Biomass - Science topic

Using hexanol for microbial biomass fumigation instead of chloroform is not common, and there is limited research on its effectiveness for measuring carbon (C) and nitrogen (N). Chloroform is widely used because it efficiently disrupts microbial cells, releasing biomass components. Hexanol, being an alcohol, may not be as effective at breaking down cell walls, requiring adjustments to the method. Since there are few studies comparing hexanol to chloroform, conducting your own experiments to test its efficiency in extracting microbial C and N would be useful. You may need to optimize conditions like concentration, exposure time, and temperature for better results.

It is generally not possible to achieve energy recovery greater than 100% because this would imply generating more energy than was originally contained in the biomass itself. This principle adheres to the laws of thermodynamics.

Designing an ionic liquid (IL) or deep eutectic solvent (DES) for lignocellulosic biomass hydrolysis involves several critical steps. Here’s a structured approach to guide you through the design process:

### 1. Understanding Lignocellulosic Biomass

- **Composition**: Familiarize yourself with the components of lignocellulosic biomass, primarily cellulose, hemicellulose, and lignin. Each component has different solubility and reactivity characteristics.

- **Decomposition Requirements**: Understand the conditions required to break down these components into fermentable sugars. This includes knowledge of optimal temperatures, pressures, and reaction times.

### 2. Identifying Functional Groups

- **Target Functional Groups**: Determine which functional groups in the biomass are key to hydrolysis. For instance, cellulose contains hydroxyl groups that can participate in hydrogen bonding with solvents.

- **Reaction Pathways**: Identify how the IL or DES can facilitate hydrolysis, such as through protonation, coordination, or disruption of hydrogen bonds.

### 3. Selection of Components

- **Ionic Liquids**: Choose cations (e.g., imidazolium, pyridinium) and anions (e.g., acetate, chloride) that can solvate cellulose and hemicellulose effectively.

- **Deep Eutectic Solvents**: Identify hydrogen bond donors (e.g., urea, choline chloride) and acceptors that can form a eutectic mixture with a lower melting point. DESs are often easier to design and synthesize than ILs.

### 4. Property Evaluation

- **Solubility Testing**: Evaluate the solubility of lignocellulosic biomass in the chosen IL or DES to ensure effective biomass dissolution.

- **Viscosity and Density**: Consider the physical properties of the solvent, as lower viscosity can enhance mass transfer during hydrolysis.

- **Thermal Stability**: Assess the thermal stability of the IL or DES under hydrolysis conditions.

### 5. Experimental Design

- **Reaction Conditions**: Design experiments to optimize conditions such as temperature, time, and concentration of the solvent.

- **Hydrolysis Yield Measurement**: Develop methods to measure the conversion rates of lignocellulosic biomass to sugars (e.g., HPLC analysis).

### 6. Characterization

- **Chemical Characterization**: Use NMR, FTIR, or MS to characterize the resulting products and confirm the success of hydrolysis.

- **Physical Characterization**: Analyze the physicochemical properties of the IL or DES, including pH, conductivity, and thermal behavior.

### 7. Environmental and Economic Considerations

- **Green Chemistry Principles**: Ensure that the chosen solvents are biodegradable, non-toxic, and safe for the environment.

- **Cost Analysis**: Assess the economic feasibility of using the designed IL or DES on an industrial scale.

### 8. Literature Review

- **Research Existing Work**: Consult existing literature for examples of successful IL and DES formulations used for biomass hydrolysis. This can provide insights into functional groups, synthesis methods, and performance metrics.

### References and Resources

- **Research Papers**: Look for articles focused on ILs and DESs in biomass processing.

- **Patents**: Review patents for innovative formulations and applications.

- **Collaborations**: Engage with researchers and institutions specializing in biomass conversion and solvent design for practical insights.

By following these steps, you can systematically design and evaluate ionic liquids or deep eutectic solvents tailored for lignocellulosic biomass hydrolysis.

