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Article

Migration and Transformation of Greenhouse Gases in Constructed Wetlands: A Bibliometric Analysis and Trend Forecast

by
Ruiyao Qi
1,
Jiahao Dong
1,
Yan Kang
2,
Huijun Xie
3,
Haiming Wu
1,
Zhen Hu
1 and
Zizhang Guo
1,*
1
Shandong Key Laboratory of Water Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
2
College of Environment and Safety Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
3
Environment Research Institute, Shandong University, Qingdao 266237, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(3), 412; https://doi.org/10.3390/w17030412
Submission received: 29 November 2024 / Revised: 14 January 2025 / Accepted: 21 January 2025 / Published: 2 February 2025
(This article belongs to the Special Issue Constructed Wetlands as a Sustainable Technology for Wastewater Treatment: Current Trends and Future Potential)
Browse Figures
Figure 1
<p>The generation and release of N<sub>2</sub>O in CWs.</p> "> Figure 2
<p>The generation and release of CO<sub>2</sub> and CH<sub>4</sub> in CWs.</p> "> Figure 3
<p>The publication number and citation frequency of research on GHG emissions in CWs per year.</p> "> Figure 4
<p>A representation of national and regional cooperation networks.</p> "> Figure 5
<p>Author cooperation network in the field of GHG emissions in CWs.</p> "> Figure 6
<p>The co-occurrence network analysis of keywords on GHG emissions from CWs.</p> "> Figure 7
<p>A visualization of the keyword cluster analysis on GHG emissions in CWs.</p> "> Figure 8
<p>Timeline view of the keyword clusters on GHG emissions in CWs.</p> ">
Versions Notes

Abstract

:
Constructed wetlands (CWs), serving as an advanced wastewater treatment system, play a vital role in both the emission and sequestration of diverse GHGs. However, there are few papers reviewing and analyzing developments in the field. In this study, bibliometrics were used as an essential tool for identifying and establishing connections among key elements within a discipline, as well as for analyzing the research status and developmental trends of the research fields. CiteSpace 6.3.1 was utilized to conduct an analysis of the references from the Web of Science Core Collection pertaining to GHG emissions from CWs over the period from 1993 to 2023. This study showed the following conclusions. (1) Organic nitrogen conversion produces N2O, which is eventually transformed into N2 and released from CWs. Anammox represents an attractive route for nitrogen removal. (2) The CO2 is the final product of the oxidation of organic matter in the influent of CWs and can be fixed by plant photosynthesis. Anaerobic fermentation and CO2 reduction produce CH4. The two are emitted through aerenchyma transport, bubble diffusion, and other forms. (3) In the past 30 years, the number of publications and citation frequency shows an increasing trend. China and the United States published more papers. The top ten authors contributed to 20.607% of the total 1019, and the cooperation between different author groups needs to be strengthened. (4) The emerging burst keywords following 2020 are “microbial fuel cell” and “microbial community”, which highlights the current hotspots in research related to GHG emissions from CWs. (5) There is still a lack of long-term and applied discussion on the role of CWs in promoting GHG emission reduction. The relevant reaction conditions and mechanisms need to be explored and the possible research directions can be genetic regulation and information technology.

