Abstract
Fourier transform infrared (FTIR) spectroscopy has been extensively used in microplastic (MP) pollution research since 2004. The aim of this review is to discuss and highlight the recent advances in FTIR (spectroscopy and chemical imaging) techniques that are used to characterize various polymer types of MPs and to trace their fate and transport in different environmental matrices. More than 400 research papers dealing with FTIR techniques in MP pollution research, which are published between January 2010 and December 2019, have been identified from the Scopus and Web of Science databases. The MPs present in sediment, water (marine and freshwater), biota, air/dust, waste water treatment plants and salt are further classified according to (1) characterization and identification, (2) weathering and aging, (3) ecotoxicology, and (4) analytical methods. The results revealed that the ATR-FTIR technique is mostly used to identify and characterize the MPs found in water and sediment. The µFTIR (FTIR imaging) is extensively used to study the ingestion of MPs in biota (both marine and freshwater). In this article, we have summarized the current knowledge of application of FTIR spectroscopy to MP research and provided insights to future challenges for understanding the risk of MPs.
Graphical Abstract
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1. Introduction
Microplastic (MP) contamination in water (both marine and fresh water) (Gago et al., Citation2016; Koelmans et al., Citation2019), sediment (Cauwenberghe et al., Citation2015; Xu, Liu, et al., Citation2019), air (Zhang et al., Citation2020), salt (Peixoto et al., Citation2019), biota (Rezania et al., Citation2018; O'Connor et al., Citation2020; Markic et al., Citation2020), wastewater treatment plant (Sun, Dai, et al., Citation2019) and honey (Muhlschlegel et al., Citation2017) has aroused as a major global environmental and economic issue. The term “microplastics” was first coined by Thompson (Thompson et al., Citation2004) in 2004 to describe the small size (less than 5 mm in size) plastic particles in the oceans. Since then, significant amount of results has been published on this topic globally. Plastic debris in the environment is classified based on their chemical composition, solid state, solubility, size, shape, color and origin. Depending on size, plastics have been categorized as nanoplastics (1 to <1000 nm), MPs (1 to <1000 µm), mesoplastics (1 to <10 mm) and macroplastics (1 cm and larger) (Hartmann et al., Citation2019). MP consists of primary MPs, which are manufactured in microscopic size for specific purpose (including microbeads) and secondary MPs, which are formed from large plastic debris degraded and fragmented by long-term physical, chemical and biological effects in the environment (Cole et al., Citation2011; Veerasingam et al., Citation2017; Besseling et al., Citation2019).
Weathering process in MPs (both primary and secondary) is first initiated at the surface of particles, where the surface layer is discolored, oxidized, embrittled and crazed (Bond et al., Citation2018). Then, the interior weathering is proceeded by a diffusion-controlled process. MP undergoes degradation due to physical (wind wave action and mixing in-between the heavy and/or abrasive beach sediments) (Efimova et al., Citation2018; Chubarenko et al., Citation2020), chemical (UV light from solar radiation) (Andrady, Citation2011, Citation2017; Song et al., Citation2017) and biological (microorganisms) (Kooi et al., Citation2017) factors. Degradation processes of MPs are categorized as follows: photo degradation (action of light or photons, usually UV light from the sun), thermal degradation (high temperature causes molecular deterioration in laboratory condition), thermo-oxidative degradation (slow oxidative, molecular deterioration at moderate temperatures), hydrolysis (reaction with water) and biodegradation (decomposition of organic materials by microorganisms). Due to weathering process, MPs change its physical properties such as mechanical, optical or electrical characteristics in crazing, cracking, erosion, discoloration and phase separation. Degradation of MPs depends on many factors including polymer type, age, and environmental conditions such as sunlight, temperature, rain, humidity, irradiation, pH, pollutants, thermal cycles, and oxygen content (Halle et al., Citation2016; Smith et al., Citation2018). Weathering of MPs in water is much slower than that in air or on beaches, as water suppresses light-induced oxidative degradation. This can be attributed to low temperatures, low oxygen concentrations and reduced transmittance of UV irradiation in water as well as increased biofilm formation (Andrady, Citation2011, Citation2017; Bond et al., Citation2018). Due to higher rate of photo-oxidation process, plastics in the hot sand beaches degraded faster than those floating in the ocean water (Veerasingam, Mugilarasan, et al., Citation2016; Sathish et al., Citation2019).
