Brewers’ spent grain (BSG) is an important waste produced in beer companies with a high po-tential to be transformed into commercial by-products. The present paper reports a forecasting technology study with the aid of bibliographic review and patent analysis tools aiming to in-vestigate the maturity of certain technologies, considering the use of BSG on a closed-loop bio-refinery and circular bioeconomy concept integrated into a brewery. To evaluate the possibili-ties of production of high-added value products in Brazil, it was presented an overview of BSG’s scientific, technological, and marketing products and applications. The comparison between numbers of articles versus patents shows that the solutions proposed by research articles are not being transformed into maturated viable technologies. The results suggest that there is a gap between the scientific research in the institutions and their applications in industry, which lead to the destination of the BSG for more economically attractive investments when compared to research in Brazil. Ultimately, from the carried-out analysis, it was possible to propose a brew-ing process connected to the biorefinery system, showing the possibility to the newly arising brewery industries.

Plant roots have significant effects on the soil erosion rates, since they can strongly change the soil detachment capacity (Dc). This study quantifies Dc at different flow rates in soils with Alnus subcordata species, compared to three other species (Brachythecium plumose, Gleditsia caspica and Sambucus ebulus species) in the Saravan forest park and develops regression equations for predicting Dc. Undisturbed samples collected from soils with the four tree species and subjected to five slopes (from 4.3 to 38.3%) and five water discharges (from 0.28 to 0.71 l m−1 s−1) using a hydraulic flume. The results showed that Dc was significantly lower in soils with Alnus subcordata species compared to Brachythecium plumose, Gleditsia caspica and Sambucus ebulus species, as the consequence of the changes in the root characteristics, so that Dc was negatively correlated with root weight density, root length and root biomass. The unit stream power had high accuracy for predicting Dc for all of the studied species. The lowest value of rill erodibility (Kr) was obtained in soils with Alnus subcordata species using regression relationship between the Dc and the shear stress of the soil. This experiment helped to show the importance of plant roots in reducing the soil detachment rates and provided a contribution in understanding the choice of appropriate species for soil conservation.

Citron watermelon (Citrullus lanatus var. citroides) is an extremely drought-tolerant cucurbit crop widely grown in sub-Saharan Africa in arid and semi-arid environments characterized by drought. The species is a C3 xerophyte used for multiple purposes, including intercropping with maize and has a deep taproot system. The deep taproot system plays a key role in the species’ adaptation to dry conditions. Understanding root system development of this crop could be useful in identifying traits for breeding water-use efficient and drought-tolerant varieties. This study compared root system architecture of citron watermelon accessions under water-stress conditions. Nine selected and drought-tolerant citron watermelon accessions were grown under non-stress (NS) and water stress (WS) conditions using the root rhizotron procedure in a glasshouse. The following root system architecture (RSA) traits were measured, namely: root system width (RSW), root system depth (RSD), convex hull area (CHA), total root length (TRL), root branch count (RBC), total root volume (TRV), leaf area (LA), leaf number (LN), first seminal root length (FSRL), seminal root angle (SRA), root dry mass (RDM), shoot dry mass (SDM), root–shoot mass ratio (RSM), root mass ratio (RMR), shoot mass ratio (SMR) and root tissue density (RTD). The data collected on RSA traits were subjected to the analysis of variance (ANOVA), correlation and principal component analyses. ANOVA revealed a significant (p < 0.05) accession × water stress interaction effect for studied RSA traits. Under WS, RDM exhibited significant and positive correlations with RSM (r = 0.65), RMR (r = 0.66), RSD (r = 0.66), TRL (r = 0.60), RBC (r = 0.72), FSRL (r = 0.73) and LN (r = 0.70). Principal component analysis revealed high loading scores for the following RSA traits: RSW (0.89), RSD (0.97), TRL (0.99), TRV (0.90), TRL (0.99), RMR (0.96) and RDM (0.76). In conclusion, the study has shown that the identified RSA traits could be useful in crop improvement programmes for citron watermelon genotypes with enhanced drought adaptation for improved yield performance under drought-prone environments.

The main purpose of this study was to determine the size and direction of the seasonal dynamics of organic carbon (Сmicro) and nitrogen (Nmicro) biomass of microorganisms and microbial index (Cmicro : Corg) of natural and agrocenoses with their different uses. Field research methods involved taking of soil samples in 0-10-, 10-20- and 20-40 сm layers. Under laboratory conditions, the content of total soil carbon was determined by dry oxygen combustion on a Vario EL III analyzer (Elementar Analyzensysteme, Hanau, Germany). The carbon content of microbial biomass (Сmicro) was determined by chloroform fumigation extraction method (CFE). To freshly taken soil samples (2 hours) and soil samples after their 24-hour fumigation with chloroform vapors, 0.5 M K2SO4 was added to extract biomass lysis products of soil microorganisms. The content of organic carbon and nitrogen in the biomass of microorganisms in the obtained filtrates was determined on the Elementar Liqui TOC II, Analyzensysteme GmbH, Germany. The carbon content of microbial biomass was calculated from the difference between carbon in fumigated and control samples using a factor of 0,45 - for carbon and 0,54 – for nitrogen. The microbial index of soils was determined by the ratio between the carbon of microorganisms and the total organic carbon of the soil – Cmicro : Corg • 100 (%). Average values and confidence intervals were determined for each defined indicator. The Bonferoni method was used to correct the errors of multiple comparative samples of a one-way ANOVA analyze. K. Pearson’s linear correlation analysis was used to establish the relationships between the dynamics of carbon biomass of microorganisms and organic carbon of the soil during the growing season. Our research has shown the dynamics of Сmicro, Nmicro, Сmicro : Nmicro and Cmicro : Corg during the growing season. Analysis of the box plot showed the largest amplitude of Сmicro changes in the upper 0-10 cm layer of izogumusol. The smallest difference in the quartile range (IQR0,25-0,75) was for no-till and overhang (Ab) in the upper 0-10-, no-till (NT) and fallow (F) - in the layer 10-20- and plowing (CT) - in a layer of 20-40 cm. The content of organic carbon biomass of microorganisms in the upper layer of izogumusol at the beginning of the growing season had the highest values of Ab (577,79  1,64 mg/kg), NT (485,43  1,97 mg/kg) and CT (470,43  0,77 mg/kg), the smallest - for F (370,15  2,18 mg/kg). The content of Nmicro during this period decreased from Ab to Comb (combined tillage), NT, CT, Rot (rotary tillage), RT (reduced (ridge) tillage) and F, respectively. In the 20-40 cm layer, the highest values of Сmicro and Nmicro were observed in mid-July. The lowest values of Сmicro and Nmicro and the largest – Сmicro : Nmicro were found in late August for all variants and layers of the study. The dynamics of the microbial index resembled the trends of Сmicro and Nmicro. The largest share of Smicro in Sorghum during the growing season, on average was: - Ab (1,82  1,85 %) and NT (1,66  1,52 %) - in the layer 0-10-, - Ab (1,23  1,27 %) and NT (1,29  1,32 %) - in the layer 10-20- and - Ab (1,19  1,09 %) and F (1,11  1,077 %) - in a layer of 20-40 cm. Different use of izogumusol affected the amplitude of seasonal changes of Сmicro and Nmicro and did not affect on their direction. The maximum content of Сmicro and Nmicro was observed at the beginning of the growing season - in a layer of 0-10 cm and in mid-July - in a layer of 20-40 cm, the minimum - at the end of the summer period. During this period, the widest ratio of Сmicro : Nmicro was for F and CT - in the layer 0-20 cm and CT and Rot - in the layer 20-40 cm. The Pearson’s correlation coefficient between Сmicro and Corg increased from the upper 0-10- to the lower 20-40 cm layer of izogumusol. "Strong" and "high" negative correlations have been established between Сmicro and Corg, but no pattern has been found between the correlation coefficient and tillage technologies.

Chaparral shrublands are the dominant wildland vegetation type in southern California and the most extensive ecosystem in the state. Disturbance by wildfire and climate change have created a dynamic landscape in which biomass mapping is key in tracking the ability of chaparral shrub-lands to sequester carbon. Despite this importance, most national and regional scale estimates do not account for shrubland biomass. Employing plot data from several sources, we built a random forest model to predict above ground live biomass in southern California using remote sensing data (Landsat NDVI) and a suite of geophysical variables. By substituting the NDVI and precipi-tation predictors for any given year we were able to apply the model to each year from 2000-2019. Using a total of 980 field plots, our model had a k-fold cross validation R2 of 0.51 and a RMSE of 3.9. Validation by vegetation type ranged from R2 = 0.17 (RMSE=9.7) for Sierran mixed conifer to R2 = 0.91 (RMSE = 2.3) for sagebrush. Our estimates showed an improvement in accuracy over a two other biomass estimates that included shrublands, with an R2 = 0.82 (RMSE = 4.7) compared to R2 = 0.068 (RMSE = 6.7) for a global biomass estimate and R2 = 0.29 (RMSE = 5.9) for a regional biomass estimate. Given the importance of accurate biomass estimates for resource managers we calculated the mean year 2010 shrubland biomass for the four national forests which ranged from 3.5 kg/m2 (Los Padres) to 2.3 kg/m2 (Angeles and Cleveland). Finally, we compared our estimates to field-measured biomass from the literature summarized by shrubland vegetation type and age class. Our model provides a transparent and repeatable method to generate biomass measure-ments in any year, thereby providing data to track biomass recovery after management actions or disturbances such as fire.