1. Introduction

Greenhouse gases (GHGs) are constituents of the atmosphere and play a vital role in the greenhouse effect, contributing to the warming of the planet. Climate change and global warming, driven by GHG emissions, have consistently been significant subjects of international discourse [1,2,3,4,5]. Since the onset of the industrial revolution, human activities have profoundly disrupted the equilibrium of these gases, resulting in intensified greenhouse effects and global climate change. GHGs mainly include nitrous oxide (N2O), carbon dioxide (CO2), methane (CH4), and various fluorinated gases. The Greenhouse Gas Bulletin (2022) published by the World Meteorological Organization (WMO) indicated that the global average surface molar fraction of CO2, CH4 and N2O hit a record high in 2021. This climatic instability threatens agricultural productivity, water resources, and biodiversity, leading to food and water insecurity for millions [6]. Therefore, the mitigation of GHG emissions is essential [7]. This necessitates a comprehensive understanding of the dynamics of GHGs to develop effective strategies for mitigating climate change.
Constructed wetlands (CWs) are engineering systems extensively used in wastewater treatment. They treat wastewater by using the synergistic effect of wetland plants, substrates and microorganisms [8]. CWs serve as a vital link between the initial treatment of municipal wastewater and its final discharge into natural environments. Due to the great economic advantages and effectiveness in wastewater purification, CWs are extensively utilized in countries such as China [9], the United States [10], Canada [11], Spain [11], Germany [8], and others. With the widespread application of CWs, the environmental impacts of their GHG emissions must be seriously considered. Nevertheless, the role of CWs as either a carbon source or a carbon sink in wastewater treatment processes remains undetermined [12]. According to different estimates, wetlands cover only 5–8% of the global land area but account for 20–30% (2500 Pg) of the world’s carbon pool [13]. The microbial transformations involved in wetlands produce several GHGs, such as N2O, CO2, and CH4, which are crucial to climate change [14,15,16]. Studies show that the world’s wetlands serve as significant carbon sinks, with an estimated capacity of approximately 830 Tg/year [13]. Most wetlands are net carbon sinks rather than sources contributing to climate change [13]. Some studies indicate that wetlands can function as both sources and sinks of carbon, depending on factors such as their age, management practices, and environmental boundary conditions including climate and location [17]. The specific effect of wetlands is still controversial [18]. Although their GHG emissions can be 2 to 10 times higher than those of natural wetlands [19], the relationship between GHG emissions and CWs is complex and multifaceted. This is attributed to the significantly greater microbial biomass and influent pollutant load present in CWs compared to natural wetlands [20,21]. Therefore, how to ensure the purification effect of CWs while minimizing GHG emissions is the key to achieving sustainable development of CWs. A comprehensive understanding of the GHG generation mechanism in CWs will help to assess its dual effects as a climate change mitigation measure.
In recent years, there has been an increasing interest in research concerning GHG emissions from CWs. However, there is a scarcity of papers that have an overall analysis and summary of the field. It is necessary to comprehend the development of relevant research to provide a reference for further work. To address this shortfall, bibliometrics approaches are critical to reviewing and synthesizing the literature to fully understand the complexity of GHG emissions in CWs [22]. Bibliometrics is utilized to analyze the research progress and developmental trends within a specific study field. It can be employed as a tool for identifying and establishing connections among key elements pertinent to a particular subject. It offers valuable insights into the growth of literature and the flow of knowledge within a particular field over time by analyzing data collected from databases, such as citations, authors, keywords, and the variety of journals referenced [23]. CiteSpace 6.3.1, a Java-based application, is designed for the visualization of bibliometric results through metrology, co-occurrence analysis, and cluster analysis [24,25]. As a scientometric tool, it serves several functions: evaluating the current state of research, mapping subject areas, delineating interdisciplinary connections, identifying trending research topics, and forecasting research trends [25]. Since its inception, the software has been widely used in bibliometrics research.
In view of the above points, this study analyzes the references of the Web of Science Core Collection in the field of GHG emissions in CWs from 1993 to 2023 through bibliometric analysis and visualization. Specifically, this study is driven by four primary objectives: (1) to analyze and summarize the process of GHG generation and emission in CWs; (2) to understand the rise and development of the field of GHG emissions in CWs through the number of papers published and the frequency of citations per year, and identify countries and authors with more research; (3) to explore research hotspots through keywords in the past three decades years; and (4) to identify the shortcomings of current research and consider the possible research directions in the future.

2. Methodology

2.1. Data Sources

The reference data for the paper were sourced from the literature database of the Web of Science Core Collection. The keywords for the literature search were determined as the synonyms of CWs and GHGs, with the Boolean operation formula being TS = (“constructed wetland*” OR “artificial wetland*” OR “treated wetland*”) AND TS = (“greenhouse gas*” OR “house gas*” OR “GHG*” OR “carbon emission*” OR “carbon dioxide*” OR “CO2” OR “methane*” OR “CH4” OR “nitrous oxide*” OR “N2O”). Document types were selected as “article” and “review article”. While early studies in this field were limited, a noticeable uptick in publications has been observed since 1993. This growth reflects the evolution and milestones within the field. Consequently, the time span for this analysis was established as 1993 to 2023, resulting in 1019 documents. The search results encompassed a range of details pertaining to each document, such as title, year, citations, country, source (journal title), author(s), and keywords. Complete records were downloaded for subsequent analysis.

