Jan Larsen

Preliminary results on optimization of pilot scale pretreatment of wheat straw used in coproduction of bioethanol and electricity

The overall objective in this European Union-project is to develop cost and energy effective production systems for coproduction of bioethanol and electricity based on integrated biomass utilization. A pilot plan reactor for hydrothermal pretreatment (including weak acid hydrolysis, wet oxidation, and steam pretreatment) with a capacity of 100 kg/h was constructed and tested for pretreatment of wheat straw for ethanol production. Highest hemicellulose (C5 sugar) recovery and extraction of hemicellulose sugars was obtained at 190°C whereas highest C6 sugar yield was obtained at 200°C. Lowest toxicity of hydrolysates was observed at 190°C; however, addition of H2O2 improved the fermentability and sugar recoveries at the higher temperatures. The estimated total ethanol production was 223 kg/t straw assuming utilisation of both C6 and C5 during fermentation, and 0.5 g ethanol/g sugar.

Quantification of blockiness in pectins - a comparative study using vibrational spectroscopy and chemometrics.

The gelling properties of pectins are related not only to the degree of esterification (DE), but also to the distribution of the ester groups. In this study, we have examined an experimentally designed series of 31 pectins originating from the same mother pectin and de-esterified using combinations of two different enzymatic mechanisms. The potential of using infrared (IR), Raman, and near infrared (NIR) spectroscopies combined with chemometrics for reliable and rapid determination of the DE and distribution patterns of methyl ester groups in a designed set of pectin powders was investigated. Quantitative calibration models using partial least squares (PLS) regression were developed and compared. The calibration models for prediction of DE obtained on extended inverse signal correction (EISC)-treated spectra of all three spectroscopic methods yielded models with cross-validated prediction errors (RMSECV) between 1.1%p and 1.6%p DE and correlation coefficients of 0.99. A calibration model predicting degree of random de-esterification (R) and block de-esterification (B) was developed for each spectroscopic method, yielding RMSECV values between 4.4 and 6.7 and correlation coefficients (r) between 0.79 and 0.92. Variable selection using interval PLS (iPLS) significantly improved the prediction of R for IR spectroscopy, yielding RMSECV of 3.5 and correlation coefficients of 0.95. All three spectroscopic methods were able to distinguish the spectral patterns of pectins with different enzyme treatments in simple classification models by principal component analysis (PCA). Extended canonical variate analysis revealed one specific signal in the Raman (1045cm(-1)) spectrum and one significant area (1250-1400cm(-1)) in the IR spectrum which are able to classify the pectin samples according to the four different enzyme treatments. In both Raman and IR spectra, the signal intensity decreased in the sequence R-B>B>B-R>R>re-methylated pectin.

A new kayak ergometer based on wind resistance

Abstract An ergometer for kayak paddlers has been developed and used for winter training, measurements of work capacity and maximal oxygen uptake ([Vdot]O2 max). Force is transmitted from the paddle by means of a wire connected to a flywheel mounted with six 9 × 9cm blades. Resistance, therefore, is based on wind turbulence generated by the flywheel. The mechanical efficiency of the ergometer at 63% (range 48-77) of [Vdot]O2 max was 17% (range 16-18) (n= 13). The [Vdot]O2 max was similar during bicycling (median 4·9; range 4·4-5·4l/min), arm cranking (median 4·8; range 4·3-5·11/min), on-water rowing in a kayak (median 4·7; range 4·0-4·91/min) and during rowing the kayak ergometer (median 4·8; range 4·3-5·21/min), (n = 6, p> 0·05). Work capacity during a 5 min ‘all-out’ test was 272 W (range 253–304 W) on the kayak ergometer (n = 17). The use of the ergometer for training helped to increase the aerobic power during arm exercise of Danish paddlers. Before introduction of the ergometer (February 1986), their...

The accuracy of the small s approximations to the probability of recombination in a Coulomb field

Numerical calcualtions are reported for the recombination probability of an islated pair in a three‐dimensional isotropic medium with a samll concentration fo scavenger. The accuracy of these expressions is discussed in detail. (AIP)

Problems Caused by Microbes and Treatment Strategies The Effect of Nitrate Injection in Oil Reservoirs – Experience with Nitrate Injection in the Halfdan Oilfield

This chapter deals with the use of nitrate injection for reservoir souring mitigation in an oilfield with seawater injection in the Danish sector of the North Sea. Nitrate impacts on the activity of sulphate-reducing bacteria (SRB) and biofilm redox potential (Larsen et al., 2007), as a result of which corrosion due to SRB activity will be reduced, souring inhibited and previously formed sulphide removed (Larsen, 2002). One important aspect is that the microbiological reduction of nitrate provides approximately three times more energy to SRB than the reduction of sulphate. Therefore, when both nitrate and sulphate are present, nitrate becomes the preferred electron acceptor and SRB capable of growing on nitrate will dominate. Nitrate provides a competitive advantage to nitrate-utilising bacteria (indicated by the general acronym NUB) during competition for available carbon sources as the NUB are capable of much faster growth than SRB.

