Is conservation agriculture controlled by greenhouse gas emissions?: Can a combination of field observations on the combination of conservation tillage and cover crops be used to control greenhouse gas emissions? In general, does plowing through the soil contribute greenhouse gases to the atmosphere? What are the new methods for preventing greenhouse gas emissions?

Conservation agriculture (CA), which combines conservation tillage and cover crops (CC), has gained increasing attention for its potential to improve soil health and mitigate climate change. Yet, there is limited research on its effects on greenhouse gas (GHG) emissions. Thus, field studies across different geographic locations were synthesised to assess the impact of CA on GHG emissions compared to tilled soil without CC (control). CA did not affect methane (CH4) uptake but had variable effects on CH4 emissions. Of 90 nitrous oxide (N2O) observations, 70% demonstrated no significant difference between CA and control. Although a 6% overall reduction in N2O was observed under CA, the effect was not statistically significant. None of the analysed driving factors (soil properties, CC types, and CA duration) significantly affected N2O emissions. In contrast, CA increased carbon dioxide (CO2) emissions by 12%, especially in soil with higher SOC levels (> 20 g kg−1 ), under legume CCs, and during the first five years of CA adoption. However, the effect diminished with long-term CA implementation. This study highlights the complex interaction of GHG emissions with management practices and soil properties, emphasising the need for site-specific strategies and long-term monitoring under diverse field conditions to understand and optimise CA practice for GHG mitigation. Anthropogenic activities have contributed to global warming by increasing the atmospheric concentrations of greenhouse gases (GHGs) like carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) (IPCC 2021). In 2023, the concentrations of CO2, N2O, and CH4 were 420 ppm, 337, and 1934 ppb, which was about 51%, 25%, and 165% higher than the pre-industrial levels, respectively (WMO 2024). The United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement adopted in 2015 aimed to limit the global average temperature increase below 2°C by 2100 or possibly limit the temperature increase to 1.5°C compared to pre-industrial levels. This requires GHG mitigation strategies for all GHG-emitting sectors, including agriculture, which accounts for 12% of global GHG emissions (IPCC 2021). Managing agroecosystems to sequester soil carbon (C) is a key strategy to mitigate anthropogenic GHG emissions. Conservation agriculture (CA) is promoted as an agriculture production system with a high potential for C sequestration and mitigation of GHG emissions (Corsi et al. 2012). CA is based on three principles: (i) minimal mechanical soil disturbance through conservation tillage (CT), i.e. no, reduced, or minimum tillage; (ii) permanent soil cover with crop residues and/or cover crops CCs); and (iii) crop diversification (FAO 2022; Kassam et al. 2022). Since 2008/09, CA has expanded by over 10 million hectares annually, covering 14.7% of the global cropland area by 2018/19 (Kassam et al. 2022). Several studies have documented the positive impact of CT or CCs on soil organic carbon (SOC) content by enhancing atmospheric carbon sequestration though increased soil organic matter (SOM) content and by reducing the loss of carbon stored in soil (Franzluebbers 2010; Varvel and Wilhelm 2011; Kumar et al. 2012; Poeplau and Don 2015; Bai et al. 2019; Jian et al. 2020; Blanco-Canqui 2022). However, while evaluating the mitigation potential of agricultural management practices, it is critical to assess the potential effects of agricultural management practices on N2O and CH4 fluxes. This is especially important given that the global warming potentials of N2O and CH4 are 273 and 30 times larger than that of CO2 over a 100-year time frame, respectively (IPCC 2021). Several meta-analyses have reported the variable effects of CT on GHG emissions, which are strongly dependent on climate, soil properties, cropland type, crop management, and tillage duration (Huang et al. 2018; Mei et al. 2018; Shakoor et al. 2021). Shakoor et al. (2021) indicated increased CO2 and CH4 emissions under CT compared to those under conventional tillage, while Huang et al. (2018) reported a decrease in CH4 emissions but no difference in CO2 emissions. However, both studies reported an increase in N2O emissions by CT practices, as reported in the meta-analysis by Mei et al. (2018). Growing CCs can increase CO2 emissions driven by enhanced biomass carbon