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. 2023 Jun 27;57(28):10319–10330. doi: 10.1021/acs.est.2c09602

Release Behavior of Liquid Crystal Monomers from Waste Smartphone Screens: Occurrence, Distribution, and Mechanistic Modeling

Qianqian Jin †,‡, Jianxin Yu †, Yinzheng Fan †, Yuting Zhan †, Danyang Tao §, Jingchun Tang ∥, Yuhe He †,‡,*
PMCID: PMC10357588  PMID: 37369363

Abstract

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Liquid crystal display (LCD) screens can release many organic pollutants into the indoor environment, including liquid crystal monomers (LCMs), which have been proposed as a novel class of emerging pollutants. Knowing the release pathways and mechanisms of LCMs from various components of LCD screens is important to accurately assess the LCM release and reveal their environmental transport behavior and fate in the ambient environment. A total of 47, 43, and 33 out of 64 target LCMs were detected in three disassembled parts of waste smartphone screens, including the LCM layer (LL), light guide plate (LGP), and screen protector (SP), respectively. Correlation analysis confirmed LL was the source of LCMs detected in LGP and SP. The emission factors of LCMs from waste screen, SP, and LGP parts were estimated as 2.38 × 10–3, 1.36 × 10–3, and 1.02 × 10–3, respectively. A mechanism model was developed to describe the release behaviors of LCMs from waste screens, where three characteristics parameters of released LCMs, including average mass proportion (AP), predicted subcooled vapor pressures (PL), and octanol–air partitioning coefficients (Koa), involving coexistence of absorption and adsorption mechanisms, could control the diffusion-partitioning. The released LCMs in LGP could reach diffusion-partition equilibrium more quickly than those in SP, indicating that LCM release could be mainly governed through SP diffusions.

Keywords: liquid crystals monomers, emission factor, diffusion-partitioning, environmental modeling, release mechanism

Short abstract

The diffusion-partitioning behaviors of LCMs released from various components of waste smartphone screens were modeled. The proposed release pathways and mechanisms provide valuable insights into the environmental transport behavior and fate of LCMs.

1. Introduction

Liquid crystal monomers (LCMs) are essential substances used in the manufacture of liquid crystal display (LCD) panels, which are key components of many commercial and household electronic devices (e-devices), such as smartphones, laptops, televisions, and advertising screens.1−3 LCMs are usually applied as a mixture of 10–20 compounds at approximately 1 mg/cm2 on the LCD panel.1−3 The occurrences and transports of LCMs in the environment are closely associated with the production, usage, and disposal of LCD panels,4,5 which might pose significant health hazards to general and occupational recipients.6−8 Up to now, more than 90 LCMs have been detected in various environmental samples, including indoor and outdoor dust, sediments, landfill leachates, airborne particles, aquatic organisms, and human skin wipes.9−14 The current global release of LCMs from waste computers and television LCD panels was estimated to be 1.07–107 kg/year.2 With the rapid increase of demands on new e-devices, it is expected that the levels of LCMs released into the environment will continuously grow, bringing increasing environmental and health concerns to exposed animals and humans.13,15

A typical LCM consists of a backbone structure and side chains containing biphenyl, cyclohexylphenyl, bicyclohexyl, and diphenyl derivatives moieties equipped with various functional groups of alkoxyl, cyclohexyl, cyano, fluorine, and bromine.4,9 These chemical moieties potentially contribute to high values of n-octanol–water partition coefficient (KOW) and octanol–air partition coefficient (Koa), resulting in bioaccumulative tendency and long-range transport potentials of LCMs.16,17 The persistent and bioaccumulative properties of LCMs have been verified by the occurrence of LCMs in environmental samples collected far away from emission sources, as well as via experimental evaluation and quantum chemical calculation.12,13,18,19 However, the current understanding of the nature, extent, and magnitude of LCM pollution is still very limited. For example, information on the environmental transport behavior and the fate of LCMs escaping from their sites of application remains unclear.

Recently, the gas–particle partitioning behavior for most LCMs in ambient air was investigated based on field-measured data collected from LCD dismantling workshops.11 Liu et al. implied that LCD screens might be an important source of indoor volatile organic compounds (VOCs), including LCMs, no matter whether the LCD panels were in operation or not.20 Although the emission kinetics of LCMs were explored at both elevated and room temperatures through an enclosed chamber, their emission characteristics were not well described by the predicted mass transfer model.21 A comprehensive understanding of the potential release pathways and behavior of LCMs from the source screens entering the ambient environment is urgently needed for the evaluation of LCMs released into the environment and health risk assessment of LCMs in general and occupational populations.

Herein, the objectives of this study include (1) determining compositions of released LCMs from various components of smartphone screens and estimating the corresponding emission factors (EF); (2) modeling release behaviors of LCMs to demonstrate their corresponding diffusion partitioning characteristics and proposing their potential release mechanisms and pathways entering ambient air; (3) exploring the potential relationships between released LCM levels and waste screen conditions to facilitate the development of strategies for reducing release and pertinent risk assessment. The results of this study provide new insights into the mechanistic release of these emerging chemicals of concern associated with LCD screens, benefiting the future design of preventive measures, environmental monitoring, and management of e-devices and electronic waste (e-waste).

