Keywords

3.1 Introduction

Contamination in the environment is generally linked with global warming, being mainly caused by extensive industrialization, high population density, and highly urbanized areas (Akpor and Muchie 2011). Negative consequences to human and animals’ health arise from improper discarding of pharmaceutical waste, endocrine disrupting compounds, personal care products, and household care products. They may include hormones, glucocorticoids, analgesics – ibuprofen, estriol, additives in drugs, etc. – and cosmetics containing siloxanes and parabens. Figure 3.1 shows a flowchart depicting sources and fate of the so-called emerging contaminants (ECs) (Gogoi et al. 2018). Unfortunately, since there is no regulation for emerging contaminants, they are not monitored in the environment (Noguera-oviedo and Aga 2016). Hence, pesticides are detected in groundwater and drinking water, even though there is a growing effort of environmental protection companies to replace these products with environmentally friendly substitutes (Aamand et al. 2015). Furthermore, existing treatments of wastewater or drinking water are not efficient to remove estrogens, androgens, or detergent compounds (Adeel et al. 2017; Kot-wasik et al. 2007).

Fig. 3.1
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Schematic design with the potential sources of emerging pollutants in the environment. (Reproduced from Ref. (Rasheed et al. 2019) with permission from Elsevier, 2018)

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Potential health problems have been usually associated with excessive amounts of emerging contaminants in drinking water, as illustrated in Fig. 3.2, including breast and prostate cancer. The effects of prolonged hormone exposure in aquatic ecosystems, even at low levels (<0.001 mg L−1), can lead to adverse effects on aquatic organisms (Jennifer et al. 2017; Kot-wasik et al. 2007) such as estrogens which may affect fish physiology and reproductive maturity in domestic and wild animals. Estrogens and steroid precursors affect roots, flowering, and germination of plants (Adeel et al. 2017). The awareness about environmental issues is crucial to forge environmentally friendly technologies according to the rules of sustainable growth (in other words, green chemistry plus green technology). In this context, also relevant are the analytical methodologies to detect trace concentrations of a broad spectrum of pollutants (Kot-wasik et al. 2007).

Fig. 3.2
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Schematic design on side effects of emerging contaminants. (Reproduced from Ref. (Rasheed et al. 2019) with permission from Elsevier, 2018)

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This chapter reviews the state of the art of groups of emerging contaminants (pesticides, polluters, and pharmaceutical chemicals) and their negative impacts on the environment. In addition, a brief description of standard analytical methodologies is provided, with emphasis on biosensors and sensors to detect emerging contaminants.

3.2 Side Effects of Pesticides

Pesticides are used in agriculture to prevent and control the spread of weeds, bacteria, insects, and rodents. Their use has increased agricultural productivity, helping to secure nearly one-third of the global crop production (Samsidar et al. 2018). In addition, pesticides are useful for controlling vegetation growth, in pet care products, and preventing disease vectors from spreading. More than 1000 pesticides are commercialized, and this number keeps increasing owing to the emergence of resistant pests (Rejczak and Tuzimski 2015). Unfortunately, most of these compounds are toxic, and their indiscriminate use yields major risks to human health, especially for agricultural workers and people living close to farms. Also, exposure to pesticides can cause long-term health effects such as cancer, Parkinson’s, Alzheimer’s, multiple sclerosis, and cardiovascular diseases (Mostafalou and Abdollahi 2013).

Pesticides are classified based on the target pests and their origin – chemical or biological (Rawtani et al. 2018) – as shown in Fig. 3.3. Biopesticides are derived from natural sources, including animals, plants, bacteria, and minerals. Chemical pesticides have been synthesized to kill different types of pests and are classified as insecticides, herbicides, fungicides, rodenticides, and nematicides (Samsidar et al. 2018). Organophosphates, carbonates, and organochlorines are among the most known chemical pesticides. Compounds such as dichlorodiphenyltrichloroethane (DDT), atrazine, malathion, and parathion have been related to adverse effects on the environment, which include destruction of the habitat of different species (Rawtani et al. 2018).

Fig. 3.3
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Classification of pesticides. (Figure based on Rawtani et al. (2018))

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3.2.1 Analysis of Pesticides

Many countries have established regulations to control the level of pesticides in the environment, especially in water, raw vegetables, and fruits (Samsidar et al. 2018; Yan et al. 2018). In order to enforce these regulations, there is an increasing demand for sensitive and accurate analytical tools to detect low concentrations of pesticides. Analytical methods have been based on conventional techniques – high-performance liquid chromatography (LC) (Picó et al. 2004; Thurman et al. 2001), capillary electrophorese (CE) (Hsu and Whang 2009), and gas chromatography (GC) (Guan et al. 2010). These techniques can be used in combination with several detectors depending on the pesticide and sample analyzed (Rejczak and Tuzimski 2015). For instance, nonvolatile pesticides have been detected using LC coupled to UV detectors, fluorescence detectors, diode-array detectors (DAD), and mass spectrometry (MS). Polar and easily vaporizable compounds are normally detected using GC coupled to detectors such as flame photometric detector (FPD), flame ionization detector (FID), and nitrogen phosphorus detectors (NPD) (Rejczak and Tuzimski 2015).