Utilization of Bidirectional Reflectance Distribution Function (BRDF) model parameters obtained from the multi-angular remote sensing is one of the approaches for the retrieval of vegetation structural information. In this research, the potential of multi-angular vegetation indices, formulated by the combination of multi-spectral reflectance from different view angles, for the retrieval of forest above ground biomass was assessed. This research was implemented in the New England region with the availability of a high quality forest inventory database. The multi-angular vegetation indices were generated by the simulation of the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters Product (MCD43A1 Version 6) based BRDF parameters. The effects of seasonal (spring, summer, autumn, and winter) composites of the multi-angular vegetation indices on above ground biomass, angular relationship of the spectral reflectance with above ground biomass, and the interrelationships between the multi-angular vegetation indices were analyzed. Among the existing multi-angular vegetation indices, only the Nadir BRDF-adjusted NDVI ( and Hot-spot incorporated NDVI ( showed significant relationship (more than 50%) with the above ground biomass. This research proposed two more sensitive vegetation structural indices, Fore-scattering Back-scattering NDVI and Vegetation Structure Index (VSI). The Fore-scattering Back-scattering NDVI showed higher sensitivity (R² = 0.62, RMSE = 52.46) towards the above ground biomass than existing multi-angular vegetation indices. Furthermore, the VSI performed in the most efficient way explaining 64% variation of the above ground biomass, suggesting that the right choice of the spectral channel and observation geometry should be considered for improving the estimates of the above ground biomass. In addition, the right choice of seasonal data (summer) was found to be important for estimating the forest biomass while other seasonal data were either insensitive or pointless. The promising results shown by the VSI suggest that it could be an appropriate candidate for monitoring vegetation structure from the multi-angular satellite remote sensing.

In the industrial production of olive oil, both solid wastes and those produced from their incineration are a serious environmental problem since only 20% w/w of the fruit becomes oil and the rest is waste, mainly orujo and alperujo. A key aspect to transform these wastes into an important source of energy such as pellets is to recognize the most appropriate time of the year for waste drying, with the objective of minimizing the environmental impact of the volatile compounds contained in the waste. In this work, the emissions produced during thermal-mechanical drying were studied along a period of six months of waste storage in which alperujo and orujo were stored in open containers under uncontrolled environmental conditions. The studied emissions were produced when both wastes were dried in a pilot rotary drying trommel at 450ºC to reduce their initial humidity of around 70-80% w/w to 10-15% w/w. Results indicated that when the storage time of the wastes in uncontrolled environments increases, the emission of odorant compounds during drying also increases as a consequence of the biological and chemical processes occurring in the containers during waste storage. The main odorant VOCs were quantified monthly for six months at the outlet of the drying trommel. It was determined that the drying of this type of waste can be carried out properly until the third month of storage. Afterwards, the concentration of most VOCs produced widely exceeded the odor thresholds of selected compounds.

Antioxidant activity is an essential feature required for oxygen-sensitive merchandise and goods, such as food and corresponding packaging as well as materials used in cosmetics and biomedicine. For example, vanillin, one of the most prominent antioxidants, is fabricated from lignin, the second most abundant natural polymer in the world. Antioxidant potential is primarily related to the termination of oxidation propagation reactions through hydrogen transfer. The application of technical lignin as a natural antioxidant has not yet been implemented in the industrial sector, mainly due to the complex heterogeneous structure and polydispersity of lignin. Thus, current research focuses on various isolation and purification strategies to improve the compatibility of lignin material with substrates and enhancing its stabilizing effect. This contribution presents antioxidant capacity studies of various lignins depending on purification degree of the raw material. In detail, the antioxidant potential of lignin-based compounds is studied using the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay. The purification procedure was monitored by thin layer chromatography (TLC) and showed that double-fold selective extraction is the most efficient purification procedure (confirmed by UV-Vis, FTIR, HSQC and 31P NMR spectroscopy, SEC and XRD analysis). Results are discussed regarding the dependency of antioxidant activity on lignin structure and biomass source. Thus, lignins obtained from industrial black liquor are compared with beech wood samples. In addition, the influence of lignin isolation (kraft versus organosolv) is discussed. Values of the antioxidant activity (DPPH inhibition) of kraft lignin fractions were 62-68% while beech and spruce/pine-mixed lignins showed values between 26, 64 and 42%, respectively. TPC values of the different isolated kraft lignin fractions varied between 26-35%, while beech, spruce/pine lignins were 34, 30 and 34%, respectively. Storage decreased the TPC values and increased the DPPH inhibition.

Activated carbons can be produced from biomass in a thermal process either in a direct carbonization-activation process or by first carbonizing the biomass and later on activating the biochars into activated carbons. The properties of the ACs are dependent on the type of process used for production. In this study, the properties of activated carbons produced in a one-stage and a two-stage process are considered. Activated carbons were produced by physical activation of two types of starting materials, bio chars produced from spruce and birch chips in a commercial carbonization plant and from the corresponding raw chips. The activated carbons produced were characterized regarding specific surfaces, pore volumes and pore size distributions. The un-activated bio chars had some degree of surface area 190 and 140 m²g^-1 for spruce and birch and pore volumes of 0.067 and 0.092 cm³g^-1. According to the results obtained, two slightly different types of activated carbons are produced depending if a one-stage or a two-stage carbonization and activation process is used. The ACs produced in the one-stage process had higher specific surface areas compared to the ones produced in a two-stage process (761-940 m²g^-1 vs. 540-650 m²g^-1) . In addition, total pore volumes were higher in one-stage process but development of micropores is greater compared to two-stage process. There was no significant difference in total carbon content between one-stage and two-stage process.

Lignocellulosic biomass has garnered attention as an abundant and sustainable alternative energy source that can facilitate reliable and environmentally friendly energy generation. Energy security improves, and environmental impacts diminish when bioethanol, a biofuel produced via lignocellulose-based processes, is utilized. The lignocellulosic biomass of Thysanolaena latifolia has considerable potential as a bioethanol feedstock due to its high carbohydrate content (62.4 ± 0.7%). In this study, feedstock derived from T. latifolia was pretreated with various concentrations of H3PO4 to determine the ideal conditions for enzymatic hydrolysis to convert the feedstock to fermentable sugar. The findings revealed that hydrolysis efficiency and glucose recovery yields were substantially improved compared to those of the untreated sample. Pretreated samples were enzymatically digested to produce a liquid hydrolysate. This hydrolysate was fermented without detoxification using Saccharomyces cerevisiae TISTR 5339 to produce ethanol. The results indicated that T. latifolia biomass hydrolysate is a promising long-term carbon source for ethanol production from cellulosic biomass. Furthermore, the morphological and crystallographic characteristics of the treated T. latifolia biomass were influenced by H3PO4 concentration, as indicated by the SEM images, X-ray diffractogram patterns, and crystallinity index values. Therefore, utilizing T. latifolia feedstock to produce bioethanol can enhance bioenergy sustainability.

Soil, geochemical, microbiological and archaeological studies were conducted at eight settlements dating from the Paleolithic to Late Medieval and New Times near the Southern Trans-Urals mountains, Russia. The forest-steppe landscapes, rivers and abundance of mineral resources have attracted people to region since ancient times. Properties of cultural layer (CLs): close to neutral pH, well structured, absence of salinity, enrichment with exchangeable calcium and anthropogenic phosphorus (0.2–0.4%). The majority of CLs start from 3–25 cm and last up to 40–60 cm and contain 6–10% organic carbon (Corg), in a layer of 0–20 cm because modern processes are developing here, at Ishkulovo site (around 14th century) Corg decreases to 1.3%, because CL is below 80 cm and in the absence of fresh organic material it is mineralized. The content of microbial biomass of the 0–10 cm layer is 520–680 μg С/g of soil, microbes cause the emission of 0.2–1.0 μg C–CO2/g soil per h. The proximity of the studied sites to deposits of copper, chromium, zinc, manganese and Magnitogorsk Metallurgical and Uchaly processing plants creates geochemical anomalies of soils. Pollutants are also released into the CLs from bronze products, ore, ceramic fragments and raw materials from their manufacture. It leads to the concentration of pollutants of the 1st (arsenic, lead, zinc) and 2nd (cobalt, copper, nickel, chromium) hazard classes in the studied CLs, often in quantities higher than the clarke and less often – more than the allowable content for human health.

