1. Introduction
1.1. The importance of greenhouse gas (GHG) emissions and its impact on the environment and health
The challenge of climate change in the Earth’s environment due to an increase of GHG can significantly affect the environment, agriculture, food security, and human health. Natural disasters, loss of biodiversity, droughts, changes in rainfall patterns, ocean acidification, and escalating wildfires are other consequences of global warming and climate change caused by the increase in GHG. In other words, climate change is a threat to many aspects of the Earth’s ecosystem, including human health, agriculture, water resources, forests, and wildlife, which can make all of them vulnerable and at risk. Carbon dioxide (CO
2), methane (CH
4), ozone (O
3), nitrous oxide (N
2O), sulphur hexafluoride (SF
6), hydrofluorocarbons (HFCs), nitrogen trifluoride (NF
3), perfluorocarbons (PFCs), and water vapor [
1], [
2], which are known as GHGs, can be traced from various sources, including energy systems, industry, buildings, transportation, and agriculture [
3]. Lamb et al. [
3] presented global GHG emission trends of different sectors from 1990 to 2018. They reported that the largest share of GHG emissions in 2018 was attributed to the energy systems (34%), industry (24.5%), agriculture (21.2%), transport (14.3%), and building operations (6%) (
Fig. 1). Although global GHG emissions are mainly composed of CO
2 (approximately 74%), other contributions are from CH
4, N
2O, and fluorinated gases, accounting for 17%, 5%, and 3% [
4]. Human activities related to food systems, including agricultural practices and land use, have greatly raised GHG levels in the Earth’s environment [
5]. According to the report of the Intergovernmental Panel on Climate Change (IPCC), approximately 57% to 60% of total global N
2O emissions and around 43% to 50% of total global CH
4 emissions are attributed to agricultural practices. The emission of various GHGs in the agricultural systems greatly depends on the type of agricultural practices and management. In particular, CH
4 is primarily emitted through enteric fermentation in ruminant livestock, such as cows, rice cultivation, and manure management [
6]. Vaghar Seyedin et al. [
7] made a comprehensive review of 159 studies and found that low livestock efficiency, poor-quality feed, lack of knowledge, and insufficient investment were the key factors contributing to methane gas emissions in low-income or developing countries. The N
2O emissions are mainly related to the management of agricultural soils, including the use of synthetic and organic fertilizers and the burning of crop residues [
8]. In this regard, He et al. [
9] made a global meta-analysis of 137 studies to assess the impact of organic fertilizers on GHG emissions compared to chemical fertilizers. Their findings revealed that N
2O emissions were significantly reduced by substituting organic fertilizers for chemical ones, while increasing global warming potential due to increased CH
4 and CO
2 emissions. Galic et al. [
10] presented a review to evaluate the impact of agricultural management through fertilizers on CO
2, CH
4, and N
2O emissions. They reported that the use of organic modifiers has significant potential for protecting the environment and reducing GHG emissions. The CO
2 emissions from the agriculture sector can be released from various sources, including changes in land use, such as deforestation for agriculture, diesel fuel combustion in machinery, the burning of biomass for energy, and the use of synthetic fertilizers [
11].
1.2. Importance of GHG sensors for improving food security in precision agriculture
The IPCC’s fifth assessment report confirms that the overall GHG emissions continue to increase despite the implementation of various climate change mitigation policies. Learning about the challenge of climate change caused by GHG, the scientific community is diligently working to measure and quantify this phenomenon. The sensors have been designed to detect and measure the concentration of GHG in the atmosphere. These sensors generate valuable data by monitoring and providing real-time and accurate measurements of GHG emissions for assessing potential risks and challenges in food production systems [
12]. This data-driven approach can be efficient in optimizing agricultural practices, enhancing productivity, and mitigating environmental impacts in the framework of food security and sustainable precision agriculture (
Fig. 2) [
13].
Numerous research groups globally have dedicated efforts to develop diverse sensor technologies for the detection of environmentally hazardous gases [
14], [
15], [
16]. The technologies of GHG sensors are updated effectively and continuously through trial and error for more accurate measurements. Various manufacturing technologies have been developed for the detection of GHGs, such as catalytic gas sensors [
17], optical gas sensors [
18], metal oxide semiconductor-based sensors [
17], [
19], electrochemical gas sensors [
20], and nuclear sensors [
16]. The performance of various sensors is determined by measurable parameters, including recovery and response time, detection limit, selectivity, operating temperature, response ratio, and sensitivity.
