*3.1.3 Risk quotient (RQ) and predicted-no-effect-concentration (PNEC) based on species sensitivity distribution (SSD)*

This method to estimate the environmental risk is completely different from those discussed in the previous sections and it has been used by 25% of the articles reviewed [13, 21]. It is an estimate of the hazardous concentration for protecting 95% of the species (HC5), the predicted-no-effect concentration (PNEC, Ec. 8), and a risk quotient (RQ) (relationship between the measured environmental concentration (MEC) and the PNEC; Ec. 9), based on a species sensitivity distribution (SSD), a tool to establish safe limits on chemical concentrations on surface waters.

The general procedure to perform an SSD is: first to compile the results of many toxicity tests performed separately on a given chemical using several species; second, a statistical distribution that best fits the data and; third, the fitted distribution is used to infer a concentration that protects the desired proportion of similar species (HC5) [26].


*Those colored in gray represent the studies that were performed with Eqs. (1)–(7) and those that are not colored represent those that used a probabilistic approach.*

#### **Table 2.**

*Reviewed articles; studied areas, equations/method used to develop the ERA, toxicology score, and ERA results.*


#### **Table 3.**

*Risk assessment of MPs pollution—MPs-induced risk index (HI) and pollution load index (PLI).*

$$\text{PNEC} = {}^{HC}\!\!\!/ \_{\text{Assembly Factor}} (\text{AF}) \tag{8}$$

$$RQ = \text{MEC} /\_{\text{PNEC}} \tag{9}$$

To estimate a PNEC for a single chemical compound using an SSD correctly, it is necessary to include a minimum of 10 chronic toxicity data and to cover eight taxonomic classes. If it does not accomplish these requirements and others (see ECHA [27]), a value of five is given to the AF. The usual requirements needed for chemical compounds are not always met by toxicological studies for MPs, in addition to uncertainties in these studies not covered by the AF. These can include; differences in the polymers used, MP morphologies, and MP sizes and colors used in the selected toxicological articles that may cause different toxic effects on the studied organisms [11].

As these articles are based on toxicological studies, the authors of this type of ERA may include articles in which the toxic effects are generated by different aspects of the MP. For example, by choosing studies where only MPs of a certain type or a certain size were used, the calculated PNEC value can be said to include type and size toxicology because both may trigger the toxic effects on which the PNEC was based. Therefore, the score given to the Refs. [13, 21] articles on the toxicology column displayed in the next section (**Table 2**), will range from 0 (when they did not screen any toxicological criteria) to 2 (when they screened specific toxicological criteria).

There are many loose ends in the development of ERAs with the SSD method. Some authors suggest addressing them with a probabilistic approach. For example, Koelmans et al. [28] proposed and tested a rescaling method to improve the alignment of SSD. Their objective was to englobe the diversity of MPs found in the environment via continuous probability density functions. They corrected the size ranges differences, developed a method to convert number to volume and mass concentration (or vice versa), and one to correct for differences in the MPs sizes, shapes, and densities. However, the authors conclude that their study will be more enriching when future experimental studies are developed with a higher level of quality in terms of sampling, laboratory control, and identification of MPs.

#### *3.1.4 Toxicity based on adsorbed pollutants*

One of the main worries of researchers around the world is the polymer's high sorption capacity toward hydrophobic organic contaminants (HOCs). MPs can

enhance HOCs transportation resulting in an extensive distribution of MP-associated chemicals entering every level of the food chain in the marine environment [19, 29]. Therefore, the study made by Chen et al. [22] is included in the present review, in order to consider this associated environmental risk.

The mentioned authors compared concentrations of dioxin-like polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyl (PCBs) extracted from micro/meso plastic debris from two plastic accumulation zones in marine environments with the effect concentration at which 10% of the species are affected EC10, or EC10 from chemicals with similar octanol-water partitioning constants (Kows) when the values were not available. They also reported variations in the concentration of these toxic compounds according to descriptive parameters including the type of polymer, form, size, adsorption capacity, and weathering. Therefore, their score on the toxicology column (where a point is given for each descriptive parameter) is the highest.

This is an unexplored way of performing risk analysis for MPs, but should be explored further, since as mentioned throughout the paper, MPs have different ways of being toxic.

### **3.2 Toxicology: results**

The following table shows the articles reviewed, the studied area, the methods each one used to perform their environmental risk analysis, their toxicology score explained before, and the results they obtained on their ERA.

The first thing to observe from **Table 2** is that the authors [14, 16–19] used the same basis (Eqs. (1)–(7)) or small variations of them (e.g., Picó et al. [16]). Therefore, they will be compared first.

