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Article

Mitigating Nitrous Oxide Emissions from Agricultural Soils with Biochar: A Scientometric and Visual Analysis

by
Jingyi Ren
1,
Yixuan Wang
1,
Mengqi Luo
1,
Yuxiang Zhuang
1,
Jixiong Wang
1,
Sen Chai
1,
Jun Liu
1,
Ziqi Zhang
1,
Yakun Li
1,
Peng Chen
1 and
Qi Wei
1,2,*
1
College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China
2
Jiangsu Province Engineering Research Center for Agricultural Soil-Water Efficient Utilization, Carbon Sequestration and Emission Reduction, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(5), 1115; https://doi.org/10.3390/agronomy15051115
Submission received: 10 April 2025 / Revised: 28 April 2025 / Accepted: 28 April 2025 / Published: 30 April 2025
(This article belongs to the Special Issue Innovative Practices for Carbon Management and GHG Mitigation in Agriculture)
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Abstract

:
The application of biochar in agricultural ecosystems has been demonstrated as an effective strategy for addressing climate change. This study conducted bibliometric analysis via CiteSpace to evaluate 989 publications (2010–2024) on biochar’s role in mitigating agricultural soil N2O emissions. Key findings include (i) rapid growth in publications and citations, with Science of the Total Environment leading in output and Soil Biology and Biochemistry in citation impact; (ii) China and the Chinese Academy of Sciences dominate national and institutional contributions, and author networks exhibit multi-tiered collaboration structures with limited overlap between high-productivity and high-impact researchers; (iii) research hotspots prioritize global warming potential, carbon footprint, and biochar’s chemistry property, mineralization, and pyrolysis processes; (iv) and the field evolved through three phases, as follows: initial emphasis on biochar–fertilizer synergies (2010–2015), followed by microbial mechanisms (2016–2020), and recent focus on soil carbon dynamics and multi-greenhouse gas interactions (2021–2024). Future research should address feedstock–pyrolysis coupling mechanisms, soil-specific application thresholds, and biochar–water–fertilizer interfacial interactions to optimize emission reduction, enhance nitrogen efficiency, and support China’s “Dual Carbon” goals. The study has important guiding significance for promoting the theoretical framework of sustainable agriculture and climate-resilient soil management.

1. Introduction

Nitrous oxide (N2O), a potent greenhouse gas with an atmospheric residence time of 114 years [1], exhibits a 100-year global warming potential (GWP) 273 times that of carbon dioxide (CO2) [2] and constitutes a major contributor to stratospheric ozone depletion [3]. Agricultural soils account for approximately 80% of global terrestrial N2O emissions and 60% of total anthropogenic N2O releases [4,5], primarily driven by excessive nitrogen fertilizer application. Therefore, how to reduce N2O emissions from agricultural soils through various agricultural measures has become a hot topic of global concern.
Biochar is a stable carbon-rich byproduct generated from biomass pyrolysis under high-temperature and oxygen-limited conditions during biofuel production [6,7]. It is characterized by low solubility, stability, and high aromaticity [8]. It has been widely employed to enhance soil carbon sequestration [9], improve soil fertility and crop yields [10,11], and mitigate climate change [11]. Studies demonstrate that biochar application significantly reduces agricultural soil N2O emissions, while enhancing nitrogen use efficiency [12,13,14]. Its mitigation mechanisms including pH elevation (28.46–68.34% emission reduction) and the regulation of nitrification or denitrification functional genes and microbial communities [15,16,17,18]. However, the mitigation effects of biochar exhibit uncertainties; field-aged biochar suppresses 17.0% of N2O emissions; whereas, microcosm experiments show inapparent impact from aged biochar and even a 15.5% increase in cumulative N2O emissions from fresh biochar [19,20]. These findings indicate that the mitigation efficacy is modulated by multiple factors, including biochar types and properties [21,22,23], application dosage and frequency [24,25], soil characteristics, and agronomic practices [26,27,28]. For example, Lan Zhongming et al. reported that peanut shell, green waste, and radiata pine-derived biochar reduced N2O emissions by 17–23% in low-hill red soils, while mallee wood and pine wood biochar increased emissions [29]; Harrison Brendan P. et al. observed 47.6% N2O reduction in acidic soils but no significant effect in neutral soils after biochar amendment [26]; Nelissen Victoria et al. demonstrated through microcosm experiments that urea ((NH2)2CO) and potassium nitrate (KNO3) applications reduced cumulative N2O emissions by 52–84%, while ammonium chloride (NH4Cl) showed no mitigation effect [30].
Although substantial empirical evidence has accumulated regarding the biochar-mediated regulation of agricultural N2O emissions, current research outcomes remain fragmented. Systematic integration and the critical evaluation of boundary conditions governing the mechanisms and spatiotemporal heterogeneity are still lacking. As a result, it causes significant gaps in effectively assessing research progress and theoretical perspectives. To establish a comprehensive overview and effectively explore emerging trends, it is urgent to employ bibliometrics to more systematically and comprehensively analyze the field’s development, hotspots, and trends. Compared with the induction and integration of experimental results in traditional reviews or meta-analyses, bibliometric statistics can construct multi-scale knowledge graphs, identify the structure of scientific research collaboration, and make up for the deficiencies of traditional experiments in the integration of cross-scale mechanisms. It can also break through the limitation of the existing total number in the qualitative description of boundary conditions.
Therefore, this study conducts a bibliometric analysis using CiteSpace to examine biochar’s effects on agricultural soil N2O emissions systematically. The research objectives are to (1) map publication and citation trends, demonstrate relevant research strength, and collaborative networks in the field; (2) track the evolution of research hotspots and identify emerging frontiers; (3) analyze current challenges and future directions; and (4) based on the results of bibliometric analysis, propose corresponding solutions to the existing problems. The systematic analysis in this study will propose optimization strategies for farmland soil N2O emission reduction technologies, while providing novel theoretical foundations for achieving the dual objectives of “emission mitigation and carbon sequestration”.

2. Materials and Methodology

2.1. Data Collection

The Web of Science Core Collection (WOSCC) is a rigorously curated citation database that indexes high-impact academic journals and major international conference proceedings across disciplines [31], hosting over 170 million publications [32]. For this study, literature data relevant to the research field were retrieved from WOSCC before 25 January 2025, using the following search query: TS (Topic Search) = (“Soil*”) AND (“N2O” OR “Nitrous oxide”) AND (“Biochar” OR “Biocarbon” OR “Biological carbon” OR “Biomass charcoal”) NOT (“Grass*” OR “Wetland*” OR “Woodland*” OR “Forest”). Articles were identified if the relevant terms appeared in at least one of the following fields: title, keywords, or abstract. The initial search yielded 1129 results. After excluding non-article publications (e.g., conference papers, review articles, books), 989 peer-reviewed research articles spanning the period 2010–2024 were retained for analysis. The final dataset, including “full records and cited references”, was exported as plain text files to serve as the foundation for subsequent data processing and analysis. After conducting a thorough evaluation of the alternative keywords, we have verified that this search method is not only reasonable but also highly effective. The results obtained from this approach are both scientifically valid and comprehensive, ensuring that the search outcomes encompass a wide range of relevant literature.

