1. Introduction
Release of engineered nanomaterials (ENM) into the natural environment is expected to happen both unintentionally and intentionally throughout the lifecycle of nanomaterial manufacturing, use and disposal [
1,
2]. This release can originate from discharges from wastewater treatment plants, landfills and waste incineration plants, all of which are likely to receive ENM from nano-enabled products disposed at the end of their life phase, from accidental spills during production or transport of nanomaterials or from releases during use [
3]. Presently, the knowledge on the environmental release and exposure of ENM in the environment is limited. A recent study [
4] collected and critically reviewed a dozen studies that modeled environmental concentrations for several ENM (
i.e., TiO
2, Ag, ZnO, CNT, fullerenes and CeO
2). Significant knowledge gaps are related to difficulties in estimating ENM production and distribution to products, resulting in an uncertain assessment of release of ENM. Mueller and Nowack [
5] published the first ENM material flow modeling study, providing scenario-based results for nano-Ag, nano-TiO
2 and CNT in natural waters, soils and air. The lifecycle-based methodology was later improved by a stochastic and probabilistic methodology [
6] that was used to predict probability distributions of mass flows and exposure concentrations for several ENMs (Ag, ZnO, TiO
2, fullerenes and CNT) in all important environmental compartments such as surface waters, sediments, soils, sewage sludge, sludge-treated soils and air [
7]. An updated modeling using newest data on production, use and fate was recently published [
8].
Also other models have been applied to model ENM concentrations, some based on simple algorithms [
9], on particle flow analysis [
10], some just considering a few nano-applications [
11,
12]. Keller et al. [
13] have modeled the flows of ten nanomaterials on a global scale. First attempts have also been made to couple the material flow models with a description of the environmental fate of the particles, obtaining a more accurate estimate of environmental concentrations in surface waters [
14,
15,
16].
The models mentioned above provide average flows and concentrations in standard environmental compartments on a large scale. Some regionalization has been considered, for example by comparing flows in the EU, the US and Switzerland [
7], or by single assessments in specific countries, e.g., Ireland [
11]. However, due to different model assumptions on production, use and fate, results in different regions using different approaches should not be compared. [
17] provide estimates for different regions, based on their global evaluation [
13]. The considered regions span the range from very large, e.g., Europe, Asia, to State-wide results in the U.S. to local assessment in one water body. However, the main variable that was used is a
per capita use and release of ENM. A similar approach has previously been used to provide concentrations at high spatial resolution in a river network [
18]. An important aspect in the regionalization of exposure data is that wastewater and solid waste handling is very different in different countries. Whereas some countries landfill all their waste, others use almost exclusively incineration. Also the connection rate to centralized wastewater treatment varies considerably from country to country. Because ENM are known to end up mostly in wastewater and solid waste, a detailed evaluation of these systems in a region is important for an accurate prediction of flows and concentrations.
The current paper provides such a detailed evaluation of ENM flows in Denmark. The modeling considered nine nanomaterials. The model for Switzerland [
8] served as main data basis for nano-TiO
2, Ag, ZnO and CNT by expanding and adjusting input parameter data to the specific situation in Denmark. This involved mainly the handling of wastewater and waste, the per-capita release of ENM but also the geography and volumes of all environmental compartments. The modeling however distinguishes the first time TiO
2, separately in photostable as well as in photocatalytic form and follows recent nanomaterial fate analysis in waste incineration processes [
19]. In addition, this study presents for the first time marine water and sediment exposure results. Additionally, this work provides the first environmental flows and concentrations for quantum dots, carbon black and CuCO
3 used in wood coatings and provides the first probability distributions for CeO
2. This paper is based on a detailed report published by the Danish Environmental Protection Agency [
20].
