A Non-catalytic Deep Desulphurization Process using Hydrodynamic Cavitation

A novel approach is developed for desulphurization of fuels or organics without use of catalyst. In this process, organic and aqueous phases are mixed in a predefined manner under ambient conditions and passed through a cavitating device. Vapor cavities formed in the cavitating device are then collapsed which generate (in-situ) oxidizing species which react with the sulphur moiety resulting in the removal of sulphur from the organic phase. In this work, vortex diode was used as a cavitating device. Three organic solvents (n-octane, toluene and n-octanol) containing known amount of a model sulphur compound (thiophene) up to initial concentrations of 500 ppm were used to verify the proposed method. A very high removal of sulphur content to the extent of 100% was demonstrated. The nature of organic phase and the ratio of aqueous to organic phase were found to be the most important process parameters. The results were also verified and substantiated using commercial diesel as a solvent. The developed process has great potential for deep of various organics, in general, and for transportation fuels, in particular.

Performances of dead-end ultrafiltration of seawater: from the filtration and backwash efficiencies to the membrane fouling mechanisms

The present work investigates the fouling mechanisms of PVDF hollow fibre membrane (0.03 μm) during the dead end ultrafiltration at a fixed permeate flux (outside to inside configuration) of complex synthetic seawater composed by humic acids, alginic acids, inorganic particles and numerous salts at high concentrations. Short term ultrafiltration experiments at 100 L.h-1.m-2 show that the optimal specific filtered volume seems to be equal to 50 L.m-2. A residual fouling resistance equal to 2.1010 m-1 is added after each cycle of filtration during 8h of ultrafiltration at 100 L.h-1.m-2 and 50 L.m-2. Most of the fouling is reversible (80%). Organics are barely (15% of humic acids) retained by the membrane. Backwash efficiency drops during operation which induces less organics into backwash waters. Humic acids could preferentially accumulate on the membrane early in the ultrafiltration and alginic acids after the build-up of a fouling pre-layer. Colloids and particulates could accumulate inside a heterogeneous fouling layer and/or the concentrate compartment of the membrane module before being more largely recovered inside backwash waters.

Processing Bio-Argo nitrate concentration at the DAC Level

The only method used to date to measure dissolved nitrate concentration (NITRATE) with sensors mounted on profiling floats is based on the absorption of light at ultraviolet wavelengths by nitrate ion (Johnson and Coletti, 2002; Johnson et al., 2010; 2013; D’Ortenzio et al., 2012). Nitrate has a modest UV absorption band with a peak near 210 nm, which overlaps with the stronger absorption band of bromide, which has a peak near 200 nm. In addition, there is a much weaker absorption due to dissolved organic matter and light scattering by particles (Ogura and Hanya, 1966). The UV spectrum thus consists of three components, bromide, nitrate and a background due to organics and particles. The background also includes thermal effects on the instrument and slow drift. All of these latter effects (organics, particles, thermal effects and drift) tend to be smooth spectra that combine to form an absorption spectrum that is linear in wavelength over relatively short wavelength spans. If the light absorption spectrum is measured in the wavelength range around 217 to 240 nm (the exact range is a bit of a decision by the operator), then the nitrate concentration can be determined. Two different instruments based on the same optical principles are in use for this purpose. The In Situ Ultraviolet Spectrophotometer (ISUS) built at MBARI or at Satlantic has been mounted inside the pressure hull of a Teledyne/Webb Research APEX and NKE Provor profiling floats and the optics penetrate through the upper end cap into the water. The Satlantic Submersible Ultraviolet Nitrate Analyzer (SUNA) is placed on the outside of APEX, Provor, and Navis profiling floats in its own pressure housing and is connected to the float through an underwater cable that provides power and communications. Power, communications between the float controller and the sensor, and data processing requirements are essentially the same for both ISUS and SUNA. There are several possible algorithms that can be used for the deconvolution of nitrate concentration from the observed UV absorption spectrum (Johnson and Coletti, 2002; Arai et al., 2008; Sakamoto et al., 2009; Zielinski et al., 2011). In addition, the default algorithm that is available in Satlantic sensors is a proprietary approach, but this is not generally used on profiling floats. There are some tradeoffs in every approach. To date almost all nitrate sensors on profiling floats have used the Temperature Compensated Salinity Subtracted (TCSS) algorithm developed by Sakamoto et al. (2009), and this document focuses on that method. It is likely that there will be further algorithm development and it is necessary that the data systems clearly identify the algorithm that is used. It is also desirable that the data system allow for recalculation of prior data sets using new algorithms. To accomplish this, the float must report not just the computed nitrate, but the observed light intensity. Then, the rule to obtain only one NITRATE parameter is, if the spectrum is present then, the NITRATE should be recalculated from the spectrum while the computation of nitrate concentration can also generate useful diagnostics of data quality.