A crucial step toward the efficient detection of pesticides in complex matrices, e.g., soil, natural waters, and food, is a sample pretreatment to remove potential interferents that may impair an accurate analysis. Efforts have been made to develop procedures for sample extraction and purification, including liquid-liquid extraction (LLE), solid-phase extraction (SPE), matrix solid-phase dispersion (MSPD), solid-phase microextraction (SPME), stir bar sorptive extraction (SBSE), and quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction (Rejczak and Tuzimski 2015). In addition to removing impurities, many of these methodologies allow one to concentrate the analytes, which is more suitable to detect trace concentrations. An alternative to pretreatment methods is to employ molecularly imprinted polymers (MIPS), which are 3-D polymeric matrices with complementary cavities designed for a template molecule (Sarafraz-yazdi and Razavi 2015). They are suitable for this protocol owing to their high selectivity, relatively low cost, stability, and easy preparation. MIPs have been used as sorbents for SPE, MSPD, and SPME methods for selective extraction of pesticides from food (Djozan et al. 2009) and human serum (Zhang et al. 2019a). Magnetic MIPs have also been used (Karimian et al. 2017), and these hybrid materials show high selectivity, with their magnetism effect allowing an effect of sample separation without requiring additional filtration or centrifugation steps.

Combining sample pretreatment approaches and analytical characteristics from more conventional techniques has made it possible to detect single molecules and mixtures of pesticides, as illustrated in Table 3.1. It should be mentioned, however, that many experimental methods require sophisticated equipment and trained operators and usually are time-consuming, limiting their application for real-time and on-site detection.

Table 3.1 Analytical methods for detecting pesticides residues
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3.2.2 Sensors and Biosensors for Pesticide Detection

The growing need for analytical methods for a rapid, selective, and accurate detection of pesticides has motivated the development of relatively low-cost sensors and biosensors. These devices normally contain nanomaterials: carbon nanotubes (Kaur et al. 2019), graphene derivatives (Hashemi et al. 2019), quantum dots (Wang et al. 2019b), and metal nanoparticles (Jiang et al. 2018). Transduction methods for these sensors include electrochemistry (Velusamy et al. 2019), fluorescence (Wu et al. 2019), surface-enhanced Raman scattering (SERS) (Jiang et al. 2018), and surface plasmon resonance (SPR) (Cakir et al. 2019). A large enhancement in SERS signal may arise from plasmonic nanostructures, then permitting detection of analytes at very low concentrations. For example, a SERS sensor containing Ag-coated Au nanoparticles (Au@Ag NPs) detected insecticide residues in peach simultaneously (Yaseen et al. 2019). Figure 3.4 shows the results for Au@Ag NPs with 26 nm Au core size and 6 nm Ag shell yielded to enhance Raman signals for pesticides, in which the limits of detection were 0.1 mg kg−1 for thiacloprid and 0.01 mg kg−1 for profenofos and oxamyl.

Fig. 3.4
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Schematic design for a surface-enhanced Raman scattering (SERS) sensor for detecting thiacloprid, profenofos, and oxamyl in peach. (Reproduced with permission from Yaseen et al. 2019)

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Biosensors have been preferred for detecting pesticides due to their selectivity provided by biological components acting as recognition units, viz., enzymes, antibodies, nucleic acids, microorganisms, biological tissues, and organelles. They can be used in combination with a physical transducer to generate intense signals due to changes in concentration of a specific analyte (Madrid et al. 2017). The selectivity of biosensors may allow for analyte detection even in complex matrices (Saini et al. 2017). Enzymes are utilized in electrochemical biosensors to detect pesticides since many products of enzymatic reactions show electroactive responses. Enzymes are usually more stable and less expensive than other common biomolecules such as antibodies (Fabiana Arduini et al. 2016). The detection protocols using enzymatic biosensors involve monitoring changes in pesticide concentration by means of either enzymatic reactions or enzyme-inhibition mechanisms.