2.2. Analysis Methods

This paper summarizes the recent research on the GHG emission mechanism of CWs. Specifically, it focuses on N2O, CO2, and CH4 to briefly elucidate the mechanisms of production and processes of release for these GHGs. CiteSpace 6.3.1 was used to analyze the fundamental information of the literature, including countries, authors, and keywords. This study followed the general procedure of visual analysis of CiteSpace 6.3.1. The 1019 articles were exported in plain text files for data preprocessing. For countries and authors, a collaborative network analysis was performed. In the CiteSpace 6.3.1 user interface, the “Years Per Slice” parameter was used to partition the time period. This function organizes the literature into chronological segments to facilitate a better understanding of research topics, trends, and developments over time. The “Years Per Slice” parameter was set to 1. In the resulting visualization, nodes (represented by circles) were labeled and sized according to their significance. Node color indicates the time sequence, progressing from earlier (center) to more recent (edge) studies.
Different selections and configurations of parameters influence the credibility level of the results. For keyword co-occurrence network analysis, “Keyword” was selected in “Node Types” and the selection criteria g-index (k) for selecting the appropriate number of nodes in each time slice was set to 4. The visualization was pruned utilizing “Minimum Spanning Tree” and “pruning sliced networks”. On this basis, keyword clustering was conducted, and two important indicators offered insights into the overall structural characteristics of the network. Modularity Q, a community detection algorithm, indicates the extent to which the author or organization of authors of literature is divided into numerous independent modules and recombined together [26,27]. The value range of Q is from 0 to 1. If Q is > 0.3, it can be considered that the structure of the network community is rational and obvious. The silhouette metric is commonly employed as an index in cluster analysis, serving to assess the quality of clustering outcomes [28]. The closer the value approaches 1, the more effective the clustering outcome becomes. When S is > 0.5, the outcome of clustering is regarded as reasonable. By analyzing the timeline and visualizing the evolution in time, a timeline view of the keyword clusters was obtained. CiteSpace 6.3.1 calculates the occurrence frequency of each keyword in different time periods. When the frequency of a keyword experiences a significant increase over a specified period, it is considered a burst keyword. This article ultimately obtained 25 burst keywords, and the length of the red line segment displayed in the visualization represents the duration of the burst keywords. The specific start and end times are also listed accordingly.

3. Results and Discussion

3.1. The Generation and Release of N2O, CO2, and CH4 in CWs

3.1.1. The Production and Release of N2O

Comprehensively considering the migration and transformation of nitrogen in CWs, the pathways for N2O production and release in CWs are obtained (Figure 1). The upper layer of CWs forms an aerobic layer due to atmosphere reaeration and radial oxygen loss (ROL) of plant root systems [29], while the lower layer forms an anaerobic layer due to the lack of a dissolved oxygen source and the consumption of dissolved oxygen by aerobic microorganisms. Organic nitrogen is converted to ammonia nitrogen by biological ammoniation, which can be carried out under aerobic or anaerobic conditions. The next step is nitrifying-denitrifying microbial nitrogen removal. Nitrification refers to the process by which ammonia nitrogen is initially oxidized to nitrite nitrogen by ammonia-oxidizing bacteria, followed by its further oxidation to nitrate nitrogen by nitrifying bacteria [30]. Microorganisms with ammonia oxidation activity include ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) [30,31]. AOB is mainly concentrated in three genera: Nitrosococcus, Nitrosomonas, and Nitrosospira [32]. AOA generally outperforms AOB in terms of quantity and diversity, with known major species including Nitrosopumilus, Nitrosophaera, Nitrosokaldus, Nitrosotalea, etc. [31]. In this process, the possible production of N2O arises from chemical oxidation with NO2− as an electron acceptor [33], or due to the chemical decomposition of hydroxylamine [34] and the intermediates of biological hydroxylamine oxidation [35]. The nitrifier denitrification process—a reduction of NO2− by AOB in combination with electron donors (e.g., pyruvate, hydrogen, or ammonia) under oxygen-limiting conditions or raised nitrite concentrations, also produces N2O [34,36,37]. Denitrification is the process in which denitrifying bacteria convert nitrate nitrogen into nitrogen through a multi-step reaction [38]. Denitrifying bacteria are mostly facultative anaerobic and chemical heterotrophic bacteria [39]. The resulting intermediate product N2O is eventually converted into N2, which is the only way to remove N2O inside the CWs. In addition, under anaerobic conditions, anaerobic ammonia-oxidizing bacteria use nitrite as an electron acceptor and directly convert ammonia nitrogen to nitrogen, which is called Anammox [40]. Anaerobic ammonia-oxidizing bacteria do not produce N2O during the process. It is an attractive route for microbial nitrogen removal.

