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Article

Tracking Human Exposure to DPG and Its Derivatives: Wastewater and Urine Analysis in Guangzhou, China

by
Mei Wang
1,
Hao Wang
2,
Jinfan Chen
1,
Shaoyu Tang
3,
Lipeng Liang
1,
Luning Cai
1,
Yexia Qin
1,* and
Xiaofei Song
1,*
1
School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
2
Department of Chemistry and Material Science, Guangdong University of Education, Guangzhou 510800, China
3
Research Center for Eco-Environmental Engineering, School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan 523808, China
*
Authors to whom correspondence should be addressed.
Water 2025, 17(8), 1130; https://doi.org/10.3390/w17081130
Submission received: 13 March 2025 / Revised: 7 April 2025 / Accepted: 9 April 2025 / Published: 10 April 2025
(This article belongs to the Section Water and One Health)
Browse Figures
Versions Notes

Abstract

:
Tire additives, extensively utilized as industrial raw materials, may enter aquatic environments through various pathways during production, usage, or disposal processes. Research has shown that these additives pose potential threats to human health. However, the information regarding human exposure to 1,3-diphenylguanidine (DPG), 1,3-di-o-tolylguanidine (DTG), and 1,2,3-triphenylguanidine (TPG) (collectively referred to as DPGs) remains limited. The objective of this research was to evaluate human exposure to DPG and its derivatives by analyzing urine and wastewater samples. DPG, DTG, and TPG were frequently detected in urine samples, with median concentrations of 0.19, 0.06, and 0.03 ng/L, respectively. The median urinary concentration of DPG was significantly higher in children than in the general population (p < 0.05). Nevertheless, higher concentrations of DPGs were detected in wastewater, with median values of 20.7 ng/L (DPG), 0.13 ng/L (DTG), and 0.85 ng/L (TPG). The per capita mass loads of ∑DPGs in wastewater treatment plants (WWTPs) were significantly higher on weekdays than weekends, whereas domestic WWTPs exhibited slightly lower average loads on weekdays compared to weekends. Additionally, urine–wastewater collaborative monitoring revealed that urinary excretion contributed only 28% to the total mass load of ∑DPGs in municipal wastewater, indicating it is not the main source in southern China. Consequently, the wastewater-based epidemiology (WBE) approach based on the analysis of parent compounds is unsuitable for assessing human exposure to DPGs. These results aid in developing an efficient surveillance system for understanding human exposure trends to DPGs.

1. Introduction

1,3-Diphenylguanidine (DPG), 1,3-di-o-tolylguanidine (DTG), and 1,2,3-triphenylguanidine (TPG) are widely used in industries, including rubber manufacturing, biology, and medicine [1,2,3]. These chemicals are also commonly found in construction materials, drinking water pipes, leather products, furniture, flooring, toys, footwear, rubber gloves, and electronic devices [4,5,6]. DPG, DTG, and TPG are additionally employed as tire additives and have been classified as emerging contaminants. DPGs are gradually released into the environment through tire wear, aging, and leaching during use, raising concerns about potential exposure. Environmental monitoring studies have confirmed the pervasive presence of DPGs across multiple matrices, including aquatic systems [7], urban air [8], and indoor dust [3], suggesting that human exposure occurs via contaminated drinking water and airborne particle inhalation. Toxicological investigations have identified DPG as a neurotoxic and endocrine-disrupting agent [9], DTG as a reproductive and developmental toxicant [10], and TPG as a potential inducer of atopic dermatitis [5].
The Organization for Economic Cooperation and Development (OECD) designates DPG as a high-production-volume chemical, with North America, Europe, and Asia-Pacific regions collectively accounting for 85% of global consumption [11]. Despite this widespread use, tire additives currently operate within a minimally regulated framework, creating substantial uncertainties in exposure risk assessment and exacerbating potential public health impacts. This regulatory gap highlights the urgent need for comprehensive exposure studies to understand human exposure to tire additives in order to inform the development and refinement of relevant regulatory policies and to strengthen the regulation of tire production and use.
Human biomonitoring (HBM), which involves quantifying parent substances and/or their metabolites in a variety of biological samples, such as hair, urine, blood, and serum, is widely used to measure human exposure [12,13,14,15]. However, despite extensive research on tire additives, urine excretion data remain underutilized for evaluating exposure to specific additives, particularly DPG, DTG, and TPG. Wastewater-based epidemiology (WBE), a complementary approach to HBM, has demonstrated efficacy in monitoring the consumption of substance including alcohol, caffeine, nicotine, illicit drugs, and pharmaceuticals [16,17,18,19]. The WBE methodology operates on the principle that consumed substances or their metabolites are metabolized and partially excreted into sewage systems, ultimately reaching wastewater treatment plants. Through the quantification of substance concentrations in influent wastewater combined with flow rate measurements and service population data, population-level consumption can be extrapolated [20]. This technique has been successfully applied to assess exposure to phthalate plasticizers, bisphenols, drugs, and other chemicals [21,22,23,24]. Notably, despite being the world’s leading recycled tire producer and a major consumer of rubber products, China lacks systematic studies assessing DPG, DTG, and TPG exposure via integrated urine–wastewater analysis frameworks [25,26].
Therefore, this research aims to accomplish the following: (1) measure the levels and dispersion of DPG, DTG, and TPG in human urine and wastewater, (2) investigate the mass loads of DPG, DTG, and TPG in municipal wastewater, and (3) assess the correlation between DPG, DTG, and TPG concentrations in urinary and wastewater matrices and explore the applicability of the wastewater-based epidemiology approach based on parent compounds.

