Global Models of Intermediate Timescale Variability on the Sun

In recent years a number of advances in both observation and theory have increased our understanding of the solar interior and how to model it. For climate studies, the timescale of interest for changes in the Sun ranges from decades to centuries. Some of the theoretical advances that will contribute to the building of global models of the Sun's variability on intermediate timescales are described. The current constraints on the important components are discussed. Finally a short discussion presenting some implications for input to climate modeling is presented

Is housing overvalued?

This paper examines whether it is more expensive to own a house or to rent. The paper assesses houses as ‘overvalued’ if home buyers pay too much, in the sense that they would be better off renting than buying. This involves comparing the financial cost of renting a home with the cost of owning a similar dwelling, where the latter depends on the purchase price, interest rates, repairs, council rates and so on. The paper also briefly examines non-financial costs but find these are small, on average. This paper finds if real house prices grow at their historical average pace, then owning a home is about as expensive as renting. If prices grow more slowly, as some forecasters predict, the framework used in this paper suggests that the average home buyer would be financially better off renting. House prices are decomposed into contributions from rents, interest rates and expected capital gains, which may help policymakers in the detection of housing bubbles. Recent data do not show signs of a bubble

Patent Citations and the Geography of Knowledge Spillovers: A Reassessment

Jaffe, Trajtenberg and Henderson (Quarterly Journal of Economics, 108(3):577-98, 1993) developed a matching method to study the geography of knowledge spillovers using patent citations, and found that knowledge spillovers are strongly localized. Their method matches each citing patent to a non-citing patent intended to control for the pre-existing geographic concentration of production. We show how the method of selecting the control group may induce spurious evidence of localized spillovers. This paper reassesses their findings using control patents selected under different criteria. Doing so eliminates evidence of strong intranational localization effects at the state and metropolitan levels, but leaves largely unaffected evidence of international localization effects.patent citations, knowledge spillovers, geography

Assessing the potential for U.S. utility green bonds

EXECUTIVE SUMMARY: Bonds are the largest single class of financial instrument across the world’s financial markets. Recently, a subclass of these bonds, called green bonds, has emerged in the market place. Green bonds are a type of bond whose proceeds may be used only for certain approved “green” investments. In exchange for agreeing to invest only in such projects, the bond issuer obtains some value greater than they would obtain from traditional financing, and are therefore encouraged to finance and undertake a greater number of green projects. This unique value may not be recognized in traditional financial accounting. Of course, like any other capital-raising investment, green bonds enable their issuer to finance a new project that should increase (or at least maintain) its revenues, profits, and cash flow. The utility sector was the second largest issuer of green bonds in 2017, accounting for $26.2 billion dollars’ worth of green bond issuance globally. These were primarily issued to finance renewable energy projects, a class of projects that makes the utility sector one of the most logical for deployment of green bonds. While choosing to issue green bonds does not seem to have any price advantage over regular bonds in the market, green bonds can provide other benefits. These benefits may include reputation effects, better treatment in secondary markets, and other intangibles (See Table ES1)

Very Early Optical Afterglows of Gamma-Ray Bursts: Evidence for Relative Paucity of Detection

Very early observations with the Swift satellite of γ-ray burst (GRB) afterglows reveal that the optical component is not detected in a large number of cases. This is in contrast to the bright optical flashes previously discovered in some GRBs (e.g., GRB 990123 and GRB 021211). Comparisons of the X-ray afterglow flux to the optical afterglow flux and prompt γ-ray fluence is used to quantify the seemingly deficient optical, and in some cases X-ray, light at these early epochs. This comparison reveals that some of these bursts appear to have higher than normal γ-ray efficiencies. We discuss possible mechanisms and their feasibility for explaining the apparent lack of early optical emission. The mechanisms considered include, foreground extinction, circumburst absorption, Lyα blanketing and absorption due to high-redshift, low-density environments, rapid temporal decay, and intrinsic weakness of the reverse shock. Of these, foreground extinction, circumburst absorption, and high redshift provide the best explanations for most of the nondetections in our sample. There is tentative evidence of suppression of the strong reverse shock emission. This could be because of a Poynting flux-dominated flow or a pure nonrelativistic hydrodynamic reverse shock

Long-term U.S transportation electricity use considering the effect of autonomous-vehicles: Estimates & policy observations

