Atmospheric Methane Concentrations Research Articles

Drivers of Methane Flux Differ Between Lakes and Reservoirs, Complicating Global Upscaling Efforts

AbstractMethane is an important greenhouse gas with growing atmospheric concentrations. Freshwater lakes and reservoirs contribute substantially to atmospheric methane concentrations, but the magnitude of this contribution is poorly constrained. Uncertainty stems partially from whether the sites currently sampled represent the global population as well as incomplete knowledge of which environmental variables predict methane flux. Thus, determining the main drivers of methane flux across diverse waterbody types will inform more accurate upscaling approaches. Here we use a new database of total, diffusive, and ebullitive areal methane emissions from 313 lakes and reservoirs (ranging in surface area from 6 m2 to 5,400 km2) to identify the best predictors of methane emission. We found that the best predictors of methane emission differed by waterbody type (lakes vs. reservoirs), and that ecosystem morphometric variables (e.g., surface area and maximum depth) were more important predictors in lakes whereas metrics of autochthonous production (e.g., chlorophyll a) were more important in reservoirs. We also found that productivity strongly predicted methane ebullition, whereas ecosystem morphometry and waterbody type were more important predictors of diffusive methane flux. Finally, we identify several knowledge gaps that limit upscaling efforts. First, we need more methane emission measurements in small reservoirs, large lakes, and both natural and artificial ponds. Additionally, more accurate upscaling efforts require improved global information about waterbody surface area, waterbody type (lake vs. reservoir), ice phenology, and the distribution of productivity‐related predictor variables such as total phosphorus, DOC, and chlorophyll a.

Nitrogen addition decreases methane uptake caused by methanotroph and methanogen imbalances in a Moso bamboo forest

Forest soils play an important role in controlling global warming by reducing atmospheric methane (CH4) concentrations. However, little attention has been paid to how nitrogen (N) deposition may alter microorganism communities that are related to the CH4 cycle or CH4 oxidation in subtropical forest soils. We investigated the effects of N addition (0, 30, 60, or 90 kg N ha−1 yr−1) on soil CH4 flux and methanotroph and methanogen abundance, diversity, and community structure in a Moso bamboo (Phyllostachys edulis) forest in subtropical China. N addition significantly increased methanogen abundance but reduced both methanotroph and methanogen diversity. Methanotroph and methanogen community structures under the N deposition treatments were significantly different from those of the control. In N deposition treatments, the relative abundance of Methanoculleus was significantly lower than that in the control. Soil pH was the key factor regulating the changes in methanotroph and methanogen diversity and community structure. The CH4 emission rate increased with N addition and was negatively correlated with both methanotroph and methanogen diversity but positively correlated with methanogen abundance. Overall, our results suggested that N deposition can suppress CH4 uptake by altering methanotroph and methanogen abundance, diversity, and community structure in subtropical Moso bamboo forest soils.

Monitoring Australian Monsoon variability over the past four glacial cycles

We analyse changes in terrigenous sedimentation along the northwestern Australian margin to monitor the latitudinal migration of the Intertropical Convergence Zone (ITCZ) and the shifting boundaries of climatic belts during the last four glacial cycles. We integrate high-resolution X-ray fluorescence (XRF) scanning elemental records from Core SO257–18548 and International Ocean Discovery Program Site U1482, situated southwest of the Scott Plateau at the southern edge of the present-day monsoonal belt, and from Core SO257–18571, located within the dust-cyclone belt offshore Northwest Cape south of the Exmouth Plateau. The chronology of these sediment successions is based on 14C dating over the last glacial termination and on correlation of the benthic oxygen isotope record to the LR04 stack (Lisiecki and Raymo, 200) and Antarctic ice core chronology. Our XRF derived records of riverine terrigenous run-off and aeolian dust input reveal rapid intensification of monsoonal precipitation and reduction of atmospheric dust during the Younger Dryas and early Holocene as well as during the terminal phase of other major deglaciations. Short-lived monsoonal maxima in the early Holocene (~10 ka), MIS 5e (~130 ka), MIS 7 (~200, ~220 and ~ 240 ka), and MIS 9 (~280, ~305 and ~ 330 ka) coincide with maxima in atmospheric carbon dioxide and methane concentrations. Monsoon intensification occurs during maxima in Southern Hemisphere spring (September) insolation, when intense heat low pressure cells over the Pilbara region trigger the southward shift of the ITCZ. Within the dust-cyclone belt, riverine sediment discharge was restricted to intervals of high atmospheric CO2 concentrations, when sea surface temperature thresholds promoted cyclone formation in the tropical Indian Ocean. Northwestern Australia remained dry and arid during MIS 5a-d, when the ITCZ was locked in a more northerly position and temperature thresholds were not attained.