2. Materials and Methods

2.1. Chemicals and Reagents

DPG, DTG, and TPG were identified as target compounds in this study, with isotopically labeled DPG (DPG-d10) serving as the internal standard. Detailed specifications for these compounds are provided in Table S1. DPG and DPG-d10 were purchased from Sigma-Aldrich (St. Louis, MO, USA), while DTG and TPG were acquired from Toronto Research Chemicals (Toronto, ON, Canada). HPLC-grade methanol supplied by Merck (Darmstadt, Germany) was utilized for chromatographic analyses. Mobile phase additives including formic acid and ammonium acetate were obtained from MACKLIN (Shanghai, China). Stock solutions of all target chemicals were prepared in methanol and stored at −20 °C prior to experimental use.

2.2. Study Area and Sample Collection

In September 2023, systematic urine and wastewater sampling campaigns were conducted within the same administrative district of Guangzhou, southern China. A total of 320 urine samples were collected by Guangzhou Medical University from healthy participants with no history of occupational exposure to tire additives. The cohort was stratified into two demographic groups: children (n = 73) and general adults (n = 247). To minimize potential confounding effects from migration patterns, all human urinary samples were exclusively obtained from individuals with sustained residential history in Guangzhou (≥3 consecutive years). The study protocol received formal ethical approval from the Ethics Committee of Guangzhou Medical University, and written informed consent was obtained from all participants prior to sample collection (approval number: S-2021-043).
Wastewater sampling commenced within one week of urine collection. Six municipal wastewater treatment plants (WWTPs) in Guangzhou were selected for influent sampling (see the operational parameters detailed in Table S2). A flow-proportional 24-h composite sampling methodology was employed at the influent distribution wells of each facility and implemented across seven consecutive days. Immediately following collection, samples were acidified with 2 M hydrochloric acid to achieve pH 2.0 ± 0.2, then promptly transported to the laboratory and kept in a freezer at −80 °C until further analysis.

2.3. Sample Pretreatment

Prior to pretreatment, urine samples were systematically pooled into 20 composite samples stratified by participant age and gender, with each pool containing 16 individuals (detailed stratification criteria are provided in Supporting Information). The pretreatment protocol was modified from established methodologies [27]. After briefly thawing at room temperature, 1 mL of urine sample was mixed with 25 µL of DPG-d10 solution (1 µg/mL, internal standard). The mixture was vortexed for homogenization and allowed to equilibrate for 30 min. Oasis HLB cartridges were preconditioned sequentially with methanol and ultrapure water before sample loading. Post-application, cartridges underwent vacuum drying (10 min) followed by elution with 3 mL of HPLC-grade methanol. The eluate was concentrated to near-dryness under a gentle nitrogen stream. Finally, the dried residue was reconstituted in 500 µL of methanol and transferred to chromatographic vials for instrumental analysis.
Pretreatment of water samples were carried out according to a previous study [28]. Thawed aqueous samples (50 mL) were sequentially filtered through glass cellulose and 0.2 µm nitrocellulose membrane. The filtrate was spiked with 25 µL of the internal standard, while retained particulates underwent ultrasonic extraction (10 mL of methanol followed by 5 mL of methanol/5 mL of 0.1% formic acid aqueous solution). Combined extracts were adjusted to 6.5% methanol (v/v) before undergoing identical solid-phase extraction (SPE) procedures as urinary specimens.

