Inland water bodies are observed as major sources of the emissions of greenhouse gases (GHGs) including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). This study shows that these entities (e.g. wetlands, constructed wetlands, reservoirs, lakes, ponds, and rivers) have a major contribution in GHG flux. However, understanding of the carbon dynamics of these water bodies is not well described. It was noticed that the emissions of GHGs from inland water bodies is a result of heavy supply of organic matter into them. Approximately 2.2–3.7% of the Earth's non-glaciated land area and inland waters are having almost similar amounts of carbon emission as also observed in the case of both net terrestrial productivity and net oceanic uptake. Wetlands and lakes are among the most studied water bodies. However, efforts should be made to understand the emission dynamics from ponds and rivers as recent studies say these are also among the potent sources of GHG emissions in the atmosphere. This review paper aims to highlight and give an elaborate insight into the contribution of inland waters to the global carbon cycle along possible remediative measures.

  • Significance of running water/small ponds in GHG emissions as annual carbon budget is explained.

  • Emissions of carbon dioxide are highest from hydroelectric reservoirs.

  • Importance of GHG measurement facilities and sophisticated sampling techniques are presented.

  • Geographical conditions and social mindset are the main factors to determine GHG emissions.

The study of long periods of weather trends is known as climatology (Sarker 2022). After the industrial revolution in the mid-18th century, the concentrations of various greenhouse gases (GHGs) (that mainly include CO2, CH4, and N2O) began to increase in the atmosphere (Von Storch & Stehr 2006). These trace gases in turn started absorbing the infrared radiation of sunlight in the outer atmosphere, resulting in the warming of Earth. Activities such as deforestation, change in land use and land cover, rice cultivation, livestock, increased number of vehicles, and rapid growth in the human population are other driving forces behind it. Apart from the aforementioned anthropogenic activities, some natural sources such as volcanic eruptions and forest fires also emit GHGs (Hansen et al. 2007). Being very particular about the water bodies, earlier there was a misconception that only large reservoirs and natural lakes are the two main inland water bodies that contribute to GHGs flux like CO2, CH4, and N2O emissions (St Louis et al. 2000; Cole et al. 2007; Bastviken et al. 2011; Raymond et al. 2013; Deemer et al. 2016; Battisti 2023). GHG emissions from inland water bodies mostly result from the breakdown of organic matter that is being transported through the surface run-off and decomposed by the activities of various microorganisms. The emission occurs through diffusion as well as ebullition, which occurs at the air–water interface of the water body. However, in ebullition, CH4 is directly released from the sediment in the form of bubbles and is mixed into the atmosphere.

Previously, the estimation of the annual carbon budget from lentic ecosystems was confined to medium and large lakes. Globally, > 90% of ponds and lakes have a small area (∼0.01 km2), which was not included in the previous studies and this was the reason for major uncertainties in the global GHG budgets (Downing et al. 2006; Verpoorter et al. 2014; Raihan 2023). Globally, very small size ponds with an area of 0.0001–0.001 km2 may total 3,200 million in number and be spread over an area of 0.8 million km2 (Downing 2010). Since the mapping of these tiny ponds is very difficult, researchers didn't estimate their input to the annual GHG budget (Lehner & Döll 2004). The areal extents of inland waters are also dominated by ponds and small lakes that correct a long-time misapprehension that only large lakes are important (Downing 2010). Still, the source of CO2 from continental waters is not known, and further research is needed to disclose the mechanism that controls global CO2 evasion (Raymond et al. 2013). It was also observed that very small size ponds with a surface area of <0.001 km2 also contribute to GHG emissions (Verpoorter et al. 2014). Due to the shallow depth and other unique physical properties of small ponds, frequent mixing occurs, which results in the intense processing of carbon and other GHGs (Downing 2010; Holgerson & Raymond 2016). In its first-of-its-kind attempt, estimation of CO2 and CH4 emissions from 427 globally distributed ponds and lakes with an area ranging from 2.5 m2 to 674 km2 were carried out. In the study, the exchange rates of gases and the distribution of both water bodies have also been quantified (Holgerson & Raymond 2016).

Various attempts have been made by researchers to present a clear picture of GHG emissions from water bodies. Previously, the estimation study was confined only to North American and European countries. GHG estimation is still opaque due to very limited studies, especially from developing nations such as China and India. The aerial volumes of GHGs from Chinese water systems may be different from that of North America and Europe due to the widespread eutrophication in its lakes (Yang et al. 2011). CH4 and CO2 emission estimations from 85 worldwide allocated hydropower reservoirs were carried out, which account for about 20% of the global area of these systems. While doing this study, chemical status, location biome, morphometric features, and reservoir age were also taken into account. However, the estimation was quite low in comparison with previous studies due to more limited data (Barros et al. 2011). In China, the Three Gorges Reservoir (TGR) was studied for the estimation of CO2, CH4, and N2O kinetics. The quantities were measured monthly at different sites. The results showed that the region has lower CH4 flux when compared with most of the newly constructed reservoirs of temperate as well as tropical regions. However, the CO2 emissions from the TGR region were found to be lower than in tropical reservoirs, and higher than the temperate reservoirs (Zhao et al. 2013). The location of water bodies also has an impact on water temperature and the storage of organic matter that subsequently influences GHG emissions (Barros et al. 2011). However, this may not be true all the time. A study was carried out for a sampling of the major GHGs from 11 hydroelectric reservoirs in Switzerland. The results showed that all the reservoirs were net emitters of CO2 and CH4 as well and one of the reservoirs (Lake Wohlen) emitted CH4 at much higher rates, of which 98% was due to ebullition (Diem et al. 2008). The studies suggested that GHGs may be released from reservoirs through four different mechanisms. These include flux at the water–air transition zones of the rivers along with downstream areas of the dams, the flux of gas bubbles formed in the shallow zones, the flux of water degassing at the outlet of the hydropower plant, and the diffusive flux at the surface of the reservoir (Yang et al. 2014).