Using Water Table Depths Inferred From Testate Amoebae to Estimate Holocene Methane Emissions From the Hudson Bay Lowlands, Canada

AbstractWetlands are the largest natural source of methane, yet the roles of source region and paleoclimate in explaining the variability in Holocene atmospheric methane concentrations remain poorly constrained. The Hudson Bay Lowlands (HBL) is one of the world's largest continuous peatland regions and a significant source of methane. We present here, using a novel proxy‐based approach, Holocene methane fluxes for the HBL. Paleo‐methane fluxes were quantified based on water table depth (WTD), inferred from testate amoeba assemblages in nine peat records. WTDs were reconstructed using a North American transfer function and were used to estimate paleo‐methane flux through a linear regression model of contemporary growing season methane fluxes and WTDs from 88 sites across the region. Following HBL peatland initiation in the Middle Holocene, total methane flux is closely related to the increasing area of land emerging from below sea level, controlled by rapid rates of glacial isostatic adjustment. In the Late Holocene, rates of uplift slowed, but methane fluxes remained high due to lower evapotranspiration in a wetter and cooler climate. We estimate that 4.8 ± 1.6 Pg C has been released from HBL peatlands to the atmosphere as CH4 over the last 8,000 years, with an average annual methane emission of 1.1 Tg CH4 yr−1 in the Late Holocene. The values estimated here are broadly consistent with those calculated from other independent methods, on modern and Holocene timescales, demonstrating that testate amoeba records provide an effective approach for scaling local processes to regional paleo‐methane emissions.

Methane-Oxidizing Communities in Lichen-Dominated Forested Tundra Are Composed Exclusively of High-Affinity USCα Methanotrophs.

Upland soils of tundra function as a constant sink for atmospheric CH4 but the identity of methane oxidizers in these soils remains poorly understood. Methane uptake rates of −0.4 to −0.6 mg CH4-C m−2 day−1 were determined by the static chamber method in a mildly acidic upland soil of the lichen-dominated forested tundra, North Siberia, Russia. The maximal CH4 oxidation activity was localized in an organic surface soil layer underlying the lichen cover. Molecular identification of methanotrophic bacteria based on retrieval of the pmoA gene revealed Upland Soil Cluster Alpha (USCα) as the only detectable methanotroph group. Quantification of these pmoA gene fragments by means of specific qPCR assay detected ~107 pmoA gene copies g−1 dry soil. The pmoA diversity was represented by seven closely related phylotypes; the most abundant phylotype displayed 97.5% identity to pmoA of Candidatus Methyloaffinis lahnbergensis. Further analysis of prokaryote diversity in this soil did not reveal 16S rRNA gene fragments from well-studied methanotrophs of the order Methylococcales and the family Methylocystaceae. The largest group of reads (~4% of all bacterial 16S rRNA gene fragments) that could potentially belong to methanotrophs was classified as uncultivated Beijerinckiaceae bacteria. These reads displayed 96–100 and 95–98% sequence similarity to 16S rRNA gene of Candidatus Methyloaffinis lahnbergensis and “Methylocapsa gorgona” MG08, respectively, and were represented by eight species-level operational taxonomic units (OTUs), two of which were highly abundant. These identification results characterize subarctic upland soils, which are exposed to atmospheric methane concentrations only, as a unique habitat colonized mostly by USCα methanotrophs.

