Fossil fuel reserves have depleted. So, renewable and sustainable energy form an important issue. Microalgae as a third generation biomass can be an alternative carbon neutral fuel source. But its fuel quality is low. Co-pyrolysis is important technique to upgrade fuel quality of microalgae. In this study, we aimed to carry out pyrolysis of polystyrene and Spirulina sp. microalgae at low temperatures (350, 400, 450 ⁰C). The plastic waste source, polystyrene (PS), was supplied as an electronic device package. Before the pyrolysis it was divided small pieces and dried in oven. The microalgae source, Spirulina (SP), was bought in powder form commercially. The experiments were done by using semi-batch reactor setup. Co-pyrolytic product yields (bio-oil, bio-char and bio-gas) were calculated. Composition of bio-oil was enlightened by using GC-MS. As a result of the analysis, it was detected aromatic compounds like styrene, toluene in the co-pyrolytic bio-oil. Besides that it was observed co-pyrolysis was increased bio-char yield while it was decreased liquid and gas product yield. For co-pyrolysis, maximum bio-char and bio-oil yield were obtained as nearly 60% by weight at 350 ⁰C and 70% by weight at 450 ⁰C respectively.

The power business is at a point of intersection. Modern technical advances have the potential to drastically alter our electricity supply, trading, and usage. Artificial intelligence (Ai) technologies are transforming the current modernization approach. Big data management, vast computational resources, telecommunications, enhanced machine learning, and deep learning techniques have all contributed to the rapid surge in Ai technology. Smooth software that improves judgment and management will automatically adjust the merging of electricity supply, usage, and sustainable energy into the electricity network. Supercomputers, power systems, and communications networks between the command center and devices are all part of a smart electricity system. Ai would be crucial in attaining this required. This research assessed whether artificial intelligence algorithms surpass conventional methods in stability, massive data management, smart grid, energy-saving optimization, and planned maintenance management for renewables. As a result, we can conclude that Ai would perform an essential position in the upcoming energy business. To get better results, the sustainable energy industry, companies, power network administrators, and independent generators of electricity might want to put more emphasis on Ai technologies.

Artificial neural networks (ANN) are preferred over some other machine learning (ML) techniques due to their extension potential. The requirement for using ML approaches inside the renewable energy market would rise significantly in the upcoming decades, due to the huge market for graduate institutions in research, mathematics, and technology connected to machine learning. Collection of data, administration, and protection are predicted to play critical roles in the effective deployment of ML techniques that may be distributed among the main players in the renewable energy industry, hence fostering the creation of large smart energy schemes. The integration of new techniques for generating accurate data, as well as other pieces of knowledge, will improve the communication of data among ML and networks. Both supervised and unsupervised learning are likely to play important roles in the renewable energy industry, however, this will hinge on the development of certain other significant topics in machine learning, like big data analytics (BDA). Because the renewable energy business is dependent on weather, forecasting is an essential aspect of renewables. Machine learning algorithms aid in the precise prediction of renewables.

The present study explains the growth pattern and polyhydroxyalkanoates (PHA) production capacity of Bacillus sp. CYR1 (DNA Data Bank of Japan accession number LC049103) uses various fatty acids as substrates. Various combinations of fatty acids were used as substrates for the growth of strain CYR1. Among them, strain CYR1 showed good growth with the combination of two fatty acids (acetic acid and butyric acid) and the combination of three kinds of fatty acids (acetic acid, propionic acid, and caproic acid). Apart from the growth pattern, PHA production was also evaluated using various fatty acids as substrates. PHA production was in coordination with the growth pattern. The amount of PHA and PHA production (% cell dry mass (CDM)) calculated based on the Soxhlet extraction method was 0.158 g/L and 41.8 (%CDM) for the combination of acetic acid and butyric acid, and 0.241 g/L and 40.16 (%CDM) for the combination of acetic acid, propionic acid, and caproic acid. The wet and dry weights were higher in the combination of the three types of combination, and the amount of PHA was higher in the combination. It is essential to reduce the cost of the substrate for PHA production by replacing expensive carbon sources with wastewater. The organic compounds in domestic wastewater and wastewater produced from various factories will contain mixed fatty acids. By studying different combinations of two or more fatty acids, we gained new insights into utilizing wastewater containing various fatty acids.

