ABSTRACT
The proliferation of metal-based nanoparticles in treated municipal wastewater (TWW) has raised environmental and health concerns. This study examined the health risks and effects of ZnO nanoparticles (NPs) in TWW on rice growth, yield, and nutrition. Continuous fertigation was used to irrigate rice plants with TWW containing 0, 2, and 5 mg L−1 of either ZnO NPs or ZnSO4. Results indicated that TWW with higher ZnO NP concentrations significantly reduced plant height and root mass but increased shoot biomass and rice yield. ZnO NPs or ZnSO4 exposure increased Zn accumulation in rice roots, shoots, and grains while reducing Cd levels by 30%. However, elevated Zn levels also increased toxic metal accumulation, such as As and Mo. The estimated daily intake values for As, Zn, and Mo increased by over 100, 29–47, and 14–18%, respectively, raising cumulative health risks from trace element exposure, with hazard index (HI) values exceeding the safe threshold (HI > 1). Despite no acute toxicity in rice plants, the continuous use of ZnO NP-contaminated TWW presents significant long-term environmental and health risks. This highlights the urgent need for stringent monitoring and management of TWW quality to safeguard the sustainability of agricultural wastewater reuse.
HIGHLIGHTS
ZnO nanoparticles (NPs) reduce plant height and root mass yet paradoxically increase shoot biomass and rice yield.
ZnO NPs decrease Cd accumulation but increase As contents in rice grains.
Elevated levels of ZnO NPs in treated wastewater significantly heighten health risks via rice consumption.
Strict regulations on NP levels in wastewater are essential to ensuring agricultural safety and sustainability.
INTRODUCTION
Metal-based nanoparticles (MNPs), including zinc oxide nanoparticles (ZnO NPs), are increasingly detected in various environmental settings due to their extensive applications across industries such as biomedicine, agriculture, electronics, and cosmetics (Wu et al. 2019; Singh & Kumar 2020; Nagar et al. 2022; Phung et al. 2022; Asif et al. 2023). Their entrance into aquatic and terrestrial ecosystems, often through applying nano-fertilizers and recycling sewage sludge and wastewater in agriculture, highlights their pervasive influence (Nemček et al. 2020; Shahane & Kumar 2022; Phung et al. 2022, 2023, 2024; Sharma et al. 2023). The resilience and mobility of these nanoparticles (NPs) necessitate ongoing research into their fate, integration into the food chain, and overall impacts on ecosystem health and human safety (Peng et al. 2017; Wu et al. 2019; Phung et al. 2022, 2023, 2024; Wang et al. 2022; Hsieh et al. 2023).
While environmental pollution encompasses a wide range of contaminants, including heavy metals and emerging organic pollutants like nitrosamines, information about their specific impacts on downstream receiving waters and other environmental matrices is limited (Zhao et al. 2021). Recent studies highlighted the increasing complexities of managing such contaminants as well as their behavior of soluble and particulate pollutants in increasingly dynamic urban water management (Zhao et al. 2022, 2021). ZnO NPs are particularly noteworthy due to their high usage volume and resultant widespread presence in the environment (Wu et al. 2019; Nagar et al. 2022; Asif et al. 2023). These NPs are frequently detected in environmental samples, with concentrations ranging from 0.05 to 76 μg L−1 in surface waters and occasionally up to 0.28 μg L−1 in tap water, underscoring their ubiquitous presence (Kirkegaard et al. 2015; Hsieh et al. 2023). At a municipal wastewater treatment plant (WWTP) in California, influent concentrations were reported at about 1600 ng L−1, although significantly reduced levels were noted in the treated effluent (Cervantes-Avilés & Keller 2021). These levels are lower than those measured in other regions (Baranidharan & Kumar 2018; Westerhoff et al. 2018). Despite these relatively low environmental concentrations posing limited immediate risks, the potential for long-term effects and bioaccumulation in agricultural ecosystems remains a substantial concern (Giovanni et al. 2015; Liu et al. 2018; Nagar et al. 2022; Sharma et al. 2023).
The strategic reuse of treated municipal wastewater (TWW) for crop irrigation promotes sustainable water management and minimizes reliance on synthetic fertilizers, fostering a circular economy (Tran et al. 2019; Phung et al. 2020; Ouoba et al. 2022). However, the introduction of ZnO NPs through TWW presents new challenges, particularly with the potential for increased NP concentrations from industrial discharges, which could negatively impact soil health, crop productivity, and food safety (Liu et al. 2018; Singh & Kumar 2020; Phung et al. 2022). Understanding the behavior of ZnO NPs in TWW and their impacts on crop-soil systems, especially at exposure levels relevant throughout a crop's full lifecycle, remain underexplored (Faizan et al. 2020; Wang et al. 2022). While prior studies have often investigated the effects of high concentrations of ZnO NPs on paddy rice, their environmental relevance is limited by unrealistic high dosages (10–1,000 mg L−1) and brief exposure durations (Phung et al. 2022; Wang et al. 2022).
This study, therefore, aims to investigate the effects of ZnO NPs in TWW on rice yield, grain nutrient composition, and potential health hazards associated with continuous irrigation using TWW. Rice was selected due to its global dietary importance and common cultivation with wastewater, making it an ideal model for studying contaminant uptake and assessing environmental and health impacts at realistic exposure levels (Phung et al. 2022; Wang et al. 2022). By comparing commercially available ZnO NPs with ionic zinc from ZnSO4, this study evaluates the differential impacts of NP and dissolved zinc forms on rice–soil systems. Moreover, it scrutinizes the adequacy of current effluent standards, setting total Zn concentrations at 2 and 5 mg L−1, levels typical of high-end exposure scenarios encountered globally in TWW (ISO 2020), ensuring compliance with the United States Environmental Protection Agency's Effluent Guidelines (EPA 2014), thereby providing a comprehensive assessment of the potential impacts of ZnO NPs on agricultural and environmental safety.
MATERIALS AND METHODS
Materials
Zinc oxide NPs (CAS number 1314-13-2) and zinc sulfate heptahydrate (ZnSO4·7H2O, CAS number 7446-20-0) were obtained from Sigma-Aldrich Japan G.K. (Tokyo, Japan). The ZnO NP powder had a particle size smaller than 50 nm and a surface area of approximately 11 m2 g−1. Zinc sulfate served as a source of Zn ions and had a purity of more than 97%. This study employed TWW collected weekly from a WWTP located in Tsuruoka City, Yamagata, Japan (38°45′28.6″N 139°50′49.1″E). This WWTP utilizes a conventional activated sludge system, which, while not specifically designed to target the removal of MNPs, effectively reduces the concentrations of heavy metals in the effluents (Phung et al. 2020; 2022). The TWW used in this experiment has been previously tested and confirmed to be free from toxic metals such as Hg and Pb (Phung et al. 2022), ensuring its suitability for agricultural irrigation and aligning with current environmental safety and public health regulations (ISO 2020). Its characteristics are documented in Table S1. The rice seedlings (Oryza sativa L., cv. Bekoaoba) were acquired from Yamagata University's Experimental Farm. The experimental soil used in this study was characterized as sandy loam soil and collected from a nearby paddy field. It had a pH of 5.7 and an electrical conductivity (EC) of 2.0 dS m−1 and contained 24, 2.6, 1.2, and 1.5 g kg−1 of total C, N, P, and K, respectively.
