Data was collected using the Web of Science (WOS) Core Collection database, with this review only considering the Science Citation Index Expanded (SCI-Expanded). Based on the findings of previous research by Yu et al. (2022), the keywords used to screen the available research on CH₄ in CWs included (“constructed wetland*” OR “treatment wetland*” OR “engineered wetland*” OR “artificial wetland*” OR “reed bed*” OR “man-made wetland*”) and (“methane sequestration*” OR “methane capture*” OR “methane emission*” OR “CH₄ capture*” OR “CH₄ sequestration*” OR “CH₄ emission*” OR “methane reduc*” OR “CH₄ reduc*”). The literature type was restricted to “article” and “review,” with publications in English from 1991 to December 2021 included (1991 was the earliest publication date available in the database). After the initial data search, 108 articles investigating CH₄ in CWs were selected. The analysis of these publications were performed using Microsoft Excel (2019), charts were generated using Origin (2019 learning version) and the S-curve was prepared using the logistic model in Loglet Lab 4. Analysis of keyword co-occurrence were performed using VOS viewer software (version 1.6.15). After exporting the 108 publications from the WOS platform in plain text form, the author keyword co-occurrence function of VOS viewer software was used to analyze keyword co-occurrence, with the thesaurus files then were merged (such as CH₄, methanes replaced with methane) and the minimum number of co-occurrences set to 3.

The publication trend for studies on CH₄ in CWs is shown in Figure 1. In the long term, the number of publications has continually increased with fluctuations, reflecting the growing concern within the scientific community about the effect of CH₄ emissions and the need to actively reduce CH₄ emissions in order to maintain global ecological security (Kasak et al., 2020). Prior to 2004, the publication number was relatively low and did not increase significantly from 2005 to 2013. However, a notable increase was observed after 2014, finally reaching 108 articles in 2021. Although the number of publications on this topic remains relatively low, work in this field is gaining importance constantly, as shown by the S-curve (R² = 0.984) in Figure 1, which indicates that research is in the growth stage and is expected to reach the inflection point in 2026 and remain stable until 2040. Therefore, publications in this field are not expected to reach saturation over the next 15 years, highlighting the high potential for innovation and development. In this sense, a comprehensive review of the current state of knowledge is essential to help stimulate and guide future development and research on CH₄ in CWs.

The results of keyword co-occurrence analysis are shown in Figure 2. The 6 most frequently co-occurring keywords were intercepted, showing that research on the effects of CH₄ on GWP, plants, and microorganisms was closely linked to studies on CH₄ emissions. Studies by Chen et al. (2020c) and Maucieri et al. (2019) attracted attention as they found that different plant species were able to exert varying effects on CH₄ emissions. Furthermore, it has been shown that microbial diversity and abundance are a critical factor affecting CH₄ fluxes, resulting in the need for further research and validation (Zhang et al., 2021a). MFC technology is a promising approach to the control of CH₄ emissions from CWs. For example, Liu et al. (2022) reported that microbial competition in a CW-MFC system can convert unstable carbon sources to CO₂ rather than CH₄, which can considerably reduce the contribution of CWs to global CH₄ emissions.

The transport of CH₄ occurs mainly via three processes: (1) direct CH₄ transport through molecular diffusion from the water and substrate column; (2) direct CH₄ transport through the ebullition flux process from substrate column; and (3) plant-mediated CH₄ transport from the substrate column via plant aerenchym (Figure 3; Thangarajan et al., 2013; Kasak et al., 2020). Ebullition plays a major role in direct CH₄ transport process, producing three-fold more CH₄ fluxes than molecular diffusion by Bonetti et al. (2021), while plant-mediated CH₄ transport is the dominant mode of CH₄ release among three processes (Liu et al., 2017), accounting for about 70% of the total-CH₄ emissions (Li et al., 2010). Moreover, the plant-mediated transport can also transport O₂ to plant organ (Silvey et al., 2019). Therefore, investigations into the plant-mediated transport process are required to further our understanding of the role of plants in CW CH₄ contributions. Plant-mediated CH₄ transport mechanisms can be classified as molecular diffusion or convective transport processes. Molecular diffusion rates depend primarily on the CH₄ gradient between plant roots and above-ground parts, along with the interior of the plant organ and the atmosphere, with the capacity for diffusion being susceptible to ambient temperatures (Joabsson et al., 1999). In contrast, gas movement by convective transport relies on the pressure difference between the inner-and outer-plant environment (Orr, 1992). Different plant species exhibit a diverse range of CH₄ transport processes, with convective transport processes typically more effective than molecular diffusion processes (Xu H. et al., 2021). In a recent study by Feng et al. (2022), a novel plant-girdling method was developed, removing the epidermis and subepidermal sclerenchyma to disrupt the O₂ transport pathway, suppressing O₂ release and increasing CH₄ emissions, verifying that wetland plants aerenchyma play a vital role in the transport of CH₄.