2.4. Chemical Analysis

Chromatographic separation was achieved using an Agilent 1290 Infinity ultra-performance liquid chromatography (UPLC) system (Agilent Technologies, Santa Clara, CA, USA). Mass spectrometric analysis was conducted using an Agilent 6410 triple quadrupole system equipped with an electrospray ionization (ESI) source. Data acquisition took place in the positive-ion multiple reaction monitoring (MRM) mode. Specific MRM parameters can be found in Table S3. Chromatographic separation was carried out under controlled conditions at 45 °C, utilizing a C18 guard column in conjunction with a reversed-phase C18 analytical column (Eclipse XDB-C18, 5 µm, 4.6 × 150 mm, Agilent Technologies).
The mobile phase used in this method consisted of two components: Solution A (5 mM ammonium acetate and 0.1% formic acid in water), and Solution B (0.1% formic acid in methanol). A gradient elution profile was implemented as follows: initial 5% B (0–1 min), linear increase to 50% B (1–4 min), progression to 100% B (4–17 min), isocratic hold (17–20 min), return to initial conditions (20–20.1 min), and a 2.4 min equilibration period. The flow rate was maintained at 0.4 mL/min with a 5 µL injection volume.

2.5. Quality Assurance and Quality Control (QA/QC)

Regression coefficients (R values) exceeding 0.999 were obtained for all analytes in calibration curves that were prepared using pooled urine and methanol as solvents. Quantitative analysis of DPG, DTG, and TPG was performed using the internal standard method. To examine background contaminants, residues, and instrumental features, a process blank, solvent blank, and 10 µg/L mixed standards were progressively performed for every 10 injections during the testing of each batch of samples. All blank values (Table S4) were subtracted from the final reported concentrations. Additionally, a procedure for determining matrix blanks was implemented when analyzing urine samples in order to rule out matrix effects. For each compound, the limit of quantification (LOQ) was 10 times the standard deviations (SDs) of 7 repeated injections of the lowest concentration of the standard curve. The recoveries of the method were obtained by adding 1, 10, and 50 µg/L of standards to the pooled urine and effluent samples, respectively. Tables S5 and S6 display more details on the QA/QC of the target compounds.

2.6. Statistical Analysis

Non-detected analyte concentrations (below method detection limits) were imputted as half the corresponding LOQ values following established protocols [29]. The statistical analysis was conducted using the SPSS 19.0 software program, with graphical visualizations generated through Origin version 2022. Statistical significance was established at α = 0.05 (two-tailed) for all hypothesis testing procedures.

2.7. Calculation Methods

The assessment methodology for determining the contribution of DPG, DTG, and TPG in urine to wastewater was based on previous studies [30]. The per capita mass loads of DPG, DTG, and TPG excreted in urine (Eurine; ng/p/d) were calculated using the following Equation (1):
E urine = C i × V
where Ci denotes the concentration of the target compound in the urine. V denotes the daily urinary excretion volume of the body (L/p/d), established at 1.57 (L/p/d) for adults and 0.66 (L/p/d) for children [31,32].
The calculation of the per capita mass loads of DPG, DTG, and TPG in wastewater (denoted as Ewastewater; ng/p/d) was performed utilizing Equation (2), as detailed below.
E w a s t w a t e r = C i × Q P
where Q is the daily wastewater flow (m3/d) and P is the number of people served by each WWTP.
Equation (3) was utilized to compute the percentage contribution of DPG, DTG, and TPG in urine to wastewater. This metric can provide insight into whether human excretion is a significant source of DPG, DTG, and TPG in wastewater.
C o n t r i b u t i o n = E u r i n e E w a s t w a t e r

3. Results and Discussion

3.1. DPG, DTG, and TPG in Urine

3.1.1. Occurrence of DPG, DTG, and TPG in Urine

The concentration levels of DPG, DTG, and TPG in human urine are shown in Table 1. Detection frequencies (DFs) of 94%, 92%, and 83% were recorded for DPG, DTG, and TPG, respectively. The target analytes were measured at a mean concentration of 0.45 ng/L (range: 0.004–43.9 ng/L), with DPG demonstrating significantly higher median concentrations (0.19 ng/L) than its derivatives (0.06 ng/L for DTG and 0.03 ng/L for TPG). These findings not only confirm the pervasiveness of human exposure to tire additives but also highlight the higher exposure levels to DPG relative to the other two compounds. Consistent with this trend, environmental media from diverse locations demonstrate a similar pattern. For instance, elevated DPG levels relative to its derivatives have been documented in Japanese lake water [33], Chinese wastewater [7], urban surface runoff [34], indoor dust collected in eleven countries [3], and sewage [35] and soil [36] in the U.S. Two physicochemical factors are proposed to drive this pattern: (1) DPG’s lower logKow (logKow = 2.78 vs. 3.88–5.04 for derivatives) enhances aquatic mobility, and (2) DPG’s current production and usage volumes exceed those of the other two compounds, resulting in a more extensive environmental distribution than DTG and TPG.
Notably, recent studies have shown that exposure to DPGs can lead to various detrimental effects such as neurotoxicity, endocrine disruption, reproductive toxicity, and genotoxicity [9,37,38]. In view of the widespread presence of DPG in the environment and human urine, along with the adverse effects it exhibits on health and ecosystems, it is strongly recommended that governments implement stringent regulations to oversee and control the production, use, and disposal of DPG to minimize its potential harm.

