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The paper reviews and evaluates a 30-year-long atmospheric CO2 data series measured at the Hegyhátsál tall-tower greenhouse gas monitoring site, a member of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW), US National Oceanic and Atmospheric Administration (NOAA), and pan-European Integrated Carbon Observation System (ICOS) networks. The paper also gives the technical description of the monitoring system and its changes over time and introduces the environment of the station. This low-elevation (248 m above mean sea level – m a.m.s.l.), mid-continental central European site shows a 3.90 ± 0.83 µmolmol-1 offset relative to the latitudinally representative marine boundary layer reference concentration, presumably due to European net anthropogenic emissions. The long-term trend (2.20 µmolmol-1yr-1) closely follows the global tendencies. In the concentration growth rate, the ENSO effect is clearly detectable with a 6–7-month lag time. The summer diurnal concentration amplitude is slightly decreasing due to the faster-than-average increase in the nighttime concentrations, which is related to the warming climate. The warming climate also caused a 0.96 ± 0.41 dyr-1 advance at the beginning of the summer CO2 -deficit season in the first half of the measurement period, which did not continue later. The summer CO2 -deficit season was extended by 9.0 ± 6.1 d during the measurement period. [ABSTRACT FROM AUTHOR]

Atmospheric emissions from anthropogenic hotspots, i.e., cities, power plants and industrial facilities, can be determined from remote sensing images obtained from airborne and space-based imaging spectrometers. In this paper, we present a Python library for data-driven emission quantification (ddeq) that implements various computationally light methods such as the Gaussian plume inversion, cross-sectional flux method, integrated mass enhancement method and divergence method. The library provides a shared interface for data input and output and tools for pre- and post-processing of data. The shared interface makes it possible to easily compare and benchmark the different methods. The paper describes the theoretical basis of the different emission quantification methods and their implementation in the ddeq library. The application of the methods is demonstrated using Jupyter notebooks included in the library, for example, for NO 2 images from the Sentinel-5P/TROPOMI satellite and for synthetic CO 2 and NO 2 images from the Copernicus CO 2 Monitoring (CO2M) satellite constellation. The library can be easily extended for new datasets and methods, providing a powerful community tool for users and developers interested in emission monitoring using remote sensing images. [ABSTRACT FROM AUTHOR]

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE Project (Spruce and Peatland Responses Under Climatic and Environmental Change, http: //mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Oce of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are: 1. Data acquisition and control system - set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components. 2. Data collection system - set of hardware and software to deliver data to a central depository for storage and further processing. 25 3. Data management plan - set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an eficient data system for managing high volume sources of in-situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data. [ABSTRACT FROM AUTHOR]

The knowledge of Green House Gases GHGs fluxes at the air--sea interface at high resolution is crucial to accurately quantify the role of the ocean in the absorption and emission of GHGs. In this paper we present a novel method to reconstruct maps of surface ocean partial pressure of CO2, pCO2, and air--sea CO2 fluxes at super resolution (4 km) using Sea Surface Temperature (SST) and Ocean Colour (OC) data at this resolution, and CarbonTracker CO2 fluxes data at low resolution (110 km). Inference of super-resolution of pCO2, and air--sea CO2 fluxes is performed using novel nonlinear signal processing methodologies that prove efficient in the context of oceanography. The theoretical background comes from the Microcanonical Multifractal Formalism which unlocks the geometrical determination of cascading properties of physical intensive variables. As a consequence, a multiresolution analysis performed on the signal of the so-called singularity exponents allows the correct and near optimal cross-scale inference of GHGs fluxes, as the inference suits the geometric realization of the cascade. We apply such a methodology to the study offshore of the Benguela area. The inferred representation of oceanic partial pressure of CO2 improves and enhances the description provided by CarbonTracker, capturing the small scale variability. We examine different combinations of Ocean Colour and Sea Surface Temperature products in order to increase the number of valid points and the quality of the inferred pCO2 field. The methodology is validated using in-situ measurements by means of statistical errors. We obtain that mean absolute and relative errors in the inferred values of pCO2 with respect to in-situ measurements are smaller than for CarbonTracker. [ABSTRACT FROM AUTHOR]

Physical soil properties create lags between temperature change and corresponding soil responses, which obscure true Q10 values and other biophysical parameters such as depth of production. This study examines an inversion approach for estimating Q10 and depth of production (Zp) using physically based soil models, constrained by observed high-frequency surface fluxes and/or concentrations. Our inversion strategy uses a 1-D multi-layered soil model that simulates realistic temperature and gas diffusion. We tested inversion scenarios on synthetic data using a range of constraining parameters, time averaging techniques, mechanisms to improve computational efficiency, and various methods of incorporating real data into the model. Overall, we have found that with carefully constrained data, inversion was possible. While inversions using exclusively surface flux measurements could succeed, constraining the inversion using multiple shallow subsurface CO2 measurements proved to be most successful. Inversions constrained by these shallow measurements returned Q10 and Zp values with average errors of 1.85 and 0.16 % respectively. This work is a first step toward building a reliable framework for removing physical effects from high frequency soil CO2 data. Ultimately, we hope that this process will lead to better estimates of biophysical soil parameters and their variability on short timescales. [ABSTRACT FROM AUTHOR]

Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks at sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote-sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Lund-Potsdam-Jena dynamic global vegetation model (LPJ), the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations and an assimilation method for incorporating the ground sample plots into LPJ. The validation results indicated that both the data fusion and data assimilation approaches reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high accuracy surface modeling to fuse the ground sample plots with the satellite observations (HASM-SOA). The estimates produced with HASM-SOA were 26.1 and 28.4% more accurate than the satellite-based approach and spatial interpolation of the sample plots, respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-SOA method. [ABSTRACT FROM AUTHOR]