Many catalytic biosensors contain organophosphorus hydrolase (OPH), which catalyzes the hydrolysis of organophosphorus compounds, including parathion and methyl parathion, by breaking P-O, P-S, and P-CN bonds (Sassolas et al. 2012). The hydrogen ions and alcohols generated as enzymatic products can be monitored by electrochemical and optical techniques (Sassolas et al. 2012). Wearable potentiometric tattoo biosensors have been built with OPH immobilized onto screen-printed transducers to detect diisopropyl fluorophosphate (DFP) (Mishra et al. 2018). Figure 3.5 shows the principle of detection for these biosensors made with electrodes printed onto a temporary tattoo paper after being modified with a pH-sensitive polyaniline (PANI) film. This PANI film helps to monitor hydrogen ion released from the enzymatic hydrolysis of DFP. This biosensor was also efficient to detect other organophosphates. Catalytic biosensors, nonetheless, have drawbacks that restrict their widespread use, including a limited number of enzymes available for catalyzing the hydrolysis of pesticides. For example, OPH-based biosensors detect only some organophosphorus compounds, since large molecules with more complex structures do not interact effectively with active enzymatic sites (Mulyasuryani and Prasetyawan 2015).

Fig. 3.5
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Illustration of tattoo biosensors for detecting nerve agents. (Reproduced with permission from Mishra et al. 2018)

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Biosensors based on enzymatic inhibition mechanisms, where the analyte is quantified through its ability to inhibit enzyme function, are more sensitive for detecting pesticides than catalytic biosensors. Figure 3.6 shows the operation principle in which the enzymatic activity can be monitored. After addition of the inhibitor, the catalytic activity decreases and so does the analytical signal (Amine et al. 2015). The properties and operation parameters for these biosensors depend on the enzyme-inhibitor interaction, which is classified as reversible or irreversible. When the interaction is irreversible, covalent bonds are formed between the inhibitor and the active site of the enzyme leading to permanent loss of enzymatic activity (Aziz Amine et al. 2006). For biosensors based on reversible inhibition, on the other hand, the enzymatic activity can be restored by washing them with water or buffer solutions, which allows one to perform multiple measurements with a single device (Amine et al. 2015).

Fig. 3.6
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Reversible and irreversible inhibition detection using biosensors based on enzyme inhibition mechanism. (Reproduced with permission from Amine et al. 2015)

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The activity of cholinesterase is inhibited irreversibly by organophosphorus and carbamate pesticides (Fabiana Arduini et al. 2010; Pundir and Chauhan 2012). These enzymes are found in insects and vertebrates, being responsible for catalyzing the hydrolysis of the acetylcholine neurotransmitter, a crucial step in the transmission of nerve impulses. Two types of cholinesterase are known, which are mainly distinguished by their substrate specificity: acetylcholinesterase (AChE), which has a higher catalytic activity toward acetyl esters, e.g., acetylcholine, and butyrylcholinesterase (BChE), which preferentially hydrolyzes butyrylcholine (Saini et al. 2017). The reaction products can be monitored using potentiometry or optical methods with pH-sensitive indicators (Sassolas et al. 2012). A simpler methodology involves artificial substrates such as acetylthiocholine and butyrylthiocholine, whose hydrolysis product – thiocholine – can be detected electrochemically at relatively low potentials. Bi-enzymatic and tri-enzymatic biosensors have also been developed, in which enzymes such as choline oxidase and peroxidase can be used to produce electrochemically detectable species (Andreescu and Marty 2006).

Paper-based biosensors relying on enzymatic inhibition have been reported for low-cost, user-friendly determination of pesticides. Arduini et al. (2019) developed paper-based biosensors using butyrylcholinesterase, alkaline phosphatase, and tyrosinase on screen-printed electrodes modified with carbon black and Prussian blue nanoparticles to improve sensitivity. Paraoxon, 2,4-dichlorophenoxyacetic acid, and atrazine were detected in standard solutions and river water samples using amperometry. A relevant limitation of biosensors based on enzymatic inhibition is the low selectivity for several enzymes, and this may impair pesticide detection in complex matrices of environmental interest owing to the presence of other, competitive inhibitors. Therefore, most of these sensors are used for screening purposes and not for detecting specific molecules (Jiang et al. 2008).

Immunosensors and aptasensors are useful to detect pesticides, since antibodies and aptamers are able to recognize analytes. For immunosensors, the interaction between antibodies (Ab) and antigens (Ag) is affected by the concentration of a specific analyte (Jiang et al. 2008). In addition to their use for detecting biomarkers of various diseases, immunosensors serve to detect pesticides and other compounds through advances in biotechnology where antibodies are generated which are specific for several molecules (Fernández-Benavides et al. 2019; Jiao et al. 2018). Aptasensors are promising for performing selective, fast, and sensitive detection of pesticides at low concentrations. They can be used in sensors as recognition elements as short oligonucleotides of RNA or DNA synthetized using the selection evolution of ligands by exponential enrichment (SELEX) technique (Liu et al. 2019). With SELEX, molecules can be obtained which possess high binding affinity and selectivity against a target analyte without using animals or cell cultures. In addition to the advantages in the production process, aptamers are more stable than antibodies and enzymes, allowing the use of aptasensors under harsh conditions. Aptasensors exploiting electrochemical techniques (Fu et al. 2019; Xu et al. 2019) and fluorescence (Cheng et al. 2018) have been used to detect pesticides.