Experimental conditions and treatment design
Research flow chart (a) and illustration of an experimental pot under CSI with TWW (b).
Research flow chart (a) and illustration of an experimental pot under CSI with TWW (b).
To elucidate the different effects of Zn in NP versus ionic forms, ZnSO4 was used as a comparative baseline of Zn ions, which allows for an in-depth exploration of the unique behaviors and impacts of ZnO NPs in the rice–soil systems. This was done to distinguish the effects of physical NP presence from the biochemical activity of dissolved Zn ions. ZnSO4 was dissolved in TWW at concentrations identical to those of ZnO NPs to ensure the comparability of ion availability. Particularly, ZnO NPs and ZnSO4 were introduced into TWW to reach total Zn concentrations of 2 and 5 mg Zn L−1, which aligned the recommended Zn limit in reclaimed water used for long-term irrigation (FAO 2003) and the effluent standard (EPA 2014), respectively. These concentrations were labeled as 2NP, 5NP, 2S, and 5S, respectively. An ultrasonic bath (100 W, 30 kHz) was used for 45 min to disperse the NPs in the influent tanks. A control group employed TWW without the addition of external Zn sources. The five treatments were replicated three times using a completely randomized approach.
Characterization of ZnO NPs and ZnSO4 in TWW
According to the methodology described by Phung et al. (2022), the concentrations of dissolved Zn ions in the irrigation TWW were determined. Briefly, the samples of the prepared irrigation TWW were subjected to centrifugation at a speed of 11,500 rpm and a temperature of 4 °C for 40 min. The supernatant was then passed through a 0.02 μm syringe filter (Whatman Anotop 25 6809-2002) (Ye et al. 2018). The total Zn concentration of the filtrates was determined using a portable colorimeter (HACH DR/890 Portable Colorimeter, HACH, USA), following the Zincon Method as modified from established water testing protocols (APHA 2017). The Zn ion concentrations released by the exogenous ZnO NPs or ZnSO4 were calculated by subtracting the total Zn concentrations in the irrigation solutions from those in the original TWW (Phung et al. 2022).
Assessment of rice growth, yield, and nutritional quality
Monitoring plant growth involved counting tillers at the stage of maximum tillering and assessing plant height at harvest. We used the soil plant analysis development (SPAD) method (SPAD-502 Plus Chlorophyll Meter, Minolta Co. Ltd, Japan) to measure leaf greenness on a weekly basis. At 126 days after transplanting, the plants were harvested and separated into roots, shoots, and panicles. These components were dried and weighed to determine yield and biomass (Phung et al. 2020, 2022). The rice protein content was calculated by multiplying the total N content of brown rice by a conversion factor of 5.26 (Fujihara et al. 2008). The total N content of brown rice was determined using an automatic NC analyzer (Sumigraph NC-220F, SCAS, Japan).
Trace element analysis
Plant, soil, and rice samples were prepared using standard acid digestion methods for elemental analysis (EPA 2004). Detail protocols have been described by Phung et al. (2023a). The total concentration of As in the samples was determined using an atomic absorption spectrometer (AA-7000, Shimadzu Corporation, Japan) equipped with a high-sensitivity graphite furnace atomizer (GFA-7000, Shimadzu Corporation, Japan). The total concentrations of Ca, Mg, Na, K, P, Fe, Cu, Zn, Mn, Mo, Cd, Cr, and Ni were determined using an inductively coupled plasma mass spectrometer (ICP-MS Elan DRC II, PerkinElmer, Japan).
Analysis of soil physicochemical properties
The air-dried soil samples were sieved through a 2-mm mesh and then analyzed using standard soil analysis methods. This analysis involved measuring the pH, EC, soil organic matter (SOM), and total concentrations of C, N, P, and K (TC, TN, TP, and TK, respectively) following the protocols described by Phung et al. (2023b).
Calculation for Zn translocation and bioaccumulation factor
Human health risk assessment
The RfD values in milligrams per kilogram of body weight (mg kg−1 day−1) for As, Cd, Cr, Ni, Fe, Zn, Cu, Mn, and Mo are 0.0003, 0.001, 1.5, 0.02, 0.7, 0.3, 0.04, 0.14, and 0.005, respectively (EPA 2021). The HQ value below one indicates that there is no potential non-carcinogenic risk associated with consuming rice exposed to a single element.
A hazard index (HI) was computed by adding the individual HQ values to assess the cumulative effect of multiple elements. If the HI is greater than one, consuming rice containing multiple elements may pose a potential health risk.
Statistical analysis
The effects of the elevated contamination of ZnO NPs in TWW were determined using a one-way analysis of variance applied to the data obtained from the control, 2NP, and 5NP treatments. To compare the means of significant treatment effects, Tukey's honest significant difference (HSD) test was applied. The Student's t-test was used to compare the effects of ZnO NPs and ZnSO4 at the same Zn concentrations. IBM SPSS Statistics 26.0 was used for all statistical analyses with a significance level of p < 0.05.
RESULTS
Dissolution of ZnO NPs and ZnSO4 in TWW
The background Zn concentrations in the original TWW (i.e., without the addition of exogenous ZnO NPs or ZnSO4) were relatively low (∼0.05 mg L−1; Table S1), whereas the altered TWW used for treatments 2NP and 2S (2 mg Zn L−1) and treatments 5P and 5S (5 mg Zn L−1) had much higher dosed concentrations. ZnSO4 exhibited remarkable solubility in TWW, with dissolution rates ranging from 93 to 97% for both tested concentrations (Figure S1). On the other hand, ZnO NPs demonstrated a slower and more gradual process of dissolving. At a concentration of 2 mg Zn L−1, more than 50% of ZnO NPs disintegrated instantly when subjected to ultrasonication. However, only 38% of the particles initially dissolved when the concentration increased to 5 mg Zn L−1. The concentrations of Zn in the 5NP treatment steadily increased over time, reaching more than 90% of the intended concentration 9 days after suspension preparation. These findings indicate that the rate at which ZnO NPs dissolve is affected by both their concentration and the length of time they are exposed. Higher concentrations of ZnO NPs resulted in slower and delayed breakdown.
Plant growth and crop yield
The inclusion of ZnO NPs in TWW significantly altered plant height (Table 1). The plants subjected to the 5NP treatment had the shortest height in comparison with the control and 2NP treatments (p < 0.05). At a concentration of 2 mg Zn L−1, the presence of ZnSO4 in the irrigation TWW caused a substantial decrease in plant height compared to ZnO NPs. At a concentration of 5 mg Zn L−1, however, ZnSO4 increased plant height compared to ZnO NPs at the same concentration. The treatments did not show any significant variation in terms of rice tillering capacity (p > 0.05; Table 1). The leaf greenness showed similar patterns, as indicated by the constant SPAD values found across all treatments throughout the growing period (Figure S2).