Since the size of MPs is very small, it can be ingested by a wide range of organisms by mistake as food for prey (Botterell et al., Citation2019). MPs are not only contaminants by themselves, they are also associated with different chemical additives, which were added during their manufacturing process to optimize their physical attributes. These chemicals, including those incorporated during plastic production (additives), can leach into biological tissues, posing health risk to organisms and bio-accumulating in the food chain (Koelmans, Citation2015; Gall & Thompson, Citation2015; Galloway et al., Citation2017). Therefore, MPs have the potential to act as vectors for the transport of hydrophobic organic pollutants (Rochman, Citation2015). The vector effect of particle mediated transport of pollutants can be divided into three groups (Syberg et al., Citation2015): (1) an environmental-vector effect (MPs with adhered pollutants are transported through the environment), (2) an organismal-vector effect (the pollutant is transported into the organisms) and (3) a cellular-vector effect (the pollutant is transported with the particle into cells).
Many analytical methods have been used to identify polymeric composition of plastic debris in different aquatic environments (summarized in ). These methods are time consuming, involving laborious sample preparation, and destructive in nature. Moreover, most of these methods are limited to volatile or ionizable compounds such as small oligomeric fragments or additives within the bulk material. FTIR and Raman techniques are versatile vibrational spectroscopic methods used to characterize different types of polymers (Kappler et al., Citation2016; Jung et al., Citation2018). In fact, FTIR spectroscopy can identify all the molecular and functional groups present in plastic polymers (Bhargava et al., Citation2003; Mecozzi et al., Citation2016).
FTIR spectroscopy deals with measurement of infrared (IR) radiation absorbed by the MP sample, allowing the study of molecular composition. An infrared spectrum represents a fingerprint of a sample (MP) with absorption peaks correspond to the frequencies of vibration between the bonds of the atoms making up the material. Because each different polymer material is a unique combination of atoms, no two compounds produce exactly the same infrared spectrum. Therefore, the chemical structure of a polymer molecule can be determined by FTIR (Chalmers, Citation2006). The IR region of the electromagnetic spectrum is divided into three regions: (1) the higher energy near infrared (NIR) region with wavenumbers of 14,000–4000 cm−1 (0.78–2.5 µm wavelength) range, which is sensitive to overtone and combinations of vibrations, (2) the mid infrared (MIR) region with wavenumbers of 4000–400 cm−1 (2.5–30 µm wavelength) range to study the fundamental vibrations and (3) the far infrared (FIR) region with wavenumbers of 400–10 cm−1 (30–1000 µm wavelength) range to study rotations (Mukherjee & Gowen, Citation2015). Among these three IR spectral regions, MIR is the most common region in the field of MP characterization. FTIR spectroscopy can be used to study the solid, liquid and gaseous samples. Since MPs are generally solid samples, we will focus our discussion on these materials. FTIR spectra of different polymers are covered in this review to illustrate the key features involved in spectral interpretation and its application for the analysis of MPs.
The objectives of this article are (1) to critically review the work of identification of MPs using FTIR technique in various environmental matrices, (2) to highlight the suitable evaluation and data processing methods for MPs identification based on FTIR measurements, and (3) to look at the current limitations in the methods and analyses, and how do we improve and harmonize the practices for future studies of MPs using FTIR measurements.
2. Data collection
A comprehensive literature search was conducted using a combination of keywords including “microplastic,” “microplastics,” “plastic,” “FTIR,” “sediment,” “water,” “waste water treatment plant,” “atmosphere,” “dust,” “biota,” “ingestion,” “salt” in Scopus and Web of Science database. The retrieved articles were screened, and only those studies carried out with FTIR technique were selected. This has resulted into 412 research articles, published between January 2010 and December 2019, and these were taken-up for detailed review. These research articles are categorized according to the topics of investigation: (1) characterization and identification, (2) weathering and aging, (3) ecotoxicology, and (4) analytical methods and future challenges. The statistics show that the number of publications pertaining to MP studies using FTIR technique has increased rapidly in the last 5 years ().