3.1.2. Gender- and Age-Specific Distinctions

Gender-specific variations in urinary concentrations of DPG, DTG, and TPG are presented in Figure 1A. Median concentrations of all three compounds in male subjects were consistently higher than in female subjects, though this difference did not reach statistical significance. This observation aligns with previous research findings reported in the literature [39], further confirming the significant role of gender as a critical determinant influencing DPG exposure levels in vivo. A potential contributing factor could be the greater involvement of males in occupations associated with the production or application of rubber-based goods, encompassing roles within manufacturing, construction, and the maintenance of industrial settings. As a result, males may be exposed to elevated levels of DPG, DTG, and TPG due to their inhalation of fumes or particles, dermal contact, or ingestion of contaminated substances [39].
To investigate the correlation between age and the concentration of DPGs, the subject population was divided into 5 groups according to age: 0–15 years, 20–40 years, 40–60 years, 60–80 years, and >80 years (Figure 1B). A notable phenomenon was identified in the present investigation: significantly higher median DPG concentrations (3.32 ng/L) were observed in children (0–15 years) compared to the other four age groups (p < 0.01). The potential reason may be that DPG is widely used in the production of toys and other children’s products, leading to the direct exposure of children to higher concentrations of DPG through contact with these products [5]. Alternatively, the observed higher concentration of DPG in children’s urine compared to adults could potentially result from age-related differences in metabolic rates. Specifically, children’s elevated metabolic activity may enhance the biotransformation and subsequent urinary excretion of DPG, leading to its increased accumulation in urine. No significant age-dependent correlations were identified for urinary DTG and TPG concentrations (p > 0.05), suggesting that DTG and TPG exposure levels may be regulated by multifactorial determinants rather than chronological age alone.

3.2. DPG, DTG, and TPG in Wastewater

3.2.1. Occurrence of DPG, DTG, and TPG in Wastewater

The occurrence profiles of the three tire additives (DPG, DTG, and TPG) in wastewater were systematically characterized across six WWTPs (Table 2). DPG, DTG, and TPG were detected in 100%, 40%, and 45%, respectively, of all wastewater samples, with median concentrations of 20.7, 0.13, and 0.85 ng/L, respectively. The results indicate that among the three target compounds, DPG remains the most predominant contaminant in wastewater. This trend is consistent with global wastewater monitoring data, though geographical variations exist. The concentration of DPG observed in this study is comparable to levels reported in an earlier study in Japan (10–100 ng/L) [33]. However, these concentrations were slightly lower than the median levels detected in Chinese and U.S. wastewater treatment plants (Chinese: 137 ng/L, U.S.: 86.8 ng/L) [7,35]. Several factors may contribute to this disparity, including sampling locations, seasonal variations, and specific wastewater treatment processes. Additionally, this study compared DPG concentrations in wastewater with those measured in the surface waters of various regions. The DPG levels detected in this investigation fell within the following global ranges: 3.47–1894 ng/L in the Pearl River Estuary [7], 5–540 ng/L in the U.S. [2], 220 ng/L in Canada [8], and 13–1079 ng/L in Australian rivers [40]. These data provide further evidence of regional and environmental disparities in DPG concentrations. Notably, the DTG and TPG concentrations are consistent with those reported by Li et al. [35] (median: DTG: 2.12 ng/L, TPG: 0.46 ng/L), indicating that both compounds exhibit relatively low environmental prevalence. This pattern suggests limited opportunities for human exposure to these derivatives compared to DPG.
The concentration contribution rates of the three target compounds across six wastewater treatment plants were calculated, and the results are illustrated in Figure 2. The most prevalent compound was DPG, making up 76.5% of the overall concentration, with DTG following at 14.4% and TPG accounting for 9.1% of the total. These findings align with the global contamination patterns reported by Li et al. [3], whose multicountry monitoring of dust revealed that DPG accounts for 87% of concentrations of ∑DPGs across eleven nations. This chemical hierarchy is further corroborated by U.S. wastewater surveillance data, in which DPG constitutes >96% of ∑DPGs in both influent and effluent streams [35]. The observed consistency across geographical regions and environmental media can be attributed to the substantially higher global consumption of DPG. The widespread distribution of DPG in the environment has been driven by its extensive usage, as evidenced not only by its presence in wastewater samples but also by its detection in dust specimens collected globally. Given the pervasive occurrence of DPG in the environment and its potential for long-range transport, a systematic ecotoxicological risk assessment is urgently required. Such evaluations are deemed critical for understanding the ecological impacts of DPG and for developing effective environmental management strategies.
A comparison of the concentrations of DPGs performed across six WWTPs revealed significant spatial variability (range: 0.13–33.2 ng/L; median: 5.48 ng/L). WWTP1 exhibited the highest median concentration of ∑DPGs (5.53 ng/L), followed sequentially by WWTP3 (5.50 ng/L), WWTP2 (5.49 ng/L), WWTP5 (4.51 ng/L), WWTP4 (4.47 ng/L), and WWTP6 (0.13 ng/L). A poor correlation (R = 0.83, p > 0.05) was observed between the study population and the concentration of ∑DPGs in wastewater treatment plants, suggesting that there are other sources of DPGs in wastewater. Notably, WWTP2 and WWTP3 (receiving 5% industrial effluent blended with municipal sewage) demonstrated significantly elevated DPG concentrations compared to exclusively domestic WWTPs. A vital component in industrial production systems, DPG has been found to persist in manufacturing effluents at notably high concentrations [35]. Therefore, the concentrations of DPG in the six WWTPs may originate from industrial wastewater inputs.