1.3. Unveiling the objectives
In recent decades, a large amount of research has focused on developing GHG sensors by creating new sensing materials, advancing manufacturing technologies, and enhancing sensor performance [
16], [
19], [
21]. In the present study, the technical performance of various sensing materials and mechanisms in the GHG sensors is investigated based on quantitatively different parameters, including sensitivity, response ratio, response time, and recovery time. This study can provide a roadmap for more efficient selection of sensors in controlling GHG emissions. Therefore, the strategies and objectives of the present study can be listed as follows: ① providing an analytical comparison of the performance of GHG sensors in terms of sensing materials and mechanisms, ② identifying the ambiguities, limitations, and gaps in existing sensor technologies, and ③ providing constructive suggestions based on the current research status and identified challenges to improve the accuracy and efficiency of GHG sensors.
2. Methods
The GHG sensors are classified by the sensing mechanism [
14] and sensing material [
17], which are discussed separately in the following subsections.
2.1. Classification of GHG sensors by sensing mechanism
2.1.1. Resistance measurement (RM) sensor
Resistance-based sensors are devices that measure the concentration of GHG by monitoring changes in electrical resistance [
14]. The schematic mechanism of a resistance-based sensor is illustrated in
Fig. 3(a). This sensor responds to GHG through a sensing element, which is often composed of or coated with various active materials such as metal oxide semiconductors or carbon nanomaterials. These elements are connected to a circuit, which measures the resistance of the sensing material [
22]. This resistance changes when the sensing material interacts with the target gas, due to the adsorption of gas molecules onto the element’s surface. Consequently, the type and quantity of gas could lead to either an increase or decrease of the electrical resistance of the sensing material [
23]. Finally, the electrical resistance of sensing material can be interpreted as the concentration of the GHG by comparing the resistance value to a calibration curve or mathematical equation of the target gas.
2.1.2. Field effect transistor (FET) sensor
The schematic mechanism of the FET-based sensor is depicted in
Fig. 3(b). The basic structure of a typical FET-based gas sensor consists of four parts, including source and drain electrodes, a sensing layer or conductive channel, a gate electrode, and an insulator. In these sensors, the conductive channel is in contact with target gas on the gate electrode. Materials such as graphene, carbon nanotubes, or metal oxides are commonly used in the conductive channel [
24], [
25]. When the sensor encounters target gas, gas molecules are adsorbed onto the surface of the channel material. This adsorption process leads to a charge transfer between gas molecules and the channel. The change in the channel conductivity is measured as a change in current between the source and drain electrodes [
26]. By analyzing these changes in the FET’s current and voltage, the concentration of GHG in the environment can be quantified using calibration curves or mathematical models.
2.1.3. Surface acoustic wave (SAW)-based micromechanical sensor
The SAW-based sensor uses surface acoustic wave technology to propagate acoustic waves along the surface of a solid material, such as quartz. The schematic mechanism of the SAW-based sensor is illustrated in
Fig. 3(c). In these sensors, a piezoelectric substrate, such as quartz or lithium niobate, generates a surface acoustic wave that propagates along its surface. A gas-sensitive material is deposited on the SAW propagation path. This layer can be metal oxide, polymer, or other material that interacts with the target gas. When the sensor encounters the target gas, gas molecules are adsorbed onto the sensitive layer. The adsorbed gas molecules increase the mass of the sensitive layer, altering the SAW velocity. This change in SAW velocity is directly related to the mass of the adsorbed gas, which can be quantified through Fourier analysis, wavelet analysis, or statistical modeling [
27], [
28].
2.1.4. Electrochemical sensor
Electrochemical-based sensors are devices that measure the concentration of GHG in the atmosphere based on the principle of redox reactions.
Fig. 4(a) shows the schematic mechanism of the electrochemical sensor. An electrochemical sensor typically consists of working (sensing) electrode, counter electrode, and reference electrode, which are separated by the electrolyte to have the electrochemical reaction with the target gas. The absorbed gas molecules onto the surface of the working electrode generate an electric current at the sensing electrode through an electrochemical reaction. This electric current is directly proportional to the concentration of the target gas. Then, the sensor converts this electric current into a readable output, such as a voltage or a digital signal, which can be used to determine the gas concentration [
13], [
20]. It is important to note that the FET-based sensors are not classified as electrochemical sensors. The FET-based sensors utilize the electrical field generated by the charges on the gate electrode to detect changes in the concentration of the target gas. In contrast, electrochemical sensors rely on chemical reactions to produce an electrical signal through the oxidation or reduction of analytes in a solution.
Catalytic gas sensors operate based on the principle of heat production resulting from the catalytic combustion of specific gases [
29].
