Desulphurisation kinetics of thiophenic compound by sulphur oxidizing Klebsiella oxytoca SOB-1

Principal component analysis-multivariate adaptive regression splines (PCA-MARS) and back propagation-artificial neural network (BP-ANN) methods for predicting the efficiency of oxidative desulfurization systems using ATR-FTIR spectroscopy

Oxidative desulfurization (ODS) of diesel fuels has received attention in recent years due to mild working conditions and effective removal of the aromatic sulfur compounds. There is a need for rapid, accurate, and reproducible analytical tools to monitor the performance of ODS systems. During the ODS process, sulfur compounds are oxidized to their corresponding sulfones which are easily removed by extraction in polar solvents. The amount of extracted sulfones is a reliable indicator of ODS performance, showing both oxidation and extraction efficiency. This article studies the ability of a non-parametric regression algorithm, principal component analysis-multivariate adaptive regression splines (PCA-MARS) as an alternative to back propagation artificial neural network (BP-ANN) to predict the concentration of sulfone removed during the ODS process. Using PCA, variables were compressed to identify principal components (PCs) that best described the data matrix, and the scores of such PCs were used as input variables for the MARS and ANN algorithms. Thecoefficientofdeterminationincalibration (R²_c), root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were calculated for PCA-BP-ANN (R²_c = 0.9913, RMSEC = 2.4206 and RMSEP = 5.7124) and PCA-MARS (R²_c = 0.9841, RMSEC = 2.7934 and RMSEP = 5.8476) models and were compared with the genetic algorithm partial least squares (GA-PLS) (R²_c = 0.9472, RMSEC = 5.5226 and RMSEP = 9.6417) and as the results reveal, both methods are better than GA-PLS in terms of prediction accuracy. The proposed PCA-MARS and PCA-BP-ANN models are robust models that provide similar predictions and can be effectively used to predict sulfone containing samples. The MARS algorithm builds a flexible model using simpler linear regression and is computationally more efficient than BPNN due to data-driven stepwise search, addition, and pruning.

Microbes-mediated sulphur cycling in soil: Impact on soil fertility, crop production and environmental sustainability

Reduction in soil fertility and depletion of natural resources due to current intensive agricultural practices along with climate changes are the major constraints for crop productivity and global food security. Diverse microbial populations' inhabiting the soil and rhizosphere participate in biogeochemical cycling of nutrients and thereby, improve soil fertility and plant health, and reduce the adverse impact of synthetic fertilizers on the environment. Sulphur is 4th most common crucial macronutrient required by all organisms including plants, animals, humans and microorganisms. Effective strategies are required to enhance sulphur content in crops for minimizing adverse effects of sulphur deficiency on plants and humans. Various microorganisms are involved in sulphur cycling in soil through oxidation, reduction, mineralization, and immobilization, and volatalization processes of diverse sulphur compounds. Some microorganisms possess the unique ability to oxidize sulphur compounds into plant utilizable sulphate (SO₄^2-) form. Considering the importance of sulphur as a nutrient for crops, many bacteria and fungi involved in sulphur cycling have been characterized from soil and rhizosphere. Some of these microbes have been found to positively affect plant growth and crop yield through multiple mechanisms including the enhanced mobilization of nutrients in soils (i.e., sulphate, phosphorus and nitrogen), production of growth-promoting hormones, inhibition of phytopathogens, protection against oxidative damage and mitigation of abiotic stresses. Application of these beneficial microbes as biofertilizers may reduce the conventional fertilizer application in soils. However, large-scale, well-designed, and long-term field trials are necessary to recommend the use of these microbes for increasing nutrient availability for growth and yield of crop plants. This review discusses the current knowledge regarding sulphur deficiency symptoms in plants, biogeochemical cycling of sulphur and inoculation effects of sulphur oxidizing microbes in improving plant biomass and crop yield in different crops.

Deciphering the biodesulfurization potential of two novel Rhodococcus isolates from a unique Greek environment

Sustainable biodesulfurization (BDS) processes require the use of microbial biocatalysts that display high activity against the recalcitrant heterocyclic sulfur compounds and can simultaneously withstand the harsh conditions of contact with petroleum products, inherent to any industrial biphasic BDS system. In this framework, the functional microbial BDS-related diversity in a naturally oil-exposed ecosystem, was examined through a 4,6-dimethyl-dibenzothiophene based enrichment process. Two new Rhodococcus sp. strains were isolated, which during a medium optimization process revealed a significantly enhanced BDS activity profile when compared to the model strain R. qingshengii IGTS8. In biocatalyst stability studies conducted in biphasic mode using partially hydrodesulfurized diesel under various process conditions, the new strains also presented an enhanced stability phenotype. In these studies, it was also demonstrated for all strains, that the BDS activity losses were decoupled from the overall cells' viability, in addition to the fact that the use of whole-broth biocatalyst positively affected BDS performance.

Monitoring of Remaining Thiophenic Compounds in Liquid Fuel Desulphurization Studies Using a Fast HPLC-UV Method

Thiophenic compounds constitute a class of sulfur compounds derived by thiophene, containing at least one thiophenic ring. Their presence in fuels (crude oil, etc.) is important and can reach 3% m/m. The combustion of fuels leads to the formation of sulfur oxides a severe source of environmental pollution issues, such as acid rain with adverse effects both to humans and to the environment. To reduce such problems, the EU and other regulatory agencies worldwide set increasingly stringent regulations for sulfur content in fuels resulting in the necessity for intense desulphurization processes. However, most of these processes are inefficient in the total removal of sulfur compounds. Therefore, thiophenic compounds such as benzothiophenes and dibenzothiophenes are still present in heavier fractions of petroleum, therefore, their determination is of great importance. Until now, all HPLC methods applied in similar studies use gradient elution programs that may last more than 25 min with no validation results provided. To fill this gap, the aim of the present study was to develop and validate a simple and fast HPLC-UV method in order to be used as a useful monitoring tool in the evaluation studies of novel desulfurization technologies by means of simultaneous determination of dibenzothiophene (DBT) and 4,6-dimethyl-dibenzothiophene and dibenzothiophene sulfone in the desulfurization effluents.