Rice growth and yield as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4
Treatment . | Plant height (cm) . | Tiller number per hill . | Shoot weight (g hill−1) . | Root weight (g hill−1) . | Brown rice yield (g hill−1) . | Rice protein (%) . |
---|---|---|---|---|---|---|
Control | 98.2 ± 0.9ab | 52.3 ± 2.5a | 84.9 ± 3.3a | 10.1 ± 0.7a | 88.4 ± 5.1a | 9.8 ± 0.6a |
2NP | 100.4 ± 0.7a | 47.0 ± 6.1a | 85.5 ± 2.0a | 7.8 ± 0.7b | 94.2 ± 2.9a | 9.4 ± 0.1a |
5NP | 96.6 ± 2.0b | 52.7 ± 5.1a | 88.4 ± 10.7a | 9.7 ± 0.1a | 91.8 ± 8.0a | 9.4 ± 0.2a |
2S | 96.9 ± 1.3* | 52.3 ± 5.0ns | 84.5 ± 4.1ns | 9.3 ± 0.3* | 94.3 ± 7.7ns | 9.8 ± 0.5ns |
5S | 100.1 ± 1.1ns | 48.3 ± 7.6ns | 87.4 ± 4.0ns | 8.7 ± 1.7ns | 95.4 ± 6.5ns | 9.3 ± 0.4ns |
Treatment . | Plant height (cm) . | Tiller number per hill . | Shoot weight (g hill−1) . | Root weight (g hill−1) . | Brown rice yield (g hill−1) . | Rice protein (%) . |
---|---|---|---|---|---|---|
Control | 98.2 ± 0.9ab | 52.3 ± 2.5a | 84.9 ± 3.3a | 10.1 ± 0.7a | 88.4 ± 5.1a | 9.8 ± 0.6a |
2NP | 100.4 ± 0.7a | 47.0 ± 6.1a | 85.5 ± 2.0a | 7.8 ± 0.7b | 94.2 ± 2.9a | 9.4 ± 0.1a |
5NP | 96.6 ± 2.0b | 52.7 ± 5.1a | 88.4 ± 10.7a | 9.7 ± 0.1a | 91.8 ± 8.0a | 9.4 ± 0.2a |
2S | 96.9 ± 1.3* | 52.3 ± 5.0ns | 84.5 ± 4.1ns | 9.3 ± 0.3* | 94.3 ± 7.7ns | 9.8 ± 0.5ns |
5S | 100.1 ± 1.1ns | 48.3 ± 7.6ns | 87.4 ± 4.0ns | 8.7 ± 1.7ns | 95.4 ± 6.5ns | 9.3 ± 0.4ns |
Data are presented as mean ± standard deviation (n = 3). The statistical relationships between the control, 2NP, and 5NP treatments are denoted by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is represented with an asterisk (*) or the abbreviation ‘ns’ (non-significance). In a column, different letters and an asterisk indicate a statistically significant difference at p < 0.05.
There was no inhibition of shoot biomass production when the contamination of ZnO NPs or ZnSO4 in TWW was elevated. Indeed, the shoots in the 2NP and 5NP treatments exhibited a little greater weight (1–4%) compared to the control. However, this difference was not statistically significant (p > 0.05; Table 1). The inclusion of ZnO NPs in TWW resulted in a significant decrease in root production. Specifically, the 2NP treatment caused a 23% reduction in root weight compared to the control (p < 0.05). The addition of ZnSO4 resulted in a substantial increase in root biomass compared to ZnO NPs, both at a concentration of 2 mg Zn L−1 (p < 0.05; Table 1). This phenomenon was not observed when the irrigation TWW had a greater contamination level of 5 mg Zn L−1.
An increase in the contamination of ZnO NPs in TWW resulted in a 4–7% gain in rice yield compared to the control. However, this difference was not considered statistically significant (p > 0.05; Table 1). Similar effects were observed at the low concentrations of both ZnSO4 and ZnO NPs. However, when the concentrations increased, treatment 5S yielded 4% higher output compared to treatment 5NP (p > 0.05).
Zinc accumulation and translocation in rice–soil systems
Accumulation of Zn in rice–soil systems as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4. The error bars represent the standard deviations (n = 3). The statistical relationship between the control, 2NP, and 5NP treatments is represented by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is denoted with an asterisk (*). In a graph, different letters and an asterisk indicate a statistically significant difference at p < 0.05. The abbreviation ‘ns’ represents non-significance.
Accumulation of Zn in rice–soil systems as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4. The error bars represent the standard deviations (n = 3). The statistical relationship between the control, 2NP, and 5NP treatments is represented by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is denoted with an asterisk (*). In a graph, different letters and an asterisk indicate a statistically significant difference at p < 0.05. The abbreviation ‘ns’ represents non-significance.
The application of the 5NP and 2NP treatments resulted in a significant rise in the accumulation of Zn in rice shoots, with concentrations that were three and two times greater than the control, respectively (p < 0.05). At a concentration of 2 mg Zn L−1, ZnSO4 resulted in a higher accumulation of Zn in the shoots compared to ZnO NPs (p > 0.05). At a contamination level of 5 mg Zn L−1, both 5NP and 5S shoots had similar Zn concentrations (p > 0.05).
The presence of lower levels of ZnO NPs in TWW (2NP) resulted in comparable levels of Zn in brown rice (19.4 mg kg−1) compared to the control (16.5 mg kg−1; p > 0.05). However, the addition of 5NP resulted in a substantial increase in the Zn content of the rice, virtually tripling it compared to the control (p < 0.05). When comparing rice grains with the same level of contamination, 2S rice grains had 150% more Zn than 2NP rice grains (p < 0.05). However, the Zn levels of 5NP and 5S rice grains were similar (p > 0.05).
The contamination of TWW with ZnO NPs greatly enhanced the root uptake of Zn from the soil. This was evident from the TFsoil−root values, which were roughly 8 times higher for the 2NP treatment and 16 times higher for the 5NP treatment, compared to the control (p < 0.05; Table 2). The presence of ZnSO4 in TWW increased Zn uptake by the roots as well. Specifically, the roots under the 5S treatment demonstrated a significant 70% increase in their ability to transport Zn from the soil compared to the roots subjected to the 5NP treatment (p < 0.05). The elevated contamination of TWW with ZnO NPs or ZnSO4 reduced the rice plants' capacity to transport Zn from the roots to the shoots by 80% compared to the control (p < 0.05). While there were no statistically significant differences observed in TFshoot−grain values across all treatments, it was noted that higher levels of Zn contamination in TWW tended to reduce the movement of Zn from shoots to grains.
