. The evaluation reported estimates of indirect GHG emission reduction, based on postcompletion methane gas production estimates of 0.2 million m3 per day:
1.0 Million tons equivalent per year, considering an adjustment factor of 0.5 as the GEF contribution [emphasis added], the indirect GHG emission reduction due to the influence of the project is estimated to be 0.5 million tons of CO2 equivalent per annum (2.5 million tons over the lifetime period of 5 years). (GEF IEO, 2013, Vol. 2, p. 91)
Yet without verification of coal bed methane capture and commercial utilization continuing, this impact cannot be claimed.
How Is Sustainability Being Captured?
Fifteen of the 17 CCM projects we reviewed in the first tranche were rated on a 4-point scale at terminal evaluation. Of those 15, 12 had overall ratings of either satisfactory or marginally satisfactory, and one highly satisfactory overall. Eleven of the sustainability ratings were either likely or marginally likely. Only two projects were rated marginally unlikely overall or for sustainability, and only one project received marginally unlikely in both categories (the Demand Side Management Demonstration energy conservation project that ended in 1999 [GEF ID 64]). Although none of the documents mentioned outcome indicators, eight of the 17 rated estimated CO2 direct and indirect impacts.
In the second pool of projects—the CCM subset of the 2019 cohort—63% of the projects were rated in the likely range for sustainability (n = 22; nine were rated likely and 13 marginally likely). This is slightly higher than the 2019 cohort as a whole, in which 59% were rated in the likely range. In turn, the 2019 annual performance report noted that “the difference between the GEF portfolio average and the 2019 cohort is not statistically significant for both outcome and sustainability rating” (GEF IEO, 2020, p. 9). It is slightly lower than the percentage of CCM projects receiving an overall rating of marginally likely or higher in the 2017 portfolio review (68%, n = 265; GEF IEO, 2017, p. 78).
In this second set of projects, only two received a rating of marginally unlikely and only one received a sustainability rating of unlikely. The remainder of the projects could not be classified using the 4-point rating scale, either because they had used an either/or estimate (one project), a 5-point scale (one project), or an estimate based on the assessment of risks to development outcome (two projects). Six projects or could not be assessed due to the absence of a publicly accessible terminal evaluation in the GEF and implementing agency archives.
How Effectively Is Sustainability Being Captured?
Throughout the first set of reports on which the sustainability was claimed, “84% of these projects that were rated as sustainable at closure also had satisfactory postcompletion outcomes, as compared with 55% percent of the unsustainable projects” (GEF IEO, 2019a, p. 29). The data did not support the claim, even during implementation.
As a Brazilian project (GEF ID 2941) showed, sustainability is unlikely when project achievements are weak, and exit conditions and benchmarks need to be clear: The exit strategy provided by IDB Invest77 is essentially based on financial-operational considerations but does not provide answers to the initial questions how an EEGM [energy efficiency guarantee mechanism] should be shaped in Brazil, how relevant it is and for whom, and to whom the EEGM should be handed over (p. 25).
In Russia, the terminal evaluation for an energy efficiency project (GEF ID 292) cited project design flaws that seemed to belie its sustainability rating of likely: “From a design-for-replication point of view the virtually 100% grant provided by the GEF for project activities is certainly questionable” (Global Environment Facility Evaluation Office [GEF EO], 2008, p. 20). Further, the assessment that “the project is attractive for replication, dissemination of results has been well implemented, and the results are likely to be sustainable [emphasis added] for the long-term, as federal and regional legislation support is introduced” (GEF EO, 2008, p. 39), makes a major assumption regarding changes in the policy environment. (In fact, federal legislation was introduced 2 years post project, and the extent of enforcement would require examination.)
A Pacific regional project (GEF ID 1058) was rated as likely to be sustained, but its report notes that it “does not provide overall ratings for outcomes, risks to sustainability, and M&E” (p. 1).
The Renewable Development Energy project in China (GEF ID 446) that closed in 2007 was evaluated in 2009 (not post project, but a delayed final evaluation). The report considered the project sustainable with a continued effort to support off-grid rural electrification, claiming, “the market is now self-sustaining, and thus additional support is not required” (p. 11). The project estimated avoided CO2 emissions and cited 363% as achieved; however, calculations were based on 2006 emissions values for thermal power sector and data from all wind farms in China, without a bottom-up estimate. The interpolation of this data lacks verification.
Similar sampling issues emerge in a project in Mexico (GEF ID 643): “A significant number of farmers . . . of an estimated 2,312 farmers who previously had had no electricity” (p. 20) saw their productivity and incomes increase as a result of their adoption of productive investments (e.g., photovoltaic-energy water-pumping systems and improved farming practices). A rough preliminary estimate is extrapolated from an evaluation of “three [emphasis added] beneficiary farms, leading to the conclusion that in these cases average on-farm increases in income more than doubled (rising by139%)” (p. 21).
