Transatlantic distribution of the Alaskan White River Ash

Volcanic ash layers preserved within the geologic record represent precise time markers that correlate disparate depositional environments and enable the investigation of synchronous and/or asynchronous behaviors in Earth system and archaeological sciences. However, it is generally assumed that only exceptionally powerful events, such as supereruptions (≥450 km3 of ejecta as dense-rock equivalent; recurrence interval of ∼105 yr), distribute ash broadly enough to have an impact on human society, or allow us to address geologic, climatic, and cultural questions on an intercontinental scale. Here we use geochemical, age, and morphological evidence to show that the Alaskan White River Ash (eastern lobe; A.D. 833–850) correlates to the “AD860B” ash (A.D. 846–848) found in Greenland and northern Europe. These occurrences represent the distribution of an ash over 7000 km, linking marine, terrestrial, and ice-core records. Our results indicate that tephra from more moderate-size eruptions, with recurrence intervals of ∼100 yr, can have substantially greater distributions than previously thought, with direct implications for volcanic dispersal studies, correlation of widely distributed proxy records, and volcanic hazard assessment.

Fair charging strategies for EVs connected to a low-voltage distribution network

The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration. © 2013 IEEE.