Laser Absorption Spectroscopy (LAS) has been used over the last several decades for the measurement of trace gasses in the atmosphere. For over a decade, LAS measurements from multiple sources and tens of retroreflectors have been combined with sparse-sample tomography methods to estimate the 2-D distribution of trace gas concentrations and underlying fluxes from pointlike sources. In this work, we consider the ability of such a system to detect and estimate the position and rate of a single point leak which may arise as a failure mode for carbon dioxide storage. The leak is assumed to be at a constant rate giving rise to a plume with a concentration and distribution that depend on the wind velocity. We demonstrate the ability of our approach to detect a leak using numerical simulation and a preliminary measurement. [ABSTRACT FROM AUTHOR]

The annual average CO2 difference between baseline data from Mauna Loa and the southern Hemisphere increased by ~ 0.8 µmolmol-1 (0.8 ppm) between 2009 and 2010, a step unprecedented in over 50 years of reliable data. We find no evidence for coinciding, sufficiently large and rapid, source/sink changes. A statistical anomaly is unlikely due to the highly systematic nature of the variation in observations. An explanation for the step, and the subsequent 5 year stability in this north-south difference, involves inter-hemispheric atmospheric exchange variation. The selected data describing this episode provide a critical test for studies that employ atmospheric transport models that interpret global carbon budgets and inform management of anthropogenic emissions. [ABSTRACT FROM AUTHOR]

Distributions of surface water partial pressure of carbon dioxide (pCO2) were measured on nine cruises in the Delaware Estuary (USA). The Delaware River was highly supersaturated in pCO2 with respect to the atmosphere during all seasons while the Delaware Bay was undersaturated in pCO2 during spring and late summer and moderately supersaturated during midsummer, fall, and winter. While the upper tidal river was a strong CO2 source (24.6 ± 2.2 mol C m-2 year-1), the bay was a weak source (1.8 ± 0.2 mol C m-2 year-1), the latter of which had a much greater area than the former. In turn, the Delaware Estuary acted as a relatively weak CO2 source (2.4 ± 0.3 mol C m-2 year-1), which is in great contrast to many other estuarine systems. Seasonally, pCO2 changes were greatest at low salinities (0 = S< 5) with pCO2 values in the summer nearly three-fold greater than those observed in the spring and fall. Undersaturated pCO2 was observed over the widest salinity range (7.5 = S< 30) during spring. Near to supersaturated pCO2 was generally observed in mid- to high salinity waters (20 = S< 30) except during spring and late summer. Strong seasonal trends in internal estuarine production and consumption of CO2 were observed throughout both the upper tidal river and lower bay. Comparably, positive correlations between river-borne and air-water CO2 fluxes in the upper estuary emphasize the significance of river-borne CO2 degassing to overall CO2 fluxes. While river-borne CO2 degassing heavily influenced CO2 dynamics in the upper tidal river, these forces were largely compensated by internal biological processes within the extensive bay system of the lower estuary. [ABSTRACT FROM AUTHOR]

Soil carbon stored in high-latitude permafrost landscapes is threatened by warming, and could contribute significant amounts of carbon to the atmosphere and hydrosphere as permafrost thaws. Permafrost disturbances, especially active layer detachments and retrogressive thaw slumps, have increased in frequency and magnitude across the Fosheim Peninsula, Ellesmere Island, Canada. To determine the effects of retrogressive thaw slumps on net ecosystem exchange (NEE) of CO2 in high Arctic tundra, we used two eddy covariance (EC) tower systems to simultaneously and continuously measure CO2 fluxes from a disturbed site and the surrounding undisturbed tundra. During the 32-day measurement period in the 2014 growing season the undisturbed tundra was a small net sink (NEE = −0.12 g C m-2 d-1); however, the disturbed terrain of the retrogressive thaw slump was a net source (NEE = +0.39 g C m-2 d-1). Over the measurement period, the undisturbed tundra sequestered 3.84 g C m-2, while the disturbed tundra released 12.48 g C m-2. Before full leaf out in early July, the undisturbed tundra was a small source of CO2, but shifted to a sink for the remainder of the sampling season (July), whereas the disturbed tundra remained a source of CO2 throughout the season. A static chamber system was also used to measure fluxes in the footprints of the two towers, in both disturbed and undisturbed tundra, and fluxes were partitioned into ecosystem respiration (Re) and gross primary production (GPP). Average GPP and Re found in disturbed tundra were smaller (+0.41 μmol m-2 s-1 and +0.50 μmol m-2 s-1, respectively) than those found in undisturbed tundra (+1.21 μmol m-2 s-1 and +1.00 μmol m-2 s-1, respectively). Our measurements indicated clearly that the permafrost disturbance changed the high Arctic tundra system from a sink to a source for CO2 during the growing season. [ABSTRACT FROM AUTHOR]

Stratospheric profiles of methane (CH4) and carbon dioxide (CO2) have been derived from solar occultation measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The retrieval is performed using a method called "Onion Peeling DOAS" (ONPD) which combines an onion peeling approach with a weighting function DOAS (Differential Optical Absorption Spectroscopy) fit. By use of updated pointing information and optimisation of the data selection and of the retrieval approach the altitude range for reasonable CH4 could be extended to about 17 to 45 km. Furthermore, the quality of the derived CO2 has been assessed such that now the first stratospheric profiles of CO2 from SCIAMACHY are available. Comparisons with independent data sets yield an estimated accuracy of the new SCIAMACHY stratospheric profiles of about 5-10 % for CH4 and 2-3 % for CO2. The accuracy of the products is currently mainly restricted by the appearance of unexpected vertical oscillations in the derived profiles which need further investigation. Using the improved ONPD retrieval, CH4 and CO2 stratospheric data sets covering the whole SCIAMACHY time series (August 2002-April 2012) and the latitudinal range between about 50 and 70° N have been derived. Based on these time series, CH4 and CO2 trends have been estimated, which are in reasonable agreement with total column trends for these gases. This shows that the new SCIAMACHY data sets can provide valuable information about the stratosphere. [ABSTRACT FROM AUTHOR]