Translocation and bioaccumulation factors of Zn within rice–soil systems
Treatment . | TFs . | BAF . | ||
---|---|---|---|---|
TFsoil−root . | TFroot−shoot . | TFshoot−grain . | ||
Control | 0.6 ± 0.1c | 0.5 ± 0.1a | 0.7 ± 0.1a | 0.2 ± 0.0b |
2NP | 4.7 ± 0.7b | 0.1 ± 0.0b | 0.6 ± 0.3a | 0.3 ± 0.2ab |
5NP | 9.9 ± 2.1a | 0.1 ± 0.0b | 0.6 ± 0.1a | 0.6 ± 0.1a |
2S | 5.7 ± 2.9ns | 0.1 ± 0.0ns | 0.7 ± 0.1ns | 0.6 ± 0.1ns |
5S | 16.8 ± 3.3* | 0.1 ± 0.0ns | 0.5 ± 0.1ns | 0.5 ± 0.1ns |
Treatment . | TFs . | BAF . | ||
---|---|---|---|---|
TFsoil−root . | TFroot−shoot . | TFshoot−grain . | ||
Control | 0.6 ± 0.1c | 0.5 ± 0.1a | 0.7 ± 0.1a | 0.2 ± 0.0b |
2NP | 4.7 ± 0.7b | 0.1 ± 0.0b | 0.6 ± 0.3a | 0.3 ± 0.2ab |
5NP | 9.9 ± 2.1a | 0.1 ± 0.0b | 0.6 ± 0.1a | 0.6 ± 0.1a |
2S | 5.7 ± 2.9ns | 0.1 ± 0.0ns | 0.7 ± 0.1ns | 0.6 ± 0.1ns |
5S | 16.8 ± 3.3* | 0.1 ± 0.0ns | 0.5 ± 0.1ns | 0.5 ± 0.1ns |
Data are presented as mean ± standard deviation (n = 3). The statistical relationships between the control, 2NP, and 5NP treatments are denoted by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is represented with an asterisk (*) or the abbreviation ‘ns’ (non-significance). In a column, different letters and an asterisk indicate a statistically significant difference at p < 0.05.
The BAF of Zn in rice grains exhibited a notable increase when rice plants were subjected to irrigation with TWW that had elevated levels of ZnO NPs. The 2NP treatment showed a 50% greater BAF than the control, whereas the 5NP treatment led to a remarkable three-fold rise (p < 0.05). The 2S and 5S treatments showed similar patterns, suggesting a general increase in the accumulation of Zn in rice grains.
Rice nutritional quality and accumulation of potentially toxic metals
There were no statistically significant differences in the protein content of brown rice among the treatments (p > 0.05; Table 1). Notably, however, the contamination of TWW with Zn, regardless of its form, tended to decrease the protein content of rice compared to the control (p > 0.05).
The increased quantities of ZnO NPs in TWW had a notable effect on the mineral composition of polished rice (Table 3). In comparison with the control, the 2NP treatment increased the levels of macronutrients (Na, K, Ca, Mg, and P) by 8–17%. Similarly, the 5NP treatment led to a 13–48% increase in these levels, although the difference was not statistically significant (p > 0.05). In contrast, ZnSO4 tended to decrease the macronutrient content in rice (p > 0.05). Particularly, the 5S treatment significantly reduced the levels of K, Ca, Mg, and P in polished rice by 12–7% compared to the 5NP treatment (p < 0.05).
Content of minerals and potentially toxic metals in polished rice grain as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4
Mineral composition (mg kg−1) . | Treatment . | ML . | ||||
---|---|---|---|---|---|---|
Control . | 2NP . | 5NP . | 2S . | 5S . | ||
Na | 67.8 ± 17a | 73.9 ± 3.4a | 76.8 ± 11.3a | 71.7 ± 4.9ns | 94.5 ± 12.7ns | – |
K | 1,150.5 ± 138.2a | 1,343.8 ± 246.5a | 1,567.9 ± 34.8a | 1,264.4 ± 127.7ns | 1,329.5 ± 2.1* | – |
Ca | 49.3 ± 4.2a | 53.1 ± 7.6a | 59.8 ± 2.1a | 52.8 ± 5.4ns | 52.7 ± 2.2* | – |
Mg | 296.1 ± 60.9a | 341.8 ± 99.4a | 437.7 ± 10.2a | 297 ± 45.5ns | 320.1 ± 28.9* | – |
P | 1,004.3 ± 123.7a | 1,129.9 ± 236.5a | 1,360.5 ± 46.2a | 1,047.5 ± 114.1ns | 1,109.9 ± 35.6* | – |
Fe | 5.4 ± 3.1a | 5.0 ± 1.8a | 5.3 ± 0.3a | 3.7 ± 0.5ns | 4.2 ± 0.8ns | – |
Zn | 14.5 ± 1.1b | 18.9 ± 2.0a | 21.3 ± 0.3a | 18.9 ± 1.1ns | 19.7 ± 0.8* | – |
Cu | 2.5 ± 0.2a | 2.5 ± 0.3a | 2.5 ± 0.1a | 2.7 ± 0.2ns | 2.6 ± 0.2ns | – |
Mn | 8.3 ± 2.3a | 9.2 ± 1.8a | 8.9 ± 0.7a | 8.0 ± 0.5ns | 8.5 ± 0.6ns | – |
Mo | 0.28 ± 0.01b | 0.32 ± 0.03ab | 0.34 ± 0.01a | 0.32 ± 0.02ns | 0.33 ± 0.03ns | – |
As | 0.031 ± 0.00b | 0.062 ± 0.00a | 0.065 ± 0.01a | 0.072 ± 0.01ns | 0.073 ± 0.00ns | 0.2 |
Cd | 0.014 ± 0a | 0.011 ± 0ab | 0.010 ± 0b | 0.011 ± 0ns | 0.011 ± 0ns | 0.4 |
Pb | ND | ND | ND | ND | ND | 0.2 |
Cr | 0.04 ± 0.02a | 0.04 ± 0.01a | 0.03 ± 0a | 0.03 ± 0ns | 0.03 ± 0ns | – |
Ni | 0.32 ± 0.06a | 0.28 ± 0.05a | 0.30 ± 0.05a | 0.27 ± 0.04ns | 0.27 ± 0.03ns | – |
Mineral composition (mg kg−1) . | Treatment . | ML . | ||||
---|---|---|---|---|---|---|
Control . | 2NP . | 5NP . | 2S . | 5S . | ||
Na | 67.8 ± 17a | 73.9 ± 3.4a | 76.8 ± 11.3a | 71.7 ± 4.9ns | 94.5 ± 12.7ns | – |
K | 1,150.5 ± 138.2a | 1,343.8 ± 246.5a | 1,567.9 ± 34.8a | 1,264.4 ± 127.7ns | 1,329.5 ± 2.1* | – |
Ca | 49.3 ± 4.2a | 53.1 ± 7.6a | 59.8 ± 2.1a | 52.8 ± 5.4ns | 52.7 ± 2.2* | – |
Mg | 296.1 ± 60.9a | 341.8 ± 99.4a | 437.7 ± 10.2a | 297 ± 45.5ns | 320.1 ± 28.9* | – |
P | 1,004.3 ± 123.7a | 1,129.9 ± 236.5a | 1,360.5 ± 46.2a | 1,047.5 ± 114.1ns | 1,109.9 ± 35.6* | – |
Fe | 5.4 ± 3.1a | 5.0 ± 1.8a | 5.3 ± 0.3a | 3.7 ± 0.5ns | 4.2 ± 0.8ns | – |
Zn | 14.5 ± 1.1b | 18.9 ± 2.0a | 21.3 ± 0.3a | 18.9 ± 1.1ns | 19.7 ± 0.8* | – |
Cu | 2.5 ± 0.2a | 2.5 ± 0.3a | 2.5 ± 0.1a | 2.7 ± 0.2ns | 2.6 ± 0.2ns | – |
Mn | 8.3 ± 2.3a | 9.2 ± 1.8a | 8.9 ± 0.7a | 8.0 ± 0.5ns | 8.5 ± 0.6ns | – |
Mo | 0.28 ± 0.01b | 0.32 ± 0.03ab | 0.34 ± 0.01a | 0.32 ± 0.02ns | 0.33 ± 0.03ns | – |
As | 0.031 ± 0.00b | 0.062 ± 0.00a | 0.065 ± 0.01a | 0.072 ± 0.01ns | 0.073 ± 0.00ns | 0.2 |
Cd | 0.014 ± 0a | 0.011 ± 0ab | 0.010 ± 0b | 0.011 ± 0ns | 0.011 ± 0ns | 0.4 |
Pb | ND | ND | ND | ND | ND | 0.2 |
Cr | 0.04 ± 0.02a | 0.04 ± 0.01a | 0.03 ± 0a | 0.03 ± 0ns | 0.03 ± 0ns | – |
Ni | 0.32 ± 0.06a | 0.28 ± 0.05a | 0.30 ± 0.05a | 0.27 ± 0.04ns | 0.27 ± 0.03ns | – |
Data are presented as mean ± standard deviation (n = 3). The statistical relationships between the control, 2NP, and 5NP treatments are denoted by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is represented with an asterisk (*) or the abbreviation ‘ns’ (non-significance). In a row, different letters and an asterisk indicate a statistically significant difference at p < 0.05.