3. Results
3.1. Material Flows
The material flow diagrams of the nine ENM are shown in
Figure 2. In all schemes the flows go from the production/manufacturing/consumption compartment in the bottom left corner to the technical compartments in the middle and then to the environmental compartments on the right. The most important photostable nano-TiO
2 and nano-ZnO flows go to wastewater due to the prevalent use in cosmetics. Most photocatalytic nano-TiO
2 finally ends up in recycling and landfills. CNTs show a high mass fraction (up to 90%–95%) ending up in recycling, waste incineration and landfilling processes. Only a marginal environmental release of CNT to both aquatic and terrestrial environments is predicted. Also for nano-CuCO
3 the main flow is finally to landfills but also direct emission to soils is relevant. The use in wood impregnation strongly leads to a high mass transfer into waste flows with discarded wood (waste incineration, recycling and landfilling). The greatest portion of nano-CuCO
3 environmental release (approx. 98%) is direct release from the impregnated wood into soils. This discharge occurs via wood-soil contact of those woods under the ground, as well as from leaching processes. The results from the material flow modeling for nano-CeO
2 gave mass flows into the natural environment which do not exceed half a ton per year. The environmental release mostly occurred via STP sludge application on soils and by limited air emissions. For both nano-Ag and QD only very small flows are predicted, with almost no environmental release for QD and some limited transfer to wastewater for nano-Ag. The carbon black model shows the highest exposure results in this work for all natural compartments. We modeled much higher use volumes (kt per year levels instead of t per year as for the other materials). Because CB is mainly used in rubber, significant release due to material degradation processes (wear and tear) is possible, especially in uses in the environment (tires). However, our model assumed that the whole released fraction of CB would occur as nanoscaled material. These model conditions certainly represent a conservative exposure assessment.
Figure 3 presents an overview of the most important sources for environmental release and the primary recipients for the nine covered ENMs. For nano-TiO
2 STP sludge is the main source, with the wastewater effluent as secondary. For other ENM such as ZnO, Ag, CeO
2 and especially CNT and CuCO
3, the main source for environmental release is direct release from production/ manufacturing/use. This is because for these materials the major flows after use end up in landfill and WIP where either no release was modeled (landfill) or release is considered to be very low (WIP) [
19,
25].
The main primary receiving environmental compartment is for most ENM the soil, mainly via application of sludge. Only for ZnO and Ag freshwater is also important because of the almost complete transformation of both compounds during wastewater treatment almost no release occurs with wastewater. Also for CB the aqueous compartments are important due to a completely different release mechanism, the abrasion of tires and direct transfer to the environment.
3.2. Concentrations in the Technical System
The concentration values for all technical compartments that were modeled in this work are given in
Table 2. These are on the one hand sewage treatment effluent and sewage sludge, on the other hand the solid waste streams solid waste, bottom ash and fly ash. The STP effluents showed the highest concentrations of photostable TiO
2 of a few to almost 100 µg/L (modal value around 13 µg/L). For photocatalytic nano-TiO
2 the concentrations are about a factor of 10 smaller. CuCO
3 is modeled to be present in wastewater at a similar level than photocatalytic TiO
2 whereas CB has potential concentrations in the mg/L range. Ag, CNT and CeO
2 have only concentrations in wastewater in the low ng/L range, QD have as maximal value a pg/L. In the solid waste materials concentrations in the mg/kg range can be expected for TiO
2, ZnO, CuCO
3 and CB. The other materials are present in the low µg/kg range.
Figure 2.
Mass flow diagrams for nine nanomaterials in Denmark. Rounded modal values are shown in tons/year (except CB where the unit is kt/y). Boxes show accumulation or transformation. The modes, combining all the Monte Carlo simulations show what has to be most likely expected at each place of the figure without necessarily reflecting in detail and holistically mass balance of the flow system. CNT: Carbon nanotubes; QD: Quantum dots; CB: Carbon Black.
Figure 2.
Mass flow diagrams for nine nanomaterials in Denmark. Rounded modal values are shown in tons/year (except CB where the unit is kt/y). Boxes show accumulation or transformation. The modes, combining all the Monte Carlo simulations show what has to be most likely expected at each place of the figure without necessarily reflecting in detail and holistically mass balance of the flow system. CNT: Carbon nanotubes; QD: Quantum dots; CB: Carbon Black.
Figure 3.
Overview of the most important ENM sources and receivers. The percentages show the most frequently modeled results (modal values).
Figure 3.
Overview of the most important ENM sources and receivers. The percentages show the most frequently modeled results (modal values).
Table 2.
Concentration of the nine nanomaterials in natural and technical compartments. Mode value and 95% interval are shown, all rounded to two significant numbers. The values for environmental sinks (soils, sediment) represent masses in 2014 accumulated since the year 2000.
Table 2.
Concentration of the nine nanomaterials in natural and technical compartments. Mode value and 95% interval are shown, all rounded to two significant numbers. The values for environmental sinks (soils, sediment) represent masses in 2014 accumulated since the year 2000.