GHG emission rates depend on various factors. In the case of impoundments and lakes, they depend on the size of the lake and the prevailing trophic state. The traditional upscaling approaches give higher CO2 and N2O fluxes while they provide lower results of CH4 by almost half (DelSontro et al. 2018). In shallow ponds, ebullition is probably very important as a larger part of CH4 emissions occurs through this process during summer (Xiao et al. 2014). The rate of ebullition and temperature are directly correlated. The annual CH4 ebullition rate has increased by 51% with the increase of 4 °C in atmospheric temperatures; however, the rate of diffusion does not affect it (Aben et al. 2017). While estimating the GHG budget from water bodies, most of the attention is given to CO2 and CH4. We think that the increased level of eutrophication and N pollution may accelerate N2O release from these ecosystems and always be a net source of GHG. N2O is primarily released through microbial activities such as nitrification as well as denitrification (Smith 1997). Nitrification is a process that is aerobic in nature and needs oxygen; it thus does not have any major importance in wetland N2O emissions. Waterlogged soils have elevated nitrate availability as denitrification can take place when soil microorganisms use nitrate during respiration as an alternative electron acceptor. During this phenomenon, nitrate was reduced to its various allotropic forms such as NO, NO2, N2, or N2O. Further, molecular oxygen is also a governing factor for both processes, nitrification as well as denitrification. Hence, the water level in water bodies may play crucial roles in the release of the N2O fluxes (van Cleemput 1994). However, other facts such as the availability of organic matter should also be considered as a regulatory factor (Johansson 2002). The method of denitrification can eliminate the aquatic N at large. Therefore, it may also play substantial roles in minimizing the nutrient load (Howarth & Marino 2006; Seitzinger et al. 2006). But, a recent study suggests that small artificial farm reservoirs are the sinks of N2O, which contradicts the previous assumptions (Webb et al. 2019).

Although most of the studies pertaining to the estimation of GHGs from inland water bodies were focused mainly on wetlands, constructed wetlands (CWs), reservoirs, and lakes, they failed to look at the fact that other small water entities might be a potential source of the same. There are plentiful studies on the aforementioned water sources. However, this particular study is an attempt to review the GHG flux from ponds and rivers along with the previous ones, which was untouched until the first study of this kind was conducted by Holgerson (2015) when she estimated the GHG emission from six temporary ponds located within the Yale Myers Forest, Connecticut, USA. Since then, the scientific community has been trying to make the most out of the study of ponds and rivers. There is also a need to amplify this kind of study in third-world countries as they have been mostly conducted previously in North American and European countries. This is essential while preparing for a region-specific GHG mitigation plan.

There are various methods available for measuring aquatic GHG fluxes, namely, floating chamber, eddy covariance towers, thin boundary methods, funnels, and acoustic methods. Most of the frequently used techniques focus on enumerating the diffusive flux of GHGs across the water–air interface. A systematized methodology for the measurement of GHG flux from the reservoir surface has been developed, which is mainly based on consultation and is extensively acknowledged in the scientific fraternity (UNESCO/IHA 2010). Diffusive flux is estimated with the help of floating chambers by introducing them over the reservoir surface. These chambers are usually made up of polyethylene or Plexiglas. Right after placing the chamber, gas samples are drawn out with the help of a syringe across a butyl rubber stopper present at the top of the chamber (Bastviken et al. 2004). Ebullition of CH4 is usually measured with the help of a submerged funnel. It can also be measured with the help of floating chambers, an approach that also offers guidance on the spatial and temporal regularities of measurements to ensure trustworthy estimation of GHG flux. Kumar et al. (2019) illustrated several methods of measuring GHGs emitted from the water bodies such as the Greenhouse Gas Risk Assessment Tool, Combined Model, Linear Statistical Model, GHG Reservoir Tool, and Hydro Calculator Tool. For details, the researchers can refer to this review paper. Similarly, Duchemin et al. (1999) enlisted static chambers and boundary layer equation methods for the estimation of methane and carbon dioxide gases in water as well as air. These methods are even able to explain the rate of exchange of such gases from air to water interface during low speed of wind. Zhao et al. (2011a, 2011b) also reported some important methods to quantify the concentrations of GHGs in the air–water interface and water reservoirs in western United States.

Regarding sources of GHGs in water, they can be categorized into two sub-categories, namely lentic and lotic. Lentic ecosystems are natural systems that entail a structure of standing water, e.g. wetlands, CWs, reservoirs, lakes, and ponds. The lotic ecosystems have running water, e.g. rivers and streams.

Wetlands

Wetlands are the unique ecological units that have the property of both terrestrial as well as aquatic ecosystems. Wetlands are usually considered the kidneys of a landscape due to their capability to stock up, assimilate, and transform pollutants detached from the soil before they meet waterways. Globally, they are spread over a small part of the Earth's surface but have a strong influence on the climate. Wetlands possess anoxic soils. This is the result of microbial activities that deplete dissolved oxygen present in the water-saturated soil. The presence of anaerobic soil differentiates wetlands from terrestrial ecosystems such as grasslands and deciduous forests. Organic matter from terrestrial origin (∼15%) is getting mixed annually in the oceans/seas, which has a significant role in global C cycling (Hedges et al. 1997; Stern et al. 2007). The organic matter decomposition process in wetlands is a complex procedure because it involves both oxic and anoxic activities. Decomposition doesn't take place completely in anoxic conditions. Therefore, the absence of oxygen within wetlands is a key cause that decides the fate of the turnover of plant detritus. Consequently, the plant residues continued to grow and accumulate in the wetlands because of the decay of these residues (Gorham et al. 1998; Collins & Kuehl 2001; Holden 2005).

Wetland soils are a conducive environment for methanogenic (methane-producing) bacteria, where they can easily flourish. Besides water spread, methane emission from wetlands also needs certain favorable climatic/weather conditions such as humidity and optimum temperature. The depth of the water table (Moore et al. 2018), the quantity as well as quality of the degradable matter, and soil temperature (Christensen et al. 2003) have a significant influence on CH4 emissions from natural wetlands. Oxygen supply and temperature are other governing elements of methane oxidation in wetlands. Table 1 presents the methane emissions from wetlands.