inputs to the soil (Muhammad et al. 2019; Shackelford et al. 2019). But the effects of CCs on N2O fluxes are inconsistent, depending on soil properties and management decisions like CC type and residue management following CC termination (Basche et al. 2014; Li et al. 2023a). The individual effects of CT and CCs on GHG emissions are relatively well documented, but limited information exists on their combined impact. In recent years, there has been a growing interest in complementing the CT practices with CCs to improve soil health and increase SOC stocks (Olson et al. 2014; Farmaha et al. 2022). This approach also reduces soil erosion (Langdale et al. 1991), enhances water quality (Kaur et al. 2024), and lowers chemical inputs (Daryanto et al. 2020). Integration of CCs with no-till (NT) systems has also shown higher climate change mitigation benefits than the single management approach. This is because of the synergetic effects of CCs and NT to increase SOC, mainly by slowing down decomposition and increasing soil C inputs (Olson et al. 2014; Bai et al. 2019; Huang et al. 2020; Breil et al. 2023). However, as the soil’s nitrogen (N) and C cycles are tightly coupled (Lal 2010; Guenet et al. 2021), any management practice to increase SOC content might impact the N cycle and associated N2O emissions. According to a recent review by Guenet et al. (2021), the climate mitigation effect induced by increased SOC storage can be overestimated if associated N2O emissions are not considered. The integration of CCs in CT systems, can increase the N2O emissions by creating a suitable environment for denitrification due to higher retention of soil moisture and increased supply of labile C (Bayer et al. 2016; Parkin et al. 2016). Additionally, CA can increase CO2 emissions due to increased C inputs (Muhammad et al. 2019; Acharya et al. 2022) and CH4 emissions due to greater water-filled pore space and labile C availability (Wolff et al. 2018; Gong et al. 2021b). However, the effect of CA on GHG emissions can vary depending on climate, soil properties, CC types, and duration of CA practices (Abdalla et al. 2016; Huang et al. 2018; Mei et al. 2018; Muhammad et al. 2019; Shakoor et al. 2021). With growing interest in implementing CA as a climate-smart practice, its effect on GHG emissions remains uncertain. Therefore, this study was aimed to (1) assess the integrated effects of CT practices and CCs on GHG emissions by synthesising data from previously published studies and (2) evaluate the influence of key driving factors like climate, soil properties, CC types, and duration of CA practices on GHG emissions using a meta-analytical approach.Materials and methods Data collection Peer-reviewed articles published in English before October 2024 were searched on Web of Science and Google Scholar using the keywords (‘tillage’ OR ‘reduced tillage’ OR ‘minimum tillage’ OR ‘no-tillage’ OR ‘zero tillage’) AND (‘cover crops’) AND (‘greenhouse gas emissions’) AND (‘carbon dioxide’ OR ‘CO2’) AND (‘methane’ OR ‘CH4’) AND (‘nitrous oxide’ OR ‘N2O’). The following selection criteria were applied for the studies to be included in this synthesis: (1) Field studies, including the pair-wise comparison between CA and non-CA practices and their effects on CO2 and/or N2O and/or CH4 emissions, (2) CA practices should either use NT or reduced tillage or minimum tillage combined with the cultivation of CCs, (3) Non-CA practices, i.e. control treatment, should be conventionally tilled without cultivation of CCs, (4) Control and CA should be managed with similar agronomic practices, such as cropping intensity, irrigation, and soil type. However, studies with a reduced fertilisation rate in CA compared to control were included in the analysis as the N fertilisation rate was reduced considering the potential biological fixation by legume CCs and, (5) Mean or cumulative GHG fluxes were available or could be calculated easily. The GHG data were extracted directly from the main text and tables or indirectly from the figures using digitising software (Plot digitiser, https://plotdigitizer.com/ app). To identify the main driving factors for GHG emissions, the studies were grouped by the following categories: climate, soil texture, SOC content, CC types and years under the implementation of CA. Due to a limited number of observations for CH4 fluxes, an analysis of driving factors was not carried out. The climate was categorised into arid (≤0.65) or humid (>0.65) according to the aridity index (ratio of mean annual precipitation to mean annual potential evapotranspiration) by UNEP (1997). Most studies (> 90%) were conducted in humid climates. Therefore, no