*2.1. Sample Materials*

The object of the study was the aerial part of the weed plant AR (Figure 1). The plants were grown in a field with cultivated plants (55◦63 N, 48◦73 E). In addition, they were divided into leaves, inflorescences (partially with seeds), and stems. Leaves and inflorescences were dried at room temperature, crushed, and sieved to obtain a mass with a particle size of less than 5 mm. The stems were crushed immediately, then dried and additionally ground; the particle size also did not exceed 5 mm.

#### *2.2. Physicochemical Characterization*

Moisture, ash content, and volatile matter (VM) were measured in accordance with ASTM E1755-01, ASTM E1756-08, GOST R 56881-2016, and GOST 32990-2014. Elemental analysis of the samples was carried out on a EuroEA3000 CHNS analyzer (Eurovector, S.p.A., Milan, Italy). The samples were weighed on a Sartorius CP2P microbalance (Germany) in tin capsules. Callidus 4.1 software was used to evaluate the obtained data.

**Figure 1.** Photographs of the dry biomass AR: (**a**) leaves; (**b**) inflorescences; and (**c**) stems.

The oxygen content (O, wt%) was calculated from the difference by Equation (1):

$$\text{O} = 100 - \text{H} - \text{C} - \text{N} - \text{Ash},\tag{1}$$

where H, C, N, and Ash are wt% of hydrogen, carbon, nitrogen, and ash content of the fuel, respectively.

Atomic H/C and O/C ratios of AR fractions and their biochars were determined with Equations (2) and (3) [31]:

$$\text{atomic} \frac{\text{H}}{\text{C ratio}} = \frac{\text{number of H atoms}}{\text{number of C atoms}} = \frac{\text{H}/1}{\text{C}/12} \tag{2}$$

$$\text{atomic} \frac{\text{O}}{\text{C ratio}} = \frac{\text{number of O atoms}}{\text{number of C atoms}} = \frac{\text{O/16}}{\text{C/12}} \tag{3}$$

The higher heating value (HHV, MJ/kg) of the leaves, inflorescences, and stems were determined using Equation (4) [32]:

$$\text{HHV}\_{\text{AR}} = 0.3491 \cdot \text{C} + 1.1783 \cdot \text{H} + 0.1005 \cdot \text{S} - 0.1034 \cdot \text{O} - 0.0151 \cdot \text{N} - 0.0211 \cdot \text{Ash}, \text{ (4)}$$

where C, H, O, N, and S, are, respectively, the carbon, hydrogen, oxygen, nitrogen, and sulfur content of the fuel, wt%.

### *2.3. Thermogravimetric Analysis*

The most common method used to study the thermal behavior and thermal stability of fuels is the thermogravimetric analysis. Thermal decomposition data were measured using an STA 449 A1 Jupiter synchronous microthermal analyzer (Netzsch, Selb, Germany). For this, the following experimental parameters were chosen:


To ensure the repeatability of the experiment with an error of 1.5%, the experimental conditions were repeated at least three times.

#### *2.4. Experimental Pyrolysis Procedure*

A laboratory setup was used to study the pyrolysis of the biomass samples. It includes a tubular reactor (Figure 2), in which various organic raw materials can be thermally treated [33,34].

**Figure 2.** Experimental setup for the study of pyrolysis.

The laboratory setup was preliminarily purged with nitrogen. The prepared biomass sample (weighing about 45 g) was placed in a retort, which was installed in a preheated tubular reactor, which was hermetically sealed with lids. In the reactor, the biomass samples were subjected to a pyrolysis process. The maximum temperature of the pyrolysis process was 550 ◦C. The heating rate in the experiment was 10 ◦C/min. As a result of the experiments, three products were obtained: pyrolysis gas, pyrolysis liquid, and solid carbonaceous residue, biochar. Upon completion of the pyrolysis process, the retort was cooled, the solid residue was extracted and its mass yield was determined. Liquid pyrolysis products were collected, and their mass was determined. The gaseous product was determined by the difference in the masses of products from the material balance. Each experiment was repeated at least three times.

#### *2.5. Expanded Measurement Uncertainty*

The combined standard uncertainty of the measured value *Y* (Equation (5)) is obtained according to the law of propagation of uncertainties by summing the squares of the products of the standard uncertainties of all influencing quantities:

$$
\mu(Y) = \sqrt{\mu^2(m\_{ind}) + \mu^2(m\_{devive}) + \mu^2(F\_{cor})} \tag{5}
$$

The standard measurement uncertainty of *mind* is calculated assuming a normal probability distribution using Equation (6):

$$u(m\_{ind}) = \sqrt{\frac{\sum\_{i=1}^{n} (m\_i - m\_{ind})^2}{n(n-1)}},\tag{6}$$

where *mi* is the result of the *i*-th repetition of the weight measurement, *mind* is the arithmetic mean of *m*; *n* is the number of repeated measurements, *n* = 3.

The uncertainty associated with the value of *mdevice* ((Equation (7)) is estimated using the manufacturer's data on the balance. In the laboratory scale passport for a measurement range of up to 50 g, the limits of weighing error are ±0.001 g (Δ). Since the value is given without a confidence level, we accept a rectangular distribution of weighing error values within these limits. The standard uncertainty is estimated according to type B and is:

$$
\mu(m\_{device}) = \frac{\Delta}{\sqrt{3}}.\tag{7}
$$

The standard uncertainty of the correction factor is calculated from the information on the allowable discrepancy between parallel weight determinations. The given allowable relative discrepancy is *r* = 20% and is considered a 95% confidence interval for the difference between two estimates of a quantity distributed according to the normal distribution law. The standard uncertainty of the correction factor will be equal to the standard deviation calculated on the basis of the specified interval, taking into account that the measurement result is taken as the arithmetic mean of the determinations of two parallel samples, according to type B and according to Equation (8):

$$
\mu(F\_{cor}) = \frac{r}{100\% \cdot 2.8 \cdot \sqrt{2}}.\tag{8}
$$

The expanded uncertainty *U* is obtained by multiplying the combined standard uncertainty by a coverage factor using Equation (9):

$$
\mathcal{U} = k \cdot \mathfrak{u}(\mathcal{Y}),
\tag{9}
$$

where *U* is the expanded uncertainty, *k* is the coverage factor (*k* = 2 at a confidence level of approximately 95%, assuming a normal probability distribution of the measure), *u*(*Y*) is standard uncertainty.