3.1.2. The Production and Release of CO2 and CH4

The production and release of CO2 and CH4 in CWs have a complex relationship with the carbon cycle [41]. CWs can fix CO2 through plant photosynthesis, and emit CO2 to the atmosphere through the respiration of plants and the oxidation and decomposition of organics in wastewater and substrate by microorganisms [42]. The release of CH4 in CWs is the result of anaerobic fermentation and CO2 reduction [43,44]. It is concluded that the CO2 released from CWs is the natural destination of organic matter and should not be included in the GHG emission catalog. Therefore, the ratio of organic matter conversion to CH4 is an important indicator to determine the final emission effect of carbon-based GHGs. Taking into account the migration and transformation of carbon in CWs, a diagram for the generation and release of CO2 and CH4 is obtained (Figure 2). Some organics in the influent of CWs are oxidized due to the activity of upper aerobic bacteria, and the final product contains CO2. There are two main ways to produce CH4—anaerobic fermentation and CO2 reduction [43,44]. Complex organic matter is hydrolyzed under the action of hydrolytic microflora (including aerobic bacteria, anaerobic bacteria, and facultative bacteria), and undergoes anaerobic fermentation to produce monomers such as fatty acids and alcohols. Then, under the action of acid-producing bacteria, acid and hydrogen are produced and CO2 is generated. Finally, methanogenic bacteria use acetic acid or CO2/H2 to produce CH4 under anaerobic conditions [45]. The generated CH4 may have oxidation in two forms: aerobic oxidation and anaerobic oxidation. Aerobic methane-oxidizing bacteria (MOB) oxidized CH4 to CO2 under aerobic conditions [46]. Anaerobic oxidation occurs in the denitrification process, where CH4 is oxidized to CO2 by denitrifying anaerobic methane-oxidizing bacteria (DamoB) and denitrifying anaerobic methane-oxidizing archaea (DamoA) [47,48]. The CO2 and CH4 generated and not eliminated in CWs are emitted through plant aeration tissue transport, bubble diffusion, and other forms [49]. Then, CO2 is fixed by plant photosynthesis.

3.2. Publication Number and Citation Frequency per Year

The number of publications and citation frequency in the field of GHGs in CWs per year is shown in Figure 3. The first study in this field was published in 1993. Overall, the number of published papers in the relevant field shows an increasing trend. The number of publications was limited from 1993 to 2000. It increased in 2001 and exhibited rapid growth after 2013, peaking at 121 publications in 2022. The citation frequency of literature also showed an increasing trend, especially after 2013, peaking at 4632 in 2022. The continuous rise in the publication number and the frequency of citations per year indicates a growing interest in this field, which is poised to propel the advancement of the field. In 2023, the number of published papers and the frequency of citations of literature both decreased, but the decline was not substantial. This could simply be a normal data fluctuation, not necessarily a research bottleneck.