2. Materials and Methods

2.1. Standards and Chemicals

In total, 64 LCM standard products, including 44 fluorinated LCMs (F-LCMs) and 20 nonfluorinated LCMs (NF-LCMs), were purchased from Tokyo Chemical Industry Co., Ltd. (Shanghai, China), J&K Chemical Ltd. (Shanghai, China), Aladdin Chemical Ltd. (Shanghai, China), and Bidepharm Chemical Ltd. (Shanghai, China). The detailed information of 64 target LCMs is listed in Table S1. Two standards, 3,3′,4,4’-tetrabromodiphenyl ether (13C12-BDE77) and 2,3′,4,4′,5-pentachlorobiphenyl (13C12-MBP118) obtained from Cambridge Isotope Laboratories (Massachusetts, USA) were selected as internal isotope standards. All organic solvents, including hexane, acetone, and dichloromethane (DCM), used in this study were high-performance liquid chromatography (HPLC) grade purchased from Duksan Pure Chemicals (Ansan-si, South Korea).

2.2. Waste Smartphone Screen Sample Collection and Description

A total of 35 waste smartphone screens were collected from a phone repair store in September 2021, of which seven screens were equipped with screen protectors (SP). Each waste smartphone screen was packed with clean aluminum foil, transferred to a sealing bag, and kept at −20 °C until further analysis. The information of each waste smartphone screen is provided in Table S2, including image, brand, screen display technology, screen size, broken status, and with or without SP layer.

2.3. Evaluation of LCM Release from Waste Smartphone Screens

The environmental emission test conducted in the sealed chamber could not differentiate between the involved processes, such as internal diffusion, interfacial diffusion, and/or surface sorption.22 Therefore, the test data cannot be directly used to determine the model parameters of diffusion-partitioning models.21,23 To evaluate the diffusion-partitioning behaviors of LCM release from various components of dismantled waste screens in realistic environments, the occurrence of LCMs in both disassembled parts of SP and light guide plate (LGP) can be used to verify the LCM release. In detail, the LCD panel is the main part of waste smartphone screens after primary dismantling,24,25 which is a complex multilayer assembly, typically consisting of a glass substrate, backlight modules, and a metal frame.25 The glass substrate comprises the face glass sheet, polarizing film, color filter, LCMs, functional film, and bottom glass sheet. The backlight module is composed of a light guide plate and backlight lamps. The glass substrate and backlight module account for 40–50 and 35–40 wt % of an LCD panel, respectively.1,26 A mixture of LCMs is physically embedded in the thin film layer between the two glass sheets. Since the thin film layers cannot be peeled off from the surface of the glass sheet,27 the LCMs attached to both film layers and glass sheets were defined as the LCM layer (LL, Figure S1). Considering that the backlight is fixed along the sides of the screen via seal adhesives, the LGP of backlight modules was also targeted for LCM quantification. Each LCD panel was disassembled into three parts, including the SP, LL, and LGP (Figure S1 and S2), for determining the 64 target LCMs. The LCM profiles were compared among SP, LL, and LGP to analyze the release behavior of LCMs.

2.4. Sample Preparation and Instrument Analysis

Based on preliminary screening results, the total amount of LCMs extracted from LL was significantly higher than those extracted from SP and LGP. Therefore, the extraction of LCMs from LL was conducted following the previously published ultrasonic-enhanced extraction method,2 and preparations of LCM extracts from the SP and LGP were conducted using a simple solvent-washing method.5,9 The detailed procedures are provided in Text S1 of the Supporting Information (SI).

The determination of 64 target LCMs was conducted by gas chromatography (GC, 2010, Shimadzu) combined with a mass spectrometer (MS, QP2010, Shimadzu) in the election impact (EI) mode, and the quantification was performed through selective ion monitoring (SIM) mode based on the retention time, selected ion fragments (m/z), and their relative abundance ratio. A DB-5HT column (30 m × 0.25 mm × 0.1 μm, J&W Scientific) was employed for separation. High-purity helium was used as carrier gas at a flow rate of 1.2 mL/min. The injector, ion source, and interface temperatures were 290, 280, and 290 °C, respectively. The GC oven temperature profile was programmed as follows: 40 °C for 1 min, increased to 210 °C by 40 °C/min, increased to 225 °C by 3 °C/min, increased to 300 °C by 15 °C/min, and hold for 10.25 min. The optimized analytical parameters for 64 target LCMs are listed in Table S3.

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

Strict QA/QC procedures were implemented to ensure accurate quantitation of LCMs. All glassware was rinsed with acetone and DCM in sequence before use to avoid any potential contamination. All experimental operations were carried out in a fume hood. The accuracy and precision of the analytical method were guaranteed by the recoveries of method blanks at two different spiked levels (2 ng and 100 ng, n = 3 for each concentration) with two internal standards (5 ng each). New screen protectors were used to develop the pretreatment method. The recoveries of 64 target LCMs were 90.3 to 129 (LL, Table S4) and 81.8 to 120% (SP and LGP, Table S5). None of the target LCMs were determined in the fifth extraction of LL from an intact screen. Two method blanks were conducted synchronously during each batch of 2 waste LCD screen samples to check the potential procedural contamination, and none of the target LCMs were found in the method blanks. The matrix effect (ME) was estimated by spiking a known LCMs (10 ng) into selected LCD screen sample extracts to ensure the method accuracy, and the matrix-spiked recovery of each LCM was the ratio of the measured concentration in the matrix-spiked sample to the added concentration. The recoveries of spiked LCMs in LL and its paired SP/LGP samples were in the ranges of 84.1 to 128 and 83.4 to 119%, respectively (Tables S4 and S5). A standard curve was performed through seven standard levels in the concentration range of 1.0–1000 ppb using the internal standard method for quantification (Table S3). The method limits of quantification (MLOQ) were defined as 10 times of signal-to-noise ratio (S/N) of chromatograms, and the results are listed in Table S4. A calibration standard was run after every 10 samples to monitor retention time deviation. A solvent blank of hexane was run after every five samples to monitor the potential instrumental contamination.

