Search Results (15)

The increase of the CO₂ content in the atmosphere caused by anthropogenic emissions from the territories of large cities (~70%) is the critical factor in determining the accuracy of emission estimations. Advanced experiment-based methods of anthropogenic CO₂ emission estimation are based on the solution of an inverse problem, using accurate measurements of CO₂ content and numerical models of atmospheric transport and chemistry. The accuracy of such models decreases the errors of the emission estimations. The aim of the current study is to adapt numerical weather prediction and atmospheric chemistry model WRF-Chem and validate its capability to simulate atmospheric CO₂ for the territories of the two large coastal cities of the Gulf of Finland—St. Petersburg (Russia) and Helsinki (Finland). The research has demonstrated that the WRF-Chem model is able to simulate annual variation, as well as the mean seasonal and diurnal variations of the near-surface CO₂ mixing ratio, in Helsinki, at a high spatial resolution (2 km). Correlation between the modelled and measured CO₂ mixing ratio is relatively high, at ~0.73, with a mean difference and its standard deviation of 0.15 ± 0.04 and 1.7%, respectively. The differences between the WRF-Chem data and the measurements might be caused by errors in the modelling of atmospheric transport and in a priori CO₂ emissions and biogenic fluxes. The WRF-Chem model simulates well the column-averaged CO₂ mixing ratio (XCO₂) in St. Petersburg (January 2019–March 2020), with a correlation of ~0.95 relative to ground-based spectroscopic measurements by the IR–Fourier spectrometer Bruker EM27/SUN. The error of the XCO₂ modelling constitutes ~0.3%, and most likely is related to inaccuracies in chemical boundary conditions and a priori anthropogenic CO₂ emissions. The XCO₂ time series in St. Petersburg by the WRF-Chem model fits well with global CAMS reanalysis and CarbonTracker-modelled data (the differences are less than ~1%). However, due to much higher spatial resolution (2 vs. over 100 km), the WRF-Chem data are in the best agreement with the ground-based remote measurements of XCO₂. According to the study, the modelling errors of XCO₂ in St. Petersburg during the whole simulated period are sufficiently minimal to fit the requirement of “Error ≤ 0.2%” in 60% of cases. This requirement should be satisfied to evaluate properly the anthropogenic CO₂ emissions of St. Petersburg on a city-scale. Full article

Time-series samples intercepted via three synchronized moored sediment traps, deployed at 1000 m, 2150 m, and 3200 m in the northern South China Sea (NSCS) during June 2009–May 2010, were analyzed to quantify the bioactive trace metal fluxes in sinking particles and investigate their different source contributions. Iron (Fe) primarily originated from lithogenic sources. Manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), and zinc (Zn) exhibited various degrees of enrichment over their continental crustal ratios. Since the sources of bioactive trace metals in sinking particles can be divided into lithogenic, biogenic, and excess fractions, mass conservation calculations were used to quantify the contribution of each source. The results showed that Fe, Mn, and Co had extremely low biogenic proportions (0.1–3.3%), while Ni, Cu, and Zn had higher proportions (2.7–17.3%), with the biogenic fraction decreasing with the depth. Moreover, excess sources accounted for a significant proportion of Mn (68–75%), Co (34–54%), Ni (60–62%), Cu (59–74%), and Zn (56–65%) in sinking particles at the three sampling depths. The excess fractions of Mn, Co, and Cu in sinking particles can be affected by authigenic particles. This is supported by their similar scavenging-type behavior, as observed via the increase in their fluxes and enrichment patterns with the increasing depth. Furthermore, the excess fractions of Ni, Cu, and Zn may have significant contributions from anthropogenic sources. The variability of Fe in sinking particles was mainly controlled via lithogenic matter. Notably, organic matter and opal were found to be pivotal carriers in the export of excess bioactive trace metals (Mn, Co, Ni, and Cu) via the water column, accompanied with the elevated ballast effect of lithogenic matter with the depth. However, the transportation of excess Zn was more complicated due to the intricate processes involved in Zn dynamics. These findings contribute to our understanding of the sources and transport mechanisms of bioactive trace metals in the marine environment. Full article