The utilization of solar energy technology is crucial for generating hydrogen in sustainable energy systems. While traditional methods involving natural gas, coal, and oil have been employed for hydrogen production, this study aims to explore environmentally friendly techniques. Green hy-drogen, despite being a more expensive option compared to fossil fuel-derived hydrogen, has prompted engineers to develop affordable and low-carbon technologies. The microgrid model was developed to showcase a self-contained DC islanded system designed to supply power to an electrolyzer, capitalizing on both a solar array and an energy storage unit. This comprehensive model offers a versatile platform for evaluating the operational dynamics involved in the sustainable production of green hydrogen. Over a span of seven days, it permits the as-sessment of hydrogen generation characteristics through the utilization of solar energy, either di-rectly from a solar array or through an integrated system that incorporates energy storage. The model encompasses a multi-domain framework, encompassing electrical, thermal liquid, and thermal gas aspects, facilitating a holistic exploration of the intricate processes underlying the green hydrogen production system. Through this simulation, the feasibility and efficiency of harnessing renewable energy sources for hydrogen production in an off-grid setting can be comprehensively examined and optimized, contributing to the advancement of sustainable energy solutions.

Shrubland and forestland covers are highly prone to fire. The Normalized Difference Vegetation Index (NDVI) has been widely used for biomass quantitative assessment. This study aims were the following: (1) to compute the NDVI annual curve for two types of land cover eucalypts and shrubland areas; (2) to collect field data in these two types of land cover to estimate aboveground biomass (AGB); and (3) to produce AGB maps for eucalypts and shrubland areas by modelling AGB with NDVI and validate them with other data sources. A study area in the central inland Portugal was considered. The Sentinel-2 MSI imagery for the year of 2022 and 2023 were used to compute the NDVI. The NDVI annual curve for 2022 showed a minimum observed between July and August, in accordance with the climatological data, and allowed differentiating eucalypts from shrubland areas. Spectral signatures also confirmed this differentiation. The fitted linear models for AGB prediction using the NDVI imagery showed good fitting performances (R2 of 0.76 and 0.69). The AGB maps provide a relevant decision support tool for forest management and for fire hazard and fire severity mitigation. Further research is needed using more robust data sets for models’ independent validation.

Pygoscelis penguin populations in the Antarctic Peninsula have dropped dramatically in the last 50 years. The main probable cause is the reduction in Krill (Euphausia superba), the most important feeding item for Pygoscelis penguins during breeding. The scientific community has expressed concerns on the potential that competition with the fishery during periods of low krill availability might be exacerbating the effects of climate change. By bringing together data on breeding success of penguin colonies throughout the Antarctic Peninsula with information of krill availability from acoustic survey and krill fishery monitoring data, we were able to show that fishery has had in the past an effect over breeding success. That is a consequence of a management strategy based on a constant catch level enabling the fishery to maintain the same levels of production even when krill availability is low. The total catch limit may have represented a substantial amount of the available krill biomass in some years, and we detected that when the catch goes over 5% of the available biomass during summer, breeding success of penguins decreased by one third. We discuss the implications of our findings to the revised ecosystem-based management strategy of the krill fishery in Antarctica.

The building sector of most tropical countries still use predominantly primary biomass as the principal fuel. This has adverse effects like CO2 emission and deforestation and is associated with issues like poverty, ill-health, and low standard of living. Therefore, energy policies try to improve on the efficiency of firewood and charcoal end-use technologies, to palliate the negative effects. In this research, the global change assessment model (GCAM) is used, to investigate the impact of efficiency improvement on the energy consumption pattern of the building sector of developing countries. The aim of the study is to provide empirical data that would better inform policymakers on the effects of modernizing these primary fuels. The study developed three scenarios with different levels of efficiency improvements. The results show that efficiency improvement rather increases primary biomass consumption and CO2 emission. However, there is a fall in the consumption of traditional biomass in the second half of the modelling period. The increase in biomass-based fuels consumption was seen to be linked to their affordability. Therefore, policymakers need not only elaborate policies that improve biomass efficiency, but also introduce and motivate other clean cooking fuels like butane, biogas, and electricity.

As a renewable industrial crop, Miscanthus offers numerous advantages, namely high photosynthesis activity (as a C4 plant) and exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. Here, we present a systematic study analyzing the correlation of the lignin structure with Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. Depending on the Miscanthus genotype and plant component (leaf versus stem), correlations between chemical structure and properties of the lignins have been determined, i.e. correlations in molecular weight, polydispersity and decomposition temperature. Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes NREL, FTIR, UV-Vis, HSQC-NMR, TGA, pyrolysis GC/MS. Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (< 1.5 Miscanthus vs. > 2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as low-input resource and Miscanthus-derived lignin as promising agricultural feedstock.

Maritime Continent (MC) positions in between Asian and Australian summer monsoons zone. Its complex topography and shallow seas around it is a major challenge for the climate researchers to model and understand it. Monsoon in this area is affected by inter-scale ocean-atmospheric interactions like El-Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden-Julian Oscillation. Monsoon rainfall in MC (especially in Indonesia and Malaysia) profoundly exhibits its variability dependency on ocean-atmospheric phenomena in this region. This monsoon shift often introduces to dreadful events like biomass burning (BB) in Southeast Asia (SEA) which sometimes leads to severe trans-boundary haze pollution. In this study, the episode of BB in 2015 of SEA is highlighted and discussed. Observational satellite datasets are tested by performing simulations with numerical weather prediction (NWP) model using WRF-ARW (Advanced research WRF). Observed and model datasets are compared to study the sea surface temperature (SST) and precipitation (rainfall) anomalies influenced by ENSO, IOD and MJO. Correlations have been recognised which explains the delayed rainfall of regular monsoon in MC due to the influence of ENSO, IOD and MJO during 2015 BB episode, eventually leading to intensification of fire and severe haze.

Nanoparticles (NP), Nanoaerosols (NA), ultrafine particles (UFP), and PM0.1 (particles with a diameter ≤ 0.1 µm or 100 nm) are interchangeably used in the field of atmospheric studies. PM0.1 are emitted from both natural and anthropogenic sources. The main emission sources of PM0.1 are combustion processes, including biomass and fossil fuel. Moreover, secondary formation via atmospheric photochemical reactions can also occur depending on meteorological conditions and the suspended pollutant species. Identifying the physical and chemical characteristics and spatial and temporal variations is vital in terms of understanding the effect of NPs on the environment, the global climate, and human health risks. This review article summarizes recent research on PM0.1 in Thailand. The review involves peer-reviewed papers from Scopus and the Web of Science databases, and includes the most recently published articles in the past ten years (2013-2022). UFPs mainly come from the combustion processes such as motor vehicles. The high mass concentration of PM0.1 that occurs during the dry season in which open fires depend on the specific region of Thailand. Particulate pollution from local and cross-border countries also needs to be considered in terms of the concentrations of ambient nanoparticles. The overall conclusions reached will likely have a beneficial long-term impact on achieving a blue sky over Thailand through the development of coherent policies and managing new air pollution challenges and sharing knowledge with a broader audience.

2,5-Di(hydroxymethyl)furan (DHMF) is a high-value chemical block than can be synthesized from 5-hydroxymethylfurfural (HMF), a platform chemical that results from the dehydration of biomass-derived carbohydrates. In this work, the HMF biotransformation capability of different Fusarium species was evaluated and F. striatum was selected to produce DHMF. The effects of the inoculum size, glucose concentration and pH of the media over DHMF production were evalu-ated by a 23 factorial design. A substrate feeding approach was found suitable to overcome the toxicity effect of HMF towards the cells when added at high concentrations (>75 mM). The pro-cess was successfully scaled-up at bioreactor scale (1.3 L) with excellent DHMF production yields (95%) and selectivities (98%). DHMF was purified from the reaction media with high recovery and purity by organic solvent extraction with ethyl acetate.

