Biogenic Fluxes Research Articles

CO2 Emissions Estimate From Mexico City Using Ground‐ and Space‐Based Remote Sensing

AbstractThe Mexico City Metropolitan Area (MCMA) stands as one of the most densely populated urban regions globally. To quantify the urban emissions in the MCMA, we independently assimilated observations from a dense column‐integrated Fourier transform infrared (FTIR) network and OCO‐3 Snapshot Area Map observations between October 2020 and May 2021. Applying a computationally efficient analytical Bayesian inversion technique, we inverted for surface fluxes at high spatio‐temporal resolutions (1‐km and 1‐hr). The fossil fuel (FF) emission estimates of 5.08 and 6.77 Gg/hr reported by the global and local emission inventories were optimized to 4.85 and 5.51 Gg/hr based on FTIR observations over this 7 month period, highlighting a convergence of posterior estimates. The modeled biogenic flux estimate of −0.14 Gg/hr was improved to −0.33 to −0.27 Gg/hr, respectively. It is worth noting that utilizing observations from three primary sites significantly enhanced the accuracy of estimates (13.6 29.2%) around the other four. Using FTIR posterior estimates can improve simulation with the OCO‐3 data set. OCO‐3 shows a similar decreasing trend in FF emissions (from 6.37 Gg/hr to 6.36 and 5.04 Gg/hr) as FTIR, but its correction trends for biogenic sources differ, changing from 0.37 to 0.48 Gg/hr. The primary reason is OCO‐3's lower temporal sampling density. Aligning the FTIR inversion timing with that of OCO‐3 yielded comparable corrections for FF emissions, yet discrepancies in biogenic emissions persisted, which can be attributed to their different sampling locations in the rural region and discrepancy in X observations. Our findings mark a significant step toward validating OCO‐3 and FTIR inversion results in metropolitan region.

High-resolution sampling in the eastern tropical North Atlantic reveals episodic Saharan dust deposition: implications for the marine carbon sink

In this study we present data collected between August 2017 and December 2018 from submarine sediment trap M1 located in the eastern tropical North Atlantic and determine lithogenic and biogenic fluxes, and grain-size distributions of aerosol dust. An unprecedented high sampling resolution of four days in combination with satellite imagery allowed the identification of thirteen major dust events of two types within the 468-day series. Seven dust events were classified as high-flux events identified by a deposition of >=25 mg m-2 d-1. The average dust deposition rate increased by 461.3% during these types of events. The remaining six events were characterized by a high composition of giant particles (>7.3 vol%). Seasonal variations of dust flux were recorded, with highest fluxes observed in spring at an average deposition rate of 14.8 mg m-2 d-1, and lowest fluxes in fall with an average rate of 8.6 mg m-2 d-1. The estimated total dust flux in the tropical North Atlantic was 4040.02 mg m-2 y-1. We suggest that most of the summer dust was likely transported over the sampling site at high altitudes while winter transport occurred closer to the sea surface, resulting in generally higher background fluxes. Grain-size distributions exhibited seasonal variations with increased occurrences of giant particles (>62.5 μm) in fall 2017 and spring, and less occurrences in winter and fall 2018. Grain-size sorting was high in spring and most variable in summer. Precipitation did not affect depositional fluxes or grain-size distributions of the aeolian dust significantly. Organic matter was deposited continuously at the sampling site with a deposition rate ranging from 14.4–862.25 mg m-2 d-1. Organic matter fluxes increased by 199.5% during high-flux dust events but decreased by 13.6% during anomalous grain-size events. Spring experienced the highest number of dust events (n=5). This unprecedented high-resolution dataset of dust deposition in marine sediment-traps enabled the distinction of dust events and their relation to organic matter flux. This suggests the possibility of a dust fertilization or mineral ballasting effect.

Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1

Abstract. Isoprene, a key biogenic volatile organic compound, plays a pivotal role in atmospheric chemistry. Due to its high reactivity, this compound contributes significantly to the production of tropospheric ozone in polluted areas and to the formation of secondary organic aerosols. The assessment of biogenic emissions is of great importance for regional and global air quality evaluation. In this study, we implemented the biogenic emission model MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature, version 2.1) in the surface model SURFEXv8.1 (SURface EXternalisée in French, version 8.1). This coupling aims to improve the estimation of biogenic emissions using the detailed vegetation-type-dependent treatment included in the SURFEX vegetation ISBA (Interaction between Soil Biosphere and Atmosphere) scheme. This scheme provides vegetation-dependent parameters such as leaf area index and soil moisture to MEGAN. This approach enables a more accurate estimation of biogenic fluxes compared to the stand-alone MEGAN model, which relies on average input values for all vegetation types. The present study focuses on the assessment of the SURFEX–MEGAN model isoprene emissions. An evaluation of the coupled SURFEX–MEGAN model results was carried out by conducting a global isoprene emission simulation in 2019 and by comparing the simulation results with other MEGAN-based isoprene inventories. The coupled model estimates a total global isoprene emission of 443 Tg in 2019. The estimated isoprene is within the range of results obtained with other MEGAN-based isoprene inventories, ranging from 311 to 637 Tg. The spatial distribution of SURFEX–MEGAN isoprene is consistent with other studies, with some differences located in low-isoprene-emission regions. Several sensitivity tests were conducted to quantify the impact of different model inputs and configurations on isoprene emissions. Using different meteorological forcings resulted in a ±5 % change in isoprene emissions using MERRA (Modern-Era Retrospective analysis for Research and Applications) and IFS (Integrated Forecasting System) compared with ERA5. The impact of using different emission factor data was also investigated. The use of PFT (plant functional type) spatial coverage and PFT-dependent emission potential data resulted in a 12 % reduction compared to using the isoprene emission potential gridded map. A significant reduction of around 38 % in global isoprene emissions was observed in the third sensitivity analysis, which applied a parameterization of soil moisture deficit, particularly in certain regions of Australia, Africa, and South America. The significance of coupling the SURFEX and MEGAN models lies particularly in the ability of the coupled model to be forced with meteorological data from any period. This means, for instance, that this system can be used to predict biogenic emissions in the future. This aspect of our work is significant given the changes that biogenic organic compounds are expected to undergo as a result of changes in their climatic factors.

CO2 fluxes of vegetation in the Greenbelt of Ontario and increased net ecosystem emissions associated with its removal

The fluxes of carbon dioxide (CO2) to and from vegetation can be significant on a regional scale. It is therefore important to understand the biogenic fluxes of CO2 in order to quantify local carbon budgets. The Greenbelt of Ontario is a protected region of cropland and natural vegetation surrounding the Greater Toronto and Hamilton Area (GTHA) in Ontario, Canada. Recently, changes were proposed to the Greenbelt, including the removal of 2,995 ha (7,400 acres) of protected land to be replaced with housing. In this study, we estimate the biogenic CO2 fluxes of the entire Greenbelt as well as the areas that were proposed for removal by using a modified version of the Solar-induced fluorescence for Modeling Urban biogenic Fluxes vegetation model. We find that, on average, the entire Greenbelt has a net sequestration of 9.9 ± 6.4 TgCO2 each year, where the uncertainty represents half of the interannual variability plus error from the individual years, for the years 2018–2020. The net amount of CO2 absorbed by the Greenbelt is roughly equivalent to a fifth of the annual human-made emissions reported for the entire GTHA. The areas proposed for removal are found to have a net sequestration of 0.0061–0.031 TgCO2 annually. During construction, these lands will remain barren, and the soil will continue to emit CO2, thus changing the area from a net sink to a net source of CO2. For a 3- to 5-year construction period, this soil efflux would result in net ecosystem emissions of 0.314 ± 0.078 TgCO2, in addition to the net sequestration lost by removing the original vegetation (−0.077 ± 0.035 TgCO2). This results in a net difference in biogenic CO2 fluxes of 0.390 ± 0.083 TgCO2, which is equivalent to the average CO2 emissions of roughly 85,000 gasoline passenger vehicles over the course of a year. In addition to biogenic fluxes, there will be CO2 emissions associated with the construction of the proposed single-family housing developments as well as larger per capita emissions associated with low-density housing compared to creating higher density housing using less land.

Complex Validation of Weather Research and Forecasting—Chemistry Modelling of Atmospheric CO2 in the Coastal Cities of the Gulf of Finland

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.