Current energy systems are becoming increasingly decentralized, diverse, and dynamic. More energy is generated and consumed locally through Distributed Energy Systems (DES) and microgrids, which support the conventional centralized system.

Both DES and microgrids can operate autonomously or in island mode, but they can also connect to a larger grid. In this way, well-designed DES can help improve the resilience of networks with a large percentage of renewable energy. An optimal DES considers the different affected agents, the technical-economic feasibility, and the efficiency of the system.

These systems are becoming increasingly important in the future of energy, as they complement conventional centralized generation. DES and microgrids are optimal solutions to create more intelligent and resilient systems that can accept a greater share of renewable energies. On the other hand, these technologies facilitate the access of prosumers (those who produce and consume energy) to energy markets.

The presented project represents a scientific novelty that solves a growing problem for the following reasons:

• The need to integrate renewable energies into the current electrical system: the capacity of electricity generated by renewable energies will reach 4800 GW of capacity in 2026, which is equivalent to the current capacity of electricity generated by fossil fuels or nuclear energy. Therefore, the electrical system needs to transform towards this type of generation since the fluctuation of weather conditions that affect energies such as wind and solar generates fluctuations in the grid.
• Generating net zero greenhouse gas emissions by 2050 is one of the COP26 objectives: this measure is necessary to maintain the rise in temperature below 1.5 degrees Celsius. To achieve this, they promote the decarbonization of the energy system, the reduction in deforestation, the shift towards electric vehicles, and the promotion of investment in renewable energies.
• Dependence on fossil fuels: today there is still enormous energy dependence on countries that produce oil, coal, and gas, as in 2019, 64% of electricity came from this type of fuel.
• The increase of electric vehicles in the global transportation system: between 2019 and 2020, the increase in electric vehicles globally was around 43%, which resulted in more than 10 million of these types of vehicles in 2020. For this growth to be sustainable, it is necessary for the electrical system to adapt to this type of load and coexist with renewable generation.
• The need to ensure good resilience in the grid for systems with renewable energies, electric vehicles, or other systems that compromise the current grid: microgrids help prevent failures and blackouts in the electrical system since these networks can operate in island mode and promote the integration of renewable energies.

Resource depletion and climate change have fostered sustainable initiatives in the waste management sector. Pyrolysis (Py) has emerged as an option for valorizing spent coffee grounds (SCG). In addition, inorganic compounds can play catalytic effects in the pyrolytic reaction of organic materials, increasing the char yield and material porosity. This study investigates the slow pyrolysis of SCG using concentrated landfill leachate residue (CLLR) (1:1 %wt) as a pyrolitic additive due to its high salinity. Biochars were characterized in terms of their thermal behaviour to discuss environmental benefits and potential application. Slow-py experiments were conducted using a lab-scale pyrolizer at heating rate of 45ºC min^-1. The lab-pyrolizer was operated at atmospheric pressure. Py conditions were as follows: temperature of 600ºC, inert gas flow of 100 cm³ N₂ min^-1, and residence time of 1 h. Thermal characterization was performed using TA Instruments, SDTQ600 model. Biochar samples were heated from 20 to 1000ºC at a rate of 20 °C min^-1 under air-flow rate of 100 mL min^-1. Biochars were characterized by higher water content and heating rate than their feedstocks. Values were 9.18 %wt and 18.11 MJ kg^-1 and 23.25 %wt and 22.05 MJ kg^-1 for biochars produced from SCG and SCG+CLLR (1:1 %wt), respectively. High water content is associated with higher porosity. In the case of the more porous biochar, water loss occurred from 20 to 150°C, followed by the combustion of organics until 550°C. Data indicated that alkali metals of the CLLR catalyzed the carbonization of organic materials making thermal decomposition faster. It is suggested that the high metal content of CLLR could change the biochar's thermal stability, decreasing the decomposition temperature. From elemental composition analysis, the produced biochar owned essential soil minerals (e.g., Na, K, and Ca); therefore, it could be used as a soil amendment for C-sink slow-release inorganic elements or energy storage devices such as batteries and supercapacitors. Future studies will include morphological characterization of biochar and carbon balance.