During CH₄ production and transport processes, CH₄ oxidation is a significant factor affecting CH₄ fluxes. CH₄ oxidation can occur via aerobic or anaerobic pathways. Aerobic oxidation of CH₄ (Table 2) mainly occurs at micro-interfaces where CH₄ and O₂ coexist, such as the substrate-air and water-air interfaces, the plant rhizosphere, and within plant tissues (Figure 3; Bonetti et al., 2021). Aerobic CH₄ oxidation is a chemical process with rapid reaction rates, depending on the concentration of O₂. Under anaerobic conditions, microbes use electron acceptors other than O₂ to oxidize CH₄, including sulfate (sulfate-reduction-dependent anaerobic methane oxidation, SAMO), NO2−/NO3− (nitrite-dependent anaerobic methane oxidation), metal oxides (e.g., Fe³⁺ and Mn⁴⁺ anaerobic methane oxidation, metal-AOM), and direct interspecies electron transfer (Wegener et al., 2015; Guerrero-Cruz et al., 2021). Among these, SAMO is driven by anaerobic methanotrophs and sulfate-reducing bacteria, while nitrite-dependent AMO is performed by Candidatus Methylomirabilis oxyfera and Candidatus Methanoperedens nitroreducens (Cui et al., 2015). Additionally, metal-AMO is thermodynamically easier than SAMO (occurring at a 2-to 10-folds faster rate than SAMO) because metal-AMO produces more energy, accelerating the AMO process (Zhang et al., 2022). Mn-AMO has been estimated to reduce total-CH₄ emissions by 66% (Liu et al., 2020) and Fe-AMO has the potential to decrease CH₄ emissions by 2-fold if it was to oxidize 10% of CH₄ worldwide (Egger et al., 2015). Among the different types of CWs, the use of VSSFCWs may be preferable for the reduction of CH₄ emissions as they have a suitable aerobic/anaerobic interface due to intermittent flooding, which is beneficial for both aerobic oxidation and AOM processes (Zhang et al., 2022).

Methyl coenzyme M reductase (mcrA) and particulate methane monooxygenase (pmoA), are key enzymes in CH₄ production and oxidation, resulting in their use as phylogenetic biomarkers for methanogens and methanotrophs (Chen et al., 2020b). Methanotrophs are the only known CH₄ biosinks, oxidizing another component of methanogenesis as carbon sources and producing CO₂, consuming at least 10% of atmospheric CH₄ in the process (O'Connor et al., 2010). CH₄ emissions have been found to positively correlate with the abundance of mcrA (Zhang et al., 2021d), and negatively correlate with the abundance of pmoA (Xu H. et al., 2021). However, no significant relationship was observed between pomA and CH₄ emissions, suggesting that other factors also mediate their function and activity (Zhang et al., 2021d). The mcrA/pmoA ratio can be used to explore the quantitative relationship between CH₄ production, oxidation and emissions, with a higher pmoA/mcrA ratio indicating higher CH₄ oxidation potential and lower CH₄ emissions (Zhao et al., 2022).

Temperature influences the production and oxidation of CH₄. The optimum temperature for methanogenesis is typically 35°C–40°C (Ralf, 2007), with low temperatures impairing the activity of methanogens and fermentative bacteria (Barbera et al., 2015) by reducing the rate of organic matter degradation and hence, substrate availability for CH₄ production (Zhu et al., 2007; Maucieri et al., 2019). CH₄ production has been found to positively correlate with temperature to some extent under sufficient substrate availability conditions (Bhattacharyya et al., 2013; Zhao et al., 2022). For example, methanogenesis rate at 12°C is significantly lower than that at 30°C (Maucieri et al., 2019). Temperature not only influence microbial activity, but also affect the succession of dominant methanogenic archaea. According to Lu Y. et al. (2015), methanogens were dominated by Methanosarcinaceae (utilizing acetate and H₂/CO₂ substrates), while as temperature lower, Methanosaetaceae dominate the methanogens (using acetate for CH₄ production). Methanotrophs is temperature non-sensitive species and their optimum temperature is 25°C. CH₄ can be oxidized either at low to-2°C or at high to 30°C (Zhang et al., 2021a).

As a result of microbial activity influenced by temperature, CWs in warm season can release higher CH₄ (3.4%–42%) than the cool or cold season (López et al., 2019; Maucieri et al., 2019; Shao et al., 2020). Johansson et al. (2004) found that CH₄ fluxes in SFCWs were strongly driven by season, fluctuating from-375 mg/m²/d to 1739 mg/m²/d for the spring to autumn period. Wang et al. (2019) concluded that average CH₄ emission in summer is 1.7 times higher than in winter, which was also proved by Zhao et al. (2014), D'Acunha and Johnson (2019), and Liu et al. (2019a). Therefore, in order to reduce the release of CH₄, it is recommended to control the temperature at an appropriate time of higher temperatures in summer.

