**3. Strategy to solve the problem**

Since microfilaments of standard material are not commercially available, a possible solution for the determination of microplastics could be the preparation and analysis of standard microfilaments in aqueous suspensions. This reliable method can help laboratories to monitor the quality of their analytical procedures. The advantage of such a procedure is that it is possible to produce different types of microfilaments with a narrow size distribution as well as blend them. This protocol could fill the gap in the knowledge of the identification and quantification of fibrous microplastics in textile or environmental matrices. In particular, the proposed procedure achieves the following objectives:


**Figure 9.** *Schematic diagram of the standard method steps.*

*Preparation and Analysis of Standard Microplastics DOI: http://dx.doi.org/10.5772/intechopen.108716*

• Identification, counting and analysis of fibrous microplastics in aqueous and non-textile aqueous matrices (**Figure 9**).

Mossotti et al. [28] developed a user-friendly method to prepare microfilament standard suspensions that can facilitate lab tests. Specifically, different synthetic threads of PA 6, PA 6.6, PET, and PP, which are shown in **Figure 10**, were used for the preparation of standard suspensions. They are commercial materials supplied by Aquafil S.p.A with a known number of filaments.

The parameters associated with all the yarns are: 1) Yellow PA 6 (180 filaments; 3450 dtex). 2) Blue PA 6.6 (68 filaments; 200 dtex). 3) Cream PET (256 filaments; 2970 dtex). 4) Orange PP (72 filaments; 70 dtex). An example of synthetic thread is shown in **Figure 11**.


#### **Figure 10.**

*Image of synthetic threads used for the preparation of the standard solution.*

**Figure 11.** *a) Yarn; b) filaments; c) single filaments.*

#### **Figure 12.**

*a) Standard fibers and wool placed in a microtome slide; b) the protruding fringe removed by razor blade b) the fiber length chosen using a suitable pusher d) the cut fibers measure about 200 μm.*

All synthetic threads were subjected to microtome cutting at a length of 200 μm according to IWTO-8-97. For the cutting step, synthetic fibers were blended with wool, as shown in **Figure 12**.

The wool is added to the synthetic yarn to fill the microtome slot completely and consequently have the correct number of synthetic filaments. The wool fibers are then removed using a hypochlorite solution. This treatment successfully eliminates the wool fiber without altering the structure of the synthetic yarns. The effect of hypochlorite on the synthetic yarn is checked using FTIR analysis.

As shown in **Figure 13** the oxidative treatment does not modify the chemical structure of the synthetic yarns since no significant changes can be seen in the absorption bands.

The presence of wool fibers can be observed using an optical microscope (OM), as shown in **Figure 14**.

The wool fibers can be easily recognized using MO analysis, as shown in **Figure 15**. Indeed, they have an irregular diameter and a surface structure consisting of overlapping scales. On the contrary, synthetic fibers typically have a wider diameter and a regular shape with a homogenous and smooth surface.

**Figure 15** shows an example of wool fibers used during the cutting stage.

After the hypochlorite treatment, the synthetic fibers were placed in an Erlenmeyer flask. For each polymeric yarn, three suspensions at 300, 500 and 900 ml were prepared and then filtered using silicon filters. The microfilaments collected on the filters were counted and the average value and standard deviation of 5 replicas were calculated.

#### **Figure 13.**

*Spectra of the synthetic fiber before (solid line) and after hypochlorite treatment (dotted line) of a) PA 6; b) PA 66; c) PET; d) f PP. No significant differences can be seen.*

#### **Figure 14.**

*Optical microscopy images (200x) of synthetic fibers (e.g., PA 6) and wool (1) cut with a microtome to 200 μm.*

#### **Figure 15.**

*a) Example of wool fine fiber used for the sample cutting stage; b) optical microscopy image of wool at 200X; c) optical microscopy image of wool at 500X. Average diameter: 16,2 μm.*

An optical microscope associated with a micro-FITR was used to count the microfilaments on the filters. This technique has several advantages:

It is fast, non-destructive, reproducible, and able to collect IR signals at a high spatial resolution. Furthermore, the coupling of a MicroFTIR with an OM opens the possibility of visualization and mapping samples across the entire surface exposed.

The MicroFTIR has become an increasingly popular instrument for characterizing samples with very small dimensions which are difficult to be chemically analyzed using the conventional FTIR.