Table 1

Methane emission flux in wetlands

Study siteBiomeWetland typeCH4 flux (mg C-CH4 m2 d1)Reference
Mexico Tropical Marsh (679.1 ± 177) –500–3,500 Marín-Muñiz et al. (2015)  
  Swamp (535.5 ± 132) –200–3,000  
Lucknow, India Subtropical Marsh 270–630 Singh et al. (2000)  
  Swamp 18–450  
Unnao, India Subtropical Swamps and Marshes 153.5 ± 23.2 Bansal et al. (2015)  
Agra, India Subtropical Freshwater 80.0 ± 11.8 Bansal et al. (2015)  
Mississippi, USA Subtropical Swamp 18–180 Koh et al. (2009)  
Africa Tropical Swamp 7.5–413 Tathy et al. (1992)  
Florida, USA Temperate Peatlands 616.32 Armentano & Menges (1986)  
Northern USA Temperate Peatlands 131.52 Armentano & Menges (1986)  
USA Forested swamps and marshes 95.76 Bartlett & Harriss (1993)  
North Wales, UK Temperate Bogs 0.15–6.39 Kang & Freeman (2002)  
  Swamps –1.3–75.4  
USA (Alaska) Tundra Wet meadow (679.1 ± 177) 15.6–426 Bartlett et al. (1992)  
Liminganlahti, Finland Boreal Marsh 206 Liikanen et al. (2009)  
Pantanal region, Brazil Tropical Swamp 142 ± 314 Marani & Alvalá (2007)  
Manitoba, Canada Boreal Peatlands 22–239 Bellisario et al. (1999)  
Study siteBiomeWetland typeCH4 flux (mg C-CH4 m2 d1)Reference
Mexico Tropical Marsh (679.1 ± 177) –500–3,500 Marín-Muñiz et al. (2015)  
  Swamp (535.5 ± 132) –200–3,000  
Lucknow, India Subtropical Marsh 270–630 Singh et al. (2000)  
  Swamp 18–450  
Unnao, India Subtropical Swamps and Marshes 153.5 ± 23.2 Bansal et al. (2015)  
Agra, India Subtropical Freshwater 80.0 ± 11.8 Bansal et al. (2015)  
Mississippi, USA Subtropical Swamp 18–180 Koh et al. (2009)  
Africa Tropical Swamp 7.5–413 Tathy et al. (1992)  
Florida, USA Temperate Peatlands 616.32 Armentano & Menges (1986)  
Northern USA Temperate Peatlands 131.52 Armentano & Menges (1986)  
USA Forested swamps and marshes 95.76 Bartlett & Harriss (1993)  
North Wales, UK Temperate Bogs 0.15–6.39 Kang & Freeman (2002)  
  Swamps –1.3–75.4  
USA (Alaska) Tundra Wet meadow (679.1 ± 177) 15.6–426 Bartlett et al. (1992)  
Liminganlahti, Finland Boreal Marsh 206 Liikanen et al. (2009)  
Pantanal region, Brazil Tropical Swamp 142 ± 314 Marani & Alvalá (2007)  
Manitoba, Canada Boreal Peatlands 22–239 Bellisario et al. (1999)  

Averages are given in parentheses and data in ranges.

Wetlands are spread all over the world and can be found even in Antarctica (Loisel et al. 2017). A study reveals that wetlands present in tropical regions contribute about 60% of the CH4 emission, whereas 35% of the emissions are contributed by the wetlands situated in the northern latitudes. The reasons for the high emissions by tropical wetlands are extreme temperatures that prevail there throughout the year. Continuous flooding could also be a possible cause of increased CH4 emission from wetlands present in the tropical region. Since the preindustrial era, CH4 concentration in the atmosphere has increased by almost 150% in 2018, from approximately 0.72 to 1.8 ppmv (parts per million by volume) (Tuckett 2018). There are great uncertainties in the global annual methane emission. As per the WETCHIMP model, it is 190 Tg per year (Melton et al. 2013); however, a more recent estimate suggests that it is 138–165 Tg per year (Rosentreter et al. 2021). Except for CH4, some other trace gases like CO2, N2O, and H2S are also emitted from wetlands in small but varying quantities. Several researchers reported that with increasing temperature, CO2 emission increases and is higher in drained as compared to flooded peatlands (Price & Waddington 2000; Waddington et al. 2001).

Constructed wetlands

Water treatment has become an integral part of society because of the water contamination level across the globe (Kaur et al. 2023; Panwar et al. 2023). CWs are the green technology that have been used to treat wastewater for the last several decades. These are man-made or artificial structures that work on the principle of natural wetlands. The capability of CWs in accumulating and sequestering organic matter received less consideration until the carbon storage potential of natural ecosystems became widely acknowledged (Anderson & Mitsch 2006). These are engineered structures that treat wastewater naturally and use the appropriate plant species, soil, and microbial diversity. The plant species that have been employed in CWs are also an important factor that may alter the emission of methane (Lai et al. 2011; Mander et al. 2014). This is because they can release CH4 directly through stems, and this process can also oxygenate root zones/sediments. Phragmites australis is amomg the common plants used at global scale in CWs (McCormick & Mathews 2010; Uddin et al. 2017). However, other species like Zizania latifolia, Juncus effuses, Phalaris arundinacea, and Typha latifolia are also used. Based on the necessities, we may further categorize CWs into various types.

CWs have been frequently used to treat diverse types of wastewater, namely, domestic, agricultural, and so on (Wu et al. 2015). Being a cost-effective technology, the number of CWs has increased exponentially in the last few years. To set up a CW, conversion of a large area is needed, which likely results in a drastic increase in the CH4 emission (Johansson et al. 2004). Therefore, the dramatic increase in CW areas created environmental deterioration owing to the possible increase in emissions of methane despite their potential to control water pollutants (Xue et al. 1999; Niu et al. 2015). Table 2 presents methane emission flux from the CWs.

Table 2

Methane emission flux from constructed wetlands

Study siteBiomeWetland typeCH4 flux (mg C-CH4 m2 d1)Reference
Ohio, USA Temperate Marsh ∼84 Altor & Mitsch (2006)  
Ohio, USA Temperate Marsh 0–450 Altor & Mitsch (2008)  
Hamilton, New Zealand Temperate Pilot-scale constructed wetlands 48–482 Tanner et al. (1997)  
Eastern China Tropical Free water surface wetland 5,220 (almost 250 times higher than natural wetlands) Tai et al. (2002)  
Kalimantan, Indonesia Tropical Marsh 234–504 Hadi et al. (2005)  
Ohio, USA Temperate Marsh 0.48–492 Sha et al. (2011)  
Southern Estonia Temperate Vertical subsurface flow planted soil filter 393.6 Mander et al. (2005)  
Estonia, Finland, Norway, and Poland – Subsurface, free surface, overland, and groundwater flow wetlands –32–38,000 Søvik et al. (2006)  
Southern Sweden Boreal Bog with a mixed forest of small trees –377 to 1,387 Ström et al. (2007)  
South Bohemia (Czech Republic) Temperate Planted horizontal subsurface flow constructed wetlands 0–2,232 Picek et al. (2007)  
Linköping, Sweden Boreal Planted horizontal subsurface flow constructed wetlands –375 to 1,739 Johansson et al. (2004)  
Study siteBiomeWetland typeCH4 flux (mg C-CH4 m2 d1)Reference
Ohio, USA Temperate Marsh ∼84 Altor & Mitsch (2006)  
Ohio, USA Temperate Marsh 0–450 Altor & Mitsch (2008)  
Hamilton, New Zealand Temperate Pilot-scale constructed wetlands 48–482 Tanner et al. (1997)  
Eastern China Tropical Free water surface wetland 5,220 (almost 250 times higher than natural wetlands) Tai et al. (2002)  
Kalimantan, Indonesia Tropical Marsh 234–504 Hadi et al. (2005)  
Ohio, USA Temperate Marsh 0.48–492 Sha et al. (2011)  
Southern Estonia Temperate Vertical subsurface flow planted soil filter 393.6 Mander et al. (2005)  
Estonia, Finland, Norway, and Poland – Subsurface, free surface, overland, and groundwater flow wetlands –32–38,000 Søvik et al. (2006)  
Southern Sweden Boreal Bog with a mixed forest of small trees –377 to 1,387 Ström et al. (2007)  
South Bohemia (Czech Republic) Temperate Planted horizontal subsurface flow constructed wetlands 0–2,232 Picek et al. (2007)  
Linköping, Sweden Boreal Planted horizontal subsurface flow constructed wetlands –375 to 1,739 Johansson et al. (2004)  