3.3 Pollutants and Side Effects

The rapid population growth and industrialization have led to discarding a huge number of contaminants into the environment, which is why the twenty-first century was coined the Century of the Environment (Azam et al. 2016). Most pollutants are hazardous and poisonous, as the case of volatile organic compounds (VOCs) (Liu et al. 2018; Malik et al. 2018), heavy metals (Kamilari et al. 2018), toxic inorganic gases (Joshi et al. 2018), dyes (Nguyen and Saleh 2016), food preservatives, and personal care products. They pose severe threats for human beings and the environment. VOCs, for instance, can easily evaporate from household products such as paints, cleansers, and furnishings, causing short- and long-term adverse effects (Spinelle et al. 2017). Real-time monitoring of VOCs is now required for several types of industries, including cosmetics, medical diagnosis, food, and beverages, and long-term exposure can cause damage to the liver, kidney, and central nervous system (Jung et al. 2012).

The International Agency for Research on Cancer (IARC) has stated that online monitoring of formaldehyde should be performed in indoor environments because formaldehyde has been linked to cancers in the nasal cavity, mouth, throat, skin, and digestive tract (Mandayo and Castaño 2013). A major concern is water contamination in community services, particularly with heavy metals (Tchounwou et al. 2012). Metals such as Hg, Pb, As, and Cd are known as bioaccumulative compounds in the human body, resulting in multi-organ disruption (Jaishankar et al. 2014; Karri et al. 2016). Another class of pollutants includes additives and dyes in foods and textile industries (Sorouraddin et al. 2015). A synthetic diazo colorant, allura red, used in beverages, ice cream, and bakery products, is known for its carcinogenic effect, also being the main cause of hyperactivity in children. In addition to those linked to air and water quality systems (Scotter 2015), there are pollutants such as brominated flame retardants (Darnerud 2003) and textile dyes used for dyeing and finishing operations. Table 3.2 shows a list of air and water pollutants and adverse effects on mankind and animals.

Table 3.2 Examples of air and water pollutants – sources and effects (Kaur and Nagpal 2017; Muralikrishna 2017)
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3.3.1 Analytical Techniques for Pollutant Detection

Quantitative and qualitative measurements of pollutants are necessary to control air and water pollution. However, these measurements are not straightforward, especially owing to the presence of interferents (Qin et al. 2013). Moreover, managing pollution requires detection of pollutants at low concentrations (Gauquie et al. 2015), which depend on mainly on:

  • Pollutant state (liquid, gaseous, aerosols, or particulate matter)

  • Sample preparation and concentration level

  • Measurement period (short or long term)

  • Measurement site (in lab or on-site)

  • Temperature and humidity effect and control

  • Cross-sensitivity with other analytes

  • Reliability and stability check with commercial sensor

For monitoring air quality, there are methods to detect hazardous analytes in the environment, as illustrated in Table 3.3. However, stability and selectivity are still a challenge for current sensor technologies. Optical and electrochemical sensors can offer high sensitivity, but bulky dimensions and high-power consumption do not allow them to be widely applied for health-care or mobile applications.

Table 3.3 Air quality sensors and detection principle (Aswal and Gupta 2006)
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There are also analytical techniques to detect pollutants such as heavy metals, VOCs, food dyes, and brominated flame retardants, as depicted in Table 3.4.

Table 3.4 Detection techniques and detection principles for heavy metals, food dyes, VOCs, and brominated flame retardants (Holbrook et al. 2012; Hori et al. 2013; Zhu et al. 2017).
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3.3.2 Sensors and Biosensors to Detect Pollutants

The need to detect pollutants in air, soil, and water has sparked research into analytical techniques (Goradel et al. 2017) to replace conventional chromatography that requires expensive, time-consuming sample preparation. Cost-effective, robust, and portable biosensing and gas sensing devices have been proposed (Materón et al. 2019) with the majority of biosensors incorporating nanomaterials to enhance sensitivity and selectivity (Hernandez-Vargas et al 2018). Electrochemical biosensors, in particular, can detect biological analytes at low concentrations with various techniques, including potentiometric, amperometric, voltammetric, and conductometric measurements (Hernandez-Vargas et al. 2018; Justino et al. 2017). Air pollution caused by hazardous gases from textile and automobile industries has become a serious issue. The major gases that cause air pollution are carbon monoxide and nitrogen oxides, and their main source is fossil fuel combustion (Joshi et al. 2018). Volatile organic compounds (VOCs) are produced by construction materials and paint industries, which may even cause headache and skin trouble for people moving into a new apartment (Campos and Sarkis 2018). For example, formaldehyde is produced in industries in the manufacture of resins, as a disinfectant, or as a preservative in consumer products; it is a dangerous indoor pollutant as it can harm all kinds of organisms (Chung et al. 2013; Lawal et al. 2017). The allowed concentration of formaldehyde is only 0.1 ppm in Netherlands and Germany (Chmielewski 2011). Also, the US Environmental Protection Agency (US EPA) has imposed strict regulations on the concentrations of environmental contaminants in air and water. In this section we will discuss the sensors and biosensors for detecting heavy metals, hazardous gases and VOCs, food dyes, and brominated flame retardants.