The Bacillus megaterium LVN01 species native to Colombia has demonstrated the ability to metabolize different co-products or industrial waste (such as fique juice, cane molasses, residual glycerol) and accumulate polyhydroxybutyrate (PHB), giving it potential in the bioplastics industry. In this research, the potential of liquid digestate as a carbon source for the production of PHA in fermentation processes with this bacterial strain was evaluated. Favorably, it was found that B. megaterium utilizes the nutrients from this residual substrate to multiply appropriately and efficiently synthesize poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV). Bench scale aerobic batch fermentation, under the operational conditions of this research [Volume: 3L; Temperature: 30.8°C; Agitation: 400 rpm; pH: 7.0 ± 0.2; Disolved Oxygen: 100% saturation; Antifoam 10% (v/v)], generated maximum values of DCW (0.56 g cell L-1) at 60 h, while the maximum PHB yield (360 mg PHB L-1) occurred at 16 h, which is very favorable for sustainable degradable bioplastics production. Additionally, GC-MS and NMR analyses confirmed that the PHBV copolymer synthesized by B. megaterium is made up of the monomers 3-hydroxybutyrate (3HB) and 3-hydroxyvalerate (3HV). Furthermore, the thermal properties determined by TGA (Tonset=283.1 ºC, Tendset= 296.98 ºC. Td =290.114 °C) and DSC (Tm= ºC155.7 °C, ΔHf= 19.80 J g-1, Xcr = 18.17%), indicate that it is a thermally stable biopolymer with low percentages of crystallinity, providing flexibility that facilitates molding, adaptation, and application in various industrial sectors.

The Circular Bioeconomy (CBE) combines the concepts of bioeconomy and circular economy. As an alternative concept to the current fossil-based, linear economy, it de-scribes an economy based on the efficient valorization of biomass. It is regional in nature and aims to improve sustainability. An analysis of the transition process, by identifying its success criteria and assessing its impacts through the modelling of technology-specific scenarios is necessary to ensure that CBE concepts are sustainable. However, a compre-hensive consideration of regional influences on both is lacking. Based on extensive literature research and an expert survey, we (i) present a compre-hensive catalog of CBE success criteria and discuss their region-specific character and (ii) develop a methodology based on evaluation matrices that enable to match CBE technolo-gies with regions. The matrices support the evaluation of technological and regional characteristics influencing the successful CBE implementation. The results show that the success criteria "biomass resources", "technological", and "social" are perceived as highly important, and that most of the success criteria are both region- and technology-specific, highlighting the relevance of developing matrices to match them. We describe such matrices indicatively for the two broadest and most im-portant success criteria clusters “social acceptance” and “biomass supply chain”. With this, we substantiate the regional nature of CBE and raise the awareness on the importance of considering regional conditions in CBE transition processes. Furthermore, we provide practical guidance on how regional conditions can be reflected in the selection of technologies, e.g. in regional CBE technology scenarios.

The ultimate analysis parameters including carbon (C), hydrogen (H), nitrogen (N), and oxygen (O) content in biomass was rarely found to be predicted by nondestructive tests until to date. In this research, we developed partial least squares regression (PLSR) models to predict the ultimate analysis parameters of chip biomass using near infrared (NIR) raw spectra of non-wood and wood samples from fast growing tree and agricultural residue and nine different traditional spectral preprocessing techniques. These techniques include first derivative (sd1), second derivative (sd2), constant offset, standard normal variate (SNV), multiplicative scatter correction (MSC), vector normalization, min-max normalization, mean centering, sd1 + vector normalization, and sd1 + MSC. Additionally, we employed a genetic algorithm (GA), successive projection algorithm (SPA), multi-preprocessing (MP) 5−range, and MP 3−range to develop a PLSR model for rapid prediction. A dataset consisting of 120 chip biomass samples was utilized for model development in which the samples was non-wood samples of 65-67% and wood samples was 33-35%, and the model performance were evaluated and compared. The selection of the optimum performing model was mainly based on criteria such as the coefficient of determination in the prediction set (R2P), root mean square error of the prediction set (RMSEP), and the ratio of prediction to deviation values (RPD). The optimal model for weight percentage (wt.%) of C was obtained using GA−PLSR, yielding R2P, RMSEP, and RPD values of 0.6954, 1.1252 wt.%, and 1.8, respectively. Similarly, for wt.% of O, the most effective model was obtained using the multi-preprocessing PLSR−5 range method with R2P of 0.7150, RMSEP of 1.3088 wt.%, and RPD of 1.9. For wt.% of N, the optimal model was obtained using the MP PLSR−3 range method, resulting in R2P, RMSEP, and RPD values of 0.6073, 0.1008 wt.%, and 1.6, respectively. However, wt.% of H model provided R2P, RMSEP, and RPD values of 0.5162, 0.2322 wt.%, and 1.5, respectively. Notably, the limit of quantification (LOQ) values for C, H, and O were lower than the minimum reference values used during model development, indicating a high level of sensitivity. However, the LOQ for N, exceeded the minimum reference value, implying the samples to be predicted by the model must be in the range of reference range in calibration set. By scatter plot analysis, the effect of combined non-wood and wood spectra of biomass chips on rapid prediction of ultimate analysis parameters using NIR spectroscopy was investigated. To include different species in a model, the species have to be not only in the different values of the constituents to make a wider range for robust model but also they must provide their trend line characteristics in the scatter plot i.e. correlation coefficient (R), slope and intercept (same slope and slope approached to 1 and intercept is same (no gap) and approached zero, high R approached to 1). The effect of the R, slope and intercept to obtain the better optimized model were studied. The results show that the different species affected model performance of each parameter prediction in a different manner and by scatter plot analysis which of these species were affecting the model negatively and how the model could be improved was indicated. This is the first time of the effect is studied by the principle of scatter plot.

Biomass exploitation is a global trend due to the circular economy and the environmentally friendly spirit. Numerous applications are now based on the use of biomass derived products. Hydrogen sulfide (H2S) is a highly toxic and environmentally hazardous gas, which emitted from various processes. Thus, the efficient removal of this toxic hazardous gas following cost effective processes is an essential requirement. In this study, we present the synthesis and characterization of biomass-derived activated-carbon/zinc-oxide (ZnO@AC) composites from different biomass sources as potential candidates for H2S sorption. The synthesis involved a facile method for activated carbon production via pyrolysis and chemical activation of biomass precursors (spent coffee, Aloe-Vera waste leaves, and corncob). Activated carbon production was followed by the incorporation of zinc oxide nanoparticles into the porous carbon matrix using a simple melt impregnation method. The synthesized ZnO@AC composites were characterized using X-ray diffraction (XRD), infrared spectroscopy (IR), thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and nitrogen porosimetry. The H2S removal performance of the ZnO@AC composites was evaluated through sorption experiments using a handmade apparatus. Our findings demonstrate that the Aloe-Vera, Spent-coffee, and Corncob derived composites exhibit superior H2S sorption capacity up to 106 mgH2S/gads., 66 mgH2S/gads., and 47 mgH2S/gads. respectively.

As a consequence of intense industrialization in the last few decades, the amount of agro-industrial wastes has increasing, where new forms of valorization are crucial. In this work, 5 residual biomasses from Maranhão (Brazil) were investigted as supports for immobilization of lipase from Thermomyces lanuginosus (TLL). The new biocatalysts BM-TLL (babaçu mesocarp) and RH-TLL (rice husk) showed immobilization efficiencies &gt;98% and hydrolytic activities of 5,331 U.g-1 and 4.608 U. g-1 respectively against 142 U. g-1 by Lipozyme® TL IM. High esterification activities were also found, with 141.4 U.g-1 and 396.4 U.g-1 from BM-TLL and RH-TLL against 113.5 U.g-1 by TL IM. Results of porosimetry, SEM and BET demonstrated BM and RH supports are mesoporous materials with large hydrophobic area, allowing a mixture of hydrophobic adsorption and confinement, resulting in hyperactivation of TLL. These biocatalysts were applied in the production of hexyl laurate, where RH-TLL was able to generate 94% conversion in 4 h. Desorption with Triton X-100 and NaCl confirmed that new biocatalysts were more efficient with 5 times less protein than commercial TL IM. All results demonstrated that residual biomass was able to produce robust and stable biocatalysts containing immobilized TLL with better results than commercial preparations.

Mushroom production in Poland is an important and dynamically developing element of diverse agriculture. Mushroom spent compost (MSC) is major waste generated during production, i.e., MSC: mushrooms is ~5:1. To date, the main use of MSC is soil application as organic fertilizer. To date, several methods of MSC treatment have been researched and developed including production of compost, bioethanol, biogas, enzyme lactase, xylo-saccharides, and hydrogen. Torrefaction may be considered a novel approach for biomass valorization. Thus, we are pioneering the potential use of MSC valorization via torrefaction. We explored valorizing the waste biomass of MSC via thermal treatment – torrefaction (‘roasting’) to produce biochar with improved fuel properties. Here for the first time, we examined and summarized the MSC torrefaction thermogravimetric analyses, fuel properties data of raw biomass of MSC and biochars generated from MSC via torrefaction. The effects of torrefaction temperature (200~300 °C), process time (20~60 min), on fuel properties of the resulting biochars were summarized. The dataset contains results of thermogravimetric analysis (TGA) as well as proximate analyses of MSC and generated biochars. The presented data are useful in determining MSC torrefaction reaction kinetics, activation energy and to further techno-economical modeling of the feasibility of MSC valorization via torrefaction. MSC torrefaction could be exploited as part of valorization resulting from a synergy between an intensive mushroom production with the efficient production of high-quality renewable fuel.