Anthropogenic CO2 emission estimates in the Tokyo metropolitan area from ground-based CO2 column observations

Abstract. Urban areas are responsible for more than 40 % of global energy-related carbon dioxide (CO2) emissions. The Tokyo metropolitan area (TMA), Japan, one of the most populated regions in the world, includes various emission sources, such as thermal power plants, automobile traffic, and residential facilities. In order to infer a top–down emission estimate, we conducted an intensive field campaign in the TMA from February to April 2016 to measure column-averaged dry-air mole fractions of CO2 (XCO2) with three ground-based Fourier transform spectrometers (one IFS 125HR and two EM27/SUN spectrometers). At two urban sites (Saitama and Sodegaura), measured XCO2 values were generally larger than those at a rural site (Tsukuba) by up to 9.5 ppm, and average diurnal variations increased toward evening. To simulate the XCO2 enhancement (ΔXCO2) resulting from emissions at each observation site, we used the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by meteorological fields at a horizontal resolution of ∼1 km from the Weather Research and Forecasting (WRF) model, which was coupled with anthropogenic (large point source and area source) CO2 emissions and biogenic fluxes. Although some of the diurnal variation of ΔXCO2 was not reproduced and plumes from nearby large point sources were not captured, primarily because of a transport modeling error, the WRF–STILT simulations using prior fluxes were generally in good agreement with the observations (mean bias, 0.30 ppm; standard deviation, 1.31 ppm). By combining observations with high-resolution modeling, we developed an urban-scale inversion system in which spatially resolved CO2 emission fluxes at >3 km resolution and a scaling factor of large point source emissions were estimated on a monthly basis by using Bayesian inference. The XCO2 simulation results from the posterior CO2 fluxes were improved (mean bias, −0.03 ppm; standard deviation, 1.21 ppm). The prior and posterior total CO2 emissions in the TMA are 1.026 ± 0.116 and 1.037 ± 0.054 Mt-CO2 d−1 at the 95 % confidence level, respectively. The posterior total CO2 emissions agreed with emission inventories within the posterior uncertainty, demonstrating that the EM27/SUN spectrometer data can constrain urban-scale monthly CO2 emissions.

Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model

Abstract. To address ambitious goals of carbon neutrality set at national and city scales, a number of atmospheric networks have been deployed to monitor greenhouse gas (GHG) concentrations in and around cities. To convert these measurements into estimates of emissions from cities, atmospheric models are used to simulate the transport of various trace gases and help interpret these measurements. We set up a modelling framework using the Weather Research and Forecasting (WRF) model applied at a high spatial resolution (up to 400 m) to simulate the atmospheric transport of GHGs and attempt a preliminary interpretation of the observations provided by the Munich Urban Carbon Column Network (MUCCnet). Building on previous analyses using similar measurements performed within a campaign for the city of Berlin and its surroundings (Zhao et al., 2019), our modelling framework has been improved regarding the initialization of tagged tracers, model settings, and input data. To assess the model performance, we validate the modelled output against two local weather stations and two radiosonde observations, as well as observed column GHG concentrations. The measurements were provided by the measurement campaign that was carried out from 1 to 30 August 2018. The modelled wind matches well with the measurements from the weather stations, with wind speeds slightly overestimated. In general, the model is able to reproduce the measured slant column concentrations of CH4 and their variability, while for CO2, a difference in the slant column CO2 of around 3.7 ppm is found in the model. This can be attributed to the initial and lateral boundary conditions used for the background tracer. Additional mismatches in the diurnal cycle could be explained by an underestimation of nocturnal respiration in the modelled CO2 biogenic fluxes. The differential column method (DCM) has been applied to cancel out the influence from the background concentrations. We optimize its application by selecting suitable days on which the assumption of the DCM holds true: a relatively uniform air mass travels over the city, passing from an upwind site to a downwind site. In particular, the Stochastic Time-Inverted Lagrangian Transport (STILT) model is used here and driven by our WRF-modelled meteorological fields to obtain footprints (i.e. the potential areas of influence for signals observed at measurement stations), further used for interpreting measurement results. Combining these footprints with local knowledge of emission sources, we find evidence of CH4 sources near Munich that are missing or underestimated in the emission inventory used. This demonstrates the potential of this data–model framework to constrain local sources and improve emission inventories.