Recently, plentiful studies have been conducted on GHG emissions from CWs. In the last century, CWs have had negligible areas worldwide when compared with agricultural land or other natural wetlands. However, with an increase in developmental activities and a decrease in the area of natural wetlands in various countries, authorities are now are opting for this sustainable wastewater treatment technology. There is almost no use of fossil fuel or electricity in the operation of CWs, thus environmental impacts are minimized. The gas dynamics of CWs are also significantly influenced by various meteorological conditions, especially moisture and temperature (MacDonald et al. 1998). Temperature directly affects the rate of photosynthesis, which is the primary source of C and energy in the ecosystem, and the activity of microorganisms that produce GHGs in the CWs. CWs may act as both source or sink for C in some seasons; however, there may be a great difference in the N2O (Huttunen et al. 2002) and CH4 fluxes (Nykánen et al. 1995). The other influencing factors that are affecting GHG flux, oxidation, emission, and entrapment should be extensively studied to get a clear picture of the dynamics of gases emitted from CWs. Also, the flux of GHGs from CWs may be affected by some other parameters such as water chemistry (e.g. NO3 or dissolved SO4−2), microbial activity, and the amount and type of substrates.

Similar to natural wetlands, the major GHGs, namely CH4, CO2, and N2O, can be released from CWs. However, a lot of studies reported on the emissions of CO2 fluxes from the CWs (Mander et al. 2005; Liikanen et al. 2006). CWs emit between 2 and 10 times more GHGs when compared with natural wetlands (Maltais-Landry et al. 2009) and this might be due to heavy plant species application for water purification. Further observation also recorded that methane emission could be a prominent GHG from the non-functional (without plant species) CW systems. However, methane emission can be decreased in the presence of plant species, but it may add carbon dioxide (Maltais-Landry et al. 2009). CH4 emissions from planted CWs are almost similar to the productive natural wetlands (Kayranli et al. 2010).

Hydroelectric reservoirs

Hydroelectric reservoirs are man-made water systems that symbolize a significant component of the Earth's territory. These are an important part of aquatic nutrient cycling and also pose many effects on the environment. First, in the early 1990s, reservoirs were discovered as a potential source of GHGs (Rudd et al. 1993; Kelly et al. 1994). On a global scale, ∼1 million dams have been constructed and are in operation (Lehner et al. 2011), and of the total, only 17% of the potential reservoirs have been used so far (Barros et al. 2011). Besides, the present area covered by these entities corresponds to about 25% of the area that is used for artificial water systems (energy generation, irrigation, water supply, and so on) (St Louis et al. 2000). Reservoirs provide a variety of services (e.g. flood control, navigation, hydropower, and water supply) that are essential for the flourishing of the human population but also significantly alter nutrient, ecosystem dynamics and fluxes, and water in the river system. We often think that the energy that we are receiving from reservoirs is green or carbon-neutral. Recent researches show that hydroelectric dams are potential emitters of trace gases into the atmosphere. Estimation of GHGs from water bodies is a comparatively nascent research and the maximum number of studies has been carried out over the last two decades. Up to about a decade ago, the majority of the GHG emissions data came from the reservoirs operational in the tropical climatic zone mostly in French Guiana and Brazil (the former primarily associated with only one reservoir, the Petit Saut). Table 3 presents the methane emission flux from the hydroelectric reservoirs.

Table 3

GHG emission flux from hydroelectric reservoirs

Study siteCH4 emissions (mg C-CH4 m2 d1)CO2 emissions (mg C-CO2 m2 d1)N2O emissions (mg N-N2O m2 d1)Reference
(Global overview) 120 330 0.30 Deemer et al. (2016)  
Eastmain-1, Québec, Canada 0.77 2,426 – Demarty et al. (2009)  
Grand Rapids, Manitoba, Canada 0.58 624 – Demarty et al. (2009)  
Serra da Mesa, Brazil 0.530–396.96 –1,738.33–11,166.61 – Marcelino et al. (2015)  
Três Marias, Brazil 0.720–2,578.03 –3,037.80–11,516.64 – Marcelino et al. (2015)  
6 reservoirs in Southeastern United States 6–187 994–2,760 – Bevelhimer et al. (2016)  
Wilcza Wola, Southeast Poland 32–451 3,893–4,161 – Gruca-Rokosz et al. (2010)  
Lokka, Finland 22.9 1,070 – Huttunen et al. (2002)  
Porttipahta, Finland 3.5 1,754 –0.26 to 0.173 Huttunen et al. (2002)  
Lake Lungern, Switzerland 0.13 242 0.05 Diem et al. (2008)  
Xiangxi River, China 5.88 1,836 – Zhao et al. (2011a, 2011b
Pengxi River, China 23.5 3,542 0.744 Jiang et al. (2012)  
Baltic coastal lakes, Poland 21.7 12,700 0.74 Woszczyk & Schubert (2021)  
Study siteCH4 emissions (mg C-CH4 m2 d1)CO2 emissions (mg C-CO2 m2 d1)N2O emissions (mg N-N2O m2 d1)Reference
(Global overview) 120 330 0.30 Deemer et al. (2016)  
Eastmain-1, Québec, Canada 0.77 2,426 – Demarty et al. (2009)  
Grand Rapids, Manitoba, Canada 0.58 624 – Demarty et al. (2009)  
Serra da Mesa, Brazil 0.530–396.96 –1,738.33–11,166.61 – Marcelino et al. (2015)  
Três Marias, Brazil 0.720–2,578.03 –3,037.80–11,516.64 – Marcelino et al. (2015)  
6 reservoirs in Southeastern United States 6–187 994–2,760 – Bevelhimer et al. (2016)  
Wilcza Wola, Southeast Poland 32–451 3,893–4,161 – Gruca-Rokosz et al. (2010)  
Lokka, Finland 22.9 1,070 – Huttunen et al. (2002)  
Porttipahta, Finland 3.5 1,754 –0.26 to 0.173 Huttunen et al. (2002)  
Lake Lungern, Switzerland 0.13 242 0.05 Diem et al. (2008)  
Xiangxi River, China 5.88 1,836 – Zhao et al. (2011a, 2011b
Pengxi River, China 23.5 3,542 0.744 Jiang et al. (2012)  
Baltic coastal lakes, Poland 21.7 12,700 0.74 Woszczyk & Schubert (2021)  