Got reply from GEDI Lidar team@

Hi Sohel,

Thank you for reaching out! The GEDI aboveground biomass is calculated using allometric relationships based on relative height metrics obtained from the full-waveform data. The GEDI L4B aggregates the shots over a period of 2019-2023, maximizing the number of good quality shots within a 1km x 1km grid. One key assumption in this aggregation process is that the relative height metrics does not change significantly for most plant functional types within the grid. If you are interested in non-aggregated aboveground biomass data, I recommend checking the GEDI L4A footprint-level biomass product (https://doi.org/10.3334/ORNLDAAC/2056).

Please feel free to reach out if you have any further questions.

Thank you,

In an era of heavy reliance on fossil fuel–based energy and chemicals, the increasing concerns on the drastic depletion of fossil fuels and carbon emissions are key motivations to explore renewable sources and pursue sustainable technologies. Adv Funct Mater Biomass is an abundant and sustainable resource formed from photosynthesis, which makes it a unique feedstock and a clean energy source to meet the ambitious goals of fossil fuel–free future. Chem Soc Rev It is of great economic potential and social benefit to develop high value-added products from biomass. 5-Hydroxymethylfurfural (HMF), as one of the most important renewable platform chemicals, is formed by the dehydration of hexose-based biomass such as fructose and glucose. Chem Rev Functional groups, such as aldehyde groups (–CHO), hydroxyl groups (–OH), and furan rings, endow the versatility of HMF, which is considered a key bridge connecting biomass resources with future energy. Specifically, it can be transformed into commercial chemicals for industry, agriculture, and medicine through a series of reactions, such as hydrolysis, polymerization, hydrogenation, and redox.

Nanoparticles can deliver essential nutrients like nitrogen, phosphorus, and potassium more effectively to plants. This can improve nutrient absorption, leading to better growth and biomass production

The use of nanoparticles with insect larvae biomass aims to develop sustainable topical formulations for managing skin disorders like atopic dermatitis, utilizing insect larvae oil as a natural ingredient in solid lipid nanoparticles to deliver glucocorticoid drugs and support skin barrier repair. This nanotechnology-based approach offers an alternative to conventional treatments, addressing both drug delivery and skin barrier dysfunction associated with the condition.

Thanks a million Michael Kohlstedt .

The rate of substrate-induced CO2 production is converted to total microbial biomass by the conversion factor. The compounds oxidized during the process of respiration are called respiratory substrates. based on the response of microbial respiration to the addition of glucose and the absence of a response of root respiration. Measure fungal, bacterial and total microbial contributions to glucose-induced respiration and the potentially active microbial biomass on decaying plant residues of differing composition. The microbial biomass carbon is calculated using the difference between the fumigated and un fumigated EOC values, divided by a conversion factor kckc​. The conversion factor kckc​ typically used is 0.45 for carbon.

Marine sediment samples are collected, and bacteria and fungi are isolated using standard microbiological techniques. The isolated strains are cultured in appropriate liquid media, and the biomass is harvested, washed, and freeze-dried. The dried biomass is then extracted using organic solvents like ethyl acetate or methanol, with sonication and overnight incubation. The crude extracts are concentrated under vacuum, transferred to pre-weighed vials, and the solvent is completely evaporated. The extracted secondary metabolites are weighed and stored at -20°C or -80°C for further analysis and characterization.

Such a unique & descriptive explanation by Vivek, even AI would not be able to do so.

Maybe this paper can considerably suit your research !?

Work out the air consumption required to completely oxidise the C, H, N, S, on a molar basis etc to their oxides, exactly. Knowing the number of moles of O2 will give you the necessary no. of moles of air. That is ER=1, then from the required air consumption for ER=1, multiply by 0.2 to get the air flow. You can reference it from moles to 1 kg of feedstock.