Implications of Emission Sources and Biosphere Exchange on Temporal Variations of CO2 and δ13C Using Continuous Atmospheric Measurements at Shadnagar (India)

AbstractDiurnal variation of atmospheric CO2 and its driving factors are studied using high‐precision in situ mixing ratio measurements and stable carbon isotopic CO2 (δ13C‐CO2) for the first time over Shadnagar, a suburban site in India, from November 2018 to October 2019. The annual mean mixing ratios of atmospheric CO2 and δ13C‐CO2 are observed to be 414.76 ± 4.26 ppm and −11.19 ‰ ± 1.63 ‰. Maximum diurnal variability of atmospheric CO2 was observed in summer monsoon (17.30 ± 9.29 ppm), and the minimum was noticed in winter (7.19 ± 0.11 ppm), indicating strong seasonality in diurnal variability of amplitude. To characterize the atmospheric CO2 sources, the Miller‐Tans model was implemented separately using the CO2 and its δ13C‐CO2 isotopic data during day and night. However, a strong source signature of δ13C‐CO2 was observed during the night‐time of summer monsoon with a slope of −37.42‰ ± 0.73‰, obtained using a reduced major axis regression. The identified source indicates possible emissions from fossil fuel combustion. Further, a Lagrangian back trajectory analysis was performed to study the influence of transport on the observed CO2 mixing ratios. The model trajectory confirms the influence of the Indian summer monsoon on the variations of atmospheric CO2 mixing ratios. Our study shows that fossil fuel emissions are one of the major contributors of CO2 in the study location (about ∼2 to 4 ppm) with biogenic fluxes adding a clear seasonality ranging from −8 to 4 ppm.

Small-scale oxygen distribution patterns in a coral reef

One mechanism giving fleshy algae a competitive advantage over corals during reef degradation is algal-induced and microbially-mediated hypoxia (typically less than 69.5 µmol oxygen L−1). During hypoxic conditions oxygen availability becomes insufficient to sustain aerobic respiration in most metazoans. Algae are more tolerant of low oxygen conditions and may outcompete corals weakened by hypoxia. A key question on the ecological importance of this mechanism remains unanswered: How extensive are local hypoxic zones in highly turbulent aquatic environments, continuously flushed by currents and wave surge? To better understand the concert of biological, chemical, and physical factors that determine the abundance and distribution of oxygen in this environment, we combined 3D imagery, flow measurements, macro- and micro-organismal abundance estimates, and experimentally determined biogenic oxygen and carbon fluxes as input values for a 3D bio-physical model. The model was first developed and verified for controlled flume experiments containing coral and algal colonies in direct interaction. We then developed a three-dimensional numerical model of an existing coral reef plot off the coast of Curaçao where oxygen concentrations for comparison were collected in a small-scale grid using fiberoptic oxygen optodes. Oxygen distribution patterns given by the model were a good predictor for in situ concentrations and indicate widespread localized differences exceeding 50 µmol L-1 over distances less than a decimeter. This suggests that small-scale hypoxic zones can persist for an extended period of time in the turbulent environment of a wave- and surge- exposed coral reef. This work highlights how the combination of three-dimensional imagery, biogenic fluxes, and fluid dynamic modeling can provide a powerful tool to illustrate and predict the distribution of analytes (e.g., oxygen or other bioactive substances) in a highly complex system.

Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions

Abstract. We assess the theoretical capability of the upcoming France–UK MicroCarb satellite, which has a city-scan observing mode, to determine integrated urban emissions of carbon dioxide (CO2). To achieve this we report results from a series of closed-loop numerical experiments that use an atmospheric transport model with anthropogenic and biogenic fluxes to determine the corresponding changes in atmospheric CO2 column, accounting for changes in measurement coverage due to cloud loading. We use a maximum a posteriori inverse method to infer the CO2 fluxes based on the measurements and the a priori information. Using an urban CO2 inversion system, we explore the relative performance of alternative two-sweep and three-sweep city observing strategies to quantify CO2 emissions over the cities of Paris and London in different months when biospheric fluxes vary in magnitude. We find that both the two-sweep and three-sweep observing modes are able to reduce a priori flux errors by 20 %–40 % over Paris and London. The three-sweep observing strategy, which generally outperforms the two-sweep mode by virtue of its wider scan area that typically yields more cloud-free observations, can retrieve the total emissions of the truth within 7 % over Paris and 21 % over London. The performance of the limited-domain city-mode observing strategies is sensitive to cloud coverage and particularly sensitive to the prevailing wind direction. We also find that seasonal photosynthetic uptake of CO2 by the urban biosphere weakens atmospheric CO2 gradients across both cities, thereby reducing the sensitivity of urban CO2 enhancements and subsequently compromising the ability of MicroCarb to reduce bias in estimating urban CO2 emissions. This suggests that additional trace gases co-emitted with anthropogenic CO2 emissions, but unaffected by the land biosphere, are needed to quantify sub-city scale CO2 emissions during months when the urban biosphere is particularly active.