However, in the last 10 years, the extent of studies has become evenly distributed and spread over the temperate and boreal climatic zones as well. There is a good scope of working on the GHG emissions from water reservoirs in Asian as well as African countries due to the relatively less work that has been reported (World Bank, 2017).

The emission of GHGs from artificial water bodies is completely different to that from natural water bodies such as ponds and lakes. To construct a reservoir, the inundation of large terrestrial and aquatic ecosystems is done. This results in the decomposition of inundated organic matters by various microorganisms, and CO2 and CH4 are emitted as an end product (Galy-Lacaux et al. 1997). Both the GHGs are transported to the atmosphere by the processes of diffusion (Huttunen et al. 2003; Guérin & Abril 2007), ebullition (Bergier et al. 2011; Jędrysek et al. 2014), advection (Boon 2000; Chen et al. 2009), and degassing (Fearnside 2003). Further, emissions of carbon dioxide from the dams are highest in comparison with methane and nitrous oxide. The GHGs emission from hydroelectric reservoirs corresponds to about 16% of total emissions from man-made sources and only 4% of the entire (natural and anthropogenic) C released by the water bodies (Barros et al. 2011). Thus, it seems that hydroelectric dams are not a major contributor to the global carbon budget. At present, abundant data are available on the emissions of CO2 and CH4 from the hydroelectric reservoirs of the world and they require further extensive research. Currently, for obtaining the annual emission of a given GHG, we simply multiply the average flux rate by all the areas covered by the specific water body (Tranvik et al. 2009; Bastviken et al. 2011). However, the emissions from hydroelectric reservoirs differ distinctly among the systems constructed in the different climatic zones and also from one measuring station to another within the same reservoir (Gruca-Rokosz 2015). Studies should also be carried out to exactly clarify which aspects are favorable in amplifying GHG emissions to the surroundings and to what extent.

These reservoirs also emit N2O, which have been considered in numerous studies. The results show that like CH4, the creation and emission of N2O differ significantly (Deemer et al. 2016; UNESCO/IHA 2017). Even though they have high global warming potential (GWP), when expressed in terms of CO2 equivalent, it is recorded that ∼4% N2O is part of the global reservoir emissions (Deemer et al. 2016). The main route for N2O transportation to the atmosphere is diffusion, while ebullition has the least contribution because of the high solubility of N2O (Guérin et al. 2008).

Lakes

Lakes are natural water bodies confined to a basin and surrounded by land. These aquatic systems are not part of the ocean and are recognized as inland or surface waters along with rivers and reservoirs. It is reported that the shallower water entities emit more trace gases (CO2, CH4, and N2O) when compared with the deeper ones, and lakes are not an exception. This happens because of more hydrostatic pressure differences along with more gas solubility (Li et al. 2014; Li et al. 2016). Until now, surface waters were ignored while estimating the annual carbon budget. But a reassessment of the area occupied by lakes (Downing et al. 2006), small ponds, and reservoirs revealed that these water bodies cover more than 3% of the globe, which is almost double the previous approximations.

Lakes play an important role in the global landscape and atmospheric carbon (C) processes. Because of an increasing trend in CH4 concentrations in the surroundings, CH4 emission estimation from lakes has been increasingly frequently carried out in the last few years (Rasilo et al. 2015; Deemer et al. 2016). The rationale behind these studies is to measure CH4 emissions and relate them to lake morphology and biogeochemistry (Marani & Alvalá 2007; Laurion et al. 2010; Koné et al. 2010).

The GHG emissions from lakes need extensive study as there are many uncertainties in the results. Most of the studies are carried out for boreal and temperate regions (Bastviken et al. 2011). The emission estimation from tropical lakes is lagging. In the tropics, research is concentrated mostly on China. As per the earlier estimates, approximately 71.6 TgC of CH4 and 1943 TgC of CO2 is contributed to the environment by lakes every year (Tranvik et al. 2009; Bastviken et al. 2011; Aufdenkampe et al. 2011). However, a recent annual CH4 estimate suggests that the mean lake emission is 150.9 Tg, and the median emission is 55.8 Tg (Rosentreter et al. 2021). Out of the total CH4 generation by water bodies, about 70% alone is added by natural lakes. This contribution is very uneven when we look at the small geographical area occupied by lakes (Bastviken et al. 2011). CH4 from lakes also reaches the air either through diffusion, ebullition, emission, or through subsurface foliage, and storage flux. The bubble emission is believed to be the most common pathway of CH4 emission from inland waters (Bastviken et al. 2011), especially in lakes, which are less than 20 m in depth.

Various factors can influence the CH4 emission from lakes. In one of the studies, temperature and rainfall have been identified as important regulators (Walter et al. 2001). The area of the lake, organic carbon, and the depth of water may be the other regulators of CH4 emissions in higher latitudes (Bastviken et al. 2004). Besides the above regulators, a recent study suggests that nutrient enrichment driven by total phosphorus, i.e. eutrophication of the lentic systems, may be a significant regulator of CH4 emissions. Due to the phenomenon of climate change and the rapid increase in the population, the productivity of aquatic systems will increase in the next century, which will result in increased CH4 emissions (30–90%). These increased emissions are almost equivalent to 18–33% of the yearly CO2 emission resulting from the burning of fossil fuels (Beaulieu et al. 2019). Besides CH4, very few studies have been conducted on the N2O contribution by lakes globally (DelSontro et al. 2018; Lauerwald et al. 2019).

Studies suggest that there are higher emission rates in climatic zones having higher mean air temperatures (Sanches et al. 2019). This means GHG emissions are positively correlated with the temperature. This may be because temperature plays a role as a driving factor for methanogenesis (Bartlett et al. 1987; Bastviken et al. 2010). It is also established that precipitation considerably influences the diffusion along with the storage CH4 flux (Sanches et al. 2019) because of the effect of rainfall during lake mixing.