Water table position determines the degree of anaerobiosis inside CWs. High water tables can exhibit slower rates of atmospheric O₂ diffusion, creating a larger anoxic zone which is beneficial to CH₄ production (McInerney and Helton, 2016). Henneberg et al. (2015) compared CH₄ emissions in CW mesocosms with 0 cm, −10 cm, and −20 cm water tables, showing that CH₄ emissions were much higher in the 0 cm water table treatment system than the −20 cm system both with and without vegetation. This phenomenon may partly be due to higher levels of CH₄ dissolution occurring at increased water depths (Zhou et al., 2020). When the water table is below the substrate surface, the CH₄ produced is oxidized as it travels through the water layer due to diffusion and ebullition, resulting in a reduction in CH₄ emissions (Bonetti et al., 2021). When the water table is high, CH₄ emissions are increased as most CH₄ enters plant root systems in the deeper anaerobic layer, before being transported to the atmosphere through the aerenchyma (Henneberg et al., 2015). A significant positive correlation has been reported between CH₄ emission rates and water table positions (Liu et al., 2009), with studies also documenting that net CH₄ fluxes are reduced in systems with a lower water table (Bridgham et al., 2013).

Redox potential (Eh) is an indicator of the internal O₂ level in CWs, which determines the activity of microbes and various enzymes, and is closely linked to CH₄ production and oxidation processes (Liu et al., 2009). Different microbial groups require varying Eh conditions, with aerobic microbes generally requiring an Eh between +300 and + 400 mV. Parthenogenic anaerobic microbes typically have a cut-off Eh of +100 mV, with aerobic respiration occurring at Eh levels above this point and anaerobic respiration occurring at lower Eh levels. Specialized anaerobic bacteria typically require an Eh of-200 to-250 mV. The conversion of organic matter to CH₄ occurs via the general anaerobic digestion pathway, while methanogens at the end of the respiratory chain require a strong reducing environment and very low Eh conditions (optimally-350 mV), with methanogenic processes initiated at Eh conditions < −200 mV (Chen et al., 2020b). The CH₄ production potential of a system increases with decreasing Eh (Liu et al., 2019b; Shao et al., 2020), and principal component analysis studies have also demonstrated that CH₄ fluxes are positively correlated with Eh conditions (Liu et al., 2019a).

CWs are classified as SFCWs, HSSFCWs and VSSFCWs due to their varying structures and characteristics, resulting in significant differences in CH₄ emission profiles (Zhang et al., 2021a). SFCW systems consist of wastewater flowing over a substrate layer (Maucieri et al., 2017), while VSSFCW systems are gradually infiltrated by wastewater being applied to the surface layer by intermittent feeding, with the wetland bed maintaining an aerobic state with strong reoxygenation capabilities (Liu et al., 2019a). In contrast, wastewater is applied to HSSFCWs through the substrate layer by horizontal percolation in a mixed environment with aerobic, anoxic, and anaerobic degradation pathways, where the bed is submerged for a prolonged period of time causing anoxia (Zhou et al., 2020).

CH₄ emissions from SSFCWs have been found to be significantly lower than from SFCWs (Table 3). In a survey by VanderZaag et al. (2010), SFCWs were found to emit 2-to 3-fold more CH₄ as a percentage of carbon removal than SSFCWs. The conditions associated with the highest CH₄ fluxes from SFCWs and the lowest fluxes from VSSFCWs were studied by Liu et al. (2009). The reason for the observed variation was that SFCWs exhibit very low reoxygenation rates, that are insufficient for the complete oxidation of organic matter and readily create anaerobic conditions that promote CH₄ release (Søvik et al., 2006), with this effect usually observed in wetland systems that do not have routine harvesting of above-ground plant biomass, providing a continual supply of organic carbon (Hernandez et al., 2018). However, SSFCWs increase the contact time in the aerobic headspace and rhizosphere, which hinders the movement of gases (Zhu et al., 2007), resulting in more CH₄ oxidation occurring in SSFCWs than in SFCWs and lower CH₄ fluxes. Liu et al. (2009) also discovered that Eh conditions < −100 mV were primarily found in SFCWs, while no Eh was identified in VSSFCWs, supporting the association between Eh conditions and the high CH₄ fluxes observed in SFCWs.

CH₄ fluxes from HSSFCWs were found to be higher than those from VSSFCWs (Table 3). For example, Bateganya et al. (2015) found that HSSFCWs emit more CH₄ than VSSFCWs, irrespective of plant growth. Zhou et al. (2020) designed a hybrid CW system that generated about 4.8-fold lower CH₄ fluxes in the VSSF bed section than the HSSF bed section. The reason for this difference may be attributed to VSSFCWs having efficient O₂ transport, while HSSFCWs contain anoxic-anaerobic conditions (Mander et al., 2008), exhibiting negative Eh levels (−100 mV to-500 mV) and low dissolved oxygen (DO) concentrations (< 2 mg/L; López et al., 2015). In contrast, the VSSF system was found to be higher than the HSSF system in a study by Zhang et al. (2021a), due to the potential for CH₄ emissions to be affected by competition between various methanogens. A life cycle assessment also concluded that the environmental impact of CH₄ emissions from VSSFCWs was half or less than those from HSSFCWs (Fuchs et al., 2011).