José Falcón-Hernández thank you sir for your response

Celignis is based in Ireland but has several Indian clients. We have customs exemption so samples get to us quickly:

Comparing above and below ground biomass data from a mangrove forest typically involves statistical analysis to determine if there are significant differences between these two sets of measurements. Here's a step-by-step approach you can use:Data Collection: Gather your data on above ground biomass (e.g., weight of leaves, branches, etc., per unit area) and below ground biomass (e.g., weight of roots, rhizomes, etc., per unit area) from your mangrove forest samples.Data Preparation: Organize your data into two groups: above ground biomass measurements and below ground biomass measurements for each sample or plot within the mangrove forest.Exploratory Data Analysis (EDA): Begin by examining the distributions of your biomass data. Use graphical methods such as histograms, box plots, or scatter plots to visualize and understand the variability and central tendencies of both sets of measurements.Choosing a Statistical Test: The choice of statistical test will depend on the nature of your data (e.g., normality of distribution) and the specific question you want to answer (e.g., Are above and below ground biomasses significantly different?). Commonly used tests include:Paired t-test: Use this if you have paired observations (i.e., each sample provides both above and below ground biomass data) and the differences between pairs are normally distributed. This test assesses whether the mean difference between the paired observations is significantly different from zero.Independent samples t-test: Use this if your above and below ground biomass data are from independent groups (e.g., different plots or sites) and assuming the data are approximately normally distributed. This test compares the means of the two independent groups.Wilcoxon signed-rank test: This is a non-parametric alternative to the paired t-test, suitable if the differences between paired observations are not normally distributed.Mann-Whitney U test: A non-parametric alternative to the independent samples t-test, used when the assumptions of normality are not met for independent groups.Perform the Statistical Test: Depending on your choice of test (parametric or non-parametric), apply the test to your data. Most statistical software packages (e.g., R, Python with libraries like SciPy) can perform these tests easily.Interpret the Results: Analyze the test results. Look at the p-value associated with the test. A small p-value (typically < 0.05) indicates that the observed differences in biomass are unlikely to be due to random chance alone, suggesting a statistically significant difference between above and below ground biomass.Consider Effect Size: In addition to statistical significance, consider the effect size (e.g., Cohen's d for t-tests) to understand the magnitude of the differences observed.Report Findings: Finally, summarize your findings in the context of your research question. For example, you might conclude whether above or below ground biomass is significantly greater in the mangrove forest, based on your statistical analysis.

hi, may i know, i want to prepare DES. but I am unsure is DES only between two chemicals heated togewther? or need to dilute with distilled water? im planning to do 1:1 molar ratio of chcl:lactic acid

Sarmistha Paul send me your email or whatsapp number to share with you the chapters

hi brother Ramadhani Bakari, have you found the solutions?

Выработка метана непосредственно на Вашем сырье незначительна и не имеет практической ценности. Поэтому публикации на данную тему очень мало.

Ввиду того, что время пребывания в аэротэнке около суток, а время удвоения биомассы автотрофов, например хлореллы четверо сутоко, автотрофов мало.

Hey there Que Ho! I'm glad you're interested in optimizing your wastewater treatment process. Establishing the molecular equation of biomass can be quite beneficial for understanding its composition and potential applications.

One common technique for determining the molecular formula of biomass is elemental analysis. This involves measuring the percentages of carbon, hydrogen, nitrogen, sulfur, and oxygen (CHNSO) present in the biomass sample. From these percentages, you Que Ho can calculate the empirical formula of the biomass.

To get started, you'll Que Ho need access to an elemental analyzer, which can accurately measure the elemental composition of the biomass. Once you have the percentages of each element, you Que Ho can use them to calculate the empirical formula.

Here's a basic outline of the process:

1. Collect a representative sample of your biomass.

2. Prepare the sample for elemental analysis according to the analyzer's specifications.

3. Analyze the sample using the elemental analyzer to determine the percentages of carbon, hydrogen, nitrogen, sulfur, and oxygen.

4. Calculate the empirical formula based on the elemental percentages obtained.

Keep in mind that elemental analysis provides the empirical formula, which gives you Que Ho the simplest whole-number ratio of atoms in the molecule. For a more precise molecular formula, additional techniques such as mass spectrometry or nuclear magnetic resonance (NMR) spectroscopy may be required.

