On-Line Process Analysis of Biomass Flash Pyrolysis Gases Enabled by Soft Photoionization Mass Spectrometry

In the current discussion about future energy and fuel supply based on regenerative energy sources, the so-called second-generation biofuels represent a vitally important contribution for the provision of carbon-based fuels. In this framework, at the Karlsruhe Institute of Technology (KIT), the bioliq process has been developed, by which biomass is flash-pyrolyzed at 500 °C for the production of so-called biosyncrude, a suspension of the pyrolysis liquids and the remaining biochar. However, little is known about the composition of the pyrolysis gases in this process with regard to different biomass feedstock and process conditions, and the influence on the subsequent steps, namely, the gasification and subsequent production of biofuels or base materials. Time-of-flight mass spectrometry (TOFMS) with two soft (i.e., fragmentation free) photoionization techniques was for the first time applied for on-line monitoring of the signature organic compounds in highly complex pyrolysis gases at a technical pyrolysis pilot plant at the KIT. Resonance-enhanced multiphoton ionization with TOFMS using UV laser pulses was used for selective and sensitive detection of aromatic species. Furthermore, single-photon ionization using VUV light supplied by an electron beam-pumped excimer light source was used to comprehensively ionize (nearly) all organic molecules. For the miscellaneous biomass feeds used, distinguishable mass spectra with specific patterns could be obtained, mainly exhibiting typical pyrolytic decomposition products of (hemi)­cellulose and lignin (phenol derivatives), and nitrogen-containing compounds in some cases. Certain biomasses are differentiated by their ratios of specific groups of phenolic decomposition products. Therefore, principal component and cluster analysis describes the varied pyrolysis gas composition for temperature variations and particularly for different biomass species. The results can be integrated in the optimization of the bioliq process

An alternative <i>in vitro</i> model considering cell-cell interactions in fiber-induced pulmonary fibrosis

Particularly since the wide-ranging health effects of asbestos exposure became known, great emphasis has been placed on detailed toxicity testing of known but also newly developed fiber materials. Exposure to respirable pollutants like fibers can lead to tissue injury causing lung diseases such as pulmonary fibrosis or cancer. In order to detect the toxic potential of such aerosols at an early stage, the development of suitable test systems is essential. In this study, we illustrate the development of an advanced in vitro cell model closely resembling the physiological structure of the alveoli, and we highlight its advantages over simpler models to predict pro-fibrotic changes. For this reason, we analyzed the cytotoxic effects of fiber-like multi-walled carbon nanotubes after 24 and 48 h exposure, and we investigated inflammatory, genotoxic and pro-fibrotic changes occurring in the developed triple culture consisting of lung epithelial cells, macrophages and fibroblasts compared to a co-culture of epithelial cells and fibroblasts or a mono culture of epithelial cells. In summary, the triple culture system is more precisely able to detect a pro-fibrotic phenotype including epithelial-mesenchymal transition as well as secondary genotoxicity, even if exhibiting lower cytotoxicity in contrast to the less advanced systems. These effects might be traced back to the complex interplay between the different cell types, all of which play an important role in the inflammatory response, which precedes wound healing, or even fibrosis or cancer development.</p

Levels of intracellular metabolite pools in aerosol-exposed macrophages.

<p>Pools of (a) lactic acid, (b) succinic acid, and itaconic acid were measured. Levels represent the mean of 9 biological replicates. *** = p < 0.001. Error bars represent s.e.m.</p

HFO particles induce activation of immune response in RAW 264.7 macrophages.

<p>(a) The Gene Ontology term GO:0006955, corresponding to activation of immune response, was found to be significantly up-regulated in HFO-treated samples (p = 0.059) and not regulated in the DF-treated samples. (b) Model of how the regulated proteins found in this study affect the NF-kB immune response pathway in the cell. Stimulation of the toll-like receptor (TLR2) leads to activation of NF-kB. Tumor necrosis factor alpha-induced protein 8-like protein 2 (TNFAIP8L2) acts as a negative regulator of TLR2, preventing hyperresponsiveness of the immune system, and inhibiting NF-kappa-B activation. Peroxiredoxin 2 (Pdrx2) reduces hydrogen peroxide, inhibiting NF-kappa-B activation.</p

Experimental set-up and global omics analyses.

<p>(A) An 80 KW common-rail-ship diesel engine was operated with heavy fuel oil (HFO) or refined diesel fuel (DF). The exhaust aerosols were diluted and cooled with clean air. On-line real-time mass spectrometry, particle-sizing, sensor IR-spectrometry and other techniques were used to characterise the chemical composition and physical properties of the particles and gas phase. Filter sampling of the particulate matter (PM) was performed to further characterise the PM composition. Lung cells were synchronously exposed at the air-liquid-interface (ALI) to aerosol or particle-filtered aerosol as a reference. The cellular responses were characterised in triplicate at the transcriptome (BEAS-2B), proteome and metabolome (A549) levels with stable isotope labelling (SILAC and ¹³C₆-glucose). (B) Heatmap showing the global regulation of the transcriptome, proteome and metabolome.</p

Chemical and physical aerosol characterisation.

<p>(A) The ship diesel engine was operated for 4 h in accordance with the IMO-test cycle. (B) Approximately 28 ng/cm² and 56 ng/cm² were delivered to the cells from DF and HFO, respectively, with different size distributions. The HFO predominantly contained particles <50 nm, and the DF predominantly contained particles >200 nm, both in mass and number. (C) Number of chemical species in the EA particles. (D) Transmission electron microscope (TEM) images and energy-dispersive X-ray (EDX) spectra of DF-EA and HFO-EA; heavy elements (black speckles, arrow); and contributions of the elements V, P, Fe and Ni in the HFO particles using EDX (* = grid-material). (E) Exemplary EA concentrations (right) and concentration ratios (left) for particulate matter-bound species. For all experiments, n = 3.</p

Summary of the main HFO- and DF-particle exposure effects.

<p>The arrows indicate the direction of regulation for cellular functions derived from the most statistically significant enriched Gene Ontology terms from the transcriptome, proteome, and metabolome (details in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126536#pone.0126536.s012" target="_blank">S2 Table</a>).</p><p>^x BEAS-2B up, A549 down</p><p>* BEAS-2B down, A549 up</p><p>Summary of the main HFO- and DF-particle exposure effects.</p

Effects of shipping particles on lung cells.

<p>The net effects from the particles were referenced against the gaseous phase of the emissions. (A) Number of the regulated components in the transcriptome shows more genes regulated by the DF than the HFO particles (in BEAS-2B cells). Similar results were observed for the proteome (B) and metabolome (C) (in A549 cells). (D) Meta-analyses for the transcriptome and proteome using the combined Gene Ontology (GO) term analysis of the 10% most regulated transcripts and proteins. Individual GO terms are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126536#pone.0126536.s012" target="_blank">S2 Table</a>; the hierarchical pathways are indicated on the right. (E) Gene regulation of Wiki-pathway bioactivation; (F) gene regulation of Wiki-pathway inflammation; g, secreted metabolites; and h, metabolic flux measurements using ¹³C-labelled glucose. For all experiments, n = 3.</p