2.6. Methods for Modeling Release Behavior of LCMs

Since the material–phase diffusion models and material–air partition coefficients (Km-a, eq S1) for LCMs were absent, the empirical models for other anthropogenic semivolatile organic compounds (SVOCs) with similar physiochemical properties, such as polycyclic aromatic hydrocarbons (PAHs) and polybrominated diphenyl ethers (PBDEs), could be used as references.10,28−30 The diffusion-partitioning of LCMs from LL to LGP and SP was estimated by using two modeling methods.

2.6.1. Modified QSPR Model

The estimation for the partition coefficients between LL and LGP (KLL-LGP) and between LL and SP (KLL-SP) were referenced from a generic quantitative structure–property relationship (QSPR) model with minor modifications. Details about the modified QSPR model (eqs S1–S9) are presented in Text S2 of the SI.

2.6.2. Diffusion-Partitioning Model Development

An approach of the gas/particle partitioning process of SVOC including parameters of the predicted subcooled vapor pressures (PL) and Koa(11,28,31) to model the diffusion-partitioning process of LCMs from LL to LGP and SP was conducted. The evaluation of equilibrium partitioning of organic compounds between two phases is commonly performed using double logarithmic correlations. This method correlates the unknown partition constant and a well-known partition constant of a particular compound, for example, partitioning between natural organic matter and water or air is correlated with the KOW or Koa, respectively.32,33 The Koa constant is commonly used to describe the partitioning behavior between environmental organic reservoirs and air for a wide variety of organic compounds, including SVOCs,34 which are often used to determine gas/particle partitioning behavior during atmospheric transport.11,29 The reasons for using an approach of gas/particle distribution of SVOC to model the diffusion-partitioning of LCMs between LL and LGP or between LL and SP are explained as follows: (1) the atmosphere contains two media: the gas phase and particle phase. The interfacial diffusion of SVOCs between these two media is a crucial aspect of the gas/particle partitioning process of SVOCs. The mature steady-state L-M-Y model of gas/particle partitioning for SVOCs was developed by adopting the approach employed for the air–soil interface, whereby the particle phase is treated as a particle film.35−37 Similarly, we assumed a particulate structure for the LGP or SP layer (Figure S3). The partitioning process of LCMs between LL and LGP or between LL and SP could be viewed as a series connection of diffusion between the boundary layer of volatilized LCMs and the particulate LGP or SP layer. (2) Most LCMs are considered SVOCs due to their low vapor pressure and high Koa.16 Such compounds may be subject to long-range atmospheric transport. In a previous study, Shen et al. suggested that air could serve as an important temporary storage and transmission medium for released LCMs, as these compounds predominantly partition to the gas phase.11 Since LCM mixtures were physically sandwiched in the LL component and their release was not constrained by solid-phase diffusion within screens,21 it could be reasonable to assume a gas-like structure for the liquid-crystal layer. (3) The assumption of the gas/particle approach could be utilized to incorporate the parameter of AP into the developed diffusion-partitioning model that was developed to explain the release of LCMs from waste smartphone screens, providing a robust theoretical basis for these developed equations (eqs 1–14).

In detail, as an important parameter to describe the diffusion-partitioning behavior of LCMs between LL and LGP, the partition fraction for LCM i in LGP part (ϕLGP-i) was defined using eq 1 by referring to the gas/particle partitioning models.11,28,31 Since the concentrations of LCMs in LL were much higher than those in LGP (Table S6), CLGP-i in the denominator was ignored, and this equation was further rewritten as follows:

2.6.2. 1

Diffusion-partitioning models between LL and LGP (LL/LGP), as well as LL and SP (LL/SP), were developed by referring to the empirical relationships based on PL and Koa.(11,29,35) The gas/particle partitioning quotient (KP, m3/ug, eq 2) is widely used to describe the gas/particle partitioning behavior of SVOCs29. The relationships between KP and PL or Koa were modeled by empirical eqs 3 and 4, respectively.38,39 Compared with the equilibrium-state model (eq 4), the steady-state of the L-M-Y model (eq 5) was more suitable to describe the gas/particle partitioning processes of SVOCs.11,35

2.6.2. 2
2.6.2. 3
2.6.2. 4
2.6.2. 5

where CP (pg/m3 of air) and CG (pg/m3 of air) are the measured concentrations of each LCM in the particle and gas phases, respectively. CTSP (μg/m3) is the concentration of total suspended particles in the air. KPS (m3/ug) is the gas/particle partitioning quotient under the steady state. fom is the content of organic matter in airborne particles, which was referred as 0.17.11C is an undermined constant influenced by the mass transfer coefficient of SVOCs between the gas phase and particulate phase, which was referred as 5 in this study.11,40