  • Heavy Metal Detection

Due to increasing industrial activity, heavy metals such as Hg, AS, Pb, and Cd have been entering into the environment which are highly toxic and carcinogenic even at a trace level. They are not biodegradable and will therefore remain for decades once released in the environment and appear at detectable levels in food resources (Tangahu et al. 2011). The sensitive conventional methods to detect heavy metals include atomic absorption spectroscopy and atomic emission spectroscopy. These methods require laborious preparation and pretreatment procedures and professional personnel (Chinna et al. 2018).

Electrochemical, optical, and field-effect transistor (FET)-based sensors have been developed using nanostructures and nanomaterials (Fig. 3.7). Luo et al. (Luo et al. 2009) used silicon nanowires (SiNWs) in FET sensors for detecting toxic heavy metal cations with a LOD of 10−7 mol L−1 for Hg2+ and 10−4 mol L−1 for Cd2+. The chemical gating effect and strong chelation between thiol groups with positively charged cations is the main reason for the high sensing behavior, and sensors could also be recycled with nearly the same sensitivity as before. Figure 3.7a shows the measuring setup, while Fig. 3.7b shows the I-V behavior of the SiNW before and after thiol modification. The ohmic contacts are formed between electrodes and SiNW, and the modification induces slight decreases in the conductance of SiNW. Figure 3.7c indicates the current change by varying Cd2+ concentration in solution. Compared to distilled water (pH = 4), the change in current was increased by 10%. When Cd2+ ion of 10−4 mol L−1 was introduced and as Cd2+ concentration further increased to 1 × 10−3, 3×10−3, 1×10−2, 2×10−2, and 4 × 10−2 mol L−1, the current increased by 28.1%, 40.2%, 56.6%, 66.7%, and 67.4%, respectively. Similarly, the current changed with the Hg2+ concentration, as illustrated in Fig. 3.7d.

Fig. 3.7
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Sensors for detecting heavy metals (a) Sensing setup system; (b) I-V characteristics of a SiNW before (dotted line) and after thiol modification; (c) current changing with increasing Cd2+ concentration; (d) current variation with increasing Hg2+ concentrations. (Reproduced with permission from (Luo et al. 2009), Copyright 2009, American Institute of Physics)

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Optical sensors to detect heavy metals can exploit various principles, including colorimetry, surface plasmon resonance (SPR), and surface-enhanced Raman scattering (SERS) (Meyer et al. 2011; Prabowo et al. 2018; Jiangcai Wang et al. 2017). SERS sensors have been used for chemical and biological sensing and medical diagnostics, but few reports exist of detection of heavy metals. SERS is the molecular spectroscopy which provides spectral fingerprints of target analytes. It is unable to detect heavy metals directly, so the plasmonic nanostructures are functionalized with organic ligands that bind specifically to heavy metal ions. Jinglian Li et al. (2011) developed SERS sensors for As3+ detection in aqueous media with glutathione (GSH)/4-mercaptopyridine (4-MPY)-modified silver nanoparticles (AgNPs). Figure 3.8a shows increased SERS signal with addition of As3+ ions owing to the As-O linkage established when the distance among AgNPs was shortened with a moderate amount of GSH and 4-MPY. The sensor achieved a limit of detection (LOD) of 0.76 ppb with selectivity over various metal ions (Fig. 3.8b). However, long-term stability and repeatability of the SERS-based sensors are still a major concern.

Fig. 3.8
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(a) Representation of glutathione (GSH) and 4-MPY-modified AgNPs; (b) SERS sensor for selective As3+ detection using silver nanoparticles. (Reproduced with permission from Jinglian Li et al. (2011). Copyright 2011, American Chemical Society)

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  • Chemical Sensors for Detection of Toxic Pollutants

Chemical sensors are a crucial part of modern life with applications in environmental monitoring, domestic safety, public security, and food quality assessment among others (Swager and Mirica 2019). They are increasingly being integrated into mass-market applications, for instance, in air quality control in buildings and motor vehicles and in traditional areas of toxic and explosive gas detection. The market for gas sensors is growing with new applications driving innovation, for instance, the analysis of gases from the gut and breath for noninvasive diagnosis of diseases (Bogue 2017). Chemiresistive sensors comprise an important part of the gas sensor market, against a host of competing technologies, due to their low cost, high sensitivity, fast response, and relative simplicity (Liu et al. 2012). The materials used in these sensors are typically wide-bandgap semiconducting metal oxides, such as tin oxide, tungsten oxide, indium oxide, or zinc oxide (Domènech-gil et al. 2017; Joshi et al. 2016; Jinwei Li et al. 2015b; Sayago et al. 2019). They function as gas sensors because adsorbed gaseous species form surface states in the metal oxide by exchange of electrons with the bulk material. The concentration of the surface states is proportional to the partial pressure of the gas impinging on the metal oxide, and hence the conductivity of the material changes in response to changes in gas concentration. These chemically induced changes can then be transduced into electrical signals by means of simple conductivity measurements.

