*Article* **Energy Recovery of Agricultural Residues: Incorporation of Vine Pruning in the Production of Biomass Pellets with ENplus® Certification**

**Leonel J. R. Nunes 1,\* , Liliana M. E. F. Loureiro <sup>2</sup> , Letícia C. R. Sá 2 , João C. O. Matias 3,4 , Ana I. O. F. Ferraz <sup>1</sup> and Ana C. P. B. Rodrigues <sup>1</sup>**


**Abstract:** The use of residual biomass of forest and/or agricultural origin is an increasingly common issue regarding the incorporation of materials that, until recently, were out of the typical raw material supply chains for the production of biomass pellets, mainly due to the quality constraints that some of these materials present. The need to control the quality of biomass-derived fuels led to the development of standards, such as ENplus®, to define the permitted limits for a set of parameters, such as the ash or alkali metal content. In the present study, samples of vine pruning, and ENplus® certified pellets were collected and characterized, and the results obtained were compared with the limits presented in the standard. The values presented from vine pruning approximated the values presented by *Pinus pinaster* wood, the main raw material used in the production of certified pellets in Portugal, except for the values of ash, copper (Cu), and nitrogen (N) contents, with vine pruning being out of the qualifying limits for certification. However, it was found that the incorporation of up to 10% of biomass from vine pruning allowed the fulfillment of the requirements presented in the ENplus® standard, indicating a path for the implementation of circular economy processes in the wine industry.

**Keywords:** energy recovery of agricultural waste; biomass pellets; circular economy; ENplus®

#### **1. Introduction**

The use of biomass as a primary source of energy is currently an established reality, with a developed and regulated market in which products are evaluated according to quality criteria and compliance with parameters defined by regulatory processes such as certification standards [1,2]. The increasingly frequent use of solid biomass-derived fuels, as is the case with biomass pellets, has led to the development of standards regulating the physical–chemical parameters of the final product [3,4]. The development of the demand, supported by a regulatory instrument, conditioned the use of raw materials presenting parameters, mainly of chemical nature, out of normative requirements [5–7].

Initially, different standards appeared in different countries to regulate the criteria based on the regional availability of available raw materials, making it possible, when compared with each other, for the values required for the parameters to differ [8,9].

**Citation:** Nunes, L.J.R.; Loureiro, L.M.E.F.; Sá, L.C.R.; Matias, J.C.O.; Ferraz, A.I.O.F.; Rodrigues, A.C.P.B. Energy Recovery of Agricultural Residues: Incorporation of Vine Pruning in the Production of Biomass Pellets with ENplus® Certification. *Recycling* **2021**, *6*, 28. https://doi.org/10.3390/ recycling6020028

Academic Editors: Junbeum Kim and Eugenio Cavallo

Received: 26 January 2021 Accepted: 21 April 2021 Published: 22 April 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

The methodologies used to perform the laboratory tests were also not uniform in the different standards, making it difficult to directly compare the results obtained for the same product, although certified by different standards [10]. For this reason, the standardization of criteria in a single standard, allowing direct comparison of products that started to have an increasingly wider global dispersion, became a necessity [11].

However, the need for this standard to present ranges of results for the different parameters, which are sufficiently extended to be used in densified materials produced with a diverse range of raw materials in different geographical locations, has already become evident. There is a high diversity of forest species that can be used in the production process and, although often related, they show variance in their chemical composition and physical structure [12,13]. For example, although they belong to the same genus *Pinus*, the species *Pinus radiata*, originally from the American continent, differs significantly from the species *Pinus pinaster*, common on the European Atlantic coasts from Portugal to England, and thus the biomass pellets produced also present significant differences from a chemical and combustibility point of view [14,15].

In this way, the standardization of the qualitative characterization criteria of biomass pellets through a single standard was a decisive step toward the stabilization of the product, since it led to homogenization of the production processes and the selection of a set of raw materials that fit the criteria defined by the new standard, ENplus® [16]. However, this regulation also came to limit the use of raw materials of waste origin reduced the quality of the final product and its market value, since producers opt mostly for products with a higher market value and commercial margins more interesting from a business perspective [17,18].

The use of residues from operations of forest management operations, as well as those resulting from agroindustrial operations, may result in the introduction of a significant volume of low-cost raw materials, provided they are properly characterized and studied so that this introduction takes place in a proportion that does not interfere with the product quality criteria defined by the norms that regulate the sector, as is the case with the ENplus® standard [19].

An example of this type of agroforestry waste is the material resulting from the pruning of vineyards, which is traditionally used as firewood in traditional domestic fireplaces and in bakery ovens all over the Mediterranean [20–22]. Currently, with the advent of the industrialization of processes and the exponential growth of the wine industry, the quantities of residual biomass resulting from such pruning reaches significant volumes. Thus, the incorporation of this residual biomass in industrial pellet production processes can be an opportunity, both from the perspective of reducing raw material costs, as well as from the environmental perspective of reducing the volume of waste, which is otherwise often eliminated by burning the remaining materials [23]. Although the available quantities are not known for certain, it is easy to infer the high potential that these waste products present, mainly due to the volume that can be produced annually. In Portugal, currently, there are about 200,000 hectares of vineyards, which can contribute in a very significant way to the supply of biomass residues to be recovered.

The objective of the present work is to characterize the residual material resulting from the pruning of vineyards in all aspects explained in the ENplus® standard, to make a comparison with the values presented by the pellets with ENplus® certification in such a way as to understand the existing differences, and then to determine the feasibility of incorporating vine pruning in the production of biomass pellets with ENplus® certification, as the only raw material, or partially, depending on the different types of pellets that the standard presents.

#### **2. Materials and Methods**

*2.1. Sample Acquisition and Preparation*

#### 2.1.1. Sampling

For the characterization analysis of the pellets, two bags of biomass pellets were purchased in a large commercial area. The 15 kg bags were produced in Portugal and had the identification of being produced using exclusively *Pinus pinaster* wood. The bags were labeled as being pellets with ENplus® certification, which was confirmed on the website of the entity responsible for certification and available at: https://enplus-pellets.eu/pt/ certificacoes-pt-pt/produtor-pt-pt.html (10 January 2021).

The two bags were mixed, and the quantities of material necessary for the characterization tests were subsequently removed. After collection, the pellets were ground to simulate the raw material used in their production. The biomass of vine pruning was collected during December 2020 in vineyards located in the Ponte de Lima region. The material was subsequently cut into portions with dimensions close to those of the pellets (Figure 1 to facilitate drying and grinding).

**Figure 1.** Samples collected for the characterization tests. (**a**) Pellets with ENplus® A1 certification; (**b**) vine pruning already cut to a size close to that of the pellets.

#### 2.1.2. Preparation of Ash for Fusibility Tests

The preparation of samples for the ash fuse tests required a procedure necessary to ensure the production of a sufficient quantity to carry out the tests with replication to ensure statistical representation and treatment. In the present study, we decided to perform all tests in triplicate, to determine an average value used as a comparison with the values from the ENplus® standard, as well as providing the standard deviation of the sample.

The materials collected from vine pruning and from *Pinus pinaster* wood were first reduced and homogenized to a maximum nominal size of 1 mm, placed inside a crucible and taken to a muffle, where they were subjected to a combustion program appropriate to the requirements of the standard in question. In this case, according to the requirements of the ENplus® standard, the program used a heating ramp up to 250 ◦C over 40 min, and remained at that temperature for 1 h. Then, it reached 815 ◦C in a period of 1 h, where it remained for 2 h, followed by a cooling period for the samples to be removed from the interior of the muffle.

2.1.3. Sample Preparation for Inductively Coupled Plasma–Optical Emission Spectroscopy (ICP-OES) and Chlorine Determination

The procedure for preparing samples for ICP-OES, both ashes and precombustion material, and for determining the chlorine content, involved the digestion of the materials

in two stages. For this purpose, the samples were reduced and homogenized to a maximum nominal size of 2 mm and subsequently mixed with reagents for the digestion of the materials. In the present study, a CEM Mars One microwaves digestion system was used. When the selected program ended, the cooling step to <100 ◦C began. After this step, we removed the sample holder carousel from the microwave and waited another 15 min before opening the containers and taking the samples. After cooling the samples, a volume of 4% H3BO<sup>3</sup> was added to carry out the second phase of the digestion. In the second phase of digestion, the procedure began with placing the samples to be analyzed and the standard sample in a microwave where they were subjected to heating to a temperature of 150 ◦C in 5 min, maintained at this temperature for a period of 15 min, then cooled for 15 min. For methods A and B, each sample was transferred to a 50 mL volumetric flask through a paper filter (taking care to wash the container and lid walls with a 1% HNO<sup>3</sup> solution, as well as the filter paper itself), and making the balloons up to 50 mL before being homogenized. Subsequently, the contents of the flasks were transferred to 60 mL flasks for use in the ICP-OES. In method C, each sample was transferred to a 150 mL beaker, taking care to wash the walls of the container and lid with purified water. Then the digest was diluted to 100 mL, and the beaker was placed in a chloride titrator autosampler where the chlorine content was determined.

#### *2.2. Heating Value*

The calorific value indicates the amount of energy released during the combustion of a given amount of biomass. The calorific value of the biomass was determined using a calorimeter. This determination was made at a reference temperature of 30 ◦C and consisted of combustion of the biomass resulting in liquid water and carbon dioxide as products. The calculated value is defined as a higher calorific value, which includes the energy related to water vaporization (enthalpy of water vaporization; it only making sense to use these values if, during the process, the water vapor is then condensed). In processes in which the water vapor is eliminated, and its calorific value is not used, a lower heating value is used, calculated from the higher heating value and removing the value related to vaporization, i.e., the energy needed to vaporize the water is not considered as heat. A calorimeter is always composed of a combustion chamber where the sample is combusted. To ignite the sample, an electrical impulse is produced between two electrodes. For access to the interior of the combustion chamber, there is a cover which guarantees the tightness of the entire calorimeter. Surrounding the combustion chamber is a thermostatic bath that guarantees homogenization and temperature control through an agitator and a thermometer. The heat exchanges between the thermostated bath and the environment are controlled using a thermal shield. The procedure for determining the calorific value consists of recording temperature changes during the combustion process of a substance. The calorific capacity of a calorimeter indicates the amount of energy required to register a change in a temperature unit. During the combustion of a biomass sample with oxygen at high pressure, the nitrogen present in the atmosphere inside the combustion chamber is oxidized, producing nitrous oxide (NO2), which will, in turn, be combined with water vapor, producing nitric acid (HNO3). The heat derived from the formation of HNO<sup>3</sup> does not come from the sample and must be discounted in determining the calorific value. Thus, it is necessary to collect the washing water from the combustion chamber and holder with NaOH 0.1 M to correct the calorific value determined in the combustion. In combustion in an atmosphere rich in oxygen, the sulfur present in the atmosphere is oxidized to SO3, which, in turn, is combined with water vapor resulting in sulfuric acid (H2SO4). In the combustion process, the sulfur should be completely transformed into SO2, and thus it is necessary to correct the heat derived from the formation of H2SO4. For this, it is necessary to know the sulfur content present in the sample. For the determination of the calorific value, the samples should ideally be reduced to a maximum nominal size of 2 mm, and the same sample should be used to calculate the moisture content, the C, H, N, ash, S and Cl contents.