As the EU is moving towards a low carbon economy and seeks to further develop its renewable energy policy, this paper quantitatively investigates the impact of plausible energy market reforms from the perspective of bio-renewables. Employing a state-of-the-art biobased variant of a computable general equilibrium model, this study assesses the perceived medium-term benefits, risks and trade-offs which arise from an advanced biofuels plan, two exploratory scenarios of a more 'sustainable' conventional biofuels plan and a 'no-mandate' scenario. Consistent with more recent studies, none of the scenarios considered present significant challenges to EU food-security or agricultural land usage. An illustrative advanced biofuels plan simulation requires non-trivial public support to implement whilst a degree of competition for biomass with (high-value) advanced biomass material industries is observed. On the other hand, it significantly alleviates land use pressures, whilst lignocellulose biomass prices are not expected to increase to unsustainable levels. Clearly, these observations are subject to assumptions on technological change, sustainable biomass limits, expected trends in fossil fuel prices and EU access to third-country trade. With these same caveats in mind, the switch to increased bioethanol production does not result in significant market tensions in biomass markets.

Surface area and pore size distribution of Eucalyptus samples pretreated by different methods were determined by the Brunauer-Emmett-Teller (BET) technique. Three methods were applied to prepare cellulosic biomass samples for BET measurements: air, freeze, and critical point drying (CPD). Air and freeze drying caused severe collapse of biomass pore structures, but CPD effectively preserved biomass morphology. Surface area of CPD prepared Eucalyptus samples was determined to be 58–161 m2/g, whereas air and freeze dried samples were 0.5–1.3 and 1.0–2.4 m2/g, respectively. Average pore diameter of CPD prepared Eucalyptus samples were 61–70Å. CPD preserved Eucalyptus sample morphology by replacing water with a non-polar solvent, CO2 fluid, which prevented hydrogen bond reformation in the cellulose.

Solventogenic Clostridium species are important for establishing sustainable industrial bioproduction of fuels and important chemicals. The inherent versatility of these species in substrate utilization and the range of solvents produced during acetone butanol-ethanol (ABE) fermentation make solventogenic Clostridium an attractive choice for biotechnological applications such as production of fuels and chemicals. The functional qualities of these microbes have thus been identified to be due to complex regulatory networks that play essential roles in modulating the metabolism of this group of bacteria. Genomes of solventogenic Clostridium species have relatively greater prevalence of genes that are intricately controlled by various regulatory molecules than most other species. Consequently, the use of genetic or metabolic engineering strategies that do not consider the underlying regulatory mechanisms will not be effective. Several regulatory factors involved in substrate uptake/utilization, sporulation, solvent production, and stress responses (Carbon Catabolite Protein A, Spo0A, AbrB, Rex, CsrA) have been identified and characterized. In this review, the focus is on newly identified regulatory factors in solventogenic Clostridium species, the interaction of these factors with previously identified molecules, and potential implications on substrate utilization, solvent production, and resistance/tolerance to lignocellulose-derived microbial inhibitory compounds.

This study analyzed the CO2 capture potential for Parque Natural Regional Serrania de las Quinchas buffer area in Colombia. For this purpose, multitemporal analysis for land covering for years 1989, 2000, 2006, 2011, 2017 and 2021 was made using the Normalized Difference Vegetation Index (NDVI), and Corine Land Cover (CLC) methodology. In the same way, Aboveground Biomass (AGB) was measured for representative parcels by measuring tree’s diameters and heights and applying the adequate allometric models; carbon content in soils was measured too. Results show that dense forest has grown since 1989 and the carbon stock in all the vegetation covers increased by 14,3% from 1989 until 2021, using literature data for tropical humid forests. If measured AGB values obtained in this study are used, the carbon stock average is 3 times this value. Measured carbon average content in AGB was 374,3 Ton C/Ha, well above the average for the content reported for humid tropical forests in Colombia; carbon content in soils was 897,19 Ton/Ha, 2,4 times that found in the AGB. In total, an average of 1271,49 Ton C/Ha (AGB+ soil) was found and a pattern of dense forest recovery was found, but in a more dispersed way than in the past. A very interesting potential for existing forests recovery was found for this area. Strategies for this include the development of sustainable practices, land use management, everything pursuing biodiversity preservation and the participation and leading of the local communities.

“Blue carbon”, apart from marine humus, includes the carbon (C) stock of coastal ecosystems such as mangroves, marshes, and seagrass meadows, which have been overlooked until recently. Information about the role of coastal wetlands in C sequestration and providing other ecosystem services is still insufficient. In the present study, we assessed the C reserves of soils and vegetation biomass in two complex coastal landscapes (tombolos) located on the coasts of the White and Baltic seas. The soil and plant C stocks were slightly higher at the plot at the Baltic Sea (93.4 ± 46.7 Mg C·ha-1 and 5.22 ± 2.51 Mg C·ha-1, respectively) than at the plot on the White Sea (71.4 ± 38.2 Mg C·ha-1 and 3.95 ± 2.42 Mg C·ha-1, respectively). We attributed the higher values of the C reserved to a warmer climate and less saline water at the plot on the Baltic Sea. Both soil and plant C showed high heterogeneity due to geomorphological complexity and differences in vegetative communities. The Phragmites australis community showed the highest plant biomass and, in some places, high soil C reserves. Allochthonous C contributed to the soil C stock at the site on the White Sea. Though P. australis sequestered more C than other communities, its effect on ecosystem services was mostly negative because the invasion of reeds reduced the biological diversity of the marshes.

Precision farming, a labor-saving and highly productive management, is gaining popularity as the number of farmers declines in contrast to the increasing global food demand. However, it requires more efficient crop phenology observation and growth monitoring. One measure is the Leaf Area Index (LAI), which is essential for estimating biomass and yield, but its validation requires destructive field measurements. Remote sensing offers a non-destructive and effective method for ground- and UAV-based field observations. Thus, in this study, a method for indirect estimation of LAI was investigated using ground and UAV observation data. A weekly plant survey was done to measure the plant height, above-ground biomass, and light intensity. Furthermore, images from ground-based and UAV-based cameras were acquired to generate NDVI and the canopy height (CH), respectively. Using the canopy photosynthetic model, derived from Lambert-Beer’s law, the daily biomass was estimated by applying the weekly estimated LAI using CH, and the observed light intensity data as input. The results demonstrated the possibility of quantitatively estimating the daily growth biomass of rice plants, including its spatial variation. The near-real-time estimation method of rice biomass by integrating observation data at fields with numerical models can be applied to the management of major crops.

Through the use of machine learning algorithms like the Support Vector Machine, it has been show that burn extent can be accurately mapped from hyperspatial drone imagery in both grasslands and forests. Despite these successes, hyperspatial imagery must be acquired via drones, requiring large amounts of time and resources to capture areas much smaller than the large catastrophic fires which result in the majority of the lands burned each year by wildland fires. To overcome this difficulty, high spatial resolution satellite imagery from Worldview2 can be substituted for hyperspatial drone imagery, allowing for larger regions of images to be acquired more easily and efficiently. Additionally, Worldview2 trades spatial resolution for spectral resolution and extent, capturing images in 8 multispectral bands as opposed to 3 band imagery in the visible spectra. This research examines the utility of each of the 8 bands observed in Worldview2 imagery using an Iterative Dichotomiser 3 decision tree, then uses these bands to map burn extent and biomass consumption. Several classifications of burn extent and biomass consumption are produced and compared based on the bands used as inputs. The results show that using Worldview2 imagery to map burn extent and biomass consumption results in highly accurate maps, with slight improvements when additional bands are added.

The new climate law introduces a policy of sustainable construction, the assumption of which is the reduction of CO2 by the construction industry and the use of environmentally friendly materials, such as agricultural, mineral, and recycled waste, while limiting the consumption of natural resources. The article is a literature review that analyzes selected waste materials from various sectors of the economy that can be used as additives or partial substitutes for natural resources in the production of cement and in and cement building materials, the production of which reduces CO2 emissions, producing materials with high mechanical strength and environmentally friendly.

