Multiple scientific studies suggest that methane emissions from natural gas systems could be larger than estimated in official inventories, with implications for the use of natural gas in sustainable energy systems. 2 Main Text:Natural gas emits less carbon dioxide during combustion than other fossil fuels and can be flexibly used in a variety of industries. This makes natural gas (NG) a potential "bridge fuel" during the transition to a decarbonized energy system. However, due to the high global warming potential (GWP) of methane (CH 4 ), climate benefits from NG depend on system leakage rates.Several recent estimates of leakage rates have challenged the benefits of fuel switching from coal to NG, a large near-term greenhouse gas (GHG) reduction opportunity (1-3). Policymakers require improved understanding of the leakage rates from NG systems. To this end, we review twenty years of scientific and technical literature on NG emissions. This study presents a first effort to systematically compare emissions estimates at scales ranging from devices (kg/y) to continent-wide atmospheric studies (Tg/y).We first present results from "top-down" studies which measure airborne methane concentrations. We then discuss "bottom-up" studies, which measure device-and facilitylevel leakage rates. We explore differences between study results, and discuss attribution of emissions to natural gas systems. Lastly, we examine implications for GHG emissions policies.Atmospheric studies employ aircraft (1, 4-7), tower (3, 5) and ground (3, 6-9) gas sampling, as well as remote sensing (6, 10,11). All such studies observe atmospheric concentrations, and must infer fluxes by accounting for atmospheric transport. Inference can be made using tracer-tracer correlations (2, 3, 6, 9,11,12), mass-balance (1, 13), and atmospheric modeling and inversion methods (4, 5, 7,14). Strengths and weaknesses exist with each approach (see SI).Figure 1 compiles published estimates of CH 4 leakage at all scales. It includes all known studies which a) performed measurements of emissions at some scale, and b) compared these measurements to inventories or established emissions factors. The ratio of observed emissions to the comparable emissions inventory is plotted on the x-axis, such that ratios >1 imply excess emissions observed relative to those expected.Figure 1 plots estimated CH 4 emissions from atmospheric studies above 10 10 gCH 4 /y. We include all atmospheric studies of CH 4 emissions -not just those that focus on NG -so as to bound emissions from NG. Across years, scales, and methods, these studies systematically find larger CH 4 emissions than predicted by inventories (ratios generally >1). Smaller-scale studies focusing on NG producing (1-3, 8) and consuming regions (2, 6,(9)(10)(11)14) find larger excess CH 4 emissions than national-level studies. This trend may be due to averaging effects of continental-scale atmospheric processes, or due to regional atmospheric studies focusing on areas with air quality problems, such as wintertime ozone (1, 3)....

Unconventional oil and natural gas extraction enabled by horizontal drilling and hydraulic fracturing (fracking) is driving an economic boom, with consequences described from "revolutionary" to "disastrous." Reality lies somewhere in between. Unconventional energy generates income and, done well, can reduce air pollution and even water use compared with other fossil fuels. Alternatively, it could slow the adoption of renewables and, done poorly, release toxic chemicals into water and air. Primary threats to water resources include surface spills, wastewater disposal, and drinking-water contamination through poor well integrity. An increase in volatile organic compounds and air toxics locally are potential health threats, but the switch from coal to natural gas for electricity generation will reduce sulfur, nitrogen, mercury, and particulate air pollution. Data gaps are particularly evident for human health studies, for the question of whether natural gas will displace coal compared with renewables, and for decadal-scale legacy issues of well leakage and plugging and abandonment practices. include data for (a) estimated ultimate recovery (EUR) of unconventional hydrocarbons, (b) the potential for further reductions of water requirements and chemical toxicity, (c) whether unconventional resource development alters the frequency of well integrity failures, (d ) potential contamination of surface and ground waters from drilling and spills, (e) factors that could cause wastewater injection to generate large earthquakes, and ( f ) the consequences of greenhouse gases and air pollution on ecosystems and human health.