For modeling the LL/LGP partitioning behavior of LCMs, the concentration units of LCMs in LL and LGP were converted to the equivalent units used for gas-like and particle-like phases, respectively (eqs 6 and 7, Figure S3), following the modeling method of the gas/particle partitioning process of SVOCs (eq 2). The LGP, treated as a layer of sphere particles (Figure S3), was composed of different numbers and species of LCM sphere with a mean diameter of d (cm) and a number of ni for each LCM i. The total number of LCM particles was Σni. Each sphere particle of LCM has a surface area of πd2, a volume of πd3/6, and a mass of πd3ρ/6, where ρ (μg/cm3) is the density of the LCM particle. Assuming that each LCM particle in this layer particle of LGP existed independently without mass transfer under a steady state, the number of ni for each LCM was a linear function of the corresponding average mass proportion (APLGP) as eq 8. Therefore, the concentration of total suspended particles in the gas/particle-like phases of LL/LGP (CTSP-LGP, μg/cm3) was given as Eq 9. Equation 6 to 9 were substituted into Eq 2 to get Eq 10, where KP-LGP (cm3/ug) was the LL/LGP partitioning quotient. By substituting eq 10 into eqs 3 and 5, the data modeling for describing the LL/LGP partitioning behavior was developed, expressed as eqs 11 and 12, respectively. Similarly, the modeling of the LL/SP partitioning behavior of LCMs was developed following the LL/LGP partitioning, of which the corresponding parameters of LGP were replaced with those of SP. Details are presented in Text S3 (eqs S10–S17) of the SI, and the developed LL/SP diffusion-partitioning models were expressed as eqs 13 and 14.

2.6.2. 6
2.6.2. 7
2.6.2. 8
2.6.2. 9
2.6.2. 10
2.6.2. 11
2.6.2. 12
2.6.2. 13
2.6.2. 14

where A (cm2) is the size of the waste screens; CG-LL (ng/cm3 of air) and CP-LGP (ng/cm3 of air) are the concentrations of the gas phase of LL and particle phase of LGP, respectively; APLGP was estimated as the statistics AP of LCMs in LGP (Table S6); the value of log(6/Adρ) was estimated to be 1.

2.7. Statistical Analysis

Statistical analysis was conducted using IBM SPSS Statistics 26.0 and OriginPro 2019 software. The results of the instrumental analysis for waste LCD screen samples were summarized as detection frequency (DF), mean, and range of measured LCM concentrations. The normality and homogeneity of measured concentrations were examined using the Shapiro–Wilk test and Levene’s test, respectively. The data that did not fit the assumptions were logarithmically transformed to approximate a normal distribution before statistical analysis. The significant difference of LCM concentrations among different analytes was examined using t-test with a significance level set at p < 0.05. Pearson correlation analysis (two-tailed) was used to assess the correlation analysis among different analytes.

3. Results and Discussions

3.1. Release of LCMs Originating from Waste Smartphone Screens

3.1.1. Occurrence of LCMs in Three Disassembled Parts of Waste Screens

Descriptive statistics of 64 target LCMs in waste smartphone screens are listed in Table S6. In total, 50 target LCMs were detected, of which 47, 43, and 33 LCMs were found in the LL, LGP, and SP samples, respectively. More F-LCMs (n = 31) were detected in waste smartphone screens compared to NF-LCMs (n = 19), which is consistent with the LCM compositions observed in waste televisions, computer LCD panels, and indoor air from waste LCD dismantling facility.2,11 As shown in Table S6, 32 out of the 50 detected LCMs were simultaneously present in all three disassembled parts of waste smartphone screens, among which 23 LCMs were detected in air samples collected from the LCD dismantling facility.11 In addition, another 9 out of the 50 detected LCMs were observed in two parts of waste screens, and the remaining nine LCMs were detected with relatively low concentrations and frequencies and only observed in one of the three parts. The frequently detected LCMs (DF > 10%) in these three disassembled parts showed a significant correlation (Pearson’s r in the range of 0.553–0.998, p < 0.05, Table S7), suggesting that LL was the source of LCMs in the LGP and SP samples. The above results implied that some LCMs escaped from the screen module across LGP and SP. The direct release of LCMs from smartphone screens might be an important source of these emerging e-waste pollutants entering the environment, and there might be a partitioning pattern among LL, LGP, and SP.

The total concentrations of all LCMs (Σ47LCMs, n = 35) detected in LL ranged from 12.3 to 245,000 ng/cm2, with a mean of 84,600 ng/cm2, which was approximately one order of magnitude lower than those found in waste television/computer LCD panels (Σ64LCMs with a mean of 556,000/788,000 ng/cm2).2 The total concentration of all LCMs (Σ43LCMs, n = 33) detected in LGP ranged from 0.561 to 423 ng/cm2, with a mean of 86.1 ng/cm2. The total concentration of all LCMs (Σ33LCMs, n = 7) detected in SP ranged from 23.1 to 407 ng/cm2, with a mean of 116 ng/cm2 (Table S6). The mean of ΣLCMs in LGP was lower than that in SP, and both of them were nearly 2–3 orders of magnitude lower than those measured in LL. The species of F-LCMs detected in LL, LGP, and SP were 29, 28, and 22, while the AP of F-LCMs detected from them were 58.9, 47.4, and 44.6%, respectively. The results in Table S8 indicated that no significant differences in the concentrations were found between F-LCMs and NF-LCMs across LL, LGP, and SP layers (p > 0.05). The concentrations of individual LCM in LL, SP, and LGP (with DF > 10% in LL) are shown in Figure 1. For a smartphone screen module, the LGP part is beneath the LL part, while the SP part is above the LL part, directly facing the ambient air (Figure S1). The concentrations and DF of individual LCM varied among the LL, LGP, and SP parts of waste screens (Figure 1). Correlation analysis showed that the linear relationship of CLL vs CLGP (R2 = 0.930; p < 0.05) was more significant than that of CLL vs CSP (R2 = 0.878; p < 0.05) (Figure S4a). The slope value for DF obtained from the plot of DFLL vs DFLGP with an R2 of 0.930 was approximately 1, which was larger than that of DFLL vs DFSP (0.592) with an R2 of 0.647 (Figure S4b), suggesting that the detected LCMs in LGP and LL had a similar pattern, which was different from those in SP. The SP part facing the ambient environment might be more inclined to further diffuse LCMs into the air. It was further supported by the distributions of F-LCMs among three disassembled parts with the order of SP < LGP < LL, since the F-LCMs usually have higher atmospheric transport potentials than NF-LCMs.5,41

Figure 1.