Geological methane emissions and wildfire risk in the degraded permafrost area of the Xiao Xing\u2019an Mountains, China

With global warming, the carbon pool in the degradation zone of permafrost around the Arctic will gradually be disturbed and may enter the atmosphere in the form of released methane gas, becoming an important factor of environmental change in permafrost areas. We selected the northwestern section of the Xiao Xing'an Mountains in China as the study area, located in the degradation zone on the southern margin of the permafrost region in Eurasia, and set up multiple study monitoring areas equipped with methane concentration sensors, air temperature sensors, pore water pressure sensors and soil temperature sensors for long-term monitoring of data changes using the high-density electrical method, ground penetrating radar and on-site drilling to survey the distribution of frozen soil and geological conditions in the study area, combined with remote sensing images of Sentinel-2 L1C and unmanned aerial vehicle photographs and three-dimensional image reconstruction, analysis of fire activities and related geological environmental factors. The results show that since 2004, the permafrost thickness of the marsh wetland in the study area has gradually reduced and the degradation rate obviously accelerated; the organic matter and methane hydrate (metastable methane hydrate and stable methane hydrate) stored in the permafrost under the marsh wetland are gradually entering the atmosphere in the form of methane gas. Methane emissions show seasonal changes, and the annual methane emissions can be divided into three main stages, including a high-concentration short-term emission stage (March to May), a higher-concentration long-term stable emission stage (June to August) and a higher-concentration short-term emission stage (September to November); there is a certain correlation between the change in atmospheric methane concentration and the change in atmospheric pressure and pore water pressure. From March to May every year (high-concentration short-term emission stage), with snow melting, the air humidity reaches an annual low value, and the surface methane concentration reaches an annual high value. The high concentration of methane gas entering the surface in this stage is expected to increase the risk of wildfire in the permafrost degradation area in two ways (increasing the regional air temperature and self-combustion), which may be an important factor that leads to a seasonal wildfire frequency difference in the permafrost zone of Northeast China and Southeast Siberia, with the peak in spring and autumn and the monthly maximum in spring. The increase in the frequency of wildfires is projected to further generate positive feedback on climate change by affecting soil microorganisms and soil structure. Southeastern Siberia and northeastern China, which are on the southern boundary of the permafrost region of Eurasia, need to be targeted to establish fire warning and management mechanisms to effectively reduce the risk of wildfires.

Thawing permafrost and methane emission in Siberia: Synthesis of observations, reanalysis, and predictive modeling.

Permafrost has been warming in the last decade at rates up to 0.39°C 10year-1, raising public concerns about the local and global impacts, such as methane emission. We used satellite data on atmospheric methane concentrations to retrieve information about methane emission in permafrost and non-permafrost environments in Siberia with different biogeochemical conditions in river valleys, thermokarst lakes, wetlands, and lowlands. We evaluated the statistical links with air temperature, precipitation, depth of seasonal thawing, and freezing and developed a statistical model. We demonstrated that by the mid-21st century methane emission in Siberian permafrost regions will increase by less than 20 Tg year-1, which is at the lower end of other estimates. Such changes will lead to less than 0.02°C global temperature rise. These findings do not support the "methane bomb" concept. They demonstrate that the feedback between thawing Siberian wetlands and the global climate has been significantly overestimated.

Genomic and Physiological Properties of a Facultative Methane-Oxidizing Bacterial Strain of Methylocystis sp. from a Wetland.

