23 research outputs found
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Leveraging private investment to expand renewable power generation: Evidence on financial additionality and productivity gains from Uganda
Effectively mitigating climate change entails a quick upscaling and redirection of electricity infrastructure investment. Given that the bulk of greenhouse gas emissions increases until 2050 will come from low- and middle-income countries, finding cost-effective ways to mitigate climate change while meeting development targets is essential. However, recent research has shown some of the limitations of broad financing mechanisms, such as the Clean Development Mechanism (CDM) and existing carbon markets. This has resulted in a growing interest in designing novel investment support schemes, such as modifications of targeted feed-in-tariffs (FiTs) that may be more cost effective and better targeted towards particular outcomes when compared to traditional deployment subsidies or broad financing mechanisms. We evaluate the design and outcomes of one such novel support schemes: the GET FiT (Global Energy Transfer Feed-in Tariff) investment support scheme in Uganda, which has attracted ~ 453 million USD in private sector investment for 17 small-scale renewable energy projects (solar, hydro, bagasse) in only three years. Using financial modelling on detailed project-level data, we find that the majority of projects were additional and would therefore not have been built without the subsidy. In addition, using firm-level panel data, we show that power outages hamper manufacturing performance in Uganda. In the absence of reliable outage-data for the entire Ugandan territory, we use nightlight variations to proxy changes in outages. We show that outages have declined substantially since the introduction of GET FiT. Yet, our analysis also demonstrates that programmes to incentivise additional renewable generation in developing countries funded internationally or domestically should liaise closely with grid authorities to ensure that supply does not outstrip demand.European Unionâs Horizon 2020 INNOPATHS project (Grant agreement no. 730403)
The Department of Land Economy and the School of Humanities and Social Sciences, University of Cambridge
Heinrich Böll Foundation
Supernova neutrino burst detection with the Deep Underground Neutrino Experiment
The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the Îœe spectral parameters of the neutrino burst will be considered
Neutrino interaction classification with a convolutional neural network in the DUNE far detector
The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2â5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects
Experiment simulation configurations approximating DUNE TDR
The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly capable near detector located on site at Fermilab, in Batavia, Illinois, and a massive liquid argon time projection chamber (LArTPC) far detector located at the 4850L of Sanford Underground Research Facility in Lead, South Dakota. The long-baseline physics sensitivity calculations presented in the DUNE Physics TDR, and in a related physics paper, rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the near and far detectors, fully automated event reconstruction and neutrino classification, and detailed implementation of systematic uncertainties. The purpose of this posting is to provide a simplified summary of the simulations that went into this analysis to the community, in order to facilitate phenomenological studies of long-baseline oscillation at DUNE. Simulated neutrino flux files and a GLoBES configuration describing the far detector reconstruction and selection performance are included as ancillary files to this posting. A simple analysis using these configurations in GLoBES produces sensitivity that is similar, but not identical, to the official DUNE sensitivity. DUNE welcomes those interested in performing phenomenological work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community
First results on ProtoDUNE-SP liquid argon time projection chamber performance from a beam test at the CERN Neutrino Platform
The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber with an active volume of 7.2Ă6.0Ă6.9 m3. It is installed at the CERN Neutrino Platform in a specially-constructed beam that delivers charged pions, kaons, protons, muons and electrons with momenta in the range 0.3 GeV/c to 7 GeV/c. Beam line instrumentation provides accurate momentum measurements and particle identification. The ProtoDUNE-SP detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment, and it incorporates full-size components as designed for that module. This paper describes the beam line, the time projection chamber, the photon detectors, the cosmic-ray tagger, the signal processing and particle reconstruction. It presents the first results on ProtoDUNE-SP's performance, including noise and gain measurements, dE/dx calibration for muons, protons, pions and electrons, drift electron lifetime measurements, and photon detector noise, signal sensitivity and time resolution measurements. The measured values meet or exceed the specifications for the DUNE far detector, in several cases by large margins. ProtoDUNE-SP's successful operation starting in 2018 and its production of large samples of high-quality data demonstrate the effectiveness of the single-phase far detector design
Low exposure long-baseline neutrino oscillation sensitivity of the DUNE experiment