3. Characterization and identification
Characterization and identification of different polymer types of MPs found in a sample are important as each polymer has its own impacts on the biosphere. MP pollution has been studied in various environmental matrices (sediment, water, biota, salt and air/dust) using FTIR technique around the world (). However, only few studies have been carried out using FTIR technique so far to assess the MPs in air (dust) samples. Most frequently obtained shapes of MPs are fibers, fragments, films, foams, microbeads and pellets. Abundance of secondary MPs is higher (fragments, fibers, and foams) than the primary MPs (microbeads and pellets). MPs collected from various environmental matrices might be linked with different organic pollutants, and that may affect the identification of their polymer types. Therefore, purification of MPs is the key to instrumental analysis. Various digestion methods including oxidant digestion (reagent: 30% H2O2/35% H2O2/5% NaCIO), acid digestion (reagent: 65% HNO3/37% HCl), alkaline digestion (reagent: 10 M NaOH/10% KOH) and enzymatic digestion (reagent: trypsin/proteinase K) are used for purification (Lusher et al., Citation2017). The review analysis shows that various polymer types have been covered in the studies—polyethylene (PE), polypropylene (PP), polystyrene (PS), polyamide (PA), and polyethylene terephthalate (PET). PE and PP are the dominant polymer types found in all environmental matrices. The MPs extracted from sediment, water, biota, waste water treatment plants, salt, and air (dust) are grouped into two categories after visual identification: (1) large MPs (5 mm–500 µm) and (2) small MPs (size <500 µm) (Eo et al., Citation2018; GESAMP, Citation2019; Hidalgo-Ruz et al., Citation2012; Lorenz et al., Citation2019; Olesen et al., Citation2019; Song, Hong, Jang, Han, Rani, et al., Citation2015).
FTIR is a well recognized, rapid and quite reliable method to identify polymer types of different MPs by comparing the resulting FTIR spectra with known plastic polymers in the spectral library (). Usually, larger MPs are identified by ATR-FTIR, whereas smaller MPs (particle down to 20 µm) are characterized by μFTIR (Okoffo et al., Citation2019). Single particles with size larger than 200–300 µm are commonly presorted using visual examination before FTIR analysis (Primpke, Christiansen, et al., Citation2020). Among the research articles considered for this review, nearly 60% of studies used ATR-FTIR technique to characterize the large single particle MPs extracted from different environmental matrices () since it is a cost-efficient method and no sample preparation or complicated mathematical correction is required. Though reflection is fully nondestructive (Primpke, Christiansen, et al., Citation2020), ATR may destroy MPs due to pressure applied (Wu, Tao, et al., Citation2019). In some studies, the larger single MPs were ground with potassium bromide (KBr) for transmission measurements either by diffuse reflection or via ATR measurements (Renner et al., Citation2016). However, in these techniques, the working time per particle is high (∼3 min per particle). Aforementioned techniques require sample transport to a laboratory. In a few studies, handheld FTIR technique was used for the direct measurement of MPs in the field (Abidli et al., Citation2018; Tang et al., Citation2019). However, the handheld FTIR system is more expensive than the benchtop FTIR instruments. Handheld FTIR systems are commonly limited to characterizing the MP particles with size of 300–500 µm (Primpke, Christiansen, et al., Citation2020).
The µ-FTIR method allows chemical imaging of larger areas of membrane filters with high resolution using focal plane array (FPA) detectors (Bergmann et al., Citation2017, Citation2019; Cincinelli et al., Citation2017; Liu, Olesen, et al., Citation2019; Mintenig et al., Citation2017; Olesen et al., Citation2019; Primpke et al., Citation2017, Citation2018, Citation2019; Primpke, Cross, et al., Citation2020; Simon et al., Citation2018; Vianello et al., Citation2019; Zarfl, Citation2019). µ-FTIR technique is extensively used for chemical imaging () of different modes—coupled with ATR (Muhlschlegel et al., Citation2017; Pegado et al., Citation2018; Song, Hong, Jang, Han, & Shim, Citation2015; Wagner et al., Citation2017), transmission (Compa et al., Citation2018; Ding et al., Citation2018; Frias et al., Citation2010; Kuhn, Schaafsma, et al., Citation2018; Liu, Lu, et al., Citation2018; Loder et al., Citation2015; Lourenco et al., Citation2017) and reflection (Kanhai et al., Citation2018; Lares et al., Citation2018; Phuong, Poirier, et al., Citation2018; Tagg et al., Citation2015; Vianello et al., Citation2013; Wang, Peng, et al., Citation2017). Though µFTIR imaging is an effective method for MP characterization, it needs long measurement time (often greater than 20 h) of samples of MP particles on a filter (Kappler et al., Citation2016; Loder et al., Citation2015; Primpke et al., Citation2017). Moreover, it also poses the risk of sample contamination or loss. µFTIR in reflection mode is required a good reflection property and it is less suitable for colored or small MP particles, whereas transmission mode may show total absorption for large or thick particles (Primpke, Christiansen, et al., Citation2020).