Methane-oxidizing bacteria are crucial players in controlling methane emissions. This study aimed to isolate and characterize a novel wetland methanotroph to reveal its role in the wetland environment based on genomic information. Based on phylogenomic analysis, the isolated strain, designated as B8, is a novel species in the genus Methylocystis. Strain B8 grew in a temperature range of 15 °C to 37 °C (optimum 30–35 °C) and a pH range of 6.5 to 10 (optimum 8.5–9). Methane, methanol, and acetate were used as carbon sources. Hydrogen was produced under oxygen-limited conditions. The assembled genome comprised of 3.39 Mbp and 59.9 mol% G + C content. The genome contained two types of particulate methane monooxygenases (pMMO) for low-affinity methane oxidation (pMMO1) and high-affinity methane oxidation (pMMO2). It was revealed that strain B8 might survive atmospheric methane concentration. Furthermore, the genome had various genes for hydrogenase, nitrogen fixation, polyhydroxybutyrate synthesis, and heavy metal resistance. This metabolic versatility of strain B8 might enable its survival in wetland environments.

Infectious Diseases, Livestock, and Climate: A Vicious Cycle?

Ruminant livestock are a significant contributor to global methane emissions. Infectious diseases have the potential to exacerbate these contributions by elevating methane outputs associated with animal production. With the increasing spread of many infectious diseases, the emergence of a vicious climate–livestock–disease cycle is a looming threat.

Using the BFAST Algorithm and Multitemporal AIRS Data to Investigate Variation of Atmospheric Methane Concentration over Zoige Wetland of China

The monitoring of wetland methane (CH4) emission is essential in the context of global CH4 emission and climate change. The remotely sensed multitemporal Atmospheric Infrared Sounder (AIRS) CH4 data and the Breaks for Additive Season and Trend (BFAST) algorithm were used to detect atmospheric CH4 dynamics in the Zoige wetland, China between 2002 and 2018. The overall atmospheric CH4 concentration increased steadily with a rate of 5.7 ± 0.3 ppb/year. After decomposing the time-series of CH4 data using the BFAST algorithm, we found no anomalies in the seasonal and error components. The trend component increased with time, and a total of seven breaks were detected within four cells. Six were well-explained by the air temperature anomalies primarily, but one break was not. The effect of parameter h on decomposition outcomes was studied because it could influence the number of breaks in the trend component. As h increased, the number of breaks decreased. The interplays of the observations of interest, break numbers, and statistical significance should determine the h value.

Multichannel fiber-optic amplifier at the wavelength of 1653 nm for lidar remote sensing of atmospheric methane concentrations

We have developed and tested a multichannel fiber-optic Raman-effect amplifier with peak output power of the order of 10 W operating at the wavelength of 1653 nm. This amplifier is intended for use in a remote-sensing lidar for atmospheric methane and consists of three power amplifiers, each with an output power of more than 3 W. The output from these amplifiers was combined in a fiber-optic multiplexer and then fed to the lidar transmitter collimator. Our modeling of a single power amplifier indicated that the Raman conversion efficiency is improved when thin-core optical fibers are used; a thin-core optical fiber can be used to decrease both the pump power and the length of the optical fiber. We describe the seed light source spectrum and the multichannel amplifier output spectrum. The output power can be increased beyond 20 W by multiplexing in another four power amplifiers, which would provide sufficient lidar transmitter power to measure gas concentrations from a spacecraft in low-Earth orbit.

NUMERICAL MODEL ON METHANE EMISSIONS FROM AGRICULTURE SECTOR

Atmospheric methane, emitted from agriculture sector such as production of rice paddies and farming of livestock populations, is one of the important factors responsible for increasing the average atmospheric temperature leading to global warming. It is, therefore, crucial to comprehend the dynamics of methane emission and its effect on global warming. In this paper, a nonlinear mathematical model is proposed and analyzed to study the increase of average atmospheric temperature (or average global warming temperature) caused by emission of methane due to various processes involved in the production of rice paddies and farming of livestock populations simultaneously. In the modeling process, six variables are considered, namely, the cumulative biomass density of rice paddies, the cumulative density of livestock populations, the cumulative density of methane formed by various processes involved in the production of rice paddies, the cumulative density of methane formed by various processes involved in the farming of livestock populations, the atmospheric concentration of methane and the average atmospheric temperature. It is assumed that both the cumulative biomass densities of rice paddies and livestock populations follow logistic models with their respective growth rates and carrying capacities. The growth rate of concentration of methane in the atmosphere is assumed to be directly proportional to the cumulative densities of various processes involved in the production of rice paddies as well as in the farming of livestock populations. This growth rate also increases with a constant rate from various natural sources such as wetlands, etc. The growth rate of average global warming temperature is assumed to be proportional to the increased level of methane concentration in the atmosphere from its equilibrium value. It is also assumed that this temperature decreases with a rate proportional to its enhanced level from its equilibrium level caused by various natural factors such as rain fall, snowfall, etc. The proposed model is analyzed using the stability theory of differential equations and numerical simulation. The analysis shows that as the emission of methane from various processes involved in the production of rice paddies and farming of livestock populations increase, the average global warming temperature increases considerably from its equilibrium level. The numerical simulation of the model confirms the analytical results.