The Deep Underground Neutrino Experiment (DUNE) will produce world-leading neutrino oscillation measurements over the lifetime of the experiment. In this work, we explore DUNE's sensitivity to observe charge-parity violation (CPV) in the neutrino sector, and to resolve the mass ordering, for exposures of up to 100 kiloton-megawatt-years (kt-MW-yr). The analysis includes detailed uncertainties on the flux prediction, the neutrino interaction model, and detector effects. We demonstrate that DUNE will be able to unambiguously resolve the neutrino mass ordering at a 3Ï (5Ï) level, with a 66 (100) kt-MW-yr far detector exposure, and has the ability to make strong statements at significantly shorter exposures depending on the true value of other oscillation parameters. We also show that DUNE has the potential to make a robust measurement of CPV at a 3Ï level with a 100 kt-MW-yr exposure for the maximally CP-violating values \delta_{\rm CP}} = \pm\pi/2. Additionally, the dependence of DUNE's sensitivity on the exposure taken in neutrino-enhanced and antineutrino-enhanced running is discussed. An equal fraction of exposure taken in each beam mode is found to be close to optimal when considered over the entire space of interest
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Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales
Improving energy efficiency (EE) is vital to ensure a sustainable, affordable, and secure energy system. The residential sector represents, on average, 18.6% of the total final energy consumption in the OECD countries in 2018, reaching 29.5% in the UK (IEA, 2020a). Using a staggered differences-in-differences approach with dynamic treatment effects, we analyse changes in residential gas consumption five years before and after the adoption of energy efficiency measures. The analysis includes energy efficiency interventions involving the installation of new heating-related insulation equipmentâi.e., of loft insulation and cavity walls, supported by energy efficiency programmes in England and Wales between 2005 and 2017âusing a panel of 55,154 households from the National Energy Efficiency Data-Framework (NEED). We control for, among other factors, energy prices and the extent to which gas consumption changes are dependent on household characteristics and variations in weather conditions. Our results indicate that the adoption of EE measures is associated with significant reductions in household residential gas consumption one year after their implementation. However, the effect does not last in the long run and energy savings disappear four years after the retrofitting of cavity wall insulation measures and after two years following the installation of loft insulation. The disappearance of energy savings in the longer run could be explained by the energy performance gap, the rebound effect and/or by concurrent residential construction projects and renovations associated with increases in energy consumption. Notably, for households in deprived areas, the installation of these efficiency measures does not deliver energy savings. These results confirm the existence of effects that reduce the energy savings from the adoption of these efficiency technologies over time and indicates that, for some groups, these net savings do not seem to materialize.Cambridge Social Sciences and Humanities Grant Schem
Systematic review of the outcomes and trade-offs of ten types of decarbonization policy instruments
The literature evaluating the technical and socio-economic outcomes of policy instruments used to support the transition to low-carbon economies is neither easily accessible nor comparable, and often provides conflicting results. We develop and implement a framework to systematically review and synthesize the impact of ten types of decarbonisation policy instruments on seven technical and socio-economic outcomes. Our systematic review shows that the selected types of regulatory and economic and financial instruments are generally associated with positive impacts on environmental, technological, and innovation outcomes. Several instruments are often associated with short-term negative impacts on competitiveness and distributional outcomes. We discuss how these trade-offs can be reduced or transformed into co-benefits by designing R&D and government procurement, deployment policies, carbon pricing and trading. We show how specific design features can promote competitiveness and reduce negative distributional impacts, particularly for small firms. An online interactive Decarbonisation Policy Evaluation Tool allows further analysis of the evidence.H2020 Framework European Commissio
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The short-term costs of local content requirements in the Indian solar auctions
Developing and emerging economies are implementing local content requirements (LCRs) to spur domestic manufacturing though their costs and benefits are not well understood and difficult to quantify. Here, we provide an empirical assessment of the short-term costs of LCRs using a credible counterfactual. We analyse data on government-run solar PV auctions held in India between 2014-2017 and exploit the fact that not all of the auctioned contracts entailed LCRs. We find that LCR policies resulted in a ~6% per kWh increase in the cost of solar PV power generated from those projects when compared to similar projects not subjected to the same LCR policy. During this three-year time period, Indian solar panels remained around 14% more expensive than international panels. We found some evidence of short-term increases in domestic manufacturing capacity, yet, during this short period Indian firms did not increase market share or break into export markets