2.2. Data Analysis

In the field of scientific knowledge mapping, mainstream bibliometric tools include CiteSpace 6.3R1, Gephi 0.9.7, VOSviewer 1.6.20, and Leximancer 4.5 [33]. Among these, CiteSpace—a Java-based visualization software developed by Chen Chaomei—has been widely adopted in disciplinary research [34,35]. As a computational and statistical bibliometric tool [36], CiteSpace enables researchers to extract critical information from published literature while providing comprehensive insights into research history, current frontiers, and future trends. Compared with other bibliometric tools, CiteSpace owns the advantages of dynamic analysis capabilities (time slicing, emergent word detection) and deep data mining functions (clustering algorithms, node information traceability), which are suitable for exploring the evolution trends and emerging hotspots in the field.
Therefore, this study employed CiteSpace to construct collaborative network analysis maps and keyword co-occurrence network analysis maps in the research domain of biochar addition effects on agricultural soil N2O emissions. The time threshold is set from January 2010 to February 2025 initially, with the slice being one year. Term Source includes title, abstract, author keywords, and keywords plus. To include more or fewer nodes, it is possible to increase or decrease the scale factor k to 25. More details of the settings will be presented in the corresponding section below. Furthermore, this study conducted an in-depth analysis of the field through keyword clustering analysis, burst detection timeline visualization, and co-citation analysis. CiteSpace facilitated the identification of relevant co-occurrence networks, intellectual foundations and research hotspots. These analytical outcomes provide scholars with objective perspectives to understand the knowledge infrastructure of this field and inform future investigations (Figure 1).

3. Results

3.1. Basic Characteristics

3.1.1. Annual Variation of the Quantities of Publications and Citations

In the 14 years from 2010 to 2024, there were 989 publications and 42,746 citations in the field. The annual number of publications and citations (Figure 2) shows that the number of publications exceeded 50 and 100, and the number of citations exceeded 1500 and 5000 for the first time in 2015 and 2020, respectively. Additionally, the average annual growth rate of publications was about 55% from 2010 to 2015, 15% from 2016 to 2020, and 20% from 2021 to 2024. At the same time, the average annual growth rate of citations from 2010 to 2015 was approximately 200%, while it only 22% from 2016 to 2020 and less than 5% from 2021 to 2024. Therefore, this paper divides the field into the following three phases: the germination stage (2010–2015), the stable development stage (2016–2020), and the rapid development stage (2021–2024). Among them, the total number of publications (TP) and the total number of citations (TC) in the germination stage account for only 14.56% and 6.32% of the total number of articles and the total number of citations in the whole period of the field, which is related to the effect of biochar on N2O emission, respectively. The average annual number of publications and citations in the stable development stage are 72.4 and 2848 times, which are 3.0 and 6.3 times higher than that of the germination stage. In the rapid development stage, the average annual number of articles and citations in the rapid development stage are 118.75 and 6345.5, accounting for 48.42% of the total number of publications and 59.97% of the total number of citations in the whole period.

3.1.2. Subject Categories Analysis

All the articles involve 44 different disciplinary categories, among which the top 10 disciplinary categories in terms of total number of publications published are shown in Table 1, including Environmental Sciences, Soil Science, Agronomy, etc. The number of articles published in different disciplines on the effect of biochar addition on N2O emission from agricultural soils at different development periods reflects the development trend of this research in different disciplines. The top three disciplines are Environmental Sciences, Soil Science, and Agronomy, accounting for 67% of the total number of publications in the ten disciplines. Except for Ecology and Agriculture Multidisciplinary, the number of publications in all disciplines shows a steady increase in both stable and rapid development periods. The number of publications in Green Sustainable Science Technology increased from 4 in the germination stage to 15 in the stable development stage, and then, to 15 in the rapid development stage. Therefore, it can be predicted that Green Sustainable Science Technology will be a hot discipline in the field of N2O emission from agricultural soils affected by the addition of biochar. In the future, there will be more studies focusing on biochar, which is a low-priced, excellent, widely used, and promising soil amendment [37,38], and on researching green sustainable science technology to reduce N2O emissions from agricultural soils [39,40].

3.1.3. Journal Analysis

(1)
Issuing journal analysis
The 989 relevant articles retrieved for this study were published in a total of 200 journals. Table 2 lists the journals with the number of publications greater than or equal to 20. Generally, the number of citations (TCb) of a paper reflects its impact level. The impact of journals may vary from one research area to another, so that the average number of citations per paper (TC/PC) can be a relatively good measure of the relative importance of a journal in a particular field. In addition, the impact factor (IFa) and h-indexd of a journal can also be a measure of its value based on its role and position in scientific communication. All the values of these parameters for the relevant issuing journals are shown in Table 2.
As can be seen from Table 2, Science of the Total Environment (STE) dominates the field with the highest number of articles (120) and citations (5543) and is the only journal with more than 100 articles. It exceeds the combined number of articles in the second place of Agricultural Ecosystems Environment (AGEE), the third place of Journal of Environmental Management (JEM), and the fourth place of Agronomy Basel, accounting for 11.74% of the total number of articles. In addition, AGEE, JEM, Agronomy Basel, and Biology and Fertility of Soils are the other journals with more than 30 articles. Although these five journals account for only 2.5% of the 200 journals, their total number of articles is 263, which is more than a quarter of the total number of articles. It can also be seen from the indicators in the other columns of Table 2 that AGEE has the highest TC/PC (102.14), and Soil Biology and Biochemistry (SBB) comes second to it (97.73). Although the number of articles in Scientific Reports and Journal of Environmental Quality have a relatively low publication volume (21 and 22 articles), their TC/PC are more than 80, ranking third and fourth, respectively. In the h-indexd ranking, there are three journals with more than 20 articles, which are STE, AGEE, and SBB. The above rankings infer that three journals, STE, AGEE, and SBB, are the leaders in terms of the number and quality of articles published in this research area.
(2)
Cited journal analysis
Only the number of journal articles is insufficient to show the influence of journals in the research field of “the effect of biochar addition on N2O emission from agricultural soils”; this article applied the citation analysis of journals to evaluate. Citation analysis is conducive to understand the influence and authority of publications in this field. Thus, this paper lists the top ten journals in terms of total citations (Table 3). From the table, it can be found that the top three journals are SBB, AGEE, and STE, whose citation counts are 907, 823, and 778, respectively, and their corresponding number of articles ranked third, second, and first. This means that these three journals occupy the top three places in the ranking of the total number of articles and citations and can be regarded as the top three in this research field as a result. Additionally, Plant and Soil, Chemosphere, Soil Science Social of America Journal, and Environmental Science Technology are not in the top ten in terms of the number of articles published in this research area. However, these journals are heavily cited in articles published in this research area, which suggests that they provide a good basis for the development of this research area as well.