A high-resolution monitoring approach of urban CO2 fluxes. Part 1 - bottom-up model development

Monitoring carbon dioxide (CO2) emissions of urban areas is increasingly important to assess the progress towards the Paris Agreement goals for climate neutrality. Cities are currently voluntarily developing their local inventories, however, the approaches used across different cities are not systematically assessed, present consistency issues, neglect the biogenic fluxes and have restricted spatial and temporal resolution. In order to assess the accuracy of the urban emission inventories and provide information which is useful for planning local climate change mitigation actions, high resolution modelling approaches combined or evaluated with atmospheric observations are needed. This study presents a new high-resolution bottom-up (BU) model which provides hourly maps of all major components contributing to the local urban surface CO2 flux (i.e. building emissions, traffic emissions, human respiration, soil respiration, plant respiration, plant photosynthetic uptake) and can therefore be used for direct comparison with in-situ atmospheric observations and development of local scale atmospheric inversion methodologies. The model design aims to be simple and flexible using inputs that are available in most cities, facilitating transferability to different locations. The inputs are primarily based on open geospatial datasets, census information, road traffic monitoring and basic meteorological parameters. The model is applied on the city centre of Basel, Switzerland, for the year 2018 and the results are compared to a local inventory. It is demonstrated that the model captures the highly dynamic spatiotemporal variability of the urban CO2 fluxes according to main environmental drivers, population activity dynamics and geospatial information proxies. The annual modelled emissions from buildings and traffic are estimated 14.8 % and 9 % lower than the respective information derived by the local inventory. The differences are mainly attributed to the emissions from the industrial areas and the highways which are beyond the geographical coverage of the model.

High resolution benthic foraminiferal δ18O and δ13C records at ODP site 807 over the past 5 Ma, Ontong Java Plateau: Evolution of North Pacific ventilation, Pliocene to Holocene

The western equatorial Pacific is pivotal to precisely understand the global climate change and its evolution over geological time. However, continuous paleoceanographic records with high time resolution and accurate age model over the last 5 Myr are few in this important ocean region. Here, we present a high time resolution (2–3 kyr) benthic foraminiferal δ 18 O and δ 13 C record from Ocean Drilling Program Site 807 on Ontong Java Plateau in the western equatorial Pacific and establish an accurate age model for the past 5.025 Myr. Comparison of the benthic δ 13 C records from the west and east equatorial Pacific, and the North and South Pacific indicates that water aging effects have dominated since the Pliocene. From 4.0 Ma to 2.7 Ma, a rapid decrease in benthic δ 13 C gradients (Δδ 13 C W-E ) between the west (Hole 807A) and east (ODP Site 849 and IODP Site U1338) equatorial Pacific potentially resulted from strong ventilation in the North Pacific during the warm Pliocene. The subsequent gentle decrease in benthic δ 13 C gradients might indicate stratification in the North Pacific and reduction of biogenic flux with the intensification of the Northern Hemisphere Glaciation (NHG) at 2.7 Ma. Both the Δδ 18 O W-E and Δδ 13 C W-E are strongly paced by 405 ka long eccentricity cycles and 41 kyr obliquity cycle, revealing the complex interplay of both high and low latitude climatic processes on deep Pacific circulation changes. • Continuous 5 Myr long high time resolution benthic foraminiferal δ 18 O and δ 13 C records in the western equatorial Pacific. • West-east equatorial Pacific δ 13 C gradient indicates the evolution of the Pacific deep ocean circulation over the past 5 Myr. • 405-kyr eccentricity cycle modulates the Pacific deep ocean circulation changes.

Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale

Abstract. Various satellite imagers of the vertically integrated column of carbon dioxide (XCO2) are under development to enhance the capabilities for the monitoring of fossil fuel (FF) CO2 emissions. XCO2 images can be used to detect plumes from cities and large industrial plants and to quantify the corresponding emission using atmospheric inversions techniques. However, this potential and the ability to catch the signal from more diffuse FF CO2 sources can be hampered by the mix between these FF signals and a background signal from other types of CO2 surface fluxes, and in particular of biogenic CO2 fluxes. The deployment of dense ground-based air-sampling networks for CO2 and radiocarbon (14CO2) could complement the spaceborne imagery by supporting the separation between the fossil fuel and biogenic or biofuel (BF) CO2 signals. We evaluate this potential complementarity with a high-resolution analytical inversion system focused on northern France, western Germany, Belgium, Luxembourg, and a part of the Netherlands and with pseudo-data experiments. The inversion system controls the FF and BF emissions from the large urban areas and plants, in addition to regional budgets of more diffuse emissions or of biogenic fluxes (NEE, net ecosystem exchange), at an hourly scale over a whole day. The system provides results corresponding to the assimilation of pseudo-data from a single track of a 300 km swath XCO2 imager at 2 km resolution and from surface ground-based CO2 and/or 14CO2 networks. It represents the diversity of 14CO2 sources and sinks and not just the dilution of radiocarbon-free FF CO2 emissions. The uncertainty in the resulting FF CO2 emissions at local (urban area/plant) to regional scales is directly derived and used to assess the potential of the different combinations of observation systems. The assimilation of satellite observations yields estimates of the morning regional emissions with an uncertainty down to 10 % (1σ) in the satellite field of view, from an assumed uncertainty of 15 % in the prior estimates. However, it does not provide direct information about emissions outside the satellite field of view or about afternoon or nighttime emissions. The co-assimilation of 14CO2 and CO2 surface observations leads to a further reduction of the uncertainty in the estimates of FF emissions. However, this further reduction is significant only in administrative regions with three or more 14CO2 and CO2 sampling sites. The uncertainty in the estimates of 1 d emission in North Rhine-Westphalia, a region with three sampling sites, decreases from 8 % to 6.6 % when assimilating the in situ 14CO2 and CO2 data in addition to the satellite data. Furthermore, this additional decrease appears to be larger when the ground stations are close to large FF emission areas, providing an additional direct constraint for the estimate of these sources rather than supporting the characterization of the background signal from the NEE and its separation from that of the FF emissions. More generally, the results indicate no amplification of the potential of each observation subsystem when they are combined into a large observation system with satellite and surface data.

Rapid timescale for an oxic transition during the Great Oxidation Event and the instability of low atmospheric O2

The Great Oxidation Event (GOE), arguably the most important event to occur on Earth since the origin of life, marks the time when an oxygen-rich atmosphere first appeared. However, it is not known whether the change was abrupt and permanent or fitful and drawn out over tens or hundreds of millions of years. Here, we developed a one-dimensional time-dependent photochemical model to resolve time-dependent behavior of the chemically unstable transitional atmosphere as it responded to changes in biogenic forcing. When forced with step-wise changes in biogenic fluxes, transitions between anoxic and oxic atmospheres take between only 102 and 105 y. Results also suggest that O2 between [Formula: see text] and [Formula: see text] mixing ratio is unstable to plausible atmospheric perturbations. For example, when atmospheres with these O2 concentrations experience fractional variations in the surface CH4 flux comparable to those caused by modern Milankovich cycling, oxygen fluctuates between anoxic ([Formula: see text]) and oxic ([Formula: see text]) mixing ratios. Overall, our simulations are consistent with possible geologic evidence of unstable atmospheric O2, after initial oxygenation, which could occasionally collapse from changes in biospheric or volcanic fluxes. Additionally, modeling favors mid-Proterozoic O2 exceeding [Formula: see text] to [Formula: see text] mixing ratio; otherwise, O2 would periodically fall below [Formula: see text] mixing ratio, which would be inconsistent with post-GOE absence of sulfur isotope mass-independent fractionation.

Worldwide Evaluation of CAMS-EGG4 CO2 Data Re-Analysis at the Surface Level.

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.