Fig. 4(b) illustrates the schematic mechanism of catalytic sensors. The sensor’s core component is a catalytic material, which is highly effective in oxidizing combustible gases. The vast majority of metal oxides including tin dioxide (SnO
2) and tungsten trioxide (WO
3), as well as noble metals such as platinum (Pt) and palladium (Pd) have catalytic behaviors. The heat produced raises the temperature of the catalytic element. The temperature change affects the electrical resistance of a heating element located near the catalytic material. This change in resistance is measured and converted into an electrical signal that corresponds to the gas concentration [
30].
2.1.5. Gas chromatography (GC) technique
The GC technique operates on the principle of separating different gases based on their distinct chemical characteristics [
16], [
31], [
32].
Fig. 5(a) shows the schematic mechanism of the GC technique. The GC technique comprises the sample injector, separation column, detector, and data acquisition system. In the sample injector component, the GHG is introduced into the system. Then, the gas mixture is transported through a separation column, which contains a stationary phase that selectively interacts with different compounds. As the gases cross the column, they are separated based on their affinity for the stationary phase. Each gas is identified by a detector, such as a thermal conductivity detector or a flame ionization detector. The detector produces a signal proportional to the concentration of each gas, which is recorded by the data acquisition system. This data can be used to quantify the amount of specific GHG present in the sample.
2.1.6. Optical sensor
The optical gas sensor uses optical technology to detect and quantify the concentration of GHG in the atmosphere. In other words, these sensors can measure the amount of light absorption by the GHG in different wavelengths. The schematic mechanism of the optical gas sensor is illustrated in
Fig. 5(b). Typically, the optical gas sensor consists of a light source, such as an light emitting diode (LED) or laser, and a detector [
33]. The light passes through a sample of gases, and the detector measures the amount of light absorbed by the gases present. These sensors can determine the concentration of GHG using distinct absorption spectra. Different types of optical gas sensors, including laser absorption spectroscopy (LAS) [
34], nondispersive infrared (NDIR) [
35], and photoacoustic spectroscopy (PAS) [
36], use optical principles to detect and measure the concentration of GHG. Generally, the main differences between these optical gas sensors are their detection principles and signal extraction methods. The LAS sensor uses a laser beam to illuminate gas samples, while the GHG absorbs light with specific wavelengths based on their molecular composition. The NDIR sensors use an infrared light source and a detector that measures the amount of infrared light absorbed by the gases in the sample. The PAS technique uses laser-induced acoustic waves to detect and analyze gases. These waves are captured by a microphone or other acoustic detection methods and can be interpreted as the concentration of GHG.
2.2. Detection of GHG emissions based on sensing materials in different sensors
In the last few years, a range of sensing materials for various sensors have been developed for the detection of GHG [
37]. Some of these materials are costly and involve complex synthesis processes, which can hinder research and large-scale application [
38]. Metal oxides (e.g., SnO
2, zinc oxide (ZnO), WO
3, cerium oxide (CeO
2), indium oxide (In
2O
3), and titanium dioxide (TiO
2)) and metal catalysts (e.g., Pt, Pd, and rhodium (Rh)) are known as the most important sensing materials in various sensors for detecting GHG (
Fig. 6). Different types of nanomaterials, including nanoparticles and nanowires composed of sensing materials such as metal oxides, carbon nanotubes, and graphene, have demonstrated significant potential for gas sensing applications. Conductive polymers, such as polyaniline (PANI), polythiophene (PT), and polypyrrole (PPy), have become highly promising materials for the development of gas sensors. These conductive polymeric materials are often used in gas sensors because of their electrical and chemical properties, which include high sensitivity, selectivity, cost effectiveness, ease of fabrication, and mechanical resilience [
39], [
40]. In contrast to many traditional gas sensors that require high operating temperatures, sensors based on conductive polymers can work effectively at room temperature, which reduces energy consumption [
41]. The great conductivity of these materials makes rapid and sensitive detection of gas molecules possible. Additionally, PANI and PPy are very suitable for long-term monitoring of GHG emissions due to their high stability and durability. In other words, these materials can endure harsh environmental conditions and continuous exposure to gases without degradation, ensuring reliable and consistent performance over an extended period. It is important to note that the selection of sensing material depends on the target gas for detection, because different sensing materials have different degrees of sensitivity and selectivity for different gases.