3.2. Collaborative Network Analysis

3.2.1. Country Analysis

(1)
Co-operation network analysis
Figure 3 shows the mapping of academic collaborations between countries on the study “the effect of biochar addition on N2O emission from agricultural soils”, with a network of 69 nodes and 466 links from 2010 to 2024. In this study, we found that more than half of the articles are from China (including Taiwan), USA, Australia, and Germany. Along with New Zealand and Wales, these countries also published their first articles in this field as early as 2010, while Germany was a year later behind, publishing its first article in 2011. It is worth mentioning that Germany’s centrality in this research field is as high as 0.30, which is the highest among 69 countries, indicating that Germany maintains long-term co-operation with other countries and has a strong influence in this field. It frequently co-operates with China, USA, Australia, Pakistan, and New Zealand. Among the top 10 countries, Italy is only ranked 9th (39 articles), but its centrality is 0.1, ranking 5th. This phenomenon indicates that Italy has close co-operation with other countries and has a high influence in the co-operation network.
(2)
High-volume countries analysis
Table 4 lists the 10 countries with the highest number of publications. China has the highest number of publications (570, including Taiwan) among all 69 countries, accounting for more than 30% of the total number of publications. China also has the highest TC (19,933) and h-indexd (71), with its TC beyond that of USA and Australia combined. Other countries with more than 80 articles include USA (148), Australia (84), and Germany (82). The TC of these countries are all more than 4000, the TC/P is more than 50, and the h-indexd is more than 30, which illustrates that China, USA, Australia, and Germany dominate in the number, quality, and influence of papers issued in this research field and have an absolute leading advantage. What is worth mentioning is that, although the number of articles published by New Zealand is only 44, its TC/P is the second highest among ten countries (70.98). It demonstrates that the articles published by New Zealand scholars have had a far-reaching influence on the research of other countries in the field of the effect of biochar additions on the emission of N2O from agricultural soils and aroused widespread attention in the world.

3.2.2. Institution Analysis

(1)
Collaborative network analysis
Figure 4 reflects the collaboration visualization mapping of each research institution or university from 2010–2024. There is a relatively high level of close co-operation between research institutions. There are four institutions with centrality over 0.10, namely the Chinese Academy of Sciences, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, and Department of Primary Industries and Regional Development NSW. Among them, the Chinese Academy of Sciences occupies the first place with 0.43. It has long co-operated with the Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Department of Primary Industries and Regional Development NSW, and other domestic and international organizations, which has a strong influence in this research field. Besides, the Ministry of Agriculture and Rural Affairs and Chinese Academy of Agricultural Sciences tied for second place with 0.14. The Department of Primary Industries and Regional Development NSW ranked third with 0.11.
(2)
High-volume institution analysis
Table 5 lists the top ten research institutions in terms of the number of publications in the relevant fields. It can be visualized intuitively from the table that there are four institutions with more than 60 publications, namely the Chinese Academy of Sciences (148), Nanjing Agricultural University (69), Ministry of Agriculture and Rural Affairs (69), and University of Chinese Academy of Sciences (66). It is worthwhile to describe that the ten research institutions listed in Table 5 are all from China, which indicates that China plays a very active role in the field of biochar additions affecting N2O emissions from agricultural soils and has had a gigantic impact on this research field.
On top of that, the TC/P of Nanjing Agricultural University ranked first with 67.90. Although the total number of articles published by Nanjing Agricultural University is less than half of that of Chinese Academy of Sciences, its TC reaches 4685. In terms of h-indexd ranking, Chinese Academy of Sciences (45) and Nanjing Agricultural University (35) still ranked first and second, respectively, and the third University of Chinese Academy of Sciences had an h-indexd of 30.

3.2.3. Author Analysis

(1)
Author collaboration network
The development and improvement of academic research disciplines depend heavily on collaboration between researchers. Figure 5 shows the co-operative network mapping between authors (due to the large number of nodes, the following figure only shows the largest 5 sub-co-operative networks). In this diagram, the size of the nodes is related to the number of authors’ publications, and the connecting line means that they are co-authors. Domestic and foreign scholars co-operate relatively closely in this research field, among which Feng Yanfang, Li Liangqing, Ding Weixin, Bai Shahla Hosseini, Hussain Qaiser, and Mueller Christoph constitute the largest collaborative network together in this research field. Meanwhile, scholars from home and abroad have also formed their own collaborative networks. For example, Xiong Zhengqin and Zhang Xi from China have worked closely together, and Sudo Shigeto and Gonai Takeru from Japan have also formed their own collaborative circle.
(2)
Highly published scholars’ analysis
Table 6 lists the top 10 authors in terms of the number of publications, of which 7 are from China, 1 from Australia, 1 from Pakistan, and 1 from Spain. Among the 7 authors from China, 4 of them were from Nanjing Agricultural University, namely Xiong Zhengqin, Pan Genxing, Li Lianqing, and Zou Jianwen, respectively. Combined with Figure 5, it can be seen that Feng Yanfang, Pan Genxing, Hussain Qaiser, Li Liangqing, Sun Haijun, and Ding Weixin are in a collaborative network, which is in close contact with each other. They are working together on the field of N2O emission from agricultural soils affected by the addition of biochar. Besides, Xiong Zhengqin from Nanjing Agricultural University has been devoted to the impact of biochar addition on the agricultural environment and the effect of microbial activity in agricultural soils on soil greenhouse gas emissions for a long time [26,41,42].
(3)
Highly Cited Scholars’ Analysis
The authors’ co-citation aims to identify distinguished scholars with a greater concentration of research in the field and to identify potential directions in the research area of the effect of biochar addition on N2O emissions from agricultural soils. Table 7 lists the authors with more than 200 citations and their related information. There are 10 authors with more than 200 citations—two from USA (Johannes Lehmann and Kurt A Spokas), two from Australia (Lukas Van Zwieten and Bhupinder Pal Singh), and two from the UK (Thomas J. Clough and Simon Jeffery). Zhang Afeng who is in fourth place, and Wang Jinyang who is in ninth place, are both from China, and the remaining two are from Spain (Maria Luz Cayuela) and Denmark (Sean D.C. Case). Furthermore, Johannes Lehmann (USA) ranked first with 508 citations, while Maria Luz Cayuela from Spain and Lukas Van Zwieten from Australia ranked second and third with 434 and 347 citations.