A simple method for calculating diffusional recombination probabilities

Abstract We present a numerical method for calculating the diffusion-controlled recombination probability of a pair of interacting particles in an isotropic medium with scavengers. The method is finite and has a controllable accuracy. The algorithm is remarkably simple and can be implemented on a programmable pocket calculator.

How Many Microorganisms Are Present? Techniques for Enumerating Microorganisms in Oilfields

The different techniques that exist for enumerating microorganisms will often yield very different results when applied to oilfield samples. For example, enumeration of sulphate-reducing bacteria (SRB) by cultivation may fail to find any microorganisms in samples for which molecular microbiological methods (MMM) indicate levels of thousands or even millions per millilitre or gram. Therefore, it is important to realise the limitations and advantages of the different techniques available to the industry and to take them into account when interpreting data. In oil systems, the most widely used techniques for quantification are based either on culturing, epifluorescence microscopy, or quantitative PCR. In complex samples in which live, inactive, and dead cells are present together with cell material in various states of decomposition, each of these three methodologies enumerates a different subset of microorganisms (Fig. 10.1).

How Many Microorganisms Are Present? Quantitative Reverse Transcription PCR (qRT-PCR)

Quantitative reverse transcription PCR (qRT-PCR) is a variation of conventional quantitative or real-time PCR, whereby mRNA is first converted into the complementary DNA (cDNA) by reverse transcription, the cDNA is then subsequently quantified by qPCR. The use of mRNA as the initial template allows the quantification of gene transcripts, rather than gene copy numbers. mRNA is only produced by actively metabolising cells and is produced by its corresponding gene to provide a ‘blueprint’ in order for a cell to manufacture a specific protein. Conventional qPCR detects not only DNA present in actively metabolising cells but also inactive and dead cells. qRT-PCR has the advantage that only actively metabolising cells are detected, hence provides a more reliable measure of microbial activity in oilfield samples. When qRT-PCR is combined with primers and probes for specific genes, the activity of microbial processes important in the oilfield, such as sulphate reduction, methanogenesis and nitrate reduction can be monitored.

Problems Caused by Microbes and Treatment Strategies: Rapid Diagnostics of Microbiologically Influenced Corrosion (MIC) in Oilfield Systems with a DNA-Based Test Kit

In the past, many operators have encountered failures due to MIC in pipelines and topside facilities contaminated with sulphate-reducing bacteria (SRB). In some cases, severe pitting has resulted in flow lines being either abandoned or replaced (Davies and Scott, 2006). However, there are reports of little or no significant MIC in some systems, despite an apparent significant contamination with SRB (Maxwell, 2006). As most bacterial counts were conducted using serial dilution techniques such as the most probable number (MPN) technique selective enumeration of SRB strains (depending on the type of growth medium used) will inevitably be conducted. Therefore, high bacterial numbers derived from cultivation-based techniques do not necessarily correlate to high SRB numbers causing MIC in the production system (Larsen et al., 2005). In addition, MIC can be caused by other microbes such as sulphate-reducing archaea (SRA), methanogens and fermentative microbes (Larsen et al., 2008, 2009). Also most samples taken by the oil industry are water samples. However, the majority of microbial activity takes place in biofilms that attach to pipeline walls, well tubing and on the inside of topside facilities.

Problems Caused by Microbes and Treatment Strategies: Monitoring Microbial Responses to Biocides; Bioassays – A Concept to Test the Effect of Biocides on both Archaea and Bacteria in Oilfield Systems

The oil and gas industry seeks to reduce the costs of oil and gas production and to minimise the risks of the operation, i.e. to have a high degree of safety for the personnel and protection of the environment. This imposes considerable demands on corrosion inhibition technologies and chemical management. The oil industry has traditionally used cultivation-based methods for microbiological surveillance of oil production facilities to monitor microbiologically influenced corrosion (MIC) risk (Sooknah et al., 2007). However, studies show that it is only possible to cultivate less than 10% of all viable microorganisms and that the population characteristics in a sample may change during the cultivation steps (Maxwell et al., 2004). Therefore, it is obvious that alternative methods are needed that can detect all the microorganisms related to MIC in a sample independent of the cultivation method.