3.2.2. Per Capital Mass Loads of DPGs in Wastewater

The per capital mass loads of the three analytes were calculated using influent concentrations and daily flow rate data from WWTPs (Table 3). DPG exhibited the highest per capital mass load (7.85 ng/p/d), followed by DTG (1.44 ng/p/d) and TPG (0.91 ng/p/d). While the per capital mass loads of DTG and TPG aligned with recent U.S. measurements, the per capital mass load of DPG was two orders of magnitude lower [35], suggesting an upward trend in industrial DPG utilization in recent years. Comparative analysis revealed that the per capital mass loads of ∑DPGs were lower than other tire additives. The ∑DPGs were three orders of magnitude lower than benzotriazole and its derivatives (BTRs), which range from 17.1–43.4 mg/d/1000 inhabitants in India [41] and 0.95–55 mg/d/1000 inhabitants in Sri Lanka [42]. Similarly, benzothiazole and derivatives (BTHs) have been reported at 0.78–17 mg/d/1000 inhabitants in Sri Lanka [42], and 6PPDs (N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine and 6PPD-quinone) have been recorded at 22.7 mg/d/1000 inhabitants in the U.S. [35]. Existing research indicates that tire additives in wastewater exhibit per capita mass loads that are higher than or comparable to those of other emerging contaminants, including bisphenol compounds (3.5–416 μg/person/day) [30], organic UV filters (0.36–1.27 mg/person/day) [43], and phthalate metabolites (10–1000 mg/day per 1000 people) [44]. Despite these substantial environmental burdens, no internationally standardized safety thresholds have been established for tire additives. This regulatory gap introduces significant uncertainties in risk assessment and management, necessitating urgent collaborative efforts between scientific institutions and policymakers to develop evidence-based exposure limits and mitigation strategies under frameworks such as the Stockholm Convention.
Samples were collected from six WWTPs over seven consecutive days, providing comprehensive insights into weekly spatial-temporal variations. Significant spatial heterogeneity in per capital mass loads was observed across the WWTPs, with domestic wastewater loads ranging from below detection limits to 14.0 ng/p/d. WWTP3 demonstrated the highest mass load of ∑DPGs (104 ng/p/d), followed sequentially by WWTP6 (76.7 ng/p/d), WWTP1 (73.5 ng/p/d), WWTP4 (72.4 ng/p/d), WWTP5 (65.4 ng/p/d), and WWTP2 (43.4 ng/p/d). The elevated per capital mass load of ∑DPGs at WWTP3 may be attributed to the comparably elevated concentration of ∑DPGs at this plant.
Notably, temporal variations in the per capita mass loads of ∑DPGs were observed across the six WWTPs. As shown in Figure 3, WWTP2 exhibited 2.5 times the load of ∑DPGs during weekdays compared to weekends (p < 0.01), revealing significant weekday–weekend divergence. Similarly, WWTP3 demonstrated a 1.3-fold elevated load of ΣDPGs on weekdays. However, this pattern was not universally consistent: WWTP1, WWTP4, and WWTP5 showed marginally higher weekend loads (0.9–1.0 times weekday values), though these differences lacked statistical significance (p > 0.05). Such heterogeneous temporal patterns suggest differential wastewater source profiles across service areas. The observed weekday surges in the loads of ΣDPGs at WWTP2 and WWTP3 correlated strongly with influent composition shifts. Given the assumption that DPGs detected on weekends primarily originated from domestic wastewater, the contribution of industrial wastewater to DPGs was estimated to range from 71% to 88%, thereby indicating that industrial sources constituted a major contributor to DPGs in wastewater. In contrast, domestic-dominated WWTPs (WWTP1/4/5/6) exhibited minimal weekday–weekend variability (load ratios: 0.9–1.0), with slight weekend elevations potentially attributable to an increased leaching of DPG-containing household products—including PVC flooring, protective gloves, and synthetic footwear—during cleaning activities [4,5,6].
These findings collectively underscore the dual origins of DPGs within urban wastewater systems, where industrial effluents dominate in mixed-source treatment facilities while household product usage generates measurable background loads. Given this dual contribution paradigm, conducting more in-depth investigations into the specific sources of DPGs in Guangzhou’s aquatic environment assumes critical importance. The research outcomes not only reaffirm the role of industrial wastewater as the primary contributor to DPG contamination in municipal sewage but also reveal the non-negligible contribution from daily household products to the overall pollutant load. Consequently, effective management of DPG pollution in urban wastewater necessitates a comprehensive consideration of both industrial discharge patterns and residential consumption behaviors when formulating targeted mitigation strategies and implementation measures. This integrated approach ensures that source control mechanisms address both production-end emissions and consumption-driven pollutants to optimize the entire wastewater management framework.