3.3. Research Hotspots

3.3.1. Keyword Co-Occurrence

High-frequency keywords represent hotspot topics within a research domain, while high-centrality keywords reflect the strategic positioning and intellectual influence of specific research themes in the field [43]. Our methodology comprised the following two principal phases: First, implementing terminological standardization by consolidating synonymous expressions (e.g., “nitrous oxide emissions”, “nitrous oxide”, “N2O”, “N2O emissions”, “nitrous oxide emission”, “nitrous oxide production”, and “N2O production”) into the unified descriptor “N2O emissions”. Subsequently, employing CiteSpace to construct a keyword co-occurrence network (Figure 6) using articles published between 2010 and 2024.
Figure 6 demonstrates intricate interconnections among keywords through dense network linkages, indicating substantial thematic associations within the research domain. The top ten keywords by frequency include N2O emissions (733), greenhouse gas emissions (452), CO2 (358), soil (339), biochar (321), CH4 (163), impact (150), denitrification (136), amendment (126), and nitrification (123). Notably, N2O emissions exhibits the largest node size, but denitrification attains the highest centrality score (0.07). It signified denitrification as a pivotal bridging role in knowledge transmission.
We used the keyword co-occurrence analysis function of CiteSpace to draw the keyword co-occurrence maps and calculate the frequency and centrality of keyword appearances for the three periods of germination period (2010–2015), stable development period (2016–2020), and rapid development period (2021–2024). Then, we carried out statistically counting of the keywords in the top ten frequency in each period, as shown in Table 8.
It illustrates that the top five keywords remained unchanged over the three stages, which were N2O emissions, greenhouse gas emissions, soil, CO2, and biochar. It indicates that the research in this field has always been centered on the effect of biochar addition on greenhouse gas emissions from agricultural soils, which is in line with the field’s research theme.
Meanwhile, the evolutionary trajectory of research hotspots reveals the structural transformation of the research paradigm in this field. The high frequency word turnover analysis shows that “manure” and “fertilizer” in the germination stage (2010–2015) drop out of the high-frequency word sequence, while “nitrification” and “amendment” are significant in the stable stage (2016–2020), indicating that the research dimension of the field has shifted from agronomic management to process regulation. The germination stage studies focusing on the synergistic effects of biochar and fertilizer dosing are essentially input–output linear response studies. For example, Jinyang Wang et al. applied nitrogen fertilizer during the second latent period of rice, which significantly suppressed N2O emissions by 102.5% [44], while L.Van Zwieten et al., by applying unpyrolyzed poultry fertilizers to the soil, increased maize yields but also increased N2O emissions [45]. The stable development stage shifted to the regulation of nitrogen conversion process by biochar’s own properties, marking the research into the microbial metabolism regulation level. For example, Shuqing Li et al. linked N2O emissions to changes in denitrifying bacteria colony abundance during composting with the application of biochar amendment, demonstrating that the application of biochar amendment significantly reduced the amount of N2O produced by manure composting [46]. Yongxin Lin et al. found that the addition of biochar amendment increased the pH of the soil, which in turn, increased the abundance and diversity of AOB as well as N2O emissions by applying wheat straw-derived biochar amendment to paddy soil [47].
In the rapid development stage, the top ten keywords N2O emissions, greenhouse gas emissions, and soil occupied the top three positions with a frequency of 338, 246, and 162, respectively. Their continued dominance suggests that greenhouse gas emissions from agricultural soils is still a subject of global climate change research at present, evenly for a considerable period of time in the future. It is noteworthy that the keyword “organic carbon” appears for the first time in the rapid development stage, which is highly coupled with the implementation sequence of the “Dual Carbon” strategy (carbon peak and carbon neutral) proposed by the Chinese government in 2020, which characterizes that the policy orientation has already restructured the research framework in depth. As a consequence, the study of carbon will be a major focus of research in this field for Chinese scholars. The research on carbon will be the focus and hotspot of Chinese scholars in this field, such as the preparation and application of biochar [14,45], the storage and conversion of organic carbon [46,47], and CO2 emissions [13,34,48].

3.3.2. Cluster Analysis of Keyword

Cluster analysis refers to groups of high-frequency co-occurring keywords through algorithms to form clusters with intrinsic correlations, and each cluster represents a potential research topic or subfield, which can show the knowledge structure of the research field [49]. This paper analyzed the keywords and hotspots related to the study of the effect of biochar addition on N2O emission from agricultural soils from 2010 to 2024 based on CiteSpace. A silhouette > 0.5 indicates that the clustering effect of the data is reasonable [50]. The results showed that the modulus Q and weighted mean contour S of the cluster analysis were 0.3062 and 0.6141, respectively, indicating that the model clustering results were scientific and reasonable.
The keywords were clustered and analyzed using LSI as a source of clustered names based on the literature co-occurrence network mapping. Figure 7 shows the annual high-frequency keywords in this research area from 2010 to 2024. In this figure, a node represents a keyword, and the larger the size the higher the frequency of that keyword. Keywords in the same year are connected by lines of the same color. Keywords appearing in different years are connected by lines of different colors, and keywords on the same horizontal line share the same research topic. A cluster represents a research field, and the smaller the cluster-ID (close to 0), the more keywords this cluster contains [36].
Figure 7 illustrates the results of the first nine clusters. As can be seen from the figure, the top nine clusters all appeared earliest in the initial germination period (2010–2015), constituting the initial research direction of the field together. Among these, only # 4 sewage sludge and # 7 composting appeared behind 2010. This indicates that, in the early stage, researchers focus on the impact of greenhouse gas emissions and their mechanisms of action (# 0 climate change, # 2 ammonia volatilization, # 3 carbon sequestration, # 5 nitrate, # 6 N2O emission, etc.). With the progress of science and the deepening of research, scholars have also begun to intensify their studies on the factors influencing greenhouse gas emissions, such as the research on fertilizer raw material (# 4 sewage sludge, # 7 composting, etc.). This shows that research in this field is developing in a broader and deeper direction, which will be conducive to future agricultural measures moving towards a more low-carbon and economical direction.
Table 9 shows the characteristics of all 12 clustering results. The largest cluster for size is # 0 climate change (97), containing keywords such as nitrous oxide, nitrogen dynamics, sodium ferrate, etc. The largest cluster for silhouette is # 8 soil carbon sequestration (0.864), containing keywords such as greenhouse gas emissions, global climate change, and global cropland. The clustering results show that climate change, nitrogen cycle regulation, and soil carbon sequestration are long-term hotspots in this field, and the synergistic development pattern of multiple themes formed at an early stage lays the foundation for subsequent research. At the same time, directions such as waste resource utilization may become new research branches.

3.3.3. Keyword Bursts Analysis

The number of occurrences of keywords can be utilized to dig out the words with the highest frequency of change in a certain period of time from a large number of subject words, so as to reflect the change of research hotspots in that period. Burst words indicate the phenomenon that the keywords to be investigated switch in a short period of time. Burst words can be detected from a large number of subject words with a high change rate in a certain period of time by investigating the word frequency, emphasizing sudden changes [51]. Therefore, this study observes rapidly growing topics by identifying keywords that surge in a short period of time and utilizing CiteSpace’s Burst Word Detection Analysis to understand how topics have changed in recent years [52].
In Table 10, the blue bars represent the entire time interval, and the red bars specifically indicate the bursting period of the keyword, representing the start time and end time of each bursting interval [53]. The keyword biochar has the highest burst intensity (13.11), which lasts from 2010 to 2015 (the entire germination stage). It means that biochar appears most frequently in the germination stage. In terms of start time and end time, the keyword chemical property has the longest duration, from 2010 to 2018 (8 years). Its mutation intensity is 6.58, ranking second among the 30 mutated keywords. The circumstance revealed that this keyword is the hotspot and focus of research in the pre-development stage of the field. It is worth mentioning that the mutation intensities of global warming potential and carbon footprint, which have only appeared in the past 5 years and continue to this day, are 5.27 and 3.27, respectively. This condition implied that the assessment system is transforming from single gas flux observation to the evaluation of the climate effect of the whole life cycle. This trend suggests that the research on global warming potential has become one of the most important research areas in this field in recent years. It can be inferred that the research in this field will pay more attention to the assessment of the systematic contribution of biochar technology in the “Dual Carbon” strategy in the coming period.