Figure 1

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LCMs concentrations and the corresponding DF in (a) SP, (b) LL, and (c) LGP disassembled from waste smartphone screens. The scatter plots (purple) represent the DF (%).

The occurrence of LCMs in the disassembled SP and LGP parts verified the release of LCMs from waste smartphone screens. Based on the concentrations of LCMs in SP and LGP, the EF values for the release of LCMs from waste smartphone screens were estimated (Table S9, eq S19, Text S4). The EF value for released LCMs from waste smartphone screens was 2.38 × 10–3, where the EF values for released LCMs from SP and LGP parts were 1.36 × 10–3 and 1.02 × 10–3, respectively. Comparisons between this study and other e-waste related organic pollutants are summarized in Figure S5. The EF values for released LCMs from waste smartphone screens were significantly higher than those of other traditional e-waste organic pollutants, such as PBDEs and polychlorinated biphenyls (PCBs), by nearly 2–3 orders of magnitude released during the usage, dismantling, crushing, segregation, recycling, and landfill.42−47 Different from the release of VOCs from dry materials and homogeneous polymers controlled by internal diffusion,48−50 a mixture of LCMs is physically sandwiched in the thin film layer between two glass sheets;27 therefore, the release of LCMs from LCD panel might be not dominated by internal diffusion, thus contributing to the higher EF values.

3.1.2. Distribution Proportions of the Released LCMs

The distribution patterns of LCMs detected in the LL component from different brands of waste screen panels were compared (Figure S6). 3VbcH was detected in all waste LCD panels and identified as the dominant LCMs in this study. Consistently, 3VbcH was also detected with high concentrations in waste television/computer LCD panels, such as Brand Y television and Brand S computer.2 These results suggested that 3VbcH was frequently assembled with large quantities in commercial LCD panels. The distribution patterns for released LCMs frequently detected from three disassembled parts of waste screen were further compared (Figure 2a). The dominant species for F-LCMs in LL was 2O3cHdFP (9.86%), followed by 2O3cHdFB (6.26%), tFPO-CF2-dF3B (5.73%), 2O2cHdFB (5.56%), and 3OdFP3bcH (5.10%). By contrast, these five F-LCMs in SP and LGP were in the orders of 2O3cHdFP (8.07%) > tFPO-CF2-dF3B (6.26%) > 2O3cHdFB (3.79%) > 2O2cHdFB (3.43%) > 3OdFP3bcH (0%), and 2O3cHdFP (7.34%) > 2O3cHdFB (7.28%) > 2O2cHdFB (6.84%) > tFPO-CF2-dF3B (5.96%) > 3OdFP3bcH (1.13%). For NF-LCMs, different distribution patterns for individual LCM were also observed among LL, SP, and LGP, where the top three NF-LCMs were in the orders of 3VbcH (28.7%) > MePVbcH (5.53%) > MPhBB (3.04%), 3VbcH (45.9%) > MPhBB (3.54%) > Pe3bcH (3.29%), and 3VbcH (43.6%) > Pe3bcH (3.89%) > MPhBB (1.90%)respectively. These findings suggested that the migration pattern for individual LCM from LL to LGP and SP could potentially follow different diffusion-partitioning behaviors, which were possibly influenced by different structures of LGP and SP, as well as different physiochemical properties of LCMs, such as molecular weights, vapor pressure, PL and Koa.11,21 In addition, 2O3cHdFP and 3VbcH were the highest compositions of F-LCMs and NF-LCMs in all three disassembled parts. Correlation analyses showed that the AP of detected LCMs were significantly correlated between LL and LGP (Pearson’s r = 0.976; p < 0.05), as well as LL and SP (Pearson’s r = 0.957; p < 0.05) (Figure 2b), indicating that AP might also play an important role for the diffusion and release of LCMs. The LCM mixture embedded in LL migrating toward both LGP and SP was also presumably driven by the concentration gradient between different parts.

Figure 2.

Figure 2

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(a) Distribution patterns of the released LCMs frequently detected from waste screens; (b) Linear relationships of AP of the released LCMs in three disassembled parts of waste screens.

3.2. Modeling of Release Behavior of LCMs

Understanding the release behavior of LCMs is critical to estimating the human exposure of LCMs during routine use of screen devices and evaluating the release of LCMs as environmental pollutants.30 Herein, two modeling methods were conducted to reveal the diffusion-partitioning mechanisms and release pathways for LCMs entering the ambient environment.