The HI values vary a lot from study to study (as observed in **Figure 1**) and are difficult to compare since the polymer types detected in the study vary according to the sampling depth (surface, mid-level, or bottom), the waterbody, the degradation compound used, and the identification method. Though, Picó et al. [16] study has the highest HI value (see **Figure 1** and **Table 2**), which matches with also having the highest PLI value for Riyadh, it is important to mention that these are the result of a more conservative approach by the authors, intended by modifying Eq. (2).

The RI was only calculated in two articles, one of freshwater environment [18], and the other one on a marine environment [17]. Considering these differences, direct comparison (by recalculation) will not be performed for this index as it varies according to the type of polymers found in the area and the concentration (it will be recalculated for the PLI comparison below).

Another aspect to notice from **Table 2** is that [14, 16–19] studies could have been comparable if they have used the same Coi. Fortunately, most of them included sufficient data to calculate the indices with a modified and equal Coi value and be able to compare the results in the present review. The Coi that will be used to compare between surface or inland waters [16, 17, 19] will be 0.15 p/L since it is the lowest value measured in the three articles, and the modification made by Picó et al. [16] on Eq. (2) will be recalculated with the original equation to get an equivalent PLI. The Coi that will be used to compare marine environments will be 1 <sup>10</sup><sup>5</sup> p/L as it is the lowest concentration measured in the two articles [14, 17]. The reason that the lowest concentration values were chosen is that this approach intends to be a conservative risk estimation.

#### **Figure 1.**

*Hazard Indexes results from five different study areas.*

#### **Figure 2.**

*Original (blue) and modified (orange) PLI results for surface/inland water environments.*

**Figure 2** and **3** exhibit the original PLI values and the results of the modifications for surface or inland waters and marine environments respectively.

**Figure 2** indicates that with the modified Coi in the first two articles observed from left to right, the PLI value increased at least six times. While in the last article [16] (from where the Coi value was chosen) and the modification made to Eq. (2) the value decreased six times, indicating that their original approach was much more conservative than the others. The hazard level (HL) increased from I to III for Yin et al. [18], I to II for Refs. [18, 19], and from I to almost II for Wang et al. [19], while decreasing from II to I in the Riyadh artificial surface channel and remaining in I in the Al-Jubail artificial water pond [16] (consult Lithner et al. [8] for each HL definition).

The three study areas are Asian waterbodies [18, 19], and were both conducted in China and Picó et al. [16] in Saudi Arabia.

The highest PLI values are found on the Chagan Lake and the Xianghai reserve. This may be the result of them both being lentic ecosystems (a lake and a wetland) with no significant water flow, being accumulation systems in which the

*Microplastics Environmental Risk Assessment: A Review DOI: http://dx.doi.org/10.5772/intechopen.105162*

#### **Figure 3.**

*Original (blue) and modified (orange) PLI results for marine environments.*

concentration of perennial pollutants such as MPs will increase over time. The difference in the PLI values between the Chagan Lake and the Xianghai Nature Reserve can be explained by the fact that in the lake, tourism, and fishing (activities that generate MP pollution) are carried out, while in the natural reserve these activities are less common but occur. Overall, the results are consistent with the findings of previous papers that establish that the concentrations of MPs in China are the highest [29]. Sampling methods may influence the results, as the smallest MPs that they were able to sample are 1, 20, and 38 μm. However, there is no relationship between the lowest detection limit (1 μm) and the highest PLI value.

PLI hazard levels for freshwater (**Figure 2**) are much lower (maximum of III) compared to PLI values for marine environments (**Figure 3**). This is attributed to the low Coi used in the modified PLIs and the high concentrations of MPs found in Chinese estuarine or coastal environments.

Although Dongshan Bay has several sources of MPs, such as wastewater discharge, seawater farming, and a special semi-closed terrain, it has the lowest PLI modified value [17], which is also the same as the original value. This may be due to the sampling method they used (Manta Trawl with 330 μm of pore opening) versus the sampling method used by Xu et al. [14] (pump with a coupled mesh of 70 μm of pore opening), which results in smaller MPs being collected, thus a larger MP concentration. The modified Coi value may be sub-estimated too, as it is based on the Dongshan Bay study but may be used as a base for future ERAs.

In two of the remaining articles [13, 21] the authors performed the risk analysis based on an SSD explained previously in the document. The authors [21] were the first ones on estimating a risk analysis based on this statistical approach proposed by Everaert et al. [9] and comparing it with real measured data (MEC). While Jung et al. [13] used the same approach but limited their study to certain toxicological MP forms (fragment and fiber) and in the size range of 20–300 μm.

The article performed by Zhang et al. [21] (one of the first articles to perform SSD), did not include the confidence intervals (CI). Later, Jung et al. [13] argued that the screening they performed, accomplished a confidence interval reduction from 52 to 19, when they included the toxicity data for all types of MP for the SSD derivation, regardless of shape and size. They also mentioned that the articles made by Refs. [9, 11, 12] reported IC values greater than 100, proving that the limitation of certain

#### **Figure 4.** *The measured environmental concentration (MEC) and the risk quotient (RQ).*

shapes, colors, sizes, and types may improve the statistical reliability when deriving a PNEC value.