Exploring new methods of estimating deposition using atmospheric concentration measurements: A modeling case study of ammonia downwind of a feedlot

Atmospheric ammonia is an important compound in the atmosphere because of its role in aerosol formation and its importance to the global nitrogen cycle. Livestock feeding operations are a major source of ammonia emissions to the atmosphere, and ammonia concentrations near these large feedlots can be many orders of magnitude higher than background. These feedlots can impact regional ecology and air quality, but uncertainty in the ammonia surface fluxes adjacent to these major sources can make the extent of the feedlot's impact difficult to determine. Ammonia surface fluxes are generally challenging to quantify with direct flux measurement techniques due to the challenges in conducting ammonia measurements with sufficient temporal resolution. Feedlots housing ruminant livestock such as cattle are also sources of methane. Because methane does not undergo appreciable dry deposition and is chemically inert on relevant spatial scales, we can use it as a tracer to constrain the downwind dilution of feedlot ammonia emissions. The ratio of atmospheric ammonia to methane has been shown to decrease with increasing distance downwind of a feedlot due to deposition and aerosol partitioning of gas-phase ammonia. In atmospheric conditions where inorganic aerosol formation is slow, the ratio of ammonia to methane can be used to estimate of the fraction of ammonia that has undergone deposition downwind of the feedlot. We use a Large-Eddy Simulation turbulent dispersion model to generate realistic concentration fields of atmospheric ammonia and methane concentrations downwind of a feedlot, and we sample the model output to produce synthetic measurements of these tracers. We then use the synthetic observations of background-corrected the ammonia:methane concentration ratio to derive the ammonia deposition rate. In this study, we explore conducting measurements from two platforms: sensors deployed on a small unmanned aerial vehicle and on a surface-based mobile observation platform. We find that the surface-based platform overestimates of ammonia deposition by a factor of 1.5 due to sampling near the surface where ammonia concentrations are depleted. However, use of the aerial platform allows more accurate estimation of the deposition fraction (relative error <0.09).

Research on the Anthropogenic Impact on Climate Change

The article is a presentation of the results of studies and calculations of climate parameters associated with anthropogenic thermal pollution of the environment. They indicate that the increase of atmospheric concentrations of carbon dioxide, methane, and nitrous oxide cannot be a cause of climate warming. The article provides information about the working principle of the natural mechanism of automatic maintenance of temperature climate parameters. The authors show that all of the gases molar mass of differs from the molar mass of nitrogen are the working bodies of the procedures for moving heat from the stratosphere to space. Water vapor is the only greenhouse gas, and to deal effectively with water vapor in the atmosphere is impossible. However, the work contains an assessment of the feasibility of some ways to assist the natural mechanism of removing heat to space. Some methods and tools of world energy development are suggested in the article. These methods could lead to a substantial reduction of anthropogenic thermal pollution of the planet.