Articles you may be interested inDielectric response of transformer oil based ferrofluid in low frequency range J. Appl. Phys. 114, 034313 (2013); 10.1063/1.4816012 Effect of nanoparticle polarization on relative permittivity of transformer oil-based nanofluids Iron oxide nanoparticles fabricated by electric explosion of wire: focus on magnetic nanofluids AIP Advances 2, 022154 (2012); 10.1063/1.4730405Effect of electron shallow trap on breakdown performance of transformer oil-based nanofluids Transformer oil-based nanofluids with conductive nanoparticle suspensions defy conventional wisdom as past experimental work showed that such nanofluids have substantially higher positive voltage breakdown levels with slower positive streamer velocities than that of pure transformer oil. This paradoxical superior electrical breakdown performance compared to that of pure oil is due to the electron charging of the nanoparticles to convert fast electrons from field ionization to slow negatively charged nanoparticle charge carriers with effective mobility reduction by a factor of about 1 ϫ 10 5 . The charging dynamics of a nanoparticle in transformer oil with both infinite and finite conductivities shows that this electron trapping is the cause of the decrease in positive streamer velocity, resulting in higher electrical breakdown strength. Analysis derives the electric field in the vicinity of the nanoparticles, electron trajectories on electric field lines that charge nanoparticles, and expressions for the charging characteristics of the nanoparticles as a function of time and dielectric permittivity and conductivity of nanoparticles and the surrounding transformer oil. This charged nanoparticle model is used with a comprehensive electrodynamic analysis for the charge generation, recombination, and transport of positive and negative ions, electrons, and charged nanoparticles between a positive high voltage sharp needle electrode and a large spherical ground electrode. Case studies show that transformer oil molecular ionization without nanoparticles cause an electric field and space charge wave to propagate between electrodes, generating heat that can cause transformer oil to vaporize, creating the positive streamer. With nanoparticles as electron scavengers, the speed of the streamer is reduced, offering improved high voltage equipment performance and reliability.

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This article presents a detailed exploration of the optical characteristics of various one-dimensional photonic crystal structures designed for use as a means of improving the efficiency and power density of thermophotovoltaic ͑TPV͒ devices. The crystals being investigated have a ten-layer quarter-wave periodic structure, and are based on Si/ SiO 2 and Si/ SiON material systems. For TPV applications the crystals are designed to act as filters, transmitting photons with wavelengths below 1.78 m to a GaSb photodiode, while reflecting photons of longer wavelengths back to the source of thermal radiation. In the case of the Si/ SiO 2 structure, the Si and SiO 2 layers were designed to be 170 and 390 nm thick, respectively. This structure was fabricated using low-pressure chemical vapor deposition. Reflectance and transmittance measurements of the fabricated Si/ SiO 2 photonic crystals were taken from 0.8 to 3.3 m for both polarizations and for a range of incident angles. Measurement results were found to correlate well with simulation results for the ideal structure. Measurement results were used to predict the TPV system efficiency, power density and spectral efficiency using an ideal thermodynamic model of a TPV system.

Change combines cutting-edge scientific research with independent policy analysis to provide a solid foundation for the public and private decisions needed to mitigate and adapt to unavoidable global environmental changes. Being data-driven, the Joint Program uses extensive Earth system and economic data and models to produce quantitative analysis and predictions of the risks of climate change and the challenges of limiting human influence on the environmentessential knowledge for the international dialogue toward a global response to climate change.To this end, the Joint Program brings together an interdisciplinary group from two established MIT research centers: the Center for Global Change Science (CGCS) and the Center for Energy and Environmental Policy Research (CEEPR). These two centers-along with collaborators from the Marine Biology Laboratory (MBL) at Woods Hole and short-and long-term visitors-provide the united vision needed to solve global challenges.At the heart of much of the program's work lies MIT's Integrated Global System Model. Through this integrated model, the program seeks to discover new interactions among natural and human climate system components; objectively assess uncertainty in economic and climate projections; critically and quantitatively analyze environmental management and policy proposals; understand complex connections among the many forces that will shape our future; and improve methods to model, monitor and verify greenhouse gas emissions and climatic impacts.This reprint is intended to communicate research results and improve public understanding of global environment and energy challenges, thereby contributing to informed debate about climate change and the economic and social implications of policy alternatives. Given uncertainty in long-term carbon reduction goals, how much non-carbon generation should be developed in the near-term? This research investigates the optimal balance between the risk of overinvesting in non-carbon sources that are ultimately not needed and the risk of underinvesting in non-carbon sources and subsequently needing to reduce carbon emissions dramatically. We employ a novel framework that incorporates a computable general equilibrium (CGE) model of the U.S. into a two-stage stochastic approximate dynamic program (ADP) focused on decisions in the electric power sector. We solve the model using an ADP algorithm that is computationally tractable while exploring the decisions and sampling the uncertain carbon limits from continuous distributions.The results of the model demonstrate that an optimal hedge is in the direction of more non-carbon investment in the near-term, in the range of 20-30% of new generation. We also demonstrate that the optimal share of non-carbon generation is increasing in the variance of the uncertainty about the long-term carbon targets, and that with greater uncertainty in the future policy regime, a balanced portfolio of non-carbon, natural gas, and coal generation is desirable.

We explore the optical characteristics and fundamental limitations of one-dimensional (1D) photonic crystal (PhC) structures as means for improving the efficiency and power density of thermophotovoltaic (TPV) and microthermophotovoltaic (MTPV) devices. We analyze the optical performance of 1D PhCs with respect to photovoltaic diode efficiency and power density. Furthermore, we present an optimized dielectric stack design that exhibits a significantly wider stop band and yields better TPV system efficiency than a simple quarter-wave stack. The analysis is done for both TPV and MTPV devices by use of a unified modeling framework.

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