2.3. Criteria for evaluating the performance of GHG sensors
Sensor performance refers to the accuracy, sensitivity, and reliability of the sensor in detecting and measuring GHG. Properties of sensing material, including response time, recovery time, sensitivity, and response ratio, can be used to investigate and evaluate the performance of GHG sensors [
19], [
23]. The sensitivity refers to the ability of the sensor to detect and measure the change in response per unit change in gas concentration [
42]. A sensor with high sensitivity can accurately detect even GHG with low concentrations as the lowest limit. Furthermore, the sensitivity of a sensor can also affect its ability to detect and distinguish different GHG, as well as its response time and reliability. The response ratio can be defined as (|
R2 −
R1|)/
R1, where
R1 and
R2 are the sensor responses at the lower and higher gas concentrations, respectively [
43]. A high response rate indicates that the sensor detects changes in gas concentrations quickly. Response time refers to the duration it takes for the sensor to accurately and meaningfully measure after detecting target gas. A shorter response time is crucial for real-time monitoring applications, where immediate and accurate readings are required. On the other hand, the recovery time refers to the duration it takes for the sensor to return to its initial state after detecting and measuring the GHG. This is particularly important to ensure that subsequent readings are not affected by residual gases or contaminants. A high-performance GHG sensor with shorter recovery and response time can provide accurate and near-real-time measurements to effectively control emissions. Taking these points into account, in the present study, the performance of GHG sensors is evaluated based on response time, recovery time, sensitivity, and response ratio on sensing materials and mechanisms in 95 different studies in the last two decades, including 42 studies related to CH
4 gas, 14 studies related to N
2O gas, and 39 studies for CO
2 gas. Consequently, studies in which these parameters were not reported were excluded from this review. The literature review revealed that many researchers have concentrated on the reactivity of various sensing materials with the target gas, while paying less attention to the mechanisms of the sensors. In contrast to the extensive research dedicated to enhancing the sensing material properties of CH
4- and CO
2-based sensors, relatively few studies have focused on the improvement of N
2O-based sensors in this regard.
3. Results and discussion
3.1. Performance evaluation of different sensing materials in CH4-based sensors
A comparison of the performance of different sensing materials based on response time, recovery time, sensitivity, and response ratio in CH
4-based sensors is summarized in
Table 1 [
42], [
43], [
44], [
45], [
46], [
47], [
48], [
49], [
50], [
51], [
52], [
53], [
54], [
55], [
56], [
57], [
58], [
59], [
60], [
61], [
62], [
63], [
64], [
65], [
66], [
67], [
68], [
69], [
70], [
71], [
72], [
73], [
74], [
75], [
76], [
77], [
78], [
79], [
80], [
81], [
82], [
83]. According to the studies by Abruzzi et al. [
43] and Yao et al. [
44] presented in
Table 1, Pd-doped SnO
2 nanoparticles utilizing the resistance change technique had the best performance in terms of response time (3 s), recovery time (5 s), sensitivity (
S = 83%), and response ratio (
R = 17.6) compared to other sensing materials in CH
4-based sensors. The good performance of Pd-doped SnO
2 nanoparticles as a sensing material in CH
4-based sensors can be attributed to the effective combination of several reasons, including sensitivity, specific surface area (SSA) or surface chemistry, and catalytic activity and stability. Pd-doped SnO
2 nanoparticles can enhance the SSA and oxygen species while altering the morphology of the sensing material to facilitate CH
4 oxidation. This increased SSA provides more active sites for gas adsorption and promotes the chemisorption of CH
4 molecules, which can improve the sensitivity and response ratio of the CH
4 gas sensor. In other words, incorporating Pd nanoparticles into SnO
2 increases the sensitivity in the absorption and oxidation reactions between CH
4 and SnO
2 due to the high affinity of Pd for CH
4 gas molecules. This can lead to improved performance of sensing material in response and detection of CH
4 gas. Yao et al. [
44] indicated that the nanoporous structure of Pd-SnO
2 and chemical sensitization of Pd could be considered as an effective strategy for achieving exceptional gas sensing performance in CH
4-based sensors.
It should be noted that high SSA is a necessary but not sufficient condition for the performance of sensing materials. The SnO
2 nanorods-nanoporous graphene in the study of Kooti et al. [
45] had a higher SSA than Pd-SnO
2 in the study of Abruzzi et al. [
43] (162.09 m
2∙g
−1 vs 50 m
2∙g
−1), but lower sensitivity was observed in the detection of CH
4 gas by SnO
2 nanorods-nanoporous graphene (24.9% vs 83%). Therefore, it appears that a variety of other factors such as the catalytic effect can significantly affect the performance of the sensing materials. Due to their high catalytic activity, Pd nanoparticles enhance the reaction kinetics of CH
4 oxidation on the surface of the sensing material, facilitating the conversion of CH
4 to CO
2 and H
2O. This catalytic activity, acting as a form of chemical sensitization, decreases the operating temperature required for CH
4 gas detection, making it a highly effective sensing material for CH
4-based sensors [
43]. Similar findings were also reported by Nasresfahani et al. [
46]. Pd-doped SnO
2 nanoparticles prevents degradation of sensing material and increases the stability, durability, reproducibility, and reliability of the sensor against environmental factors and multiple sensing cycles over an extended period.