Baseline to terminal evaluation comparisons were rare, with the exception of photovoltaic energy projects in China and Mexico, and none were post project. Two were mid-term evaluations, which could not assess final outcomes much less sustainability. Ex-post project evaluations far more typically focus on the contributions that projects made, because only in rare cases can the attribution be isolated, especially for a project pool, where the focus is often on creating an enabling environment reliant on a range of actors. One such example is the Indian energy efficiency project approved in 1998 (GEF ID 404), in which
the project resulted in a favorable environment for energy-efficiency measures and the sub-projects inspired many other players in similar industries to adopt the demonstrated technologies. Although quantitative data for energy saved by energy efficiency technologies in India is not available, it is evident that due to the change in policy and financial structure brought by this project, there is an increase in investment in energy efficiency technologies in the industries. (GEF IEO, 2013, Vol. 2., p. 95)
And while such GEF evaluators are asking for ex-post evaluation, in an earlier version of this book, Evaluating Climate Change Action for Sustainable Development (Uitto et al., 2017), the authors encouraged us to be “modest” in expectations of extensive ex-post evaluations and exploration of ex-post’s confirmatory power seemingly has not occurred:
The expectations have to be aligned with the size of the investment. The ex-post reconstruction of baselines and the assessment of quantitative results is an intensive and time-consuming process. If rigorous, climate change-related quantitative and qualitative data are not available in final reports or evaluations of the assessed projects, it is illusive to think that an assessment covering a portfolio of several hundred projects is able to fill that gap and to produce aggregated quantitative data, for example on mitigated GHG emissions. When producing data on proxies or qualitative assessments, the expectations must be realistic, not to say modest. (p. 89)
Following an analysis of the sustainability estimates in the first pool of projects, we screened project documentation and terminal evaluations for conditions that foster sustainability during planning, implementation, and exit. We also analyzed how well the projects reported on factors that could be measured in a post project evaluation and factors that would predispose projects to sustainability. These sustained impact conditions consisted of the following elements: (a) resources, (b) partnerships and local ownership, (c) capacity building, (d) emerging sustainability, (e) evaluation of risks and resilience, and (f) CO2 emissions (impacts).
Although documentation in evaluations did not verify sustainability, many examples exist of data collection that could support post project analyses of sustainability and sustained impacts in the future. Most reports cited examples of resources that had been generated, partnerships that had been fostered for local ownership and sustainability, and capacities that had been built through training. Some terminal evaluations also captured emerging impacts due to local efforts to sustain or extend impacts of the project that had not been anticipated ex-ante.
The Decentralized Power Generation project (GEF ID 4749) in Lebanon provides a good example of a framework to collect information on elements of sustainability planning at terminal (see Table 3).
Tangible examples of the above categories at terminal evaluations include the following.
The most widespread assumption for sustainability was sufficient financial and in-kind resources, often reliant on continued national investments or new private international investments, which could be verified. National resources that could sustain results include terminal evaluation findings such as:
Funding for fuel cell and electric vehicle development by the Chinese Government had increased from Rmb 60 million (for the 1996-2000 period) to more than Rmb 800 million (for the 2001-2005 period). More recently, policymakers have now targeted hydrogen commercialization for the 2010-2020 period. (GEF ID 445, p. 17)
Another example is: “About 65 percent of [Indian] small Hydro electromechanical Equipment is sourced locally” (GEF ID 386; GEF IEO, 2013, Vol.2, p. 76). The terminal evaluation of a global IFC project stated that “Moser Baer is setting up 30 MW solar power plants with the success of the 5 MW project. Many private sector players have also emulated the success of the Moser Baer project by taking advantage of JNNSM scheme” (GEF ID 112, p. 3).
Local Ownership and Partnerships
The Russian Market Transformation for EE Buildings project (GEF ID 3593) showed in its recommendation to governmental stakeholders that their ownership would be essential for sustainability, describing “a suitable governmental institution to take over the ownership over the project web site along with the peer-to-peer network ensuring the sustainability of the tools [to] support the sustainability of the project results after the project completion” (p. xi). An Indian project (GEF ID 386) noted how partnerships could sustain outcomes:
By 2001, 16 small hydro equipment manufacturers, including international joint ventures (compared to 10 inactive firms in 1991) were operational. . . . State government came up with policies with financial incentives and other promotional packages such as help in land acquisition, getting clearances, etc. These profitable demonstrated projects attracted private sector and NGOs to set up similar projects. (GEF IEO, 2013, Vol. 2, p. 74)
The Renewable Energy for Agriculture project in Mexico (GEF ID 643) established the “percentage of direct beneficiaries surveyed who learned of the equipment through FIRCO’s promotional activities” (86%), “number of replica renewable energy systems installed” (847 documented replicas), and “total number of technicians and extensionists trained in renewable energy technologies” (p. 33). This came to 3022, or 121% of the original goal of 2500, which provides a good measure of how the project exceeded this objective.