3.2.1. Modified QSPR Model Fitting

Comparison results between modified QSPR model predictions and measured data are shown in Figure S7. It can be seen that 30 and 38% of mean logKLL-LGP points for F-LCMs and NF-LCMs were within the acceptable deviation range (ADR)29,51 (Figure S7a), while 15% and 30% of mean logKLL-SP points for F-LCMs and NF-LCMs were within the ADR range, respectively (Figure S7b). There was a significant overall discrepancy between the predictions and measured data for frequently detected F-LCMs and NF-LCMs, potentially indicating that the diffusion-partitioning behaviors of LCMs in waste smartphone screens were not solely determined by Koa. These comparison results indicated that most of the predicted logKLL-LGP and logKLL-SP values were higher than the measured values, implying that the corresponding predictions of LCMs released from LL to LGP were lower than the actual concentrations (eqs S4 and S5). These results also explained the previous laboratory study for underestimation of released LCMs compositions escaping from obsolete smartphone screens in all examined temperature ranges due to this similar overestimation of the corresponding used Km-a.(21) Different from the SVOCs encapsulated in building materials and furniture, LCM mixtures were physically embedded in the thin film layer between two glass sheets of the LL component. Therefore, the release of LCMs from LL could not be fully controlled by internal diffusion.52 Feng et al. also discovered a similar fact that the emissions of volatile LCMs were not constrained by solid-phase diffusion within screens.21 Previous studies indicated that the emission mass, a parameter similar to AP, affected the external release process of SVOCs, where their internal diffusion was assumed to be negligible.53,54 Although the modified QSPR models were not suitable for modeling the partition coefficients of LCMs in waste smartphone screens, the above discussion improved our understanding on the diffusion-partitioning behaviors of LCMs.

3.2.2. Development of Diffusion-Partitioning Model

The diffusion-partitioning of LCMs among LL, LGP, and SP is an important factor in revealing their mass transfer mechanisms and determining the environmental fates of LCMs. The developed LL/LGP and LL/SP diffusion-partitioning models were first verified by the relationships of log(ϕ/AP)–logPL and log(ϕ/AP)–logKoa for the LCMs frequently detected in waste screens. For both F-LCMs and NF-LCMs, significant linear correlations of log(ϕ/AP)–logPL and log(ϕ/AP)–logKoa for the two diffusion-partitioning processes (LL/LGP and LL/SP) were obtained, with R2 values and absolute slope values in the ranges of 0.715–0.922 (p < 0.01) and 0.179–0.994, respectively (Figure 3). The fitting results from the developed mechanistic models (eqs 15–22) revealed that the characteristic parameters of released LCMs, including AP, PL, and Koa, could control the diffusion-partitioning processes of LL/LGP and LL/SP, where LCMs with higher AP and Koa, or higher AP and lower PL might have a greater tendency to migrate from LL to LGP and SP layers. The absolute slopes of log(ϕ/AP)–logKoa (0.179–0.744, Figure 3c,d) for F-LCMs and NF-LCMs in the LL/LGP and LL/SP diffusion-partitioning processes were lower than the corresponding values of log(ϕ/AP)–logPL with a range of 0.317–0.994 (Figure 3a,b). Similar trends were also observed for gas–particle partitioning of LCMs and chlorinated paraffins (CPs) described by PL and Koa.11,38 These results suggested that both LL/LGP and LL/SP diffusion-partitioning behaviors of LCMs exhibited a significant gas/particle-like partitioning pattern.

3.2.2. 15
3.2.2. 16
3.2.2. 17
3.2.2. 18
3.2.2. 19
3.2.2. 20
3.2.2. 21
3.2.2. 22
Figure 3.

Figure 3

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Log(ϕ/AP) as a function of (a, b) logPL and (c, d) logKoa for individual LCM frequently detected in paired LL/LGP and LL/SP, respectively.

Previous field and laboratory studies supported that logKP tends to be linearly correlated with logPL, and its slope value should be near −1 when the equilibrium partition is attained.55,56 The slope values of log(ϕLGP/APLGP) versus logPL were −0.341 and −0.994 for F-LCMs and NF-LCMs, respectively (Figure 3a). The slope values of log(ϕSP/APSP) versus logPL were −0.317 and −0.726 for F-LCMs and NF-LCMs, respectively (Figure 3b). These results suggested that F-LCMs and NF-LCMs might exhibit different diffusion-partitioning behaviors for the two diffusion-partitioning processes of LL/LGP and LL/SP. The slope value of log(ϕLGP/APLGP)–logPL (−0.994) for NF-LCMs detected in this study was lower than that of the same collection of NF-LCMs (−0.72) in the gas and particle samples collected near e-waste facilities sites, while this slope value for F-LCMs (−0.341) was higher than that of F-LCMs (−0.79) in the same air samples,11 suggesting that LL/LGP diffusion-partitioning for NF-LCMs was closer to equilibrium, while the state for F-LCMs was far away from equilibrium.57−59 Different from the similar slope values (close to −1) for the groups of F-LCMs and NF-LCMs in ambient air samples,11 NF-LCMs compounds might reach diffusion-partition equilibrium more quickly than F-LCMs compounds in their originating source waste LCD panels. These results further suggested that F-LCMs might have higher long-range atmospheric transport potential than NF-LCMs.