#### *2.3. Elementary Analysis (CHNO)*

The content of carbon, hydrogen and nitrogen are important factors in assessing the quality of biomass. Through the carbon content, information can be obtained regarding the amount of CO<sup>2</sup> emission during combustion. The nitrogen content can be used to obtain information regarding NO<sup>x</sup> emission. The elemental composition of the samples was analyzed, using an elemental analyzer LECO CHN, in accordance with standard EN 15,104:2011, Solid Biofuels—Determination of the Total Content of Carbon, Hydrogen and Nitrogen—Instrumental Methods. The oxygen content was, thereafter, estimated using weight difference according to Equation (1):

$$\mathbf{w(O)} = 100 - \mathbf{w(C)} - \mathbf{w(H)} - \mathbf{w(N)} - \mathbf{w(S)},\tag{1}$$

where w(O) is the oxygen content (%), w(C) is the carbon content (%), w(H) is the hydrogen content (%), w(N) is the nitrogen content (%), and w(S) is the sulfur content (%).

#### *2.4. Thermogravimetric Analysis (TGA)*

Moisture content is a necessary characteristic for calculation of the various characteristics on a dry basis. The volatile content corresponds to the loss of mass (eliminating the contribution of the loss of mass of moisture) that occurs when biomass, in an inert atmosphere, is heated to a given temperature. The ash content of biomass corresponds to the content of noncombustible (inorganic) content. The quality of the ash depends on the biomass itself, and also on the biomass collection and pretreatment processes. The ash content values vary widely depending on the type of biomass. One of the reasons for using biomass materials with low ash contents is that they have higher calorific values, since there is less noncombustible material. Therefore, for the same biomass, a lower ash content corresponds to a greater calorific value. Another great reason for wanting a low ash content is the treatment and elimination of ash formed in energy conversion processes, such as combustion or pyrolysis. Ash can cause problems, such as slagging or fouling in furnaces, in which deposits of noncombustible inorganic material accumulate. In this way, the ash formed in these processes affects the costs of running and maintaining a factory, as ash is difficult to remove and can obstruct mechanical equipment. Fixed carbon is the portion of a biomass that is consumed in thermal processes, such as combustion. In this way, fixed carbon is a good indicator of the calorific value of biomass. Thermogravimetric analysis (TGA) is a method of thermal analysis in which the physical and chemical properties are determined as a function of temperature or as a function of time. In the present study, an Eltra ThermoStep equipment (Haan, Germany) was used, in which the samples were reduced and homogenized to a maximum nominal size of 1 mm.

#### *2.5. Chemical Analysis by ICP-OES*

The analysis of the major elements of the ash of biomass allows for comparison of the formation of ash in the process of thermal conversion according to the metal content. Most of the ash formed in biomass combustion processes is primarily made up of a mixture of oxides of Ca, Si, Mg, and Al. The relationship between these oxides is important because it influences the characteristics of the ash, such as the melting temperature and viscosity. The formation of CaO in combustion processes leads to an increase in the ash melting temperature, which implies a higher ash formation at the same temperature. In some cases, the formation of CaCO<sup>3</sup> can occur, which is responsible for the accumulation of material (fouling). SiO<sup>2</sup> is the main component involved in ash formation (slagging). Aluminum (Al) is not used in biological processes by the plant; therefore, its presence in high ash levels may indicate contamination of the biomass with soil. Magnesium (Mg) is a component of chlorophyll, which is present in the green parts of plants. The formation of MgO during the combustion of biomass has the same effect as CaO, i.e., increasing the melting temperature of ash. High concentrations of iron (Fe) indicate that the sample may have been contaminated with dirt. In coal combustion processes, iron causes slagging (ash

formation at the base of the furnace). The presence of potassium (K) is usually common in fast-growing plants and its concentration depends on the seasonality of plant growth. In combustion processes, potassium remains volatile, and is an element that contributes to the emission of particles into the environment. Being a volatile element, this is one of the components that causes the formation of fouling (the clogging of pipes). When present in large concentrations, the melting temperature of the ash decreases, increasing the formation of slagging. The presence of sodium (Na) can occur naturally in plants originating from places by the sea. In large concentrations, it may indicate the presence of contamination. The effects of the presence of sodium are analogous to the presence of potassium: fouling, slagging and particle emissions. Sulfur (S) is an element causing air pollution through the formation of SO2. In addition, vaporized sulfur can lead to the formation of K2SO<sup>4</sup> particulate emissions. The presence of sulfur decreases the melting temperature of ash and increases the effects of fouling and slagging. The presence of chlorine (Cl) influences the emissions of HCl and KCl particles, which are corrosive substances. Chlorine decreases the melting temperature of the ash by increasing the formation of fouling, as it is a volatile element not found in large quantities at the bottom of the furnaces (slagging). Toxic metals, such as Cd, Pb, Zn, and Cr, are monitored due to their higher concentration in ash. Cd, Pb and Zn are partially volatile and participate in the emission of particles. Ti and Mn are elements typically found in very low concentrations. Their presence in higher concentrations may indicate contamination. For example, titanium (Ti) is a common element in paints and may indicate a mixture of biomass with wood waste with paint remnants. To determine the metal content in trace concentrations, ICP-OES (Inductively Coupled Plasma–Optical Emission Spectroscopy) was used, also called ICP-AES (Inductively Coupled Plasma– Atomic Emission Spectroscopy). ICP produces a high potential difference spark to transform argon gas into plasma. This potential difference produces ionized particles (electrons and ions) that are then accelerated by an applied magnetic field, which causes collisions with the neutral argon particles. These collisions cause a greater degree of ionizationproducing plasma. The plasma state is maintained by the continuous collisions induced by the applied magnetic field and can reach temperatures of 10,000 ◦C. The sample is nebulized to the plasma and its components are immediately ionized. As the elements return to the ground state, electromagnetic radiation is released at specific wave lengths for each element. The wavelength of the electromagnetic radiation released and its intensity are detected by the OES analyzer, which allows for determination of the concentration of an element in a sample by comparison with standards of strictly known concentrations. For each sequence of analysis in an ICP, it is necessary to perform a standard calibration with the elements to be detected. Different dilutions of standards are required depending on the method of analysis to be performed and are listed in Table 1.

The above standards were prepared in 50 mL flasks, according to the following scheme shown in Figure 2.

Subsequently, the 50 mL vials were placed in the ICP-OES autosampler, in ascending order of concentration, depending on the method to be used, and depending on the type of material to be analyzed. When the concentration of a given element was found to be greater than the measurement range, the sample was reanalyzed by performing a 1:2 dilution (5 mL of the sample + 5 mL HNO<sup>3</sup> at 1%), taking care to carry out the same dilution for the digestion blank. For every 10 test tubes, two standards were placed to adjust the values acquired after the analysis (one standard with low concentration and another standard with high concentration).


**Table 1.** Patterns used to the different sets of elements to be determined using ICP-OES.

**Figure 2.** Preparation sequence of the solutions for determining the different elements using ICP-OES. (**a**) Multielements; (**b**) As, S, P, and Ti; (**c**) Si; and (**d**) S.

#### *2.6. Fusibility of the Ashes*

The ashes fusibility test can be used for the prediction of the formation of slagging and fouling in thermal conversion processes. These data must be related to the ash content (determined using the TGA) and the content of the different ash components (determined by ICP/OES). The fusibility test can be carried out with an oxidizing atmosphere (air) or reducing atmosphere (60% CO + 40% CO2). The choice of atmosphere must be related to the combustion conditions of the boiler or burner. If the boiler operates in atmospheres rich in fuel (with an oxygen deficit), the atmosphere will be mostly reducing with incomplete combustion and CO formation. As a general rule, reducing atmospheres cause ash to melt at lower temperatures, thus, causing greater slagging and fouling problems. Therefore, the fuse test must reflect these characteristics and adapt to the customer's combustion process. During the fusibility test, the ash melting behavior was monitored and the following characteristic temperatures were determined.


In the present study, the samples were converted to ashes according to the procedure described in Section 2.1.2. Subsequently, the ashes were placed in a plastic dish, where two drops of ethyl alcohol were added and, using a spatula, they were homogenized until a uniform paste was obtained. Then, this paste was transferred to the mold where the cylinder was compacted. After being removed from the mold, the cylinders were placed on the zirconia lamella. The samples were then placed inside the chamber of the ash fusibility furnace, which, in this specific case, was a SYLAB IF 2000-G device.

#### *2.7. Determination of Chlorine Content*

The determination of chloride content was conducted through a potentiometric titration, where an Ag–AgCl electrode (silver–silver chloride) with an internal KCl electrolyte (potassium chloride) was used. The electrode consisted of a filament of Ag (s) coated with AgCl (s). This filament was, in turn, in contact with an aqueous solution of KCl. A potentiometric titration consists of measuring a signal (potential difference) as titrant is added. The equivalence point is calculated by plotting the first derivative and identifying the volume that corresponds to the maximum of the first derivative. In the potentiometric titration of chlorides, an AgNO<sup>3</sup> solution of known concentration is used as the titrant. The oxidation-reduction reaction that occurs in this titration is presented in Equation (1):

$$\rm{Cl^{-}}\_{(aq.)} + AgNO\_{3(aq.)} \rightarrow AgCl\_{(s)} + NO\_{3(aq.)} \text{.}\tag{2}$$

With the equivalence volume and the concentration value of the *AgNO<sup>3</sup>* solution, it is possible to calculate the concentration of chlorides (*Cl*−) using a SI Analytics automatic titrator.

#### *2.8. Fouling and Slagging Rates for Ash in Industrial Furnaces*

Measurements of ash fuse temperatures aim to identify the behavior of the different types of compounds that make up the ash that forms during combustion processes, especially in an industrial environment given the quantities of materials that may be involved in the processes and the size of the equipment used. The damage caused by the occurrence of certain types of compounds, for example the elements belonging to the group of alkali metals, or chlorine, can cause considerable losses, since the natural corrosion and incrustation processes, related to the chemistry of combustion processes, can be exponentially enhanced and accelerated forcing technical stops for maintenance and repair of equipment. These

phenomena of corrosion and scale that occur inside the combustion equipment, mainly in the furnace areas due to interaction with the bottom ash, but also in the areas where the heat exchange occurs due to the presence of fly ash and gases containing chlorine or sulfur, have been studied with regard the combustion processes for producing thermal energy in an industrial environment. The development of methodologies for the analysis of ash fusibility and its behavior started with the use of coal as an energy source, and all the indices that are currently used were derived from the analysis of coal ash to other solid fuels, such as biomass.

