**2.1 Humidity greater than 75%**

#### *2.1.1 Wet and dry biodigestion*

When dealing with high humidity content, wet and dry biodigestion are the recommended options. Wet biodigestion requires less thermal and mechanical intervention and is suitable for urban waste, while dry biodigestion is more convenient for residual biomass from agro-industries. Mathematical expressions can provide a better understanding of the transformation process and the production of by-products, according to [4].

$$\text{Vol } CH4Nm^3 = \frac{\left(\text{Methane molar mass} \frac{\text{g}}{\text{mol}}\right) \left(\text{dry weight mass kg}\right)}{\left(\text{molar mass dry weight } \frac{\text{g}}{\text{mol}}\right) \left(\text{Methane density } \frac{\text{kg}}{\text{m}^3}\right)} \tag{1}$$

Where: *Nm*<sup>3</sup> = Normal cubic meter. Methane molar mass = 234 *<sup>g</sup> mol:* Molar mass dry weight = 521 *<sup>g</sup> mol*

#### **Figure 1.**

*Technological routes for the transformation of biomass into bioenergy according to their moisture content.* Source: *[3].*

*Moisture and Solid Mass as Indicators of the Ideal Transformation Technology DOI: http://dx.doi.org/10.5772/intechopen.112272*

**Figure 2.**

*Scheme for the use of residual biomass to produce three by-products (3).*

Methane density = 0.717 *kg m*<sup>3</sup> Additionally, carbon dioxide is produced during this process.

$$\text{Vol } CO\_2Mn^3 = \frac{\left(CO\_2\text{ }molar\text{ }mass\frac{\text{g}}{mol}\right)(dry\text{ }weight\text{ }mass\text{ kg})}{\left(molar\text{ }mass\text{ }dry\text{ }weight\frac{\text{g}}{mol}\right)\left(CO\_2\text{ }density\frac{\text{kg}}{m^3}\right)}\tag{2}$$

Where:

*Nm*<sup>3</sup> = Normal cubic meter Carbon dioxide molar mass = 589 *<sup>g</sup> mol* Molar mass dry weight = 521 *<sup>g</sup> mol* Carbon dioxide density = 1.978 *kg m*<sup>3</sup>

A continuous model for receiving high-moisture residual biomass and producing biogas at a corresponding rate for electricity generation is proposed (**Figure 2**).

While the general scheme is illustrated, variations may be necessary depending on the specific case, such as rural or urban environments (**Figure 3**).

#### **2.2 Humidity less than 50%**

#### *2.2.1 Combustion*

For lower humidity levels, other technologies are considered for biomass transformation. These technologies are more suitable for biomass containing carbohydrates, starches, sugars, fats, and lignocellulosic fibers, indicating forest residues (**Figure 4**).

If the biomass moisture content exceeds 50%, a drying process is necessary prior to incineration. The energy required to reduce the humidity can be estimated by subtracting the current content from 50% and multiplying it by the water vaporization value (2250 kJ/kg).

Pelletizing the biomass for improved transport and presentation may be an option, although it incurs additional costs. The energy delivered can be estimated using the lower calorific power (LCP) formula.

**Figure 3.** *Model of the biomass use system to produce energy, heat, and agricultural amendment.*

**Figure 4.** *Biomass combustion process for electricity generation.*

*Moisture and Solid Mass as Indicators of the Ideal Transformation Technology DOI: http://dx.doi.org/10.5772/intechopen.112272*

#### **Figure 5.**

*Scheme of operation of the combustion as a technology of energetic transformation of the residual biomass.*

$$PCI = PCS \* \frac{1-w}{100} - 2.447 \* \frac{w}{100} - \left(\frac{h}{100} \* 2\right) \* 18.02 \* 2.447 \* \left(\frac{1-w}{100}\right) \|M\|\,\tag{3}$$

Where:

*LCP* ¼ Lower calorific power ⟦65,460 *MJ*⟧ *HCP* ¼ Higher calorific power⟦*MJ*⟧

*w* ¼Moisture (%)

*h* ¼Hydrogen content (% weight)

Subtracting the costs of humidity reduction and pellet production from the obtained value provides the useful energy for electricity generation through a turbine (**Figure 4**). The biomass combustion scheme is presented in **Figure 5**.