CWs are increasingly being designed with composite structures that are more valid and robust for the treatment of a wide range of wastewater types (Liu et al., 2019a), However, these composite CW systems often have a negative effect on CH₄ fluxes (Zhou et al., 2020). For example, a monitoring study found that CH₄ emissions from VSSF-HSSF-SF CW was higher than from both VSSFCW and SFCW (Liu et al., 2009). Liu et al. (2019a,b) and Liu et al. (2018) designed integrated VSSFCWs that consist of alternating multifunctional layers of aerobic-anoxic-anaerobic-anoxic-aerobic conditions, leading to the accumulation of methanogens and increased CH₄ emissions (Zhang et al., 2021a). Waste resource conservation and reducing environmental influence have become priorities in sustainable engineering design. Therefore, the small occupation area of VSSFCWs, along with their high treatment efficiency and relatively low level of CH₄ fluxes, make VSSFCW systems more extensively used, and a more CH₄ flux can be reduced via an enhanced O₂ transfer approach (Liu et al., 2019b).

The relationships between CH₄ emissions and plant occurrence and diversity in CWs remain unknown (Han et al., 2019), as plants are able to both produce CH₄ independently, and mediate or influence CH₄ emission pathways. For example, organic matter and root exudates (such as sugars and amino acids) synthesized by plants via photosynthesis, can provide electron donors (Chen et al., 2020c; Liu et al., 2022), while root exudates also release degradable carbon which increases the number of methanogens and methanotrophs (Zhang et al., 2018b). Furthermore, plant root-secreted O₂ can provide electron acceptors (Kasak et al., 2020), with the intensity of O₂ secretion varying depending on the plant species, biomass, temperature, O₂ concentration, and photointensity conditions (Feng et al., 2022). In typical VSSFCWs, O₂ released by plant roots can provide approximately 0.43–1.12% of the biochemical oxygen demand (Zhang et al., 2014). The rhizosphere is a crucial zone for the production and oxidation of CH₄, with plant species composition, diversity, and planting density affecting the release of CH₄ (Chen et al., 2020c).

It has been observed that vegetation-covered CWs produce less CH₄ than those without vegetative cover (Zhu et al., 2007; Bateganya et al., 2015). However, contradictory results have been reported by Silvey et al. (2019), with this variation potentially due to plant species variation. Chen et al. (2020c) reported that planting Cyperus alternifolius resulted in CWs having lower CH₄ fluxes than unvegetated CWs, while planting Phragmites australis and Canna indica had the opposite effect, highlighting the varying effect of different species on CH₄ fluxes. Firstly, some plants have been found to suppress CH₄ fluxes (Table 4). A monitoring study by Bateganya et al. (2015) found that planting Cyperus papyrus was more effective for the suppression of CH₄ fluxes regardless of the CW types, due to the extensive belowground rhizome network facilitating O₂ transfer (Xu et al., 2019; Zhang et al., 2021a). Cyperus alternifolius is a ciliate with large root surface areas and root lengths of approximately 20 cm, providing them with the capacity to reach the bottom of CWs and release high amounts of root O₂, leading to a more extensive aerobic environment (Chen et al., 2020c). The presence of Oenanthe javanicade has been shown to reduce the carbon concentration in wastewater, minimizing the production of CH₄ (Zhao et al., 2016; Han et al., 2017). In contrast, some plant species enhance CH₄ emissions (Table 4; Du et al., 2018; Maucieri et al., 2019). Juncus effusus has a significant capacity to transport CH₄ (Henneberg et al., 2015), and Rumex japonicus possesses a high root biomass capable of secreting low molecular weight substances (Zhao et al., 2016), accelerating microbial activity and increasing CH₄ emissions (Du et al., 2018). Overall, the contribution of plants to CH ₄ emissions remains unclear. For example, Phragmites australis has an extensive rhizome system that typically penetrates substrate depths of 0.6–1.0 m, and has been reported to effectively reduce CH₄ fluxes (Xu et al., 2019), while other studies have reported that Phragmites australis possesses highly developed aerenchyma that allow more efficient gas transfer and increase CH₄ emissions (Sheng et al., 2015; Chen et al., 2020c). Moreover, some studies have proposed that certain plant species has no overall impact on CW CH₄ emissions (Han et al., 2019; Maucieri et al., 2019). Instead, plant characteristics such as root porosity and belowground biomass can regulate microbial community competition, O₂ transfer efficiency to the root system, and carbon source inputs, leading to varying levels of CH₄ productivity in different species (Maucieri et al., 2017; Zhang et al., 2018b). The average CH₄ fluxes of submerged plants are generally lower than those of emergent plants (Niu et al., 2015; Zhang et al., 2018a). O₂ and carbon inputs from emergent plants can significantly affect the methanogenic community structure and methanogenic pathways, while submerged plants are primarily subject to regulation by DO and nitrogen levels (Zhang et al., 2018a). Furthermore, in contrast to the comparatively less-rigid forb species, some structurally rigid graminoids exhibit larger aerenchyma, which increases their ability to transport O₂ between the roots. Mesocosms containing Asclepias incaranta were found to have average CH₄ fluxes that were 8-fold higher than those of mesocosms containing Alisma triviale (Silvey et al., 2019). Therefore, the selection of suitable plant species composition is essential to minimize CH₄ emissions from CWs.