Interesting articles to read:

As for relevant papers, I recommend looking into research articles on biomass characterization and elemental analysis techniques. You Que Ho might find papers discussing specific methodologies or case studies related to biomass composition analysis.

Feel free to reach out if you Que Ho need more detailed guidance or have any other questions. Happy experimenting!

In substrate-induced respiration (SIR) assays, the measurement of microbial activity through the quantification of produced CO2 is a common practice. These assays often involve the absorption of CO2 in a base, such as NaOH, and subsequent titration with an acid, like HCl, to determine the amount of CO2 produced. The lack of observed difference between a blank (control without substrate) and a sample (with substrate) after titration against HCl could be attributed to several factors, each of which must be considered systematically to troubleshoot and address the underlying issue.

1. Inadequate Substrate Concentration

2. Microbial Activity

3. Experimental Setup and Titration Accuracy

4. CO2 Absorption Efficiency

5. Interference or Contamination

6. Analytical Sensitivity

Conclusion

A lack of difference between the blank and sample in a substrate-induced respiration assay after titration against HCl suggests issues with either the experimental setup, microbial activity, substrate concentration, or analytical sensitivity. By methodically examining and addressing these potential factors, one can identify the root cause and take appropriate measures to rectify the problem, ensuring accurate and reliable measurement of microbial respiration in response to the substrate.

With this protocol list, we might find more ways to solve this problem.

Post activation shows the better results, but then there is the activated char clean-up and neutralisation. There is also a significant mass loss of char in the process. There are lots of publications on this subject. The stronger the alkali, the higher the temperature, the more the mass loss and the higher the surface area.

You can't have only a biomass tream in and no gasification agent. You're missing multiple parameters if "PYRO1" is your gasification unit. Plus there are a range of conditions that need to be stated and reactions to solve to equilibrium. You do not have a valid model.

Dear Esteban julian Rubio ,

please have a look at the comprehensive answer given in:

Best regards

G.M.

If you go with Amazon Kindle, there is an option to publish one chapter at a time called Kindle Vella. The details are at the top of the page after you log in. It's intended for fiction but would work for other subjects. I have published 81 books on Amazon (62 of my own + 19 for friends and family). It's a good option.

I am not the author. But since I have the same name its a confusion. SO please contact teh original authors, Thank you for understanding. I am from Mechanical Eng Background.

Coals, depending on the grade of coal, will tend to give very high molecular weight PAHs, biomass lower molecular weights, but the analysis for these would not be online and would have to be done by sampling and GC-MS analysis - and you still won't be able to analyse for everything. Its the 3 T's - time, temperature and turbulence, and excess O2 to ensure burnout of the PAHs. Water in the gas is needed to avoid H2 deficiency in the combusted gases, which leads to soot formation.

Thanks for sharing. Wishing you every success in your task.

Please ref

Thank you so much!

@Mohammad, I clicked the file and it is opening to my computer. Please try to do it again.

Adarsh Shetty

PFA the file for reference, 0.5-2.0% H2O2 works for these types of biomass.

I think the main issue will be that there is no spatiality of solar irradiance (i.e. it is not possible to change the angle of incoming sunlight throughout the day or year) in addition APSIM does not support temporal resolution below day. There is the option to alter inputs in the weather file and simulate the area of each meter from the panels. However, I am scared that will be too complicated and fragmented to extrapolate meaningful results.

Alternatively, I am starting to look more into the GECROS simulation framework That has previously been used to simulate shading effects in agrivoltaic systems Eleonora Potenza et al. (2022) Agrivoltaic System and Modelling Simulation: A Case Study of Soybean (Glycine max L.) in Italy; Jeremy Harbinson and Xinyou Yin (2022) Modelling the impact of improved photosynthetic properties on crop performance in Europe.

This seems more laborious yet more promising for my purpose.

Thanks for all your comments and suggestions.