Sensing materials of Pd nanoparticles-doped ZnO nanorods [
47], SnO
2 nanorods-graphene nanoporous hybrid [
45], and Pd-decorated ZnO/reduced graphene oxide hybrid [
46] had the longest sensing response time of 420, 369, and 300 s, respectively (
Table 1). It seems that there is still a long way to go to design CH
4 gas sensors based on ternary hybrids. A crucial aspect to consider in ternary hybrid-based sensors is the synergistic effect of the sensing materials, ensuring that the combined effect of all three components is greater and more effective than that of each individual component. Pd-doped SnO
2 nanoporous sensor had a shorter response and recovery time than Pd-doped ZnO nanorods sensor (
Table 1). This could be attributed to the optimized structure and composition of the SnO
2 nanoporous material, which increases the interaction between CH
4 and the surface of the sensing material. Gold (Au) nanoparticles-decorated vanadium dioxide (VO
2) nanosheets sensor had a high sensitivity of 45% at room temperature for 100 ppm of CH
4 compared to other sensing materials, which could be attributed to the formation of a heterojunction at the interface of the VO
2 nanosheets and Au nanoparticles [
48]. Additionally, the Au nanoparticles-decorated VO
2 nanosheets sensor had higher sensitivity than VO
2 nanorods (45% vs 15%), which could be caused by the catalytic effect of Au.
The research findings from various literature studies on CH
4-based sensors (
Table 1) revealed that certain nanostructure morphologies, such as nanoporous, nanorods, and nanosheets, had higher sensitivity and response ratio compared to those of conventional materials with larger SSA. Additionally, Pd nanoparticles, which have a more effective catalytic effect in sensing materials, improve the response ratio and performance of the CH
4-based sensors.
3.2. Performance evaluation of different sensing materials in N2O-based sensors
In N
2O-based sensors,
Table 2 [
49], [
84], [
85], [
89], [
90], [
91], [
92], [
93], [
94], [
95], [
96], [
97], [
98], [
99] pointed to the fact that WO
3 nanowires with a diameter ranging from 0.5 to 15 nm had the best performance in terms of response time (10 s), recovery time (60 s), and sensitivity (
S = 2690% to 100 ppm) compared to other sensing materials using the resistance change and electrochemical techniques, as noted in the studies by Deb et al. [
84] and Rout et al. [
85]. Additionally, Rout et al. [
85] reported a high response ratio (
R = 40 to 60) for In
2O
3 nanowires with a diameter of 20 nm in the detection of N
2O gas (
Table 2).
The good performance of WO
3 and In
2O
3 nanowires makes them ideal sensing materials for N
2O gas sensors, attributed to several factors, including high surface-to-volume ratio, morphology and stability against humidity and temperature. Single crystalline nanowires and nanowire networks (mats) serve as efficient devices with an exceptionally high surface-to-volume ratio, showing great potential for detecting N
2O gas at low concentrations [
86]. Nanowires have a high surface-to-volume ratio, which provides numerous active surface sites for N
2O gas molecules to interact with the sensing material. This increases the sensitivity and response ratio of the sensor to N
2O gas. In this regard, various studies have demonstrated that WO
3 nanowires have high sensitivity to nitrogen oxide (NO
x) gases, including N
2O, and can accurately detect and measure N
2O gas at very low concentrations [
85], [
86], [
87], [
88].
The morphology and one-dimensional structure of nanowires can increase gas diffusion and absorption. These characteristics can improve gas absorption and sensor response time by providing a pathway for gas molecules to easily access active surface sites. In other words, the presence of oxygen vacancies and/or other defects in the structure of WO
3 and In
2O
3 nanowires can create and facilitate surface states or trap states for gas absorption, thereby increasing the conductivity changes induced by gas molecules. In relation to the structure of the nanowires, Deb et al. [
84] reported that highly networked nanowires had higher sensitivity in detecting N
2O gas when used as sensing materials compared to randomly oriented nanoparticle layers. On the other hand, the WO
3 nanowires have rapid response and recovery, facilitating real-time monitoring of N
2O levels in the atmosphere. The WO
3 nanowires have high stability and durability against increasing thermal conditions and relative humidity, allowing them to withstand the elevated operating temperatures typically necessary for gas sensing applications. Such stability ensures the longevity of the sensors over extended periods under harsh conditions, such as high temperatures and varying humidity levels, without significant performance degradation.
The research findings of several literature studies on N
2O-based sensors (
Table 2) revealed that nanowires and networked nanowires had higher sensitivity and response ratios compared to conventional materials with larger SSA. Besides, WO
3 and In
2O
3 nanowires, known for their high sensitivity and response ratios respectively, can be used in CH
4-based sensors, while the WO
3 nanowires provide a better response time.