The choice of technology depends on the specific circumstances, such as geographical location and temperature conditions. Cold areas have different combustion efficiencies compared to tropical or desert areas due to heat dissipation and bacterial activity during biodigestion.

#### *2.2.2 Gasification*

According to (Probiomasa, FAO [5]), the following are the stages of gasification within an industrial plant.

**Conditioning of the biomass:** The gasifiers can run powered by different types of biomasses.

a. Fine biomass: peel of rice, peanuts, pomace, etc.

b. Biomass derived from wood: chips, pellets, briquettes.

**Gasification:** It takes place in reactors or gasifiers, where they carry out a complex process with thermochemicals.

**Adequacy of synthesis gas (syngas):** For its transformation into electric power, gasification gas must be cleaned to remove tars, and cool down. If one has to use internal combustion motors (ICM), they must be treated in ultracool systems.

**Energy generation, thermal or electric:** On generators or turbo-steam cogenerators, internal combustion engines or cycle engines must be combined.

**Water treatment process:** Current gasification systems operate in a closedcycle pattern, pointing to the maximum utilization of the resources.

The gasification process yields 2.5 to 3 normal *m*<sup>3</sup>*:* of gas per kilogram of dry biomass, with a calorific value ranging from 1000 to 1300 normal kcal/*m*3.

Gasification offers an economical option for many, producing synthesis gas (syngas) with specific chemical compositions, which are presented in the following **Table 1**.


#### **Table 1.**

*Chemical composition of synthesis gas (syngas).*

#### *2.2.3 Other energy and non-energy products*

Fermentation, a part of bioethanol production, yields by-products and useful raw materials depending on the biomass type and composition. Major bioethanol producers like Brazil and the United States primarily, close to 60% [1], utilize sugar cane and cereals (such as corn and wheat), respectively.

Fermentation of biomass results in the production of by-products, such as processing of cassava, and this must go through a hydrolysate with enzyme α-amylase, which is a pretreatment before fermentation. After this, dextrins and maltodextrins are produced, useful for the production of antibiotics such as penicillin, cephalosporin, and streptomycin, and other organic acids (citric, lactic, gluconic, and itaconic), some amino acids, xanthan gum, glucans, dietary fibers, flavorings, dietary supplements, aroma compounds, acetone, enzymes [1], etc.

#### **2.3 Selection of the appropriate technology as the case may be**

With a wide range of technologies available, the chemical composition of biomass becomes a crucial factor in the transformation process. Theoretical estimates and mathematical expressions that represent biomass characteristics and energy potential help determine the ideal technology. Selection methods, such as the analytical hierarchical process developed by Professor Thomas Satty, aid in quantitative decisionmaking by considering independent criteria or variables that may conflict. Comparative matrices and pairwise comparison tables assist in evaluating and prioritizing alternative technologies.

#### **Figure 6.**

*Hierarchy of importance of selection criteria with respect to the alternatives.*

*Moisture and Solid Mass as Indicators of the Ideal Transformation Technology DOI: http://dx.doi.org/10.5772/intechopen.112272*


**Table 2.**

*Matrix of qualifiers between pairs to be compared of the analytical hierarchical process (AHP).*

This selection method is very useful in decision-making, having both quantitative and qualitative aspects at hand, which makes it a multi-attribute method, being widely used in the field of business, economics, or operations research [6], like in this particular case of choosing the most appropriate technology to transform biomass into electricity.

Select an alternative among several proposals based on a series of criteria or variables, normally hierarchical, see **Figure 6** [6].

It is important that criteria are independent of each other, which makes it easier for the comparative matrices to yield more reliable results, with the support of the comparison **Table 2** between pairs, see **Figure 2**, which is essential when qualifying the selection priorities of the alternatives.