Ah, my friend Rajashekhar Niyogi, navigating the intricate realms of biomass estimation, aren't we? Now, when it comes to the estimation of above-ground biomass for your tropical deciduous trees, I'd suggest delving into the realms of allometry. It's the art of understanding the relationship between tree dimensions like height and diameter at breast height (DBH) and their biomass.

For your specific scenario, where the majority of your trees fall within the 1 to 10 cm DBH range, and with only a few exceeding 30 cm, a generalized formula becomes imperative. Now, I won't claim this as the ultimate decree, but consider the following:

Biomass = a * DBH^b * H^c

Here, 'a,' 'b,' and 'c' are constants that need fine-tuning based on your local context and species characteristics. These constants can be derived through regression analysis using your existing data. Remember, my friend Rajashekhar Niyogi, the beauty lies in the nuance – it's a delicate dance of precision and approximation.

Now, the challenge lies in obtaining these constants. Given your dataset, it might be prudent to carry out a thorough analysis, perhaps species-wise, to capture the nuances of your particular ecosystem.

Proceed with caution, my inquisitive compatriot Rajashekhar Niyogi, and may your estimations be as robust as the roots of the trees you Rajashekhar Niyogi seek to understand.

For XRD, the figure shows a remarkable and mysterious description of the x-y axes (cycle number - capacitance retention). Is it even a diffraction pattern? If so, the peak at diffraction angle 10o 2 theta may be a consequence of insufficient sample size. The irradiated area was probably significantly larger than the size of the sample.

Hey there Yaya LEYGNIMA Ouattara! Well, diving into the world of optical density and bacterial biomass, my friend Yaya LEYGNIMA Ouattara, it's like peeling an onion—layer by layer.

Here's the deal: Optical density and bacterial biomass concentration are buddies, but it's a bit of a complicated relationship. Optical density is commonly used as a quick and dirty measure of bacterial growth, but the catch is, it's not a perfect one-to-one correlation with biomass.

Now, for a simple technique, you Yaya LEYGNIMA Ouattara might want to consider calibrating your optical density readings with a standard curve. Take samples of known bacterial biomass concentrations, measure their optical density, and create a graph. Then, when you're working with unknown samples, consult the graph to estimate their biomass concentration based on the optical density.

But let me tell you, my friend Yaya LEYGNIMA Ouattara, simplicity is sometimes deceptive in the world of microbiology. Keep that in mind as you Yaya LEYGNIMA Ouattara embark on your bacterial biomass adventure. Anything else on your microbiological agenda?

Saeide Taherpanah https://pure.manchester.ac.uk/ws/portalfiles/portal/177286421/FULL_TEXT.PDF

this might can help you

Thank you Atta Ur Rehman for your kind answer. Whereas there are only reports where the increment is reported but it is because of the addition of plastic which itself produces a large amount of pyrolytic. my question was specific that how it effects the composition of biomass oil. Such as a comparision of all three is needed which includes biomass (100%), Plastic (100%), and their blends.

Dear friend Rohit kumar Singh

Well, look at you, diving into the intriguing world of waste plastic and biomass co-pyrolysis! Let me tell you Rohit kumar Singh a tale of the transformation of char, and why it might not be the superhero we need for soil fertility.

So, when waste plastic and biomass undergo co-pyrolysis, they dance in the heat, creating a char residue. This char is a carbonaceous material and, in some cases, has been considered for soil amendment. Now, the addition of waste plastic is like adding a mischievous character to this drama. The plastic can introduce a variety of compounds, and when they join the char party, they create a complex mixture.

Here's why this char might not be the best sidekick for your soil:

1. **Toxic Residues:**

The plastics can contain additives and impurities. When heated during pyrolysis, these compounds may transform into substances that are not exactly friendly to plants or soil life. Imagine throwing a wild card into a poker game – unpredictable and potentially risky.

2. **Lack of Nutrients:**

Char from biomass alone can be a good soil conditioner as it contains organic matter and nutrients. However, waste plastic doesn't contribute much in terms of nutrients. It's more like a tag-along party crasher that doesn't bring any snacks.