Compared with the absolute slope values obtained from the relationships of log(ϕ/AP)–logPL and log(ϕ/AP)–logKoa for F-LCMs and NF-LCMs (i.e., 0.179 ∼ 0.726, Figure 3b,d) in the LL/SP diffusion-partitioning process, the corresponding values (i.e., 0.194 ∼ 0.994, Figure 3a,c) of models fitting for the LL/LGP diffusion-partitioning process were relatively higher. These phenomena showed that the diffusion-partitioning of LCMs between LL and SP could be further away from the equilibrium compared to that of LL and LGP, explaining the fact that the concentrations of the released LCMs detected in SP might be higher than those in LGP, which is consistent with the mean values of ΣLCMs in LGP and SP (Table S6). These results suggested that the release of LCMs from waste smartphone screens into the ambient air could be mainly governed through SP diffusions. The differences in diffusion-partitioning states for F-LCMs and NF-LCMs among LL, LGP, and SP parts in waste screens might lead to differential atmospheric transport fate of individual LCM.10−12

Based on the above results, the possible release pathways and mechanisms of diffusion-partitioning for F-LCMs and NF-LCMs from waste screens into the air were proposed. The release of LCMs from waste screen panels included the internal and external diffusion processes. Previous studies have determined that internal material diffusion for LCMs releases from LL to the interior LL surface could be negligible,21 consistent with the estimated results of logKLL-LGP/logKLL-SP (Figure S7). The external diffusion processes for the released LCMs could be governed by the diffusion partitioning between the interior LL surface and the LGP or SP part immediately adjacent to and then release through the boundary layers of LGP and SP into the ambient air.48,53 Different from the adsorption or absorption mechanisms described by log(ϕ/AP)–logPL, log(ϕ/AP)–logKoa favored the absorption mechanism for describing the diffusion-partitioning behavior of LCMs.38 The intermolecular interactions that primarily dominated the adsorption and absorption of LCMs could be physisorption,23 including nonspecific van der Waals interactions (e.g., dispersion interactions), specific polar interactions hydrogen-bonds, and electrostatic interaction. These interactions are commonly observed in the partitioning equilibrium of PBDEs and poly-/perfluoroalkyl substances.60,61 Thus, during the external diffusion process, the diffusion-partitioning of LL-adsorbed LCMs to SP and LGP could involve both adsorptions to the surfaces of SP and LGP and absorption into the interconnect material of LCD panels, such as organic adhesives.62,63 Since the proportion of organic adhesives in LCD panels is much lower than the SP and LGP parts, the adsorption could be the dominating process. The diffusion-partitioning behaviors for individual LCM varied widely depending on the types of LCMs, and the release of NF-LCMs tended to reach diffusion equilibrium more quickly than that of F-LCMs on both boundaries of SP and LGP. Then, the adsorbed LCMs on the surfaces of SP and LGP parts could further diffuse into the air via desorption. Since the boundary of SP is directly facing ambient air, their release into the ambient air could be governed by the SP rather than LGP diffusions. The overall release of LCMs exhibited a gas/particle-like diffusion-partitioning behavior, and the further atmospheric transports of LCMs could be governed by the movement of air gas.11

The comparisons of obtained measurements logϕ for released F-LCMs and NF-LCMs versus the modeled values based on the steady-state approximation (eqs 12 and 14) were performed. It can be seen that more than 90 and 56% of mean logϕLGP points for NF-LCMs and F-LCMs were within the ADR range, respectively (Figure 4a), while 75 and 42% of mean logϕSP points for NF-LCMs and F-LCMs were within the ADR range, respectively (Figure 4b). The measured logϕ data for NF-LCMs obtained in the diffusion-partitioning processes of LL/LGP and LL/SP compared fairly well to the model predictions, which is probably attributed to the fact that the progress of diffusion-partitioning for NF-LCMs might reach the steady-state in reality, satisfied with the premise assumption. Nearly half of measured logϕ data for F-LCMs were substantially overestimated, especially for those with high Koa values and low AP values,21 such as tFPO-CF2-dF3PyB, tFPO-CF2-tF3T, and tFMeO-3cHtFT. These differences between predictions and measurements for F-LCMs were justified to some extent by the fact that the adsorbed LCMs on the surface of SP and LGP parts with high Koa values might further diffuse into the air.38,51 In addition, the evaluation of the release of LCMs by simplifying the structure of waste screens, such as ignoring the plastic frames and their instability of storage environment before sampling the waste screens, might also result in disparities.64 The good fitting results for most LCMs in Figure 4 verified the reliability of the present models and the determined key parameters. These mechanistic models should need further investigation, such as accounting for the concentrations of LCMs releasing through the boundary layers of LGP and SP into the ambient air in the release models, for optimization purposes.

Figure 4.

Figure 4

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Measured logϕ as a function of predicted logϕ by the diffusion-partitioning model for frequently detected LCMs in paired (a) LL and LGP, and (b) LL and SP. ADR was defined as ±1 log unit on both sides of the 1:1 line.

3.3. Influence of the Conditions of Waste Screens

The physical conditions of each waste smartphone screen are summarized in Table S2. Given the potential for LCMs release and human exposure, it is important to estimate the relevance of screen physical conditions and their association with increased LCM concentration to facilitate the development of strategies for reducing release and pertinent risk assessment. A similar statistical analysis has been commonly used in various pollution surveys,65−67 such as the relevance of home characteristics and their association with increased trace metal concentrations in the dust.65 Different screen display technologies utilize different compositions of LCMs mixtures in smartphone screens. The released concentration of LCMs from each waste LCD screen was higher than that originated from each waste active-matrix organic light-emitting diode (AMOLED) screen, which was largely due to the significant difference in their corresponding concentrations in the display layers (p < 0.01, Table S10), more likely because AMOLED used more other organic light-emitting materials (OLEMs) instead of 64 target LCMs tested in this study.13

To better understand the influence of screen conditions on the release of LCMs, relationships among concentrations of LCMs determined in LGP and SP, together with service year, screen size, and crack length of screens, were examined using Pearson correlation analysis (Table S11). There was no significant correlation between concentrations of released LCMs and conditions of waste screens. This result potentially indicated that LCMs could diffuse from LL to LGP and SP during the lifetime of screen, no matter whether the screen was broken or intact. Previous studies indicated that the LCD screen-induced LCMs release might be a long-term source of indoor VOCs, regardless of the status of LCDs,20 which is consistent with the results of correlation analysis. The diffused LCMs might further volatilize and be absorbed into airborne dust/particles, which has been observed from the swipe samples collected from the surface of working LCD screens.51