The development of platinum group metal-free (PGM-free) electrocatalysts derived from cheap and environmentally friendly biomasses for oxygen reduction reaction (ORR) is a topic of relevant interest, particularly from the point of view of sustainability. Fe-nitrogen-doped carbon materials (Fe-N-C) have attracted particular interest as alternative to Pt-based materials, due to the high activity and selectivity of Fe-Nx active sites, the high availability and good tolerance to poisoning. Recently, many studies focused on developing synthetic strategies, which could transform N-containing biomasses into N-doped carbons. In this paper chitosan was employed as a suitable N-containing biomass for preparing Fe-N-C catalyst in virtue of its high N content (7.1%) and unique chemical structure. Moreover, the major application of chitosan is based on its ability to strongly coordinate metal ions, a precondition for the formation of Fe-Nx active sites. The synthesis of Fe-N-C consists in a double step thermochemical conversion of a dried chitosan hydrogel. In acidic aqueous solution, the preparation of physical cross-linked hydrogel allows to obtain sophisticated organization, which assure an optimal mesoporosity before and after the pyrolysis. After the second thermal treatment at 900 °C, a highly graphitized material was obtained, which has been fully characterized in term of textural, morphological and chemical properties. RRDE technique was used for understanding the activity and the selectivity of the material versus the ORR in 0.5 M H2SO4 electrolyte. Special attention was put in the determination of the active site density according to nitrite electrochemical reduction measurements. It was clearly established that the catalytic activity expressed as half wave potential linearly scales with the number of Fe-Nx sites. It was also established that the addition of the iron precursor after the first pyrolysis step leads to an increased activity because of both an increased number of active sites and of a hierarchical structure, which improves the access to active sites. At the same time, the increased graphitization degree, and a reduced density of pyrrolic nitrogen groups are helpful to increase the selectivity toward the 4e- ORR pathway.

This paper presents ensemble learning of multi-source satellite sensors dataset to obtain better predictive performance of the forest biomass. Spectral, spectral-indices, and spectral-textural features were generated from two optical satellite sensors, Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI). In addition, two radar satellite sensors, Sentinel-1 C-band Synthetic Aperture Radar (CSAR), and Advanced Land Observing Satellite (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) were utilized to generate backscattering and backscattering-textural features. The plot-wise above ground biomass data available from five forests in New England region were utilized. Ensemble learning of multi-source satellite sensors dataset was carried out by employing four machine learning regressors namely, Support Vector Machines (SVM), Random Forests (RF), Gradient Boosting (GB), and Multilayer Perceptron (MLP). A five-fold cross-validation method was used to evaluate predictive performance of the multi-source satellite sensors. The integration of multi-source satellite features, comprising of spectral, spectral-indices, backscattering, spectral-textural, and backscattering-textural information, through ensemble learning and cross-validation approach implemented in the research showed promising results (R² = 0.81, RMSE = 46.2 Mg/ha) for the estimation of plots-level forest biomass in New England region.

Reduced nutrient mineralization rates under minimum tillage are usually compensated by mineral fertilizer application. These cannot be applied in organic farming systems, however. We hypothesized that organic minimum tillage based on frequent cover cropping and application of dead mulch will improve soil fertility and can compensate for the potential negative effects of minimum tillage. Two long-term field experiments were set up in 2010 and 2011 comparing plough versus minimum tillage including application of transferred mulch. As second factor, the application of compost versus mineral potassium and phosphorus was compared. In 2019, soils were analyzed for soil pH, organic carbon, macro-, micronutrients, microbial biomass, microbial activity and total nematode abundance. In addition, performance of pea in the same soils was determined under greenhouse conditions. Across both experiments, macronutrients (+52%), micronutrients (+11%), microbial biomass (+51%), microbial activity (+86%), and bacterivorous nematodes (+112%) increased in minimum tillage compared with the plough-based system. In the greenhouse, pea biomass was 45% higher in the soil that had been subjected to minimum tillage compared to the plough. In conclusion, soil fertility can be improved in organic minimum tillage systems by intensive cover cropping and application of dead mulch to levels higher than in a plough-based system.

Strip-mined land (SML) disturbed by coal-mining is the non-crop land resource that can be utilized to cultivate high-yielding energy crops such as miscanthus for bioenergy applications. However, the biomass yield potential, annual availability and environmental impacts on growing energy crops in SML are less understood. In this study, we estimated the yield potential of miscanthus (Miscanthus sinensis) in SML and its environmental impacts on local streams using the Soil and Water Assessment Tool (SWAT). After calibration and validation of the SWAT model, the results demonstrated that miscanthus yield potentials were 2.6 (0.8−5.53), 10.0 (1.3−16.0) and 16.0 (1.34−26.0) Mg ha^-1 with the fertilizer application rate of 0, 100, and 200 kg-N ha^-1 respectively. Furthermore, cultivation of miscanthus in the SML has the potential to reduce sediment (~20%) and nitrate (2.5%−10.0 %) loads reaching to water streams with a marginal increase in phosphorus load. The available SML in the United States could produce about 10 to 16 dry Tg of biomass per year without negatively impacting the water quality. In conclusion, SML can provide a unique opportunity to produce biomass for bioenergy applications, while improving stream water quality in highly dense mining area (the Appalachian region) in the United States.

In this short review paper we have assembled the main characteristics of partial oxidation reactions (oxidative dehydrogenation and selective oxidation to olefins or oxygenates, as aldehydes and carboxylic acids and nitriles), as well as total oxidation, particularly for depollution, environmental issues and wastewater treatments. Both gas-solid and liquid-solid media have been considered with recent and representative examples within these fields. We have also discussed about their potential and prospective industrial applications. Particular attention has been brought to new raw materials stemming from biomass and to liquid-solid catalysts cases. This review paper also summarizes the progresses made in the use of unconventional activation methods for performing oxidation reactions, highlighting the synergy of these technologies with heterogeneous catalysis. Focus has been centered on usual catalysts activation methods but also on less usual ones, such as the use of ultrasounds, microwaves, grinding (mechanochemistry) and photo-activated processes, as well as their combined use.

Understory plants are important components of forest ecosystem productivity and diversity. Compared to biomass models of overstory canopy trees, few are available for understory saplings and shrubs and therefore their roles in estimation of forest carbon pools are often ignored. In this study, we harvested 24 understory species including 4 saplings, 9 tree-like shrubs and 11 typical shrubs in coniferous and broadleaved mixed forest in northeastern China and developed the best fit allometric equations of above- and below-ground and total biomass by species-specific or multispecies using morphological measurements of basal diameter, height and crown area as independent variables. The result showed that single basal diameter, height or crown area had good explanatory power for both species-specific and multispecies (p<0.001). The best-fit models included only basal diameter in sapling and tree-like shrubs, and combinations of crown area, height, and basal diameter in typical shrubs. The logarithmic model was most desired among the 4 model forms of linear, quadratic, multiple linear and logarithmic, for species-specific and multispecies. The models we developed should help the estimation of forest ecosystem carbon stocks, especially for belowground component, and provide tools for quantification of individual species biomass of understory plants.

The present study evaluates mold fungal resistance of newly developed loose-fill thermal insulation materials from wheat straw, corn stalk and water reed. Three different processing methods of raw materials was performed by mechanical crushing (Raw, ≤ 20 mm), thermal-mechanical pulping (TMP) using 4% NaOH and steam explosion pulping (SEP). An admixture of boric acid (8%) and tetraborate (7%) was applied to all processed substrates due to their anti-fungal properties. Additionally, the fourth sample group was prepared from SEPs of all raw species without boric acid and tetraborate (SEP*) as control. Samples from all treatments were separately inoculated by 5 different fungal species and incubated in darkness for 28 days at 28 ℃ and RH &gt;90%. The highest resistance to the colonization of mold fungi was achieved by TMP and SEP processing coupled with addition of boric acid and tetraborate, where molds infest only around 35% to 40% of the inoculated sample area. The lowest mold fungi resistance was detected for Raw and SEP* samples, each ~75% that was affected by rich amount of accessible nutrients, suggesting that boric acid and tetraborate additives alone did not prevent mold fungal growth as effective as in combination with TMP and SEP treatments. Together, the achieved fungal colonization scores after combined fungicide and pulping treatments are acceptable for the application of various renewable materials in future thermal insulation product development.

We present a novel passive satellite remote sensing approach for observing the three-dimensional distribution of aerosols emitted from wildfires. This method, called AEROS5P, retrieves vertical profiles of aerosol extinction from measurements of the TROPOMI satellite sensor onboard the Sentinel 5 Precursor mission. It uses a Tikhonov-Phillips regularization which iteratively fits cloud-free near-infrared and visible selected reflectances to simultaneously adjust the vertical distribution and abundance of aerosols. The information on the altitude of the aerosol layers is provided by TROPOMI measurements of the reflectance spectra at the oxygen A-band near 760 nm. In the present paper, we use this new approach for observing the daily evolution of the three-dimensional distribution of biomass burning aerosols emitted by Australian wildfires on 20-24 December 2019. Aerosol optical depths (AOD) derived by vertical integration of the aerosol extinction profiles retrieved by AEROS5P are compared with MODIS, VIIRS and AERONET coincident observations. They show a good agreement in the horizontal distribution of biomass burning aerosols, with a correlation coefficient of 0.86 and a mean absolute error of 0.2 with respect to VIIRS. A fair agreement is found between coincident transects of vertical profiles of biomass burning aerosols derived from AEROS5P and from the CALIOP spaceborne lidar. The mean altitude of these aerosols derived from these two measurements show a good agreement, with a small mean bias (185 m) and a correlation coefficient of 0.83. Moreover, AEROS5P observations reveal the height of injection of the biomass burning aerosols in 3D. The highest injection heights during the period of analysis are coincident with the largest fire radiative power derived from MODIS. Consistency is also found with respect to the vertical stability of the atmosphere.

