Atmospheric chemistry-climate feedbacks

We extend the theory of climate feedbacks to include atmospheric chemistry. A change in temperature caused by a radiative forcing will include, in general, a contribution from the chemical change that is fed back into the climate system; likewise, the change in atmospheric burdens caused by a chemical forcing will include a contribution from the associated climate change that is fed back into the chemical system. The theory includes two feedback gains, G_(che) and G_(cli). G_(che) is defined as the ratio of the change in equilibrium global mean temperature owing to long-lived greenhouse gas radiative forcing, under full climate-chemistry coupling, to that in the absence of coupling. G_(cli) is defined as the ratio of the change in equilibrium mean aerosol or gas-phase burdens owing to chemical forcing under full coupling, to that in the absence of coupling. We employ a climate-atmospheric chemistry model based on the Goddard Institute for Space Studies (GISS) GCM II', including tropospheric gas-phase chemistry, sulfate, nitrate, ammonium, black carbon, and organic carbon. While the model describes many essential couplings between climate and atmospheric chemistry, not all couplings are accounted for, such as indirect aerosol forcing and the role of natural dust and sea salt aerosols. Guided by the feedback theory, we perform perturbation experiments to quantify G_(che) and G_(cli). We find that G_(che) for surface air temperature is essentially equal to 1.00 on a planetary scale. Regionally, G_(che) is estimated to be 0.80–1.30. The gains are small compared to those of the physical feedbacks in the climate system (e.g., water vapor, and cloud feedbacks). These values for G_(che) are robust for the specific model used, but may change when using more comprehensive climate-atmospheric chemistry models. Our perturbation experiments do not allow one to obtain robust values for G_(cli). Globally averaged, the values range from 0.99 to 1.28, depending on the chemical species, while, in areas of high pollution, G_(cli) can be up to 1.15 for ozone, and as large as 1.40 for total aerosol. These preliminary values indicate a significant role of climate feedbacks in the atmospheric chemistry system

Hopf Bifurcation and Chaos in a Single Inertial Neuron Model with Time Delay

A delayed differential equation modelling a single neuron with inertial term is considered in this paper. Hopf bifurcation is studied by using the normal form theory of retarded functional differential equations. When adopting a nonmonotonic activation function, chaotic behavior is observed. Phase plots, waveform plots, and power spectra are presented to confirm the chaoticity.Comment: 12 pages, 7 figure

Business Model Innovation and Factors Influencing Business Model Innovation

Thesis purpose: The thesis aims to explore business model innovation in companies and the main factors having influence on the decision making process towards business model innovation. The thesis addresses a gap in the literature in regards to the main factors having impact on business model innovation and their interdependence.Theoretical perspectives: Key concepts of this study are business model innovation and factors influencing business model innovation (Amit & Zott 2001; Chesbrough, 2010; Demil and Lecocq, 2010; Sako, 2012).Conclusions: It has been revealed that there are a few main factors having impact on decision making towards business model innovation. These factors have been divided into drivers and barriers. And while literature discusses mainly barriers for business model innovation, we have explored both, drivers and barriers. They influence in opposite directions to business model innovation. The empirical findings in Skanska Oresund reflected argument of Johnson et al. (2008) that business model innovation should be undertaken only when companies are able to make sure that the opportunity is large enough to warrant the effort and risk.Methodology: A case study design was picked for the purpose of exploring the topic stated. A four months internship in a company provided the authors with conditions to explore in-depth the phenomenon. Iterative approach has been employed, meaning that data collection and analysis were done simultaneously and referred back to each other during the process. This approach helped the authors to explore factors more comprehensively, including those identified in extant literature as well as new emerging ones, and to identify important patterns. This approach also allowed the authors to adjust the method during the data collection, which is a key feature of theory building case study. The empirical data collection was effectuated through semi-structured interviews. At the end this research aims to contribute to the literature by filling the gap identified

Limiting efficiencies of solar energy conversion and photo-detection via internal emission of hot electrons and hot holes in gold

We evaluate the limiting efficiency of full and partial solar spectrum harvesting via the process of internal photoemission in Au-semiconductor Schottky junctions. Our results based on the ab initio calculations of the electron density of states (e-DOS) reveal that the limiting efficiency of the full-spectrum Au converter based on hot electron injection is below 4%. This value is even lower than previously established limit based on the parabolic approximation of the Au electron energy bands. However, we predict limiting efficiency exceeding 10% for the hot holes collection through the Schottky junction between Au and p-type semiconductor. Furthermore, we demonstrate that such converters have more potential if used as a part of the hybrid system for harvesting high- and low-energy photons of the solar spectrum.Comment: Proc. SPIE 9608, Infrared Remote Sensing and Instrumentation XXIII, 960816 (September 1, 2015) 7 pages, 4 figure

Numerics of the Lattice Boltzmann Method: Effects of Collision Models on the Lattice Boltzmann Simulations

We conduct a comparative study to evaluate several lattice Boltzmann (LB) models for solving the near incompressible Navier-Stokes equations, including the lattice Boltzmann equation with the multiple-relaxation-time (MRT), the two-relaxation-time (TRT), the single-relaxation-time (SRT) collision models, and the entropic lattice Boltzmann equation (ELBE). The lid-driven square cavity flow in two dimensions is used as a benchmark test. Our results demonstrate that the ELBE does not improve the numerical stability of the SRT or the lattice Bhatnagar-Gross-Krook (LBGK) model. Our results also show that the MRT and TRT LB models are superior to the ELBE and LBGK models in terms of accuracy, stability, and computational efficiency and that the ELBE scheme is the most inferior among the LB models tested in this study, thus is unfit for carrying out numerical simulations in practice. Our study suggests that, to optimize the accuracy, stability, and efficiency in the MRT model, it requires at least three independently adjustable relaxation rates: one for the shear viscosity ν (or the Reynolds number Re), one for the bulk viscosity ζ, and one to satisfy the criterion imposed by the Dirichlet boundary conditions which are realized by the bounce-back-type boundary conditions. © 2011 American Physical Society