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A critical review on the biochar production techniques, characterization, stability and applications for circular bioeconomy.

ABSTRACT: There is an upsurge enthusiasm for utilizing biochar produced from waste-biomass in different fields, to address the most important ecological issues. This review is focused on an overview of remediating harmful contaminants utilizing biochar. Production of biochar utilizing various systems has been discussed. Biochar has received the consideration of numerous analysts in building up their proficiency to remediate contaminants. Process parameters are fundamentally answerable for deciding the yield of biomass. Biochar derived from biomass is an exceptionally rich wellspring of carbon produced from biomass utilizing thermal combustion. Activating biochar is another particular region for the growing utilization of biochar for expelling specific contaminations. Closed-loop systems to produce biochar creates more opportunities. Decentralized biochar production techniques serve as an effective way of providing employment opportunities, managing wastes, increasing resource proficiency in circular bioeconomy. This paper also covers knowledge gaps and perspectives in the field of remediation of toxic pollutants using biochar.

SUBMITTER: Yaashikaa PR

PROVIDER: S-EPMC7718465 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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A critical review on the biochar production techniques, characterization, stability and applications for circular bioeconomy.

Yaashikaa P R PR Kumar P Senthil PS Varjani Sunita S Saravanan A A

Biotechnology reports (Amsterdam, Netherlands) 20201121

There is an upsurge enthusiasm for utilizing biochar produced from waste-biomass in different fields, to address the most important ecological issues. This review is focused on an overview of remediating harmful contaminants utilizing biochar. Production of biochar utilizing various systems has been discussed. Biochar has received the consideration of numerous analysts in building up their proficiency to remediate contaminants. Process parameters are fundamentally answerable for deciding the yie ...[more]

PMID: 33304842

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Project description:Plastics are present in the majority of daily-use products worldwide. Due to society's production and consumption patterns, plastics are accumulating in the environment, causing global pollution issues and intergenerational impacts. Our work aims to contribute to the development of solutions and sustainable methods to mitigate this pressing problem, focusing on the ability of marine-derived actinomycetes to accelerate plastics biodegradation and produce polyhydroxyalkanoates (PHAs), which are biodegradable bioplastics. The thin plastic films' biodegradation was monitored by weight loss, changes in the surface chemical structure (Infra-Red spectroscopy FTIR-ATR), and by mechanical properties (tensile strength tests). Thirty-six marine-derived actinomycete strains were screened for their plastic biodegradability potential. Among these, Streptomyces gougerotti, Micromonospora matsumotoense, and Nocardiopsis prasina revealed ability to degrade plastic films-low-density polyethylene (LDPE), polystyrene (PS) and polylactic acid (PLA) in varying conditions, namely upon the addition of yeast extract to the culture media and the use of UV pre-treated thin plastic films. Enhanced biodegradation by these bacteria was observed in both cases. S. gougerotti degraded 0.56% of LDPE films treated with UV radiation and 0.67% of PS films when inoculated with yeast extract. Additionally, N. prasina degraded 1.27% of PLA films when these were treated with UV radiation, and yeast extract was added to the culture medium. The main and most frequent differences observed in FTIR-ATR spectra during biodegradation occurred at 1740 cm-1, indicating the formation of carbonyl groups and an increase in the intensity of the bands, which indicates oxidation. Young Modulus decreased by 30% on average. In addition, S. gougerotti and M. matsumotoense, besides biodegrading conventional plastics (LDPE and PS), were also able to use these as a carbon source to produce degradable PHA bioplastics in a circular economy concept.

Project description:Background: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, and ingestible and implantable sensors are increasingly used by individuals and clinicians to capture the health outcomes or behavioral and physiological characteristics of individuals. Time series classification (TSC) is very commonly used for modeling digital clinical measures. While deep learning models for TSC are very common and powerful, there exist some fundamental challenges. This review presents the non-deep learning models that are commonly used for time series classification in biomedical applications that can achieve high performance. Objective: We performed a systematic review to characterize the techniques that are used in time series classification of digital clinical measures throughout all the stages of data processing and model building. Methods: We conducted a literature search on PubMed, as well as the Institute of Electrical and Electronics Engineers (IEEE), Web of Science, and SCOPUS databases using a range of search terms to retrieve peer-reviewed articles that report on the academic research about digital clinical measures from a five-year period between June 2016 and June 2021. We identified and categorized the research studies based on the types of classification algorithms and sensor input types. Results: We found 452 papers in total from four different databases: PubMed, IEEE, Web of Science Database, and SCOPUS. After removing duplicates and irrelevant papers, 135 articles remained for detailed review and data extraction. Among these, engineered features using time series methods that were subsequently fed into widely used machine learning classifiers were the most commonly used technique, and also most frequently achieved the best performance metrics (77 out of 135 articles). Statistical modeling (24 out of 135 articles) algorithms were the second most common and also the second-best classification technique. Conclusions: In this review paper, summaries of the time series classification models and interpretation methods for biomedical applications are summarized and categorized. While high time series classification performance has been achieved in digital clinical, physiological, or biomedical measures, no standard benchmark datasets, modeling methods, or reporting methodology exist. There is no single widely used method for time series model development or feature interpretation, however many different methods have proven successful.

Project description:Carbonization of biomass can prepare carbon materials with excellent properties. In order to explore the comprehensive utilization and recycling of Caragana korshinskii biomass, 15 kinds of Caragana korshinskii biochar (CB) were prepared by controlling the oxygen-limited pyrolysis process. Moreover, we pay attention to the dynamic changes of microstructure of CB and the by-products. The physicochemical properties of CB were characterized by Scanning Electron Microscope (SEM), BET-specific surface area (BET-SSA), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), and Gas chromatography-mass spectrometry (GC-MS). The optimal preparation technology was evaluated by batch adsorption application experiment of NO3-, and the pyrolysis mechanism was explored. The results showed that the pyrolysis temperature is the most important factor in the properties of CB. With the increase of temperature, the content of C, pH, mesoporous structure, BET-SSA of CB increased, the cation exchange capacity (CEC) decreased and then increased, but the yield and the content of O and N decreased. The CEC, pH, and BET-SSA of CB under each pyrolysis process were 16.64-81.4 cmol·kg-1, 6.65-8.99, and 13.52-133.49 m2·g-1, respectively. CB contains abundant functional groups and mesoporous structure. As the pyrolysis temperature and time increases, the bond valence structure of C 1s, Ca 2p, and O 1s is more stable, and the phase structure of CaCO3 is more obvious, where the aromaticity increases, and the polarity decreases. The CB prepared at 650 °C for 3 h presented the best adsorption performance, and the maximum theoretical adsorption capacity for NO3- reached 120.65 mg·g-1. The Langmuir model and pseudo-second-order model can well describe the isothermal and kinetics adsorption process of NO3-, respectively. Compared with other cellulose and lignin-based biomass materials, CB showed efficient adsorption performance of NO3- without complicated modification condition. The by-products contain bio-soil and tail gas, which are potential source of liquid fuel and chemical raw materials. Especially, the bio-oil of CB contains ?-d-glucopyranose, which can be used in medical tests and medicines.

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A critical review on the biochar production techniques, characterization, stability and applications for circular bioeconomy.

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A critical review on the biochar production techniques, characterization, stability and applications for circular bioeconomy.

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