Currently, energy security and environmental degradation are the two biggest challenges before humanity that can be surmounted with the use of green and sustainable biofuels produced from lignocellulosic crops. In the future, to ensure adequate and cost-effective supply of biofuels, it requires a sufficient amount of amenable and quality lignocellulosic feedstocks. Therefore, agricultural yields of lignocellulosic biomass crops should be substantially increased by intense genetic maneuvering of key gene regulatory mechanisms and signaling pathways that control plant biomass yield. Recently, numerous miRNAs families are identified, characterized, and validated across the plant kingdom. Plant microRNAs (miRNAs) are 21 to 24 nucleotides long, non-coding small RNAs, act as regulators of their target genes via inducing modifications in transcription, translation, and epigenome. MiRNAs represent many hallmark characteristics like sequence-specific regulation, tissue, and species-specific expression, evolutionary conservation, and functional diversity. They coordinate well physiological and life cycle processes in plants under adverse environmental conditions. Hence, miRNAs offer accurate, precise, and efficient regulatory switches in the miRNA-targeted genetic networks. It is evident from the study of the miR156 family and its target SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) genes network that controls highly significant agronomic traits in crop plants. The miR156/SPL module acts as a master circuit that synchronizes many intricate complex biological functions such as growth and development, and metabolic processes by sensing internal and external environmental signals in plants. Therefore, miR156 can prove a potential target for miRNAs based plant biotechnology to harmonize complex biofuel traits and improve biomass yield in lignocellulosic biomass crops.

Thrombosis is characterized by the pathological formation of fibrin clots within a blood vessel, leading to the obstruction of blood flow. Fibrinolytic enzymes from microorganisms have exhibited promising effects to dissolve clots in a more efficient and safe way. Then, the aim of this study was to evaluate the biomass and fibrinolytic enzyme production of Tetradesmus obliquus under autotrophic and mixotrophic conditions using different concentration of corn steep liquor (CSL). Different extraction and precipitating methods were tested, and the enzyme was purified by ion exchange chromatography. More advantageous culture condition was mixotrophic using 0.25% CSL, showing the highest values of biomass productivity (Px = 169.3 ± 44.36 mg∙L-1day-1) and specific growth rate (µmax = 0.17 ± 0.00 day-1), and significant fibrinolytic production (391.34 ± 40.03 U∙mg-1). Moreover, fibrinolytic activity was higher when extracted by homogenization and precipitated using acetone, which exhibited clear zone of fibrin degradation in the fibrinolytic plate assay. Additionally, the purified enzyme showed specific activity of 1176.90 ± 140.37 U∙mg-1 and molecular weight around 97 kDa. Finally, the enzyme has higher enzymatic activity than various fibrinolytic enzymes, and the obtained enzyme has potential to be developed as a therapeutic agent in thrombosis treatment. Additional studies are need to investigate the biochemical properties and biological profile of this enzyme.

Forest degradation is known to be widespread in the tropics, but is currently very poorly mapped, in part because there is little quantitative data on which satellite sensor characteristics and analysis methods are best at detecting it. To improve this, we used data from the Tropical Forest Degradation Experiment (FODEX) plots in the southern Peruvian Amazon, where different numbers of trees had been removed from four 1 ha forest plots, carefully inventoried by hand and Terrestrial Laser Scanning before and after the logging to give a range of biomass change (ΔAGB) values. We conducted a comparative study of six multispectral optical satellite sensors (WorldView-3, SkySat, SPOT-7, PlanetScope, Sentinel-2 and Landsat 8) at 0.3 – 30 m spatial resolution, to find the best combination of sensor and remote sensing indicator for change detection. Spectral reflectance, the Normalized Difference Vegetation Index (NDVI) and texture parameters were extracted after radiometric calibration and image preprocessing. The strength of the relationships between the change in these values and field-measured ΔAGB (computed in % ha−1) was analysed. The results demonstrate that: (a) texture measures correlates more with ΔAGB than simple spectral parameters; (b) the strongest correlations are achieved for those sensors with spatial resolutions in the intermediate range (1.5 - 10 m), with finer or coarser resolutions producing worse results, and (c) when texture is computed using a moving square window ranging between 9 - 14 m in length. Maps predicting ΔAGB showed very promising results using a NIR-derived texture parameter for 3 m resolution PlanetScope (R2 = 0.97 and RMSE = 1.80 % ha−1), followed by 1.5 m SPOT-7 (R2 = 0.74 and RMSE = 5.25 % ha−1) and 10 m Sentinel-2 (R2 = 0.71 and RMSE = 5.55 % ha−1). Texture models derived from 0.3 m WorldView-3 improved with increasing window size, with highest R2 of 0.62 and RMSE = 6.35 % ha−1 for a window of 14 m in length. The degradation in our field plots is invisible to the 30 m resolution Landsat data. Our findings imply that, at least for lowland Peru, low-medium intensity disturbance can be detected best in optical wavelengths using a texture measure derived from 3 m PlanetScope data. That such data are being collected daily, and currently released free as monthly mosaics over tropical forests as part of the Norway’s International Climate and Forest Initiative (NICFI), is excellent news for monitoring such degradation.

Ethanol produced from various biobased sources (bioethanol) has been gaining high attention lately due to its potential to cut down net emissions of carbon dioxide while reducing burgeoning world dependence on fossil fuels. Global ethanol production has increased more than six-fold from 18 billion liters at the turn of the century to 110 billion liters in 2019 (1,2). Sugar cane and corn have been used as the major feedstocks for ethanol production. Lignocellulosic biomass has recently been considered as another potential feedstock. This paper reviews recent developments and current status of commercial production of ethanol across the world. The review includes the ethanol production processes used for each type of feedstock, both currently practiced at commercial scale and newly developed technologies, and production trends in various regions and countries in the world.

Morphological parameters like cotton height, branches, Leaf Area Index and biomass are mainly affected by the vegetation water content (VWC). Periodical assessment of the VWC and crop parameters is required for timely management of the crop for maximizing yield. The study aimed at using both optical and microwave remotely sensed data to assess cotton crop condition based on the above mentioned traits. Vegetation indices (VI) derived from ground based measurements (5 narrow band and 2 broad band VIs) as well as satellite derived reflectance (2 broad band VIs) were assessed. Regression models were derived for estimating LAI, biomass and plant water content using the ground based indices and applied to the satellite derived spectral index (from LISS-III) map to estimate the respective parameters. HH and HV polarization from RISAT-1 were used to derive Radar Vegetation Index (RVI). The coefficient of determination of the model for estimating LAI, biomass and vegetation water content of cotton with optical vegetation index as input parameter were found to be 0.42, 0.51 and 0.52, respectively. The correlation between RVI and plant height, date of planting in terms of the age of the crop and vegetation water content were found to range between 0.4 to 0.6. The fresh biomass from RVI showed spatial variability from 100 gm-2 to 4000 gm-2 while the dry biomass map derived from NDVI showed spatial variability of 50 to 950 g m-2 for the study area. Plant water content in the district varied from 65 to 85%. The correlation between optical vegetation index and RVI was not significant. Hence a multiple linear regression model using both optical index (NDVI and LSWI) and SAR index (RVI) was developed to assess the LAI, biomass and plant water content. The model showed a R2 of 0.5 for LAI estimation but not significant for biomass and water content. This study show cased the use of combined optical and microwave (C band) remote sensing for cotton condition assessment.

Food waste disposal to landfills practice contributes to greenhouse problem due to the emission of gases such as methane to the atmosphere. Shelf-life extension of food products and further valorization of food wastes such as the conversion to activated carbon are tested nowadays as alternative techniques. The development and use of biobased active coatings against food oxidation/bacterial deterioration is an environmentally friendly technique. In this study, a novel food active coating was successfully developed based on a chitosan (CS)/poly-vinyl alcohol (PVOH) matrix activated with a nanohybrid of natural thymol (TO) adsorbed in activated carbon (AC) derived from spent coffee. The results shown that, compared to the pure CS/PVOH polymeric matrix, the coating with 15% wt. TO@AC nanohybrid concentration achieved +23.5 % Young’s modulus value, +20.1% ultimate strength value, increased barrier of +50.2% for water and +74.0 % for oxygen, +69.0% antioxidant activity, increased antibacterial activity of +5.5% against Escherichia coli, +17.8% against Salmonella enterica, +42.5% against Staphylococcus aureus, and +2.5% against Listeria monocytogenes. A visual evaluation of this coating shown a delay to fresh bananas enzymatic browning and significantly decrease their weight loss. This indicates that it could be potentially used to extend the shelf-life of fresh fruits.