The different lake size classes are also significant drivers of GHG emission rates. Small size lakes may play greater roles in the global emissions of carbon dioxide because of their large cumulative capacity and the negative correlation between lake size and CO2 emission flux. The areal CH4 emissions had similar emission rates among most of the classes; however, areal N2O emission rates increased with the lake size (DelSontro et al. 2018).

Ponds

Among the inland waters, ponds are the smallest unit compared to the others. Ponds may be both natural and artificial. Ponds located amidst populations receive various kinds of organic matter and food leftovers besides the pesticides and fertilizers from nearby crop fields through surface run-off. These particulate and dissolved organic matters settle down at the bottom and make these water bodies eutrophic. Until now, generally the studies on GHG emissions in stagnant water bodies have focused only on medium- to large-sized lakes and small ponds have been excluded from all the global biogeochemical cycles because they are very difficult to map. Table 4 presents the methane emissions from the ponds.

Table 4

GHG emission fluxes from small ponds and aquaculture ponds

Study siteCH4 emissions (mg C-CH4 m2 d1)CO2 emissions (mg C-CO2 m2 d1)N2O emissions (mg N-N2O m2 d1)Reference
Urban ponds of Uppsala, Sweden 30.3 752 – Peacock et al. (2019)  
22 small artificial ponds in Queensland, Australia 1–5,425 – – Grinham et al. (2018)  
Study siteCH4 emissions (μmol L–1)CO2 emissions (μmol L–1)N2O emissions (μmol L–1)Reference
Connecticut, USA 33.4 (21.0–58.9) 352.3 (273.3–553.4) – Holgerson (2015)  
Sweden; Wisconsin and Minnesota, USA 1.3 (0.3–2.3) – – Bastviken et al. (2004)  
Finland 1.5 (0.7–2.6) 171.0 (81.0–313.0) – Kankaala et al. (2013)  
Study siteCH4 emissions (mmol m−2 h−1)CO2 emissions (mmol m−2 h−1)N2O emissions (μmol m−2 h−1)Reference
Eutrophic pond of Nanjing, Jiangsu, China 2.81 ± 0.19 (summer) – – Liu et al. (2017)  
0.63 ± 0.10 (Autumn) – – 
0 (Winter) – – 
0.62 ± 0.14 (Spring) – – 
Aquaculture pond of Southeast China 0.66 ± 0.31 (DPa0.75 ± 0.12 (DPa19.54 ± 2.08 (DPaYang et al. (2018)  
0.07 ± 0.06 (UDPb–0.49 ± 0.09 (UDPb0.01 ± 0.04 (UDPb
Study siteCH4 emissions (mg C-CH4 m2 d1)CO2 emissions (mg C-CO2 m2 d1)N2O emissions (mg N-N2O m2 d1)Reference
Urban ponds of Uppsala, Sweden 30.3 752 – Peacock et al. (2019)  
22 small artificial ponds in Queensland, Australia 1–5,425 – – Grinham et al. (2018)  
Study siteCH4 emissions (μmol L–1)CO2 emissions (μmol L–1)N2O emissions (μmol L–1)Reference
Connecticut, USA 33.4 (21.0–58.9) 352.3 (273.3–553.4) – Holgerson (2015)  
Sweden; Wisconsin and Minnesota, USA 1.3 (0.3–2.3) – – Bastviken et al. (2004)  
Finland 1.5 (0.7–2.6) 171.0 (81.0–313.0) – Kankaala et al. (2013)  
Study siteCH4 emissions (mmol m−2 h−1)CO2 emissions (mmol m−2 h−1)N2O emissions (μmol m−2 h−1)Reference
Eutrophic pond of Nanjing, Jiangsu, China 2.81 ± 0.19 (summer) – – Liu et al. (2017)  
0.63 ± 0.10 (Autumn) – – 
0 (Winter) – – 
0.62 ± 0.14 (Spring) – – 
Aquaculture pond of Southeast China 0.66 ± 0.31 (DPa0.75 ± 0.12 (DPa19.54 ± 2.08 (DPaYang et al. (2018)  
0.07 ± 0.06 (UDPb–0.49 ± 0.09 (UDPb0.01 ± 0.04 (UDPb

aDrained pond.

bUndrained pond.

Apart from their contribution in the aerial distribution of GHGs, small ponds are also hotspots of C cycling. The quantities of CO2 and CH4 were maximum in ponds of lesser area and inversely proportional to the size. This shows a negative correlation between GHG emissions and surface area because of the variation in the physical characteristics of the ponds and also their size gradient (Holgerson & Raymond 2016). Small ponds receive higher earthly carbon compared to their water retaining capacity, which provides the substrate for bacterial activities. This, in turn, increases CO2 emissions (Sobek et al. 2005). The variability of gas concentration in small ponds is more when compared with that in the larger lakes. This variation is probably due to the various influencing factors such as depth, canopy cover, and dissolved organic carbon (DOC; Laurion et al. 2010; Holgerson 2015). Interestingly, the CO2-to-CH4 concentration ratio tended to increase with the increase in the lake size. With regard to CO2 equivalent, the CH4 concentration was only 10 times smaller than the CO2 in small ponds, but 150 times smaller in the case of larger lakes. The CO2-to-CH4 ratio is perhaps influenced by the surface area of the pond and its associated lake depth (Holgerson & Raymond 2016). CH4 is formed in anaerobic deposits and waters and is oxidized in the column of water. The probability of CH4 oxidation is higher in deeper lakes as the residence time is longer when compared with shallow waters (Bastviken et al. 2008). Peacock et al. (2019) conducted a general survey of 40 artificial ponds in Uppsala (Sweden) to investigate the spatial variation of CO2 and CH4 fluxes. No effect of size was observed on the dissolved GHGs, which is contradictory to the study of Holgerson & Raymond (2016), who established that small area natural ponds can have maximum concentrations. Additionally, they also found that there are no dissimilarities in GHGs between pond function/category (water regulation or ornamental), which is also in contrast with the study conducted by Grinham et al. (2018). Despite the better apprehension of the magnitude and the causal agents of GHG release from domestic water bodies, water level fluctuation and evaporation status are inadequately addressed. A study carried out in small temporary ponds in Menorca, Spain, implied that temporary lakes and ponds release CO2 throughout the year even when they are dry. The dry areas surprisingly release a bigger amount of carbon into the atmosphere (Obrador et al. 2018). New research indicates that temperate ponds may have the burial potential of trace gases, which depends on the vegetation there. The sequestration rate in these ponds was 20–30 times higher than the other habitats such as grasslands or woodlands, and higher than those of other natural wetlands (Taylor et al. 2019). In another study carried out for the typical lowland temperate ponds, the combined estimation of sediment carbon stock over the top 10 cm was found to be 4.18 ± 2.12 kg C m−2 (Gilbert & Kittel 2021). The nutrient sequestration capability of 14 stormwater wet detention ponds from the seaside region of South Carolina (USA) was also studied, which suggests that they have a long-term storage potential of C, N, and P that would otherwise have been transported to coastal receiving waters (Schroer et al. 2019). Due to the continuous inflow of nutrients and other organic matter, waste stabilization ponds (WSPs) may be a potential source of GHGs. They are very effective, natural, and low-cost solutions for treating municipal wastewater (Mara 2004). A bathymetric study and two sampling drives were conducted in Ucubamba WSP in Cuenca, Ecuador, to examine the spatiotemporal variations in GHGs released from WSPs with effects of sludge distribution emphasized. The results signified that the spatial variation of GHG releases was highly correlated with sludge dispersal. A thick layer of sludge was deposited followed by a rigorous aeration in facultative ponds, which had released considerable amounts of CO2 and CH4 emissions of 21.3% and 78.7%, respectively, out of the total emissions from the pond (Ho et al. 2021).