further analysis was made about the effects of climate. Soil texture was categorised into fine (clay, silty clay loam, clay loam, and sandy clay loam), medium (silt loam and loam), and coarse (loamy sand, sandy loam, and sandy). The data on SOC content from various depths within 0–30 cm soil depth were grouped as < 10 g C kg−1 , 10–20 g C kg−1 , and > 20 g C kg−1 . If only the SOM content was given, then the SOC content was computed, assuming that SOM consists of 50% SOC (Pribyl 2010). The three categories of CCs were legumes, non-legumes, and a mixture of legumes and non-legumes. The years under practice were categorised into three time periods: < 5 years, 5– 10 years, and > 10 years. Data analysis For N2O and CO2 emissions, metanalysis was also performed to determine the effects of CA on N2O and CO2 emissions using the natural logarithmic response ratio as a proxy for effect size (Hedges et al. 1999): ln R = ln Xt Xc (1) where, lnR, Xt and Xc is the natural log response ratio, cumulative or average GHG emissions from treatment with CA and control, i.e. conventional tillage without CCs, respectively. The variance estimation was challenging to synthesise as the factors for determining the variances were often lacking in many studies. Therefore, weighing factor (w) was determined based on the number of replicates used in the study based on Adams et al. (1997) and recently used in the meta-analysis by Joshi et al. (2023) and Yue et al. (2021) as: w = (Nt × NC) (Nt + NC) (2) where, Nt and NC are the number of replicates for the CA and control treatments, respectively. The overall weighted effect sizes (lnR) of CA on GHG fluxes were calculated with intercept-only linear mixed models using the "lme4” package in R version 4.3.1 (R Core Team 2023). In the model, lnR was fitted as the response variable, and the primary studies were treated as a random effect (Yue et al. 2021). The 95% confidence interval (CI) of lnR was generated by bootstrapping with 4999 iterations using the package ‘lmeresampler’ in R. The effect of CA was considered significantly different from the control if the 95% confidence interval did not overlap with zero. The effects of potential drivers of GHG emissions were also tested using a linear mixed model with drivers as a fixed effect and the studies as a random effect. The effect size of each factor was calculated by determining separate means and their 95% CIs for each factor. The mean effect size and their 95% CI were back-transformed to calculate the percentage change in GHG emissions as: m = (elnR − 1) × 100 % (3) where, m is the change of GHG emission under CA compared to control treatment.Results: A total of 15 studies with 41 observations, 35 studies with 90 observations, and 22 studies with 59 observations were identified to be included in this analysis to determine the combined effects of CT and CCs on CH4, N2O, and CO2 emissions, respectively. The studies were conducted in 14 countries: Japan, Korea, Pakistan, Tanzania, the Czech Republic, Denmark, France, Ireland, Italy, Lithuania, Spain, Brazil, Canada, and the USA. Most of the studies were from the USA (33%) and Brazil (23%). Out of 41 observations on CH4 fluxes, 59% reported net CH4 emissions, while the remaining 41% showed net CH4 uptake (Table 1). Among the studies showing CH4 uptake, the majority (94%) reported no significant difference between the CA practices and the control, suggesting the limited influence of CA practices on CH4 uptake. In contrast, studies reporting CH4 emissions showed variability in CA effects. 42% of observations reported no change in CH4 emissions under CA compared to the control, whereas 38% demonstrated higher emissions, and 21% reported reductions. These mixed responses reflect a complex interaction of CA practices on CH4 emissions. Most of the studies reporting CH4 emissions were conducted in rice (Oryza sativa) cropping system. Only two studies reported higher CH4 emissions from upland crops {maize (Zea mays) and soybean (Glycine max)}, both in soil with higher SOC content (> 20 g C kg−1 ) and with leguminous cover crops. The data obtained in the present study indicated variable effects of CA practices on N2O fluxes (Table 2). Out of 90 observations, the majority (70%) showed no significant change in N2O emissions under CA compared to the control, while only 19% and 8% of the observations reported an increase and decrease, respectively. The remaining 3% didn’t report the statistical analysis of the N2O emissions under CA and control. Annual N2O fluxes were reported in 61% of the observations. The calculated average annual N2O emissions from those observations {excluding Javed et al. (2024) due