The closed chamber technique is widely used to measure the exchange of methane (CH4) and carbon dioxide (CO2) from terrestrial ecosystems. There is, however, large uncertainty about which model should be used to calculate the gas flux from the measured gas concentrations. Due to experimental uncertainties the robust linear regression model (first order polynomial) is often applied, even though theoretical considerations of the technique suggest the application of other, curvilinear models. High-resolution automatic chamber systems which sample gas concentrations several hundred times per flux measurement make it possible to resolve the curvilinear behavior and study the information imposed by the natural variability of the temporal concentration changes. We used more than 50 000 such flux measurements of CH4 and CO2 from five field sites located in peat forming wetlands to calculate fluxes with different models. The flux differences from independent linear estimates are generally found to be smaller than the local flux variability on the plot scale. The curvilinear behavior of the gas concentrations within the chamber is strongly influenced by wind driven chamber leakage, and less so by changing gas concentration gradients in the soil during chamber closure. Such physical processes affect both gas species equally, which makes it possible to isolate biochemical processes affecting the gases differently, such as photosynthesis limitation by chamber headspace CO2 concentrations under high levels of incoming solar radiation. We assess the possibility to exploit this effect for a partitioning of the net CO2 flux into photosynthesis and ecosystem respiration and argue that high-resolution automatic chamber measurements could be used for purposes beyond the estimation of the net gas flux. [ABSTRACT FROM AUTHOR]

Climatologies, which depict mean fields of oceanographic variables on a regular geographic grid, and atlases, which provide graphical depictions of specific areas, play pivotal roles in comprehending the societal vulnerabilities linked to ocean acidification (OA). This significance is particularly pronounced in coastal regions where most economic activities, such as commercial and recreational fisheries and aquaculture industries, occur. In this paper, we unveil a comprehensive data product featuring coastal ocean acidification climatologies and atlases, encompassing the fugacity of carbon dioxide, pH on the total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle factor, total dissolved inorganic carbon content, and total alkalinity content. These variables are provided on 1° × 1° spatial grids at 14 standardized depth levels, ranging from the surface to a depth of 500 m, along the North American ocean margins, defined as the region between the coastline and a distance of 200 nautical miles (∼370 km) offshore. The climatologies and atlases were developed using the World Ocean Atlas (WOA) gridding methods of the NOAA National Centers for Environmental Information (NCEI) based on the recently released Coastal Ocean Data Analysis Product in North America (CODAP-NA), along with the 2021 update to the Global Ocean Data Analysis Project version 2 (GLODAPv2.2021) data product. The relevant variables were adjusted to the index year of 2010. The data product is available in NetCDF (https://doi.org/10.25921/g8pb-zy76 , Jiang et al., 2022b) on the NOAA Ocean Carbon and Acidification Data System: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0270962.html (last access: 15 July 2024). It is recommended to use the objectively analyzed mean fields (with "_an" suffix) for each variable. The atlases can be accessed at https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/synthesis/nacoastal.html (last access: 15 July 2024). [ABSTRACT FROM AUTHOR]

Previous research has shown that stratospheric aerosol causes only a small temperature change per unit forcing because they produce stronger cooling in the tropical Indian Ocean and the western Pacific Ocean than in the global mean. The enhanced temperature change in this so-called "warm-pool" region activates strongly negative local and remote feedbacks, which dampen the global mean temperature response. This paper addresses the question of why stratospheric aerosol forcing affects warm-pool temperatures more strongly than CO 2 forcing, using idealized MPI-ESM simulations. We show that the aerosol's enhanced effective forcing at the top of the atmosphere (TOA) over the warm pool contributes to the warm-pool-intensified temperature change but is not sufficient to explain the effect. Instead, the pattern of surface effective forcing, which is substantially different from the effective forcing at the TOA, is more closely linked to the temperature pattern. Independent of surface temperature changes, the aerosol heats the tropical stratosphere, accelerating the Brewer–Dobson circulation. The intensified Brewer–Dobson circulation exports additional energy from the tropics to the extratropics, which leads to a particularly strong negative forcing at the tropical surface. These results show how forced circulation changes can affect the climate response by altering the surface forcing pattern. Furthermore, they indicate that the established approach of diagnosing effective forcing at the TOA is useful for global means, but a surface perspective on the forcing must be adopted to understand the evolution of temperature patterns. [ABSTRACT FROM AUTHOR]

Ocean acidification is a predictable consequence of rising atmospheric carbon dioxide (CO2), and is highly likely to impact the entire marine ecosystem - from plankton at the base to fish at the top. Factors which are expected to be impacted include reproductive health, organism growth and species composition and distribution. Predicting when critical threshold values will be reached is crucial for projecting the future health of marine ecosystems and for marine resources planning and management. The impacts of ocean acidification will be first felt at the seasonal scale, however our understanding how seasonal variability will influence rates of future ocean acidification remains poorly constrained due to current model and data limitations. To address this issue, we first quantified the seasonal cycle of aragonite saturation state utilizing new data-based estimates of global ocean surface dissolved inorganic carbon and alkalinity. This seasonality was then combined with earth system model projections under different emissions scenarios (RCPs 2.6, 4.5 and 8.5) to provide new insights into future aragonite under-saturation onset. Under a high emissions scenario (RCP 8.5), our results suggest accounting for seasonality will bring forward the initial onset of month-long undersaturation by 17 years compared to annual-mean estimates, with differences extending up to 35 ± 17 years in the North Pacific due to strong regional seasonality. Our results also show large-scale under-saturation once atmospheric CO2 reaches 486 ppm in the North Pacific and 511 ppm in the Southern Ocean independent of emission scenario. Our results suggest that accounting for seasonality is critical to projecting the future impacts of ocean acidification on the marine environment. [ABSTRACT FROM AUTHOR]