Compartment | Unit | Photostable TiO2 | Photocatalytic TiO2 | ZnO | CuCO3 |
---|
Mode | Range | Mode | Range | Mode | Range | Mode | Range |
---|
Technical compartments | | | | | | | | | |
Sewage treatment effluent | µg/L | 13 | 3.4–92 | 1.6 | 0.4–14 | 0 | | 1.3 | 0.3–4.1 |
Sewage treatment sludge | mg/kg | 770 | 69–1500 | 85 | 9.3–230 | 0 | | 9.1 | 5.2–17 |
Waste mass incinerated | mg/kg | 15 | 1.4–32 | 2.8 | 0.3–6.8 | 0.3 | 0.04–1.5 | 2 | 1.3–3 |
Bottom ash | mg/kg | 33 | 3.4–88 | 6 | 0.7–18 | 0.7 | 0.1–3.9 | 4.4 | 2.7–8.5 |
Fly ash | mg/kg | 170 | 17–430 | 30 | 3.3–90 | 3.6 | 0.5–19 | 22 | 13–42 |
Natural compartments | | | | | | | | | |
Surface water (fresh water) | ng/L | 3 | 0.6–100 | 0.27 | 0.05–7 | 0.45 | 0.09–13 | 2 | 0.1–6 |
Sea water | ng/L | 0.30 | 0.04–1 | 0.02 | 0.004–0.099 | 0.04 | 0.006–0.4 | 0.04 | 0.02–0.07 |
Sediments (fresh water) | µg/kg | 1200 | 200–28,000 | 92 | 17–2600 | 160 | 30–4800 | 880 | 43–2100 |
Sediments (sea water) | µg/kg | 390 | 49–1300 | 27 | 4.3–120 | 49 | 6–220 | 42 | 25–83 |
Agricultural soils | µg/kg | 0.085 | 0.01–0.39 | 0.7 | 0.1–1.7 | 0.052 | 0.008–0.35 | 28 | 18–41 |
Natural soils | µg/kg | 0.18 | 0.024–1.1 | 1.5 | 0.2–4.9 | 0.12 | 0.018–0.9 | 60 | 39–130 |
Urban soils | µg/kg | 0.33 | 0.039–1.5 | 2.7 | 0.3–6.7 | 0.2 | 0.03–1.3 | 110 | 70–160 |
Sludge treated soils | µg/kg | 1300 | 130–3100 | 170 | 17–480 | 0 | 0 | 48 | 32–70 |
Air | ng/m3 | 0.10 | 0.01–0.5 | 0.70 | 0.08–2 | 0.04 | 0.005–0.2 | 0.02 | 0.005–0.04 |
| Unit | Ag | CNT | CeO2 | QD |
| Mode | Range | Mode | Range | Mode | Range | Mode | Range |
Technical compartments | | | | | | | | | |
Sewage treatment effluent | ng/L | 0.5 | 0.012–59 | 0.3 | 0.1–3.5 | 9.3 | 1.1–60 | 3.00E−05 | 5E−6–0.001 |
Sewage treatment sludge | µg/kg | 82 | 4.2–250 | 7.6 | 2.7–62 | 350 | 44–2300 | 2.40E−04 | 4E−5–0.003 |
Waste mass incinerated | µg/kg | 15 | 10–23 | 800 | 440–1300 | 180 | 21–930 | 0.9 | 0.1–4.4 |
Bottom ash | µg/kg | 35 | 21–66 | 76 | 27–710 | 360 | 50–2500 | 2.2 | 0.2–11 |
Fly ash | µg/kg | 170 | 100–330 | 330 | 88–4800 | 2200 | 240–12,000 | 10 | 1–57 |
Natural compartments | | | | | | | | | |
Surface water (fresh water) | pg/L | 15 | 0–44 | 1 | 0.2–15 | 4 | 0.6–100 | below fg/L | |
Sea water | pg/L | 0.25 | 0–0.6 | 0.05 | 0.02–0.2 | 0.3 | 0.03–2 | below fg/L | |
Sediments (fresh water) | µg/kg | 5.4 | 0–16 | 0.5 | 0.1–5.6 | 1.6 | 0.2–45 | 1.6 | 0.2–45 |
Sediments (sea water) | µg/kg | 0.3 | 0–0.7 | 0.1 | 0–0.2 | 0.3 | 0.04–2 | 0.3 | 0.04–2 |
Agricultural soils | ng/kg | 10 | 6–21 | 35 | 18–75 | 76 | 10–530 | nq | |
Natural soils | ng/kg | 24 | 13–61 | 83 | 41–220 | 170 | 24–1500 | nq | |
Urban soils | ng/kg | 40 | 23–81 | 130 | 71–290 | 300 | 39–2100 | nq | |
Sludge treated soils | ng/kg | 170 | 20–530 | 60 | 30–180 | 1500 | 94–5100 | 0.001 | 1E−4–0.013 |
Air | ng/m3 | 0.007 | 0.004–0.011 | 0.042 | 0.022–0.091 | 0.1 | 0.01–0.6 | nq | |
Compartment | Unit | CB | | | |
Mode | Range | | | | | | |
Technical compartments | | | | | | | | | |
Sewage treatment effluent | mg/L | 1.2 | 0.29–3.9 | | | | | | |
Sewage treatment sludge | mg/kg | 2500 | 580–7700 | | | | | | |
Waste mass incinerated | mg/kg | 1400 | 660–2500 | | | | | | |
Bottom ash | mg/kg | 140 | 44–1300 | | | | | | |
Fly ash | mg/kg | 540 | 150–8600 | | | | | | |
Natural compartments | | | | | | | | | |
Surface water (fresh water) | µg/L | 0.5 | 0.1–6 | | | | | | |
Sea water | µg/L | 0.034 | 0.015–0.08 | | | | | | |
Sediments (fresh water) | mg/kg | 730 | 36–2200 | | | | | | |