to exceptionally high emissions} were 1.6 (range −0.04 to 16.2) and 1.4 (range −0.1 to 10) kg N2O-N ha−1 year−1 for control and CA treatments, respectively indicating no effect of CA on annual N2O emissions compared to the control (Figure 1a). Based on the metanalysis, the overall weighted average emissions across all observations were 6% lower under CA than under control, with a 95% confidence interval (CI) ranging from -22 to 14%, indicating no significant difference in N2O emissions between the CA and control treatments. (Figure 2). Neither soil texture nor SOC content significantly affected N2O emissions for the CA relative to the control treatments. Legume CCs showed an average 13% increase in N2O emissions under CA relative to the control, though the increase was not statistically significant (95% CI, -5%, 35%) (Figure 2). However, the number of studies using legume CCs was relatively low compared to nonlegumes in this synthesis. Non-legume CCs were predominantly used in 60% of studies, followed by legumes (30%) and mixtures (10%) (Table 2). Among non-legumes, ryegrass (Lolium multiflorum) was most commonly used (37%), followed by annual rye (Secale cereale)(26%). The duration of implementing CA didn’t result in significant differences in N2O emissions (P = 0.38). Among the observations, CA practices were implemented for less than 5 years in 46% of cases and for over 10 years in 39%, indicating a nearly equal distribution of studies between short and long-term adoption. Similar to the observations for N2O, the effect of CA on CO2 emissions was inconsistent. While a substantial proportion of observations (32%) reported significantly higher CO2 emissions under CA than the control, the majority (61%) showed no significant difference (Table 3). However, even among non-significant studies, there was a tendency towards higher emissions under CA. A small fraction (7%) of observations reported reductions (Table 3). The average annual CO2 emissions calculated from the studies reporting annual emissions were higher for CA (8.4 Mg CO2-C ha−1 year−1 ) compared to the control (7.1 Mg CO2-C ha−1 year−1 ) (Figure 1b). This finding was supported by the weighted average emissions from meta-analysis, which showed 12% higher emissions under CA than control with 95% of confidence interval ranging from 0.0 to 25% (Figure 3). There was neither the effect of climate (P = 0.92) nor soil texture (P = 0.43) on the effect of CA on CO2 emissions. CA practices significantly increased CO2 emissions by an average of 49% (95% CI, 13%, 94%) compared to the control in soils with a SOC content greater than 20 g kg−1 USA . Legume CCs significantly increased CO2 emissions by an average of 25% (95% CI, 3%, 52%), while non-legume CCs increased emissions by 15% (95% CI, 0%, 32%) under CT systems compared to the control (Figure 3). Most studies (61%) included in this analysis implemented the CA recently (i.e. < 5 years). In these cases, CO2 emissions were significantly higher by an average of 15% (95% CI, 4%, 27%) from CA than the control. However, no effect on CO2 emissions was observed after long-term implementation of CA practices, i.e. greater than 5 or even 10 years. Discussion Effects of conservation tillage practices combined with cover crops on methane fluxes In soil, CH4 flux is governed by the balance between methanogenesis (CH4 production under anaerobic conditions) and methanotrophy (CH4 oxidation under aerobic conditions) (Le Mer and Roger 2001). CA practices have the potential to influence both these processes (Yagioka et al. 2015; Wolff et al. 2018; Gong et al. 2021b). On the one hand, CT and CC systems increase the input of labile C, reduce soil bulk density, and increase water-filled pore space, which favours CH4 production (Yagioka et al. 2015; Wolff et al. 2018; Gong et al. 2021b). On the other hand, CA can improve soil macro-porosity, thus increasing gas diffusivity and oxidation capacity of methanotrophic bacteria, favouring CH4 consumption (Yagioka et al. 2015; Blanco-Canqui and Ruis 2020). In the upland soils, CH4 fluxes were low, ranging from a small sink to a source, consistent with the predominantly aerobic condition of these soils (Mosier et al. 2006; Adviento-Borbe et al. 2007). The data presented in this study showed no significant effect of CA on CH4 fluxes in upland soils. However, higher CH4 emissions in two upland soils with higher SOC levels and leguminous CCs (Kimaro et al. 2016; Gong et al. 2021b) demonstrated the importance of SOC and residue quality on CH4 emissions. Higher SOC can enhance soil moisture retention (Lal 2020), creating an anaerobic microsite conducive for CH4 production. This, in