Nutrient supply to reed canary grass as a bioenergy crop

Production of renewable energy from herbaceous crops on agricultural land is of great interest since fossil fuels need to be replaced with sustainable energy sources. Reed canary grass (RCG), Phalaris arundinacea L. is an interesting species for this purpose. The aim of this thesis was to study different approaches to reduce the requirement of mineral fertilizers in RCG production for bioenergy purposes. Paper I describes a study where fertilization effects and risk of heavy metal enrichment were studied, using annual applications of ash for seven years. Ash from co-combustion of RCG and municipal wastes (mixed ash), pure RCG ash and commercial fertilizers were compared. The experiment was harvested each spring. Paper II describes an ongoing study in which the effects of intercropping RCG in mixture with nitrogen-fixing perennial legumes are examined in two experiments, in combination with various fertilization treatments. Three fertilization treatments were applied: high N, low N (half of the high N) and low N + RCG ash/sewage sludge. A delayed harvest method was used; cutting the biomass in late autumn and harvesting in spring. Besides dry matter yield, the N-fixation rate was estimated. The results from paper I showed no differences between treatments in the dry matter yields or in the heavy metal concentrations in the biomass. Soil samples, taken when the experiment was finished, showed differences between treatments for Cd, Pb and Zn only in the uppermost soil level, highest levels for the mixed ash treatment. The results in paper II showed that at one site the legume proportion in the mixtures was low and did not affect RCG growth negatively. The high N treatment gave a higher spring yield than the low N treatments. Mean rates of N2-fixation in the first production year were 12-28, 33-40 and 55 kg N ha-1 kg for goat´s rue (Galega orientalis Lam.), red clover (Trifolium pratense L.), and alsike clover (Trifolium hybridum L.), plots, respectively. At the other site, competition with higher proportion of the clovers affected RCG growth and spring yield negatively. The N-fixation rates were 33 - 42 kg N ha-1 for red clover and 24 kg N ha-1 for alsike clover. As a conclusion, pure RCG ash can be used to complement mineral fertilizers in RCG crops, but it is important to analyse the ash for plant nutrients and heavy metals before use. There was no spring yield benefit of legume/RCG intercropping. Thus, the method cannot be recommended in a spring harvest system, at least not under the tested conditions

Neighbourhoods, economic incentives and post compulsory education choices

There are large differences in income and education levels, unemployment and ethnic composition between neighbourhoods. An interesting question is whether a neighbourhood’s characteristics affect the behaviour of its residents. This paper investigates neighbourhood effects on youths’ post primary education choice. Besides including usual variables the paper also includes neighbourhood specific economic incentives. Estimating linear probability models as well as multinomial logit models using Swedish register data, covering the county of Stockholm and the years 1988–1992, I find that both neighbourhood characteristics and economic incentives affect the choice. For the latter the results are quite clear although the size of the effect is small: an increase in the expected income of an alternative increases the probability that this alternative is chosen. For the neighbourhood variables the results differ to some extent depending on the model. The proportion of individuals with at most compulsory education in a neighbourhood does however seem to have a negative effect on applying for a university preparatory programme. The proportion of immigrants in a neighbourhood tend to have a positive effect on immigrants’ probability to apply for a university preparatory programme.Neighbourhoods; economic incentives; educational choice

SIR - an Efficient Solver for Systems of Equations

The Semi-Implicit Root solver (SIR) is an iterative method for globally convergent solution of systems of nonlinear equations. Since publication, SIR has proven robustness for a great variety of problems. We here present MATLAB and MAPLE codes for SIR, that can be easily implemented in any application where linear or nonlinear systems of equations need be solved efficiently. The codes employ recently developed efficient sparse matrix algorithms and improved numerical differentiation. SIR convergence is quasi-monotonous and approaches second order in the proximity of the real roots. Global convergence is usually superior to that of Newtons method, being a special case of the method. Furthermore the algorithm cannot land on local minima, as may be the case for Newtons method with linesearch.Comment: 10 pages, 1 figur

