Fundamentals of hydrogen storage in nanoporous materials

Physisorption of hydrogen in nanoporous materials offers an efficient and competitive alternative for hydrogen storage. At low temperatures (e.g. 77 K) and moderate pressures (below 100 bar) molecular H2 adsorbs reversibly, with very fast kinetics, at high density on the inner surfaces of materials such as zeolites, activated carbons and metal–organic frameworks (MOFs). This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, covers the fundamentals of H2 adsorption in nanoporous materials and assessment of their storage performance. The discussion includes recent work on H2 adsorption at both low temperature and high pressure, new findings on the assessment of the hydrogen storage performance of materials, the correlation of volumetric and gravimetric H2 storage capacities, usable capacity, and optimum operating temperature. The application of neutron scattering as an ideal tool for characterising H2 adsorption is summarised and state-of-the-art computational methods, such as machine learning, are considered for the discovery of new MOFs for H2 storage applications, as well as the modelling of flexible porous networks for optimised H2 delivery. The discussion focuses moreover on additional important issues, such as sustainable materials synthesis and improved reproducibility of experimental H2 adsorption isotherm data by interlaboratory exercises and reference materials

Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24 % and -35 % for particles with dry diameters > 50 and > 120 nm, as well as -36 % and -34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N-3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N-3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13 % and -22 % for updraft velocities 0.3 and 0.6 m s(-1), respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (partial derivative N-d/partial derivative N-a) and to updraft velocity (partial derivative N-d/partial derivative w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities partial derivative N-d/partial derivative N-a and partial derivative N-d/partial derivative w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.Peer reviewe

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer

Determining the bulk viscosity of rigid water models

We use equilibrium molecular dynamics methods to compute the shear and bulk viscosities of the pairwise additive and rigid SPC/E, TIP4P, and TIP4P/2005 water models. For the latter model it was found in a recent study (J. Chem. Phys.2009, 131, 246101) an excellent agreement with experiment in the prediction of the shear viscosity over a range of different thermodynamic conditions. Here, we examine, for a wide range of temperatures, whether this remarkable accuracy of the TIP4P/2005 model remains in the prediction of the bulk viscosity. Moreover, we examine whether equilibrium molecular dynamics methods provide reasonable accuracy in the calculation of the bulk viscosity, as it was previously found for the shear viscosity (J. Chem. Phys.2010, 132, 096101). We concluded that, by performing the appropriate data analysis, accurate estimates of the bulk viscosity can be obtained, while, compared to the other simple rigid/pairwise additive water models, the predictions of the TIP4P/2005 model for the bulk viscosity are significantly closer to the experiment. © 2012 American Chemical Society.This work has been supported by DGICYT, Spain, Grant No. FIS2010-18132 and FIS2011-29596-C02-01. G.S.F. gratefully acknowledges funding by MEC, Spain (REF No. SB2009-0008) and a grant provided by the E.U. Seventh Framework Program FP7/2007- 2013 (Grant No. 205066).Peer Reviewe

Modeling structural and transport properties of pure liquid water and aqueous ion systems

Recent Progresses on the Experimental & Theoretical-Computational Techniques for the Study of Liquids and Supercritical Fluids From Simple to Complex Systems, Platanias - Chania, Crete, Greece,11th - 16th September 2016 ; http://www.emlg2016.org/book.htmlPeer Reviewe

Large gain in air quality compared to an alternative anthropogenic emissions scenario

International audienceDuring the last 30 years, significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistry-transport simulations of atmospheric composition over the past 3 decades have been performed to estimate what the air quality levels would have been under a scenario of stagnation of anthropogenic emissions per capita as in 1980, accounting for the population increase (BA1980) or using the standard practice of neglecting it (AE1980), and how they compare to the historical changes in air quality levels. The simulations are based on assimilated meteorology to account for the year-to-year observed climate variability and on different scenarios of anthropogenic emissions of pollutants. The ACCMIP historical emissions dataset is used as the starting point. Our sensitivity simulations provide clear indications that air quality legislation and technology developments have limited the rapid increase of air pollutants. The achieved reductions in concentrations of nitrogen oxides, carbon monoxide, black carbon, and sulfate aerosols are found to be significant when comparing to both BA1980 and AE1980 simulations that neglect any measures applied for the protection of the environment. We also show the potentially large tropospheric air quality benefit from the development of cleaner technology used by the growing global population. These 30-year hindcast sensitivity simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air quality may have been masked by the explosive increase in local population and the disproportional increase in energy demand partially due to the globalization of the economy

Large gain in air quality compared to an alternative anthropogenic emissions scenario

International audienceDuring the last 30 years, significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistry-transport simulations of atmospheric composition over the past 3 decades have been performed to estimate what the air quality levels would have been under a scenario of stagnation of anthropogenic emissions per capita as in 1980, accounting for the population increase (BA1980) or using the standard practice of neglecting it (AE1980), and how they compare to the historical changes in air quality levels. The simulations are based on assimilated meteorology to account for the year-to-year observed climate variability and on different scenarios of anthropogenic emissions of pollutants. The ACCMIP historical emissions dataset is used as the starting point. Our sensitivity simulations provide clear indications that air quality legislation and technology developments have limited the rapid increase of air pollutants. The achieved reductions in concentrations of nitrogen oxides, carbon monoxide, black carbon, and sulfate aerosols are found to be significant when comparing to both BA1980 and AE1980 simulations that neglect any measures applied for the protection of the environment. We also show the potentially large tropospheric air quality benefit from the development of cleaner technology used by the growing global population. These 30-year hindcast sensitivity simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air quality may have been masked by the explosive increase in local population and the disproportional increase in energy demand partially due to the globalization of the economy