Most of the indices that are applied in the analysis of coal ash are based on the melting temperatures of the ash and its chemical composition, mainly on the ratios of acidic metal oxides, such as SiO<sup>2</sup> and Al2O3, in relation to basic metal oxides, such as Fe2O3, CaO, MgO, Na2O and K2O. These indices present a perspective of the ash fuse temperature, which then allows determination of the probability of the occurrence of corrosion, fouling, and slagging phenomena. For this reason, these indices are still widely used in industrial applications, mainly as tools for predicting potential damage and optimizing preventive maintenance, although their technical limitations are recognized. With the advent of the use of fuels derived from biomass in an industrial environment, as an alternative to the consumption of coal, the same indexes have been adapted for the new fuels. Most biomass materials have a strong presence of alkali metals, with K being the dominant element present in the bottom ash, while Na is in a form that enhances its volatilization and appears more associated with fly ash. Thus, the fouling and slagging indices developed for fuels derived from biomass are fundamentally based on the total levels of alkali metals present in the fuel. The indices used in the present study were based on the following equations.

1. Slagging Index (SI) represents the acid/base ratio used to quantify the tendency for the occurrence of slagging caused by ash from a fuel, and is determined numerically by Equation (3):

$$SI\left(\frac{B}{A}\right) = \frac{Fe\_2O\_3 + CaO + MgO + K\_2O + Na\_2O}{SiO\_2 + TiO\_2 + Al\_2O\_3}.\tag{3}$$

Equation (2) was initially developed for fossil fuels with low levels of phosphorus (P). Later, with the need to apply these methodologies also to fuels with high levels of P, another relationship developed, which is presented in Equation (3):

$$SI\left(\frac{B}{A} + P\right) = \frac{Fe\_2O\_3 + CaO + MgO + K\_2O + Na\_2O + P\_2O\_5}{SiO\_2 + TiO\_2 + Al\_2O\_3} \tag{4}$$

where the *SI* < 0.5 indicates a low propensity for slagging to occur; 0.5 < *SI* < 1.0 indicates an average propensity for slagging to occur; *SI* = 1.0 indicates a high propensity for slagging to occur and *SI* > 1.75 indicates a severe propensity for slagging to occur.

2. Fouling Index (FI) represents the propensity for the formation of fouling in industrial furnaces through the relation presented in Equation (5):

$$FI = \frac{B}{A} \times (K\_2O + Na\_2O)\_\prime \tag{5}$$

where *FI* < 0.6 represents a low propensity for the formation of fouling; 0.6 < *FI* < 40 represents a high propensity for the formation of fouling and *FI* > 40 represents a severe propensity for the formation of fouling.

3. Alkali Index (AI): this index represents and expresses the quantity of alkaline oxides per unit of energy, and is determined using Equation (6):

$$AI = \frac{1 \times 10^6 \times Ash \text{ (\%)} \times (K\_2O + Na\_2O) \text{ (\%)}}{HHV \text{ (kJ/kg)}} \tag{6}$$

where *AI* < 0.17 indicates a low propensity for the occurrence of slagging and fouling phenomena; 0.17 < *AI* < 0.34 indicates a high propensity for the occurrence of fouling and slagging phenomena and *AI* > 0.34 indicates a severe propensity for the occurrence of slagging and fouling phenomena.

#### **3. Results**

#### *3.1. Samples of Vine Pruning*

3.1.1. Heating Value

The values obtained for the high calorific value varied between 18.94 MJ/kg and 18.95 MJ/kg, and the average value calculated for the three samples was 18.95 ± 0.002 MJ/kg with a standard deviation of 0.002 MJ/kg. As expected, the low calorific value also showed very close values, with an average of 17.58 ± 0.002 MJ/kg and a standard deviation of 0.002 MJ/kg.

#### 3.1.2. Elementary Analysis

The results obtained for the elementary analysis are shown in Table 2.

**Table 2.** Elemental analysis (CHNO).


The value of the C content fluctuated between a minimum of 45.23% and a maximum of 47.12%, with an average value of 46.28 ± 1.09% and a standard deviation of 0.96%. H varied between a minimum value of 6.05% and a maximum value of 6.42%, with an average value of 6.28 ± 0.22% and a standard deviation of 0.20%. N had a minimum value of 0.280% and a maximum value of 0.710%, with an average value of 0.540 ± 0.26% and a standard deviation of 0.230%. O oscillated between the minimum value of 45.79% and the maximum value of 48.42%, with an average value of 46.89 ± 1.55% and a standard deviation of 1.37%.

#### 3.1.3. Thermogravimetric Analysis

The results obtained for the thermogravimetric analysis are shown below in Table 3.


The moisture of the samples of vine pruning after drying varied between the minimum value of 3.51% and the maximum value of 3.77%, with an average value of 3.67 ± 0.16% and a standard deviation of 0.14%. The volatile content fluctuated between the minimum value of 77.72% and the maximum value of 77.84%, with an average value of 77.80 ± 0.08% and a standard deviation of 0.07%. The ash content was between the minimum value of 1.41% and a maximum value of 1.42%, with an average value of 1.42 ± 0.01% and a

standard deviation of 0.01%. The fixed carbon content varied between the minimum value of 19.16% and the maximum value of 19.78%, with an average value of 19.18 ± 0.20% and a standard deviation of 0.17%.

3.1.4. Chemical Analysis by ICP-OES Major Elements

The results obtained using the ICP-OES for the major elements are shown in Table 4.


**Table 4.** Major elements obtained using ICP-OES.

The Al content varied between a minimum value of 53.4 mg/kg and a maximum value of 74.5 mg/kg, with an average value of 60.6 ± 13.71 mg/kg and a standard deviation of 12.1 mg/kg. Ca varied between the minimum value of 6972.5 mg/kg and the maximum value of 7722.4 mg/kg, with an average value of 7445.4 ± 465.69 mg/kg and a standard deviation of 411.5 mg/kg. Fe varied between the minimum value of 31.2 mg/kg and the maximum value of 38.6 mg/kg, with an average value of 34.0 ± 4.52 mg/kg and a standard deviation of 4.0 mg/kg. Mg varied between the minimum value of 1303.7 mg/kg and the maximum value 1387.8 mg/kg, with an average value of 1359.3 ± 54.46 mg/kg and a standard deviation of 48.1 mg/kg. P oscillated between a minimum value of 1077.5 mg/kg and a maximum value of 1107.9 mg/kg, with an average value of 1095.8 ± 18.26 mg/kg and a standard deviation of 16.1 mg/kg. K had a minimum value of 8120.4 mg/kg and a maximum value of 8444.4 mg/kg, with an average value of 8244.4 ± 197.87 mg/kg and a standard deviation of 174.9 mg/kg. Si varied between the minimum value of 131.7 mg/kg and the maximum value of 188.8 mg/kg, with an average value of 152.7 ± 35.60 mg/kg and a standard deviation of 31.5 mg/kg. Na showed a minimum value of 407.3 mg/kg and a maximum value of 444.4 mg/kg, with an average value of 421.8 ± 22.45 mg/kg and a standard deviation of 19.8 mg/kg. Ti showed a minimum value of 2.7 mg/kg and a maximum value of 3.5 mg/kg, with an average value of 3.0 ± 0.47 mg/kg and a standard deviation of 0.4 mg/kg.

Minor Elements

The results obtained using the ICP-OES for the minor elements are those shown in Table 5.


**Table 5.** Minor elements obtained using ICP-OES.

As had a minimum value of 0.58 mg/kg and a maximum value of 0.88 mg/kg, with an average value of 0.73 ± 0.17 mg/kg and a standard deviation of 0.15 mg/kg. Cd showed a minimum value of 0.34 mg/kg and a maximum value of 0.58 mg/kg, with an average value of 0.44 ± 0.14 mg/kg and a standard deviation of 0.13 mg/kg. Co had a minimum value of 0.20 mg/kg and a maximum value of 0.40 mg/kg, with an average value of 0.31 ± 0.11 mg/kg and a standard deviation of 0.10 mg/kg. Cr had a minimum value of 0.04 mg/kg and a maximum value of 0.48 mg/kg, with an average value of 0.29 ± 0.25 mg/kg and a standard deviation of 0.22 mg/kg. Cu varied between the minimum value of 23.16 mg/kg and the maximum value of 26.48 mg/kg, with an average value of 24.93 ± 1.89 mg/kg and a standard deviation of 1.67 mg/kg. Mn varied between a minimum value of 39.64 mg/kg and a maximum value of 43.44 mg/kg, with an average value of 41.34 ± 2.18 mg/kg and a standard deviation of 1.93 mg/kg. Ni showed a minimum value of 0.13 mg/kg and a maximum value of 0.63 mg/kg, with an average value of 0.39 ± 0.28 mg/kg and a standard deviation of 0.25 mg/kg. Pb varied between the minimum value of 0.09 mg/kg and the maximum value of 0.29 mg/kg, with an average value of 0.16 ± 0.13 mg/kg and a standard deviation of 0.11 mg/kg. Zn had a minimum value of 14.51 mg/kg and a maximum value of 78.40 mg/kg, with an average value of 35.81 ± 41.73 mg/kg and a standard deviation of 36.88 mg/kg. Hg showed a value below the detection limit of the equipment used in the present study and, therefore, was presented as ≤0.1 mg/kg.

Determination of the S and Cl Content

The S content varied between a minimum value of 0.0181% and a maximum value of 0.0190%, with an average value of 0.0185 ± 0.0005% and a standard deviation of 0.00046%. The Cl content varied between a minimum value of 0.0001% and a maximum value of 0.0008%, with an average value of 0.0005 ± 0.0004% and a standard deviation of 0.0003%.

3.1.5. Analysis of the Ash Fusibility

The temperatures determined for the ash fusibility test are shown in Table 6.


**Table 6.** Ash fusibility temperature analysis: initial deformation temperature, softening temperature, hemisphere temperature, and flow temperature.

> The results obtained for the shrinking temperature varied between the minimum value of 858 ◦C and the maximum value of 901 ◦C, with an average value of 882 ± 25 ◦C and a standard deviation of 22 ◦C. The strain temperature showed a minimum value of 1476 ◦C and a maximum value of 1570 ◦C, with an average value of 1527 ± 54 ◦C and a standard deviation of 47 ◦C. The hemisphere temperature varied between the minimum value of 1572 ◦C and the maximum value of 1579 ◦C, with an average value of 1576 ± 4 ◦C and a standard deviation of 4 ◦C. The fluidity temperature varied between the minimum value of 1581 ◦C and the maximum value of 1588 ◦C, with an average value of 1584 ± 4 ◦C and a standard deviation of 4 ◦C.

#### *3.2. Characterization of the Raw Material of Pinus Pinaster Wood Pellets with ENPlus Certification* 3.2.1. High and Low Heating Value

The high calorific value showed a minimum value of 19.02 MJ/kg and a maximum value of 19.79 MJ/kg, with an average value of 19.35 ± 0.45 MJ/kg and a standard deviation of 0.40 MJ/kg. The low calorific value varied between the minimum value of 17.20 MJ/kg and the maximum value of 18.47 MJ/kg, with an average value of 17.87 ± 0.72 MJ/kg and a standard deviation of 0.64 MJ/kg.