Automatic FTIR imaging such as FPA (focal plane array) is used for fast acquisition of several spectra within an area through one single measurement. Liu, Olesen, et al. (Citation2019) used μFTIR imaging with a 125 × 125 Mercury-Cadmium-Telluride (MCT) FPA detector (spectral resolution of 5.5 μm) to identify the polymer types of MPs. Bergmann et al. (Citation2019) applied µFTIR equipped with a FPA (64 × 64 detector elements) for scanning an area of 20 × 20 FPA (14.1 by 14.1 mm), which allowed the detection of MP particles down to 11 μm in 4.5 h. Various sophisticated softwares are used for spectral correlation analysis in MP research. Approximately, 1.8 million spectra, which take 48 hrs data analysis time using the Bruker OPUS software, and take only 4 hrs time using the siMPle software to complete the spectral correlation (Peeken et al., Citation2018; Primpke, Cross, et al., Citation2020). Though mercury cadmium telluride (MCT) detector is used in µFTIR chemical imaging of MPs, it is a time-consuming method for larger filter areas (Harrison et al., Citation2012; Vianello et al., Citation2013; Yu et al., Citation2016). Loder et al. (Citation2015) used ten filters with different materials, pore size and thickness to test their applicability for FPA based MP characterization experiment using µFTIR (both reflectance and transmittance modes). Out of eight tested filters, only two filters, viz., polycarbonate and the aluminum oxide, were suitable for FPA based µFTIR measurements of MPs. The problems of remaining six filters were their IR window range, i.e., IR transparency was either too narrow, IR characteristics had high diffractive error (reflectance mode) or absorbance values much higher than 0.5, resulting in unclear IR spectra. Small MP particles were often concentrated on various filters (e.g., aluminum oxide filters, and metal covered PC filters) (Bergmann et al., Citation2017; Loder et al., Citation2015; Mani, Primpke, et al., Citation2019; Mintenig et al., Citation2017, Citation2019; Peeken et al., Citation2018; Primpke et al., Citation2017, Citation2018, Citation2019; Primpke, Christiansen, et al., Citation2020), silicon membranes (Kappler et al., Citation2015, Citation2016), slides (Kunz et al., Citation2016; Wagner et al., Citation2017), compression cells (Cai et al., Citation2019; Frias et al., Citation2014) and windows made of infrared transparent or reflective materials (Loder et al., Citation2015; Pham et al., Citation2017; Primpke, Christiansen, et al., Citation2020). The cost of aluminum oxide filter is cheaper than other filters (Bergmann et al., Citation2017; Mani, Primpke, et al., Citation2019; Mintenig et al., Citation2017, Citation2019; Primpke et al., Citation2017, Citation2018, Citation2019). However, the aluminum oxide filters have wavenumber limitation toward 3600–1250 cm−1 compared to other filters (FPA: 3600–900 cm−1 and even lowest for MCT (Primpke, Christiansen, et al., 2017, Citation2020). However, characterization of MPs using FTIR measurements cannot be performed in the presence of water as its spectrum will overlay the target spectra (Primpke, Christiansen, et al., Citation2020; Primpke, Cross, et al., Citation2020).