A new coastal background site has been established for observations of greenhouse gases (GHGs) in the central Namib Desert at Gobabeb, Namibia. The location of the site was chosen to provide observations for a data-poor region in the global sampling network for GHGs. Semi-automated, continuous measurements of carbon dioxide, methane, nitrous oxide, carbon monoxide, atmospheric oxygen, and basic meteorology are made at a height of 21ma.g.l., 50 km from the coast at the northern border of the Namib Sand Sea. Atmospheric oxygen is measured with a differential fuel cell analyzer (DFCA). Carbon dioxide and methane are measured with an early-model cavity ring-down spectrometer (CRDS); nitrous oxide and carbon monoxide are measured with an off-axis integrated cavity output spectrometer (OA-ICOS). Instrument-specific water corrections are employed for both the CRDS and OA-ICOS instruments in lieu of drying. The performance and measurement uncertainties are discussed in detail. As the station is located in a remote desert environment, there are some particular challenges, namely fine dust, high diurnal temperature variability, and minimal infrastructure. The gas handling system and calibration scheme were tailored to best fit the conditions of the site. The CRDS and DFCA provide data of acceptable quality when base requirements for operation are met, specifically adequate temperature control in the laboratory and regular supply of electricity. In the case of the OA-ICOS instrument, performance is significantly improved through the implementation of a drift correction through frequent measurements of a working tank. [ABSTRACT FROM AUTHOR]

Planetary boundary layer (PBL) CO2 mole fraction data are needed by transport models and carbon budget models as both input and reference for validation. The height of in situ CO2 mole fraction measurements is usually different from that of the model levels where the data are needed; data from short towers, in particular, are dificult to utilize in atmospheric models that do not simulate the surface layer well. Tall tower CO2 mole fraction measurements observed at heights ranging from to 115ma.g.l. at a rural site in Hungary and regular airborne vertical mole fraction profile measurements (136 vertical profiles) above the tower allowed us to estimate how well a tower of a given height could estimate the CO2 mole fraction above the tower in the PBL. The statistical evaluation of the height-dependent bias between the real PBL CO2 mole fraction profile (measured by the aircraft) and the measurement at a given elevation above the ground was performed separately for the summer and winter half years to take into account the different dynamics of the lower troposphere and the different surface CO2 flux in the dif15 ferent seasons. The paper presents: (1) how accurately the vertical distribution of CO2 in the PBL can be estimated from the measurements on the top of a tower of height H, (2) how tall a tower would be needed for the satisfaction of different requirements on the accuracy of the estimation of the CO2 vertical distribution, (3) how accurate a CO2 vertical distribution estimation can be expected from the existing towers; and (4) how much improvement can be achieved in the accuracy of the estimation of CO2 vertical distribution applying the virtual tall tower concept. [ABSTRACT FROM AUTHOR]

The northern Scotia Sea contains the largest seasonal uptake of atmospheric carbon dioxide yet measured in the Southern Ocean. This study examines one of the main routes by which this carbon fluxes to the deep ocean, through the production of faecal pellets (FPs) by the zooplankton community. Deep sediment traps were deployed in two sites with contrasting ocean productivity regimes (P3, naturally iron-fertilized and P2, iron-limited), within the same water mass. The magnitude and seasonal pattern of particulate organic carbon (POC) and FPs in the traps was markedly different between the two sites. Maximum fluxes at P3 (22.91mgCm-2 d-1; 2534x10 FPm-2 d-1 ) were an order of magnitude higher than at P2 (4.01mgCm-2 d-1 ; 915x10 FPm-2 d-1), with flux at P3 exhibiting a double seasonal peak, compared to a single flatter peak at P2. The maximum contribution of FP carbon to the total amount of POC was twice as high at P3 (91%) compared to P2 (40%). The dominant FP category at P3 varied between round, ovoidal, cylindrical and tabular over the course of the year while, at P2, ovoidal FPs were consistently dominant, always making up more than 60% of the FP assemblage. There was also a difference in the FP state between the two sites, with FPs being relatively intact at P3, while FPs were often fragmented with broken peritrophic membranes at P2. The exception was ovoidal FPs, which were relatively intact at both sites. Our observations suggest that there was community shift from an herbivorous to an omnivorous diet from spring through to autumn at P3 while detritivores had a higher relative importance over the year at P2. Furthermore, the flux was mainly a product of the vertically migrating zooplankton community at P3 while the FP flux was more likely to be generated by deeper-dwelling zooplankton feeding on recycled material at P2. The results demonstrate that the feeding behavior and vertical distribution of the zooplankton community plays a critical role in controlling the magnitude of carbon export to the deep ocean in this region. [ABSTRACT FROM AUTHOR]

Accurately monitoring tropical forest carbon stocks is an outstanding challenge. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference in the coming years. However, this reference model shows a systematic bias for the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass dataset on 673 trees measured in five tropical countries (101 trees > 100 cm in diameter) and an original dataset of 130 forest plots (1 ha) from central Africa to quantify the error of biomass allometric models at the individual and plot levels when explicitly accounting or not accounting for crown mass variations. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88%. This proportion was constant on average for trees < 10 Mg (mean of 34%) but, above this threshold, increased sharply with tree mass and exceeded 50% on average for trees = 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Accounting for a crown mass proxy in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error from -23-16 to 0-10%. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by accounting for a crown mass proxy for the largest trees in a stand, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost. [ABSTRACT FROM AUTHOR]

The management of agroecosystems plays a crucial role in the global carbon cycle with soil tillage leading to known organic carbon redistributions within soils and changes in soil CO2 emissions. Yet, discrepancies exist on the impact of tillage on soil CO2 emissions and on the main soil and environmental controls. A meta-analysis was conducted using 46 peer-reviewed publications totaling 174 paired observations comparing CO2 emissions over entire seasons or years from tilled and untilled soils across different climates, crop types and soil conditions with the objective of quantifying tillage impact on CO2 emissions and assessing the main controls. On average, tilled soils emitted 21% more CO2 than untilled soils, which corresponded to a significant difference at P < 0.05. The difference increased to 29% in sandy soils from arid climates with low soil organic carbon content (SOCC < 1%) and low soil moisture, but tillage had no impact on CO2 fluxes in clayey soils with high background SOCC (> 3%). Finally, nitrogen fertilization and crop residue management had little effect on the CO2 responses of soils to no-tillage. These results suggest no-tillage is an effective mitigation measure of carbon dioxide losses from dry land soils. They emphasize the importance of including information on soil factors such as texture, aggregate stability and organic carbon content in global models of the carbon cycle. [ABSTRACT FROM AUTHOR]