#### 3.2.2. Elemental Analysis

The results obtained for the elemental analysis are presented in Table 7.


**Table 7.** *Pinus pinaster* wood elemental analysis.

C varied between a minimum value of 50.04% and a maximum value of 50.38%, with an average value of 50.21 ± 0.19% and a standard deviation of 0.17%. H varied between a minimum value of 5.96% and a maximum value of 6.17%, with an average value of 6.07 ± 0.12% and a standard deviation of 0.10%. N varied between the minimum value 0.062% and the maximum value of 0.093%, with an average value of 0.080 ± 0.02% and a standard deviation of 0.020%. O varied between the minimum value of 43.35% and the maximum value of 43.81%, with an average value of 43.64 ± 0.28% and a standard deviation of 0.25%.

#### 3.2.3. Thermogravimetric Analysis (TGA)

The results obtained for the thermogravimetric analysis are presented in Table 8.


**Table 8.** *Pinus pinaster* wood thermogravimetric analysis.

The humidity present in the Pinus pinaster wood, as received, varied between a minimum value of 6.31% and a maximum value of 6.44%, with an average value of 6.42 ± 0.03% and a standard deviation of 0.02. The volatile content varied between a minimum value of 80.65% and a maximum value of 81.19%, with an average value of 80.87 ± 0.32% and a standard deviation of 0.28%. The ash content varied between a minimum value of 0.63% and a maximum value of 0.72%, with an average value of 0.67 ± 0.01% and a standard deviation of 0.04%. The fixed carbon content varied between a minimum value of 18.14% and a maximum value of 18.64%, with an average value of 18.46 ± 0.31% and a standard deviation of 0.28%.

#### 3.2.4. ICP-OES Chemical Analysis of Pinus Pinaster Wood Major Elements

The results obtained for the chemical analysis are presented in Table 9.


**Table 9.** *Pinus pinaster* major elements (mg/kg) obtained using ICP-OES.

The Al content varied between a minimum value of 277.73 mg/kg and a maximum value of 326.06 mg/kg, with an average value of 307.24 ± 29.28 mg/kg and a standard deviation of 25.88 mg/kg. Ca varied from a minimum value of 1539.69 mg/kg to a maximum value of 1781.17 mg/kg, with an average value of 1645.15 ± 139.87 mg/kg and a standard deviation of 123.61 mg/kg. Fe varied from a minimum of 256.60 mg/kg to a maximum of 275.37 mg/kg, with an average value of 268.37 ± 11.61 mg/kg and a standard deviation of 10.26 mg/kg. Mg varied from a minimum of 614.03 mg/kg to a maximum of 683.48 mg/kg, with an average value of 645.28 ± 39.88 mg/kg and a standard deviation of 35.24 mg/kg. P ranged from a minimum value of 73.27 mg/kg to a maximum value of 81.04 mg/kg, with an average value of 78.08 ± 4.75 mg/kg and a standard deviation of 4.20 mg/kg. K ranged from a minimum value of 672.11 mg/kg to a maximum value of 762.32 mg/kg, with an average value of 723.84 ± 52.67 mg/kg and a standard deviation of 46.55 mg/kg. Si fluctuated between the minimum value of 896.04 mg/kg and a maximum value of 1073.16 mg/kg, with an average value of 993.31 ± 101.66 mg/kg and a standard deviation of 89.84 mg/kg. Na varied from a minimum value of 365.07 mg/kg to a maximum value of 523.96 mg/kg, with an average value of 436.70 ± 91.17 mg/kg and a standard deviation of 80.56 mg/kg. Ti varied from a minimum value of 17.82 mg/kg to a maximum value of 20.73 mg/kg, with an average value of 19.22 ± 1.65 mg/kg and a standard deviation of 1.46 mg/kg.

#### Minor Elements

The results of the determination of the minor elements carried out using the ICP-OES to *Pinus pinaster* wood are shown in Table 10.


**Table 10.** *Pinus pinaster* minor elements (mg/kg) obtained using ICP-OES.

The As content varied between the minimum value of 0.89 mg/kg and the maximum value of 1.02 mg/kg, with an average value of 0.94 ± 0.08 mg/kg and a standard deviation of 0.07 mg/kg. Cd varied between the minimum value of 0.32 mg/kg and the maximum value of 0.35 mg/kg, with an average value of 0.34 ± 0.02mg/kg and a standard deviation

of 0.01 mg/kg. Co varied between a minimum value of 0.07 mg/kg and a maximum value of 0.44 mg/kg, with an average value of 0.22 ± 0.22 mg/kg and a standard deviation of 0.20 mg/kg. Cr varied between a minimum value of 1.84 mg/kg and a maximum value of 2.20 mg/kg, with an average value of 1.99 ± 0.21 mg/kg and a standard deviation of 0.19 mg/kg. Cu varied between a minimum value of 1.89 mg/kg and a maximum value of 4.92 mg/kg, with an average value of 3.55 ± 1.73 mg/kg and a standard deviation of 1.53 mg/kg. Mn varied between the minimum value of 36.84 mg/kg and the maximum value of 39.51 mg/kg, with an average value of 38.44 ± 1.59 mg/kg and a standard deviation of 1.41 mg/kg. Ni varied between a minimum value of 0.98 mg/kg and a maximum value of 1.20 mg/kg, with an average value of 1.08 ± 0.12 mg/kg and a standard deviation of 0.11 mg/kg. Pb varied between a minimum value of 0.27 mg/kg and a maximum value of 1.55 mg/kg, with an average value of 0.71 ± 0.82 mg/kg and a standard deviation of 0.72 mg/kg. Zn varied between a minimum value of 8.07 mg/kg and a maximum value of 8.33 mg/kg, with an average value of 8.08 ± 0.29 mg/kg and a standard deviation of 0.25 mg/kg. Hg showed a value below the detection limit of the equipment used in the present study, and, therefore, it was presented as ≤0.1 mg/kg.

Determination of the S and Cl Content

The S content determined using the ICP-OES varied between a minimum value of 0.0039% and a maximum value of 0.0055%, with an average value of 0.0045 ± 0.001% and a standard deviation of 0.0008%. The chlorine content varied between a minimum value of 0.012% and a maximum value of 0.021%, with an average value of 0.020 ± 0.005% and a standard deviation of 0.005%.

#### 3.2.5. Ash Fusibility

The temperatures determined for the ash fusibility test obtained by burning *Pinus pinaster* wood are summarized in Table 11.

**Table 11.** Ash fusibility temperature analysis: initial deformation temperature, softening temperature, hemisphere temperature, and flow temperature.


The results obtained for the shrinking temperature varied between a minimum temperature of 867 ◦C and a maximum temperature of 901 ◦C, with an average temperature of 879 ± 22 ◦C and a standard deviation of 19 ◦C. The deformation temperature varied between a minimum temperature of 1212 ◦C and a maximum temperature of 1215 ◦C, with an average temperature of 1214 ± 2 ◦C and a standard deviation of 2 ◦C. The temperature of the hemisphere varied between a minimum temperature of 1226 ◦C and a maximum temperature of 1227 ◦C, with an average temperature of 1227 ± 1 ◦C and a standard deviation of 1 ◦C. The fluidity temperature varied between a minimum temperature of 1234 ◦C and a maximum temperature of 1243 ◦C, with an average temperature of 1239 ± 5 ◦C and a standard deviation of 5 ◦C.

#### *3.3. Determination of the Fouling and Slagging Propensity Indices*

The values determined for the fouling and slagging indices, namely through the calculation of the Slagging indexes (B/A and B/A + P), Fouling index (FI), and Alkali index (AI), are shown in Table 12.


**Table 12.** The Fouling and Slagging indexes for samples of vine pruning and *Pinus pinaster*.

For the slagging index (B/A), values of 1.94 and 1.89 were obtained, respectively, for samples of vine pruning and for *Pinus pinaster* wood. For index slagging (B/A + P), the values were 2.05 and 1.96, a value of 0.28 was obtained both for samples of vine pruning and for wood samples of *Pinus pinaster*. For the alkali index, the value for samples of vine pruning was 20.48, while, for *Pinus pinaster* wood, the value was 4.78.

#### **4. Discussion**

The analysis of the physical–chemical parameters of the pellets acquired with ENplus® certification proved that the referred pellets fulfilled all the requirements presented by the standard. Table 13 shows the results obtained, both for *Pinus pinaster* wood pellets and for the biomass resulting from vine pruning, as well as the parameters defined by the ENplus® standard [17].

**Table 13.** Parameters defined by the ENplus® standard and the results obtained for *Pinus pinaster* wood pellets and the biomass of vine pruning.


\* The categories A1, A2 and B correspond to different levels of quality of pellets with ENPlus ® certification, and are related to the different types of raw materials used in their production.

> As can be seen in the results presented in Table 13, the values obtained for the biomass of vine pruning are in agreement with the requirements of the ENplus® standard, with the exception of the parameters corresponding to the ash content, where the average value obtained was 1.42%, the N content, where the average value obtained was 0.536% and the Cu content, where the average value obtained was 24.93 mg/kg.

> Despite being outside the requirements presented by the standard for ash content, making it impossible to use for the production of pellets in categories A1 and A2, the ash content determined had significantly lower values compared with the characterizations carried out in other previous studies, such as the study by Zanetti et al. (2017) where the values varied between 3.3% and 5.5% [24].

> This difference may be related to the fact that there may be differences between the compositions of the different varieties, and also with the influence of the types of soils

and the method of harvesting during pruning, since the method used to collect the samples for the present study was that of manual collection, directly from the grapevine. Therefore, there was no contamination with the soil through mixing with inert materials such as earth, stones, or sand. Regarding the N content, the value presented is in line with the values presented by Zanetti et al. (2017), which varied between 0.560% and 0.640%. That is, values close to 0.536% were determined for the samples analyzed in the present study. The Cu content had a value significantly higher than that presented in the study referred to above, which reported values ranging between 13.1 and 16.3 mg/kg. The value of 24.93 mg/kg may indicate the presence of the remains of a Bordeaux mixture. A combination of copper sulfate, lime and water used as fungicide and bactericide in the vineyards, which when mixed properly, provides a long-lasting protection against diseases. However, this statement requires confirmation through further analysis and monitoring of the vineyard where the samples were collected.

The occurrence of a set of elements, namely those belonging to the group of alkali metals, such as Na or K, with levels that may indicate a low melting temperature of ash, has been described in several previous works. An example of this is the work of Niue et al., (2010), which presented the analysis of residual biomasses of agricultural origin, such as capsicum stalks, cotton stalks and wheat stalks, with the ash prepared by calcining the material at 400, 600, and 815 ◦C [25]. In that study, there was a tendency for the occurrence of low ash melting temperatures, closely related to the occurrence of high levels of alkali metals and also to other elements, such as Ca, which is a recognized melting agent [25,26].