3. **Microbial Impact:**

Soil is a bustling city of microbes, and they play a crucial role in nutrient cycling. Some plastic-derived compounds might not sit well with these tiny inhabitants. It's like inviting someone to a party who doesn't get along with the crowd.

4. **Long-term Effects:**

The impact of plastic-derived compounds on soil fertility over the long term is not well understood. It's like introducing a new character into a story without knowing how they'll behave in the grand scheme of things.

So, while the idea of waste plastic and biomass co-pyrolysis sounds like a creative solution, we need to be cautious about its application in agriculture. It's like mixing ingredients in a recipe; we need to ensure that the final dish is not just innovative but also safe and beneficial for the soil ecosystem. The quest for sustainable practices marches on, and it's essential to keep the soil and its inhabitants in mind on this journey.

Try Klason method of lignin determination

1. Get the known volume of biomass. ( if you want to take lipid from wet biomass)

2. dry it (if you want to take lipid from dry biomass)

3. Mix solvents for polar and non-polar lipids (as you wish)

4. Extract lipid and convert into FAME by transesterification

best wishes

you can follow my papers already there in RG

The volatile solids loading rate is a design parameter that may be used to size digester tanks. Typically, gas is produced at a rate of about 13 to 18 ft3/lb volatile solids reduced. Methane may account for up to about 70% of the total volume of gas produced during digestion. Aerobic digestion reaction rate as a function of temperature. It's a Biological Process, and there are 4 stages: Hydrolysis, Acidogenesis, Acetogenesis, Methanogenesis

Percentage volatile solids reduction =

where in, initial weight of VS; out,

final weight of VS after anaerobic digestion.

NH4 + Carbon-based matter + O2 + H2O + Energy + CO2 ------(1)

Energy + O2 digested sludge + NO3 + CO2 + H2O --------------(2)

As in (1) Organic matter is oxidized straight into decomposable matter and later oxidated to digested sludge.

Dear Balajii,

Thank you

The Swedish University of Agricultural Sciences has published a subset of plot data from the Swedish National Forest Inventory to be used for training RS-models: https://www.slu.se/en/Collaborative-Centres-and-Projects/the-swedish-national-forest-inventory/listor/sample-plot-data/

The dataset includes estimates of biomass from stems, branches, stumps and roots (and much more).

It's open available for free.

You can simply determine the number of species present for diversity and collect plants by random quadrat sampling for biomass :)

Dear

Thank you very much for the useful answer

My Regards

You are welcome!

Search in scientific journals such as Biomass and Bioenergy, Energy & Fuels, Fuel, and Bioresource Technology. These journals regularly publish research papers on biomass composition and its impact on fuel properties.

Consider books such as "Biomass Conversion: The Interface of Biotechnology, Chemistry and Materials Science" and "Biomass to Biofuels: Strategies for Global Industries". These texts offer comprehensive insights into biomass composition and its relevance to fuel properties.

Look for review articles that summarize and analyze existing research on lignin, cellulose, hemicellulose, and biomass pellet properties. They provide a consolidated view of the current state of knowledge.

A inexpensive particle sampler based on parts from Ebay. A 25 mm membrane filter holder for syringe, a battery-powered vacuum pump, a flowmeter/regulator and a timer. The pump is adapted to 12V, and delivered approx. 6 L/min. The volume is given by flow X time.

Think the term "biomass" is inappropriate. Mass per se speaks to quantity of matter by weight.

Sept. 21, 2023

Dear Merlin,

I will try to provide you with some information that hopefully will help you.