4. Discussion

4.1. Current Research Focus and Hotspots

The current research pattern is characterized by multi-scale interactions. The results of the keyword burst analysis (Table 10) indicate that the current research hotspot centers on the ternary coupling system of “greenhouse gas emissions, soil heterogeneity, and biochar functional regulation”. The primary driving factors behind this focus include the porous structure and surface properties of biochar, the physicochemical characteristics of the soil (such as texture and pH), and the strength of water–nitrogen coupling in agronomic practices [44,54,55,56]. However, the results of biochar-mediated N2O emission fluxes and soil quality impacts are still highly uncertain [57], which sharply contrasts with the cascading environmental effects caused by the annual loss of 120 Tg of reactive nitrogen. This 120 Tg amount of reactive nitrogen is equivalent to the total annual input of inorganic nitrogen fertilizers from global cropland systems. This loss not only contributes to air pollution (specifically PM2.5) and the depletion of stratospheric ozone but also significantly accelerates biodiversity loss due to climate change. In light of these issues, it is crucial to establish a fitness model that integrates the biochar–soil system with agronomic practices to effectively reduce N2O emissions, alleviate environmental pollution, and mitigate the greenhouse effect.
The precise application of biochar requires the establishment of a multi-parameter adaptive system of “raw material process–soil management”. Studies have shown that the N2O reduction effect of biochar is coupled with its physicochemical properties and application scenarios. Deng Bangliang et al. revealed that the 0.5–2 mm particle size section has the lowest N2O emission rate due to the optimal pore connectivity in a particle-size grading test of oil tea husk biochar [35]. Muhammad Jaffar et al. found that nitrogen-enriched biochar caused a 157.3% surge in cumulative N2O emissions due to nitrite accumulation triggered by C/N imbalance in loamy soils; whereas, normal biochar decreased by 14.7%. On the contrary, both nitrogen-enriched and normal biochar reduced N2O emissions in sandy soils [58]. Liu Hongyuan et al. held field experiments, and the results showed that a continuous application pattern of 4 t/ha per year had a more significant emission reduction than a one-time large application (12 t/ha) [59]. Besides, some other studies also reported the negative effects of biochar on agriculture soil; namely, biochar based on different biomass conversion processes have an adverse influence on soil carbon mineralization [58], the alkaline soil with biochar applied leads to intensified N2O emissions due to the high NO3 content in the early stage [60], the transport of root secretions and biochar particles in rice plants may also reduce the stability of biochar in paddy soil, thereby affecting the stability of farmland soil [61], etc. All of the above studies showed that the effect of biochar application on the reduction in N2O emissions varies according to the physicochemical properties of biochar and the application scenarios.
Except for selecting biochar with appropriate physicochemical properties for different application scenarios, optimizing agricultural practices (moisture management, fertilization practices, and straw return to the field, etc.) can also achieve the goal of N2O emission reductions. In terms of water management, deficit irrigation reduced N2O emission fluxes by 17.4% and 15.5% in wheat and maize seasons, respectively, by lowering soil water content known to nitrify enzyme activity [47], while continuous and intermittent irrigation reduced N2O emission fluxes by 40% and 26%, respectively [62]. In the fertilization practice part, compared with conventional inorganic fertilizers, the combination of organic fertilizers and inorganic fertilizers could significantly reduce N2O emissions by lowering the concentration of ammoniacal nitrogen (NH4+) in the soil [63,64]. The application of urea and NO3− fertilizers also reduced cumulative N2O emissions (52–84%), but NH4+ fertilizers resulted in a failure of N2O emission reduction due to the known denitrifying enzyme activity [30]. Studies have shown that biochar increased AOA, AOB, nirK, nirS, and nosZ genes’ copy numbers during the period of high N2O emissions in the corn season [65], while straw return decreased them [66]. Besides, either straw return or biochar alone as a carbon source caused an increase in N2O emissions from agricultural fields, while the combination of the two facilitated the reduction in N2O emissions from biochar [15,41,67].
The results of this study show that current research on biochar-mediated N2O mitigation in agricultural soils continues to focus on three core aspects: biochar characteristics, soil variability, and farming practices—a framework expected to dominate future research. Within this structure, the following three emerging priorities are advancing the field: (1) Soil–biochar compatibility: developing systematic selection criteria for biochar types based on soil properties. (2) Integrated farming solutions: combining biochar application with precision irrigation and smart fertilization to enhance N2O reduction. (3) Microbial network dynamics: analyzing how biochar modifies microbial communities involved in nitrogen cycling. Building on the bibliometric findings and prior discussions, this study synthesizes multidimensional data with dynamic feedback systems to create a conceptual model (Figure 8) for designing experiments on biochar-driven N2O emission control.

4.2. Current Challenges and Future Prospects

Biochar demonstrates potential for agricultural greenhouse gas mitigation, yet achieving precise control of its N2O reduction efficacy faces persistent challenges across the following three domains: production optimization, environmental compatibility, and agronomic integration. Critical knowledge gaps persist in real-time process modeling, interfacial interaction mechanisms within soil systems, and comprehensive ecological risk evaluation. This study systematically examines the “material–soil management” adaptation bottlenecks in biochar implementation, proposing a methodological framework that integrates machine learning, multi-model fusion, and multiscale monitoring technologies (Figure 9). These advanced approaches aim to establish theoretical foundations and technical frameworks for precision-controlled biochar-based emission reduction systems.

4.2.1. Accurate Prediction of Biochar Preparation and Optimization of Application Rates

Studies have shown that biochar can directly or indirectly affect soil N2O emissions by virtue of its unique physical structure [68], high cation exchange capacity (CEC) and adsorption capacity [69], and its role as a carrier of variable charge [70], etc. However, the biochar-mediated N2O abatement mechanism is characterized by a significant material–environment coupling. The difficulties in the preparation of biochar and the selection of the application rate are summarized from the existing studies, mainly including the irreversible variation of biochar in the pyrolysis process and the spatial heterogeneity of the application effect [71,72], the nonlinear variation of key parameters, such as the yield and pore size of biochar with the pyrolysis temperature [73] and the inhibitory effects of a too-high application rate of biochar on the crop yield and microbial activity [74], etc.
Considering the above difficulties, this study revealed the following outlooks: (1) Developing a biochar property prediction system: constructing a model with the help of machine learning and artificial intelligence and optimizing the experimental parameters through the prediction results of big data in order to realize the accurate prediction of the structure and properties of biochar under different preparation processes [13]. (2) Establishing a “biochar application amount–soil N2O emission” function model: integrating the DNDC model with metagenomic data to quantify the threshold relationship between the application amount and N2O emission intensity in soils with different textures [73].