3.3. Performance evaluation of different sensing materials in CO2-based sensors
In CO
2-based sensors, the results in
Table 3 [
82], [
100], [
101], [
102], [
103], [
104], [
105], [
106], [
107], [
108], [
109], [
110], [
111], [
112], [
113], [
114], [
115], [
116], [
117], [
118], [
119], [
120], [
121], [
122], [
123], [
124], [
125], [
126], [
127], [
128], [
129], [
130], [
131], [
132], [
133], [
134], [
135], [
136], [
137] showed that barium titanate (BaTiO
3)-CuO-Ag with nanocomposite structures and 400 nm nanofilms had the best performance based on response time (3 s), recovery time (5 s), and sensitivity (
S = 27%) compared to other sensing materials utilizing the resistance change technique, as reported by Joshi et al. [
100] and Herrán et al. [
101]. The good performance of BaTiO
3-CuO-Ag nanostructures as a sensing material in CO
2 gas sensors can be attributed to several key factors, including a big surface area, catalytic properties, synergistic effect, and a big dielectric constant. The nanocomposite structure of BaTiO
3-CuO-Ag provides a large surface area for gas interactions, facilitating effective adsorption and desorption of CO
2 molecules. This enhancement in surface interactions can lead to increased sensitivity to CO
2 gas and improved sensor performance. By incorporating CuO and Ag nanoparticles into the BaTiO
3 matrix, the electrical conductivity of the nanocomposite is increased. This improvement facilitates quicker and more accurate detection of resistance changes induced by CO
2 gas. Joshi et al. [
100] attributed the good performance and structural stability of this sensing material to the electrical and chemical contributions of Ag and CuO, which could create alternating nanointerfaces with BaTiO
3 spheres.
Both CuO and Ag nanoparticles have high catalytic properties, which can promote and facilitate the oxidation and reduction reactions involved in the sensing process. Ag increases the sensitivity of the sensing material by catalyzing the carbonation reaction, affecting the acceptor density and reducing the potential barrier between CuO and BaTiO
3 [
100]. On the other hand, the combination of BaTiO
3, CuO, and Ag nanoparticles in the nanocomposite leads to a synergistic effect, whereby the individual properties of each component improve the performance of the sensing material. To support this claim, BaTiO
3 is highly sensitive to changes in the surrounding environment due to its big dielectric constant and ferroelectric properties. Therefore, by incorporating CuO and Ag nanoparticles into the nanocomposite, its sensing capabilities are further improved. Consequently, the catalytic effect, along with the combined effect, improves the sensitivity and stability of the sensor, promoting efficient detection of CO
2 gas. In addition to the BaTiO
3-CuO-Ag nanocomposite, Hsu et al. [
102] reported a high response ratio (
R = 10.1) for Au-La
2O
3-doped SnO
2 nanofibers compared to other sensing materials in CO
2-based sensors (
Table 3). The presence of Au nanoparticles in the nanofibers facilitates efficient electron transfer between gas molecules and the sensing material. Such an electron transfer process increases the electrical conductivity of the nanofibers, which can improve the response ratio of the sensor to CO
2 gas. Hsu et al. [
102] expressed that Au particles effectively improved the sensor response by 50%.
The research findings of several literature studies for CO
2-based sensors (
Table 3) revealed that nanostructures, including nanocomposites, nanofilms, and nanofibers, had higher sensitivity and response ratio compared to those of conventional materials such as powders of barium carbonate (BaCO
3)-doped cobalt oxide (Co
3O
4) [
103], La
2O
3/SnO
2 stacked layers [
104], and thick films of lanthanum oxychloride (LaOCl)-doped SnO
2 [
105]. In contrast to CH
4-based sensors, the performance of CO
2 gas sensors utilizing a designed ternary hybrid structure of sensing materials was better than that of the double hybrid structure, such as Sn-doped CdO [
106] and LaOCl-doped SnO
2 [
105]. Such improvement may be attributed to a combination of synergistic and catalytic effects. Both CuO and SnO
2 can serve as components of this ternary hybrid structure of sensing materials.
The data in
Table 1,
Table 2,
Table 3 indicate that metal oxides and metal catalysts are the most commonly used sensing materials in resistance-based sensors for detecting GHG.