Net ecosystem exchange (NEE) estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system

Abstract. Three-hourly net ecosystem exchange (NEE) is estimated at spatial scales of 0.25∘ over the European continent, based on the pre-operational inverse modelling framework “CarboScope Regional” (CSR) for the years 2006 to 2019. To assess the uncertainty originating from the choice of a priori flux models and observational data, ensembles of inversions were produced using three terrestrial ecosystem flux models, two ocean flux models, and three sets of atmospheric stations. We find that the station set ensemble accounts for 61 % of the total spread of the annually aggregated fluxes over the full domain when varying all these elements, while the biosphere and ocean ensembles resulted in much smaller contributions to the spread of 28 % and 11 %, respectively. These percentages differ over the specific regions of Europe, based on the availability of atmospheric data. For example, the spread of the biosphere ensemble is prone to be larger in regions that are less constrained by CO2 measurements. We investigate the impact of unprecedented increase in temperature and simultaneous reduction in soil water content (SWC) observed in 2018 and 2019 on the carbon cycle. We find that NEE estimates during these 2 years suggest an impact of drought occurrences represented by the reduction in net primary productivity (NPP), which in turn leads to less CO2 uptake across Europe in 2018 and 2019, resulting in anomalies of up to 0.13 and 0.07 PgC yr−1 above the climatological mean, respectively. Annual temperature anomalies also exceeded the climatological mean by 0.46 ∘C in 2018 and by 0.56 ∘C in 2019, while Standardised Precipitation–Evaporation Index (SPEI) anomalies declined to −0.20 and −0.05 SPEI units below the climatological mean in both 2018 and 2019, respectively. Therefore, the biogenic fluxes showed a weaker sink of CO2 in both 2018 and 2019 (−0.22 ± 0.05 and −0.28 ± 0.06 PgC yr−1, respectively) in comparison with the mean −0.36 ± 0.07 PgC yr−1 calculated over the full analysed period (i.e. 14 years). These translate into a continental-wide reduction in the annual sink by 39 % and 22 %, respectively, larger than the typical year-to-year standard deviation of 19 % observed over the full period.

Quantification of Urban Forest and Grassland Carbon Fluxes Using Field Measurements and a Satellite‐Based Model in Washington DC/Baltimore Area

AbstractCities are taking the lead on climate change mitigation with ambitious goals to reduce carbon dioxide (CO2) emissions. The implementation of effective mitigation policies will require accurate measurements to guide policy decisions and monitor their efficacy. Here, we present a comprehensive CO2inventory of an urban temperate forest and unmanaged grassland using field observations. We estimate the annual storage of CO2by vegetation and soils and place our biogenic flux estimates in the context of local fossil fuel (FF) emissions to determine when, where, and by how much biogenic fluxes alter net CO2flux dynamics. We compare our hourly estimates of biogenic fluxes in the forest site to modeled estimates using a modified version of Urban‐Vegetation Photosynthesis and Respiration Model (Urban‐VPRM) in Washington DC/Baltimore area presenting the first urban evaluation of this model. We estimate that vegetation results in a net biogenic uptake of −2.62 ± 1.9 Mg C ha−1 yr−1in the forest site. FF emissions, however, drive patterns in the net flux resulting in the region being a net source of CO2on daily and annual timescales. In the summer afternoons, however, the net flux is dominated by the uptake of CO2by vegetation. The Urban‐VPRM closely approximates hourly forest inventory based estimates of gross ecosystem exchange but overestimates ecosystem respiration in the dormant season by 40%. Our study highlights the importance of including seasonal dynamics in biogenic CO2fluxes when planning and testing the efficacy of CO2emission reduction polices and development of monitoring programs.

Total diffuse CO2 flux from Yellowstone caldera incorporating high CO2 emissions from cold degassing sites