4.2.2. Selection of Soil Environment and Properties

The ecological and environmental effects of biochar are nonlinearly regulated by soil multi-interface coupling [57]. The intensity and direction of its effects depend on the multidimensional interactions network of soil microclimatic parameters (temperature, moisture [75]), physicochemical factors (pH [44], salinity [76], fertility [77]), biotic factors (microorganisms [78]), and even, pollution (white pollutants, heavy metal ions, etc.) [79]. Synthesizing the existing studies, it is known that the difficulties in the selection of soil environment and properties are mainly due to the fact that the response mechanism of the biochar–microbial–plant inter-root interaction network has not yet been clarified [28], the lack of studies on the interaction of biochar–pollutant composite effects in soils [80], and the limited studies on the effects of biochar on soils with different properties [81]. Considering the above difficulties, this study revealed the following outlooks: (1) Soil chemical risk assessment: an environmental risk assessment should be conducted to confirm that biochar does not pose any ecological risk in certain soil environments prior to the widespread application of biochar [82]. (2) Long-term monitoring of N2O emissions from biochar application in different types of soils: based on short-term data, an additional long-term study was conducted to assess the effects of biochar on N2O emissions under different soil types [26].

4.2.3. Combination of Biochar and Water Fertilization Measures

Water and fertilizer measures mainly include the type of fertilizer, the amount of fertilizer applied, fertilization methods, irrigation methods, and the amount of irrigation water, etc. Unreasonable fertilization or irrigation methods will make the effect of biochar in mitigating N2O emissions poor [15,62,83] or even cause the opposite effect. Crop residues, straw returned to the field, and compost can also be used as fertilizers to supplement soil fertility, but direct application to the soil will stimulate N2O emissions [84]. Therefore, the difficulties in combining biochar with water fertilization measures are mainly due to the lack of long-term and accurate field studies on the efficacy of biochar and biochar–compost mixtures on different soil types and agroclimatic zones [85], the unquantified thresholds for biochar–straw application to regulate N2O emissions in soils with different structures and properties [86], and improper irrigation, which can affect both crop yields and nitrate uptake by crops [87].
This study made the following outlooks: (1) Develop a coupled soil–crop–atmosphere continuum water–nitrogen model: optimize the spatial and temporal matching scheme of the effects of fertilizer level and irrigation system on crop yield and N2O emission [18]. (2) Establish a prediction model of emission reduction efficiency: explore the effects of biochar on the metabolic function genes and enzyme activities related to N2O emission in the process of composting [88]. (3) Constructing a carbon footprint optimization model based on life cycle assessment: quantifying the greenhouse effect potential of measures, such as straw return and crop residue in combination with biochar [74].

4.3. Limitations

Through bibliometric analysis, this article comprehensively and clearly presents the evolution of keywords and hotpots in the field of the effect of biochar addition on N2O emission from agricultural soils and predicts the future development trends of the research field. This will be beneficial to scholars gaining an in-depth understanding of the development process in this field and provide ideas for future research. However, this study still has certain limitations.
(1) The limitations of the database. The scope of this study is constrained by its exclusive reliance on the Web of Science Core Collection (WOSCC) as the sole data source. While WOSCC encompasses a wide range of high-quality journals, its coverage is inherently constrained. Notably, certain discipline-specific journals (e.g., Advances in Agriculture, International Journal of Agricultural Science) remain excluded. Furthermore, WOSCC exhibits a pronounced disciplinary selectivity, prioritizing journals in natural sciences and medicine over those in social sciences, arts, and humanities. This systemic bias may result in the omission of critical literature, particularly in emerging interdisciplinary domains (e.g., computational sociology integrated with agricultural biology), which are underrepresented due to the database’s current indexing framework. Such limitations underscore potential gaps in comprehensively capturing the full spectrum of scholarly discourse.
(2) The limitations of publication types. Grey literatures (such as conference abstracts, technical reports, preprints, government documents, etc.) are usually excluded in the WOS database. To maintain publication quality, the document types of this study are only articles, which may unintentionally exclude research data from this field. This leads to the omission of early signals of research hotspots or emerging trends. Future research can extend the data collection to other types of publications (such as reviews, meetings, etc.).
(3) The subjectivity of analysis. Although the bibliometric analysis conducted using professional software is objective, the interpretation of the results still has subjectivity. Different researchers have different understandings and interpretations of the same content.
(4) Lack of practice. Although this paper has put forward certain solutions and suggestions for the problems found in the research, these comprehensive conclusions and suggestions still lack practical verification and require more research for subsequent supplementation, explanation, and application.

5. Conclusions

The current research summarizes the research progress on the effect of biochar addition on N2O emission from agricultural soils, further outlines the current research hotspots and challenges, and predicts the future development trend. The main findings are summarized as follows:
(1) The number of papers and citations in this research area is increasing rapidly, and it is currently in a “rapid development stage”. The core disciplines are Environmental Sciences, Soil Science, and Agronomy, and the leading journals are Science of The Total Environment (no.1 in terms of number of publications) and Soil Biology and Biochemistry (no.1 in terms of citations).
(2) China (569) and Chinese Academy of Sciences (148) are the countries and institutions with the highest number of publications, while Science of the Total Environment and Xiong Zhengqin are the journals and authors with the highest number of publications. The author co-operation network shows a multi-circle structure, but the correlation between high publications and high cited authors is weak.
(3) N2O emissions, greenhouse gas emissions, ammonia volatilization, and carbon sequestration are the hot topics, and climate change is the most widely covered direction. Global warming potential and carbon footprint are the focus of current research. The core research centers around biochar, chemistry property, decomposition, mineralization, and pyrolysis.
(4) Research Evolution: Initially, the research focuses on the synergistic effect of N2O emission reduction through the combination of biochar and fertilizers. In recent years, the research has shifted to microbial mechanisms (nitrification or denitrification) and soil microbial community regulation. Then, this has been expanded to the conversion of soil organic carbon and the synergistic mechanism of multi-greenhouse gas emission in 2021–2024.
To advance biochar’s agricultural application, this study proposes clarifying feedstock–pyrolysis interactions, developing dynamic application thresholds based on soil variations, and revealing biochar’s synergy with water–fertilizer systems. These efforts aim to enhance its role in reducing farmland greenhouse emissions and achieving China’s “Dual Carbon” goals, thereby supporting low-carbon agriculture and efficient nitrogen utilization.

Author Contributions

J.R.: codology, writing—original draft. Y.W.: data curation, writing—review and editing. M.L.: data curation, software. Y.Z.: software, data curation. J.W.: data curation, methodology. S.C.: conceptualization, writing—review and editing. J.L.: formal analysis, visualization. Z.Z., Y.L. and P.C.: visualization, data curation. Q.W.: methodology, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Innovative Training Program for University Students (202410294054Z), National Natural Science Foundation of China (51809077), and Research and Development Project of Jiangsu Environmental Engineering Technology Co., Ltd. (No. JSEP-GJ20220013-RE-ZL).