Within a FTIR spectrum of MP, not every spectral region contains relevant information (Renner, Nellessen, et al., Citation2019). Therefore, the spectrum can be reduced to a more compact and highly characteristic sub-spectrum, which can increase the selectivity of library searching (Hendrickson et al., Citation2018; Kappler et al., Citation2015; Kroon, Motti, Talbot, et al., Citation2018; Renner et al., Citation2017). Usually, FTIR spectra of MPs can be divided into three regions: 4000–2750, 2750–1850, and 1850–700 cm−1. Renner, Nellessen, et al. (Citation2019) found that the variance (intensity) and specificity (number of individual signals) are very high in the fingerprint region (1850–700 cm−1) (). Therefore, it is suggested that the fingerprint region is suitable for the identification of MPs, whereas the middle region (2750–1850 cm−1) is not appropriate for this purpose due to its low variance and specificity (Cabernard et al., Citation2018; Kappler et al., Citation2016). FTIR spectra for various types of polymers are shown in . These spectra have been evaluated using five different spectral ranges, such as stretching vibration of CH/CH2/CH3 groups (2980–2780 cm−1), CH2 bending vibration (1480–1400 cm−1), C = O stretching vibration (1760–1670 cm−1), C = O stretching vibration (1800–1740 cm−1) and CF2 stretching vibration (1174–1087 cm−1). FTIR spectra of unknown MPs can be effectively identified through comparing to a commercially available polymer library of known recorded spectra of polymers (Renner, Nellessen, et al., Citation2019).
4. Weathering and aging
Understanding the surface degradation of MPs in the environment increases our knowledge of the pollutant-plastic interaction. In addition, knowing the weathering of MPs is important for understanding the ecological impacts of the most common type of plastic debris. The environmental degradation of MPs via photo-, bio-, oxidative-, hydrolytic and altogether were studied using FTIR techniques by many researchers (Andrade, Fernandez-Gonzalez, et al., Citation2019; Auta et al., Citation2018; Bond et al., Citation2018; Brandon et al., Citation2016; Costa et al., Citation2018; Nazareth et al., Citation2019; Rajakumar et al., Citation2009; Ren et al., Citation2019; Tang et al., Citation2019; Tofa et al., Citation2019; von Friesen et al., Citation2019). FTIR results highlight three likely areas of weathering related changes in MPs: hydroxyl groups (broad peaks from 3100 to 3700 cm−1, centered at 3300–3400 cm−1), alkenes or carbon double bonds (1600–1680 cm−1) and carbonyls (1690–1810 cm−1). FTIR spectroscopy is used to measure the changes in chemical bond structures (carbonyl groups, hydroxyl, and carbon-oxygen) with weathering (Brandon et al., Citation2016). Carbonyl index (CI) is commonly used to measure the light induced photo-oxidation of polyethylene MPs, since it normally increases with increasing exposure time, i.e., increasing degree of photo-degradation (Endo et al., Citation2005; Veerasingam, Saha, et al., Citation2016). Carbonyl index is defined as the absorbance of carbonyl bond peaks relative to the absorbance of reference peaks (methylene bond). The carbonyl absorption bands are considered in the region 1760–1690 cm−1 and the methylene absorption bands are taken in the region 1490–1420 cm−1 (methylene scissoring peak) (Halle et al., Citation2016). Hydroxyl index (HI) is calculated as the ratio of the absorbance peak at 3340 cm−1 (3300–3400 cm−1) to the absorbance at reference peak. It is found that several reference peaks are used, including 974 and 2720 cm−1 for PP and 1465 and 2020 cm−1 for PE (Brandon et al., Citation2016). Rajakumar et al. (Citation2009) noted significant changes of HI only at the time of rapid growth of CI value. Carbon-oxygen index (COI) is measured based on the ratio between absorbance peak in the region 1000 to 1200 cm−1 and reference peak. Reference peak regions for PE and PP are 2908–2920 cm−1 and 2885–2940 cm−1, respectively. Changes in HI and COI values could be readily diagnosed by FTIR, followed by CI value (Brandon et al., Citation2016).