3.3. Country and Author Analysis

From 1993 to 2023, the network of collaborating nations and territories comprised a total of 85 nodes (Figure 4). The cooperation network reflects extensive international and regional cooperation. Table 1 presents the 16 countries and territories that contributed the most to the total. The leading top 10 countries in terms of publication number are China, the United States, Canada, Spain, Germany, India, England, Australia, Estonia, and Italy. The color transition from the center to the periphery of the nodal circle illustrates the annual increase of pertinent research across various countries. Research in countries such as the United States, Germany, England, Estonia, and Japan commenced earlier. In contrast, research in China, Canada, Spain, India, and Australia is more recent. Although research on GHG emissions from CWs started later, China has the largest number of papers, with 453. It suggests a strong recent interest in this field among Chinese researchers. This can be attributed to the rapid economic growth in China, where the accelerated pace of industrialization and urbanization brings environmental challenges [9]. CWs offer an optimal alternative solution due to their effective purification effect, low cost, and low energy consumption. The demand promotes the related research of CWs in China [50]. In addition, from the centrality perspective, the United States (0.34) and China (0.28) have a significant international influence. They are the leading countries in this field.
The ranking of the top 10 authors with the most record counts in the domain of GHG emissions from CWs is listed in Table 2. The publications authored by the 10 individuals account for 20.607% of the total 1019 publications. Zhang J ranks first, accounting for 2.846% of the full count of 1019, and holds the highest number of publications (29). Mandel Ü and Chang J follow, with 28 and 25 papers respectively, accounting for 2.784% and 2.453%, respectively. In addition, the authors ranking from fourth to tenth all have at least 15 papers, including Ge Y, Wu HM, Chen W, Luo HB, Zhang K, He SB, and Hu Z. The main authors of publications in a field have a relatively accurate grasp of the development context, research hotspots, and emerging trends in this domain. By continuously tracking the latest research results of the main authors and their teams, the mainstream research direction can be achieved in real time. Author cooperation was analyzed by CiteSpace 6.3.1 (Figure 5). Closely related author groups have been formed among the authors, such as Wu Haiming, Zhang Jian, Hu Zhen, Chen Yi, Guo Wenshan, He Qiang. Among these groups, Wu Haiming, Zhang Jian, and Hu Zhen have greater influence. As shown in Figure 5, there are five prominent author groups, with a higher proportion of Chinese authors. This could be attributed to the heightened interest of Chinese researchers in this particular field, as mentioned in the previous paragraph. Cooperation between researchers from different geographic areas remains to be seen. Furthermore, cooperation primarily takes place within teams. Limited cooperation occurs among different groups of authors, indicating a necessity to enhance inter-team cooperation.

3.4. Keyword Analysis

The analysis of keyword co-occurrence frequency is visualized in Figure 6. The details of the top 24 keywords (Table 3) show that “constructed wetlands”, “constructed wetland”, “waste water treatment”, “removal”, and “performance” exhibited higher frequencies compared to other terms, with respective counts of 379, 253, 199, 186, and 182. This is because one of the important purposes of the construction of CWs is to treat wastewater. Specifically, this involves the effective removal of nutrients (nitrogen, phosphorus, etc.) in wastewater through the processes of plants and microorganisms.
In the keyword clustering analysis (Figure 7), the Q value and S value of the graph parameters are 0.3645 and 0.7655, indicating good rationality and credibility. These studies are extensively distributed across 8 categories, and keyword clusters involving #0 constructed wetland, #5 constructed wetlands, and #6 greenhouse gas indicates that the graph is consistent with the research theme. Phosphorus removal is shown as #1 phosphorus removal in the cluster diagram. The timeline view of the keyword clusters (Figure 8) shows that the smaller cluster, #7 rice, appeared earlier, around 1995. The content is only about rice paddy, coarse fibers, and fields. Since then, there have been less relevant studies.
Other keywords that appear more frequently include “nitrogen removal”, “denitrification”, “nitrous oxide”, “carbon dioxide”, “nutrient removal”, and “methane emissions”. These mainly involve the migration and transformation of nitrogen and carbon and are closely related to the production and removal of GHGs, such as N2O, CO2, and CH4. It is also expressed in clustering as #3 nitrogen removal and #4 methane. The role of microorganisms in this process is critically significant, as demonstrated by the #2 microbial community cluster. In addition, as indicated in Table 4, the emerging burst keywords following 2020 are “microbial fuel cell” (2021–2023) and “microbial community” (2021–2023), with strengths of 6.12 and 5.67, respectively. This highlights the current hotspots in research related to GHG emissions from CWs.