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation. Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation -wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations comprise Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models using two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs), sensitivity tests for the effect of climate and CO2, as well as a sensitivity analysis using two alternative parameteri-sations of the semi-empirical burned-area model. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load, and faster litter turnover in a warmer climate. [ABSTRACT FROM AUTHOR]

Stream networks were recently discovered as major but poorly constrained natural greenhouse gas (GHG) sources. A fundamental problem is that several measurement approaches have been used without cross comparisons. Flux chambers represent a potentially powerful methodological approach if robust and reliable ways 5 to use chambers on running water can be defined. Here we compare the use of anchored and freely drifting chambers on various streams having different flow velocities. The study clearly shows that (1) drifting chambers have a very small impact on the water turbulence under the chamber and thus generate more reliable fluxes, (2) anchored chambers enhance turbulence under the chambers and thus elevate fluxes, (3) the bias of the anchored chambers greatly depends on chamber design and sampling conditions, and (4) there is a promising method to reduce the bias from anchored chambers by using a flexible plastic foil seal to the water surface rather than having rigid chamber walls penetrating into the water. Altogether, these results provide novel guidance on how to apply flux chambers in running water, which will have important consequences for measurements to constrain the global GHG balances. [ABSTRACT FROM AUTHOR]

Gross primary production (GPP), separated from flux tower measurements of net ecosystem exchange (NEE) of CO2, is used increasingly to validate process-based simulators and remote sensing-derived estimates of simulated GPP at various time steps. Proper validation should include the uncertainty associated with this separation at different time steps. This can be achieved by using a Bayesian framework. In this study, we estimated the uncertainty in GPP at half hourly time steps. We used a nonrectangular hyperbola (NRH) model to separate GPP from flux tower measurements of NEE at the Speulderbos forest site, The Netherlands. The NRH model included the variables that influence GPP, in particular radiation, and temperature. In addition, the NRH model provided a robust empirical relationship between radiation and GPP by including the degree of curvature of the light response curve. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. Adopting a Bayesian approach, we defined the prior distribution of each NRH parameter. Markov chain Monte Carlo (MCMC) simulation was used to update the prior distribution of each NRH parameter. This allowed us to estimate the uncertainty in the separated GPP at half-hourly time steps. This yielded the posterior distribution of GPP at each half hour and allowed the quantification of uncertainty. The time series of posterior distributions thus obtained allowed us to estimate the uncertainty at daily time steps. We compared the informative with non-informative prior distributions of the NRH parameters. The results showed that both choices of prior produced similar posterior distributions GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications. [ABSTRACT FROM AUTHOR]

Recently, it has been proposed that alkalinity release from sediments can play an important role in the carbonate dynamics on continental shelves, lowering the pCO2 of seawater and hence increasing the CO2 uptake from the atmosphere. To test this hypothesis, sedimentary alkalinity generation was quantified within permeable and muddy sediments across the North Sea during two cruises in September 2011 (basinwide) and June 2012 (Dutch coastal zone). Benthic fluxes of alkalinity (AT) and dissolved inorganic carbon (DIC) were determined using shipboard closed sediment incubations. These results show that sediments can be an important source for alkalinity, particularly in the shallow southern North Sea, where high AT and DIC fluxes were recorded in near shore sediments of the Belgian, Dutch and German coastal zone. In contrast, fluxes of AT and DIC are substantially lower in the deeper, seasonally stratified, northern part of the North Sea. Overall, our results show that sedimentary alkalinity generation should be considered an important factor in the CO2 dynamics of shallow coastal systems. [ABSTRACT FROM AUTHOR]

Ocean acidification (OA) is likely to have an effect on the fertilizing potential of desert dust in high-nutrient, low-chlorophyll oceanic regions, either by modifying Fe speciation and bioavailability, or by altering phytoplankton Fe requirements and acquisition. To address this issue, short incubations (4 days) of northeast subarctic Pacific waters enriched with either FeSO4 or dust, and set at pH 8.0 (in situ) and 7.8 were conducted in August 2010. We assessed the impact of a decrease in pH on dissolved Fe concentration, phytoplankton biomass, taxonomy and productivity, and the production of dimethylsulfide (DMS) and its algal precursor dimethylsulfoniopropionate (DMSP). Chlorophyll a (chl a) remained unchanged in the controls and doubled in both the FeSO4-enriched and dust-enriched incubations, confirming the Fe-limited status of the plankton assemblage during the experiment. In the acidified treatments, a significant reduction (by 16-38%) of the final concentration of chl a was measured compared to their non-acidified counterparts, and a 15% reduction in particulate organic carbon (POC) concentration was measured in the dust-enriched acidified treatment compared to the dust-enriched non-acidified treatment. FeSO4 and dust additions had a fertilizing effect mainly on diatoms and cyanobacteria. Lowering the pH affected mostly the haptophytes, but pelagophyte concentrations were also reduced in some acidified treatments. Acidification did not significantly alter DMSP and DMS concentrations. These results show that dust deposition events in a low-pH iron-limited Northeast subarctic Pacific are likely to stimulate phytoplankton growth to a lesser extent than in today's ocean during the few days following fertilization and point to a low initial sensitivity of the DMSP and DMS dynamics to OA. [ABSTRACT FROM AUTHOR]