Data Availability Statement

The data are available from the corresponding author and can be shared upon reasonable request.

Conflicts of 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.

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Agronomy 15 01115 g001
Figure 1. Flowchart of literature retrieval and analysis.
Figure 1. Flowchart of literature retrieval and analysis.
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Figure 2. Annual number of publications and citations from 2010 to 2024.
Figure 2. Annual number of publications and citations from 2010 to 2024.
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Figure 3. Country co-operation network map.
Figure 3. Country co-operation network map.
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Figure 4. Institutional collaboration network map.
Figure 4. Institutional collaboration network map.
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Figure 5. Author’s collaborative network.
Figure 5. Author’s collaborative network.
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Figure 6. Keyword co-occurrence network.
Figure 6. Keyword co-occurrence network.
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Figure 7. Keyword clustering timeline chart.
Figure 7. Keyword clustering timeline chart.
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Figure 8. Conceptual framework for experimental design of biochar N2O emission reduction based on bibliometric evidence.
Figure 8. Conceptual framework for experimental design of biochar N2O emission reduction based on bibliometric evidence.
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Figure 9. Current challenges and future prospects.
Figure 9. Current challenges and future prospects.
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Table 1. The publication numbers of top 10 disciplinary categories.
Table 1. The publication numbers of top 10 disciplinary categories.
Subject Category2010–20152016–20202021–20252010–2025
Environmental Sciences57191252500
Soil Science5096107253
Agronomy195285156
Plant Sciences12285797
Engineering Environmental9184471
Ecology21132862
Agriculture Multidisciplinary19162560
Energy Fuels10212759
Biotechnology Applied Microbiology9192755
Green Sustainable Science Technology4153352
Table 2. Journals with a number of publications greater than or equal to 20.
Table 2. Journals with a number of publications greater than or equal to 20.
JournalsPCTCbTC/PCh-IndexdIFaInitial Year
Science of the Total Environment120554346.19458.22011
Agriculture Ecosystems Environment444494102.14276.02010
Journal of Environmental Management3695226.44168.02014
Agronomy Basel331905.7693.32018
Soil Biology and Biochemistry30293297.73269.82011
Global Change Biology Bioenergy26178368.58195.92012
Applied Soil Ecology2468128.38154.82014
Geoderma22100045.45175.62013
Journal of Environmental Quality22185484.27172.22010
Biology and Fertility of Soils22104047.27175.12011
Scientific Reports21182186.71163.82013
Journal of Cleaner Production2046523.13139.82015
Environmental Pollution20103051.50147.62013
Note: IFa: a journal-level metric, impact factor data from the 2024 edition of Journal Citation Reports® in Web of Science. TCb: the total citations for a journal. TC/PC: average number of citations per paper for a journal. h-indexd: according to Hirsch in 2005: A scientist has index H if H of his/her Np papers have at least H citations each, and the other Np-H papers have no more than H citations each, in which Np is the number of articles published during n years. A higher h-indexd indicates greater academic impact.
Table 3. Information about the top ten journals in terms of total citations.
Table 3. Information about the top ten journals in terms of total citations.
TCInitial YearCited Journal
9072010Soil Biology and Biochemistry
8232010Agriculture Ecosystems Environment
7782010Science of The Total Environment
7342010Plant and Soil
6632011Geoderma
6582010Biology and Fertility of Soils
5852010Chemosphere
5632010Journal of Environment Quality
5432010Soil Science Social of America Journal
5342010Environmental Science Technology
Table 4. Top 10 countries with the highest number of publications.
Table 4. Top 10 countries with the highest number of publications.
RankCountryCountTCTC/Ph-Index
1China57019,93334.6771
2USA148925062.0849
3Australia84796994.8739
4Germany82485359.1837
5Pakistan48225446.9623
6New Zealand44319470.9827
7Spain44256058.1821
8Canada41167739.9322
9Italy39207153.120
10South Korea3694126.1415
Table 5. Top 10 organizations with the highest number of publications.
Table 5. Top 10 organizations with the highest number of publications.
RankInstitutionPsTCTC/Ph-Index
1Chinese Academy of Sciences148566037.9945
2Nanjing Agricultural University69468567.9035
3Ministry of Agriculture and Rural Affairs69163722.9227
4University of Chinese Academy of Sciences66293843.8530
5Nanjing Institute of Soil Science57236441.4727
6Chinese Academy of Agricultural Sciences55139025.2721
7Northwest A&F University—China51169430.8024
8Nanjing Forestry University3057318.4814
9Jiangsu Academy of Agricultural Sciences2994528.6418
10China Agricultural University2767825.1112
Table 6. Top 10 authors based on publications.
Table 6. Top 10 authors based on publications.
AuthorFreq.InstitutionCountry
Xiong Zhengqin23Nanjing Agricultural UniversityChina
Feng Yanfang17Ministry of Agriculture and Rural AffairsChina
Pan Genxing16Nanjing Agricultural UniversityChina
Lukas Van Zwieten15NSW Department of Primary IndustriesAustralia
Hussain Qaiser14Pir Mehr Ali Shah Arid Agriculture UniversityPakistan
Li lianqing14Nanjing Agricultural UniversityChina
Sun Haijun13Nanjing Forestry UniversityChina
Ding Weixin13Chinese Academy of SciencesChina
Zou Jianwen13Nanjing Agricultural UniversityChina
Maria Luz Cayuela13Consejo Superior de Investigaciones Científicas (CSIC)Spain
Table 7. Authors with more than 200 citations and their affiliations.
Table 7. Authors with more than 200 citations and their affiliations.
TCInitial YearAuthorAuthor Unit
5082010Johannes LehmannCornell University, USA
4342011Maria Luz CayuelaCSIC—Centro de Edafología y Biología Aplicada del Segura (CEBAS), Spain
3472010Lukas Van ZwietenNSW Department of Primary Industries, Australia
3172011Zhang AfengNorthwest A&F University, China
3172011Kurt A SpokasUSDA-ARS, Soil and Water Management Unit, St.Paul, MN, USA.
2912010Thomas J. CloughImperial College London, UK
2472013Sean D.C. CaseUniversity of Copenhagen, Denmark.
2442010Bhupinder Pal SinghMurdoch University, Australia
2302012Wang JinyangNanjing Agricultural University, China
2212013Simon JefferyHarper Adams University, UK
Table 8. Top 10 keywords in germination stage (2010–2015), stable development stage (2016–2020), and rapid development stage (2021–2025).
Table 8. Top 10 keywords in germination stage (2010–2015), stable development stage (2016–2020), and rapid development stage (2021–2025).
2010–20152016–20202021–2025
KeywordFreq.Cen.KeywordFreq.Cen.KeywordFreq.Cen.
N2O emissions1100.02N2O emissions2850.02N2O emissions3380.05
biochar820.01greenhouse gas emissions1500.03greenhouse gas emissions2460.05
CO2610.15CO21470.02soil1620.07
greenhouse gas emissions560.10soil1260.00CO21500.03
soil510.05biochar1090.00biochar1300.01
denitrification290.06impact660.04CH4970.03
impact240.02denitrification550.01amendment670.01
manure210.16CH4480.14impact600.03
fertilizer200.04nitrification480.02organic carbon530.01
CH4180.19amendment460.00nitrification530.02
Table 9. Characteristics of all clustering results.
Table 9. Characteristics of all clustering results.
Cluster IDSizeSilhouetteTop Term (LSI)
0970.482nitrous oxide; nitrogen dynamics; sodium ferrate; greenhouse gases; straw incorporation; greenhouse gas emissions; carbon footprint; carbon budget; rice paddies; rainfed winter wheat
1840.583nitrous oxide; intensive vegetable production; yield-scaled N2O emissions; biochar rate; wheat yield; N2O emissions; gene abundance; water regimes; yield-scaled N2O emissions; intensive vegetable production
2750.536greenhouse gas emissions; microbial community; cropping rice system; greenhouse gases; wheat productivity; soil fertility; organic matter; soil mesofauna; mediterranean climate; cropping rice system
3740.722nitrous oxide; greenhouse gas emissions; soil carbon; exchangeable cations; fumigation; carbon sequestration; greenhouse gas; carbon neutrality; agricultural soil management; release
4460.648nitrous oxide; first-principles calculation; sodium ferrate; nitrification; manure; greenhouse gases; soil amendment; cropping systems; soil porosity; banana peels
5430.675nitrous oxide; nitrification inhibitors; biochar application; nitrogen mineralization; camellia oleifera; N2O emissions; fertilizer; impact; sorption; nitrification
6410.674nitrous oxide; soil moisture; temporal variation; available n; labile carbon; N2O emission; clayey loam soil; bulk density; water retention capacity; field-aged biochar
7240.781N2O emissions; soil moisture; fertilizer; nutrient; drainage ditches; greenhouse gases; sewage sludge; bacterial agents; microbial functional genes; pyrolysis atmosphere
8180.864greenhouse gas emissions; global climate change; global cropland; biochar application; functional theory calculation; nitrous oxide; nitric oxide; nitrogen oxide; plant growth bioassay; rice–vegetable rotation
Table 10. Keyword burst analysis.
Table 10. Keyword burst analysis.
KeywordStrengthBeginEnd2010–2025
biochar13.1120102015▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂
chemical property6.5820102018▃▃▃▃▃▃▃▃▃▂▂▂▂▂▂▂
manure5.1620102016▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂
increases4.3720102012▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂
microbial biomass3.9320102012▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂
bioenergy3.5420102014▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂
amendments5.0520112017▂▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂
sequestration3.5120112012▂▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂
mineralization4.0720122017▂▂▃▃▃▃▃▃▂▂▂▂▂▂▂▂
pyrolysis3.8720122017▂▂▃▃▃▃▃▃▂▂▂▂▂▂▂▂
organic matter3.4520122014▂▂▃▃▃▂▂▂▂▂▂▂▂▂▂▂
decomposition3.1420122018▂▂▃▃▃▃▃▃▃▂▂▂▂▂▂▂
polycyclic aromatic hydrocarbons3.5320132015▂▂▂▃▃▃▂▂▂▂▂▂▂▂▂▂
rice paddy3.5620142016▂▂▂▂▃▃▃▂▂▂▂▂▂▂▂▂
slow pyrolysis4.1920152018▂▂▂▂▂▃▃▃▃▂▂▂▂▂▂▂
cropping systems3.0820152016▂▂▂▂▂▃▃▂▂▂▂▂▂▂▂▂
sorption3.4020162018▂▂▂▂▂▂▃▃▃▂▂▂▂▂▂▂
crop productivity2.8520162017▂▂▂▂▂▂▃▃▂▂▂▂▂▂▂▂
abundance4.1820182019▂▂▂▂▂▂▂▂▃▃▂▂▂▂▂▂
paddy soils3.0220182020▂▂▂▂▂▂▂▂▃▃▃▂▂▂▂▂
reduction3.0520192022▂▂▂▂▂▂▂▂▂▃▃▃▃▂▂▂
field2.9220192021▂▂▂▂▂▂▂▂▂▃▃▃▂▂▂▂
pathways2.9120192022▂▂▂▂▂▂▂▂▂▃▃▃▃▂▂▂
nitric oxide2.8720202022▂▂▂▂▂▂▂▂▂▂▃▃▃▂▂▂
NH3 volatilization3.5020212022▂▂▂▂▂▂▂▂▂▂▂▃▃▂▂▂
global warming3.3620212022▂▂▂▂▂▂▂▂▂▂▂▃▃▂▂▂
volatilization3.8620222023▂▂▂▂▂▂▂▂▂▂▂▂▃▃▂▂
heavy metals3.4020222023▂▂▂▂▂▂▂▂▂▂▂▂▃▃▂▂
carbon footprint3.2720222025▂▂▂▂▂▂▂▂▂▂▂▂▃▃▃▃
global warmingpotential5.2720232025▂▂▂▂▂▂▂▂▂▂▂▂▂▃▃▃
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MDPI and ACS Style