addition to lower C: N of legumes, can supply labile carbon for methanogens (Gong et al. 2021b), which can further promote CH4 emissions. In rice-cultivated areas, one of the significant sources of CH4 emissions from agriculture (IPCC 2021), CH4 emissions showed variable effects upon conversion to CA, ranging from no impact to an increase and a decrease in CH4 emissions. Under the NT system in rice, CH4 emissions are reported to be lower due to the inhibition of CH4 emission caused by soil compaction (Li et al. 2023b) and lower input of biomass C attributable to reduced residue incorporation (Bayer et al. 2014; Mezzari et al. 2023). Though the addition of CCs in NT systems can increase the labile C fractions in the soil, the seasonal CH4 emissions from 20-year NT soil with rye-grass and birdsfoot trefoil were similar to those from NT soil with winter fallow, but lower than conventionally tilled soil with winter fallow (Mezzari et al. 2023). In contrast, some studies have reported higher CH4 emissions under CA primarily due to higher residue retention in NT soil (de Souza et al. 2023; Grohs et al. 2024). Residue management in the control system plays an important role in determining the relative difference in CH4 emissions between the CA and control systems. For instance, when the rice straws are incorporated into the soil after the rice harvest in control, reducing the amount of surface residue, CH4 emissions are higher in CA (de Souza et al. 2023; Grohs et al. 2024). In contrast, if the straws are incorporated right before rice sowing, CH4 emissions are higher in the control treatment (Mezzari et al. 2023). Besides the soil C input, CA can alter soil moisture status, influencing CH4 emissions (Gong et al. 2021b; Yagioka et al. 2015). For instance, Karki et al. (2021) compared the CH4 emissions from furrow-irrigated rice with and without CCs and found lower emissions in CCs areas due to drier soil conditions.Effect of conservation tillage combined with cover crops on nitrous oxide fluxes N2O is primarily produced by the microbiological process of nitrification and denitrification, which is strongly influenced by several factors like soil pH, texture, temperature, moisture, and C and N contents (Signor and Cerri 2013). Besides, management practices like fertilisation, irrigation, tillage, cropping system, and climate, i.e. temperature and precipitation, can directly and indirectly affect soil N2O emissions. CA practices can have contrasting effects on soil N2O emissions. CA can increase soil N2O emissions by creating an anoxic condition conducive to denitrification, driven by increased SOM and higher soil moisture retention (Bayer et al. 2016; Parkin et al. 2016; Guenet et al. 2021). However, increased anoxia can also reduce N2O emissions by promoting the complete reduction of N2O to N2 (Butterbach-Bahl et al. 2013). Additionally, CCs can reduce residual N by scavenging it, thereby limiting substrate availability for denitrification and subsequently reducing N2O emissions (Behnke and Villamil 2019; Acharya et al. 2022). Furthermore, CA improves soil structure, which can directly influence the N2O dynamics (Dhaliwal et al. 2024a). For instance, NT combined with CCs has been shown to increase soil macroporosity and relative gas diffusion coefficient (Yagioka et al. 2015; Panday and Nkongolo 2021; Araya et al. 2022). These improvements in soil structure may reduce anaerobic microsites, thereby limiting N2O production. However, they may also facilitate the release of N2O into the atmosphere. Therefore, the impact of CA practices on soil N2O emission depends on the balance of all these factors, which may vary depending on local soil and climate conditions and management practices. The type of CC plays a critical role in controlling N2O emissions (Basche et al. 2014; Muhammad et al. 2019). Legume CCs generally tend to increase soil N2O emissions relative to non-legume CCs due to higher soil inorganic N content from atmospheric N fixation and enhanced soil mineralisation driven by their low C: N ratios (Bayer et al. 2016; Gong et al. 2021b). Though legume CCs showed a tendency to increase N2O emissions from CA in this meta-analysis; the effect was not significant. The lack of increased emissions from legume CCs may be attributed to CT systems where CC residues were left on the soil surface rather than incorporated. Incorporating CC residues increases the contact of residues with microorganisms, increasing the N2O emissions rather than leaving CC residues on the soil surface (Basche et al. 2014; Muhammad et al. 2019). Soil texture significantly influences the impact of conservation practices on N2O emissions as it