The Kolyma River in Northeast Siberia is among the six largest arctic rivers and drains a region underlain by vast deposits of Holocene-aged peat and Pleistocene-aged loess known as yedoma, most of which is currently stored in ice-rich permafrost throughout the region. These peat and yedoma deposits are important sources of dissolved organic matter (DOM) to inland waters that in turn play a significant role in the transport and ultimate remineralization of organic carbon to CO2 and CH4 along the terrestrial flow-path continuum. The turnover and fate of terrigenous DOM during offshore transport will largely depend upon the composition and amount of carbon released to inland and coastal waters. Here, we measured the optical properties of chromophoric DOM (CDOM) from a geographically extensive collection of waters spanning soil pore waters, streams, rivers, and the Kolyma River mainstem throughout a 250 km transect of the northern Kolyma River basin. During the period of study, CDOM absorbance values were found to be robust proxies for the concentration of DOM, whereas additional CDOM parameters such as spectral slopes (S) were found to be useful indicators of DOM quality along the flow-path. In particular, CDOM absorption at 254nm showed a strong relationship with dissolved organic carbon (DOC) concentrations across all water types (r2 = 0.958,p < 0.01). The spectral slope ratio (SR) of CDOM demonstrated statistically significant differences between all four water types and tracked changes in the concentration of bioavailable DOC, suggesting that this parameter may be suitable for clearly discriminating shifts in organic matter characteristics among water types along the full flow-path continuum across this landscape. The heterogeneity of environmental characteristics and extensive continuous permafrost of the Kolyma River basin combine to make this a critical region to investigate and monitor. With ongoing and future permafrost degradation, peat and yedoma deposits throughout the Northeast Siberian region will become more hydrologically active, providing greater amounts of DOM to fluvial networks and ultimately to the Arctic Ocean. The ability to rapidly and comprehensively monitor shifts in the quantity and quality of DOM across the landscape is therefore critical for understanding potential future feedbacks on the arctic carbon cycle. [ABSTRACT FROM AUTHOR]

Global warming has accelerated the formation of permafrost thaw ponds in several subarctic and arctic regions. These ponds are net heterotrophic as evidenced by their greenhouse gas (GHG) supersaturation levels (CO2 and CH4), and generally receive large terrestrial carbon inputs from the thawing and eroding permafrost. We measured seasonal and vertical variations in the concentration and type of dissolved organic matter (DOM) in five subarctic thaw (thermokarst) ponds in northern Quebec, and explored how environmental gradients influenced heterotrophic and phototrophic biomass and productivity. Late winter DOM had low aromaticity indicating reduced inputs of terres trial carbon, while the high concentration of dissolved organic carbon (DOC) suggests that some production of non-chromophoric dissolved compounds by the microbial food web took place under the ice cover. Summer DOM had a strong terrestrial signature, but was also characterized with significant inputs of algal-derived carbon, especially at the pond surface. During late winter, bacterial production was low (maximum of 0.8mgCm-3 d-1) and was largely based on free-living bacterioplankton (58%). Bacterial production in summer was high (up to 58mgCm3 d1), dominated by particleattached bacteria (67%), and strongly correlated to the amount of terrestrial carbon. Primary production was restricted to summer surface waters due to strong light limitation deeper in the water column or in winter. The phototrophic biomass was equal to the heterotrophic biomass, but as the algae were mostly composed of mixotrophic species, most probably they used bacteria rather than solar energy in such shaded ponds. According to the δ13C analyses, non-algal carbon supported 51% of winter and 37% of summer biomass of the phantom midge larvae, Chaoborus sp., that are at the top of the trophic chain. Our results point to a strong heterotrophic energy pathway 25 in these thaw pond ecosystems, where bacterioplankton dominates the production of new carbon in both summer and winter. [ABSTRACT FROM AUTHOR]

As an important component of ecosystem carbon budgets, soil carbon dioxide (CO2) flux is determined by a combination of a series of biotic and abiotic processes. Although there is evidence that the abiotic component can be important in total soil CO2 flux, its relative importance has never been systematically assessed. In this study, the total soil CO2 flux (Rtotal) was partitioned into biotic (Rbiotic) and abiotic (Rabiotic) components over eight typical landscapes in a desert-oasis ecotone, including cotton field, hops field, halophyte garden, reservoir edge, native saline desert, alkaline soil, dune crest and interdune lowland in the Gurbantunggut Desert, and the relative importance of these two components was analyzed. Results showed that Rabiotic always contributed to Rtotal for the eight landscapes, but the degree of contribution varied greatly. In the cotton and hops fields, the ratio of Rabiotic to Rtotal was extremely low (< 10%); whereas Rabiotic was dominant in the alkaline soil and dune crest. Statistically, Rabiotic=Rtotal decreased logarithmically with rising Rbiotic, suggesting that Rabiotic strongly affected Rtotal when Rbiotic was low. This pattern confirms that soil CO2 flux is predominantly biological in most ecosystems, but Rabiotic can dominate when biological processes are weak. On a diurnal basis, Rabiotic resulted in no net gain or loss of carbon but its effect on instantaneous CO2 flux was significant. Temperature dependence of Rtotal varied among the eight landscapes, determined by the predominant components of CO2 flux: with Rbiotic driven by soil temperature and Rabiotic regulated by the rate of change in temperature. Namely, declining temperature resulted in negative Rabiotic (CO2 went into soil), while rising temperature resulted in a positive Rabiotic (CO2 released from soil). Furthermore, without recognition of Rabiotic, Rbiotic would have been either overestimated (for daytime) or underestimated (for nighttime). Thus, recognition that abiotic component in total soil CO2 flux is ubiquitous in soils has widespread consequences for the understanding of carbon cycling. While the abiotic flux will not change net daily soil CO2 exchange and not likely directly constitute a carbon sink, it can alter transient soil CO2 flux significantly, either in magnitude or in its temperature dependency. [ABSTRACT FROM AUTHOR]