Fig. 7 illustrates the bubble cloud diagram of metal oxides and metal catalysts used in the studies reviewed for GHG detection. Based on the data in
Table 1 and
Fig. 7, SnO
2 metal oxide and Pd metal catalyst were the most frequently used materials for detecting CH
4 emissions, appearing in 43% and 17% of the reviewed studies, respectively. Additionally, SnO
2 was used in 36% and 26% of the reviewed studies, respectively, for the detection of N
2O and CO
2 emissions (
Table 2,
Table 3 and
Fig. 7). In this regard, Love et al. [
38] also reported the common use of tin oxide in their study. Following SnO
2, the metal oxides WO
3 and CuO were used in 21% and 20% of the studies reviewed, respectively, for detecting N
2O and CO
2 emissions in resistance-based sensors, as illustrated in
Fig. 7. The data in
Fig. 7 indicates that sensing technologies using nano-structured metal oxides and metal catalysts provide a more reliable and accurate measurement of GHG emissions compared to carbon nanotubes and polymers. In other words, metal oxides are used as high-potential materials for detecting a wide variety of GHGs due to their high sensitivity, fast response, very low cost, and user friendliness [
138], [
139]. The strong performance of metal oxides can be attributed to their structural and morphological features. Metal oxides have a wide band gap, enabling a complete range of unique physical and chemical properties. Furthermore, many metal oxides and their compounds have catalytic abilities that can be highly effective in interacting with target gases [
19].
3.4. Performance evaluation of different sensing mechanisms in CH4-, N2O-, and CO2-based sensors and their limitations
Different users, including agricultural and environmental experts and farmers, can select the most suitable and effective sensing mechanisms for generating accurate data on GHG emissions by understanding the advantages and disadvantages of different sensing techniques. However, by generating accurate data, a more reliable understanding of GHG emissions and their impacts on the environment and crop production can be provided. Additionally, by applying the appropriate sensing mechanisms, we can ensure optimal and efficient resource use while minimizing the maintenance and operational costs of the sensor, which is one of the primary goals in precision agriculture.
The advantages and disadvantages of the sensing mechanisms are outlined in
Table 4 [
14], [
23], [
24], [
25], [
27], [
43], [
62], [
140], [
141], [
142], [
143], [
144], [
145], [
146], [
147]. The data of
Table 4 is derived from the findings of the studies presented in
Table 1,
Table 2,
Table 3. When analyzing GHG sensors, factors such as sensitivity or response ratio at low concentrations, real-time monitoring, cost effectiveness, and portability were considered as key components contributing to the advantages of the sensing mechanisms. By using effective sensor mechanisms, GHG emissions can be continuously monitored and detected with high speed and accuracy. This information can be used to develop a plan that safeguards animals or agricultural products from adverse effects. Conversely, the factors of initial cost, sensitivity to environmental influences, complexity and difficulty in interpreting data were considered significant disadvantages of the sensing mechanisms. Nevertheless, acknowledging these elements as disadvantages may require a considerable investment in the purchase, installation, calibration, and maintenance of sensors to obtain reliable readings of GHG.
However, after a closer look at the literature review on the performance of different sensing mechanisms, some limitations are revealed. Two known limiting variables in the RM-based mechanism are limited sensitivity and environmental effects such as temperature and humidity, which can reduce the accuracy of the GHG sensors [
45]. When there is noise or interference, through the RM-based mechanisms, minor changes in resistance with low accuracy can be detected. The FET- and SAW-based mechanisms have a restricted sensitivity range and may not be suitable for measuring very low or very high values of GHG emissions [
140], [
141]. Working electrodes in sensors utilizing electrochemical mechanisms, as well as catalytic sensors, are often designed to respond to a specific target gas. Their effectiveness and selectivity may be compromised when other substances or environments with multiple potential interferents are detected [
29]. This limitation can affect the accuracy of measurements in complex matrices. Additionally, electrochemical and catalytic sensors require regular maintenance and calibration over time due to chemical reactions taking place on the electrode’s surface [
55], [
65], [
95]. The gas chromatography technique is expensive and time-consuming, requiring skilled personnel for sample analysis and a complex process setup [
32]. In optical sensors, signal degradation can occur due to interference, absorption, and scattering, particularly in complex media or turbid samples. These optical sensors should be regularly calibrated because of variations in the intensity of the light source and the length of the optical path [
18], [
58]. Besides, the application of optical sensors is limited due to their high cost. According to recent research, resistance- and electrochemical-based sensors provide significant advantages for CO
2 and CH
4 detection due to their high sensitivity, simplicity, ease of use, and low cost in device fabrication [
43], [
66], [
76], [
85], [
102]. However, several other sensing mechanisms, such as optical, chromatography, FET and SAW techniques, have not yet achieved a level of development that is high enough for N
2O detection.