3.5. Hotspot Analysis

The role of microorganisms is to run through the wastewater treatment process in CWs. As can be seen from Section 3.1, microorganisms are particularly important in GHG emissions in CWs. From the study of microbial species and functions to the investigation of the mechanism of action and the gene level, research related to microorganisms has always been carried out, and new discoveries and applications continue to be made. According to the keyword analysis in Section 3.4, the latest research trend of GHG emission reduction in CWs can be obtained. In recent years, microbial fuel cells (MFC) and microbial communities have become research hotspots.
The basic physical processes in CWs and MFCs are highly complementary, and combining them to operate MFCs in CWs can effectively control GHG emissions. Ke Zhang et al. studied the position of plant roots in relation to the electrodes and concluded that operating MFCs effectively reduced CH4 emission irrespective of whether the plant roots were situated at the cathode or anode [51]. In the context of CW-MFC operating under sequencing batch conditions, the rhizosphere situated at the cathode was found to be more effective in suppressing CH4 emission, while the rhizosphere situated at the anode was more advantageous for the generation of electricity [52]. The external resistance exhibited no significant effect on the CH4 emission of CW-MFCs [52]. The study showed that the role of MFCs in CH4 emissions was due to the competition between methanogens and electrogens. This interaction altered the structure of the biochemical process and microbial community in CWs [53]. Proteobacteria, the primary electricigen in CW-MFCs, were boosted with rhizospheres situated at the cathode, and the CH4 emission exhibited a negative correlation with the abundance of proteobacteria [53]. Although the CW-MFC technology has a high potential for the control of CH4 emissions, the relationship between CH4 and CO2 emissions needs to be further addressed [54]. Researchers have conducted a quantitative comparison of pollutant removal efficiency and gas emissions between batch-fed wetland systems (BF CWs) and MFC CWs. The findings indicated that MFC CWs demonstrated considerably lower global warming potential than BF CWs [55]. In terms of cathode materials, carbon fiber felt (CFF) has the lowest emissions of CH4 and N2O, compared to carbon cloth (CC) and stainless-steel wire mesh (SSM) [56]. Moreover, by controlling variable factors such as the C/N ratio and the pH of the influent, it is suggested that CW-MFCs provide an environment-friendly method for the management of GHG emissions [56].
The CW-MFC system presents significant potential for advancement in the field of wastewater treatment. However, it also faces several limitations and challenges. The mechanisms by which microbial activity is influenced remain incompletely understood. Further investigation is needed on issues such as the role of plant rhizospheres in relation to electrodes and the selection of optimal electrode materials. Additional studies are essential to enhance system configuration, improve treatment efficiency, and mitigate GHG emissions. Beyond the scope of laboratory exploration, the technology needs to be considered for more practical applications.
Not only MFCs, but also factors such as substrate types, plants, and supplementary carbon sources in CWs have an impact on GHG emissions to a large extent through microorganisms. The structure of a microbial community offers valuable insights into the function of CWs [57], and the related analysis has received more attention. To investigate the effects of iron and manganese oxides on microbial communities, Cheng et al. extracted DNA samples from vertical subsurface-flow CWs (VSSCWs) and performed high-throughput sequencing. The addition of manganese oxides improved the overall relative abundance of Actinobacteria, Chloroflexi, and Proteobacteria, resulting in increased total nitrogen (TN) removal and reduced N2O fluxes, in contrast to quartz sand and iron oxides [58]. The relative abundance of Euryarchaeota in Fe-VSSCWs and Mn-VSSCWs were 0.40% and 0.19%, respectively. Both of these were lower than previously observed in the control group (0.51%). This discrepancy may contribute to the reduced CH4 fluxes [58]. Compared with clay ceramsite, the amendment of biochar distinctly mitigated N2O and CH4 fluxes from CWs by promoting a higher abundance of mcrA and nosZ genes and higher ratios of pmoA/mcrA and nosZ/(nirK + nirS) [59]. Xushun Gu et al. concluded that the presence of plants supported the abundance of ammonia oxidation bacteria, such as Nitrosomonas and Nitrosospira, as well as the amoA gene, when an additional carbon source was provided [60]. Wetlands with plants primarily functioned as carbon sinks, exhibiting a net carbon dioxide absorption flux of approximately 13,000 mg m−2 d−1. They had the capacity to offset emissions of N2O and CH4, with maximum values recorded at a maximum of 12.24 mg m−2 d−1 and 2.52 mg m−2 d−1, respectively [60]. For supplementary carbon sources, alkali-heated corncobs improved the abundance of heterotrophic denitrifying bacteria and increased nitrogen functional genes while GHG fluxes were lower compared to common corncobs [61].
With the development of omics technologies, our understanding of microbial community structure and gene function has deepened significantly. This helps to precisely regulate the environment of CWs, improve purification efficiency, and reduce the GHG emissions of CWs.