The Geostationary Emission Explorer for Europe (G3E) is a concept for a geostationary satellite sounder that targets at constraining the sources and sinks of the greenhouse gases carbon dioxide (CO2) and methane (CH4) for continental-scale regions. Thereby, its primary focus is on Central Europe. G3E carries a spectrometer system that collects sunlight backscattered from the Earth's surface and atmosphere in the near-infrared (NIR) and shortwave-infrared (SWIR) spectral range. Solar absorption spectra allow for spatiotemporally dense observations of the column-average concentrations of carbon dioxide (XCO2), methane (XCH4), and carbon monoxide (XCO) including sampling of the diurnal variation with several measurements per day during summer. Here, we present the mission concept and carry out an initial performance assessment of the retrieval capabilities. The radiometric performance of the 4 grating spectrometers is tuned to reconcile small ground-pixel sizes (~ 2 km × 3 km at 50° latitude) with short single-shot exposures (~ 2.9 s) that allow for sampling continental regions such as Central Europe within 2 h while providing sufficient signal-to-noise. The noise errors to be expected for XCO2, XCH4, and XCO are assessed through retrieval simulations for a European trial ensemble. Generally, single-shot precision for the targeted XCO2 and XCH4 is better than 0.5% with some exception for scenes with low infrared surface albedo observed under low sun conditions in winter. For XCO, precision is generally better than 10%. Performance for aerosol and cirrus loaded atmospheres is assessed by mimicking G3E's slant view on Europe for an ensemble of atmospheric scattering properties used previously for evaluating nadir-viewing low-Earth-orbit (LEO) satellites. While retrieval concepts developed for LEO configurations generally succeed in mitigating aerosol and cirrus induced retrieval errors for G3E's setup, residual errors are somewhat greater in geostationary orbit (GEO) than in LEO. G3E's deployment in the vicinity of the Meteosat Third Generation (MTG) satellites suggests making synergistic use of MTG's sounding capabilities e.g. with respect to characterization of aerosol and cloud properties or with respect to enhancing carbon monoxide retrievals by combining G3E's solar and MTG's thermal infrared spectra. [ABSTRACT FROM AUTHOR]

From basic physical assumptions we derive a simple linear model of the global CO2 cycle without free parameters. It yields excellent agreement with the observations reported by the carbon dioxide information analysis center (CDIAC) as time series of atmospheric CO2 growth, of sinks in the ocean and of absorption by the biosphere. The agreement extends from the year 1850 until present (2013). Based on anthropogenic CO2 emission scenarios until 2150, future atmospheric CO2 concentrations are calculated. As the model shows, and depending on the emission scenario, the airborne fraction of CO2 begins to decrease in the year ~ 2050 and becomes negative at the latest in ~ 2130. At the same time the concentration of the atmospheric CO2 will reach a maximum between ~ 500 and ~ 900 ppm. As a consequence, increasing anthropogenic CO2 emissions will make the ocean and the biosphere the main reservoirs of anthropogenic CO2 in the long run. Latest in about 150 years, anthropogenic CO2 emission will no longer increase the CO2 content of the atmosphere. [ABSTRACT FROM AUTHOR]

From January 2011 to December 2013, we constructed a comprehensive pCO2 dataset based on voluntary observing ship (VOS) measurements in the Western English Channel (WEC). We subsequently estimated surface pCO2 and air-sea CO2 fluxes in north-west European continental shelf waters using multiple linear regressions (MLRs) from remotely sensed sea surface temperature (SST), chlorophyll a concentration (Chl a), the gas transfer velocity coefficient (K), photosynthetically active radiation (PAR) and modeled mixed layer depth (MLD). We developed specific MLRs for the seasonally stratified northern WEC (nWEC) and the permanently well-mixed southern WEC (sWEC) and calculated surface pCO2 with relative uncertainties of 17 and 16 µ atm, respectively. We extrapolated the relationships obtained for the WEC based on the 2011-2013 dataset (1) temporally over a decade and (2) spatially in the adjacent Celtic and Irish Seas (CS and IS), two regions which exhibit hydrographical and biogeochemical characteristics similar to those of WEC waters. We validated these extrapolations with pCO2 data from the SOCAT database and obtained relatively robust results with an average precision of 4_22 µatm in the seasonally stratified nWEC and the southern and northern CS (sCS and nCS), but less promising results in the permanently well-mixed sWEC, IS and Cap Lizard (CL) waters. On an annual scale, seasonally stratified systems acted as a sink of CO2 from the atmosphere of -0.4, -0.9 and -0.4 mol C m-2 year-1 in the nCS, sCS and nWEC, respectively, whereas, permanently well-mixed systems acted as source of CO2 to the atmosphere of 0.2, 0.4 and 0.4 mol C m-2 year-1 in the sWEC, CL and IS, respectively. Air-sea CO2 fluxes showed important inter-annual variability resulting in significant differences in the intensity and/or direction of annual fluxes. We scaled the mean annual fluxes over six provinces for the last decade and obtained the first annual average uptake of -0.95 Tg C year-1 for this part of the north-western European continental shelf. Our study showed that combining VOS data with satellite observations can be a powerful tool to estimate and extrapolate air-sea CO2 fluxes in sparsely sampled area. [ABSTRACT FROM AUTHOR]

An automated identification and integration method has been developed to investigate in-use vehicle emissions under real-world conditions. This technique was applied to high time resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada during four seasons, through month-long campaigns in 2013-2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number, black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the light-duty gasoline dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mgkg-1 and 7.7×1014 kg-1, respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of coemitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25 %) contributed significantly to total fleet emissions; 95, 93, 76, and 75% for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter. However, regulatory strategies to more efficiently target multi-pollutants mixtures may be better developed by considering the co-emitted pollutants as well. [ABSTRACT FROM AUTHOR]

Many factors are known to influence greenhouse gas emissions from coastal wetlands, but it is still unclear which factors are most important under field conditions when they are all acting simultaneously. The objective of this study was to assess the effects of water table, salinity, soil temperature and vegetation on CH4 emissions and ecosystem respiration (Reco) from five coastal wetlands in the Liaohe Delta, northeast China: two Phragmites australis (common reed) wetlands, two Suaeda salsa (sea blite) marshes and a rice (Oryza sativa) paddy. Throughout the growing season, the Suaeda wetlands were net CH4 sinks whereas the Phragmites wetlands and the rice paddy were net CH4 sources emitting 1.2-6.1 gCH4m-2 y-1. The Phragmites wetlands emitted the most CH4 per unit area and the most CH4 relative to CO2 . The main controlling factors for the CH4 emissions were water table, temperature and salinity. The CH4 emission was accelerated at high and constant (or managed) water tables and decreased at water tables below the soil surface. High temperatures enhanced CH4 emissions, and emission rates were consistently low (< 1mgCH4 m-2 h) at soil temperatures < 18 °C. At salinity levels> 18 ppt, the CH4 emission rates were always low (< 1mgCH4 m-2 h-1) probably because methanogens were outcompeted by sulphate reducing bacteria. Saline Phragmites wetlands can, however, emit significant amounts of CH4 as CH4 produced in deep soil layers are transported through the air-space tissue of the plants to the atmosphere. The CH4 emission from coastal wetlands can be reduced by creating fluctuating water tables, including water tables below the soil surface, as well as by occasional flooding by high-salinity water. The effects of water management schemes on the biological communities in the wetlands must, however, be carefully studied prior to the management in order to avoid undesirable effects on the wetland communities. [ABSTRACT FROM AUTHOR]