Monoterpenes are volatile organic compounds that play important roles in atmospheric chemistry, plant physiology, communication, and defense. This review compiles the monoterpene emission flux data reported for different regions and plant species and highlights the role of abiotic environmental factors in controlling the emissions of biogenic monoterpenes and their emission fluxes for terrestrial plant species (including seasonal variations). Previous studies have demonstrated the role and importance of ambient air temperature and light in controlling monoterpene emissions, likely contributing to higher monoterpene emissions during the summer season in temperate regions. In addition to light and temperature dependence, other important environmental variables such as carbon dioxide (CO₂), ozone (O₃), soil moisture, and nutrient availability are also known to influence monoterpene emissions rates, but the information available is still limited. Throughout the paper, we identify knowledge gaps and provide recommendations for future studies. Full article

Dust storms have large impacts on air quality and meteorological elements; however, their relationships with atmospheric greenhouse gases (e.g., CO₂) and radiation components remain uncertain. In this study, the co-variation of dust and CO₂ concentrations and its possible influencing mechanism are examined using observations at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station along with simulations of the Vegetation Photosynthesis and Respiration Model coupled with the Weather Research and Forecasting model (WRF-VPRM), during two dust storm events on 15 and 28 March 2021. During these events, hourly CO₂ concentrations decreased by 40–50 ppm at SDZ while dust concentrations increased to 1240.6 and 712.4 µg m⁻³. The elevated dust increased diffusive shortwave irradiance by 50–60% and decreased direct shortwave irradiance by ~60% along with clouds. The dust events were attributed to the passages of two cold front systems over northern China. At SDZ, during the frontal passages, wind speed increased by 3–6 m s⁻¹, and relative humidity decreased by 50–60%. The CO₂ variations associated with the frontal systems were captured by the WRF-VPRM despite the overestimated surface CO₂ level at SDZ. Biogenic CO₂ flux plays an indistinctive role in the large CO₂ variation at SDZ, as it is weak during the non-growing season. The cold fronts pushed polluted air southeastward over the North China Plain and replaced it with low-CO₂ air from Northwest China, leading to the decline in CO₂. These findings demonstrate that mesoscale synoptic conditions significantly affect the regional transport and dispersion of CO₂, which can influence the prediction of terrestrial carbon balance on a regional scale. Full article

This study systematically examines the global uncertainties and biases in the carbon dioxide (CO₂) mixing ratio provided by the Copernicus Atmosphere Monitoring Service (CAMS). The global greenhouse gas re-analysis (EGG4) data product from the European Centre for Medium-Range Weather Forecasts (ECMWF) was evaluated against ground-based in situ measurements from more than 160 of stations across the world. The evaluation shows that CO₂ re-analysis can capture the general features in the tracer distributions, including the CO₂ seasonal cycle and its strength at different latitudes, as well as the global CO₂ trend. The emissions and natural fluxes of CO₂ at the surface are evaluated on a wide range of scales, from diurnal to interannual. The results highlight re-analysis compliance, reproducing biogenic fluxes as well the observed CO₂ patterns in remote environments. CAMS consistently reproduces observations at marine and remote regions with low CO₂ fluxes and smooth variability. However, the model’s weaknesses were observed in continental areas, regions with complex sources, transport circulations and large CO₂ fluxes. A strong variation in the accuracy and bias are displayed among those stations with different flux profiles, with the largest uncertainties in the continental regions with high CO₂ anthropogenic fluxes. Displaying biased estimation and root-mean-square error (RMSE) ranging from values below one ppmv up to 70 ppmv, the results reveal a poor response from re-analysis to high CO₂ mixing ratio, showing larger uncertainty of the product in the boundaries where the CAMS system misses solving sharp flux variability. The mismatch at regions with high fluxes of anthropogenic emission indicate large uncertainties in inventories and constrained physical parameterizations in the CO₂ at boundary conditions. The current study provides a broad uncertainty assessment for the CAMS CO₂ product worldwide, suggesting deficiencies and methods that can be used in the future to overcome failures and uncertainties in regional CO₂ mixing ratio and flux estimates. Full article