3.3. Contribution of DPG, DTG, and TPG in Urine to Their Mass Loads in Wastewater

Within the integrated urine–wastewater monitoring framework, the contribution of urinary excretion to wastewater contamination was assessed through comparative analysis of mass load ratios between biological and wastewater matrices (Table 4). Urinary excretion was found to contribute only 28% to the total mass load of ∑DPGs in municipal wastewater, with individual contributions of 11% for DPG, 11% for DTG, and 6.2% for TPG. This finding indicates that 72% of DPG-related compounds in Guangzhou’s wastewater system originate from non-excretory pathways. Industrial discharges (e.g., rubber manufacturing effluents) and tire wear particle runoff are likely dominant contamination sources [34,35]. The limited urinary contribution to wastewater ∑DPGs challenges the validity of WBE in assessing human exposure to tire additives when employing parent compound analysis. Recent applications of WBE have successfully monitored pesticide metabolites, phthalate derivatives, organophosphate flame retardants, and plasticizers. The methodology works well for compounds with urinary excretion rates higher than 60%, according to validation studies [45,46]. However, the substantial non-excretory origins of industrial chemicals like DPGs (evidenced by 71–88% industrial contributions in mixed-source WWTPs) suggest that sole reliance on parent compound analysis may lead to significant exposure overestimations.
These findings collectively demonstrate the necessity of source-specific validation when applying WBE to industrial chemicals. For DPGs and analogues, complementary industrial emission inventories and metabolite-based biomarker approaches should be integrated with conventional WBE protocols to improve exposure assessment accuracy.

4. Conclusions

This study detected DPG, DTG, and TPG in 89% of human urine samples, with median concentrations of 0.19 ng/L, 0.06 ng/L, and 0.03 ng/L, respectively. DPG was identified as the predominant contaminant in human urine. Compared to females, males exhibited consistently higher median urinary concentrations of DPG, DTG, and TPG, primarily due to their greater occupational involvement in rubber product manufacturing and related industries. Consequently, males may be exposed to elevated levels of DPGs through their inhalation of fumes or particles, dermal contact, or ingestion of contaminated substances. Furthermore, urinary DPG concentrations in children were significantly higher than in adults (p < 0.05). This phenomenon may be attributed to the widespread use of DPG in toys and other children’s products, leading to direct exposure through contact. An alternative explanation involves age-related metabolic differences, where children’s enhanced metabolic activity may increase the biotransformation and subsequent urinary excretion of unmetabolized DPG. In contrast, urinary DTG and TPG concentrations showed no significant age-related correlations (p > 0.05), suggesting their exposure levels are regulated by multifactorial determinants beyond chronological age.
Municipal wastewater contained substantially higher concentrations of DPG, DTG, and TPG than human urine, with median values of 21.7 ng/L, 0.85 ng/L, and 0.13 ng/L, respectively. These results confirm that DPG remains the primary contaminant. Per capita mass loads of DPG, DTG, and TPG were estimated at 7.85 ng/p/d, 1.44 ng/p/d, and 0.91 ng/p/d, respectively, based on influent concentrations and daily wastewater flow rates. Spatial and temporal variations observed across six WWTPs suggest industrial wastewater may be a major source of DPGs.
Additionally, urine–wastewater collaborative monitoring revealed that urinary excretion contributed only 28% to the total mass load of ∑DPGs in municipal wastewater, with individual contributions of 11% for DPG, 11% for DTG, and 6.2% for TPG. These findings demonstrate that over 72% of DPG-related compounds in Guangzhou’s wastewater system originate from non-excretory pathways, with industrial discharges (e.g., rubber manufacturing effluents) and tire wear particle runoff likely serving as dominant contamination sources. Consequently, a WBE method based on the analysis of parent compounds is not suitable for assessing human exposure to such contaminants.