Sediments (sea water) | mg/kg | 41 | 18–97 | | | | | | |
Agricultural soils | mg/kg | 0.7 | 0.3–1.3 | | | | | | |
Natural soils | mg/kg | 1.5 | 0.7–3.9 | | | | | | |
Urban soils | mg/kg | 2.6 | 1.2–5.2 | | | | | | |
Sludge treated soils | mg/kg | 5 | 1.6–17 | | | | | | |
Air | µg/m3 | 0.2 | 0.1–0.3 | | | | | | |
3.3. Concentrations in Environmental Compartments
All air concentrations were marginal for the studied ENMs, and showed values in the range of pg/m3. This mostly reflected very small direct emissions from nanoproduct uses and almost complete removal during waste incineration.
The fresh water photostable nano-TiO2 concentrations reached at most 0.1 µg/L while those for seawater were at pg/L concentrations. Soils and sediments were the most significant nano-TiO2 sinks, with most likely concentrations for 2014 of 1.3 mg/kg in sludge treated soils and a few tenths of µg/kg in non-sludge-based fertilized soils. In sediments (fresh water and marine water), 1.2 and 0.39 mg/kg were modeled.
The photocatalytic nano-TiO2 flow to surface water did only add about one-tenth to the total nano-TiO2 flow. The concentrations in surface waters were at most in the ng/L range. Therefore, depending on the various types of ENM applications, the nano-TiO2 aquatic relevancy may vary considerably. In the context of risk assessment and toxicology studies, it will be crucial to distinguish these two material categories in the future. Relatively small PECs have been modeled for sediments, and concentrations of approximately 90 µg/kg (freshwater sediment) and 30 µg/kg (seawater sediment) are predicted for 2014. In soils receiving STP sludge, we modeled about 170 µg/kg for 2014.
For nano-ZnO we did not model any significant concentrations, neither in waters nor in soils. The freshwater PECs were mainly in the range of pg/L to a few ng/L, originating from direct release or untreated wastewater; the marine water PECs were by a factor 10 smaller, and all were at pg/L concentrations. Soils and sediments represented the final sinks for nano-ZnO; however, they receive very low quantities. In 2014, around 200 ng/kg are expected in soils, and a few hundred µg/kg in sediments.
The nano-Ag concentrations in freshwater and seawater are at the level of pg/L. Because nano-Ag was almost completely transformed into other chemical forms during wastewater treatment, the soil concentrations were also very low.
CNT concentrations in natural waters only reached pg/L levels; in marine water some fg/L concentrations. We do not expect more than a few µg/kg in freshwater sediments in 2014, also the concentrations in soils is not be above a few dozen ng/kg in that year.
The most likely concentrations of CuCO3 are a few ng/L in freshwater and pg/L levels in marine waters. In soils values up to approximately 100 µg/kg of soil could be expected. However, these values reflect our worst-case exposure model, which assumed a significant use of nano-CuCO3 in wood impregnation.
The nano-CeO2 freshwater and marine water concentrations were at pg/L levels. Concentrations of a few hundred ng/kg are expected in soils, a few µg/kg in STP-sludge-treated soils.
The modeled environmental concentrations of QD in surface waters were so small that a detailed evaluation of their probability distributions was not conducted. The results mostly reflected numbers lower than some fg/L. A few µg/kg are expected in freshwater sediments in 2014 and even lower values for marine sediments.