Camellia japonica is an underexplored medicinal plant with associated bioactivities (Pereira et al., 2022). Innovative approaches to the large-scale application of C. japonica are proposed, with one of the main lines being the extraction of phenolic compounds (Cho et al., 2009). Significant efforts are taken in order to develop rapid technological progress with low costs, labor and time. Green extractions, and among them microwave and ultrasounds assisted extraction (MAE and UAE), are popular and relatively inexpensive extraction techniques (Hanula et al., 2020). Therefore, the purpose of this study was to find the optimal green extraction method of C. japonica var. Eugenia de Montijo flowers´ (ultrasound or microwaves) able to isolate extracts containing the highest yields and amounts of phenolic compounds. Both processes were optimized by response surface methodology using a five-level central composite design combining the independent variables of processing time (t, 5-25 min), temperature (T, 50-180ºC) and solvent (S, acidify ethanol 0-100%) for MAE and ultrasound power (P, 150-400 W), t (0-45 min) and S (acidify ethanol 0-100%) in the case of UAE. The main extracted compounds were identified and quantified by LC-MS/MS. Two responses were studied: extraction yield and content of phenolic compounds. The results showed that the maximum yields (80%) were obtained with MAE at high temperatures and low times (180ºC, 5 min). The main family of phenolic compounds were flavonols (i.e., kaempferol 3-o-acetyl-glucoside, dihydroquercetin). Based on these results, the current study contributes to the valorization of underutilized flower species common in Spain's North-West region by obtaining rich extracts in phenolic compounds that can potentially be used as ingredients in various industrial fields.

Grass biomass (GB) is an excellent feedstock as biogas production material for anaerobic co-digestion (AD) because of its organic solids content of more than 20%. However, a high concentration of fibres and material ability to layering makes this substrate problematic to digest in bioreactors. Lignocellulosic grass biomass has a huge potential to be used as feedstock for the sustainable production of fuels and chemicals through fermentation. Today, plant substrates, also entitled lignocellulosic biomass, are seen as one of the most promising materials to replace fossil resources in the production of fuels and chemicals with reduced GHG emissions. However, the recalcitrance of these materials is one of the major hurdles in their efficient utilization. In this sense, microbial research has been mainly focused on the production of cheaper enzymes and in more efficient utilization of biomass derived sugars. The influence of selected inoculum for anaerobic fermentation of lignocellulosic grass biomass in every specific case varies. In cellulolytic rumen bacteria, highly active cellulolytic and hemicellulolytic enzymes are combined in extracellular multienzyme complexes, cellulosomes.

In this study, the degradation of lignocellulose in biogas processes has been focused on the innoculant microorganisms involved, with a view to gaining a deeper understanding and improving lignocellulose degradation. The aim of this study was to determine the effect of dairy rumen anaerobic bacteria inoculum on grass biomass biogas production and how anaerobic bacteria inoculated into dairy rumen will influence the quality of biogas generated from grass biomass.

It was examined in this study how dairy rumen fluid inoculum influences the anaerobic treatment of organic fractions of GB. To evaluate the influence of dairy rumen fluid inoculum BMP experiment was performed in four sets of two 500 mL glass bottles (bioreactors) with a working volume of 800 mL at 37 ± 0,2 ^oC. There was a constant amount of GB added to all experiments - 16 g. Reactor set “A” was loaded with 800 grams rumen fluid (proportion 100%/0%), Reactor set “B” was loaded with 400 g rumen fluid and 400 g digestate from bioreactor (proportion 50%/50%), Reactor set “C” was loaded with 800 g digestate directly from the same bioreactor as mentioned in Reactor “B” (proportion 0%/100 %). To evaluate inoculum BMP Reactor “D” was started without any GB addition and it served as a negative control for residual methanogenic activity. All experimental sets were set as triplicate samples.