ND, not detected; ML, maximum limits (FAO & WHO 2019).
A similar trend was observed for micronutrients, where the 2NP and 5NP treatments remarkedly increased the Zn, Mn, and Mo contents of polished rice (Table 3). Specifically, the 2NP and 5NP rice grains had 30 and 47% higher levels of Zn, respectively, compared to the control (p < 0.05). These treatments resulted in a substantial increase in Mo content, ranging from 14 to 21%, compared to the control (p < 0.05). In addition, the presence of ZnO NPs in TWW resulted in a 7–11% increase in Mn concentration compared to the control. However, this increase was not statistically significant (p > 0.05). The contamination of TWW with ZnO NPs had no appreciable effect on the accumulation of Fe and Cu in polished rice (p > 0.05). In contrast, ZnSO4 tended to reduce the levels of Fe and Mn in rice, whereas it slightly increased the accumulation of Cu compared to ZnO NPs, regardless of contamination levels (p > 0.05). Importantly, the 5S treatment decreased Zn accumulation in polished rice significantly relative to the 5NP treatment (p < 0.05).
The accumulation of potentially toxic metals (As, Cd, Cr, and Ni) in rice grains was substantially impacted by Zn contamination in TWW (Table 3). The presence of ZnO NPs in TWW resulted in a two-fold increase in the concentration of As in polished rice grains when compared to the control (p < 0.05). This effect was further exacerbated by ZnSO4, with the 2S and 5S treatments increasing the accumulation of As in polished rice by approximately 2.3 times compared to the control. On the other hand, Zn contamination in TWW resulted in a significant reduction in the accumulation of Cd (p < 0.05) but had very minor effects on the buildup of Cr and Ni in polished rice grains (p > 0.05).
Pearson's correlation matrix between trace elements in polish rice grains. The asterisk (*) denotes statistical significance at p < 0.05.
Pearson's correlation matrix between trace elements in polish rice grains. The asterisk (*) denotes statistical significance at p < 0.05.
Human health risk assessment
The EDI values of As, Zn, and Mo for the 2NP and 5NP treatments were significantly greater than those in the control (p < 0.05; Table 4). The elevated presence of ZnO NPs in TWW resulted in a significant increase in Zn intake through rice consumption. Specifically, the intake of Zn rose by 29% with the 2NP treatment and 47% with the 5NP treatment, compared to the control. In addition, the 2NP and 5NP treatments resulted in a more than two-fold increase in daily intake of As, with the impact being intensified by the increased concentrations of ZnO NPs in TWW (p < 0.05). The contamination of ZnO NPs in TWW led to an increase of 14–18% in the EDI of Mo through the consumption of rice (p < 0.05). Furthermore, ZnO NP contamination in TWW led to marginal elevations in the EDI values of Cu and Mn (p > 0.05), slight reductions in the EDI values of Cd and Fe (p > 0.05), and no significant changes in the intake levels of Cr and Ni. The impacts of ZnO NPs and ZnSO4 were similar, except for As and Zn. The 2S treatment significantly raised the EDI of As compared to the 2NP treatment (p < 0.05), whereas the 5S treatment lowered the EDI of Zn compared to the 5NP treatment (p < 0.05). The EDI values of the elements in each of the investigated treatments were below the RfD of the trace elements, resulting in HQ values that were less than one.
