We employed a bottom-up modeling framework to examine a set of scenarios to generate insights on the techno-economic and environmental implications of increasing levels of electric vehicle (EV) penetration using Nigeria as a case study. Results indicate that, despite Nigeria having a natural gas-dominated electricity system, the deployment of EVs can support the decarbonization of the transportation and power sectors but at a relatively high cost. The cost of EVs would need to drop by similar to 40% to become cost-competitive. However, if variable renewable energy sources deliver the EVs power requirement with a bidirectional vehicle-to-grid (V2G) charging strategy, then the cost of EVs would need to decline by only similar to 30%. Not all EVs need to participate in a V2G charging strategy in order to realize the full benefits of the strategy. Expanding renewables capacity leads to additional reduction in CO2 emission and decarbonization cost but at different magnitudes based on the charging strategy.

Carbon dioxide emissions from deforestation disturbance (e.g. clear-cutting, forest fires) are in the same units as carbon dioxide emissions from fossil fuels. However, if the forest is allowed to regrow, there is a large difference between climate effects of that forest disturbance and climate effects of fossil CO2. In this study, using a set of idealized global climate-carbon model simulations with equal amounts of CO2 emissions, we show that on century to millennial timescales the response of the climate system to fossil-fuel burning versus deforestation disturbance are vastly different. We performed two 1000 year simulations where we add abrupt emissions of about 600 PgC to the preindustrial state as a consequence of either fossil fuel use or deforestation disturbance with vegetation regrowth. In the fossil fuel simulations, after 1000 years, about 20% of the initial atmospheric CO2 concentration perturbation remains in the atmosphere and the climate is about 1 degrees C warmer compared to preindustrial state. In contrast, in the case of deforestation with regrowth, after 1000 years, atmospheric CO2 concentration returns close to preindustrial values, because deforested land will typically recover its carbon over the decades and centuries in the absence of further human intervention. These results highlight the differences in the degree of long-term commitment associated with fossil-fuel versus deforestation emissions.

Solar photovoltaics, with sufficient power generation potential, low-carbon footprint, and rapidly declining costs, could supplant fossil fuels and help produce lower-cost net-zero emissions energy systems. Here we used an idealized linear optimization model, including free lossless transmission, to study the response of electricity systems to increasing prescribed amounts of solar power. Our results show that there are initially great benefits when providing solar power to the system, especially under deep decarbonization scenarios. The marginal value of additional solar power decreases substantially with increasing cumulative solar capacities. At costs near today's levels, the modeled zero-emission electricity system with free solar generation equaling twice the annual mean demand is more costly than a carbon-emitting natural-gas-based system supplying the same electricity demand with no solar. Taking full advantage of low-cost solar will depend on developing and deploying low-cost approaches to temporally shift either energy supply (e.g., storage) or electricity loads (e.g., load-shifting).

Wind and solar photovoltaic generators are projected to play important roles in achieving a net-zero-carbon electricity system that meets current and future energy needs. Here, we show potential advantages of long-term site planning of wind and solar power plants in deeply decarbonized electricity systems using a macro-scale energy model. With weak carbon emission constraints and substantial amounts of flexible electricity sources on the grid (e.g., dispatchable power), relatively high value is placed on sites with high capacity factors because the added wind or solar capacity can efficiently substitute for running natural gas power plants. With strict carbon emission constraints, relatively high value is placed on sites with high correlation with residual demand because resource complementarity can efficiently compensate for lower system flexibility. Our results suggest that decisions regarding long-term wind and solar farm siting may benefit from consideration of the spatial and temporal evolution of mismatches in electricity demand and generation capacity.