Unpolarized, incoherent repumping light for prevention of dark states in a trapped and laser-cooled single ion

Many ion species commonly used for laser-cooled ion trapping studies have a low-lying metastable 2D3/2 state that can become populated due to spontaneous emission from the 2P1/2 excited state. This requires a repumper laser to maintain the ion in the Doppler cooling cycle. Typically the 2D3/2 state, or some of its hyperfine components if the ion has nuclear spin, has a higher multiplicity than the upper state of the repumping transition. This can lead to dark states, which have to be destabilized by an external magnetic field or by modulating the polarization of the repumper laser. We propose using unpolarized, incoherent amplified spontaneous emission (ASE) to drive the repumping transition. An ASE source offers several advantages compared to a laser. It prevents the buildup of dark states without external polarization modulation even in zero magnetic field, it can drive multiple hyperfine transitions simultaneously, and it requires no frequency stabilization. These features make it very compact and robust, which is essential for the development of practical, transportable optical ion clocks. We construct a theoretical model for the ASE radiation, including the possibility of the source being partially polarized. Using 88Sr+ as an example, the performance of the ASE source compared to a single-mode laser is analyzed by numerically solving the eight-level density matrix equations for the involved energy levels. Finally a reduced three-level system is derived, yielding a simple formula for the excited state population and scattering rate, which can be used to optimize the experimental parameters. The required ASE power spectral density can be obtained with current technology

Dark-state suppression and optimization of laser cooling and fluorescence in a trapped alkaline-earth-metal single ion

We study the formation and destabilization of dark states in a single trapped 88Sr+ ion caused by the cooling and repumping laser fields required for Doppler cooling and fluorescence detection of the ion. By numerically solving the time-dependent density matrix equations for the eight-level system consisting of the sublevels of the 5s 2S1/2, 5p 2P1/2, and 4d 2D3/2 states, we analyze the different types of dark states and how to prevent them in order to maximize the scattering rate, which is crucial for both the cooling and the detection of the ion. The influence of the laser linewidths and ion motion on the scattering rate and the dark resonances is studied. The calculations are then compared with experimental results obtained with an endcap ion trap system located at the National Research Council of Canada and found to be in good agreement. The results are applicable also to other alkaline earth ions and isotopes without hyperfine structure

Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo. Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-"coupled"- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g. coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as em goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz-Kalos-Lebowitz algorithm's philosophy, where here events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach

Optimal co-adapted coupling for a random walk on the hyper-complete-graph

The problem of constructing an optimal co-adapted coupling for a pair of symmetric random walks on $Z_2^d$ was considered by Connor and Jacka (2008), and the existence of a coupling which is stochastically fastest in the class of all such co-adapted couplings was demonstrated. In this paper we show how to generalise this construction to an optimal co-adapted coupling for the continuous-time symmetric random walk on $K_n^d$, where $K_n$ is the complete graph with $n$ vertices. Moreover, we show that although this coupling is not maximal for any $n$ (i.e. it does not achieve equality in the coupling inequality), it does tend to a maximal coupling as $n\to\infty$.Comment: 20 pages, 1 figur

Can Forecasting Performance of the Bayesian Factor-Augmented VAR be Improved by Considering the Steady-State? An application to Swedish inflation

This paper investigates whether the forecasting performance of Bayesian factor-augmented VAR (BFAVAR) models can be improved by incorporating an informative prior on the steady-state of the time series in the system. The BFAVAR model is compared to the extended steady-state BFAVAR in an application to forecasting Swedish inflation, making use of data from 1996 to 2016. Results show that the out-of-sample forecasting performance of incorporating an informative prior into the BFAVAR models increase compared to an autoregressive model. When comparing BFAVAR models with and without an informative prior on the steady-state, the BFAVAR model with an informative prior marginally outperform the BFAVAR model without the informative prior. The results of this paper indicate that most of the gains in forecasting performance by incorporating an informative prior on the steady-state are associated with longer forecasting horizons