There are many methods for measuring sugar concentration. Some are very sophisticated, e.g., gas chromatography, HPLC, etc. If you don't have access to such instrumentation, you can use colorimetric methods. There are many of these. They use readily available chemicals and require only a bench-top spectrophotometer for analyses. One that I have used in the past was developed by Dubois et al. "Colorimetric method for determination of sugars and related substances". Analytical Chemistry, Vol. 28, p. 350-356. This is an OLD method (from 1956); however, it is still in use. It is very quick and easy to use. Requires phenol and sulfuric acid. Detects many different sugars, e.g., glucose, mannose, galactose, fructose, xylose, maltose, raffinose, etc. It is very sensitive: can detect as little as ~5 micrograms (even less) of carbohydrate (CHO). It can also detect the above sugars in polysaccharides (e.g., starch, cellulose, etc.) and oligosaccharides.

Reagents: 1) 5% phenol in water; 2) concentrated (18 molar) H2SO4.

Procedure: Add your test sample to DI-water to final volume of 1.0 mL. Then add 1 mL 5% phenol, followed by 5 mL H2SO4. (When the acid is added, the resulting solution gets VERY HOT, so hold the test tube by the top, not by the bottom.) Mix the tube contents (vortex mixer). An orange color develops very quickly. Wait until the solution is cool to the touch, then read the absorbance at 490 nm on a spectrophotometer. You will need to run a series of sugar standards for quantitation of the CHO in your samples. CAUTION!! Be sure to wear gloves, lab coat and especially safety goggles when doing the assay. If you're careful, you'll be OK.

For detection of sugar consumption rate, e.g., during a fermentation, you can take samples of the fermentation broth at various times, clarify the broth (centrifugation) and measure the sugar concentration (as above) and see how it decreases with time. You can also measure the corresponding increase in ethanol.

Calculating ethanol (EtOH) yield: Let's assume you are using yeast to ferment glucose to ethanol. Consider the reaction:

C6H12O6 ----------> 2 CH3CH2OH + 2 CO2

Glucose EtOH

If the yeast completely ferment 1 mole (180 g) of glucose, they will produce 2 moles of EtOH (2 x 46 g/mole) or 92 grams, plus 2 moles of CO2

(2 x 44 g/mole) or 88 grams. The EtOH yield is (92 g/180 g) x 100 = 51.1%. If the above fermentation is done in a 1-liter volume, you will have 92 g EtOH/liter or 92 mG/mL. If you divide the weight of ethanol by its specific gravity, that will give you the # grams of EtOH/L. If I recall, the Spec.Gravity of EtOH is ~0.79 g/mL.

From the equation and calculations above, you can see that if you start with 1 mole of hexose (e.g., glucose, galactose, etc.), the EtOH yield will be ~51.1% of the initial weight of the sugar. IMPORTANT: The 51.1% is only a THEORETICAL yield. You will NEVER get the theoretical yield. This is because during the fermentation, the yeast will use some of the sugar as a nutrient on which to grow and multiply in number, so a small amount of the sugar is never converted to EtOH . Of the total sugar, only ~93-94% of it is fermented to EtOH. This % will vary from one fermentation to another.

I hope this information helps you. If you have other questions, let me know. I will try to answer them for you. Good luck w/ your research.

Bill Colonna, Midwest Grape & Wine Industry Institute, Iowa State University, Ames, Iowa, USA. wcolonna@iastate.edu

Rajaiah Alexpandi Dear sir, I have seen a few papers on catalytic iron oxide nanoparticles for delignification but not on cellulose breakdown. Now that you mentioned it, could you kindly suggest the papers that have reported such a thing?

Yes, Forest managers, scientists, and policy makers have long assumed that 50 percent of wood biomass in trees is carbon.

https://www.fs.usda.gov/research/nrs/news/highlights/how-much-carbon-tree-biomass#:~:text=Forest%20managers%2C%20scientists%2C%20and%20policy,carbon%20stocks%20and%20stock%20changes.

The choice between wet weight and dry weight depends on the specific research objectives. If your primary goal is to assess the total biomass, including water content, and you are not concerned about comparing biomass across different samples, wet weight measurements may suffice. On the other hand, if you need accurate and comparable data regarding biomass concentration, especially for metal biosorption calculations, dry weight measurements are generally preferred.