5. Study Limitations

The integrated urine–wastewater analytical framework proposed in this study provides initial insights into tire additive exposure, but complex contextual factors still need to be systematically considered. The complexity of municipal wastewater, comprising both domestic and industrial sources, creates analytical challenges. This mixed composition may obscure the statistical association between excretion levels and specific contaminant sources. In addition, a variety of factors at the population level, including occupational differences, lifestyle variations, and residential environment heterogeneity, may introduce variability in source attribution. In the future, targeted decentralized effluent sampling could be conducted for residential/industrial areas to differentiate contamination sources. In addition, further studies and comprehensive exposure assessment of more diverse populations are needed to comprehensively characterize the long-term effects of DPG and its derivatives on human health.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/w17081130/s1. Table S1. Target analytes names, abbreviations, chemical structures, chemical formula, Log Kow, and purities. Table S2. Information on the six WWTPs investigated in this study. Table S3. Target analytes, isotopically labeled internal standard, and their optimized MRM parameters. Two transitions were optimized for each analyte, one for quantification (q) and the other for confirmation (c). One transition was optimized for the internal standard. MRM parameters include precursor ion (Q1), product ion (Q3), declustering potential (DP), entrance potential (EP), collision energy (CE), collision cell exit potential (CXP), and retention time. Table S4. Concentrations of DPG, DTG and TPG in procedure blanks (ng/L). Table S5. Calibration range, curve, R2, of target chemicals by LC–MS/MS. Table S6. Summary of method performance results. References [47,48] are cited in the Supplementary Materials.

Author Contributions

M.W.: Conceptualization, Methodology, Software, Data Curation, Writing—Original Draft, and Writing—Review and Editing. H.W.: Methodology, Investigation, and Writing—Review and Editing. J.C.: Investigation, Methodology, and Writing—Review and Editing. S.T.: Writing—Review and Editing. L.L.: Methodology and Writing—Review and Editing. L.C.: Software and Methodology. Y.Q.: Methodology, Resources, Writing—Review and Editing, Supervision, and Funding Acquisition. X.S.: Methodology, Resources, Writing—Review and Editing, Supervision, and Funding Acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Key R&D Program Project of the Ministry of Science and Technology, grant number 2022YFB3807400, and was supported by the Guangdong Grassroots Science Popularization Action Plan Project, grant number GDKP 2024-3-055.

Data Availability Statement

Data will be made available on request.