This study assessed leaf fluxes of CO₂, CH₄ and biogenic volatile organic compounds (BVOC) for two common urban tree species, Platanus × acerifolia (exotic) and Schinus molle (native), widely distributed in Santiago, Chile. The emission factors (EF) and the Photochemical Ozone Creation Index (POCI) for S. molle and P. × acerifolia were estimated. The global EF was 6.4 times higher for P. × acerifolia compared with S. molle, with similar rates of photosynthesis for both species. Isoprene represented more than 86% of the total BVOCs leaf fluxes being 7.6 times greater for P. × acerifolia than S. molle. For P. × acerifolia, BVOCs represented 2% of total carbon fixation while representing 0.24% for S. molle. These results may suggest that plant species growing outside their ecological range may exhibit greater BVOCs leaf fluxes, proportional to photosynthesis, compared to well-adapted ones. The results found may contribute to better urban forest planning. Full article

During the last decade, advances in the remote sensing of greenhouse gas (GHG) concentrations by the Greenhouse Gases Observing SATellite-1 (GOSAT-1), GOSAT-2, and Orbiting Carbon Observatory-2 (OCO-2) have produced finer-resolution atmospheric carbon dioxide (CO₂) datasets. These data are applicable for a top-down approach towards the verification of anthropogenic CO₂ emissions from megacities and updating of the inventory. However, great uncertainties regarding natural CO₂ flux estimates remain when back-casting CO₂ emissions from concentration data, making accurate disaggregation of urban CO₂ sources difficult. For this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) land products, meso-scale meteorological data, SoilGrids250 m soil profile data, and sub-daily soil moisture datasets to calculate hourly photosynthetic CO₂ uptake and biogenic CO₂ emissions with 500 m resolution for the Kantō Plain, Japan, at the center of which is the Tokyo metropolis. Our hourly integrated modeling results obtained for the period 2010–2018 suggest that, collectively, the vegetated land within the Greater Tokyo Area served as a daytime carbon sink year-round, where the hourly integrated net atmospheric CO₂ removal was up to 14.15 ± 4.24% of hourly integrated anthropogenic emissions in winter and up to 55.42 ± 10.39% in summer. At night, plants and soil in the Greater Tokyo Area were natural carbon sources, with hourly integrated biogenic CO₂ emissions equivalent to 2.27 ± 0.11%–4.97 ± 1.17% of the anthropogenic emissions in winter and 13.71 ± 2.44%–23.62 ± 3.13% in summer. Between January and July, the hourly integrated biogenic CO₂ emissions of the Greater Tokyo Area increased sixfold, whereas the amplitude of the midday hourly integrated photosynthetic CO₂ uptake was enhanced by nearly five times and could offset up to 79.04 ± 12.31% of the hourly integrated anthropogenic CO₂ emissions in summer. The gridded hourly photosynthetic CO₂ uptake and biogenic respiration estimates not only provide reference data for the estimation of total natural CO₂ removal in our study area, but also supply prior input values for the disaggregation of anthropogenic CO₂ emissions and biogenic CO₂ fluxes when applying top-down approaches to update the megacity’s CO₂ emissions inventory. The latter contribution allows unprecedented amounts of GOSAT and ground measurement data regarding CO₂ concentration to be analyzed in inverse modeling of anthropogenic CO₂ emissions from Tokyo and the Kantō Plain. Full article

Nowadays, different approaches for CO₂ anthropogenic emission estimation are applied to control agreements on greenhouse gas reduction. Some methods are based on the inverse modelling of emissions using various measurements and the results of numerical chemistry transport models (CTMs). Since the accuracy and precision of CTMs largely determine errors in the approaches for emission estimation, it is crucial to validate the performance of such models through observations. In the current study, the near-surface CO₂ mixing ratio simulated by the CTM Weather Research and Forecasting—Chemistry (WRF-Chem) at a high spatial resolution (3 km) using three different sets of CO₂ fluxes (anthropogenic + biogenic fluxes, time-varying and constant anthropogenic emissions) and from Copernicus Atmosphere Monitoring Service (CAMS) datasets have been validated using in situ observations near the Saint Petersburg megacity (Russia) in March and April 2019. It was found that CAMS reanalysis data with a low spatial resolution (1.9° × 3.8°) can match the observations better than CAMS analysis data with a high resolution (0.15° × 0.15°). The CAMS analysis significantly overestimates the observed near-surface CO₂ mixing ratio in Peterhof in March and April 2019 (by more than 10 ppm). The best match for the CAMS reanalysis and observations was observed in March, when the wind was predominantly opposite to the Saint Petersburg urbanized area. In contrast, the CAMS analysis fits the observed trend of the mixing ratio variation in April better than the reanalysis with the wind directions from the Saint Petersburg urban zone. Generally, the WRF-Chem predicts the observed temporal variations in the near-surface CO₂ reasonably well (mean bias ≈ (−0.3) − (−0.9) ppm, RMSD ≈ 8.7 ppm, correlation coefficient ≈ 0.61 ± 0.04). The WRF-Chem data where anthropogenic and biogenic fluxes were used match the observations a bit better than the WRF-Chem data without biogenic fluxes. The diurnal time variation in the anthropogenic emissions influenced the WRF-Chem data insignificantly. However, in general, the data of all three WRF-Chem model runs give almost the same CO₂ temporal variation in Peterhof in March and April 2019. This could be related to the late start of the growing season, which influences biogenic CO₂ fluxes, inaccuracies in the estimation of the biogenic fluxes, and the simplified time variation pattern of the CO₂ anthropogenic emissions. Full article

Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types. Full article

Carbon cycling within the deep mangrove forest floor is unique compared to other marine ecosystems with organic carbon input, mineralization, burial, and advective and groundwater export pathways being in non-steady-state, often oscillating in synchrony with tides, plant uptake, and release/uptake via roots and other edaphic factors in a highly dynamic and harsh environment. Rates of soil organic carbon (C_ORG) mineralization and belowground C_ORG stocks are high, with rapid diagenesis throughout the deep (>1 m) soil horizon. Pocketed with cracks, fissures, extensive roots, burrows, tubes, and drainage channels through which tidal waters percolate and drain, the forest floor sustains non-steady-state diagenesis of the soil C_ORG, in which decomposition processes at the soil surface are distinct from those in deeper soils. Aerobic respiration occurs within the upper 2 mm of the soil surface and within biogenic structures. On average, carbon respiration across the surface soil-air/water interface (104 mmol C m⁻² d⁻¹) equates to only 25% of the total carbon mineralized within the entire soil horizon, as nearly all respired carbon (569 mmol C m⁻² d⁻¹) is released in a dissolved form via advective porewater exchange and/or lateral transport and subsurface tidal pumping to adjacent tidal waters. A carbon budget for the world’s mangrove ecosystems indicates that subsurface respiration is the second-largest respiratory flux after canopy respiration. Dissolved carbon release is sufficient to oversaturate water-column pCO_2, causing tropical coastal waters to be a source of CO₂ to the atmosphere. Mangrove dissolved inorganic carbon (DIC) discharge contributes nearly 60% of DIC and 27% of dissolved organic carbon (DOC) discharge from the world’s low latitude rivers to the tropical coastal ocean. Mangroves inhabit only 0.3% of the global coastal ocean area but contribute 55% of air-sea exchange, 14% of C_ORG burial, 28% of DIC export, and 13% of DOC + particulate organic matter (POC) export from the world’s coastal wetlands and estuaries to the atmosphere and global coastal ocean. Full article

Quantifying the uncertainty of inversion-derived ${\mathrm{CO}}_2$ surface fluxes and attributing the uncertainty to errors in either flux or atmospheric transport simulations continue to be challenges in the characterization of surface sources and sinks of carbon dioxide (${\mathrm{CO}}_2$). Despite recent studies inferring fluxes while using higher-resolution modeling systems, the utility of regional-scale models remains unclear when compared to existing coarse-resolution global systems. Here, we present an off-line coupling of the mesoscale Weather Research and Forecasting (WRF) model to optimized biogenic ${\mathrm{CO}}_2$ fluxes and mole fractions from the global Carbon Monitoring System inversion system (CMS-Flux). The coupling framework consists of methods to constrain the mass of ${\mathrm{CO}}_2$ introduced into WRF, effectively nesting our regional domain covering most of North America (except the northern half of Canada) within the CMS global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions (${\mathrm{XCO}}_2$) over North America for 2010. We find mean model-model differences in summer of ∼0.12 ppm, significantly lower than the original coupling scheme (from 0.5 to 1.5 ppm, depending on the boundary). While 85% of the ${\mathrm{XCO}}_2$ values are due to long-range transport from outside our North American domain, most of the model-model differences appear to be due to transport differences in the fraction of the troposphere below 850 hPa. Satellite data from GOSAT and tower and aircraft data are used to show that vertical transport above the Planetary Boundary Layer is responsible for significant model-model differences in the horizontal distribution of column ${\mathrm{XCO}}_2$ across North America. Full article