Previous calculations of total diffuse carbon dioxide (CO2) emissions from Yellowstone National Park have been based on flux measurements from thermally active, altered basins. However, our recent measurements show that thermally inactive, cold degassing sites can emit more diffuse CO2 per km2 than thermally active basins. The contribution of these cold degassing sites must be included in calculations of total diffuse CO2 flux for adequate quantification of Yellowstone's role as a major contributor within the global CO2 budget.We acquired 1342 diffuse CO2 flux point measurements across 19 different sites in Yellowstone National Park during summer 2018 and 2019. Eleven of the measured sites are thermally active with heat flux elevated above background, four sites are vegetation sites, and four sites are thermally inactive, cold degassing sites outside the caldera. Our measurements of diffuse CO2 flux agree with previous findings that the highest average flux occurs in acid sulfate soils (706 ± 79 gm−2 day−1, average for both thermally active and cold degassing sites) with lower diffuse CO2 flux in travertine (189 ± 98 gm−2 day−1) and neutral-chloride (19 ± 8 gm−2 day−1) soils. All cold degassing sites measured were in acid sulfate dominated soil chemistries. The average diffuse CO2 flux for these cold degassing sites was higher (840 ± 163 gm−2 day−1) than the average flux through acid sulfate soils in thermally active basins (625 ± 79 gm−2 day−1). We also measured the carbon isotope composition of diffuse CO2 soil gas samples from most sites to characterize the potential source(s) of these emissions. The majority of carbon isotope values from cold degassing sites are within the typical range of values for Yellowstone fumaroles. This suggests that cold degassing sites have a similar magmatic source for diffuse CO2.Previous calculations of the total daily diffuse CO2 emitted through Yellowstone National Park use the arithmetic average flux per soil chemistry and extrapolate that value across the entire park using only thermally active altered soils. Instead, we calculate the total CO2 flux per site in tons CO2 per km2 per day using Gaussian Geostatistical Simulations through the Geostatistical Analyst toolbox in ArcGIS. To account for the large component of cold degassing CO2, we extrapolate the average emission rate per soil chemistry to all hydrothermally altered soils rather than only thermally active soils across the entire area of Yellowstone National Park. We calculate a total deeply sourced (biogenic flux removed) CO2 flux of 24 ± 12 kt CO2 per day, with nearly two-thirds of that flux estimated to be from cold degassing acid sulfate soils. Cold diffuse degassing sites can be significant sources of magmatic carbon emissions and this has implications for the relationship between the flux of CO2 and heat as well as for global contributions from mantle CO2 emissions.

Assessment of urban CO2 budget: Anthropogenic and biogenic inputs

Understanding combinations of biogenic and anthropogenic inputs, and dynamics of carbon dioxide (CO2) fluxes in the urban environment is critical to investigate feedback between carbon cycle and climate system. The main objectives of this study are to analyse the role and interactions of anthropogenic and biogenic CO2 emission sources and sinks in the total carbon cycle within city limits, determine processes controlling urban ecosystem-atmosphere gas exchange under varying environmental conditions with a high temporal and spatial resolution.The research addressing this issue was carried out in Wroclaw, the fourth largest city in Poland, throughout the year from July 2017 to August 2018. Chamber measurements of surface-atmosphere CO2 and CO2 net fluxes across various types of land cover (grassland, city park and arable land) provided the basis for assessing biogenic component of the urban C budget. In particular, the approach applied Picarro CRDS (cavity ring-down spectroscopy) technique with model G2201-I. Anthropogenic C fluxes were reported based on local statistical datasets and existing emission inventories, as well as the Low Emission Economy Plan from the Wroclaw urban area.The findings showed that biogenic fluxes, over the course of one year, accounted for about 16.3% (RESP = 0.68 Mton CO2·yr−1) of the total city carbon emissions for Wroclaw, being entirely compensated by local vegetation C uptake (GEE = −0.89 Mt. CO2·yr−1). Compared to fluxes given by the previously reported emission inventory, the net biogenic CO2 sink (NEE) of 0.201 Mt. CO2·yr−1 was substantially greater, which indicates that the biosphere in Wroclaw is a net biogenic C sink. The average annual C budget in Wroclaw, obtained from the investigation of sectoral emission trends including those related to energy, road traffic, industrial processes, and other fluxes (human respiration), reaches about 3.87 kg C·m−2·yr−1.

Atmospheric Deposition Promotes Relative Abundances of High‐Dimethylsulfoniopropionate Producers in the Western North Pacific

AbstractHaptophytes and Dinoflagellates are two cosmopolitan algae associated with dimethylsulfoniopropionate (DMSP) synthesis, which regulates the marine biogenic flux of DMS to the atmosphere with potential effects on global climate. Attempting to reveal the potential impact of atmospheric deposition on the growth of high‐DMSP producers, four bioassay experiments were conducted in the western North Pacific (WNP) by adding aerosols, nutrients, and trace metals. Our results showed that the percentage of high‐DMSP producers increased substantially from coastal seas (<1%) to the open ocean (∼17%) with the dominance of Dinophyceae and Haptophyceae, respectively. Aerosol additions largely increased the percentage of high‐DMSP producing species in the subtropical gyre of WNP. Specifically, atmospheric dissolved inorganic nitrogen, soluble Cu and Fe promoted Dinophyceae taxa, Chrysochromulina, and Phaeocystis and E. huxleyi, respectively. It is very likely that atmospheric deposition could lift the relative abundance of high‐DMSP producers in the vast oligotrophic oceans and potentially contribute to the climate change.