Other works, such as those presented by Ma et al., (2016), Wang et al., (2017), Rizvi et al., (2015) and Li et al., (2019), analyzed the relationships between the contents of various elements with the melting temperatures of the ash and with the behavior of these melting materials and their chemical and structural reorganization [27–30]. Another way of assessing the impact of ash fusion was described in several studies, which resorted to the transposition of analysis methodologies that are common in coal science through the adaptation of indices that relate the different constituents to each other, allowing a qualitative assessment of the potential for the occurrence of fouling or slagging phenomena. Examples of this include the works of Yao et al., (2017), Lee et al., (2018), Yao et al., (2020), Ruscio et al., (2016), and Yao et al., (2020) [31–35]. The results obtained in the determination of fouling and slagging prediction indices in the present study, described in Section 2.8, indicated a severe tendency for the occurrence of slagging processes, both for vine pruning and for wood pellets of *Pinus pinaster*. This is most likely due to the presence of Na2O, which contribute to the sintering of bottom ash, while K2O contributes in a greater proportion to the potential occurrence of fouling processes but, due to the relationships with other present compounds, shows a low tendency for the occurrence of this phenomenon.

This is an issue of increasing importance, particularly for large-scale uses, where the amounts of these compounds involved can gain significant weight, since the potential damage caused may lead to unplanned stops in energy conversion equipment. In the case of smaller equipment, such as domestic equipment, this problem is not important and there is an excellent possibility for reducing production costs by the inclusion of residual materials [36,37]. The high deformation temperatures presented by the samples of vine pruning, indicate that their use is not a problem, as they were significantly higher than those observed for the *Pinus pinaster* wood samples.

From the results obtained for the characterization of the samples of vine pruning, with the exception of the situations described in the previous paragraphs, there is a strong probability of making mixtures to incorporate biomass from vine pruning for the production of pellets with ENplus® certification. Table 14 presents the calculated results for the main physical–chemical parameters resulting from the mixtures between percentages of biomass from vine pruning with *Pinus pinaster* wood. As can be seen, for an incorporation of 50% of biomass from vine pruning, the Cu content precludes certification in any of the types (A1, A2, and B). However, for the incorporation of 25%, Cu has values within the permitted ranges, including for type A1, which is not achieved due to the ash content, but is still

higher than 0.7%, and which only allows type A2 certification. For incorporations of 10%, all parameters fall within type A1.


**Table 14.** Mixtures of *Pinus pinaster* wood and vine pruning (PP% + VP%).

The ash content values may vary significantly and, therefore, the incorporation of residual biomass should lead to the incorporation in type B productions, as defined by the standard for the use of residual materials in type B products. Preferably, these materials should be applied for domestic use, where the quantities are not continuously high and where the potential negative effects of corrosive and fouling phenomena are more easily controllable.

The definitive validation of these considerations still lacks reference to the production of pellets since the present work dealt with characterization of parameters related to the chemical properties of the materials. However, due to the fact that densification is a purely physical process, it does not appear that there were constraints in the parameters related to the quality of the pellets, such as the final moisture, durability, fines content, dimensions or density at bulk.

#### **5. Conclusions**

The current perspective of mitigating the effects of climate change has led to an increasing demand for alternative forms of energy, which can be used to replace sources of fossil origin, such as oil, coal or natural gas. Biomass appears as a very interesting possibility, and has proven to be viable as demonstrated by several large-scale tests carried out in coal-fired power plants with the use of wood pellets in cocombustion with mineral coal, through the use of wood chips produced from forest residues for the production of steam in industrial units in the textile sector, or in the heating of agricultural and aviary greenhouses. On a smaller scale, and with greater proximity, the use of fuels derived from biomass for domestic uses, mainly for heating residential spaces but also for heating spaces of a commercial and small industrial nature (as is the case, for example, with bakeries), has positively and increasingly adhered to the use of these solid fuels. However, due to the quality requirements imposed by the regulatory instruments, the production of these materials has not incorporated a wide range of residual materials resulting from activities of an agroindustrial nature, which includes the wine sector, a major producer of waste. Regarding vine pruning, the characterization studies carried out over the past few years have shown that these materials present properties, both energetic, physical and chemical, that enable their incorporation in the production processes of pellets of biomass or briquettes, which is already a current practice. However, given the volumes produced

annually, the existence of constraints related to the quality of the final products, namely the ash content or the copper content, has not allowed the incorporation of the majority of the waste produced, leading wine producers to frequently resort to less environmentally acceptable practices, such as burning the leftovers or simply abandoning them in piles.

**Author Contributions:** Conceptualization, L.J.R.N., A.I.O.F.F., A.C.P.B.R., J.C.O.M. and L.M.E.F.L.; methodology, L.J.R.N., A.I.O.F.F., J.C.O.M. and L.M.E.F.L.; validation, L.J.R.N., L.C.R.S., J.C.O.M. and L.M.E.F.L.; formal analysis, L.J.R.N., A.I.O.F.F., A.C.P.B.R., J.C.O.M. and L.M.E.F.L.; investigation, L.J.R.N. and L.C.R.S.; resources, L.M.E.F.L.; data curation, L.J.R.N., A.I.O.F.F., A.C.P.B.R., L.M.E.F.L., J.C.O.M. and L.C.R.S.; writing—original draft preparation, L.J.R.N., A.I.O.F.F., A.C.P.B.R. and L.M.E.F.L.; writing—review and editing, L.J.R.N., A.I.O.F.F., A.C.P.B.R., J.C.O.M. and L.M.E.F.L.; supervision, L.J.R.N., A.I.O.F.F., A.C.P.B.R., J.C.O.M. and L.M.E.F.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work is a result of the project TECH—Technology, Environment, Creativity and Health, Norte-01-0145-FEDER-000043, supported by the Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). L.J.R.N. was supported by proMetheus, Research Unit on Energy, Materials and Environment for Sustainability-UIDP/05975/2020, funded by national funds through FCT—Fundação para a Ciência e Tecnologia.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available because the research is not yet concluded, and the data will be updated.

**Acknowledgments:** The authors would like to acknowledge the companies YGE (Yser Green Energy SA) and AFS (Advanced Fuel Solutions SA), both in Portugal, for the execution of the laboratory tests.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


### *Article* **Energy Recovery from Invasive Species: Creation of Value Chains to Promote Control and Eradication**

**Leonel J. R. Nunes 1,\* , Abel M. Rodrigues 2,3, Liliana M. E. F. Loureiro <sup>4</sup> , Letícia C. R. Sá 4 and João C. O. Matias 5,6**


**Abstract:** The use of biomass as an energy source presents itself as a viable alternative, especially at a time when the mitigation of climate change requires that all possibilities of replacing fossil fuels be used and implemented. The use of residual biomass also appears as a way to include in the renewable energy production system products that came out of it, while allowing the resolution of environmental problems, such as large volumes available, which are not used, but also by the elimination of fuel load that only contributes to the increased risk of rural fires occurrence. Invasive species contribute to a significant part of this fuel load, and its control and eradication require strong investments, so the valorization of these materials can allow the sustainability of the control and eradication processes. However, the chemical composition of some of these species, namely *Acacia dealbata*, *Acacia melanoxylon*, *Eucalyptus globulus*, *Robinia pseudoacacia* and *Hakea sericea*, presents some problems, mainly due to the nitrogen, chlorine and ash contents found, which preclude exclusive use for the production of certified wood pellets. In the case of *Eucalyptus globulus*, the values obtained in the characterization allow the use in mixtures with *Pinus pinaster*, but for the other species, this mixture is not possible. From a perspective of local valorization, the use of materials for domestic applications remains a possibility, creating a circular economy process that guarantees the sustainability of operations to control and eradicate invasive species.

**Keywords:** invasive forest species; wood pellets; circular economy; sustainability; value chain

#### **1. Introduction**

The use of biomass as an energy source is increasingly presented as a current alternative, in the permanent search for more sustainable forms of energy, which can somehow replace traditional sources of fossil origin, such as oil and coal [1]. However, the use of biomass as an energy source is not a recent application, since this is the oldest energy source that man learned to use, from the moment that they discovered how to control fire for their own benefit, passing this on to be part of daily life situations [2]. Since time immemorial, human populations have started to have in their routine the acquisition of biomass fuels, through their collection and storage, thus being available to supply needs such as space heating, cooking, lighting, and even protection by keeping wild animals away [3].

**Citation:** Nunes, L.J.R.; Rodrigues, A.M.; Loureiro, L.M.E.F.; Sá, L.C.R.; Matias, J.C.O. Energy Recovery from Invasive Species: Creation of Value Chains to Promote Control and Eradication. *Recycling* **2021**, *6*, 21. https://doi.org/10.3390/ recycling6010021

Received: 8 February 2021 Accepted: 6 March 2021 Published: 13 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Currently, biomass remains the most widespread source of energy among the most remote populations, essentially due to its availability and ease of use, giving it the epithet "energy of the poor", since they are usually the most disadvantaged populations, mainly in Africa, Southeast Asia and some regions of Latin America, which this more rudimentary use continues to occur [4]. However, in the more developed countries there is also an increase in the use of biomass as a source of primary energy because of, in addition to the traditional consumption associated with the heating of residential spaces in the form of firewood consumption, the consumption of fuels derived from biomass, such as wood pellets and briquettes, both for heating, but also for more industrial applications, such as the production of industrial steam, and even the production of electric energy [5].

These more industrial uses, however, have led to an increasing standardization of fuel quality criteria in order to optimize their use, defining a set of characteristics, namely its heating value, but also the maximum limits of certain chemical constituents, such as the content of sulfur, chlorine and alkali metals, due to their behavior during combustion, and contribution to the occurrence of corrosive, fouling and slagging phenomena [6,7]. For this reason, the use of biomass is currently very limited to selected types which meet a set of quality requirements, leaving a set of forms of biomass considered to be residual in the supply chains, as are the materials resulting from operations forest management and agricultural activity [8,9].

Within this huge group of residual biomasses resulting from forest management operations, there are numerous tree and shrub species, which, since they have no commercial and/or industrial application, are abandoned on forest land, even after cutting, contributing to the increase in fuel load and consequent increase in the risk of rural fires [10]. Some of these species, in turn, are even exotic species, with invasive behavior, which due to their aggressiveness and competitiveness vis-à-vis native species, are conquering space and replacing native flora, making it possible to identify these situations all over the world [11]. This substitution of native species by invasive species has very negative effects that go far beyond the loss of biodiversity and changes in ecosystems, since they also hinder the development of productive forests by competing directly with the installed species [12].

In Portugal, the phenomenon of the expansion of invasive species has acquired very worrying proportions, mainly with a group of species of the genus *Acacia*, from which the *Acacia dealbata* and the *Acacia melanoxylon* stand out, but also with other species, namely the *Eucalyptus globulus*, the *Robinia pseudoacacia* and *Hakea sericea* [13]. This group of species has progressed almost exponentially, already covering extensive areas. However, the problem is not limited to these species, there are also problematic situations with *Acacia longifolia*, *Cortaderia selloana*, *Arundo donax* and *Ailanthus altissima*, among others, with which different means have been employed in order to try to eradicate, or at least control, the progression of these species [14]. The most serious situation in Portugal is that of the uncontrolled expansion of *Acacia dealbata*. This species has grown in area by more than 400% since the 70s of the 20th century, being currently the invasive species that occupies the largest area in the national territory (Figure 1). However, other species exhibit similar behaviors, making the situation even more serious.