EDI and HQ of trace elements through rice consumption as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4
Treatment . | As . | Cd . | Cr . | Ni . | Fe . | Zn . | Cu . | Mn . | Mo . |
---|---|---|---|---|---|---|---|---|---|
EDI (mg kg−1 day−1) | |||||||||
Control | 0.00007a | 0.000033a | 0.0001a | 0.0007a | 0.0126a | 0.034b | 0.0057a | 0.019a | 0.00066b |
2NP | 0.00014a | 0.000026ab | 0.0001a | 0.0007a | 0.0116a | 0.044a | 0.0059a | 0.021a | 0.00075ab |
5NP | 0.00015a | 0.000023b | 0.0001a | 0.0007a | 0.0124a | 0.050a | 0.0059a | 0.021a | 0.00078a |
2S | 0.00017* | 0.000025ns | 0.0001ns | 0.0006ns | 0.0086ns | 0.044ns | 0.0063ns | 0.019ns | 0.00075ns |
5S | 0.00017ns | 0.000025ns | 0.0001ns | 0.0006ns | 0.0097ns | 0.046* | 0.0061ns | 0.020ns | 0.00078ns |
HQ | |||||||||
Control | 0.24b | 0.033a | 0.00007a | 0.037a | 0.018a | 0.11b | 0.14a | 0.14a | 0.13b |
2NP | 0.48a | 0.026ab | 0.00006a | 0.033a | 0.017a | 0.15a | 0.15a | 0.15a | 0.15ab |
5NP | 0.51a | 0.023b | 0.00005a | 0.034a | 0.018a | 0.17a | 0.15a | 0.15a | 0.16a |
2S | 0.56* | 0.025ns | 0.00005ns | 0.031ns | 0.012ns | 0.15ns | 0.16ns | 0.13ns | 0.15ns |
5S | 0.57ns | 0.025ns | 0.00005ns | 0.031ns | 0.014ns | 0.15* | 0.15ns | 0.14ns | 0.16ns |
Treatment . | As . | Cd . | Cr . | Ni . | Fe . | Zn . | Cu . | Mn . | Mo . |
---|---|---|---|---|---|---|---|---|---|
EDI (mg kg−1 day−1) | |||||||||
Control | 0.00007a | 0.000033a | 0.0001a | 0.0007a | 0.0126a | 0.034b | 0.0057a | 0.019a | 0.00066b |
2NP | 0.00014a | 0.000026ab | 0.0001a | 0.0007a | 0.0116a | 0.044a | 0.0059a | 0.021a | 0.00075ab |
5NP | 0.00015a | 0.000023b | 0.0001a | 0.0007a | 0.0124a | 0.050a | 0.0059a | 0.021a | 0.00078a |
2S | 0.00017* | 0.000025ns | 0.0001ns | 0.0006ns | 0.0086ns | 0.044ns | 0.0063ns | 0.019ns | 0.00075ns |
5S | 0.00017ns | 0.000025ns | 0.0001ns | 0.0006ns | 0.0097ns | 0.046* | 0.0061ns | 0.020ns | 0.00078ns |
HQ | |||||||||
Control | 0.24b | 0.033a | 0.00007a | 0.037a | 0.018a | 0.11b | 0.14a | 0.14a | 0.13b |
2NP | 0.48a | 0.026ab | 0.00006a | 0.033a | 0.017a | 0.15a | 0.15a | 0.15a | 0.15ab |
5NP | 0.51a | 0.023b | 0.00005a | 0.034a | 0.018a | 0.17a | 0.15a | 0.15a | 0.16a |
2S | 0.56* | 0.025ns | 0.00005ns | 0.031ns | 0.012ns | 0.15ns | 0.16ns | 0.13ns | 0.15ns |
5S | 0.57ns | 0.025ns | 0.00005ns | 0.031ns | 0.014ns | 0.15* | 0.15ns | 0.14ns | 0.16ns |
Data are presented as mean ± standard deviation (n = 3). The statistical relationships between the control, 2NP, and 5NP treatments are denoted by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is represented with an asterisk (*) or the abbreviation ‘ns’ (non-significance). In a column, different letters and an asterisk indicate a statistically significant difference at p < 0.05.
Potential health risks caused by multiple trace elements through rice consumption as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4.
Potential health risks caused by multiple trace elements through rice consumption as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4.
Changes in soil physicochemical properties
The introduction of ZnO NPs into TWW had no significant impact on the observed soil parameters (p > 0.05; Table 5). However, with the rise in ZnO NP concentrations in TWW, there was a minor drop in soil EC and TC, while there was a slight increase in soil TN and TK compared to the control (p > 0.05). The addition of ZnSO4 to the soils resulted in a considerably higher rise in soil TN compared to ZnO NPs, both at the same concentrations in TWW (p < 0.05). More precisely, the soil TN increased by 15 and 18.5% in the 2S and 5S treatments, respectively, when compared to the 2NP and 5NP treatments.
Changes in soil properties as affected by the elevated contamination of irrigation TWW with ZnO NPs and ZnSO4
Treatment . | Soil parameters . | ||||||
---|---|---|---|---|---|---|---|
pH . | EC (dS m−1) . | SOM (%) . | TC (g kg−1) . | TN (g kg−1) . | TP (g kg−1) . | TK (g kg−1) . | |
Control | 6.1 ± 0.2a | 2.1 ± 1.0a | 5.3 ± 0.1a | 24.0 ± 0.5a | 2.6 ± 0.0a | 1.2 ± 0.0a | 1.4 ± 0.1a |
2NP | 6.0 ± 0.2a | 1.8 ± 0.3a | 5.2 ± 0.0a | 22.8 ± 1.3a | 2.6 ± 0.1a | 1.1 ± 0.0a | 1.6 ± 0.2a |
5NP | 6.1 ± 0.1a | 1.7 ± 0.1a | 5.3 ± 0.1a | 23.3 ± 0.1a | 2.7 ± 0.0a | 1.2 ± 0.0a | 1.6 ± 0.1a |
2S | 6.2 ± 0.0ns | 2.0 ± 0.3ns | 5.2 ± 0.1ns | 24 ± 0.5ns | 3.0 ± 0.1* | 1.2 ± 0.0ns | 1.8 ± 0.2ns |
5S | 6.2 ± 0.0ns | 1.8 ± 0.4ns | 5.1 ± 0.1ns | 24.2 ± 1.3ns | 3.2 ± 0.1* | 1.2 ± 0.0ns | 1.7 ± 0.2ns |
Initial soil | 5.7 ± 0.2 | 2.0 ± 2.2 | 5.1 ± 0.2 | 24.0 ± 1.4 | 2.6 ± 0.1 | 1.2 ± 0.0 | 1.5 ± 0.0 |
Treatment . | Soil parameters . | ||||||
---|---|---|---|---|---|---|---|
pH . | EC (dS m−1) . | SOM (%) . | TC (g kg−1) . | TN (g kg−1) . | TP (g kg−1) . | TK (g kg−1) . | |
Control | 6.1 ± 0.2a | 2.1 ± 1.0a | 5.3 ± 0.1a | 24.0 ± 0.5a | 2.6 ± 0.0a | 1.2 ± 0.0a | 1.4 ± 0.1a |
2NP | 6.0 ± 0.2a | 1.8 ± 0.3a | 5.2 ± 0.0a | 22.8 ± 1.3a | 2.6 ± 0.1a | 1.1 ± 0.0a | 1.6 ± 0.2a |
5NP | 6.1 ± 0.1a | 1.7 ± 0.1a | 5.3 ± 0.1a | 23.3 ± 0.1a | 2.7 ± 0.0a | 1.2 ± 0.0a | 1.6 ± 0.1a |
2S | 6.2 ± 0.0ns | 2.0 ± 0.3ns | 5.2 ± 0.1ns | 24 ± 0.5ns | 3.0 ± 0.1* | 1.2 ± 0.0ns | 1.8 ± 0.2ns |
5S | 6.2 ± 0.0ns | 1.8 ± 0.4ns | 5.1 ± 0.1ns | 24.2 ± 1.3ns | 3.2 ± 0.1* | 1.2 ± 0.0ns | 1.7 ± 0.2ns |
Initial soil | 5.7 ± 0.2 | 2.0 ± 2.2 | 5.1 ± 0.2 | 24.0 ± 1.4 | 2.6 ± 0.1 | 1.2 ± 0.0 | 1.5 ± 0.0 |
Data are presented as mean ± standard deviation (n = 3). The statistical relationships between the control, 2NP, and 5NP treatments are denoted by lowercase letters, whereas the relationship between 2NP and 2S or 5NP and 5S is represented with an asterisk (*) or the abbreviation ‘ns’ (non-significance). In a column, different letters and an asterisk indicate a statistically significant difference at p < 0.05.