Recent post project evaluations also address what emerged after the project that was unrelated to the existing theory of change. These emerging findings are rarely documented in terminal evaluations, but some projects in the first pool included information about unanticipated activities or outcomes at terminal evaluation, and these could be used for future post project fieldwork follow-up. As a consequence of the hydroelectric resource project, for example, the Indian Institute “developed and patented the designs for water mills” (GEF ID 386; GEF IEO, 2013, Vol. 2, p. 73). The terminal evaluation for another project stated that “following the UNDP-GEF project, the MNRE [Ministry of New and Renewable Energy] initiated its own programs on energy recovery from waste. Under these programs, the ministry has assisted 14 projects with subsidies of US$ 2.72 million” (GEF ID 370; GEF IEO, 2013, Vol. 2, p. 62).
Benchmarks, Risks, and Resilience
As the GEF’s 2019 report itself noted, “The GEF could strengthen its approach to assessing sustainability further by explicitly addressing resilience” (GEF IEO, 2019a, p. 33). Not doing so is a risk, as our climate changes. Two evaluations noted “no information on environmental risks to project sustainability;” these were the Jamaican pilot on Removal of Barriers to Energy Efficiency and Energy Conservation (GEF ID 64; p. 68) and a Pacific regional project (GEF ID 1058). For likelihood of sustainability, the Jamaican project was rated moderately unlikely and the Pacific Islands project was rated likely but “does not provide overall ratings for outcomes, risks to sustainability, and M&E” other than asserting that
the follow-up project, which has been approved by the GEF, will ensure that the recommendations entailed in the documents prepared as part of this project are carried out. Thus, financial risks to the benefits coming out of the project are low. (p. 3)
Greenhouse Gas Emissions (Impacts)
In GEF projects, timeframe is an important issue, which makes post project field verification that much more important. As the GEF IEO stated in 2018, “Many environmental results take more than a decade to manifest. Also, many environmental results of GEF projects may be contingent on future actions by other actors.” (GEF IEO, 2018, p. 34).
Uncertainty and Likelihood Estimates
Estimating the likelihood of sustainability of greenhouse gas emissions at terminal evaluation raises another challenge: the relatively high level of uncertainty concerning the achievement of project impacts related to GHG reduction. GHG reductions are the primary objective stated in the climate change focal area, and they appear as a higher level impact across projects regardless of the terminology used. For a global project on bus rapid transit and nonmotorized transport, the objective was to “reduce GHG emissions for transportation sector globally” (GEF ID 1917, p. 9). For a national project on building sector energy efficiency, the project goal was “the reduction in the annual growth rate of GHG emissions from the Malaysia buildings sector” (GEF ID 3598; Aldover & Tiong, 2017, p. i). For a land management project in Mexico, the project objective was to “mitigate climate change in the agricultural units selected . . . including the reduction of emissions by deforestation and the increase of carbon sequestration potential” (GEF ID 4149, p. 21). For a national project to phase out ozone-depleting substances, the project objective was to “reduce greenhouse gas emissions associated with industrial RAC (refrigeration and air conditioning) facilities in The Gambia” (GEF ID 5466, p. vii). Clearly, actual outcomes in GHG emissions need to be considered in any assessment of the likelihood of sustainability of outcomes.
Unlike projects in the carbon finance market, GEF projects estimate emissions for a project period that usually exceeds the duration of the GEF intervention. In most cases, ex-ante estimated GHG reductions in the post project period are larger than estimated GHG reductions during the project lifetime. In practice, this means that for projects for which the majority of emissions will occur after the terminal evaluation, evaluators are being asked to estimate the likelihood that benefits will not only continue, but will increase due to replication, market transformation, or changes in the technology or enabling environment. Table 4 provides several examples from the GEF 2019 cohort of how GHG reductions may be distributed over the project lifecycle.
The range in Table 4 shows the substantial variation in uncertainty when estimating the likelihood of long-term project impacts. For projects designed to achieve all of their emission reductions during their operational lifetimes, the achievement of GHG reductions can be verified as a part of the terminal evaluation. However, most projects assume that nearly all estimated GHG reductions will occur in the post project period, so uncertainty levels are much higher and estimates may be more difficult to compile. In other evaluations, evaluators may identify inconsistent GHG estimates (e.g., GEF ID 4157 and 5157), or recommend that the ex-ante estimates be downsized (e.g., GEF ID 3922, 4008, and 4160). These trends may also be difficult to capture in likelihood estimates.