**Figure 1.** Evolution of the area occupied by *Acacia dealbata* (adapted from [14–16]).

The creation of value chains, with the objective of promoting the use of these species, presents itself as a possibility that allows the balance of the costs generated with the operations of control of the invaders [17]. These value chains, which already exist today, encourage the forwarding of these residual materials to biomass thermoelectric plants, which give them a low financial value, often scarcely enough to pay for the different tasks of forest management, such as cutting, filling and transport, and giving no value to the combustible material, claiming its low density, high moisture content and, mainly, due to the low energy properties that some species have [18]. However, there are some species that may have a good potential for energy recovery, and that, even if they are not used as the sole source of raw material for the production of fuels derived from biomass, can be incorporated with traditional species, namely the *Pinus pinaster*, or other resinous species [19].

This perspective of valorization of residual biomasses, originating from invasive species, can be very helpful in combating, almost always unevenly, the dispersion of these species, contributing to the share of costs with the control and eradication operations [20]. In this way, the creation of these value chains may play a decisive role in the preservation of indigenous biodiversity, while contributing to the reduction in the risk of occurrence of rural fires, since the need to supply valuable raw materials promotes permanent pressure on invasive species, controlling their growth and dispersion, limiting the accumulation of fuel load [21]. In this article, the potential use of these species in the production of wood pellets is discussed, both individually and in mixtures with *Pinus pinaster* wood, in order to justify the creation of value chains that promote pressure on invasive species, ensuring the sustainability of control and eradication operations for these species. The present work has as its main objective the characterization of a set of species, namely, *Acacia dealbata*, *Acacia melanoxylon*, *Robinia pseudoacacia*, *Eucalyptus globulus* and *Hakea sericea*, and their subsequent comparison with the dominant species most used in production of solid fuels derived from biomass, such as wood pellets, which is *Pinus pinaster*.

#### **2. Results**

#### *2.1. Thermogravimetric Analysis*

The results obtained in the thermogravimetric analysis are shown in Figure 2.

**Figure 2.** Results of the thermogravimetric analysis.

Moisture is a less important characteristic because it depends directly on the time and type of drying performed. For drying described in Section 2.1. Sampling and preparation, the results varied between 6.42% of *Pinus pinaster* and 9.28% of *Acacia melanoxylon*. The remaining species show very close values, between 6.85% and 8.98%. The volatile content varied between a minimum value of 77.02%, for *Robinia pseudoacacia*, and a maximum value of 82.27%, for *Eucalyptus globulus*. The remaining species varied between 79.00% and 82.23%. The ash content varied between a minimum value of 0.52% for *Acacia dealbata* and a maximum value of 5.14% for *Robinia pseudoacacia*. The remaining species varied between a minimum value of 0.62% and a maximum value of 1.82. The fixed carbon content showed a minimum value of 16.80%, for *Eucalyptus globulus*, and a maximum value of 19.20%, for *Hakea sericea*. The remaining species showed values between 17.25% and 18.60%.

#### *2.2. Elemental Analysis CHNO*

The results obtained in the elemental analysis are shown in Figure 3.

The carbon content varied between a minimum value of 47.00% for *Acacia dealbata* and a maximum value of 60.00% for *Hakea sericea*. The remaining species varied between 47.30% and 50.21%. The hydrogen content varied between a minimum value of 5.61%, for *Acacia melanoxylon*, and a maximum value of 6.07%, for *Pinus pinaster*. The remaining species varied between 5.67% and 5.92%. The nitrogen content varied between a minimum value of 0.080%, for *Pinus pinaster*, and a maximum value of 0.711%, for *Hakea sericea*. The remaining species varied between 0.099% and 0.582%. The oxygen content varied between a minimum value of 33.40% for *Hakea sericea* and a maximum value of 47.07% for *Acacia melanoxylon*. The remaining species varied between 43.64% and 46.93%.

**Figure 3.** Results of the elemental analysis CHNO.

The results of the sulphur and chlorine content determination are shown in Figure 4.

The sulfur content varied between a minimum value of 0.005%, for *Eucalyptus globulus* and *Pinus pinaster*, and a maximum value of 0.042%, for *Robinia pseudoacacia*. The remaining species varied between 0.006% and 0.040%. The chlorine content varied between a minimum value of 0.016% for *Pinus pinaster* and a maximum value of 0.094% for *Robinia pseudoacacia*. The remaining species varied between 0.048% and 0.090%.

#### *2.4. Determination of the High and Low Heating Value*

The results of the heating value determination are shown in Figure 5.

**Figure 5.** Higher heating value (HHV) and lower heating value (LHV) results.

The high heating value varied from the minimum value of 19.35 MJ/kg, for *Acacia melanoxylon* and for *Pinus pinaster*, to the maximum value of 20.45 MJ/kg, for *Hakea sericea*. The remaining species varied between 19.37 MJ/kg and 19.54 MJ/kg. The low heating value varied from the minimum value of 17.87 MJ/kg, for *Pinus pinaster*, to the maximum value of 19.17 MJ/kg, for *Hakea sericea*. The remaining species varied between 18.11 MJ/kg and 18.27 MJ/kg.

#### *2.5. Determination of the Content of Major Elements*

The results of the content of major elements are shown in Figure 6.

The Al content varied between a minimum value of 8.05 mg/kg for *Acacia dealbata* and a maximum value of 307.24 mg/kg for *Pinus pinaster*. The remaining species varied between 19.08 mg/kg and 215.18 mg/kg. The Ca content varied between a minimum value of 1645.15 mg/kg, for *Pinus pinaster*, and a maximum value of 21,917.90 mg/kg, for *Robinia pseudoacacia*. The remaining species ranged from 2214.41 mg/kg to 4830.83 mg/kg. The Fe content varied between a minimum of 21.51 mg/kg for *Acacia dealbata* and a maximum of 268.37 mg/kg for *Pinus pinaster*. The remaining species varied between 38.77 mg/kg and 187.90 mg/kg. The Mg content varied between a minimum of 564.19 mg/kg for *Acacia dealbata* and a maximum of 1474.89 mg/kg for *Robinia pseudoacacia*. The remaining species varied between 645.28 mg/kg and 1120.13 mg/kg. The P content varied from a minimum value of 78.08 mg/kg, for *Pinus pinaster*, up to a maximum value of 480.22 mg/kg. The remaining species varied between 124.93 mg/kg and 312.28 mg/kg. The K content varied from a minimum value of 723.84 mg/kg, for *Pinus pinaster*, up to a maximum value of 3848.58 mg/kg, for *Robinia pseudoacacia*. The remaining species ranged from 1427.42 mg/kg to 3003.84 mg/kg. The Si content varied from a minimum value of 5.13 mg/kg, for *Acacia melanoxylon*, to a maximum value of 993.31 mg/kg, for *Pinus pinaster*. The remaining species varied between 31.47 mg/kg and 856.28 mg/kg. The Na content varied between a minimum value of 436.79 mg/kg, for *Pinus pinaster*, and a maximum value of 1984.70 mg/kg, for *Hakea sericea*. The remaining species varied between 738.66 mg/kg and 1106.17 mg/kg. The Ti content varied between a minimum of 1.22 mg/kg for *Acacia dealbata* and a maximum of 19.22 mg/kg for *Pinus pinaster*. The remaining species ranged from 1.84 mg/kg to 15.68 mg/kg.

**Figure 6.** Content of major elements.

#### *2.6. Determination of the Content of Minor Elements*

The results of the content of minor elements are shown in Figure 7.

**Figure 7.** Content of minor elements.

The As content varied between the minimum value of 0.81 mg/kg, for *Acacia dealbata*, and the maximum value of 2.55 mg/kg, for *Robinia pseudoacacia*. The remaining species ranged from 0.94 mg/kg to 2.12 mg/kg. The Cd content varied between the minimum value of 0.00 mg/kg, for *Hakea sericea*, up to a maximum value of 0.34 mg/kg, for *Pinus pinaster.* The remaining species varied between 0.01 mg/kg and 0.03 mg/kg. The Co content varied between the minimum value of 0.07 mg/kg, for *Hakea sericea*, and the maximum value of 1.25 mg/kg, for *Acacia melanoxylon*. The remaining species varied between 0.09 mg/kg and 0.36 mg/kg. The Cr content varied between the minimum value of 0.23 mg/kg, for *Acacia dealbata*, and the maximum value of 2.28 mg/kg, for *Acacia melanoxylon*. The remaining species varied between 0.34 mg/kg and 1.99 mg/kg. The Cu content varied between the minimum value of 2.80 mg/kg, for *Acacia dealbata*, and the maximum value of 13.56 mg/kg, for *Robinia pseudoacacia*. The remaining species varied between 3.55 mg/kg and 8.77 mg/kg. The Mn content varied between the minimum value of 15.79 mg/kg, for *Robinia pseudoacacia*, and the maximum value of 288.36 mg/kg, for *Hakea sericea*. The remaining species varied between 24.59 mg/kg and 94.25 mg/kg. The Ni content varied between the minimum value of 0.44 mg/kg, for *Acacia dealbata*, and the maximum value of 1.77 mg/kg, for *Acacia melanoxylon*. The remaining species varied between 0.85 mg/kg and 1.60 mg/kg. The Pb content varied between the minimum value of 0.23 mg/kg, for *Hakea sericea*, and the maximum value of 1.64 mg/kg, for *Acacia melanoxylon*. The remaining species varied between 0.33 mg/kg and 0.77 mg/kg. The Zn content varied between the minimum value of 3.62 mg/kg, for *Eucalyptus globulus*, and the maximum value of 11.38 mg/kg. The remaining species varied between 4.08 mg/kg and 10.42 mg/kg.

#### *2.7. Ash Fusibility*

The results of the ash fusibility temperatures are shown in Figure 8.

Deformation temperatures ranged from the minimum value of 1057 ◦C, for *Robinia pseudoacacia*, and the maximum value of 1569 ◦C, for *Acacia dealbata*. The remaining species varied between 1123 ◦C and 1464 ◦C. Hemispherical temperatures varied between the minimum value of 1227 ◦C, for *Pinus pinaster*, and the maximum value of 1581 ◦C, for *Acacia dealbata*. The remaining species varied between 1238 ◦C and 1483 ◦C. The flow temperatures varied between the minimum value of 1239 ◦C, for *Pinus pinaster*, and the maximum value of 1588 ◦C, for *Acacia dealbata*.