Marine sediments of the Blake Ridge province exhibit clearly defined geophysical indications for the presence of gas hydrates and a free gas phase. Despite being one of the world’s best-studied gas hydrate provinces and having been drilled during Ocean Drilling Program (ODP) Leg 164, discrepancies between previous model predictions and reported chemical profiles as well as hydrate concentrations result in uncertainty regarding methane sources and a possible co-existence between hydrates and free gas near the base of the gas hydrate stability zone (GHSZ). Here, by using a new multi-phase finite element (FE) numerical model, we investigate different scenarios of gas hydrate formation from both single and mixed methane sources (in-situ biogenic formation and a deep methane flux). Moreover, we explore the evolution of the GHSZ base for the past 10 Myr using reconstructed sedimentation rates and non-steady-state P-T solutions. We conclude that (1) the present-day base of the GHSZ predicted by our model is located at the depth of ~450 mbsf, thereby resolving a previously reported inconsistency between the location of the BSR at ODP Site 997 and the theoretical base of the GHSZ in the Blake Ridge region, (2) a single in-situ methane source results in a good fit between the simulated and measured geochemical profiles including the anaerobic oxidation of methane (AOM) zone, and (3) previously suggested 4 vol.%–7 vol.% gas hydrate concentrations would require a deep methane flux of ~170 mM (corresponds to the mass of methane flux of 1.6 × 10⁻¹¹ kg s⁻¹ m⁻²) in addition to methane generated in-situ by organic carbon (POC) degradation at the cost of deteriorating the fit between observed and modelled geochemical profiles. Full article

Air-sea interactions play an important role in atmospheric circulation and boundary layer conditions through changing convection processes and surface heat fluxes, particularly in coastal areas. These changes can affect the concentrations, distributions, and lifetimes of atmospheric pollutants. In this Part II paper, the performance of the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are intercompared for their applications over quadruple-nested domains in Australia during the three following field campaigns: The Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2) and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). The results are used to evaluate the impact of air-sea interaction representation in WRF/Chem-ROMS on model predictions. At 3, 9, and 27 km resolutions, compared to WRF/Chem, the explicit air-sea interactions in WRF/Chem-ROMS lead to substantial improvements in simulated sea-surface temperature (SST), latent heat fluxes (LHF), and sensible heat fluxes (SHF) over the ocean, in terms of statistics and spatial distributions, during all three field campaigns. The use of finer grid resolutions (3 or 9 km) effectively reduces the biases in these variables during SPS1 and SPS2 by WRF/Chem-ROMS, whereas it further increases these biases for WRF/Chem during all field campaigns. The large differences in SST, LHF, and SHF between the two models lead to different radiative, cloud, meteorological, and chemical predictions. WRF/Chem-ROMS generally performs better in terms of statistics and temporal variations for temperature and relative humidity at 2 m, wind speed and direction at 10 m, and precipitation. The percentage differences in simulated surface concentrations between the two models are mostly in the range of ±10% for CO, OH, and O₃, ±25% for HCHO, ±30% for NO₂, ±35% for H₂O₂, ±50% for SO₂, ±60% for isoprene and terpenes, ±15% for PM_2.5, and ±12% for PM₁₀. WRF/Chem-ROMS at 3 km resolution slightly improves the statistical performance of many surface and column concentrations. WRF/Chem simulations with satellite-constrained boundary conditions (BCONs) improve the spatial distributions and magnitudes of column CO for all field campaigns and slightly improve those of the column NO₂ for SPS1 and SPS2, column HCHO for SPS1 and MUMBA, and column O₃ for SPS2 at 3 km over the Greater Sydney area. The satellite-constrained chemical BCONs reduce the model biases of surface CO, NO, and O₃ predictions at 3 km for all field campaigns, surface PM_2.5 predictions at 3 km for SPS1 and MUMBA, and surface PM₁₀ predictions at all grid resolutions for all field campaigns. A more important role of chemical BCONs in the Southern Hemisphere, compared to that in the Northern Hemisphere reported in this work, indicates a crucial need in developing more realistic chemical BCONs for O₃ in the relatively clean SH. Full article