Growth and rapid succession of methanotrophs effectively limit methane release during lake overturn

Lakes and reservoirs contribute substantially to atmospheric concentrations of the potent greenhouse gas methane. Lake sediments produce large amounts of methane, which accumulate in the oxygen-depleted bottom waters of stratified lakes. Climate change and eutrophication may increase the number of lakes with methane storage in the future. Whether stored methane escapes to the atmosphere during annual lake overturn is a matter of controversy and depends critically on the response of the methanotroph assemblage. Here we show, by combining 16S rRNA gene and pmoA mRNA amplicon sequencing, qPCR, CARD-FISH and potential methane-oxidation rate measurements, that the methanotroph assemblage in a mixing lake underwent both a substantial bloom and ecological succession. As a result, methane oxidation kept pace with the methane supplied from methane-rich bottom water and most methane was oxidized. This aspect of freshwater methanotroph ecology represents an effective mechanism limiting methane transfer from lakes to the atmosphere.

Fingerprint of rice paddies in spatial\u2013temporal dynamics of atmospheric methane concentration in monsoon Asia

Agriculture (e.g., rice paddies) has been considered one of the main emission sources responsible for the sudden rise of atmospheric methane concentration (XCH4) since 2007, but remains debated. Here we use satellite-based rice paddy and XCH4 data to investigate the spatial–temporal relationships between rice paddy area, rice plant growth, and XCH4 in monsoon Asia, which accounts for ~87% of the global rice area. We find strong spatial consistencies between rice paddy area and XCH4 and seasonal consistencies between rice plant growth and XCH4. Our results also show a decreasing trend in rice paddy area in monsoon Asia since 2007, which suggests that the change in rice paddy area could not be one of the major drivers for the renewed XCH4 growth, thus other sources and sinks should be further investigated. Our findings highlight the importance of satellite-based paddy rice datasets in understanding the spatial–temporal dynamics of XCH4 in monsoon Asia.

Machine learning based analysis for relation between global temperature and concentrations of greenhouse gases

Climate change is an important topic that needs to be addressed soon. As the consequences of climate change are extremely serious, such as ocean acidification and extreme weather conditions, it is paramount to learn what are the causes behind the phenomenon to battle it effectively. In this work, authors modeled the relationship between global temperatures and atmospheric concentrations of nitrous oxide, methane, and carbon dioxide on a dataset of 65 years using linear regression, decision tree regression, random forest regression, and Artificial Neural Network. Authors have analyzed the performance of these machine learning algorithms on the data and established that ANN outperforms the other algorithms on the basis of mean square error. Further authors have calculated the importance of each feature (carbon dioxide, methane, and nitrous oxide) using the best performing model-ANN and proved that the contribution of carbon dioxide in the increase of global temperatures is the maximum of the given greenhouse gases.

Effects of increased precipitation combined with nitrogen addition and increased temperature on methane fluxes in alpine meadows of the Tibetan Plateau

Climate change and anthropogenic activities have resulted in increased atmospheric methane (CH4) concentration. Increased nitrogen deposition and precipitation accompanies climate warming and can change soil carbon and nitrogen dynamics and microbial processes and alter CH4 fluxes. To quantify the sink of the vast alpine meadows of the Tibetan Plateau and to examine how precipitation addition (P), warming (W), and nitrogen addition (N) affect CH4 fluxes in alpine meadows, we conducted continuous 3-growing season experiments in an alpine meadow using the static chamber and gas chromatograph method. Soil CH4 samples were collected during the early, peak, and late stages of the growing season from 2015 to 2017. Our results suggested that neither P, W, nor N had an interaction effect on soil CH4 uptake. P significantly increased and decreased the copies number of particulate methane monooxygenase alpha subunit (pmoA) and methyl-coenzyme M reductase alpha subunit (mcrA), respectively. However, P significantly decreased CH4 uptake, particularly under the combined treatment of P and N. Compared with the control, CH4 uptake decreased under P, N, PW, and PN by 50.64%, 6.24%, 39.37%, and 75.06%, respectively, whereas under W and WN CH4 uptake increased by 16.19% and 7.56%, respectively. Soil CH4 uptake was positively correlated with soil temperature and pmoA and negatively correlated with soil moisture and NH4+-N content. CH4 uptake was significantly affected by the sampling period. CH4 uptake was significantly lower rates during peak growing season compared with those during the early and late stages of the growing season. Our results suggest that, (1) CH4 fluxes of alpine grassland ecosystems are more sensitive to P than W or N, and (2) precipitation controls CH4 flux response to increasing nitrogen deposition in alpine meadows on the Tibetan Plateau. Therefore, future research should focus on the response and feedback of CH4 uptake to changes in precipitation.