DISCUSSIONS
While MNPs are unavoidable wastewater components, there is no current standard for NPs in effluent discharge (Singh & Kumar 2020; Phung et al. 2022). Current regulatory approaches, such as the Effluent Guidelines provided by the United States Environmental Protection Agency, are inadequate for setting limits on MNPs in surface waters due to knowledge gaps in toxicity, degradability, and bioaccumulation. Ongoing research has been focusing on the mitigation of MNP toxicity and improving regulatory frameworks. It is assumed that the presence of ZnO NPs in the effluent of the WWTP is a consequence of incomplete removal even though conventional wastewater treatment can remove 84–99% of most MNPs in wastewater (Cervantes-Avilés & Keller 2021). The concentrations of ZnO NPs present in TWW used in this study were below the regulatory limits for Zn in effluents (5 mg L−1), allowing them to be conventionally discharged and potentially reintroduced into rice paddy fields via TWW irrigation. Our research offers valuable insights into the intricate dynamics of ZnO NPs in wastewater irrigation and its consequences for regulatory policy and sustainable agriculture practices.
The dissolution of ZnO NPs in water environments is strongly dependent on the initial concentration and water chemistry (Hsieh et al. 2023). Due to the low concentrations of Zn in the original TWW (0.04–0.05 mg L−1; Table S1), we assumed that these background concentrations of Zn did not affect the dissolution of the added Zn sources. Our observations indicated that ZnO NPs exhibited a slower and more protracted dissolution in TWW compared to ZnSO4, potentially leading to different temporal patterns of Zn availability to rice plants. The prolonged presence of ZnO NPs in agricultural contexts could have a continuing impact on the uptake of Zn from soils and performance crops, leading to concerns about their long-term effects (Chen 2018; Wang et al. 2021). Further work is necessary to examine the possible long-term environmental and health effects of ZnO NPs even at very low concentrations.
The results of this study suggest that the presence of ZnO NPs in TWW can have a detrimental influence on rice plants, leading to a decrease in plant height and root weight. This can potentially hinder root development and overall plant growth, ultimately decreasing crop yield and agricultural productivity. These findings are consistent with other research that has shown the phytotoxic effects of MNPs at elevated concentrations (Bandyopadhyay et al. 2015; García-Gómez et al. 2017; Chen et al. 2018). For instance, Boonyanitipong et al. (2011) showed the phytotoxicity of ZnO NPs on rice seedlings, where short-term exposure to a broad range of ZnO NP concentrations (10–1,000 mg L−1) inhibited root length and reduced the number of rice roots. Rice seedlings exposed to certain concentrations of CuO NPs (62.5–2,000 mg Cu L−1) also exhibited inhibited root elongation and decreased growth rates in other studies (Yang et al. 2020). Root and shoot growth of barley sprouts were also inhibited due to the contamination of soil with ZnO NPs at 30 mmol Zn kg soil−1 (Nemček et al. 2020). However, our findings indicate that even at lower concentrations, long-term exposure may have negative consequences, therefore justifying the need for additional investigation into the mechanisms by which MNPs impact rice metabolism in different environmental circumstances.
The observed differences in plant growth responses to ZnSO4 and ZnO NPs suggest that ZnO NPs may exert additional physical or chemical interactions that are not solely attributable to the release of Zn ions. These interactions could involve mechanical effects on root surfaces or localized changes in rhizosphere chemistry, which are not replicated by the soluble ion form of Zn from ZnSO4. As an essential micronutrient for plants, Zn plays a vital role in numerous metabolic processes (Broadley et al. 2007; Hänsch & Mendel 2009; Stanton et al. 2022). The presence of ZnO NPs in TWW can serve as a source of this essential micronutrient for plant growth. In line with this, Lv et al. (2022) reported that optimal concentrations of ZnO NPs maintained a steady release of Zn ions, thereby enhancing photosynthesis, enzyme activities, and the plant's uptake of other essential nutrients. This aspect highlights the dual role of ZnO NPs as both a nutrient source and a potential stressor, underscoring the need for balancing nutrient supply with potential toxicity.
The significant accumulation of Zn in the roots, shoots, and grains of rice plants exposed to ZnO NPs in TWW suggests that rice plants can absorb and distribute these MNPs. However, in the presence of elevated levels of Zn contamination in TWW, Zn translocation from roots to shoots was drastically reduced, indicating that the plant's ability to efficiently transport Zn from their roots to their aerial parts may be compromised, thereby affecting the distribution of Zn within the plant. It has been shown that MNPs, such as CuO NPs, are primarily absorbed and stored in rice roots, with only a small portion transported upwards (Da Costa & Sharma 2016; Phung et al. 2022; Yang et al. 2002). This was possible due to the inherent ability of plants to detect and respond to an excess of Zn in their roots and shoots. This biological mechanism allows plants to activate various genetic, cellular, organ, and whole-plant homeostatic processes designed to prevent Zn accumulation in their tissues, allowing them to proactively regulate Zn transport and prevent its translocation to the upper plant parts before toxicity develops (Sinclair & Krämer 2012; Stanton et al. 2022).
The study did not observe any significant alterations in the physicochemical properties of the soil because of exposure to ZnO NPs. However, the possibility of subtle and long-lasting effects on soil health indicates the need for more extensive research to fully comprehend the consequences of NP accumulation in agricultural soils.
While ZnO NPs have shown the potential to enhance the nutritional value of rice by increasing the concentrations of macronutrients (Na, K, Ca, Mg, and P) and micronutrients (Zn, Mn, and Mo) in the grains, they also raise significant concerns due to the accumulation of potentially toxic metals like As. This duality suggests complex interactions within the soil–plant system, influenced by the increased levels of ZnO NPs in TWW. Previous studies have highlighted that ZnO NPs can improve the mineral composition of rice by facilitating the uptake of Zn2+ ions, which are known to stimulate essential micronutrient transporters (NRAMP3 and NRAMP4) and the metal tolerance proteins (MTP1 and MTP8), thereby facilitating the translocation of other elements to the upper parts of plants (Sharifan et al. 2020; Yang et al. 2021). This mechanism promotes the translocation of these elements from the roots to the aerial parts of the plant, potentially enhancing overall plant nutrition (Yang et al. 2013; da Cruz et al. 2019; Sharifan et al. 2020). As these nutrients play essential roles in human health and nutrition (Ministry of Health Labour and Welfare of Japan 2020), their elevated accumulation is of particular interest. However, the accumulation of trace metals like Zn and As in edible parts of the crop can pose risks to food safety and human health (Fraga 2005).
The observed decrease in Cd levels in rice grains, which is often elevated in rice due to ZnO NP exposure (Zhang et al. 2019; Tavarez et al. 2022), can be attributed to the antagonistic interaction between Zn and Cd, where elevated Zn levels competitively inhibit the uptake and transport of Cd in rice plants (Sasaki et al. 2014). The transporters OsHMA2 and OsHMA3 play a crucial role in the uptake and transport of both Cd and Zn in rice plants, and when Zn concentrations rise, Zn competes with Cd for uptake and translocation pathways (Ishikawa et al. 2012; Takahashi et al. 2012; Yoneyama et al. 2015). Similar trends were also observed in other plant parts treated with ZnO NPs, including brown rice, husk, and roots, indicating a negative correlation between Cd and Zn concentrations (Wang et al. 2018).