The outcome parameters of the BMP experiment showed that the maximum volumetric biogas yield (12,17 ± 0,62 l/l) was obtained from the substances used in experiment “B” with rumen fluid and the digestate composition. According to the results, the second largest volumetric biogas yield was achieved in experiment “C”, where grass biomass and digestate were used as inputs. With rumen fluid and grass biomass, experiment “A” yielded the least biogas at only 1,14 l/l. The least volumetric yield of biogas came from digestate (0,35 ± 0,08 l/l) as it did not contain additional green biomass. The highest concentration of methane was gained from experiment B (63,2 ± 1,5 %). Biogas gained from digestate (experiment “C”) had a slightly lower concentration of methane, at 54,6 ± 1,1%).

Background: The stability of the finished medicinal product has a significant impact on the effectiveness of the medicinal product as well as the safety of the patient. With this in mind, stability testing is now a legal requirement for medicinal products throughout the drug development process. In the present study, the stability of effervescent tablets was assessed using a non-invasive X-ray microtomography technique.

Methods: Two types of effervescent tablets of one commercial product containing vitamin C which is available at the Polish market were analyzed, i.e. unexpired (expiration date: 04.2023) and expired (expiration date: 02.2020). X-ray microtomography (GE Sensing & Inspection Technologies GmbH, Wunstorf, Germany) was used to register the scans of analyzed tablets. The tablets were scanned at a voltage of 180 kV. An object analyzed by this method absorbs X-rays in proportion to its density. In the microtomographic image, the density is reflected by the gray level, i.e. “bright” pixels represent areas of high density, while “dark” pixels represent areas of low density. A phantom with known density areas (Micro-CT HA Phantom D32) was scanned together with effervescent tablets to establish the grayscale level of the reference density.

Results: We analyzed 70 random regions of interest (ROIs) from the 20 microtomographic slices of each type of the effervescent tablets. The average brightness of the pixels was measured with ImageJ software. A curve of dependence between brightness and density of known area from the phantom was drawn. A significant difference was observed in the density of the inner structure between the two types of analyzed effervescent tablets with vitamin C (p<0.001). The higher mean density was observed in the case of unexpired tablets (1.250 g/cm³) compared to expired tablets (1.242 g/cm³). Thus, unexpired effervescent tablets containing vitamin C showed better homogeneity than expired ones.

Conclusions: The applied method of three-dimensional µCT imaging allowed rapid detection of differences in the microstructure of expired and unexpired tablets. On the basis of quantitative data, significant differences in the tablet density of the studied drug forms were demonstrated.

Farmers widely use malathion, even in households, and significant amounts of seep through groundwater and effluent wastewater. It is toxic to animal and human life. Hence its removal from wastewater is necessary. Here, we report the applicability of hydroxyapatite as a catalyst in the UV-light-assisted degradation of malathion. The hydroxyapatite was synthesized via calcination from milkfish (MF1000) and cream dory (CD1000) bones. FTIR and PXRD results proved the successful synthesis of hydroxyapatite from the fish bones. SEM images revealed that the synthesized hydroxyapatite varies from 19 to 52 nm in size with a pseudo-spherical morphology. Degradation efficiency increases when catalyst dosage or irradiation time is increased. Degradation efficiencies range from 8.18% to 67.80% using MF1000 and from 20.50% to 67.90% using CD1000. Malathion obeys the first-order kinetics with a kinetic constant up to 7.0289 x 10^-3 min^-1 for 0.6 g catalyst loading. Meanwhile, malathion obeys second-order kinetics with a kinetic constant up to 1.1946 x 10^-3 L min^-1 mg^-1 for 0.6 g loading. Across all catalyst loadings, CD1000 has faster degradation kinetics compared to MF1000. The results of this study validate that the calcined fish bones are effective in removing malathion in an aqueous solution, which significantly impacts lessening the detrimental effects of pesticides in groundwater and wastewater.