Abstract: Lignin removal plays a crucial role in the efficient bioconversion of lignocellulose to fermentable sugars. As a delignification process, fungal pretreatment has gained great interest due to its environmental friendliness and low energy consumption. In our previous study, a positive linear correlation between acid-insoluble lignin degradation and the achievable enzymatic saccharification yield has been found, hereby highlighting the importance of the close follow-up of lignin degradation during the solid-state fungal pretreatment process. However, the standard quantification of lignin, which relies on the two-step acid hydrolysis of the biomass, is highly laborious and time-consuming. Vibrational spectroscopy has been proven as a fast and easy alternative; however, it has not been extensively researched on lignocellulose subjected to solid-state fungal pretreatment. Therefore, the present study examined the suitability of near-infrared spectroscopy (NIR) for the rapid and easy assessment of lignin content in poplar wood pretreated with Phanerochaete chrysosporium. Furthermore, the predictive power of the obtained calibration model and the recently published ATR-FTIR spectroscopy-based model were compared for the first time using the same fungus-treated wood data set. PLSR was used to correlate the NIR spectra to the acid-insoluble lignin contents (19.9%-27.1%) of pretreated wood. After normalization and second derivation, a PLSR model with a good coefficient of determination (RCV2 = 0.89) and a low root mean square error (RMSECV = 0.55%) were obtained despite the heterogeneous nature of the fungal solid-state fermentation. The performance of this PLSR model was comparably good to the one obtained by ATR-FTIR (RCV2 = 0.87) while it required more extensive spectral pre-processing. In conclusion, both methods will be highly useful for the high-throughput and user-friendly monitoring of lignin degradation in a solid-state fungal pretreatment-based biorefinery concept.

Abstract: Green infrastructure (GI) is already known to be a suitable way to enhance air quality in urban environments. Living wall systems (LWS) can be implemented in locations where other forms of GI, such as trees or hedges, are not suitable. However, much debate remains about the variables that influence their particulate matter (PM) accumulation efficiency. This study attempts to clarify which plant species are relatively the most efficient in capturing PM and which traits are decisive when it comes to the implementation of a LWS. We investigated 11 plant species commonly used on living walls, located close to train tracks and roads. PM accumulation on leaves was quantified by magnetic analysis (Saturation Isothermal Remanent Magnetization (SIRM)). Several leaf morphological variables that could potentially influence PM capture were assessed, as well as the Wall Leaf Area Index. A wide range in SIRM values (2.74–417 μA) was found between all species. Differences in SIRM could be attributed to one of the morphological parameters, namely SLA (specific leaf area). This suggest that by just assessing SLA, one can estimate the PM capture efficiency of a plant species, which is extremely interesting for urban greeners. Regarding temporal variation, some species accumulated PM over the growing season, while others actually decreased in PM levels. This decrease can be attributed to rapid leaf expansion and variations in meteorology. Correct assessment of leaf age is important here; we suggest individual labeling of leaves for further studies. Highest SIRM values were found close to ground level. This suggests that, when traffic is the main pollution source, it is most effective when LWS are applied at ground level. We conclude that LWS can act as local sinks for PM, provided that species are selected correctly and systems are applied according to the state of the art.

Abstract: Generalized Möbius-Listing surfaces and bodies generalize Möbius bands, and this research was motivated originally by solutions of boundary value problems. Analogous to cutting of the original Möbius band, for this class of surfaces and bodies, results have been obtained when cutting such bodies or surfaces. In general, cutting leads to interlinked and intertwined different surfaces or bodies, resulting in very complex systems. However, under certain conditions, the result of cutting can be a single surface or body, which reduces complexity considerably. These conditions are based on congruence and rotational symmetry of the resulting cross sections after cutting, and on the knife cutting the origin

Abstract: Dry deposition is an important process determining pollutant concentrations, especially when studying the influence of urban green infrastructure on particulate matter (PM) levels in cities. Computational fluid dynamics (CFD) models of PM capture by vegetation are useful tools to increase their applicability. The meso-scale models of Zhang et al. (Atmos Environ 35:549-560, 2001) and Petroff and Zhang (Geosci Model Dev 3(2):753-769, 2010) have often been adopted in CFD models, however a comparison of these models with measurements including all PM particle sizes detrimental to health has been rarely reported and certainly not for green wall species. This study presents dry deposition experiments on real grown Hedera helix in a wind tunnel setup with wind speeds from 1 to 4 m s(-1) and PM consisting of a mixture of soot (0.02 – 0.2 mu mu m) and dust particles (0.3 – 10 mu mu m). Significant factors determining the collection efficiency (%) were particle diameter and wind speed, but relative air humidity and the type of PM (soot or dust) did not have a significant influence. Zhang's model outperformed Petroff's model for particles < 0.3 mu mu m, however the inclusion of turbulent impaction in Petroff's model resulted in better agreement with the measurements for particles > 2 – 3 mu mu m. The optimised model had an overall root-mean-square-error of similar to 4% for collection efficiency (CE) and 0.4 cm s-1 for deposition velocity (nu d), which was shown to be highly competitive against previously described models. It can thus be used to model PM deposition on other plant species, provided the correct parameterisation of the drag by this species. A detailed description of the spatial distribution of the vegetation could solve the underestimation for particle sizes of 0.3 – 2 mu mu m.