However, we also noted a significant increase in As accumulation in rice grains. As a toxic element with adverse health effects, the increased accumulation of As raises food safety concerns (Karagas et al. 2019). This finding is contrary to previous research, suggesting that higher concentrations of ZnO NPs could mitigate As uptake by competing for adsorption sites in the growing medium and reducing its mobility within the plant (Ma et al. 2020; Wu et al. 2020; Yan et al. 2021). However, in our case, the relatively low concentrations of ZnO NPs used (2–5 mg Zn L−1) may not have been sufficient to effectively reduce As translocation to the grains. Instead, the presence of Zn could have facilitated the uptake of As, possibly by forming Zn–arsenate complexes that are then transported within the plant (Wang et al. 2017). Abid et al. (2019) also reported that 75 μM Zn (∼4.9 mg Zn L−1) significantly increased As accumulation in Pteris vittata fronds when compared to 50 μM Zn (∼3.3 mg Zn L−1). It is important to note that the interaction between Zn and As in natural systems is not well understood, and outcomes can vary depending on a number of factors (Kader et al. 2017). To comprehend the mechanisms underlying the promotion of As accumulation under elevated Zn concentrations in irrigation water, even at relatively low concentrations as observed in this study, additional research is required.
The significant increases in the EDI values of As, Zn, and Mo indicate that elevated levels of ZnO NPs in the irrigation water result in increased consumption of these elements via rice. Notably, the EDI levels of all trace elements examined in this study were below the levels of concern for adverse health effects, indicating that exposure to a single element poses no immediate health risk. However, the elevated HI values when rice plants were exposed to ZnO NPs and ZnSO4 in the irrigation TWW indicate an increased cumulative risk from exposure to multiple trace elements, reflecting the additional metal burden introduced through the reuse of TWW containing ZnO NPs or ZnSO4. This distinction is crucial for accurately interpreting the potential environmental and health impacts of using MNPs in agricultural practices. Among all the examined elements, As was the most significant contributor. The presence of As in rice grains raises concerns about possible health risks to consumers (Al-Saleh & Abduljabbar 2017; Karagas et al. 2019). Although the concentrations tested in this study complied with current regulations, the high HI values observed suggest that these regulations may not adequately protect against cumulative health risks associated with multiple trace elements. Indeed, the findings of this study support the need for revising existing standards to reflect the complex interactions and bioaccumulation potential of metal-based NPs. Therefore, measures should be taken to reduce the concentrations of this toxic element to ensure the safety and quality of rice and reduce potential health risks. It is crucial to acknowledge that this study provides important insights into the immediate health risks associated with consuming rice irrigated with TWW containing ZnO NPs. For a comprehensive understanding of the long-term effects and implications of exposure to trace elements, additional research and monitoring are required.
This study highlights the urgent need for diligent management of MNP concentrations in TWW used for irrigation due to their potential to impact crop quality and safety. In Japan, where government initiatives have increasingly promoted the reuse of TWW and other sewerage system resources for agriculture, this research aligns with national efforts to reduce reliance on imported agricultural inputs and enhance the use of local renewable resources (Tran et al. 2019; Phung et al. 2020; Takeuchi & Tanaka 2020). Japan's regulatory focus on preventing and controlling exposure to nanomaterials, rather than merely reporting and registration, encourages innovation and broad acceptance of the use of nanomaterials in various industries (Nasu & Faunce 2013). However, regulatory gaps remain concerning the fate of MNPs in agricultural settings. The transition to using sewage-derived resources for crop fertilization has raised concerns about the impacts of emerging contaminants, including MNPs, found in wastewater and treated effluents (Phung et al. 2022; 2023a). Current regulations lack specific guidelines on the presence of MNPs in TWW and their reuse in agriculture (Takeuchi & Tanaka 2020; Phung et al. 2022; 2023a).
To mitigate risks associated with MNPs, we recommended implementing periodic monitoring of MNP levels in irrigation water and systematic soil health assessments to prevent harmful accumulation and maintain crop health and productivity. Additionally, our findings advocate for the urgent need to establish robust regulatory frameworks that manage MNP levels in wastewater more effectively. Integrating advanced NP removal technologies, such as membrane filtration, adsorption techniques, and advanced oxidation processes, could significantly enhance the removal efficiency of MNPs, thus minimizing environmental discharge risks. Furthermore, regulatory bodies must update existing wastewater discharge standards to specifically address MNP pollution. This update should include more stringent monitoring requirements and the establishment of precise limits for MNP concentrations in TWW based on their observed impacts on crop and soil health. Those standards will clarify regulatory pathways for wastewater treatment facilities and ensure that agricultural practices using TWW remain safe and sustainable.
This study was limited to ZnO NP contamination in TWW and did not investigate the potential presence and interactions of other types of MNPs that may be present in TWW simultaneously. Future research should examine a broader range of MNPs that are commonly found in wastewater systems. In addition, the study was primarily concerned with the short-term effects of consuming rice with elevated levels of trace elements. Understanding the chronic health effects on human populations is impossible without long-term surveillance and epidemiological research. Furthermore, it is important to note that the study was conducted in a laboratory under controlled conditions, which may not reflect actual agricultural practices and environmental conditions. Validating the findings and assessing their applicability in actual field settings requires extensive field research that considers the complexities of agricultural systems, such as differences in soil types, crop management practices, and irrigation methods. Addressing these limitations and conducting additional research will lead to a more comprehensive understanding of the potential risks associated with the presence of MNPs in wastewater and their impact on food safety and human health.
CONCLUSIONS
This study elucidated the intricate effects of ZnO NPs in irrigation TWW on rice plants. ZnO NPs at concentrations of 2 and 5 mg L−1 resulted in increases of approximately 30 and 50% in Zn accumulation in rice grains, respectively. Additionally, ZnO NPs significantly enhanced the uptake of macronutrients and micronutrients, thereby improving the nutritional quality of rice compared to control conditions. However, a pivotal finding was the two-fold increase in As levels in rice grains at these concentrations, which critically elevated the HI values beyond the safe threshold (HI > 1), presenting serious food safety concerns. This marked accumulation of toxic metals underscores the inadequacies in current environmental regulations and highlights the pressing need for updated standards regulating effluent discharge and the agricultural reuse of wastewater. This study emphasizes the importance of diligently managing ZnO NP levels in TWW to protect crop health, ensure public safety, and promote sustainable agricultural practices.
ACKNOWLEDGEMENTS
We thank the Bureau of Sewerage System, Tsuruoka City Government for providing TWW for our experiment.
FUNDING
This research was supported by the Environment Research and Technology Development Fund (JPMEERF20233005) of the Environmental Restoration and Conservation Agency provided by the Ministry of the Environment of Japan.
AUTHOR CONTRIBUTIONS
S.D.A. investigated the article, analyzed the data, and wrote the original draft. L.D.P. conceptualized the study, performed the methodology, wrote the original draft, and reviewed and edited the article. Y.S. carried out the methodology. A.K. acquired funding. T.W. acquired funding, conceptualized the study, and supervised the article.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.