Air pollution and associated human exposure are important research areas in Greater Sydney, Australia. Several field campaigns were conducted to characterize the pollution sources and their impacts on ambient air quality including the Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2), and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). In this work, the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are applied during these field campaigns to assess the models’ capability in reproducing atmospheric observations. The model simulations are performed over quadruple-nested domains at grid resolutions of 81-, 27-, 9-, and 3-km over Australia, an area in southeastern Australia, an area in New South Wales, and the Greater Sydney area, respectively. A comprehensive model evaluation is conducted using surface observations from these field campaigns, satellite retrievals, and other data. This paper evaluates the performance of WRF/Chem-ROMS and its sensitivity to spatial grid resolutions. The model generally performs well at 3-, 9-, and 27-km resolutions for sea-surface temperature and boundary layer meteorology in terms of performance statistics, seasonality, and daily variation. Moderate biases occur for temperature at 2-m and wind speed at 10-m in the mornings and evenings due to the inaccurate representation of the nocturnal boundary layer and surface heat fluxes. Larger underpredictions occur for total precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. The model performs well at 3-, 9-, and 27-km resolutions for surface O₃ in terms of statistics, spatial distributions, and diurnal and daily variations. The model underpredicts PM_2.5 and PM₁₀ during SPS1 and MUMBA but overpredicts PM_2.5 and underpredicts PM₁₀ during SPS2. These biases are attributed to inaccurate meteorology, precursor emissions, insufficient SO₂ conversion to sulfate, inadequate dispersion at finer grid resolutions, and underprediction in secondary organic aerosol. The model gives moderate biases for net shortwave radiation and cloud condensation nuclei but large biases for other radiative and cloud variables. The performance of aerosol optical depth and latent/sensible heat flux varies for different simulation periods. Among all variables evaluated, wind speed at 10-m, precipitation, surface concentrations of CO, NO, NO₂, SO₂, O₃, PM_2.5, and PM₁₀, aerosol optical depth, cloud optical thickness, cloud condensation nuclei, and column NO₂ show moderate-to-strong sensitivity to spatial grid resolutions. The use of finer grid resolutions (3- or 9-km) can generally improve the performance for those variables. While the performance for most of these variables is consistent with that over the U.S. and East Asia, several differences along with future work are identified to pinpoint reasons for such differences. Full article

Here, we present the first detailed study on diffuse CO₂ degassing in the lakes in the Western Group (Corvo and Flores islands) of the Azores archipelago. This research is of interest in order to determine (1) the overall CO₂ emission from such lakes, as volcanic lakes are often underrepresented in the databases of these water bodies, and (2) the diffuse CO₂ degassing estimates in active volcanic areas such as the Azores. The lake waters on Corvo and Flores islands are mainly of the Na–Cl type, which is likely caused by the lakes’ sea salt signatures, arising from nearby seawater spraying; however, a few samples show evidence of slight alkali earth metal and bicarbonate enrichments in the lake waters, suggesting a contribution of water–rock interaction. In this study, diffuse CO₂ flux measurements were taken using the accumulation chamber method, and statistical analyses utilizing the graphical statistical approach (GSA) and sequential Gaussian simulation (sGs) were conducted on the CO₂ flux data, showing that the CO₂ flux values measured in these lakes were relatively low (0.0–18.6 g m⁻² d⁻¹). The results seem to indicate that there is a single source of CO₂ (a biogenic source), which is also supported by the waters’ δ¹³C isotopic signatures. Significant differences in the final CO₂ output values were verified between surveys (e.g., 0.16 t d⁻¹ in R1; 0.32 t d⁻¹ in R2), and these differences are probably associated with the monomictic character of the lakes. CO₂ emissions ranged between 0.18 t d⁻¹ (CE1) and 0.50 t d⁻¹ (CW1) for the Corvo lakes and between 0.03 t d⁻¹ (P1) and 0.32 t d⁻¹ (R2) for the seven lakes studied on Flores Island. The presence of a dense macrophyte mass in a few of the lakes appears to enhance the CO₂ flux in these lakes. Full article