Three significant changes have occurred in the winter climate in Europe recently: increased UK flooding; Iberian drought; and warmer temperatures north of the Alps. The literature links all three to a persistent, significant increase in sea level pressure over Southern Europe, the Mediterranean, Iberia and the Eastern Atlantic (SEMIEA) which changes the atmospheric circulation system: forcing cold fronts to the north away from Iberia; and creating a south westerly flow around the northern perimeter of the high-pressure region bringing warmer, moist air from the subtropical Atlantic to the UK and Europe which increases precipitation in the UK and raises the temperature in Europe. I use the Last Millennium Ensemble, MERRA-2 and Terra-NCEP data to demonstrate that the extreme, anthropogenic, West African aerosol Plume (WAP) which only exists from December to April perturbs the northern, regional Hadley Circulation creating the high pressure in the SEMIEA. I also show that the anthropogenic WAP has only existed in its extreme form in recent decades as the two major sources of the WAP aerosols: biomass burning; and gas flaring have both increased significantly since 1950 due to: a four-fold increase in population; and gas flaring rising from zero to 7.4 billion m3/annum and note that this time span coincides with the changes in the three elements of the winter climate of Europe. I also suggest that it may be possible to eliminate the WAP and return the winter climate of Europe to its natural state after the crucial first step of recognising the cause of the changes is taken.

Current satellite remote sensing methods struggle to detect and map forest degradation, a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (hϕ) is a promising variable for measuring forest disturbances, as it is closely related to mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrain, despite the fact that much of the worlds’ remaining tropical forests are found in hilly areas, and this inevitably introduces artifacts in sideways imaging systems. In this paper, we find a relationship between hϕ and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising the level of multilooking in the interferometric processing chain strengthens this relationship, and that degradation estimates across steep slopes in the surrounding region are improved by selecting data from the most appropriate pass directions on a pixel-by-pixel basis. This shows that TanDEM-X InSAR can measure the magnitude of degradation, and that topographic effects can be mitigated if data from multiple SAR viewing geometries are available.

Peat is the main type of peloid used in Polish cosmetic/healing spa facilities. Depending on treatment and origin, peat waste can be contaminated microbiologically, and as result, it has to be incinerated in medical waste incineration plants without energy recovery (local law). Such a situation leads to peat waste management costs increase. Therefore in this work, we checked the possibility of peat waste upcycling to carbonized solid fuel (CSF) using torrefaction. Torrefaction is a thermal treatment process that removes microbiological contamination and improves the fuel properties of peat waste. In work torrefaction conditions (temperature and time) on CSF quality were tested. Parallelly, peat decomposition kinetics using TGA, and torrefaction kinetics with lifetime prediction using macro-TGA were determined. Furthermore, torrefaction theoretical mass and energy balance were determined. The results of the tested peat were compared with reference material (wood), and as result, obtained data can be used to adjust currently used wood torrefaction technologies for peat torrefaction. The results show that torrefaction can improve the high heating value of peat waste from 19.0 MJ x kg-1 to 21.3 MJ x kg-1, peat main decomposition takes place at 200-550 °C following second reaction order (n=2), with an activation energy of 33.34 kJ x mol-1 and pre-exponential factor of 4.40 x 10-1 s-1. Moreover, DSC analysis revealed that peat torrefaction required slightly more energy than wood torrefaction, and macro TGA showed that peat torrefaction has lower torrefaction constant reaction rates (k) than wood 1.05 x 10-5 - 3.15 x 10-5 vs 1.43 x 10-5 - 7.25 x 10-5 s-1.

Poland is the 3^rdproducer of mushrooms in the world. Mushroom production in Poland accounts for nearly 25% of the total production in the EU, and it is still growing. One type of waste generated during mushroom production is mushroom spent compost (MSC), with a 5:1 (MSC: mushrooms) production rate. We investigated valorizing the MSC to produce fuel via torrefaction (‘roasting’, a.k.a. low-temperature pyrolysis). Specifically, we developed models for the MSC torrefaction kinetics using thermogravimetric analyses (TGA) and the effects of torrefaction temperature (200~300 °C) and process duration time (20~60 min) on the resulting biochar (fuel) properties. The estimated activation energy value of MSC torrefaction was 22.3 kJ^.mol^-1. The highest higher heating value(HHV) = 17.9 MJ^.kg^-1d.m. was found for 280 °C (60 min torrefaction time). The temperature of torrefaction significantly (p<0.05) increased the HHVfor constant process duration. The torrefaction duration time significantly (p<0.05) increased the HHVfor 220 °C and decreased HHVfor 300 °C. The highest mass yield 98.5% was found for 220 °C (60 min), while the highest energy yield was found for 280 °C (60 min). In addition, estimations of the value (€132.3·Mg^-1d.m. or 27.7 €·Mg^-1w.m) and quantity of resulting biochar (from torrefied MSC with 65.3% moisture content) were made based on the 280°C (60 min) torrefaction variant, assuming the price of commercially available coal fuel. We have shown a concept for an alternative utilization of abundant biowaste (MSC). The initial economic evaluation showed that MSC torrefaction might be profitable. This research provides a basis for alternative use of an abundant biowaste and can help charting improved, sustainable mushroom production.

The emergence of cloud computing, big data analytics, and machine learning has catalysed the use of remote sensing technologies to enable more timely land management of sustainability indicators such as ground cover and grassland biomass, given the uncertainty of future climate and drought conditions. Here, we examine the potential of “regenerative agriculture”, as an adaptive grazing management strategy to minimise bare ground exposure while maximising pasture biomass productivity. High-intensity sheep grazing treatments were conducted in small fields (less than 1 hectare) for short durations (typically less than 1 day). Paddocks were subsequently spelled to allow pasture biomass recovery (treatments comprising 3, 6, 9, 12, and 15 months) with each compared with control treatments with lighter stocking rates for longer periods (2,000 DSE). Pastures were composed of wallaby grass (Austrodanthonia species), kangaroo grass (Themeda triandra), Phalaris (Phalaris aquatica, and cocksfoot (Dactylis glomerata) were destructively sampled to estimate total standing dry matter (TSDM), standing green biomass, standing dry biomass and trampled biomass. We then invoked a machine learning model using Sentinel-2 imagery to quantify TSDM, standing green biomass and standing dry biomass. Faced with La Nina conditions, regenerative grazing did not significantly impact pasture productivity, with all treatments showing similar TSDM and green biomass. However, regenerative treatments significantly impacted litter fall and trampled material, with the high intensity grazing treatments causing more dry matter trampling, increasing litter, enhancing decomposition rates and surface organic matter. Pasture digestibility was greatest for treatments with minimal spelling (3 months), whereas both standing senescent and trampled material were significantly greater for the treatment with 15-month spell periods. Estimates of TSDM using machine learning with Sentinel-2 imagery underestimated TSDM in treatment plots but explained spatiotemporal variability associated within and across treatments. The root mean square error between the measured and modelled TSDM was 903 kg DM/ha, which was less than the variability measured in the field. We conclude that regenerative grazing with short recovery periods (3-6 months) are most conducive to increasing pasture production under high rainfall conditions, and we speculate that high intensity grazing is likely to positively impact on soil organic carbon through increased litterfall and trampling. Our study paves the way forward for using machine learning with satellite imagery to quantify pasture biomass at small scales, enabling management of pastures from afar.

In many Indian regions increased wastewater is both a threat and an opportunity. Efficient wastewater treatment and reuse schemes are needed in India to face impending water and fertiliser shortages. This study explores the application potential of wastewater fertigated Short Rotation Coppice systems (wfSRC) as a cost-efficient and promising solution for treating and reusing wastewater in a specific region (400 km2, 184 settlements) of Aligarh (UP), India. Based on real data from a local wfSRC pilot site using bamboo, willow, and poplar, we analysed the system’s treatment performance, nutrient recovery, carbon sequestration potential, land requirements, biomass production potential, and cost-benefit, under various scenarios. The results show that the pilot wfSRC system is efficiently treating 250 m3/day of domestic wastewater on 6,864 m2 of land, and serving 2,500 people. The land requirements for wfSRC systems vary depending on local conditions and user requirements, ranging from 2.75 – 25.7 m2/PE which equates to a required land area in the whole study region of between 108 and 1006 ha in 2036. This would produce up to 100 DM t/ha/yr of valuable biomass. Early local stakeholder involvement and monitoring of pollutants are recommended as priorities during the planning process for large-scale implementation of wfSRC systems in India.