Plant species diversity has been widely studied in recent years, and its contribution to CH₄ emissions has increasingly being investigated. Several studies have observed a positive correlation between CH₄ emissions and plant species diversity (Du et al., 2018), as high species diversity increases carbon source available and promotes CH₄ emissions (Zhang et al., 2012). Some studies have also found that plant species diversity have no significant influence on CH₄ emissions (Zhao et al., 2016; Han et al., 2019), as in high ammonium environments, denitrification has a higher capacity to produce thermodynamic processes than methanogenesis (Chen et al., 2020c). In addition, denitrifying bacteria have a competitive organic substrate advantage, limiting CH₄ formation (Zhang et al., 2018a), in which high ammonium loading and plant biomass can perform CH₄ offsetting functions, leaving CH₄ emissions unchanged overall (Han et al., 2019). Moreover, plant density has been reported to have no influence on CH₄ emissions (Hernandez et al., 2018). In conclusion, species characteristics remain a critical driver although more research is required in this field.

The contribution of plant harvesting to CH₄ emissions is also significant (Feng et al., 2022). Non-harvested wetland plants can promote methanotrophic CH₄ consumption by transporting O₂ to the roots and substrate through aerenchyma (Zhu et al., 2007). However, the dying plant biomass provides an abundant source of bioenergy and promotes methanogenesis, with the potential to generate 10–40% of annual atmospheric CH₄ emissions worldwide (Juutinen et al., 2003; Keppler et al., 2006), highlighting the need for plant harvesting to be carefully managed. The time and manner of harvesting of aboveground macrophytes also affects CH₄ emissions from CWs (Kasak et al., 2020). Ensuring that harvesting occurs at the end of the growing season (i.e., before nutrient transfer to belowground plant structures) can significantly reduce CH₄ emissions. However, biomass harvesting during peak periods of plant growth and soil microbial activity has been shown to significantly enhance CH₄ emissions (Barbera et al., 2015), due to the rapid release of CH₄ accumulated in the vascular system of plant stalks (Kasak et al., 2020). Therefore, effective planning to optimize harvesting time and method can effectively reduce CH₄ emissions from managed wetlands, and thus enhance their multiple ecological benefits.

Biochar is an organic carbon-enriched product that is considered a promising alternative substrate (Zhuang et al., 2022). Ji et al. (2021) showed that biochar-based CWs contained a higher pmoA/mcrA ratio than none-biochar CWs, with the addition of biochar having an inhibitory effect on CH₄ fluxes, possibly due to biochar promoting the secretion of O₂ from plant roots, increasing CH₄ oxidation (Ji et al., 2020). However, Chen et al. (2020a) and Guo et al. (2020) proposed contrasting conclusions, finding that CH₄ fluxes were consistently higher in biochar-added CWs than CWs without added biochar. This may be due to biochar enhancing direct interspecies electron transfer between methanogens and Geobacteraceae, while also providing organic matter to methanogens, resulting in the stimulation of CH₄ emissions (Liu et al., 2012). Overall, the influences of biochar on CH₄ emissions remains unclear (Table 5), with the reported differences primarily caused by variations in the raw biochar materials, operating conditions, and the properties of the microbial community within the system (Chen et al., 2020a), highlighting the need for further research to determine the role of biochar in regulating CH₄ emissions (Zhuang et al., 2022). Walnut shell is also loaded with high concentrations of organic matter. Xu G. et al. (2021) showed that CH₄ emissions from walnut shell substrate were 14.8-fold higher than from the control substrate, due to the release of large amounts of degradable organic carbon from walnut shell, resulting in high CH₄ fluxes.

Highly crystalline iron oxides and manganese oxides are electron-exchange substrates that are abundant and readily available, making them highly suitable for use as CW substrate materials (Zhang et al., 2021b; Yu et al., 2022). Cheng et al. (2021a) reported that CWs using iron oxide substrates emitted less CH₄, finding that iron oxide increased CH₄ emissions by promoting electron transfer between Geobacter and methanogens, while also directly inhibiting the activity of methanogens and some enzymes involved in CO₂ reduction, and promoting the AOM process under the influence of dissimilated metal-reducing bacteria, ultimately resulting in a reduction in CH₄ emissions overall (Cheng et al., 2021b). Mn ore substrates have been found to reduce CH₄ emissions from CWs (Liu et al., 2020). In addition, Cheng et al. (2021b) observed that both Mn ore and iron ore substrates inhibited CH₄ emissions, with Mn ore reported to be more effective due to the fact that Mn ore promotes AOM processes mainly by competing for organic substrates and providing electron acceptors, almost completely inhibiting CH₄ production (Xu G. et al., 2021). However, the use of iron oxide as a substrate has more complex implications, such as different forms and valences of iron affecting CH₄ production (Cheng et al., 2021a).