The availability of high-resolution satellite imagery cannot even appropriately classify the ponds as having a size less than 0.002 km2 (Verpoorter et al. 2014). Therefore, there is a need for an active study agenda on small and very small ponds to take them to the scientific community and also to know the input of these minor ecosystems to the biosphere. Initial researches also show that they are the most active and important environments on Earth.

Rivers

Among lotic ecosystems, rivers and streams also contribute to the annual GHG budget, but the emissions are quantified inadequately. Direct GHGs released from terrestrial habitats due to increased human interventions have received much attention. However, GHG discharges from the rivers and streams have been less talked about and are consequently less constrained, although research has continually pointed out that these ecosystems play a crucial role in the global GHG budget (Cole et al. 2007; Borges et al. 2015). They are among the prime paths for the delivery of particulate inorganic carbon (PIC), particulate organic carbon (POC), dissolved inorganic carbon (DIC), and DOC from inland waters and terrestrial landscapes to coastal areas (Gaillardet et al. 1999; Cole et al. 2007). The surface run-off received by rivers is rich in carbon (C) as well as nitrogen (N). It makes them supersaturated with GHGs and hence net emitters of GHGs (Butman & Raymond 2011; Raymond et al. 2013; Crawford et al. 2014). Rivers and streams also work as vessels/containers for various biogeochemical alterations within complex carbon compounds present there. Such types of processes involve the discharge and utilization of C-gases and also recognize the atmospheric exchanges of CH4 and CO2 (Mayorga et al. 2005; Guérin et al. 2006, 2007; Cole et al. 2007). Similarly, the excess N in streams undergoes various N cycling processes such as nitrification and denitrification, which are responsible for the release of N2O into the atmosphere.

Rivers have been invaluable assets of society that play a role in the global biogeochemical cycles, but they were mostly ignored, as they were conceptualized as unreactive ‘pipelines’ carrying water from terrestrial to the oceanic environment (Leopold et al. 1964; Cole et al. 2007; Denman et al. 2007; Battin et al. 2009). The channel bottom of a stream or river, known as the streambed, has been recognized as a ‘hotspot’ for C turnover (McClain et al. 2003; Lautz & Fanelli 2008; Trimmer et al. 2012; Krause et al. 2013). It is characterized by the high metabolic activities of aquatic organisms and the spiraling of nutrients (Jones & Holmes 1996; Boulton et al. 1998; Seitzinger et al. 2006; Krause et al. 2009, 2011). A rise in riverine temperatures because of the changing climate can cause a noticeable increase in CO2 and CH4 emissions from the streambeds (Comer-Warner et al. 2019).

The riverine systems surrounding the urban landscapes may also be a pertinent source of GHGs because of being filled with treated as well as untreated quantities of sewage. The studies conducted on urban rivers are mostly confined to the spatial and temporal variations of GHG fluxes, damming, and the effect of sewage discharge (Jin et al. 2018; Wang et al. 2020; Li et al. 2020). Sometimes, the areal emissions of GHG from the rivers can be 10 times more than reported from less-urbanized rivers (Zhang et al. 2021).

Based on the aforementioned discussion, it can be inferred that additions of organic matters from diffused sources may elevate the levels of organic matters in water bodies, and that will increase the emissions of GHGs from such water reservoirs. Global warming and climate change are the main consequences of the GHG emissions, and climate change may increase the frequency of the hydrological disasters and drought conditions. Further, it may also promote the substantial extinctions of the biodiversity from the Earth, alteration in weather phenomenon, reductions in glacier ice volume, changes in sea levels, and so forth (Kumar et al. 2021). Hence, extensive research is required to resolve this issue so that societal problems due to climatic uncertanties can be minimized. Overall, the objectives of the present paper are depicted in Figure 1 as follows:
Figure 1

Overall methodology and outcome of the present paper.

Figure 1

Overall methodology and outcome of the present paper.

Close modal

Kroeger et al. (2017) reported on restoring the tides for reducing methane emissions from the wetlands. In their study, the authors have established that significant reductions in methane as well as carbon dioxide can be achieved through the restoration of saline tides in coastal areas. Such types of studies are entirely different from that on the carbon sequestration of forest biomass or wetland biomass, for example. Further, Limpert et al. (2020) observed that change in the hydrological conditions of a wetland will have negative impacts on its carbon sequestration capacity. Therefore, the water table of a freshwater reservoir can naturally store the carbon from the soil. Moreover, microbial communities can be helpful in recycling of carbon during rehabilitation of the wetland and this has been a little-explored area. Zou et al. (2022) also observed similar trends in which they found miscellaneous changes in the fluxes of GHGs such as carbon dioxide, methane, and nitrous oxide in the manipulated hydrological conditions of the inland water reservoirs. However, during the flood-like situations, the emissions of GHGs could be higher because of decomposition of the plant and animal bodies. Gordon et al. (2010) recognized three main strategies for the management of water in agriculture so that nutrient load additions to nearby freshwater reservoirs can be controlled. Conservation of agroaquatic ecosystems can be helpful in reducing methane emissions from water as nutrient enrichment can lead to eutrophication followed by methane emissions (Beaulieu et al. 2019). According to Williamson et al. (2009), lakes and water reservoirs are a part of the global complexities of geographies, which can be regulators of climate change because of their physicochemical roles in climate change. Moreover, biological communities (especially microbes) and bottom sediments can determine the level of emissions of GHGs from inland surface water bodies. The bottom sediments of the water bodies are also helpful in recycling aquatic carbon since ancient eras.