#### **3. Discussion**

There are many works available where characterizations of the most diverse types of biomass are presented, in order to assess their combustibility and their physical-chemical properties. An example of this is the review work presented by Cai et al. (2017), where several lignocellulosic biomasses are characterized, including several residual biomasses

of agricultural origin, such as rice husk, rice stalk, cotton stalk, wheat straw or corn stalk, but also residual biomasses of forest origin, like pine or poplar [22]. The objective of this study by Cai et al. (2017) fits that of many others, such as those presented by García et al. (2012), Chiang et al. (2012), Wilson et al. (2011), Fang et al. (2015) or Patel and Gami (2012), always from the perspective that using lignocellulosic biomassderived biofuels can reduce reliance on fossil fuels and contribute to climate change mitigation [23–27]. Many works are also available regarding the behavior of different forms of biomass when subjected to thermochemical conversion processes, such as torrefaction, pyrolysis or gasification, such as the work of Chen et al. (2014), which addresses the non-oxidative and oxidative torrefaction characterization and SEM observations of fibrous and ligneous biomass [28], or the work of Neves et al. (2011), where biomass pyrolysis is addressed, regarding models, mechanisms, kinetics and some information on product yields and properties [29]. In fact, this perspective of energy recovery through the use of energy densification technologies foresees, at the outset, a need to improve, or in some way, correct, the less positive characteristics, such as low heating value, low density or high content of ashes. However, the most frequent uses presuppose the direct combustion of materials [30–32].

The comparative analysis of forms of residual biomass and their potential framing with premium raw materials, certified by the international standards in force, as is the case of ENplus ®, has also been addressed by extensive literature. For example, the work presented by Agar et al. (2018) addresses the production of pellets from agricultural and forest biomass [33], while de Souza et al. (2020) addressed the possibility of producing pellets from eucalyptus biomass and coffee growing wastes residues with acceptable properties for commercialization standards, which includes the ENplus ® standard [34]. In other words, the possibility of integrating different forms of biomass has been a necessity for a long time, since it would allow, in case of success and compliance with the quality criteria, the reduction in the cost of the acquisition of raw materials at the same time, which presents a solution for the disposal/reuse of a set of waste, which until now has not been subject to any type of recovery [13].

Thus, the classification of the properties of any residual raw material, as is the case of the species selected in the present study, with the parameters defined with one of the standards used internationally for the certification of fuels derived from biomass, as is the case of ENplus ® standard, allows, in a simple and accessible way, the validation or exclusion of the use of a certain material (species), or at least, it allows indicating whether it is possible to incorporate a certain percentage of these materials in any way [35]. Table 1 shows the values allowed for the main parameters indicated for the raw materials used in the production of wood pellets by the ENplus ® standard. This standard divides products into three categories according to the origin of the raw materials, with categories A2 and B destined to products resulting from the processing of waste materials, which include the species used in the present study [36]. However, in the case of incorporating percentages of residual biomass with premium raw materials, and if the parameters defined in the standard are met, the final products can be included in category A1, which has the highest added value [37].

The results obtained by the characterization of these biomass species, which are summarized in Table 2, present a relatively different framework. In the table, the values marked in italics represent the values that meet the requirements of categories A2 or B, and in bold, the values that do not fit into any of the categories. The remaining values are within the limits imposed by the ENplus ® A1 standard. As expected, *Pinus pinaster* fully complies with all the requirements presented by the ENplus ® standard, while none of the other species fully comply with all parameters. However, some of the species present values very close to the permitted limits, so that their incorporation with, for example, *Pinus pinaster*, appears as possible, and thus meet the requirements defined by the standard ENplus ®.


**Table 1.** Limit values for properties defined by the ENplus ® standard.

**Table 2.** Comparative analysis of the results obtained with the parameters defined by the ENplus ® standard.


As can be seen in the results presented in Table 2, the incorporation of these materials in the production of certifiable wood pellets, only seems possible for the biomass of *Eucalyptus globulus*, which would easily dilute the values above the requirements defined in the standard, allowing the incorporation of a percentage of 25%, which allows the production of wood pellets of category A1. An incorporation of 50% of *Eucalyptus globulus* biomass would only allow for category B certification, since the chlorine content would always be close to the upper limit of 0.03% indicated in the standard for this category. The remaining species present values that are too high in some parameters, namely in nitrogen content, with values ranging between 0.308% and 0.711%, mainly for *Hakea sericea* and *Robinia pseudoacacia*, but also due to the accumulation of other parameters outside the limits defined, as for the ash content, with *Robinia pseudoacacia* reaching 5.14%, and in the chlorine content, where it reaches 0.09%, together with Hakea sericea. However, the use of these residual biomasses remains possible, especially if the objective is not to produce certified materials, but rather to be used less domestically, and to support the local biomass recovery.

The local valorization of residual biomasses, as those analyzed in the present study, as well as others with similar properties, can always be a solution. Usually, given the lower

requirement of the proximity markets, where the most evaluated requirement is the fuel cost, in detriment to the quality and combustibility requirements, such products can be used. The possibility of using these residual biomasses in thermochemical conversion processes, namely in the production of biochar, not as an energy product, but rather as a soil amendment product and as a carbon sequestration methodology, must be evaluated, with regard to the creation of value chains for residual biomass. This perspective of creating value chains, which aim to promote the maintenance of actions to control and eradicate invasive species, contributes systematically to the revitalization of ecosystems. This positive condition is effective when the pressure caused on the populations of invasive species decrease their strength, allowing native species to develop and return to occupy their space.

#### **4. Materials and Methods**

#### *4.1. Sampling and Material Preparation*

The species were selected for their availability and abundance and were collected in areas where their proliferation has been noted for the speed of propagation and occupation of space. Thus, the samples were collected in the locations shown in Table 3. Thus, samples of five invasive species were collected, namely, *Acacia dealbata*, *Acacia melanoxylon*, *Eucalyptus globulus*, *Robinia pseudoacacia* and *Hakea sericea*. Samples of *Pinus pinaster* were also collected to serve as a point of comparison. All samples were collected in the form of adult tree trunks, and in the case of invasive species, the all-in method was chosen. That is, none of the constituent parts, such as branches or leaves, have been discarded.

**Table 3.** Location of sample collection points used in the present study.


In the sample preparation procedure, the sequence used in a wood pellet production unit was followed, using exclusively *Pinus pinaster* as a raw material, so the *Pinus pinaster* wood was previously debarked before proceeding with the drying. The rest of the wood was not debarked, since the industrial debarking process used is optimized to operate only with *Pinus pinaster* logs, and if the other mentioned species were included in the process, this operation would not be carried out efficiently. Then, the size of the collected samples was reduced to a granulometry equivalent to that normally used in the industrial process, that is, to a G30 size woodchips, which was subjected to drying in a laboratory oven at 100 ◦C for a period of 12 h. After drying, the material of all samples was ground again, until the dimension normally used in the industrial process of wood pellet production was reached, with a d<sup>50</sup> within the range [1.13–3.86]. Subsequently, the laboratory characterization of the samples followed with the thermogravimetric analysis, the elemental analysis, the calorimetric analysis, the chemical analysis and the analysis of the fusibility of the ashes. All samples were collected and analyzed in triplicate and the results presented are the average values for each species.

#### *4.2. Thermogravimetric Analysis (TGA)*

The thermogravimetric analyzer used was an ELTRA THERMOSTEP model. One gram of each sample was introduced into crucibles and placed inside an oven, along with an empty reference crucible. As temperature increased, crucibles were weighted on a precision scale. Moisture, volatiles, and fixed carbon content were determined in this order throughout the heating process. Lastly, the final residue represents the ash content.

#### *4.3. Elemental Analysis (CHNO)*

Elemental analysis was performed in a LECO CHN628. The operational principle consists of weighing a sample in tin foil that is later placed in the autoloader. The sample is then introduced into the primary furnace containing only pure oxygen, which results in fast and complete combustion. Carbon, hydrogen, and nitrogen present in the sample are oxidized to CO2, H2O, and NOx, respectively, and are swept by the oxygen carrier gas through a secondary furnace for further oxidation and particulate removal. Detection of H2O and CO<sup>2</sup> occurs through separate, optimized, non-dispersive infrared cells, while the NO<sup>x</sup> gases are reduced to N. Lastly, N<sup>2</sup> is detected when the gas passes through a thermal conductivity cell. After the analysis is complete, moisture content obtained through thermogravimetric analysis is introduced into the software and the CHN contents are automatically calculated. Following that, it is possible to estimate the oxygen content on a dry basis (wO,db) from Equation (1), as follows:

$$\mathbf{w\_{O,db}} \text{ (\%)} = 100 - \mathbf{w\_{C,db}} - \mathbf{w\_{H,db}} - \mathbf{w\_{N,db}} - \mathbf{w\_{S,db}} - \mathbf{w\_{C,db}} \tag{1}$$

where wC,db is the carbon content on a dry basis (%), wH,db is the hydrogen content on a dry basis (%), wN,db is the nitrogen content on a dry basis (%), wS,db is the sulfur content on a dry basis (%), and wCl,db is the chlorine content on a dry basis (%).

#### *4.4. Determination of Chlorine Content*

Chloride titration was the method chosen to determine the chlorine content, and the equipment used was a TITROLINE 7000 titrator from SI Analytics. For this procedure, sample preparation involves previous digestion of the sample, performed in a SINEO MDS-6G microwave, since titration requires a liquid sample. Chlorine content determination is achieved by potentiometric titration. This method consists of measuring the potential difference while the titrant, in this case, AgNO3, is added. Equation (2), as follows, presents the redox reaction that occurs:

$$\rm Cl^{-}\_{\rm (aq.)} + AgNO\_{3(aq.)} \to AgCl\_{(S)} + NO\_{3}^{-} \text{(aq.)}\tag{2}$$

As next step, a software creates a spreadsheet with the potential difference and titrant volume variation over time. First derivative can then be calculated through Equation (3), as follows, and the equivalence point can be determined as the volume corresponding to the maximum of the first derivative:

$$\mathbf{f}'(\mathbf{x}) = \frac{\Delta \mathbf{U}}{\Delta \mathbf{V}} = \frac{\mathbf{U}\_{\mathbf{i}} - \mathbf{U}\_{\mathbf{i}-1}}{\mathbf{V}\_{\mathbf{i}} - \mathbf{V}\_{\mathbf{i}-1}} \mathbf{f}'(\mathbf{x}) = \frac{\Delta \mathbf{U}}{\Delta \mathbf{V}} = \frac{\mathbf{U}\_{\mathbf{i}} - \mathbf{U}\_{\mathbf{i}-1}}{\mathbf{V}\_{\mathbf{i}} - \mathbf{V}\_{\mathbf{i}-1}},\tag{3}$$

where ∆U is the potential difference variation (mV) and ∆V is the volume variation (mL). Chlorine content on a dry basis (wCl,db) is then determined by Equation (4), in compliance with the European standard EN15289:

$$\mathrm{w}\_{\mathrm{C,dB}}\left(^{\mathrm{\text{\textbullet}}}\mathrm{\text{\textbullet}}\right) = \frac{\left(\mathrm{C} - \mathrm{C}\_{0}\right) \times \mathrm{V}}{\mathrm{m}} \times 100 \times \frac{100}{100 - \mathrm{M\_{ad}}} \mathrm{w}\_{\mathrm{C,dB}}\left(^{\mathrm{\textbullet}}\mathrm{\textbullet}\right) = \frac{\left(\mathrm{C} - \mathrm{C}\_{0}\right) \times \mathrm{V}}{\mathrm{m}} \times \mathrm{d} \times \frac{100}{100 - \mathrm{M\_{ad}}}\tag{4}$$

where C is the concentration of chloride in the solution (mg/L), C<sup>0</sup> is the concentration of chloride in the blank solution (mg/L), V is the volume of the solution (l), m is the mass of the test portion used in the digestion (mg), and Mad is the moisture content in the analysis test sample (%).