Indeed, the microscopic component provides information about morphology, size, color, and shape. On the other hand, the spectroscopic component provides information about the specific chemical bonds by capturing the absorption spectrum of the microplastic, thus performing qualitative analysis. Finally, the possibility of developing an automated spectroscopic analysis procedure is more efficient and labor-saving than other analytical methods. In MicroFTIR mapping mode, it is possible to collect spectra in different sampling points that are measured and integrated and then used to map the distribution, as shown in **Figure 16** [29].

This technology also allows the determination of the presence of contaminants inside the sample. For instance, some cellulosic fibers were found in the control water sample (hypochlorite, wool and demineralized water). Through OM analysis, the typical ribbon shape was recognized and MicroFTIR identified the characteristic absorption bands related to cellulosic fibers, as shown in **Figure 17**.

All the collected data were statistically elaborated using a logit regression analysis to study the relationship between the concentration and probability of detection of an individual microfilament, as well as the impact of the type of polymer used as shown in **Figure 18** [30]. It is as well used to investigate the relationship between a binary response variable and some other explanatory ones.

**Figure 16.** *Counting and chemical mapping of the microfilaments (PET) collected on a silicon filter using MicroFTIR.*

**Figure 17.** *a) Optical image and b) spectra of cellulosic contaminants fibers collected in a control water sample.*

It was chosen because of the binary nature of the data, in which a dependent variable has two possible values expressed as identification or non-identification for each individual microfilament in the suspension. Let Yij, i = 1,…, n, j = 1,… m, denote the response, that is the number of detected microfilaments for the i-th sample and j-th replication. Let K be the theoretical number of microfilaments in the sample, that is the number of independent trials that can be performed on it. Then Yij is distributed as a binomial random variable of size K and probability of identification pi. The logit model used explicitly the relationship between the probability of detection of the single microfilaments, pi, and the covariates by modeling: *Preparation and Analysis of Standard Microplastics DOI: http://dx.doi.org/10.5772/intechopen.108716*

**Figure 18.**

*Boxplot of the fraction of counted versus theoretical burrs in relation to material and solution volume.*

$$\log \text{tr} \left( \mathbf{E} \left( Z\_{\left\| \mathbf{k} \right\|}, \mathbf{X}\_{\mathbf{i}, \left\| \right\|}, \mathbf{X}\_{\mathbf{z}, \left\| \right\|} \right) \right) = \log \left( \mathbf{p}\_{\text{i}} \left( \mathbf{z} - \mathbf{p}\_{\text{i}} \right) \right) = \boldsymbol{\upbeta}\_{\text{o}} + \boldsymbol{\upbeta}\_{\text{i}} \left. \mathbf{X}\_{\mathbf{i}, \left\| \right\|} + \boldsymbol{\upbeta}\_{\text{M}(\mathbf{i})} \right) \tag{1}$$

where Zijk, k = 1,…,K is a Bernoulli random variable representing the detection of the k-th microfilament in the i-th sample and j-th replication, X1,ij the concentration used and βM(i) the parameter representing the material's effect used for the i-th sample.

This statistical elaboration underlines that there is a strict relationship between the concentration of the microfilaments detection probability. Indeed, increasing the number of microfilaments there is a reduction of the detection probability.

The results of statistical analysis show that:


### **4. Conclusions**

This chapter has tackled the problem of microplastic release from textiles by trying to identify a suitable protocol for the preparation of standard microfilaments. Indeed, there is a growing concern about the microfilament from textiles released in

the environment. Since the average textile consumption is increasing, the number of synthetic microfilaments released in particular in water is rapidly enhanced. Thus, the necessity to have a reliable method for the identification and quantification of microplastic released by textiles are becoming mandatory. For this reason, in this chapter, it has been proposed not only a complete overview of the problem of the microplastics related to the textile sector but also a novel approach for the quantification and identification of them. Therefore, this chapter describes a protocol in which some standards of different synthetic fibers have been prepared in order to introduce them in a real sample. Actually, it describes the preparation of standard suspensions with a 76–853 N filaments/L concentration range using polymer threads cut at predetermined lengths of 200 mm following IWTO-8-97 and dispersed in three solutions of 300, 500, 900 ml to obtain three different concentrations. Afterward, the solutions were filtered through a silicon filter, and the collected microfilaments were counted with optical microscopy coupled with a MicroFTIR instrument. Five replicates were carried out for each sample and the data were statistically analyzed using a logit method. The probability of detecting the microfilaments is higher than 95% when the concentration of microfilaments/L is lower than 200. Thus, these microfilaments can actually work as an internal standard and the micro-FITR can be a suitable tool for the correct identification and quantification of microplastics.