To achieve sustainability in climate change management, further disappearance of the ponds, lakes, streams, and rivers must be prevented. Moreover, the formulation and implementation of effective policies should be ensured strictly integrating wetland conservation and their benefits for the climate change management at the regional, national, as well as international levels (Moomaw et al. 2018). Further, Butler et al. (2017) added that a significant transformation is required from traditional to modern approaches in the strategies for dealing with climate change, because some well-established problems can only be solved using technical innovations in traditional approaches (Gleick 2000; Pahl-Wostl et al. 2011). Hence, to solve modern challenges raised by climate change, urban water management should be adopted to ensure water sustainability through change in approach (Brown & Farrelly 2009; Pahl-Wostl et al. 2011).

Such types of statements are also supported by global agencies including the World Health Organization (WHO), the Intergovernmental Panel on Climate Change (IPCC), and the United Nations. For example, in the 2030 Vision of WHO, it has been well placed that resilience in water supply along with sanitation should be given priority (WHO & DFID 2009). Similarly, IPCC also emphasized the water resilience three decades ago (IPCC 2001). Further, per the United Nations, sustainable development can only be achieved through upgraded quality of water conservation and management. However, it is a very critical issue and should be ascribed huge and continuous investments for water conservation practices (UN-Water 2010). But, Marlow et al. (2013) found that this is very difficult to achieve due to the negligence of water management at every level including individual, institutional, policy makers, and local administration. Thus, it seems that all the stakeholders should come forward to join hands for genuine efforts against climate change through managing water reservoirs at the regional, national, and international levels.

Recently, Hammer et al. (2022) reported some strategies to manage carbon emissions expected from aquaculture. There are projects underway for reductions in carbon emissions in UK and Scotland and their objectives are to achieve zero carbon emissions by the years 2045 and 2050, respectively. Further, per Deemer et al. (2016), getting measurements of GHG emissions from diverse sources is a major problem for the researchers in most regions of the world (e.g. Africa, Australia). Additionally, types of GHG emissions also need to be identified precisely because methane and nitrous oxides have higher global warming potentials (GWP) than carbon dioxide (Ciais et al. 2014; Myhre et al. 2014; López et al. 2023). However, emissions of carbon dioxide are in greater amounts than that of other GHGs. Furthermore, local geagraphical conditions, temperature, structure and functions of ecosystems, social mindset, and so forth are also among the main factors to determine the emissions of GHGs and their effects on Earth (Deemer et al. 2016; Huang et al. 2023). Kucukvar et al. (2021) also found some environmental benefits after adopting the process of circular economy thorough social sustainability. Apart from anthropogenic activities some natural sources such as the death and decay of aquatic organisms may also contribute to raising the level of GHGs in water resources (Ciais et al. 2014). Therefore, extensive research should be carried out in upcoming years on the development of sustainable and inclusive policies after adequate brainstorming among all the stakeholders to reduce the additions of organic materials in water bodies (Kumar et al. 2021). Deemer et al. (2016) highlighted the research requirements for the improvement of strategies to deal with the emissions of GHGs especially in the water reservoirs. Many studies have promoted the importance of environmental sustainability. For example, McKee & Chatzisymeon (2022) highlighted the water treatment processes under the application of ultra-violet lamps. Nwanekezie et al. (2022) also supported that some policy-related evaluations should be carried out in the management of sources of renewable energy as they have done in Canada. It means that sustainability has become a concern of every field to reduce the level of environmental deterioration.

Implications of the present study

There have been many studies on the role of rejuvenation of water reservoirs such as lakes (Ramachandra et al. 2020) and rivers (Sarker 2021; Sarkar et al. 2023) in dealing with climatic variations. Gao et al. (2022) analyzed some fragile locations where dams were made on the Mekong River Basin, which flows through China, Laos, Myanmar, Thailand, etc. and has become a topic of concern for environmentalists. This study indicated that the presence of many dams on this river along with other human activities have created huge ecological imbalances across the geographical areas. The study could help in identifying the sensitive activities that can be prevented to minimize ecological disturbances. Similar, recent studies have been reported by Sarker (2023) and Singhal et al. (2024) in which the researchers identified significant data on locations related in topography as well as hydrology, so that climatic variations can be avoided. Such types of information can be useful for the management of floods in plain areas. Thus, these studies can be significantly helpful in the identification of the risks, monitoring, climate change resilience, and so on for future extensive works in climate change studies.

GHG emissions on the global scale have continued to rise at a steady pace, following over one and half centuries of industrial growth. Being specific to the water bodies, CO2, CH4, and N2O are the major GHGs emitted from them. Wetlands, CWs, reservoirs, lakes, ponds, and rivers are the major contributors to GHG emissions. Wetlands are the most studied water entity and the fraction of CH4 is the greatest among all the GHGs emitted. Apart from estimating GHG flux from wetlands, the role of microorganisms and various plant species in carbon budget and emitting CH4 is still opaque. Thus, more research is needed to get a clear picture of the impacts of the respective flora under changeable nutrient regimes and loading rates. However, very few studies consider CO2 emission from CWs, and if not managed properly, they could become a potential source of GHGs. Per the available estimates of GHG fluxes from natural and CWs, emission flux from CWs is higher compared to natural wetlands, and the latter has more carbon sequestration potential than the former. The percentage of CO2 is highest in the case of emissions from hydroelectric reservoirs followed by CH4 and N2O. In addition, it emerges that eutrophication, which results from high nutrient load, leads to amplified radiative forcing by these reservoirs owing to increased CH4 emissions. This relationship between reservoir GHG emissions and eutrophication should be studied in detail and could be the very first step in reducing reservoir GHGs. Rivers and streams have been less talked about and are consequently less considered while preparing the annual carbon budget. But, there is a lack of homogeneity in GHGs’ estimation worldwide because of the limitations in measurement facilities and sophisticated sampling techniques. While estimating GHGs for a longer period, regular sampling and standardized analysis procedures are needed to know the emission variability.

In the recent Conference of Parties (COP) 26 at Glasgow, 105 countries pledged to reduce their CH4 emissions by 2030 by 30% from the 2020 levels. Because of the reactivated interest by all countries to reduce GHG emissions through various means, this review assesses the role and contributions of the water bodies in contributing to this basket of GHGs. It may be helpful in devising strategies for regular monitoring of water bodies to mitigate GHG emissions. Rejuvenation efforts for water bodies can also contribute to achieving this goal.

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.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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Author notes

These authors contributed equally.

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