Metal oxides are the most common and even commercially available sensors; however, they rely on high temperature modulation to achieve high sensitivity and selectivity which decreases the sensor lifetime and makes the system more complex (Zhou et al. 2014b). In order to obtain room temperature sensing, 2D materials have been investigated owing to their high surface to volume ratio, but the speed of recovery is still a limitation. Liu et al. (2018) demonstrated new AC phase sensing of graphene FETs for chemical vapors with fast recovery, with a new concept illustrated in Fig. 3.9. To get rid of the effects of trap states and defects, those authors used the reversible and stable phase change as the sensing parameter instead of the vulnerable DC resistance (see Fig. 3.9a). The phase lag between channel resistance and the gate voltage was detected with the AC voltage applied on the gate electrode, as shown in Fig. 3.9b. The recovery speed is ten times faster than with DC resistance signals. Figure 3.9c illustrates the key difference between AC and DC measurements where AC measurements are more sensitive to weak adsorption of vapor molecules, while DC measurement results are sensitive to a strong adsorption-desorption process. Malik et al. (2018) employed Au-TiO2@g-CN nanohybrids to detect volatile organic amines (VOAs), such as triethylamine (TEA), using a two-step method (hydrothermal and nanocasting). The average times for response and recovery of the Au-TiO2@m-CN sensor toward TEA gas are 9–16 and 6–12 s for 1–50 ppm range.

Fig. 3.9
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(a) Schematic of gas sensing performance using the phase lag detection method with fast recovery compared to the DC resistance method. (b) Schematic of phase lag φAB,g between VAB and Vg on a CVD graphene FET sensor under the exposure to chemical vapor. (c) Vapor adsorption process and desorption on the graphene surface illustrating that the AC sensing scheme is more effective to detect weakly adsorbed gases away from the graphene surface, while the DC sensing scheme is more effective to detect molecules close to the surface. (Reproduced with permission from (Liu et al. 2018) Copyright 2018, Elsevier)

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  • Detection of Food Dyes

Manufacturing industries use large amounts of cost-effective artificial ingredients for improving their consumer characteristics and appearance (Leo et al. 2017; Lipskikh et al. 2018; Nambiar et al. 2018; Zhu et al. 2017). Monitoring the quality of food dyes in drinks has therefore become of paramount importance. Brilliant Blue (E133), Tartrazine (E102), Sunset Yellow (E110), and Amaranth (E123) (molecular structure and commercial name and details in Table 3.5) are synthetic dyes added to nonalcoholic beverages. The Brazilian Agency for Public Surveillance (ANVISA) has issued legal provision in 2002 to regulate the use of food dyes, since their high consumption could induce skin allergies and bronchial asthma. The maximum level allowed is 0.01 g/100 mL for Sunset Yellow, Tartrazine, and Brilliant Blue in nonalcoholic beverages, while the value for Amaranth is 0.005 g/100 mL.

Table 3.5 Food colorants and their structures and commercial names. European Community (EC) number, and food (F) and drug (D) number (Oplatowska-stachowiak and Elliott 2015)
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The analytical techniques to determine concentrations of food colorants include thin-layer chromatography (TLC), spectrophotometry in the visible region, high-performance liquid chromatography, and capillary electrophoresis. Reverse phase LC and ion-pair high-performance liquid chromatography (LC IP) are the most used in drinks. For instance, sulfonated azo dyes used in 330 commercial samples of orange and grape carbonated soft drinks were determined using ion-pair LC combined with photodiode array and thin-layer chromatography (TLC) (Andrade et al. 2014). A liquid chromatography diode-array detector (LC-DAD) was utilized to distinguish natural and synthetic colorants in dairy samples such as milk shakes, yogurts, and ice creams (Gallego and Valca 2003). Second-order derivative linear sweep voltammetry was used to detect tartrazine where glassy carbon electrodes were coated with a TiO2-reduced graphene oxide composite (He et al. 2018).

  • Detection of Brominated Flame Retardants

Brominated flame retardants (BFRs) such as polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecane (HBCD) are mainly used in plastics and electronic equipment to prevent combustion. Exposure to PBDEs may lead to endocrine disruption and neurodevelopmental toxicity in humans and hepatotoxicity, endocrine disruption, gene expression, and impaired reproductive physiology in animals. They have been banned in Europe, North America, and Australia (Mcgrath et al. 2017). Most BFRs are detected with gas chromatography/mass spectrometry (Geng et al. 2017).