In this paper, we model three layers of transportation disruption – first electrification, then autonomy, and finally sharing and pooling – in order to project transportation electricity demand and greenhouse gas emissions in the United States to 2050. Using an expanded kaya identity framework, we model vehicle stock, energy intensity, and vehicle miles traveled, progressively considering the effects of each of these three disruptions. We find that electricity use from light duty vehicle transport will likely be in the 570–1140 TWh range, 13–26%, respectively, of total electricity demand in 2050. Depending on the pace at which the electric sector decarbonizes, this increase in electric demand could correspond to a decrease in LDV greenhouse gas emissions of up to 80%. In the near term, rapid and complete transport electrification with a carbon-free grid should remain the cornerstones of transport decarbonization policy. However, long-term policy should also aim to mitigate autonomous vehicles’ potential to increase driving mileage, urban and suburban sprawl, and traffic congestion while incentivizing potential energy efficiency improvements through both better system management and the lightweighting of an accident-free vehicle fleet

Final report: Workshop on: Integrating electric mobility systems with the grid infrastructure

EXECUTIVE SUMMARY: This document is a report on the workshop entitled “Integrating Electric Mobility Systems with the Grid Infrastructure” which was held at Boston University on November 6-7 with the sponsorship of the Sloan Foundation. Its objective was to bring together researchers and technical leaders from academia, industry, and government in order to set a short and longterm research agenda regarding the future of mobility and the ability of electric utilities to meet the needs of a highway transportation system powered primarily by electricity. The report is a summary of their insights based on workshop presentations and discussions. The list of participants and detailed Workshop program are provided in Appendices 1 and 2. Public and private decisions made in the coming decade will direct profound changes in the way people and goods are moved and the ability of clean energy sources – primarily delivered in the form of electricity – to power these new systems. Decisions need to be made quickly because of rapid advances in technology, and the growing recognition that meeting climate goals requires rapid and dramatic action. The blunt fact is, however, that the pace of innovation, and the range of business models that can be built around these innovations, has grown at a rate that has outstripped our ability to clearly understand the choices that must be made or estimate the consequences of these choices. The group of people assembled for this Workshop are uniquely qualified to understand the options that are opening both in the future of mobility and the ability of electric utilities to meet the needs of a highway transportation system powered primarily by electricity. They were asked both to explain what is known about the choices we face and to define the research issues most urgently needed to help public and private decision-makers choose wisely. This report is a summary of their insights based on workshop presentations and discussions. New communication and data analysis tools have profoundly changed the definition of what is technologically possible. Cell phones have put powerful computers, communication devices, and position locators into the pockets and purses of most Americans making it possible for Uber, Lyft and other Transportation Network Companies to deliver on-demand mobility services. But these technologies, as well as technologies for pricing access to congested roads, also open many other possibilities for shared mobility services – both public and private – that could cut costs and travel time by reducing congestion. Options would be greatly expanded if fully autonomous vehicles become available. These new business models would also affect options for charging electric vehicles. It is unclear, however, how to optimize charging (minimizing congestion on the electric grid) without increasing congestion on the roads or creating significant problems for the power system that supports such charging capacity. With so much in flux, many uncertainties cloud our vision of the future. The way new mobility services will reshape the number, length of trips, and the choice of electric vehicle charging systems and constraints on charging, and many other important behavioral issues are critical to this future but remain largely unknown. The challenge at hand is to define plausible future structures of electric grids and mobility systems, and anticipate the direct and indirect impacts of the changes involved. These insights can provide tools essential for effective private ... [TRUNCATED]Workshop funded by the Alfred P. Sloan Foundatio

First results from the LUCID-Timepix spacecraft payload onboard the TechDemoSat-1 satellite in Low Earth Orbit

The Langton Ultimate Cosmic ray Intensity Detector (LUCID) is a payload onboard the satellite TechDemoSat-1, used to study the radiation environment in Low Earth Orbit ($\sim$635km). LUCID operated from 2014 to 2017, collecting over 2.1 million frames of radiation data from its five Timepix detectors on board. LUCID is one of the first uses of the Timepix detector technology in open space, with the data providing useful insight into the performance of this technology in new environments. It provides high-sensitivity imaging measurements of the mixed radiation field, with a wide dynamic range in terms of spectral response, particle type and direction. The data has been analysed using computing resources provided by GridPP, with a new machine learning algorithm that uses the Tensorflow framework. This algorithm provides a new approach to processing Medipix data, using a training set of human labelled tracks, providing greater particle classification accuracy than other algorithms. For managing the LUCID data, we have developed an online platform called Timepix Analysis Platform at School (TAPAS). This provides a swift and simple way for users to analyse data that they collect using Timepix detectors from both LUCID and other experiments. We also present some possible future uses of the LUCID data and Medipix detectors in space.Comment: Accepted for publication in Advances in Space Researc