Integrating uncertainty into public energy research and development decisions

Public energy research and development (R&D) is recognized as a key policy tool for transforming the world’s energy system in a cost-effective way. However, managing the uncertainty surrounding technological change is a critical challenge for designing robust and cost-effective energy policies. The design of such policies is particularly important if countries are going to both meet the ambitious greenhouse-gas emissions reductions goals set by the Paris Agreement and achieve the required harmonization with the broader set of objectives dictated by the Sustainable Development Goals. The complexity of informing energy technology policy requires, and is producing, a growing collaboration between different academic disciplines and practitioners. Three analytical components have emerged to support the integration of technological uncertainty into energy policy: expert elicitations, integrated assessment models, and decision frameworks. Here we review efforts to incorporate all three approaches to facilitate public energy R&D decision-making under uncertainty. We highlight emerging insights that are robust across elicitations, models, and frameworks, relating to the allocation of public R&D investments, and identify gaps and challenges that remain

Systematic assessment of the achieved emission reductions of carbon crediting projects

Carbon markets play an important role in firms’ and governments’ climate strategies. Carbon crediting mechanisms allow project developers to earn carbon credits through mitigation projects. Several studies have raised concerns about environmental integrity, though a systematic evaluation is missing. We synthesized studies relying on experimental or rigorous observational methods, covering 14 studies on 2346 carbon mitigation projects and 51 studies investigating similar field interventions implemented without issuing carbon credits. The analysis covers one-fifth of the credit volume issued to date, almost 1 billion tons of CO2e. We estimate that less than 16% of the carbon credits issued to the investigated projects constitute real emission reductions, with 11% for cookstoves, 16% for SF6 destruction, 25% for avoided deforestation, 68% for HFC-23 abatement, and no statistically significant emission reductions from wind power and improved forest management projects. Carbon crediting mechanisms need to be reformed fundamentally to meaningfully contribute to climate change mitigation

Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales

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Patenting and business outcomes for cleantech startups funded by the Advanced Research Projects Agency-Energy

Innovation to reduce the cost of clean technologies has large environmental and societal benefits. Governments can play an important role in helping cleantech startups innovate and overcome risks involved in technology development. Here we examine the impact of the US Advanced Research Projects Agency-Energy (ARPA-E) on two outcomes for startup companies: innovation (measured by patenting activity) and business success (measured by venture capital funding raised, survival, and acquisition or initial public offering). We compare 25 startups funded by ARPA-E in 2010 to rejected ARPA-E applicants, startups funded by a related government programme and other comparable cleantech startups. We find that ARPA-E awardees have a strong innovation advantage over all the comparison groups. However, while we find that ARPA-E awardees performed better than rejected applicants in terms of post-award business success, we do not detect significant differences compared to other cleantech startups. These findings suggest that ARPA-E was not able to fully address the ‘valley of death’ for cleantech startups within 10–15 yr after founding

Multilevel actor networks in China’s growing fossil-fuel based role in the global electricity sector

Abstract Chinese investments into fossil fuel-based electricity generation capacity under its Belt and Road Initiative will create lock-in for decades. Despite China’s recent rise as major public finance provider for the electricity sector of the developing world and the related environmental impacts, there is limited knowledge of the extent and characteristics of non-Chinese participation in Chinese-funded projects. We apply complexity theory approaches and network modelling on a new dataset that links funding activities of Developmental Institutions (Chinese Developmental Institutions (CDIs), Western-backed Multilateral Development Banks (MDBs)) and the involvement of companies in different roles (i.e., as direct investors, contractors, equipment suppliers, and other service providers) to power plants around the world at the unit-level (1999-2020). Previous literature suggests that CDI funded projects show preference to Chinese commercial partners, but we find more than 70% include non-Chinese participants. This also applies for fossil-fuel based technologies where we observe increasing shares of international actors that together account for nearly every third commercial linkage. However, involvement levels and interaction patterns not only differ by technologies (fossils, hydro, non-hydro renewable, nuclear) but also by the time period and types of commercial partners and we observe overall convergence between the CDI- and MDB-supported power plant networks over time. The decreasing involvement of Chinese companies in CDI-funded projects, across technologies, in favour of increasing Western involvement, has important implications for development and climate policy on which we elaborate. However, the failure of both MDB and CDI funding to promote domestic company involvement in the recipient countries may be the largest failing of both sets of agencies in the pursuit of development outcomes.</jats:p

The impact of open access mandates on scientific research and technological development in the U.S.

Summary: Getting to a net-zero emissions economy requires faster development and diffusion of novel clean energy technologies. We exploit a rare natural experiment to study the impact of an open-access mandate on the diffusion of scientific research into patented technologies. From 2014 onwards, the U.S. Department of Energy (DOE) required its 17 National Laboratories (NLs) to publish all peer-reviewed scientific articles without a paywall. Using data from more than 300,000 scientific publications between 2012 and 2018, we show that scientific articles subject to the mandate were used on average 42% more in patents, despite embargo periods of up to 12 months. We also show that articles subject to the mandate were not cited more frequently by other academic articles. Our findings suggest that the mandate primarily contributed to technological development but has not led to additional academic research. Lastly, we show that small firms were the primary beneficiaries of the increased diffusion of scientific knowledge

Estimates of expert's elicited 50th percentile of overnight capital cost

<p><b>Table 2.</b>  Estimates of expert's elicited 50th percentile of overnight capital cost. <em>Y</em> = ln(<em>p</em>50). (Note: robust <em>p</em>-values in brackets.) </p> <p><strong>Abstract</strong></p> <p>Characterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030. We show that controlling for expert, technology, and design characteristics increases experts' implied public RD&D elasticity of expected costs by 25%. Public sector and industry experts' cost expectations are 14% and 32% higher, respectively than academics. US experts are more optimistic than their EU counterparts, with median expected costs 22% lower. On average, a doubling of public RD&D is expected to result in an 8% cost reduction, but the uncertainty is large. The difference between the 90th and 10th percentile estimates is on average 58% of the experts' median estimates. Public RD&D investments do not affect uncertainty ranges, but US experts are less confident about costs than Europeans.</p

RD&D and technology cost with and without observable expert, technology and study characteristics

<p><strong>Figure 2.</strong> RD&D and technology cost with and without observable expert, technology and study characteristics. Axes in logarithmic scales.</p> <p><strong>Abstract</strong></p> <p>Characterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030. We show that controlling for expert, technology, and design characteristics increases experts' implied public RD&D elasticity of expected costs by 25%. Public sector and industry experts' cost expectations are 14% and 32% higher, respectively than academics. US experts are more optimistic than their EU counterparts, with median expected costs 22% lower. On average, a doubling of public RD&D is expected to result in an 8% cost reduction, but the uncertainty is large. The difference between the 90th and 10th percentile estimates is on average 58% of the experts' median estimates. Public RD&D investments do not affect uncertainty ranges, but US experts are less confident about costs than Europeans.</p