3.5. Investigating the effect of environmental temperature and humidity on the performance of GHG sensors and offering strategies for different conditions
The GHG sensors can be used in various environmental conditions, from humid tropical climates to dry arid regions. In this context, changes in humidity and temperature can affect the sensors’ readings, leading to inaccurate and unreliable measurements of GHG concentrations [
45], [
148], [
149], [
150]. By investigating and comprehending the environmental impacts on sensor performance, researchers can be assisted to ensure reliability and stability when measuring GHG concentrations over time. Furthermore, by understanding the performance range of sensors based on humidity and temperature, appropriate sensors can be selected for specific environments and it can help to determine the frequency of maintenance and calibration.
Generally, the reactivity and electrical conductivity of various sensing materials, particularly metal oxide semiconductors, rise with an increase of operating temperature, which can affect their interaction with target gases and the sensor output signal, respectively [
43]. In most cases, a rise in temperature leads to greater sensitivity and shorter response and recovery time for the sensor. Through such an increase in sensitivity in sensors, GHG in low concentrations can be detected. In contrast to temperature, high humidity may increase the response and recovery time of sensors, because water molecules compete with GHG molecules for adsorption on the surface of the sensor material [
14]. This competition reduces the sensitivity of the sensor to target gases. Liu et al. [
151] investigated the impact of temperature on CO
2 concentration measurements by the infrared sensor. Their findings revealed that gas concentration measurement values (level of detection) decreased concomitantly with the decline of temperature and humidity.
Researchers are trying to build and develop sensors with a flexible operating temperature and high humidity resistance to increase performance with minimal fluctuations [
150]. Yuan et al. [
150] noted that Ag
2Te nanowires were humidity-resistant, which could provide a new pathway for developing room-temperature humidity-resistant gas sensors. The results of the reviewed studies on CH
4 gas indicated that the Pd-SnO
2 with an operating temperature ranging from 25 (room temperature) [
46] to 400 °C [
50] had strong performance in terms of sensitivity, response ratio, response time, and recovery time. Regarding N
2O gas, sensing materials such as SnO
2-graphene nanomaterial [
81], In
2O
3 nanowires [
85], and WO
3 nanowires [
85] had good performance in terms of response and recovery time at 25, 150, and 250 °C, respectively. BaTiO
3-CuO and BaTiO
3-CuO-Ag thin films, as studied by Herrán et al. [
112] and Herrán et al. [
101], respectively, had flexibility in operating temperatures ranging from 25 to 250 °C for CO
2 gas detection.
Long-term exposure to high temperatures and humidity can accelerate the degradation of sensing materials, reducing their lifespan and performance [
152].
Fig. 8 highlights practical strategies in the effective use of GHG sensors for different environmental conditions. As illustrated in
Fig. 8, regular calibration of sensors [
153], the implementation of temperature and humidity compensation techniques [
154], correct placement of sensors, provision of thermal insulation [
155], effective sealing to prevent interference from humidity and other external factors [
156], and consistently monitoring on sensors [
157] are crucial strategies for optimizing the performance of GHG sensors under different environmental conditions.
4. Conclusions
By understanding the challenges in the performance of GHG sensors, constructive suggestions and solutions can be effectively provided to raise the detection level of GHG emissions. In this regard, by recognizing current challenges and providing constructive suggestions, farm management practices and strategies can be improved. The primary challenges in various studies include detecting low concentrations of GHG in complex environments, distinguishing target gases from interfering substances, maintaining consistent performance over time and under different conditions, developing sensors, and minimizing energy requirements for practical applications. Therefore, potential solutions and constructive suggestions for increasing the accuracy and efficiency of GHG sensors can be sought through several key parts, including advanced materials and nanostructures, sensor design and optimization, calibration and validation, and cost reduction. In connection with advanced materials and nanostructures, the selection of materials featuring nanostructures with a big SSA and strong affinity for GHG, such as Pd-doped SnO2 nanoparticles, In2O3 nanowires, WO3 nanowires, and Au-La2O3-doped SnO2 nanofibers, can be highly effective in the detection of GHG. From the perspective of sensor design, the development of hybrid sensors based on technology (such as optical, electrochemical, and thermal) and materials (double and triple hybrids) can significantly affect sensor optimization. Among other constructive suggestions, by using accurate and verifiable reference standards for GHG concentrations and doing comparative studies among different types of sensors, we can ensure the control process and data quality. Additionally, using low-power components and circuits to minimize energy consumption and costs, along with using wireless sensor networks for ongoing remote monitoring and data transmission, is essential. Finally, the accuracy and efficiency of GHG sensors in the agricultural sector can be improved by applying these constructive suggestions, leading to improved monitoring of gas emissions, reduced environmental impacts, and more sustainable agricultural practices.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (32271980) and the Key Pioneer Research Project of Zhejiang Province (2022C02014).
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