Operation of the boreal peatland methane cycle across the past 16 k.y.

Abstract The role of boreal wetlands in driving variations in atmospheric methane (CH4) concentrations across the last deglaciation (20–10 ka) and the Holocene is debated. Most studies infer the sources of atmospheric methane via ice-core records of methane concentration and its light stable isotopic composition. However, direct evidence for variations in the methane cycle from the wetlands themselves is relatively limited. Here, we used a suite of biomarker proxies to reconstruct the methane cycle in the Chinese Hani peat across the past 16 k.y. We found two periods of enhanced methanogenesis, at ca. 15–11 ka and ca. 10–6 ka, whereas weak methanogenesis characterized the late Holocene. These periods of enhanced methanogenesis relate to periods of high/increasing temperatures, supporting a temperature control on the wetland methane cycle. We found no biomarker evidence for intense methanotrophy throughout the past 16 k.y., and, contrary to previous studies, we found no clear control of hydrology on the peatland methane cycle. Although the onset of methanogenesis at Hani at ca. 15 ka coincided with a negative shift in methane δ13C in the ice cores, there is no consistent correlation between changes in the reconstructed methane cycle of the boreal Hani peat and atmospheric CH4 concentrations.

Anthropogenic methane plume detection from point sources in the Paris megacity area and characterization of their δ13C signature

Mitigating anthropogenic methane emissions is one of the available tools for reaching the near term objectives of the Paris Agreement. Characterizing the isotopic signature of the methane plumes emitted by these sources is needed to improve the quantification of methane sources at the regional scale. Urbanized and industrialized regions such as the Paris megacity are key places to better characterize anthropogenic methane sources. In this study, we present the results of the first mobile surveys in the Paris region, assessing methane point sources from 10 landfills (which in the regional inventory are the main emission sector of methane in the region), 5 gas storage sites (supplying Paris) and 1 waste water treatment (WWT) facility (Europe's largest, second worldwide). Local atmospheric methane concentration (or mixing ratio) enhancements in the source plumes were quantified and their δ13C in CH4 (further noted δ13CH4) signature characterized. Among the 10 landfills sampled, at 6 of them we detected atmospheric methane local enhancements ranging from 0.8 to 8.5 parts per million (ppm) with δ13CH4 signatures between −63.7 ± 0.3 permils (‰) to −58.2 ± 0.3‰. Among the 5 gas storage sites surveyed, we could observe that 3 of them were leaking methane with local methane concentration enhancements ranging from 0.8 to 8.1 ppm and δ13CH4 signatures spanning from −43.4 ± 0.5‰ to −33.8 ± 0.4‰. Dutch gas with a δ13CH4 signature of −33.8 ± 0.4‰ (typical of thermogenic gas) was also likely identified. The WWT site emitted local methane enhancements up to 4.0 ppm. For this site, two δ13CH4 signatures were determined as −51.9 ± 0.2‰ and −55.3 ± 0.1‰, typical of a biogenic origin. About forty methane plumes were also detected in the Paris city, leading to local concentration enhancements whose origin was in two cases interpreted as natural gas leaks thanks to their isotopic composition. However, such enhancements were much less common than in cities of North America. More isotopic surveys are needed to discriminate whether such urban methane enhancements are outcoming from gas line leaks and sewer network emanations. Furthermore, our results lead us to the conclusion that the regional emissions inventory could underestimate methane emissions from the WWT sector. Further campaigns are needed to assess the variability and seasonality of the sources and of their isotopic signature, and to estimate their emissions using methods independent of the inventory.