#### *4.5. Heating Value*

Heating value, also known as the heating value, defines the energy content of biomass fuel [38]. This parameter can be described in two ways: higher heating value (HHV), or gross heating value, refers to the heat released from fuel combustion along with the vaporization energy from water. On the other hand, lower heating value (LHV) or net heating value is based on steam as the product, which means its vaporization energy is

not considered heat [39]. The heating value of biomass, both higher and lower, can be determined experimentally by employing an adiabatic bomb calorimeter. The model used in this project was the 6400 Automatic Isoperibol Calorimeter by PARR INSTRUMENT. After each procedure, the equipment provides the corrected temperature increase that is later used for the determination of the heating value. Due to the nitrogen and oxygen-rich atmosphere inside the calorimeter, nitric acid and sulphuric acid are formed, respectively, and the heat of formation of both acids must be disregarded. For HNO3, the wash water for the pump was titrated with NaOH (0.1 M), and Equation (5) was applied, while for H2SO4, knowing the sulfur content Equation (6) can be applied:

$$\mathbf{Q\_{N,S}} = 1.43 \times \mathbf{V\_{NaOH}} \,\tag{5}$$

where QN,S is the heat contribution relative to nitric acid formation (cal) and VNaOH is the volume of NaOH used in the titration of the wash water of the pump (ml).

$$\mathbf{Q\_{S,add}} = \mathbf{13.61} \times \mathbf{w\_{S,dd}}\_{\mathbf{v}, \mathbf{db'}} \tag{6}$$

where QS,add is the additional contribution relative to sulfur dioxide formation and wS,db is the sulfur content on a dry basis (%).

With this information, Equation (7) can be applied to obtain the gross heating value, or high heating value, at a constant volume, qV,gr (J/g), as follows:

$$\mathbf{q}\_{\rm V,gr} = \left(\frac{\boldsymbol{\varepsilon} \times \boldsymbol{\theta} - \mathbf{Q}\_{\rm flread} - \mathbf{Q}\_{\rm N,S}}{\mathbf{m}} - \mathbf{Q}\_{\rm S,add}\right) \times 4.1868,\tag{7}$$

where ε is the heating capacity of the calorimeter (previously determined) (cal/◦C), θ is the corrected temperature increase (◦C), Qthread is the heat contribution relative to the thread combustion (cal), QN,S is the heat contribution relative to nitric acid formation (cal), QS,add is the additional contribution relative to sulfur dioxide formation (cal), and m is the mass of the sample (g).

Equation (8) was used to calculate the gross heating value at constant volume on a dry basis, qV,gr,db (J/g), as follows:

$$\mathbf{q}\_{\rm V,gr,db} = \mathbf{q}\_{\rm V,gr} \times \frac{100}{100 - \mathbf{M}\_{\rm ad}} \mathbf{q}\_{\rm V,gr,db} = \mathbf{q}\_{\rm V,gr} \times \frac{100}{100 - \mathbf{M}\_{\rm ad}} \tag{8}$$

where qV,gr,db is the gross heating value at constant volume (J/g) and Mad is the moisture content in the analysis test sample (%). Lastly, the net heating value at constant pressure on a dry basis, qp,net,db (J/g), can be calculated through Equation (9), as follows:

$$\mathbf{q}\_{\rm p,net,db} = \mathbf{q}\_{\rm V,gr,db} - 212.2 \times \mathbf{w}\_{\rm H,db} - 0.8 \times (\mathbf{w}\_{\rm O,db} + \mathbf{w}\_{\rm N,db}) \tag{9}$$

where qV,gr,db is the gross heating value at constant volume on a dry basis (J/g), wH,db is the hydrogen content on a dry basis (%), wO,db is the oxygen content on a dry basis (%), and wN,db is the nitrogen content on a dry basis (%). According to the European standard EN14918, (wO,db + wN,db) is obtained from Equation (10), as follows:

$$(\mathbf{w}\_{\rm O,db} + \mathbf{W}\_{\rm N,db}) = 100 - \mathbf{w}\_{\rm A,db} - \mathbf{w}\_{\rm C,db} - \mathbf{w}\_{\rm H,db} - \mathbf{w}\_{\rm S,db} \tag{10}$$

where wA,db is the ash content on a dry basis (%), wC,db is the carbon content on a dry basis (%), wH,db is the hydrogen content on a dry basis (%), and wS,db is the sulfur content on a dry basis (%).

#### *4.6. Chemical Analysis by ICP-OES*

Inductively coupled plasma atomic emission spectroscopy (ICP-AES), also known as inductively coupled plasma optical emission spectrometry (ICP-OES), is an analytical

technique, which produces excited atoms and ions that emit electromagnetic radiation at different wavelengths and is used for the determination of trace elements. The main advantages are its multi-element capability, broad dynamic range, and effective background correction [40]. For the preparation of the samples, microwave digestion was once again necessary to ensure that the capillaries did not get obstructed. The model used for the analysis was a THERMO SCIENTIFIC (iCAP 6000 series). A peristaltic pump delivered the digested samples to an analytical nebulizer and introduced them into the plasma flame that breaks down the samples into charged ions, releasing radiation with specific wavelengths. In the end, a software generates a spreadsheet with the results. Equations (11) and (12) were used, as follows, to calculate the content of each element in the sample on a dry basis (wi,db), in compliance with standards EN15289, EN15290 and EN15297:

$$\text{bw}\_{\text{i,db}} = \left(\frac{\text{mg}}{\text{kg}}\right) = \frac{(\text{C} - \text{C}\_{\text{i,0}}) \times \text{V}}{\text{m}} \times \frac{100}{100 - \text{M}\_{\text{ad}}} \tag{11}$$

where C<sup>i</sup> is the concentration of the element in the diluted sample digest (mg/L), Ci,0 is the concentration of the element in the solution of the blank experiment (mg/L), V is the volume of the diluted sample digest solution (mL), m is the mass of the test portion used (g), and Mad is the moisture content in the analysis test sample (%).

$$\text{w}\_{\text{S,db}} \left( \text{\textdegree\text{\textquotesingle}o} \right) = \frac{(\text{C} - \text{C}\_0) \times \text{V}}{\text{m}} \times 0.3338 \times 100 \times \frac{100}{100 - \text{M}\_{\text{ad}}} \tag{12}$$

where C<sup>i</sup> is the concentration of sulfate in the solution (mg/L), Ci,0 is the concentration of sulfate in the solution of the blank experiment (mg/L), V is the volume of the diluted sample digest solution (mL), m is the mass of the test portion used (g), 0.3338 is the stoichiometric ratio of the relative molar masses of sulfur and sulfate, and Mad is the moisture content in the analysis test sample (%).

#### *4.7. Fusibility of the Ashes*

This determination makes it possible to estimate the behavior of biomass ash when combustion is carried out, for example, in boilers or burners. During the combustion process, ashes may occur, such as slagging and fouling. Slagging is the deposit of ash in the bottom and walls of the furnaces, while fouling is the deposit of ash in the air flow zones (which can cause clogging of pipes). The formation of slagging and fouling depends on the ash content of a biomass, as well as on the elemental composition of the ash. The determination of ash fusibility consists of monitoring the behavior of ash melting along a temperature ramp. Thus, this test allows to predict the formation of slagging and fouling in thermal conversion processes. These data must be related to the ash content (determined using the TGA) and the content of the different ash components (determined by ICP/OES). The fusibility test can be carried out with an oxidizing atmosphere (air) or reducing atmosphere (60% CO + 40% CO2). The choice of atmosphere must be related to the combustion conditions of the boiler or burner. If the boiler operates in atmospheres rich in fuel (with oxygen deficit), its atmosphere will be mostly reducing, with incomplete combustion and CO formation. As a general rule, reducing atmospheres cause ash to melt at lower temperatures, thus causing greater slagging and fouling problems. Therefore, the fuse test must reflect these characteristics and adapt to the customer's combustion process. During the fusibility test, the ash melting behavior is monitored and the following characteristic temperatures are determined:


• Fluid temperature: temperature at which the height is equal to half the height recorded at the hemisphere temperature.

In the present study, the samples, converted to ashes, were subsequently placed in a plastic dish, where two drops of ethyl alcohol are added, and using a spatula they are homogenized until a uniform paste is obtained. Then this paste is transferred to the mold, where the cylinder is compacted. After being removed from the mold, the cylinders are placed on the zirconia lamella. The samples are then placed inside the chamber of the ash fusibility furnace, which in this specific case was a SYLAB IF 2000-G device.

#### **5. Conclusions**

The use of residual biomass in the production of wood pellets is an opportunity for the circularization of the local economy associated with forest management operations. It also presents itself as an opportunity for the sustainability of operations to control invasive species, as it contributes to the creation of value chains for residual products that until now had no added value. The incorporation of these materials in the production of certified wood pellets presents some difficulties, since these materials do not meet the chemical requirements imposed by the standards that regulate the quality of the final products. However, the recovery of residual biomass from actions to control and eradicate invasive species can be a reality, especially for uses that do not imply product certification, and especially when the recovery of materials in industrial environments is not involved, where adverse effects, such as corrosion, fouling or slagging, can result in serious damage and unforeseen maintenance to combustion equipment.

**Author Contributions:** Conceptualization, L.J.R.N., J.C.O.M. and A.M.R.; methodology, L.J.R.N. and J.C.O.M.; validation, L.J.R.N., L.C.R.S. and L.M.E.F.L.; formal analysis, L.J.R.N., J.C.O.M. and A.M.R.; investigation, L.J.R.N., L.C.R.S. and L.M.E.F.L.; data curation, L.J.R.N., J.C.O.M., A.M.R., L.C.R.S. and L.M.E.F.L.; writing—original draft preparation, L.J.R.N., J.C.O.M. and A.M.R.; writing—review and editing, L.J.R.N., J.C.O.M. and A.M.R.; supervision, L.J.R.N., J.C.O.M. and A.M.R. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work is a result of the project TECH—Technology, Environment, Creativity and Health, Norte-01-0145-FEDER-000043, supported by Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). L.J.R.N. was supported by proMetheus, Research Unit on Energy, Materials and Environment for Sustainability—UIDP/05975/2020, funded by national funds through FCT—Fundação para a Ciência e Tecnologia.

**Acknowledgments:** The authors would like to acknowledge the companies YGE—Yser Green Energy SA, and AFS—Advanced Fuel Solutions SA, both in Portugal, for the execution of the laboratory tests.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