In **Figure 4** the values of the obtained MEC, the minimum and maximum RQ values measured on the study area can be observed, as well as the RQ safe limit (that is one), can be observed.

The observed differences between studies are related to differences in sampling sites and methodologies. The risk analysis by Jung et al. [13] was made on a marine environment, they based their SSD on chronic toxicity data of marine and freshwater species and limited their study to certain form and size of MPs. On the other side, the study by Zhang et al. [21] was performed on a river, based their statistical analysis on toxicity data of freshwater organisms, and did not screen any MP feature. Also although, Jung et al. [13] used a sampling method with a pore opening of 20 m and Zhang et al. [21] of 50 m, their MEC and RQ values are lower, which agrees with other studies that indicate that freshwater systems have higher MPs concentrations [30].

The approach taken by Jung et al. [13] is a good start to delimit statistical analyses and make their results more reliable. The selected PNEC to compare the RQ value (Eq. (9)) was the one obtained by Zhang et al. [21] in their SSD analysis. It was chosen since it was the lower of the two analyses (Jung et al. [13] obtained a value of 12) and as in previous comparisons, the lower concentrations are chosen to have a more conservative approach to this pollution problem.

The last study Chen et al. [29], used a very different approach than the others. Therefore, there will not be a comparison as such, but the results will be commented on.

The authors discovered that the DLCs adsorption on plastic particles is influenced by the coastal and oceanic regions, polymer types, aging effects but did not find a relationship between the size and the sorbed pollutants. For pollutants on unaged pellets, the concentration is lower than the EC10 thresholds, and dioxin-like effects may not occur (EC10 can replace the no observed effect concentration (NOEC)). However, for aged pellets and styrofoam PAHs and PCBs concentrations are higher than the EC10 on 11 out of 11 scenarios for aged pellets and on 2 out of 11 scenarios for styrofoam. In addition, dioxin-like effects are likely to occur once these MPs are exposed to marine organisms [29].

The toxicological score given to these three articles is 2 for Jung et al. [13], on which the toxicological studies were screened (form and size), therefore the ERA is developed from two distinct approaches; 0 for Zhang et al. [21] as they did the SSD without screening the toxicological studies, and 4.5 for Chen et al. [29] because they compared the toxic effects of the plastic particle type (0.5 because they only compared three types), weathering, size, form, and adsorbed pollutants.

When conducting ERAs, it is recommended that a standard Coi is used in addition to the baseline found in the study zone to be able to compare them with other risk analyses in different areas. The SSD can be improved by screening information, as mentioned above. Sampling, separation, and identification methods should also be reported to understand differences in results when these do not make sense to the naked eye as in the case of Dongsham Bay. For this reason, a score will be given to the experimental studies compared in this review.

#### **3.3 Concentration and quality assurance**

The scores observed in **Table 4** are based on the criteria explained in **Table 1**. It is important to highlight that in **Table 2**, Wang et al. [19] has the highest scores, while one of the lowest in **Table 4**. In the quality assurance section, specifically in the sampling section no date, coordinates, surface depth, sample size, processing, and storage data are specified. In the laboratory preparation, no clean air specifications, sample treatment, positive nor negative controls are specified. It is essential to meet all the criteria listed in **Table 1** or at least report whether they were considered or why they could not be met.

The highest score is accomplished by Chen et al. [22], they reached the highest punctuation of the concentration section, as they reported and did every criterion. Unlike the quality section, in which they did not achieve the points for the minimum sample size criterion of 500 L, they did perform a negative control but without triplicate, and like all the other articles they did not report a positive control (see Koelmans et al. [6]).

Only Pan et al. [17] had the two points that represented a sampling size higher than 500 L, as they used a special-made manta trawl net, and other authors used sampling containers or pumps. This can be also related to their low MP concentration reported, as the nets pore opening is of 300 μm, which might allow from MPs below 300 μm to not be accounted for.

The LOD criterion was one of the least accomplished, although each step of the experimentation should have detection limits in terms of size, type, and shape of the


**Table 4.**

*Toxicology score, concentration score, and quality assurance (QA) score for the reviewed articles.*

polymer. For example, if the surface of a waterbody is sampled, it is likely that only polymers with a certain density are being recovered because more dense polymers are usually found at the bottom. The problems arising from density difference also apply to density separation. In addition, in the stereoscopic visualization step, certain colors, and sizes may not be clearly visible. Finally, in the detection step, the micro-Raman is known to be sensitive to fluorescence so it may miss certain colors of MPs [30].

In any case, it is important to use reviews and articles already published to identify these detection limits and report them in any experimental work. Especially if a risk analysis is to be done, in which the study will likely be compared with others where different methods are used.