The CB results in this study are the highest for all natural compartments caused by the much higher use and release amounts (kt per year levels instead of t per year). Since CB is mainly used in rubber, significant release due to wear and tear can be expected. As a conservative approach our model assumed that all the released CB is present as nanosized material. Insofar, the actual nanoparticulate CB exposure concentrations would be expected to be much lower. Less than a µg/L are expected in natural waters, a few mg/kg in soils, mainly due to diffuse input.
4. Discussion
Most of the modeled ENM have only a small annual discharge into the natural environment. In most cases (e.g., nano-Ag, CNT, nano-CeO
2, QD) the flows do not even reach ton per year levels. These results about the total flows to the environment are in line with other European results [
7,
8]. Notable environmental release and exposure has been found for photostable nano-TiO
2 and CB in the aquatic and terrestrial environment as well as for nano-CuCO
3 in soils. This is on the one hand caused by relatively high production amounts for these materials but on the other hand also by their use in products with significant release. In addition there is a lack of transformation reactions for these materials. Transformation reactions are on the other hand very important for ZnO and Ag. For both materials it has been shown that wastewater treatment can efficiently remove them and also transforms them into the respective sulfide forms [
26,
27,
28]. This results in almost zero flows of the parent ENM into the environment through wastewater. Because our modeling is specific for the ENM and does not track the total mass, loss of the nano-form or the parent material constitutes an elimination in our modeling. The flows and concentrations of the ENMs therefore need to be compared to the total flows of the respective metal, e.g., total Zn or Ag [
4]. These flows are many orders of magnitude larger and a transformation of a nanoparticle into another form is therefore not significantly increasing the total flow of the respective metal. Also for nano-CuCO
3 we need to consider transformation reactions because it is relatively soluble depending on the pH and the presence of ions such as carbonate. However, due to the lack of data for this specific material we did not take into account any transformation reactions in our model. The nano-CuCO
3 concentrations therefore represent a worst-case scenario that is very likely an overestimate. However, the model for nano-CuCO
3 is also different to the others in that it represents a future scenario under the assumption of wide-spread use of nano-CuCO
3 in wood protection and does not constitute realistic current flows and concentrations as for all the other materials.
Photocatalytic nano-TiO
2 has about a factor of 10 smaller concentrations that photostable nano-TiO
2, a fact that is very important for the environmental risk assessment of nano-TiO
2. A recent study that quantified the environmental risks of ENM found that nano-TiO
2 has one of the highest probabilities for environmental risks [
29]. This is mainly due to some ecotoxicological studies with photocatalytic TiO
2 in the presence of UV light that result in very low effect concentrations. Using separate exposure concentrations and different evaluations of the ecotoxicological literature is therefore clearly needed because both forms have very different effects and using a “generic TiO
2” model is clearly overestimating the possible risks because the more toxic photocatalytic form has lower exposure concentrations than the photostable TiO
2 used in sunscreens.
In our work we also modeled for the first time QD concentrations. Due to the very low production volume and the use in products with limited release during use, the environmental exposure concentrations are extremely small. Given the fact that many QDs are prone to dissolution under natural conditions [
30,
31], their actual concentrations will be even lower.
The new data for CeO
2 and CuCO
3 can be compared to the results reported by [
16] who predicted their concentrations using a simple material flow model. For CeO
2 concentrations in water between 1 and 10 µg/L were predicted, for Cu between 0.02 and 0.1 µg/L. In sediments the values from that study were around 100 µg/kg for CeO
2 and 5 µg/kg for Cu. However, it has to be noted that no ranges were given in that study and only single values are reported. The values for CeO
2 are orders of magnitude larger than what we modeled in our study. Reference [
17] provided data for STP effluents for these ENM and reported for San Francisco Bay between 0.02 and 1 µg/L CeO
2 and 0.001 to 0.01 µg/L for Cu. Our modeled range for CeO
2 is 1–60 ng/L and 0.3–4.1 µg/L for CuCO
3, therefore within the range given by [
13], for CeO
2 and above for CuCO
3. However, also their work does not incorporate any uncertainty with respect to production, use and behavior and the ENM flows that form the basis of the concentration calculation are point values and not ranges. Concentrations for materials with such limited knowledge on production, use and fate as CeO
2 and CuCO
3 derived by different models define therefore a range of possible concentrations values.