4. Research Limitations and Prospects

Since not all of the included articles focused entirely on GHG research in CWs, this study has some limitations, but it is enough to provide a relatively comprehensive insight into this field. Despite the deepening of relevant studies, there is still a lack of long-term and applied discussions on the practical role of CWs in promoting GHG emission reduction, and a unified understanding has not been formed. The biological action and reaction mechanism involved in the production and release of GHGs still need to be further explored. Future research may be considered from the following aspects:
(1)
The impact of different environmental factors is complex, and comprehensive consideration is needed for factors that affect GHG emissions from CWs, such as operation mode, substrate configuration, plant selection, and carbon source supplementation;
(2)
Further in-depth research is needed on the GHG conversion process involving microorganisms within CWs, such as the interaction between multiple N2O production pathways and the mechanism of CH4 anaerobic oxidation;
(3)
Genetic technology can be strategically employed to enhance microorganisms that are beneficial for mitigating GHG emissions in CWs;
(4)
Intelligent supervision systems, in conjunction with information technology, can be developed to precisely control operating conditions and monitor the effectiveness of CWs.

5. Conclusions

Based on CiteSpace 6.3.1 and the Web of Science Core Collection, this study provides a clear knowledge map and many conclusions can be drawn.
(1)
Organic nitrogen is converted to ammonia nitrogen by biological ammoniation and produces N2O through nitrifying-denitrifying microbial nitrogen removal. The resulting product N2O is eventually converted into N2, which is released from CWs. Anammox, a process that directly transforms ammonia nitrogen to nitrogen, represents an attractive route for nitrogen removal.
(2)
Organics in the influent of CWs are oxidized and the final product contains CO2. Anaerobic fermentation and CO2 reduction produce CH4. The CO2 and CH4 are emitted through plant aeration tissue transport, bubble diffusion, and other forms. After that, CO2 is fixed by plant photosynthesis.
(3)
In the past 30 years, the number of published papers and the citation frequency in the relevant fields show an increasing trend. China and the United States published more papers. The top ten authors contributed to 20.607% of the total 1019, and the cooperation between different author groups needs to be strengthened.
(4)
The emerging burst keywords following 2020 are “microbial fuel cell” and “microbial community”, which highlights the current hotspots in research related to GHG emissions from CWs. Beyond the scope of laboratory exploration, the CW-MFC needs to be considered for more practical applications. The deepened understanding of microbial communities helps to precisely regulate the environment of CWs and reduce the GHG emissions of CWs.
(5)
Despite relevant studies, there is still a lack of long-term and applied discussion on the role of CWs in promoting GHG emission reduction. The relevant reaction conditions and mechanisms need to be explored, and the possible research directions in the future can be genetic regulation and information technology.

Author Contributions

Conceptualization, H.W. and Z.G.; Methodology, J.D. and Z.G.; Software, R.Q.; Validation, Y.K. and Z.G.; Formal analysis, H.X.; Investigation, Z.G.; Resources, Z.G.; Data curation, R.Q. and J.D.; Writing—original draft, R.Q.; Writing—review & editing, J.D.; Visualization, R.Q.; Supervision, H.X., H.W., Z.H. and Z.G.; Project administration, Z.H. and Z.G.; Funding acquisition, Z.G. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (Nos. 52270158, 52200196, 51925803, and 51908326).