Acknowledgments

We thank Zeng Feng’s team at Sun Yat-sen University for technical support.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Water 17 01130 g001
Figure 1. (A) Median concentrations (±standard deviation) of DPGs in human urine samples from male and female participants. (B) Comparison of median concentrations (±standard deviation) of DPGs in human urine samples across five age groups.
Figure 1. (A) Median concentrations (±standard deviation) of DPGs in human urine samples from male and female participants. (B) Comparison of median concentrations (±standard deviation) of DPGs in human urine samples across five age groups.
Water 17 01130 g001
Water 17 01130 g002
Figure 2. Compositional profiles of DPG, DTG, and TPG in six WWTPs.
Figure 2. Compositional profiles of DPG, DTG, and TPG in six WWTPs.
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Water 17 01130 g003
Figure 3. The difference in the mass load of ∑DPGs (total concentration of DPG, DTG, and TPG) in six WWTPs on weekdays and weekends.
Figure 3. The difference in the mass load of ∑DPGs (total concentration of DPG, DTG, and TPG) in six WWTPs on weekdays and weekends.
Water 17 01130 g003
Table 1. Occurrence and concentrations of DPG, DTG, and TPG in urine (ng/L).
Table 1. Occurrence and concentrations of DPG, DTG, and TPG in urine (ng/L).
CompoundsAverageMedianRangeDF 1LOQ
DPG1.140.190.31–43.994%0.06
DTG0.110.060.10–2.1492%0.05
TPG0.040.030.005–0.4583%0.01
Note: 1 DF: detection frequency.
Table 2. Concentrations of DPG, DTG, and TPG in wastewater collected from six WWTPs (n = 42, ng/L).
Table 2. Concentrations of DPG, DTG, and TPG in wastewater collected from six WWTPs (n = 42, ng/L).
WWTPCompoundDF 1Mean ± SDMedianMaxMin
W1DPG100%15.0 ± 2.4115.318.210.1
DTG57%4.15 ± 1.81<LOQ8.61<LOQ
TPG57%2.44 ± 1.67<LOQ5.59<LOQ
W2DPG100%24.9 ± 2.4024.829.721.7
DTG14%1.94 ± 0.660.858.45<LOQ
TPG71%3.98 ± 1.435.495.62<LOQ
W3DPG100%27.1 ± 5.0727.633.220.3
DTG43%4.25 ± 1.93<LOQ9.17<LOQ
TPG86%4.71 ± 1.875.505.50<LOQ
W4DPG100%20.8 ± 4.3820.728.016.0
DTG43%4.22 ± 1.90<LOQ8.85<LOQ
TPG43%2.42 ± 0.64<LOQ5.49<LOQ
W5DPG100%17.5 ± 4.5116.624.912.5
DTG57%5.36 ± 2.918.459.06<LOQ
TPG0<LOQ<LOQ<LOQ<LOQ
W6DPG100%20.0 ± 3.5120.923.611.9
DTG43%4.22 ± 0.90<LOQ9.17<LOQ
TPG28%1.67 ± 0.40<LOQ5.59<LOQ
AllDPG100%20.9 ± 5.7420.733.210.1
DTG40%4.02 ± 1.850.139.17<LOQ
TPG45%2.56 ± 0.680.855.62<LOQ
Note: 1 DF: detection frequency.
Table 3. Daily per capita mass loads of DPG, DTG, and TPG in wastewater (ng/p/d) 1.
Table 3. Daily per capita mass loads of DPG, DTG, and TPG in wastewater (ng/p/d) 1.
DPGDTGTPG∑DPGs 2
WWTP17.48
(5.06–9.09)		1.83
(0–4.30)		1.18
(0–2.79)		73.5
WWTP25.14
(4.49–6.14)		0.25
(0–1.74)		0.81
(0–1.16)		43.4
WWTP311.4
(8.54–14.0)		1.58
(0–3.85)		1.97
(0–2.31)		104
WWTP47.16
(4.82–7.84)		1.29
(0–3.05)		0.81
(0–1.89)		64.8
WWTP57.27
(5.19–10.3)		2.07
(0–3.76)		<LOQ65.4
WWTP68.65
(5.15–10.2)		1.61
(0–3.96)		0.68
(0–2.42)		76.7
All 37.85
(4.49–14.0)		1.44
(0–4.30)		0.91
(0–2.79)		428
Notes: 1 Average concentrations (minimum and maximum in brackets) are shown for all samples. 2 Indicates the sum concentration of DPG, DTG, and TPG. 3 The sum of all six WWTPs.
Table 4. Comparison of per capita urinary excretion of chemicals and per capita daily input mass loads into wastewater (ng/p/d).
Table 4. Comparison of per capita urinary excretion of chemicals and per capita daily input mass loads into wastewater (ng/p/d).
CompoundUrinary ExcretionDaily Input into WastewaterContribution Rate
DPG0.898.011%
DTG0.161.411%
TPG0.0560.916.2%
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Wang, M.; Wang, H.; Chen, J.; Tang, S.; Liang, L.; Cai, L.; Qin, Y.; Song, X. Tracking Human Exposure to DPG and Its Derivatives: Wastewater and Urine Analysis in Guangzhou, China. Water 2025, 17, 1130. https://doi.org/10.3390/w17081130

AMA Style

Wang M, Wang H, Chen J, Tang S, Liang L, Cai L, Qin Y, Song X. Tracking Human Exposure to DPG and Its Derivatives: Wastewater and Urine Analysis in Guangzhou, China. Water. 2025; 17(8):1130. https://doi.org/10.3390/w17081130

Chicago/Turabian Style

Wang, Mei, Hao Wang, Jinfan Chen, Shaoyu Tang, Lipeng Liang, Luning Cai, Yexia Qin, and Xiaofei Song. 2025. "Tracking Human Exposure to DPG and Its Derivatives: Wastewater and Urine Analysis in Guangzhou, China" Water 17, no. 8: 1130. https://doi.org/10.3390/w17081130

APA Style

Wang, M., Wang, H., Chen, J., Tang, S., Liang, L., Cai, L., Qin, Y., & Song, X. (2025). Tracking Human Exposure to DPG and Its Derivatives: Wastewater and Urine Analysis in Guangzhou, China. Water, 17(8), 1130. https://doi.org/10.3390/w17081130

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