3.4 Pharmaceutical and Personal Care Products (PPCPs)

Pharmaceutical (human and veterinary therapeutic drugs) and personal care products (PPCPs) comprise a well-known group of emerging contaminants (Boxall 2004; Boxall et al. 2012; Jennifer et al. 2017). Some of this pollution comes from human excretion of contraceptives and other medicines (e.g., acetaminophen, acetylsalicylic acid, ibuprofen, naproxen, and carbamazepine), which are eventually found in water (Boxall 2004). These drugs are absorbed, metabolized, and excreted to the sewage system, with some metabolized products being even more toxic than the non-metabolized drugs. Furthermore, many of the water treatment systems are not capable of removing the drugs and may transform the products into more toxic ones (Boxall 2004; Boxall et al. 2012; Jennifer et al. 2017; Kümmerer 2009; Vieno and Sillanpää 2014). The main sources of environmental pollution from pharmaceutical products are:

  • Effluents from manufacturing and hospital waste

  • Excretion by animals treated with antibiotics or other drugs

  • Human excretion of pharmaceutical and personal care products (Richardson and Bowron 1985; Rzymski et al. 2017)

The traditional methods to treat water include adsorption, solvent extraction, reduction, flocculation, coagulation, chemical or biological oxidation, ultrasound, and membrane filtration (Fan et al. 2018; Jing Wang et al. 2019a). The reported concentrations of pharmaceutical products are low, between ng L−1 (groundwater) and μg L−1 (wastewater), but many drugs can have cumulative effects and bring health problems, such as cancer (Boxall 2004; Christou et al. 2018).

3.4.1 Current Analysis of Pharmaceutical Products

The large number of recent reports of emerging pollutants in the environment may give the impression that this is a new problem. However, this is not new, and such pollution was simply ignored in the past owing to the lack of analytical methods with sufficient sensitivity to detect trace amounts (Buchberger 2011). Indeed, already in 1977 Hignite and Azarnoff found clofibric acid (used to lower plasma triglycerides and cholesterol concentrations in humans) and salicylic acid at low ppb levels in sewage treatment plant effluents (Hignite and Azarnoff 1977). Kolpin et al. (2002) detected 95 pharmaceutical contaminants such as hormones and other organic wastewater contaminants (OWCs) in water resources in the USA in 1999 and 2000 (Kolpin et al. 2002). Ternes reported the discovered drugs in the aquatic environment at concentrations up to approximately 1 μg l−1 in the UK (Ternes 1998). Pharmaceutical and chemotherapeutic drugs were found in the sewage, sewage effluents, river, and potable water (Richardson and Bowron 1985). Unfortunately, some drug residues could survive the various water treatment processes and remain at low concentrations <μg L−1 (Richardson and Bowron 1985; Ternes 1998).

In a review about ecotoxicity of hospital waste effluents, Orias and Perrodin (2013) listed a variety of toxic substances (Jean et al. 2012; Orias and Perrodin 2013), and human and veterinary pharmaceutical substances were found in surface water, groundwater, tap/drinking water, and soil (Beek et al. 2016). The anti-inflammatory drug diclofenac was found in higher-than-expected concentrations in 50 countries (aus der Beek et al. 2016). Also relevant are the effects of cocktails of drugs released in the environment after human consumption or/and incomplete removal at the waste treatment plant, which increase ecotoxicity (Vasquez et al. 2014) that is increasing over the years owing to their availability in town pharmacies (Parrella et al. 2014), (Besse et al. 2012). Ferrando-Climent and co-workers found tamoxifen and ciprofloxacin in the river upstream the sewage discharge (Ferrando-Climent et al. 2014), and Miller et al. (2018) discussed bioaccumulation of pharmaceuticals and its metabolite products in aquatic fauna, including anticancer drugs (Miller et al. 2018).

The increasing environmental contamination with pharmaceutical products requires alternative analytical techniques (Webb et al. 2003) to liquid (LC) and gas chromatography (GC) coupled to mass spectrometry (MS) (Fatta et al. 2007; Miller et al. 2018). Other methodologies to detect emerging pollutants are given in Table 3.6, including titrimetric measurements, UV-vis spectroscopy, near-infrared spectroscopy (NIRS), fluorometry, phosphorimetry, and nuclear and magnetic resonance spectroscopy (NMR) (Turci et al. 2003).