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

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Water 17 00412 g001
Figure 1. The generation and release of N2O in CWs.
Figure 1. The generation and release of N2O in CWs.
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Figure 2. The generation and release of CO2 and CH4 in CWs.
Figure 2. The generation and release of CO2 and CH4 in CWs.
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Figure 3. The publication number and citation frequency of research on GHG emissions in CWs per year.
Figure 3. The publication number and citation frequency of research on GHG emissions in CWs per year.
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Figure 4. A representation of national and regional cooperation networks.
Figure 4. A representation of national and regional cooperation networks.
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Figure 5. Author cooperation network in the field of GHG emissions in CWs.
Figure 5. Author cooperation network in the field of GHG emissions in CWs.
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Figure 6. The co-occurrence network analysis of keywords on GHG emissions from CWs.
Figure 6. The co-occurrence network analysis of keywords on GHG emissions from CWs.
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Figure 7. A visualization of the keyword cluster analysis on GHG emissions in CWs.
Figure 7. A visualization of the keyword cluster analysis on GHG emissions in CWs.
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Figure 8. Timeline view of the keyword clusters on GHG emissions in CWs.
Figure 8. Timeline view of the keyword clusters on GHG emissions in CWs.
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Table 1. The top 16 countries and territories ranked by frequency.
Table 1. The top 16 countries and territories ranked by frequency.
Country and RegionFrequencyCentralityCountry and RegionFrequencyCentrality
China4530.28Estonia310.01
USA1720.34Italy290.17
Canada570.02France270.11
Spain500.11Denmark260.02
Germany470.08Japan250
India410.02Netherlands240.04
England360.04Sweden210.08
Australia340.05Brazil180.05
Table 2. The ten authors with the most publications in the field of GHG emissions in CWs.
Table 2. The ten authors with the most publications in the field of GHG emissions in CWs.
AuthorsRecord Count% of 1019AuthorsRecord Count% of 1019
Zhang J292.846%Chen W177.164%
Mander Ü282.748%Luo HB177.066%
Chang J252.453%Zhang K176.084%
Ge Y242.355%He SB154.907%
Wu HM232.257%Hu Z152.846%
Table 3. Top 24 keywords with a high frequency in the domain of GHG emissions in CWs.
Table 3. Top 24 keywords with a high frequency in the domain of GHG emissions in CWs.
No.KeywordsFrequencyCentralityNo.KeywordsFrequencyCentrality
1constructed wetlands3790.3713carbon dioxide660.05
2constructed wetland2530.3214nutrient removal620.04
3waste water treatment1990.1115wastewater treatment610.1
4removal1860.2316methane emissions600.1
5performance1820.1417community570.06
6nitrogen removal1580.1218nitrogen540
7denitrification1500.1519carbon490.03
8nitrous oxide1450.1820nitrate removal470.06
9waste water1380.2121organic matter400.02
10greenhouse gas emissions1320.0822CH4390.01
11soil700.0823phragmites australis390.08
12microbial community680.0424nitrification380.01
Table 4. Top 25 keywords with the strongest citation bursts. The red stripe represents the time period when the keyword burst, while the light blue stripe represents the time period when the keyword did not appear.
Table 4. Top 25 keywords with the strongest citation bursts. The red stripe represents the time period when the keyword burst, while the light blue stripe represents the time period when the keyword did not appear.
NoKeywordsYearStrengthBeginEnd1994–2023
1constructed wetlands19985.0319982003Water 17 00412 i001
2removal20039.3820032011
3oxidation20034.9220032007
4nitrous oxide20025.7220052011
5soil19995.4 20052011
6phragmites australis20007.7420072016
7CH4200911.0820092016
8N2O200010.3920092017
9greenhouse gases19955.1520112015
10diversity20114.7720112016
11methane emissions19956.6820122017
12constructed wetland19976.4720122013
13flow20135.2820132017
14nitrogen20045.1320152016
15flow constructed wetlands20177.0120172020
16nitrous oxide emissions20145.9320172018
17intermittent aeration20187.8520182020
18flow constructed wetland20185.9720182021
19organics20185.2720182019
20horizontal subsurface flow20196.3920192020
21N2O emission20135.7820192020
22N2O emissions20135.4720192020
23greenhouse gas20207.6920202023
24microbial fuel cell20216.1220212023
25microbial community20175.6720212023
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Qi, R.; Dong, J.; Kang, Y.; Xie, H.; Wu, H.; Hu, Z.; Guo, Z. Migration and Transformation of Greenhouse Gases in Constructed Wetlands: A Bibliometric Analysis and Trend Forecast. Water 2025, 17, 412. https://doi.org/10.3390/w17030412

AMA Style

Qi R, Dong J, Kang Y, Xie H, Wu H, Hu Z, Guo Z. Migration and Transformation of Greenhouse Gases in Constructed Wetlands: A Bibliometric Analysis and Trend Forecast. Water. 2025; 17(3):412. https://doi.org/10.3390/w17030412

Chicago/Turabian Style

Qi, Ruiyao, Jiahao Dong, Yan Kang, Huijun Xie, Haiming Wu, Zhen Hu, and Zizhang Guo. 2025. "Migration and Transformation of Greenhouse Gases in Constructed Wetlands: A Bibliometric Analysis and Trend Forecast" Water 17, no. 3: 412. https://doi.org/10.3390/w17030412

APA Style

Qi, R., Dong, J., Kang, Y., Xie, H., Wu, H., Hu, Z., & Guo, Z. (2025). Migration and Transformation of Greenhouse Gases in Constructed Wetlands: A Bibliometric Analysis and Trend Forecast. Water, 17(3), 412. https://doi.org/10.3390/w17030412

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