Recently, Andrade, Winemiller, et al. (Citation2019) found that FTIR could be used as a low-cost technique to monitor changes in different polymer types (polyamide, polypropylene and polystyrene) of MPs during oceanic aging. In polyamide MPs, the photo-oxidation and/or thermo-oxidation processes increase the intensity of 1150 cm−1 band in FTIR spectra. The IR spectrum of polypropylene MP changes substantially with weathering due to the appearance of following functional groups: 3370 and 3240 cm−1 (hydroxyl groups), 1640 cm−1 (C = O and double bonds), 1530 cm−1 (C = O ketones), 1440 cm−1 (carboxylic acids), 1140 cm−1 (alkanes), 1100 cm−1 (C–O bond), and 720 cm−1 (CH2) (Andrade, Fernandez-Gonzalez, et al., Citation2019; Tang et al., Citation2019). The FTIR spectra of weathered polystyrene MP showed spectral changes correspond to the formation of new bands at 3360–3240 cm−1 (hydroxyl group), 1640 cm−1 (double bond or C = O groups), and 1100 cm−1 (C-O bonds) (Andrade, Fernandez-Gonzalez, et al., Citation2019). The degree of crystallinity of polymer is a key variable in defining the morphological, physical and mechanical properties of the MP. Crystallinity is calculated by the method used in Stark and Matuana (Citation2004). The doublet peaks observed at 1474–1464 cm−1 and 730–720cm−1 correspond to PE crystalline content (1474 and 730 cm−1) and amorphous content (1464 and 720 cm−1), respectively. The percentage of the crystalline content, X, can be calculated using the following equation: where Ia and Ib can be determined from the bands at either 1474 and 1464 cm−1 or 730 and 720 cm−1, respectively. Crystallinity increases when chain scission occurs in MPs. The shorter chains produced by chain scission events can crystallize more readily than the crosslinks. The chain scission affects the tie molecules, and thereby the crystallinity is decreased. Holmes et al. (Citation2014) found that the weathering process is more influenced in the absorption of trace metals by MPs than its polymer types. It is found that during the aging process, the absorbance ratio between contaminant vibrational band and polymer vibrational band is increased. However, aging of polymers is a very complex process and it is nearly impossible to estimate average duration of existence of MPs in an environmental compartment. Instead, aging extent of several MPs can be compared with one another (Renner et al., Citation2017). Wang, Zhou, et al. (2019) reported that the probable sources of major MPs can be identified based on polymer types, shape and topographic features.
5. Ecotoxicology
Globally, environmental-vector of MPs have been studied in various marine and freshwater biota, especially in fish, bivalves and birds (Anbumani & Kakkar, Citation2018; Chang et al., Citation2020; Du et al., Citation2020). Several toxicology studies (organismal-vector) including uptake of MPs and associated pollutants have been conducted in laboratories (Browne et al., Citation2013; Cole et al., Citation2013; Koelmans et al., Citation2016). Fishes and bivalves, which are used as bio-indicators to assess the health of aquatic ecosystems, are also used as the most common organisms to study ecotoxicology of MPs. The major toxic effects of MPs on biota can be categorized as follows: (1) physical toxicity, (2) chemical toxicity, (3) cellular toxicity, and (4) Toxicity due to pathogenic microbes (Bhattacharya & Khare, Citation2020). Following are the adverse effects of ingested MPs in aquatic and terrestrial organisms reported in the publications: (1) feeding activity and behavioral changes (Bour et al., Citation2018; Scherer et al., Citation2017; Wang, Mao, et al., Citation2019; Wu, Tao, et al., Citation2019), (2) inhibition of growth, reproduction and fecundity (Garrido et al., Citation2019), (3) histopathological damage and/or death (Lei et al., Citation2018), (4) Oxidative stress (Yu et al., Citation2018), (5) neurotoxicity (Barboza et al., Citation2018), (6) immune system responses (Avio et al., Citation2015), (7) changes in gene expression (Rochman et al., Citation2014, Citation2015), and (8) energy deficiency (Rodriguez-Seijo, Citation2018). Prokic et al. (Citation2019) found that in biota, MPs can have the following effects: (1) induce oxidative damage (increased lipid peroxidation and DNA strand breaks), (2) alter anti-oxidative system (superoxide dismutase, catalase and glutathione peroxidase were parameters with the highest and significant changes in activities) and metabolism (isocitrate dehydrogenase and lactate dehydrogenase activity), and (3) have neurotoxic effects (inhibition of acetylcholinesterase activity). These effects depend on size and dose of used MPs, and/or their interaction with other xenobiotics.