affects soil structure, soil porosity, and moisture dynamics (Mei et al. 2018; Muhammad et al. 2019; Li et al. 2023a). However, this analysis didn’t find any effect of soil texture on N2O emissions. In fine-textured soils, NT can lead to soil compaction and increase the soil bulk density, creating anaerobic conditions that promote denitrification and N2O emissions (Mei et al. 2018; Li et al. 2023b). However, while NT may create conditions hat favour N2O emissions in fine-textured soils, including cover crops, can counteract this. Cover crops can decrease soil bulk density and increase soil macroporosity (Blanco-Canqui and Ruis 2020; Koudahe et al. 2022), which is less favourable for denitrification. These opposing effects might be why this study lacks a clear relationship between soil texture and N2O emissions. The duration of CA practices is known to affect the magnitude of N2O (Mei et al. 2018; Li et al. 2023a). Previous meta-analyses have shown that adopting CT practices, particularly in the short term, can significantly increase N2O emissions. However, this effect tends to diminish after the long-term implementation, as the soil structure stabilises (Six et al. 2004; van Kessel et al. 2013; Mei et al. 2018). In contrast, this analysis didn’t find any effect of the duration of CA practices on N2O emissions. This lack of effect might be due to the large variability in the dataset, driven by site-specific factors such as climate, soil properties, nitrogen management, and CC types (Basche et al. 2014; Mei et al. 2018; Shakoor et al. 2021; Li et al. 2023b). In addition, inconsistencies in measurement frequency and time period of N2O measurement, i.e. during the cover crops or cash crop phase (Basche et al. 2014; Li et al. 2023a), can further confound the results. Effect of conservation tillage combined with cover crops on carbon dioxide emissions Soil CO2 emissions are strongly influenced by C input and the soil’s physiochemical properties, which impact the decomposition of organic matter and, subsequently, CO2 emissions. In general, the adoption of CT reduced decomposition of organic matter as a result of improved soil aggregation, decreased soil aeration, and reduced contact of crop residues with soil (Six et al. 2000; Ussiri and Lal 2009; Abdalla et al. 2016). However, this doesn’t always result in decreased CO2 emissions (Huang et al. 2018; Shakoor et al. 2021). The impact of CT on CO2 emissions is highly dependent on sitespecific factors such as climate, soil properties, crop management, and tillage duration (Abdalla et al. 2016; Huang et al. 2018; Shakoor et al. 2021). Growing CCs can increase CO2 emissions on the one hand due to increased soil C inputs (Muhammad et al. 2019; Shackelford et al. 2019; Acharya et al. 2022). On the other hand, CCs can decrease CO2 emissions due to improvements in soil aggregation, a decrease in soil temperature, and higher retention of soil moisture (Sainju et al. 2008; Blanco-Canqui et al. 2015). Therefore, the net effect of CA, which combines both CT and CC, on CO2 emissions is the result of these contrasting mechanisms and interactions with site-specific factors. Higher CO2 emissions from legume CCs are primarily due to their low C/N ratio, resulting in faster and higher decomposition rates (Mancinelli et al. 2013; Rigon et al. 2018; Nilahyane et al. 2020). However, CO2 emissions are also strongly correlated with the CCs biomassgreater CC biomass generally results in higher CO2 emissions (Muhammad et al. 2019). Unfortunately, CC biomass data were not consistently reported across all studies, limiting the ability to directly compare the effect of CC types and their biomass productivity on CO2 emissions. Studies have shown that if the biomass production in legume crops is lower than in nonlegume crops, it can reduce CO2 emissions under NT management practices (Sainju et al. 2008; ZugastiLópez et al. 2024). The data showed higher CO2 emissions under CA than control from soil with SOC content greater than 20 g kg−1 . In soil with low SOC levels, carbon input can reduce CO2 emissions due to enhanced SOC stabilisation within soil aggregates, whereas in carbon-rich soils, added carbon may contribute to higher CO2 emissions as a significant portion of added carbon can be released into the atmosphere (Abdalla et al. 2016). However, this finding should be interpreted cautiously as only 22% of the observations were from soil with SOC content exceeding 20 g kg−1 . Under CT systems, higher CO2 emissions have been reported after longterm implementation (> 10 years), due to an increase in SOC contents under CT (Huang et al. 2018; Li et al. 2023b). Bai et al. (2019) have demonstrated