Knowledge about sedimentation is significant for computing the residence time of the nanomaterials in water, as well as their subsequent transfer into sediments. This affects both the water as well as the sediment concentrations. One limit of our model was that we assumed that the probability of the transfer factor from water to sediment was spread out over the total possible spectrum from complete sedimentation to no sedimentation at all. Depending on the type of ENM, its coating and functionalization and the water chemistry, the stability of ENM in natural waters can vary greatly [
32,
33]. A coupling of mass flow models with geographically explicit fate modeling of different water bodies is needed to allow an accurate description of aggregation and sedimentation of ENM in natural waters such as presented in [
14].
For all ENM we not only provide concentrations in environmental compartments but also in technical compartments such as wastewater, sewage sludge, solid waste, slag and ash from waste incineration. As a large fraction of the total ENM flows end up for many ENM in landfills receiving either directly solid waste or incineration residues [
34,
35,
36], providing data on these materials is important for the current discussion on the nano-relevance of waste. Walser & Gottschalk [
19] recently confirmed that for inert metals such as nano-CeO
2 waste incineration plant processes cannot be seen as a nanomaterial end of life treatment procedures but rather as nanomaterial sources for fly ash and slag that may end up in recycling (and landfills). Depending on the type of ENM, also the flows into recycling are important. These release from recycling operations was not further modeled in this work but recently an evaluation of ENM-flows after recycling has been published [
37]. These authors have shown that the main ENM flows after recycling go to landfill and waste incineration. Our model did also not take into account possible release from landfills. For Danish standards of those infrastructures, these seem to be a realistic model assumptions but future research has to investigate the potential for the presence of ENM in landfill leachates and the further dissipation.
Although our model clearly reveals the concentration range that can be expected (as 95% interval), we have to explicitly emphasize the limitations in interpreting the model outcomes. The expected future exposures may be considerably higher if production and use of the investigated ENM increases. The increased electrification of mobility could lead to much higher use increase of ENM, for example in batteries (e.g., QD and CNT). The future expectations for CNTs are large and are anticipated in a broad field of applications (consumer electronics, textiles, polymer composites, etc.); however, currently a wide-spread commercially significant use volumes do not seem to be observed. A potential complete market penetration of the use of nano-CuCO3 in wood treatment, or nanosized CeO2 as a fuel additive, may lead to scenarios with high environmental relevance. More information with respect to volumes of nanomaterial production and use on the part of industry would help considerably in making the exposure modeling more precise. As long as the companies are reluctant to provide the current (and anticipated) quantities of ENM produced and used, the exposure modeling cannot be improved. Because currently good production data are lacking, a forecast of ENM flows and concentrations remains attached with high uncertainties and models needs to incorporate them. Hence, there is a need for a better understanding and more empirical data for the ENM use in different countries and economies, and this by far represents the most important factor necessary for the updating of the environmental exposure assessment of nanomaterials.
Compared to previous published studies with a comprehensive set of ENM that are currently on the market such as published by [
13] and [
16], our work presents a much more exhaustive list of concentrations in both technical and natural environments and as such the new values are of invaluable help for ecotoxicologists that need knowledge on realistic exposure concentrations for these ENMs. These data are needed both for the design of experiments as well as for critical evaluations of published effect data. Also for analytical chemists these data are very useful because they indicate the range of expected concentrations that new methods need to be able to detect in different media.
Concluding, one must underline that we are still faced with distinct difficulties regarding the secure validation of all kinds of predicted exposure results for ENM. This will not change as long as trace analytical approaches are not applicable for the pollutant quantification and detection at trace levels of nanomaterials. Recent reviews [
4,
38] evaluated all available modelling and analytical contributions that provide concentrations and found at several occasions accordance between models and measurements. The differences found cover besides the mentioned analytical shortcomings difficulties in the distinction between nanomaterial of anthropogenic and natural origin as well as the limited or very crude consideration in the models of the nanomaterial fate in the environment. However, as far as the whole possible range of events for such nanomaterial fate is considered, the large spectrum models do not miss any significant events. Thus, several recent modelling studies [
7,
13,
16] were seen to correlate well for concentrations ranging from water (surface water and sewage treatment effluents) to solid media (soils, biosolids, sediments) [
38]. Furthermore, Sun
et al. [
8] showed in a TiO
2 case study that the probabilistic/stochastic mass balance approach may be used also for predictions of the bulk material of this compound that may be documented and confirmed by measurements. Finally, these stochastic mass balance studies do not promise any unrealistic precision in the results but allow us to consider the entire currently conceivable model input and output spectrum. Hence, we do not have to validate the well established mass balance principles, but must rather ensure that we have at our disposal more and better parameter data.