Abstract: Indoor air pollution affects the global population, especially in developed countries where people spend around 90% of their time indoors. The recent pandemic exacerbated the exposure by relying on indoor spaces and a teleworking lifestyle. VOCs are a group of indoor air pollutants with harmful effects on human health at low concentrations. It is widespread that plants can remove indoor VOCs. To this day, research has combined principles of phytoremediation, biofiltration, and bioremediation into a holistic and sustainable technology called botanical biofiltration. Overall, it is sustained that its main advantage is the capacity to break down and biodegrade pollutants using low energy input. This differs from traditional systems that transfer VOCs to another phase. Furthermore, it offers additional benefits like decreased indoor air health costs, enhanced work productivity, and well-being. However, many disparities exist within the field regarding the role of plants, substrate, and phyllosphere bacteria. Yet their role has been theorized; its stability is poorly known for an engineering approach. Previous research has not addressed the bioaugmentation of the phyllosphere to increase the performance, which could boost the system. Moreover, most experiments have studied passive potted plant systems at a lab scale using small chambers, making it difficult to extrapolate findings into tangible parameters to engineer the technology. Active systems are believed to be more efficient yet require more maintenance and knowledge expertise; besides, the impact of the active flow on the long term is not fully understood. Besides, modeling the system has been oversimplified, limiting the understanding and optimization. This review sheds light on the field’s gains and gaps, like concepts, experiments, and modeling. We believe that embracing a multidisciplinary approach encompassing experiments, multiphysics modeling, microbial community analysis, and coworking with the indoor air sector will enable the optimization of the technology and facilitate its adoption.

Abstract: The number and composition of species in a community can be quantified with alpha-diversity indices, including species richness (R), Simpson's index (D), and the Shannon-Wiener index (HGREEK TONOS). In forest communities, there are large variations in tree size among species and individuals of the same species, which result in differences in ecological processes and ecosystem functions. However, tree size inequality (TSI) has been largely neglected in studies using the available diversity indices. The TSI in the diameter at breast height (DBH) data for each of 999 20 m x 20 m forest census quadrats was quantified using the Gini index (GI), a measure of the inequality of size distribution. The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat. We also examined the relationships of alpha-diversity indices with the GI using correlation tests. The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions, with most root-mean-square errors (990 out of 999 quadrats) being < 0.0030. There were significant positive correlations between each of three alpha-diversity indices (i.e., R, D, and H') and the GI. Nevertheless, the total abundance of trees in each quadrat did not significantly influence the GI. This means that the TSI increased with increasing species diversity. Thus, two new indices are proposed that can balance alpha-diversity against the extent of TSI in the community: (1 – GI) x D, and (1 – GI) x H'. These new indices were significantly correlated with the original D and HGREEK TONOS, and did not increase the extent of variation within each group of indices. This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities, especially in the face of cumulative species loss under global climate change.

Abstract: Rhodotorula kratochvilovae has shown to be a promising species for microbial oil production from lignin-derived compounds. Yet, information on R. kratochvilovae’s detoxification and microbial oil production is scarce. This study investigated the growth and microbial oil production on the phenolic-containing effluent from poplar steam explosion and its detoxification with five R. kratochvilovae strains (EXF11626, EXF9590, EXF7516, EXF3697, EXF3471) and compared them with Cutaneotrichosporon oleaginosum. The R. kratochvilovae strains reached a maximum growth rate up to four times higher than C. oleaginosum. Furthermore, all R. kratochvilovae strains generally degraded phenolics more rapidly and to a larger extent than C. oleaginosum. However, the diluted substrate limited the lipid production by all strains as the maximum lipid content and titre were 10.5% CDW and 0.40 g/L, respectively. Therefore, future work should focus on increasing lipid production by using advanced fermentation strategies and stimulating the enzyme excretion by the yeasts for complex substrate breakdown.