4. Environmental Implications

According to the latest report, the average replacement period of smartphones is 25.3 months, of which 78.6% of users were compelled to replace their smartphones because of damage, performance stuttering, and short battery life.68 The average service life of collected waste smartphones in this study was 4.2 years (Table S2), which means most of them were produced and sold in 2017. Based on the HIS Markit data, the global production of mobile phone displays in 2017 was estimated to be 2.01 billion units.69 Considering these facts, it is reasonably assumed that at least 78.6% of the smartphone screens produced in 2017 have already been discarded as e-waste. Based on the mean size of display screens (68.7 cm2, Table S2) and the measured mean concentrations of LCMs (Table S6), we estimated the total discarded amounts of LCMs from waste smartphones to be 9.20 ton/year (Table S12), contributing to approximately 4.13% of global discarded LCMs.2 Based on the results obtained from this study, the LCMs passively released from waste smartphones would be at least 21.9 kg/year (Table S12). Currently, recovery of LCMs substances from waste LCD panels remains challenging.3,70,71 To alleviate the potential risk of LCMs released into the environment, future studies should develop novel LCMs with low toxicity and low migration ability to decrease their environmental pollution.11 In addition, there are some significant deficiencies in knowledge regarding LCMs in various fields. Areas that require further investigation include conducting a comprehensive survey with LCMs and LCD producing industries to obtain a list of LCMs currently being produced, identifying the dominant species of LCMs used in the manufactory of LCD panels and analyzing the general trend for LCM compositions in various electronic devices. The government should also implement updated guidelines and regulations for a greener application of LCMs substances involved in the production, usage, disposal, monitoring, and management of related e-device and e-waste.

This study demonstrates that the proposed diffusion models could help understand the mechanisms governing the mass transfer of released LCMs from various components of waste smartphone screens into the ambient air. Since the screen size of LCD panels was not taken into consideration when developing the diffusion-partitioning models in this study, the developed model of this study might be potentially applied to other electronic devices, such as televisions and computers, by modifying the coefficients of AP, PL, and Koa. The uncertainties associated with the developed diffusion-partitioning model were mainly derived from (1) the uncertainty in the input parameters, namely, the undermined constants of C and organic content of fom for SVOC, which were used for LCMs; (2) the simplified structure of waste screens that ignored other components such as backlight, plastic frames, and organic adhesives; (3) neglecting the content of LCMs released from the boundary layers of LGP and SP into the ambient air. Much work remains to be conducted to confirm the realistic release models. For example, further investigation is needed to understand the molecular mechanisms underlying the partitioning equilibrium of LCMs between LGP and LL or SP and LL parts using molecular structural descriptors via quantum chemical computations.32 To determine the total release mass of LCMs, it is essential to consider the content of LCMs in the LCMs layer as well as their release time (usage time). In future research, it will be necessary to develop release kinetics models for LCMs from LCD panels. Air could be an important temporary storage and transfer medium for released LCMs due to the predominant partitioning of LCMs to gas phase,11 but another possible mass transfer pathway via direct contact with dust should not be ignored. This valuable information could help reveal the migration pathways of LCMs entering the environment as well as their transport behavior in the atmospheric environment.

Acknowledgments

The project was supported by the National Natural Science Foundation of China (42177223), the Research Grants Council of Hong Kong (CityU 11311222), and Marine Ecology and Enhancement Fund (MEEF2021002A) to Y.H. and Guangdong Basic and Applied Basic Research Foundation (2022A1515110549) to Q.J.. This work was also supported by the Innovation and Technology Commission (ITC) of the Hong Kong SAR Government which provides regular research funding to the State Key Laboratory of Marine Pollution. However, any opinions, findings, conclusions, or recommendations expressed in this publication do not reflect the views of the Hong Kong SAR Government or the ITC.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.2c09602.

  • Sample preparation (Text S1); modified QSPR model (Text S2); LL/SP diffusion-partitioning model development (Text S3); emission factors (Text S4); physical and chemical properties of LCMs (Table S1); detailed information of collected waste smartphone screens (Table S2); analytical parameters of individual LCMs (Table S3); QA/QC data for samples of LL (Table S4); QA/QC data for samples of SP and LGP (Table S5); descriptive statistics of the target 64 LCMs (Table S6); Pearson’s correlation analysis for detected LCMs in different parts of waste screens (Table S7); comparison of different types of LCMs released from various components in smartphone screens (Table S8); emission factors of LCMs from waste screen (Table S9); comparison of LCMs released from smartphones using different display technologies (Table S10); Pearson’s correlation analysis for LCMs released from waste screen with different conditions (Table S11); global estimated releases of LCMs from waste smartphone panels (Table S12); multilayer structure of LCD panel (Figure S1); disassembly of waste LCD panels (Figure S2); imaginary of gas/particles-like phases of LL/LGP (Figure S3); correlation of individual LCM among different layers (Figure S4); comparison of LCMs emission factors with other e-waste related organic pollutants (Figure S5); distribution patterns of LCMs detected in LL component from different brands (Figure S6); Comparison of modified QSPR model predictions and measured data (Figure S7); and references (PDF)

The authors declare no competing financial interest.

Supplementary Material

es2c09602_si_001.pdf (1.7MB, pdf)

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