Fe-C is widely used as a substrate in wastewater treatment, utilizing chemistry-coupled biological processes for the removal of pollutants (Dong et al., 2020). Zeolite, a common silicate mineral, is considered to be a high-performance gas adsorption material, due to its relatively well-developed pore network and skeletal configuration (Wang Y. et al., 2020), with well characterized CH₄ adsorption, storage, and oxidation capabilities (Wang H. et al., 2020; Zhou et al., 2020). Zhao et al. (2022) monitored CH₄ emissions from laboratory-scale CWs containing different substrates, showing that systems utilizing Fe-C and zeolite as substrates all exhibited lower average CH₄ fluxes than the control groups (Table 5), as Fe-C can compete with methanogens for substrate in the presence of iron-reducing bacteria, inhibiting the production of CH₄. In addition, Fe³⁺ has a high Eh as an electron acceptor (Bond and Lovley, 2002), and the larger surface area of activated carbon facilitates biofilm generation, promoting CH₄ oxidation. Zeolite incorporation into the substrate has been found to significantly reduce CH₄ emissions from CWs. Zhou et al. (2020) discovered that CWs containing zeolite substrate exhibited reduced CH₄ fluxes by about 2-fold compared to those of gravel substrate CWs, due to the porous structure of zeolite improving local atmospheric DO concentrations and reducing methanogen activity. The results of these studies are further supported by the observation that Fe-C and zeolite substrates contained a reduced abundance of the functional gene mcrA and a significantly increased abundance of pmoA (Zhao et al., 2022). Activated alumina is also a powerful adsorption substrate, as shown in a study by Xu G. et al. (2021) in which activated alumina significantly reduced CH₄ emissions from CWs due to its strong adsorption capacity, leading to reduction in organic matter content and inhibiting methanogenic microbial activity (Alvarez and Cervantes, 2012). In addition, sand, ceramsite and gravel have also been utilized as adsorption fillers (Table 5; Wang Y. et al., 2020), but they have been gradually replaced due to poor CH₄ adsorption capacities (Ji et al., 2020; Cheng et al., 2021a; Zhao et al., 2022). With a survey of CWs finding that mcrA and pmoA were not detectable in all gravel substrates (Chen et al., 2020c), which was attributed to the fact that methanogens and methanotrophs do not easily attach to gravel so it is gradually replaced.

Open or closed circuit systems are one of the essential factors affecting CH₄ fluxes from CW-MFCs. Liu et al. (2022) found that the CH₄ emissions from non-planted CW-MFCs, were about 0.21 ± 0.01 mg/m²/h higher in open-circuit systems than in closed-circuit systems, while in the planted open-circuit system the CH₄ emissions were 0.46 ± 0.02 mg/m²/h higher than in the closed-circuit planted system. A study by Xu et al. (2021b) yielded CH₄ fluxes of 6.37–7.28 mg/m²/h and 7.43–8.36 mg/m²/h for closed and open circuit CW-MFC systems, respectively. Zhang et al. (2021e) noted that running a MFC in CWs can suppress a third of all CH₄ emissions. These studies show that CW-MFCs can effectively reduce CH₄ emissions from CWs, with similar findings also reported by Zhang K. et al. (2020) and Zhang et al. (2021c), with the main contributory factor being the bioanode. In anaerobic environments, methanogens are dominant in CWs due to the absence of current transmission, resulting in an increase in the production of CH₄ (Zhang et al., 2021d). In contrast, because organic matter is more readily available for electrochemically active bacteria (EAB) in closed-circuit CW-MFC systems, electrical stimulation of EAB growth results in a current that inhibits methanogens (Liu et al., 2022). In addition, electrons from the anode may compete with methanogens as the anode layer of the CW-MFC has a higher Eh, allowing electron-producing bacteria to capture electrons more easily than methanogens, leading to a reduction in CH₄ emissions (Zhang et al., 2021e).

CH₄ emissions are significantly affected by plants in CW-MFC systems. Recently, an increasing number of studies have demonstrated that plant root location has an influential effect on CH₄ emissions in CW-MFC systems (Liu et al., 2017). When the plant rhizosphere is in the cathode layer, electron acceptors provided by root-secreted O₂ favor cathode reactions and power generation (Zhang et al., 2021e). Since CW-MFC anodes are typically in an anoxic state rather than an anaerobic state, the small amount of O₂ secreted by plant roots has little effect on the O₂ levels in the anode environment (Zhang et al., 2021d). Therefore, plant rhizospheres in the anodic zone can provide photosynthetic organic matter as an alternative energy source, increasing CH₄ emissions. Zhang et al. (2021e) reported that CW-MFC systems with rhizospheres in the cathode zone emit less total-CH₄ (29.21 mg/m²/d) than those with rhizospheres at the anode (33.01 mg/m²/d). Zhang et al. (2021d) observed that growing Typha orientalis and Cyperus alternifolius in the cathode zone of a reactor, resulted in lower CH₄ emissions than when grown at the anode. Zhang et al. (2021c) reported a similar conclusion, with methanogens becoming more active as the organic matter content of the rhizosphere increases, resulting in an increase in CH₄ emissions. Additionally, the O₂ provided by plant roots has been found to have less of an impact on lowering CH₄ emissions than the organic matter in the root system (Lu L. et al., 2015).