Table 3.6 Methods to detect pharmaceutical products in the environment
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3.4.2 Sensors and Biosensors to Detect Pharmaceutical and Personal Care Products (PPCPs)

Pharmaceutical products and derivatives are among the most demanding contaminants to detect in the environment. Highly frequent are the antibiotics introduced into the ecosystem via excretion from humans and animals (Khor et al. 2011). Antibiotics have been found in water resources, effluent from industries, sludge, manure, soil, plants, and organisms, the most common being b-lactams, sulfonamides, monobactams, carbapenems, aminoglycosides, glycopeptides, lincomycin, macrolides, polypeptides, polyenes, rifamycin, tetracyclines, chloramphenicol, quinolones, and fluoroquinolones (Gothwal and Shashidhar 2014). Negative effects from antibiotics include reduction of the growth, photosynthesis, content of photosynthetic pigments, chlorophylls, and carotenoids in plants. Moreover, fluoroquinolones inhibit DNA synthesis in eukaryotic cells, and b-lactams affect the plastid division in lower plants (Gothwal and Shashidhar 2014). In humans, fluoroquinolones may cause side effects such as nausea, dyspepsia, vomiting, dizziness, insomnia, and headache (Norrby 1991). The most serious problem, though, is the potential resistance development in human and animal pathogens (Norrby 1991; Larsson 2014).

Detection of pharmaceutical products has also been performed with electrochemical techniques that may offer low cost, robustness, easy miniaturization, low detection limits, small analyte volume, and real-time monitoring (Wang et al. 2008). Electroanalytical methods may also be combined with standard techniques to improve sensitivity (Brett 2001). They employ enzymes, antibodies, nucleic acids, or whole cells immobilized onto amperometric or potentiometric electrode transducers, without requiring sample pretreatment (Joseph Wang 2002). Biosensors with a chemically selective layer (Stradiotto et al. 2003) may encompass immunosensors, such as the one to detect the fluoroquinolone antibiotic enrofloxacin in milk and waters (Khor et al. 2011). An immunosensor prepared in a microfluidic device modified with antibodies was used to detect ibuprofen in water from various sources with a limit of detection at 0.25 pg mL−1 (Nagaraj et al. 2014), where the principle of detection was impedance spectroscopy. Aptasensors have been used to detect the hormone progesterone (P4) in a concentration range from 10 ng mL−1 to 60 ng mL−1 with a detection limit of 0.90 ng mL−1 (Jiménez et al. 2014). This impedimetric aptasensor was fabricated by immobilizing an aptamer on gold electrodes, as depicted in Fig. 3.10.

Fig. 3.10
figure 10

Design of the impedimetric aptasensor to detect progesterone (P4). (Reproduced with permission from (Jiménez et al. 2014). Copyright 2019, American Chemical Society)

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Illicit drugs have also been found in sewage and wastewater (Mccall et al. 2015). Huerta-fontela et al. determined cocaine and metabolites in wastewater at concentrations from 4 ng L−1 to 4.7 μg L−1 and from 9 ng L−1 to 7.5 μg L−1, respectively, while concentrations of amphetamine type stimulatory drugs ranged from 2 to 688 ng L−1 (Huerta-fontela et al. 2008). Drugs found in tap water included ecstasy, caffeine, paraxanthine, fentanyl, and methadone (Boleda et al. 2011). Fentanyl exemplifies the risk because it causes death owing to overdoses (Ciccarone 2017). Goodchild and co-workers (2019) developed a sensor to detect fentanyl made with screen-printed carbon electrodes (SPCE) modified with the ionic liquid (RTIL) 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide [C4C1PYrr][NTF2] using cycling square voltammetry (Goodchild et al. 2019). Data for this sensor, whose limit of detection was 5 μmol L−1, are illustrated in Fig. 3.11:

Fig. 3.11
figure 11

Fentanyl sensor based in screen-printed modified with the room temperature ionic liquid (RTIL). (Reproduced with permission from (Goodchild et al. 2019). Copyright 2019, American Chemical Society)

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Table 3.7 shows other examples of sensors and biosensors used for pharmaceutical detection in the environment. The presence of emerging pollutants in the environment, mainly in potable water, is already a worrying reality in many countries. Novel sensors and biosensors need to be developed to detect pollutants, pesticides, and pharmaceutical products in the environment.

Table 3.7 Electrochemical methods to detect pharmaceutical products in the environment
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As mentioned above, there is no doubt that electroanalytical techniques are an outstanding alternative to monitor contaminants due to low-cost and excellent detection limits.

3.5 Final Remarks

The problem of emergent contaminants has been ignored for an extended time because many environmental entities consider lower concentrations to be harmless. Consequently, these low concentrations lead to serious health problems in humans and animals, due to many products that are accumulated or can cause compounds to be more toxic when metabolized by the body.

Undoubtedly, the emergent contaminants are a significant problem that should be resolved by new regulations about the environmental quality that support green chemistry and the development of devices to monitor these product toxics in the environment – followed by more toxicity studies and rigorous control of products that will be brought to market.

As mentioned in this chapter, the electrochemical techniques have been postulated as a tool for detection of pollutants, pharmaceutical products, and pesticides with a low price, simplicity, and selectivity, rather low detection limits and multiple designs that allow miniaturization. These techniques also have the possibility of being coupled with conventional measurement methods improving their sensitivity.