Computational Methodologies and Physical Insights into Electronic Energy Transfer in Photosynthetic Light-Harvesting Complexes

We examine computational techniques and methodologies currently in use to explore electronic excitation energy transfer in the context of light-harvesting complexes in photosynthetic antenna systems, and comment on some new insights into the underlying physics. Advantages and pitfalls of these methodologies are discussed, as are some physical insights into the photosynthetic dynamics. By combining results from molecular modelling of the complexes (structural description) with an effective non-equilibrium statistical description (time evolution), we identify some general features, regardless of the particular distribution in the protein scaffold, that are central to light-harvesting dynamics and, that could ultimately be related to the high efficiency of the overall process. Based on these general common features, some possible new directions in the field are discussed.Comment: Invited Perspective Article for Phys. Chem. Chem. Phy

Life cycle assessment (LCA) applied to the process industry: a review

Purpose : Life cycle assessment (LCA) methodology is a well-established analytical method to quantify environmental impacts, which has been mainly applied to products. However, recent literature would suggest that it has also the potential as an analysis and design tool for processes, and stresses that one of the biggest challenges of this decade in the field of process systems engineering (PSE) is the development of tools for environmental considerations. Method : This article attempts to give an overview of the integration of LCA methodology in the context of industrial ecology, and focuses on the use of this methodology for environmental considerations concerning process design and optimization. Results : The review identifies that LCA is often used as a multi-objective optimization of processes: practitioners use LCA to obtain the inventory and inject the results into the optimization model. It also shows that most of the LCA studies undertaken on process analysis consider the unit processes as black boxes and build the inventory analysis on fixed operating conditions. Conclusions : The article highlights the interest to better assimilate PSE tools with LCA methodology, in order to produce a more detailed analysis. This will allow optimizing the influence of process operating conditions on environmental impacts and including detailed environmental results into process industry

Electron flux models for different energies at geostationary orbit

Forecast models were derived for energetic electrons at all energy ranges sampled by the third-generation Geostationary Operational Environmental Satellites (GOES). These models were based on Multi-Input Single-Output Nonlinear Autoregressive Moving Average with Exogenous inputs methodologies. The model inputs include the solar wind velocity, density and pressure, the fraction of time that the interplanetary magnetic field (IMF) was southward, the IMF contribution of a solar wind-magnetosphere coupling function proposed by Boynton et al. (2011b), and the Dst index. As such, this study has deduced five new 1 h resolution models for the low-energy electrons measured by GOES (30–50 keV, 50–100 keV, 100–200 keV, 200–350 keV, and 350–600 keV) and extended the existing >800 keV and >2 MeV Geostationary Earth Orbit electron fluxes models to forecast at a 1 h resolution. All of these models were shown to provide accurate forecasts, with prediction efficiencies ranging between 66.9% and 82.3%

Reduced density matrix hybrid approach: Application to electronic energy transfer

Electronic energy transfer in the condensed phase, such as that occurring in photosynthetic complexes, frequently occurs in regimes where the energy scales of the system and environment are similar. This situation provides a challenge to theoretical investigation since most approaches are accurate only when a certain energetic parameter is small compared to others in the problem. Here we show that in these difficult regimes, the Ehrenfest approach provides a good starting point for a dynamical description of the energy transfer process due to its ability to accurately treat coupling to slow environmental modes. To further improve on the accuracy of the Ehrenfest approach, we use our reduced density matrix hybrid framework to treat the faster environmental modes quantum mechanically, at the level of a perturbative master equation. This combined approach is shown to provide an efficient and quantitative description of electronic energy transfer in a model dimer and the Fenna-Matthews-Olson complex and is used to investigate the effect of environmental preparation on the resulting dynamics.Comment: 11 pages, 8 figure

Sensible and latent heat flux from radiometric surface temperatures at the regional scale: methodology and validation

The CarboEurope Regional Experiment Strategy (CERES) was designed to develop and test a range of methodologies to assess regional surface energy and mass exchange of a large study area in the south-western part of France. This paper describes a methodology to estimate sensible and latent heat fluxes on the basis of net radiation, surface radiometric temperature measurements and information obtained from available products derived from the Meteosat Second Generation (MSG) geostationary meteorological satellite, weather stations and ground-based eddy covariance towers. It is based on a simplified bulk formulation of sensible heat flux that considers the degree of coupling between the vegetation and the atmosphere and estimates latent heat as the residual term of net radiation. Estimates of regional energy fluxes obtained in this way are validated at the regional scale by means of a comparison with direct flux measurements made by airborne eddy-covariance. The results show an overall good matching between airborne fluxes and estimates of sensible and latent heat flux obtained from radiometric surface temperatures that holds for different weather conditions and different land use types. The overall applicability of the proposed methodology to regional studies is discusse

Biological processes and links to the physics

Analysis of the temporal and spatial variability of biological processes and identification of the main variables that drive the dynamic regime of marine ecosystems is complex. Correlation between physical variables and long-term changes in ecosystems has routinely been identified, but the specific mechanisms involved remain often unclear. Reasons for this could be various: the ecosystem can be very sensitive to the seasonal timing of the anomalous physical forcing; the ecosystem can be contemporaneously influenced by many physical variables and the ecosystem can generate intrinsic variability on climate time scales. Marine ecosystems are influenced by a variety of physical factors, e.g., light, temperature, transport, turbulence. Temperature has a fundamental forcing function in biology, with direct influences on rate processes of organisms and on the distribution of mobile species that have preferred temperature ranges. Light and transport also affect the physiology and distribution of marine organisms. Small-scale turbulence determines encounter between larval fish and their prey and additionally influences the probability of successful pursuit and ingestion. The impact of physical forcing variations on biological processes is studied through long-term observations, process studies, laboratory experiments, retrospective analysis of existing data sets and modelling. This manuscript reviews the diversity of physical influences on biological processes, marine organisms and ecosystems and their variety of responses to physical forcing with special emphasis on the dynamics of zooplankton and fish stocks

Optimal design of batch plants under economic and ecological considerations: Application to a biochemical batch plant

This work deals with the multicriteria cost-environment design of multiproduct batch plants, where the design variables are the equipment item sizes as well as the operating conditions. The case study is a multiproduct batch plant for the production of four recombinant proteins. Given the important combinatorial aspect of the problem, the approach used consists in coupling a stochastic algorithm, indeed a Genetic Algorithm (GA) with a Discrete Event Simulator (DES). To take into account the conflicting situations that may be encountered at the earliest stage of batch plant design, i.e. compromise situations between cost and environmental considerations, a Multicriteria Genetic Algorithm (MUGA) was developed with a Pareto optimal ranking method. The results show how the methodology can be used to find a range of trade-off solutions for optimizing batch plant design