The presence of plants and the selected plant species also influence CH₄ emissions in CW-MFC systems. Liu et al. (2022) reported that CH₄ emissions increased by 0.48 ± 0.02 mg/m²/h in closed-circuit CW systems with plants, compared to the non-planted group. A similar conclusion was reached by Xu et al. (2021b), with a 21.79% reduction in average CH₄ emissions from non-planted reactors, as compared to those with plants. Zhang et al. (2021d) reported lower CH₄ emissions in systems with anode grown Typha orientalis (3.9 mg/m²/h), than with anode grown Cyperus alternifolius (4.5 mg/m²/h). A study comparing the effects of three plant species, Typha orientalis, Thalia dealbata, and Cyperus alternifolius, found that CH₄ emissions from the CW-MFC were highest in the Typha orientalis system, and lowest in the Cyperus alternifolius system (Zhang K. et al., 2020). These results emphasize the importance of further research to determine the effect of different plant species on CH₄ emissions from CW-MFC systems.

The important role that plants play in CH₄ emissions from CW-MFC systems is becoming increasingly apparent, with both the plant species and root location influencing CH₄ emissions, although root location appears to have a more pronounced effect (Zhang et al., 2021d). Therefore, focusing on plant selection to ensure that plants with inhibiting methanogenesis or poor CH₄ transport are utilized, with their roots located in the cathodic zone, has been shown to be more advantageous for the sustainable development of wastewater treatment systems, in terms of reactor power generation and CH₄ reduction.

The long-term application of external resistance in CW-MFC systems affects the microbial community structure and biochemical metabolism in the anode biofilm (Zhang et al., 2021c). Liu et al. (2022) observed that an external resistance of 1,000 Ω leads to an increase in CH₄ emissions by 0.67 ± 0.01 mg/m²/h compared to a 100 Ω resistance. Wang et al. (2019) found that CH₄ emissions tended to increase with the addition of external resistances >500 Ω. This effect occurs due to variation in microbial metabolic activities, electron transfer rates and substrate utilization kinetics, under varying external resistance conditions (Liu et al., 2022). Higher external resistance loads slow down the flow of electrons to and from EAB, which encourages methanogens to consume more substrate and increases CH₄ emissions (Liu et al., 2017). However, it has also been found that insufficiently low external resistances lead to rapid electron flow rates, which are not conducive to the sustainable utilization of CW-MFC systems, and eventually leads to a decline in power generation (Nikhil et al., 2018). Therefore, a suitable relatively low external resistance should be applied, ensuring that CW-MFC systems generate maximum levels of power, while releasing minimum CH₄ (Liu et al., 2022).

Substrate. CH₄ emissions in CW-MFC systems are also driven by substrate type. A Mn CW-MFC system was shown to generate lower CH₄ emissions (53.44–66.64 mg/m²/h) than a clinopyrite CW-MFC system (62.69–88.02 mg/m²/h; Zhang et al., 2021b). Furthermore, Xu et al. (2021b) observed a 25.42% reduction in average CH₄ emissions from Mn-based reactors compared to graphite granule-based reactors. This may be due to the occurrence of Mn-driven Mn-AOM lowering CH₄ emissions, while dissimilatory metal reduction processes encourage competition between EABs and methanogens, as well as increasing the growth of EABs on Mn ore anodes, further inhibiting the growth of methanogens (Li et al., 2019; Zhang et al., 2021b, 2022). Therefore, different substrate materials have varying electron acceptor functions and significantly affect CH₄ emissions, with Mn exhibiting high prospects as a substrate for CH₄ emissions reduction.

HRT. Due to the relatively high organic load in CW-MFCs, there is a positive correlation between CH₄ emissions and HRT. Lower HRTs result in a higher load and increased CH₄ emissions (Zhang et al., 2021e). It was observed that when the HRT in plant systems increased, CH₄ fluxes tended to reduce, with higher organic matter contents stimulating the activity of inactive microorganisms, consuming DO, and promoting the growth of methanogens (Wang et al., 2019). HRT is an extremely vital operating parameter for conventional wetlands (Zhang K. et al., 2020). A longer HRT can prolong the contact time between microorganisms and wastewater (Zhang et al., 2021d), ensuring the effective removal of organic matter as well as the suppression of CH₄ emissions. Finally, it has been found that CW-MFC systems have a stronger CH₄ reduction effect when operated in continuous flow mode than in batch mode (Wang et al., 2019).