FERTILISER CREDIT AND AGROECOLOGICAL USE OF ORGANIC SOIL AMENDMENTS IN NORTHERN GHANA

Contemporary African agricultural policy embodies the African Green Revolution’s drive towards modernisation and commercialisation. Agroecologists have criticised this movement on ecological, social and political grounds. Northern Ghanaian fertiliser credit schemes provide a good example through which these critiques can be examined in a context where agricultural policy reflects the African Green Revolution’s ideals. This study aimed to determine the relationship of such credit schemes to farmers’ use of organic amendments, elucidate other factors related to organic amendment use, and comment on the relevance of this modernisation policy and its relationship to agroecology. A first research phase employed semi-structured key informant interviews. Qualitative data from these informed construction of a semi-structured questionnaire that was used in a survey of 205 farmers. Multistage sampling purposively identified five villages and selected farmers within who had joined government and donor-funded fertiliser credit schemes. The use of organic and inorganic amendments was compared to that of peers who had not taken part in such schemes. Quantitative data were used in binomial logistic regression, inferential and descriptive statistics. Qualitative data were content analysed. Credit group membership was associated with higher fertiliser application and yield, but had little influence on the extent of commercialisation. Farmers who applied organic amendments were 40% less likely to belong to a fertiliser credit scheme than not, indicating substitution between organic and inorganic fertilisers. Organic amendments were 40% more likely to be applied to compound farms than outfields and six times more likely to be applied by household heads than other household members. However, household heads also preferentially joined credit groups. This was part of an agroecological soil fertility management strategy. Household heads appreciated the soil moisture retention properties of organic amendments, and applied them to compound farms to reduce risk to their household food supply in a semi-arid environment. They simultaneously accessed fertiliser to enhance this household provisioning strategy. They appreciated the increased yields this achieved, yet complained that the repayment terms of credit schemes were unfair, fertiliser did not enhance yields in dry conditions and fertilisers were supplied late. Farmers’ use of credited fertiliser alongside their existing agroecological strategy is helpful to the extent that it raises yields, yet is problematic in that it conflicts with risk-reduction strategies based on organics. There is some potential for modernised and agroecological management paradigms to coexist. For fertiliser credit to play a role in this, schemes must use fairer repayment terms and involve a focus on simultaneous use of organic amendments.

Modeling the Effect of Vapor Wall Deposition on the Formation of Secondary Organic Aerosol in Chamber Studies

Laboratory chamber experiments are used to investigate formation of secondary organic aerosol (SOA) from biogenic and anthropogenic precursors under a variety of environmental conditions. Simulations of these experiments test our understanding of the prevailing chemistry of SOA formation as well as the dynamic processes occurring in the chamber itself. One dynamic process occurring in the chamber that was only recently recognized is the deposition of vapor species to the Teflon walls of the chamber. Low-volatility products formed from the oxidation of volatile organic compounds (VOCs) deposit on the walls rather than forming SOA, decreasing the amount of SOA formed (quantified as the SOA yield: mass of SOA formed per mass of VOC reacted). In this work, several modeling studies are presented that address the effect of vapor wall deposition on SOA formation in chambers.

A coupled vapor-particle dynamics model is used to examine the competition among the rates of gas-phase oxidation to low volatility products, wall deposition of these products, and mass transfer to the particle phase. The relative time scales of these rates control the amount of SOA formed by affecting the influence of vapor wall deposition. Simulations show that an effect on SOA yield of changing the vapor-particle mass transfer rate is only observed when SOA formation is kinetically limited. For systems with kinetically limited SOA formation, increasing the rate of vapor-particle mass transfer by increasing the concentration of seed particles is an effective way to minimize the effect of vapor wall deposition.

This coupled vapor-particle dynamics model is then applied to α-pinene ozonolysis SOA experiments. Experiments show that the SOA yield is affected when changing the oxidation rate but not when changing the rate of gas-particle mass transfer by changing the concentration of seed particles. Model simulations show that the absence of an effect of changing the seed particle concentration is consistent with SOA formation being governed by quasi-equilibrium growth, in which gas-particle equilibrium is established much faster than the rate of change of the gas-phase concentration. The observed effect of oxidation rate on SOA yield arises due to the presence of vapor wall deposition: gas-phase oxidation products are produced more quickly and condense preferentially onto seed particles before being lost to the walls. Therefore, for α-pinene ozonolysis, increasing the oxidation rate is the most effective way to mitigate the influence of vapor wall deposition.

Finally, the detailed model GECKO-A (Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere) is used to simulate α-pinene photooxidation SOA experiments. Unexpectedly, α-pinene OH oxidation experiments show no effect when changing either the oxidation rate or the vapor-particle mass transfer rate, whereas GECKO-A predicts that changing the oxidation rate should drastically affect the SOA yield. Sensitivity studies show that the assumed magnitude of the vapor wall deposition rate can greatly affect conclusions drawn from comparisons between simulations and experiments. If vapor wall loss in the Caltech chamber is of order 10^-5 s^-1, GECKO-A greatly overpredicts SOA during high UV experiments, likely due to an overprediction of second-generation products. However, if instead vapor wall loss in the Caltech chamber is of order 10^-3 s^-1, GECKO-A greatly underpredicts SOA during low UV experiments, possibly due to missing autoxidation pathways in the α-pinene mechanism.