increased SOC content with the longer-term implementation of CT and CCs, which may also contribute to increases in CO2 emissions. However, this trend was not evident in the present meta-analysis. While CA can increase the SOC content with the longer-term implementation (Bai et al. 2019), a substantial portion of this carbon may be stabilised within aggregates, making it less accessible for microbial decomposition (Kan et al. 2021).This study provided a comprehensive synthesis of CA (integrating CT with CCs) effects on soil GHG emissions compared to conventional tillage without CCs. No differences were observed between CA and control treatments regarding CH4 uptake and N2O emissions. CA can, however, increase CH4 and CO2 emissions under specific conditions such as rice cropping systems, legume CC, high SOC soils, and during early years for CA adoption. CA overall resulted in a 12% increase in CO2 emissions as compared to conventionally tilled soil without CCs. Despite this, the increase in CO2 emissions should not be a concern, as this increase can likely be offset by the CO2 uptake by CCs, contributing to net carbon gains. Previous studies have demonstrated that CA through the combined use of CC and no till can enhance the SOC sequestration compared to the control system due to the reduced disturbance and cover crop biomass inputs (Wolff et al. 2018; Huang et al. 2020; Tiecher et al. 2020; Gong et al. 2021b; Breil et al. 2023; Mezzari et al. 2023). A meta-analysis by Bai et al. (2019) further showed that the combination of CCs and conservation tillage increased the SOC content by 11%, significantly higher than using CCs (6%) or CT (5%) alone. Previous studies have shown that implementing CA can reduce overall GHG emissions, potentially transforming agricultural soil into a net GHG sink (Table 4).Limitations and future recommendations Among the notable limitations of this analysis are fewer studies on integrating CT practices and CCs and their effects on GHG fluxes. Though some of the studies reported GHG fluxes from such conservation practices (Bayer et al. 2016; Parkin et al. 2016; Mahama et al. 2020; Acharya et al. 2022), comparison with conventional tillage with no CCs was lacking. The effects of CA can vary depending on the types of CCs, soil, and management practices. In addition, climate also plays a vital role in affecting GHG fluxes under CA (Abdalla et al. 2016; Huang et al. 2018; Li et al. 2023a). However, most of the studies included in this analysis were conducted in humid climates. CA showed a tendency to have increased CH4 emissions under rice cropping systems. However, all rice-related data originated from Brazil, limiting the broader applicability of these findings. Therefore, studies conducted in diverse climatic conditions are needed to provide better insights into the effects of CA on GHG fluxes. Many studies lack data on cover crop biomass, which directly influences GHG emissions (Muhammad et al. 2019), limiting the Analysis of its role in greenhouse gas emissions. The difference in greenhouse gas emissions between CA and control can vary significantly depending on the time of measurements. For example, CO2 emissions are often higher immediately after plowing in control (Abdalla et al. 2014; Huang et al. 2018). However, in CA, CO2 emissions can be higher during the CC growth phase (Acharya et al. 2022). Also, N2O emissions differ during the CC growth or cash crop phase (Basche et al. 2014; Li et al. 2023a). If measurements are made throughout the year, rather than limited to specific periods, the effects of CC on N2O emissions can be negligible (Basche et al. 2014). However, not all studies have used annual measurements. Therefore, to better understand the impact of CA on greenhouse gas emissions, more field trials with annual measurements are necessary, as they provide a more accurate representation of greenhouse gas emissions from different management practices.Since the duration of CA implementation plays an important role in greenhouse gas fluxes, studies that monitor greenhouse gases over several years would be useful in assessing the effects of CA on greenhouse gas fluxes. Most studies have reported data on one or two greenhouse gases. To assess the net benefits of CA on greenhouse gas fluxes, it is necessary to assess its impact on CO2, CH4, and N2O. This study did not consider the trade-off between increased CO2 emissions and CO2 removals under CA. However, to accurately estimate the overall contribution of CA to greenhouse gas reduction, a comprehensive assessment of the net greenhouse gas balance, including all three greenhouse gases as well as CO2 removals, is necessary.