Shortage of DO in CWs due to prolonged saturation and rapid microbial metabolism is a major limitation to the removal of organic matter from conventional CWs (Wang et al., 2022). Intermittent aeration and tidal flow are considered to be the most effective oxygenation strategies to directly influence CH₄ emissions, allowing the manipulation of DO conditions in CWs (Table 5; Ji et al., 2020), providing additional O₂ for the inhibition of CH₄ biochemical processes and the acceleration of CH₄ oxidation, reducing CH₄ fluxes (Ji et al., 2021). D'Acunha and Johnson (2019) found that CH₄ fluxes could be reduced by 60.7% using intermittent microaeration under optimal aeration conditions. Furthermore, Zhao et al. (2022) observed increased CH₄ fluxes in aerated sections of CWs compared to non-aerated sections, which was attributed to CH₄ production primarily occurring in non-aerated sections, while CH₄ emissions were enhanced by agitation and blowing in aerated sections, with the change in emissions consistent with the aeration rate and dissolved CH₄ concentration. Ji et al. (2020) showed that only a slight decrease in CH₄ fluxes occurred under tidal flow oxygenation conditions, although Ji et al. (2021) concluded that the total CH₄ fluxes were slightly higher due to the loss of large amounts of CH₄ from the empty substrate after drainage. However, the use of intermittent aeration increases operational costs and energy input requirements, making it more suitable for use in CWs in relatively concentrated communities or limited land areas. In contrast, the tidal flow process involves no significant additional costs or maintenance expenses.

The available carbon sources in CWs can be supplied internally or externally. Internal carbon sources mainly include plant roots or microbial secretions, plant deadfall, organic matter decomposition, and substrates (Liu et al., 2019a), while external carbon sources include biodegradable carbon, natural plant material, and soluble carbon from natural organic matter (Liu et al., 2019b). To balance the nutritional ratio in CWs, additional carbon sources must be provided in some CWs, directly affecting CH₄ emissions (Chen et al., 2020b). C/N ratios represent the relative amount of carbon and nitrogen available in the wastewater, with different C/N ratios promoting or inhibiting microbial activity (Guo et al., 2020). Yan et al. (2012) found that CH₄ fluxes in CWs with C/N ratios of 2.5, 5, and 10 were 1.36 ± 0.09 mg/m²/h, 2.02 ± 0.07 mg/m²/h, and 2.34 ± 0.15 mg/m²/h, respectively, showing that CH₄ fluxes were lowest with low C/N ratio conditions. Corbella and Puigagut (2015) also reported a positive correlation between CH₄ emissions and influent C/N conditions, which may be attributed to increases in C/N causing rapid O₂ consumption, resulting in a lower Eh and higher CH₄ production (Guo et al., 2020). However, Chen et al. (2020b) analyzed CWs with influent C/N ratios of 0, 5, 10, 15, and 20, showing that CH₄ emissions did not differ significantly, reaching a minimum value of −42.49 mg/m²/h at a C/N ratio of 10. Zhao et al. (2014) combined SSFCWs with an earthworm eco-filter and found that CH₄ emissions increased in accordance with the influent C/N ratio regardless of the sequence of treatment, as the earthworm activity greatly increased the permeability of the SSFCW. Therefore, lower C/N ratio conditions are more favorable for CH₄ emissions reduction. Liu et al. (2019a) observed that the addition of urea as an external carbon source at concentrations of 0, 12.1, 30, 45, 61, and 80 mmol/L, resulted in a trend of increasing and then decreasing CH₄ emissions, achieving the lowest emission level with a urea concentration of 80 mmol/L. Similar results were obtained by Liu et al. (2019b) using ethanol as an external carbon source, with results showing that Eh values after the addition of ethanol (except for the highest ethanol concentration of 32 mmol/L) were higher than the control groups, resulting in more CH₄ emissions. Excessive carbon source concentration increases the water purification load. Therefore, when external carbon sources are provided, the dosage should be adjusted to ensure optimal water purification performance with CH₄ emission control.

With increasing levels of water scarcity, desalination, or the direct utilization of seawater in coastal areas is becoming increasingly common, generating large quantities of saline wastewater. CWs are increasingly being used for the treatment of saline wastewater in response to different regional treatment strategies (Shao et al., 2020). The salinity of the influent affects not only the growth of wetland plants but also the structure, abundance and activity of microbial communities (Sheng et al., 2015; Xiao et al., 2016). According to Shao et al. (2020), CH₄ emissions were higher at salinities of 0 and 0.5%, continually decreasing with increasing salinity, with a substantial decrease occurring at 1.0%. Sheng et al. (2015) also observed that CH₄ emissions decreased significantly with increasing salinity due to inhibition of methanogen growth and activity (Xiao et al., 2016). In addition, salinity has been repeatedly shown to inhibit CH₄ emissions in tidal wetlands, due to competition between sulfate and methanogens for substrates in tidal waters (Poffenbarger et al., 2011; Marton et al., 2012). In summary, the effect of salinity on CH₄ fluxes in CWs is pronounced, with emissions promoted by low salinity and inhibited by high salinity conditions.