In this study, high pressure infrared (IR) absorption and Raman scattering studies for ammonium azide (NH4N3) were carried out at room temperature up to 20 GPa and 22 GPa, respectively. For comparison and further assignment, the vibrational spectra at ambient conditions were calculated using CASTEP code, particularly for the far-and mid-IR modes. The recorded vibrational data consistently indicated a pressure-induced phase transition at 2.9 GPa. All observed vibrational modes maintained their identities at the high pressure phase, indicating that NH4N3 was still presented in the form of ammonium cations and azide anions linked by the hydrogen bond (N-H center dot center dot center dot N). Above 2.9 GPa, the relative magnitude of the torsional mode weakened and the N-H symmetric stretch displayed a redshift, indicating strengthened hydrogen bonding energy. The opposite effects were observed above 12 GPa, where the relative magnitude of the torsional mode strengthened and the N-H symmetric stretch reverted to a blueshift, indicating weakened hydrogen bonding energy. It can be concluded that the hydrogen bonding energy exhibited a weakening (0-2.9 GPa), strengthening (2.9-12 GPa), and then again weakening (12-22 GPa) phenomena with the increasing of compression. The hydrogen bonding energy changing with the increase of pressure can be ascribed to a phase transition at 2.9 GPa and a rotational or bending behavior of azide ions at 12 GPa. (C) 2014 AIP Publishing LLC.

We report the high-pressure studies of RbN3 by Raman and IR spectral measurements at room temperature with the pressure up to 28.5 and 30.2 GPa, respectively. All the fundamental vibrational modes were resolved by combination of experiment and calculation. Detailed spectroscopic analyses reveal two phase transitions at similar to 6.5 and similar to 16.0 GPa, respectively. Upon compression, the shearing distortion of the unit cell induced the displacive structural transition of phase alpha -> gamma. Further analyses of the mid-IR spectra indicate the evolution of N-3(-) with the arrangement sequence of orthogonal -> parallel -> orthogonal during the phase transition of phase alpha -> gamma -> delta. Additionally, the pressure-induced nonlinear/asymmetric existence of N=N=N and the two crystallographically nonequivalent sites of N-3(-) were observed in phase delta.

The geometrically frustrated pyrochlore Eu2Sn2O7 is an insulator with slight trigonal lattice distortion at ambient condition. High pressure is applied to this system to investigate the responses of structural evolution, optical emission and electrical transport properties. In situ high pressure synchrotron X-ray diffraction, Raman spectroscopy, and photoluminescence studies are performed in Eu2Sn2O7 up to 31.2 and 34.1 GPa, respectively. The abrupt change of the oxygen atomic position without breaking the crystal symmetry is accompanied by disappearing of Raman mode involving SnO6 octahedron distortion around 17.8 GPa. It indicates a pressure induced second-order iso-structural transition, which suppresses the trigonal distortion in the SnO6 octahedron but enhances the local symmetry distortion of EuO8 hexahedron. Anomalous luminescence of the Eu3+ 4f-4f transition is observed, which confirms the enhancement of EuO8 hexahedral distortion at high pressure region. In situ high-pressure electrical transport property is measured by alternating current (AC) impedance spectroscopy up to 32.5 GPa. A rapid increase in resistance with gain of 4 orders of magnitude by applied pressure is observed until 16.6 GPa, and it is followed by a slight decreasing to the highest pressure measured here. All these observations indicate a pressure-enhanced trigonal lattice distortion before the transition pressure, and thus it will enlarge an opening gap at the Fermi energy, followed by releasing distortion at higher pressures.

La2Sn2O7 is a transparent conducting oxide (TCO) material and shows a strong near-infrared fluorescent at ambient pressure and room temperature. By in situ high-pressure research, pressure-induced visible photoluminescence (PL) above 2 GPa near 2 eV is observed. The emergence of unusual visible PL behavior is associated with the seriously trigonal lattice distortion of the SnO6 octehedra, under which the Sn-O1-Sn exchange angle is decreased below 22.1 GPa, thus enhancing the PL quantum yield leading to Sn P-3(1) S-1(0) photons transition. Besides, bandgap closing followed by bandgap opening and the visible PL appearing at the point of the gap reversal, which is consistent with high-pressure phase decomposition, are discovered. The high-pressure PL results demonstrate a well-defined pressure window (7-17 GPa) with flat maximum PL yielding and sharp edges at both ends, which may provide a great calibration tool for pressure sensors for operation in the deep sea or at extreme conditions.

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.