FTIR spectroscopic imaging (µFTIR) is found to be label-free, nondestructive chemical analysis and powerful tool for studying live biological cells (Chan & Kazarian, Citation2013; Baker et al., 2014). Recently, µ-FTIR spectroscopy was used to describe the distribution of MPs in different fish organs and the possibility of bio-accumulation in fish tissues (Su, Deng, et al., Citation2019). Sun, Chen, et al. (Citation2018) used FTIR technique to investigate the toxic effects of polystyrene nano- and micro-particles on the marine bacterium Halomonas alkaliphila. FTIR absorption bands for carbohydrate, polysaccharides, and amide were shifted to a higher wavenumber when Halomonas alkaliphila was exposed to nanoplastics, but not in MPs. Thus, the size of plastics plays an important role in the alteration of the bacterial chemical composition (Sun, Chen, et al., Citation2018). Therefore, FTIR technique is not only used to identify the polymer types of MPs ingested by biota, but also used to investigate the toxicity effects in the biota.
6. Analytical methods and future challenges
The quality, spectral contrast and quantitative precision of FTIR spectrum recorded from a MP sample depends on the choice of sample preparation method and/or sampling technique. Transmission, attenuated total reflectance, diffuse reflectance, reflectance (mapping) and reflectance (focal plane array mapping) techniques are used extensively in MP research, and every technique has its own advantages and disadvantages () depending on analytical issue and sample properties (Renner et al., Citation2016). Three steps are followed to characterize the MPs using FTIR spectra: (1) inspection of data quality, (2) evaluation of FTIR spectra to identify the corresponding MPs, and (3) identification using spectral library search—calculation of a similarity value called “Hit Quality Index” (HQI).
Inspection of data quality has two steps—looking at the characteristic shape of the whole spectrum and characterizing individual vibrational bands. However, this inspection method requires much experience and it is very time consuming. Smoothing and baseline correction are important to improve the quality of FTIR spectra of MPs (smoothing to increase signal-to-noise ratio). The moving average and Savitzky-Golay smoothing are well established and both are useful techniques to enhance the certainty of results. The common baseline correction methods used in FTIR spectroscopy are Savitzky-Golay differentiation (based on Savitzky-Golay smoothing), rolling-circle filter, asymmetric least squares, and adaptive iteratively reweighted penalized least squares (Renner, Nellessen, et al., Citation2019).
Evaluation of FTIR spectra is the most critical step in MP analysis. Manual interpretation of relevant absorption peaks based on reference tables and comparison of complete spectra with a reference spectral library are the two common approaches in the evaluation. Manual interpretation is time consuming and requires expert knowledge, and thus, it suits only for a low throughput quantity. Spectra obtained from analysis of MPs are typically compared and matched with those of model samples from library databases. For example, in one study, the spectra matched with HQI ≥0.7 were accepted, those with HQI <0.6 were rejected and spectra with HQI = 0.6 were individually interpreted (Woodall et al., Citation2014).
FTIR spectra acquired from different modes (transmission, reflection and diffuse reflectance) are not the same (Picollo et al., Citation2014). Only a few researchers are working on this topic (Xu & Gowen, Citation2019; Xu, Thomas, et al., Citation2019), and adequate attention is not given for comparing/matching the unknown spectra with literature/spectral library. Several degradation processes in MPs cause spectral alterations relative to pristine reference library spectra. Thus, library searching could be vulnerable to misidentification of MP samples. However, most studies ignored spectral changes caused by MP degradation when comparing or matching with the reference spectral library. Therefore, it is important to improve new library searching procedures, which are more robust and can handle the problem of comparing the weathered MPs with virgin polymer references. Substrate (holding MPs) has a minimum spectral interference and can immobile the MPs especially for µ-FTIR imaging, where the stage moves during scanning (Corami et al., Citation2020; Vianello et al., Citation2013; Xu, Thomas, et al., Citation2019). Therefore, it is necessary to address the importance of appropriate substrate material for obtaining high quality results with minimum spectroscopic interference in the FTIR spectra.