Ren, J.; Wang, Y.; Luo, M.; Zhuang, Y.; Wang, J.; Chai, S.; Liu, J.; Zhang, Z.; Li, Y.; Chen, P.; et al. Mitigating Nitrous Oxide Emissions from Agricultural Soils with Biochar: A Scientometric and Visual Analysis. Agronomy 2025, 15, 1115. https://doi.org/10.3390/agronomy15051115

AMA Style

Ren J, Wang Y, Luo M, Zhuang Y, Wang J, Chai S, Liu J, Zhang Z, Li Y, Chen P, et al. Mitigating Nitrous Oxide Emissions from Agricultural Soils with Biochar: A Scientometric and Visual Analysis. Agronomy. 2025; 15(5):1115. https://doi.org/10.3390/agronomy15051115

Chicago/Turabian Style

Ren, Jingyi, Yixuan Wang, Mengqi Luo, Yuxiang Zhuang, Jixiong Wang, Sen Chai, Jun Liu, Ziqi Zhang, Yakun Li, Peng Chen, and et al. 2025. "Mitigating Nitrous Oxide Emissions from Agricultural Soils with Biochar: A Scientometric and Visual Analysis" Agronomy 15, no. 5: 1115. https://doi.org/10.3390/agronomy15051115

APA Style

Ren, J., Wang, Y., Luo, M., Zhuang, Y., Wang, J., Chai, S., Liu, J., Zhang, Z., Li, Y., Chen, P., & Wei, Q. (2025). Mitigating Nitrous Oxide Emissions from Agricultural Soils with Biochar: A Scientometric and Visual Analysis. Agronomy, 15(5), 1115. https://doi.org/10.3390/agronomy15051115

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