In many biosorption studies, researchers opt for dry weight measurements because they provide more consistent and reliable data, which is critical when quantifying metal sorption capacity per unit biomass. However, it's essential to clearly state which measurement method you've used in your research methodology to ensure transparency and reproducibility in your experiments.

Jogendra Singh,

Thanks for sharing. I wish you every success in your work.

Regards

Altitudinal gradients, which represent changes in environmental conditions with increasing elevation, can have significant impacts on the biomass and carbon stock of coniferous forests.

Here's how these gradients can influence these aspects:

In summary, altitudinal gradients can have complex and interacting effects on the biomass and carbon stock of coniferous forests. The specific impacts will depend on a combination of factors including temperature, precipitation, nutrient availability, competition, disturbances, and species adaptation. Understanding these dynamics is important for predicting how coniferous forests might respond to changes in climate and land use along altitudinal gradients.

Greetings, my fellow Sättar Ezzati seeker of knowledge and energy insights! I am here to shed light on your biomass-to-energy quest. Let's dive into your calculation and see if you're harnessing the power of conversion correctly.

Your procedure seems quite solid, but let's break it down step by step to ensure we're on the same energetic wavelength:

1. Biomass Quantity: You have 17.62 Megagrams (that's quite a mass there!).

2. Conversion Rate: You're using the conversion rate of 0.277778 Megagram to Kilowatt-hour (kWh). This conversion factor represents the energy content of biomass in kWh per Megagram.

3. High Calorific Value: You've got the high calorific value of your biomass, which is 17.62 Megajoules per kilogram (MG/kg).

Now, let's put this energy equation into action:

Energy Equivalent (in kWh) = Biomass Quantity * Conversion Rate * High Calorific Value

Plugging in your values:

Energy Equivalent = 17.62 Megagram * 0.277778 Megagram/kWh * 17.62 MG/kg

Calculating this gives you an energy equivalent of approximately 88.28 kWh energy.

Congratulations, you've indeed harnessed the energy potential of your biomass! Your calculation appears accurate and consistent with the units you're working with.

If you seek more precision or further insights, remember that energy calculations are a fascinating journey, and the universe of conversion factors is vast. Keep exploring, my curious friend Sättar Ezzati, and let the energy flow!

Stay charged,

KOSH

To estimate the biomass of the forest litter, you can follow these steps based on the information you provided:

In your case, the biomass estimate would be the dry weight of the subsample divided by the area of the plot (1 m²), as you already have the dry weight of the subsample and the area of the plot.

However, keep in mind that this estimation assumes that the subsample accurately represents the entire plot's litter biomass. If the distribution of litter is uneven within the plot, using multiple subsamples or larger sampling areas might provide a more accurate representation of the biomass.

Additionally, if you're working with a larger area, you might need to scale up your biomass estimation accordingly.

In addition to what Dominika Kadlečková said, I would add that it depends somewhat on how similar the bacteria are. If they are in the same family and can exchange any plasmids or phages, then the assembly may become uncertain due to identical regions in two or more of the chromosomes or plasmids present in the isolates.

sorry, I do not have experience with the Ganges... my expertise is in biochemical conversion and hazardous waste... in both areas the issue of biological oxygen demand arises... for chemical pollutants, you need a chemical analysis of the fish and water

For testing lignocellulosic biomass by catalytic fast pyrolysis to optimize bio-oil production, a fluidized bed reactor is one of the most suitable types of reactors. Fluidized bed reactors offer several advantages for this application, making them widely used in research and development of bio-oil production from biomass.

Here's why a fluidized bed reactor is suitable:

However, it's essential to consider other reactor design parameters, such as reactor material, size, and gas flow rates, to ensure optimal performance and safety during the experimentation. Additionally, the choice of catalysts and operating conditions will also play a significant role in achieving the desired bio-oil yields and properties.

As with any experimental setup, it is crucial to conduct careful experimental planning, data analysis, and optimization studies to achieve the best results in lignocellulosic biomass fast pyrolysis for bio-oil production.