In general, two approaches are followed to analyze MPs on filter materials: (1) measurement of complete filter area spot by spot (Kappler et al., Citation2016; Loder et al., Citation2015; Primpke et al., Citation2017) and (2) measurement of selected points of interest (Maes et al., Citation2017). In complete filter measurement method, the maximum number of spots are analyzed (also high analysis time) and big data sets are needed to be evaluate. However, without either FPA detector or charge-coupled device, this approach is not recommended. In the select points of interest measurement method, the number of spots (also less analysis time) is reduced, and FPA detector is not needed. But there is a risk of overlooking MP particles and also an additional step is required to define points of interest (Renner et al., Citation2020). Though the automated evaluation method demonstrated that the analysis time has decreased from several days to 4–9 h for a scanning, only recently this technique is introduced in the MP research (Chen et al., Citation2020; Primpke, Christiansen, et al., Citation2020). Therefore, further improvements are needed in constructing a reference spectrum for weathered MPs, and also reducing the analytical time. Moreover, training the classifier can increase the analysis speed substantially when dealing with large datasets of FTIR spectra. For example, automated identification methods were tested based on hierarchical cluster analysis (Primpke et al., Citation2018), shortwave infrared imaging (Schmidt et al., Citation2018), identification of the most relevant bands (Renner et al., Citation2017; Renner, Nellessen, et al., Citation2019), random decision forest method (Hufnagl et al., Citation2019), modified chemometric identification concept (Renner, Sauerbier, et al., Citation2019), machine learning method (Kedzierski et al., Citation2019), Python based μFTIR mapping (Renner et al., Citation2020) and Hybrid fusion method (Chabuka & Kalivas, Citation2020). The analysis of FTIR spectra is time-consuming as often it is needed to compare the spectra one by one with the reference spectra. Moreover, appearance of additional bands in the spectra due to aging of MPs and/or fouling present on particles is a significant part of misinterpretation. More often, the reference spectra in the spectral library are made of new and clean plastics, and there could be a possibility that MPs may not be identified successfully with the matching algorithm and spectral library of FTIR instrument. Therefore, it is mandatory to develop additional accessories to combine with FTIR techniques for the characterization of MP particles less than 10 µm size.
7. Conclusions
MPs have been identified and reported in environmental matrices from the poles to equator and from atmosphere to deep ocean. Though the usage of FTIR techniques in MP research has increased tremendously since 2004, there are still some challenges to be overcome in the area of standardizing the operational protocols for identification and quantification. Among the reviewed research articles, ATR-FTIR has been used in 60% of the studies to characterize different polymer types at various environmental matrices. Attenuated total reflectance (ATR) technique coupled with FTIR spectroscopy is widely used to characterize the large size MPs, whereas smaller MPs require the use of µFTIR coupled with detector, especially, µFTIR coupled with focal plane array detector facilitates a much faster generation of chemical imaging of MPs by simultaneously scanning several thousand spectra within a single measurement. FTIR technique is also used to study the changes in chemical bond structures (hydroxyl, carbonyl groups and carbon-oxygen) of MPs during various weathering process. Moreover, FTIR method is used to understand the ecological effects of ingested MPs and its associated pollutants and biochemical variations at the cellular level. Following criteria are needed to be considered during data processing, evaluation and identification MPs using FTIR spectroscopy: (1) when we compare/match an unknown spectrum with literature or a commercial spectral library, it is necessary to check the mode of acquisition of FTIR spectra (acquired the same mode or different modes), (2) the spectral change caused by weathering and aging, when comparing or matching with the spectral library, and (3) desirable substrate to be used to reduce the spectral interference. Standardization of chemometric techniques, decrease in data processing time, better file handling capabilities of systems are expected to improve FTIR analysis in MP pollution research. Since identification of MP particles <10 µm using FTIR technique is a challenging task, development of novel additional accessories or proper combination use of existing techniques is needed for future MP research.
Supplemental Material
Download MS Word (90.1 KB)Acknowledgements
This work was carried out under the following projects: (1) QUEX-ESC-QP-TM-18/19, funded by Qatar Petroleum through ESC, Qatar University, Qatar, (2) INT/RUS/RFBR/P-339, funded by Department of Science & Technology, India, and (3) RFBR No. 18-55-45024, funded by RFBR, Russia. Open Access funding provided by the Qatar National Library.
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