Oceanic uptake of anthropogenic carbon dioxide (CO2) is altering the seawater chemistry of the world's oceans with consequences for marine bioregions, especially calcareous organisms such as corals, foraminifera and coccolithophores. The coccolithophores, one of the most abundant and widespread groups of calcifying plankton, are responsible for a large proportion of modern oceanic carbonate production. However, culture experiments examining the response of coccolithophores to elevated CO2 partial pressure (pCO2) have mostly been based on investigations of a single strain and have yielded contradictory results from different experiments between and even within species. Here, four strains of the coccolithophores Emiliania huxleyi (E. huxleyi) and Gephyrocapsa oceanica (G. oceanica), which contained separately naked and calcifying strains, were investigated simultaneously for the first time in a bubbling batch culture at four CO2 grades ranging from approximately 380 to 2000 µatm. We synchronously determined multiple physiological parameters of four coccolithophore strains involving growth, photosynthesis, nitrogen uptake, elemental compositions and calcification efficiency in the process of cultivation. The results did not show a uniform response from different strains to elevated pCO2 up to 2000 µatm, and the naked strain E. huxleyi (N-E) was seriously suppressed, in sharp contrast to the positive response of the different levels of the other three algae. In addition, we fitted nitrogen uptake rate response curves relative to changing pCO2 for the four strains and applied kinetic constants from the response curves to further analyze the hypostatic difference among different strains, which reflected the same variational trend of the four stains above vs. increasing CO2. We determined that the responses of coccolithophores to ocean acidification are inter- and intra-specific, and this variation may cause changes to biodiversity and other ecosystem processes in the future ocean. [ABSTRACT FROM AUTHOR]

Increased natural gas production in recent years has spurred intense interest in methane (CH4) emissions associated with its production, gathering, processing, transmission and distribution. Gathering and processing facilities (G&P facilities) are unique in that the wide range of gas sources (shale, coal-bed, tight gas, conventional, etc.) results in a wide range of gas compositions, which in turn requires an array of technologies to prepare the gas for pipeline transmission and distribution. We present an overview and detailed description of the measurement method and analysis approach used during a 20-week field campaign studying CH4 emissions from the natural gas G&P facilities between October 2013 and April 2014. Dual tracer flux measurements and onsite observations were used to address the magnitude and origins of CH4 emissions from these facilities. The use of a second tracer as an internal standard revealed plume-specific uncertainties in the measured emission rates of 20-47 %, depending upon plume classification. Combining downwind methane, ethane (C2H6), carbon monoxide (CO), carbon dioxide (CO2), and tracer gas measurements with onsite tracer gas release allows for quantification of facility emissions, and in some cases a more detailed picture of source locations. [ABSTRACT FROM AUTHOR]

The continuous in-situ measurement of δ18O in atmospheric CO2 opens a new door to differentiating between CO2 source and sink components with high temporal resolution. Continuous 13C-CO2 measurement systems have been commercially available already for some time, but until now, only few instruments have been able to provide a continuous measurement of the oxygen isotope ratio in CO2. Besides precise 13C/12C observations, the Fourier Transform InfraRed (FTIR) spectrometer also measures the 18O/16O ratio of CO2, but the precision and accuracy of the measurements has not been evaluated yet. Here we present a first analysis of δ18O-CO2 (and δ13C CO2) measurements with the FTIR in Heidelberg. We find that our spectrometer measures 18O in CO2 with a reproducibility of better than 0.3‰ at a temporal resolution of less than 10 min, as determined from surveillance gas measurements over a period of ten months. An Allan deviation test shows that the δ18O repeatability reaches 0.15‰ for half-hourly means. The compatibility of our spectroscopic measurements was determined by comparing FTIR measurements of calibration gases and ambient air to mass-spectrometric measurements of flask samples, filled with the cylinder gases or episodically collected over a diurnal cycle (event). We found that direct cylinder gas measurements agree to 0.01±0.04‰ (mean and standard deviation) for δ13C-CO2 and 0.01±0.11‰ for δ18O. Two weekly episodes of recent ambient air measurements, one in winter and one in summer, are discussed in view of the question, which potential insights and new challenges combined highly resolved δ18O-CO2 and δ13C-CO2 records may provide in terms of better understanding regional scale continental carbon exchange processes [ABSTRACT FROM AUTHOR]

A meta-analysis of photosynthesis/irradiance measurements was completed using data from the Ross Sea, Antarctica. A total of 544 independent measurements were included. PsB, the maximum, chlorophyll-specific, irradiance-saturated rate of photosynthesis, averaged 1.07±0.060 µg C µg chl)-1 h-1. Light-limited photosynthetic rates (α) averaged 0.03±0.023 µg C &#181g chl)-1 h-1 (µmolphotonsm-2s-1)-1. Significant variations in Ps and a were found as a function of season, with spring maximum photosynthetic rates being 59 % greater than those in summer. Similarly, α values were 48% greater in spring. There was no detectable effect of space on the photosynthetic parameters, and temperature and macronutrient (NO3) concentrations also did not exert a strong influence. However, irradiance, dissolved iron concentrations, and carbon dioxide concentrations when altered under controlled conditions exerted significant influences on photosynthetic parameters. Specifically, reduced irradiance resulted in decreased PsB and β values, whereas reduced iron concentrations were associated with increased PsB and α values. Increased CO2 concentrations also resulted in significantly increased PsB and α values. No significant difference was detected between stations dominated by diatoms and those dominated by the haptophyte Phaeocystis antarctica. The meta-analysis generally confirms the photosynthetic rates predicted from global analyses that are based solely on temperature and irradiance availability, but suggests that for more accurate predictions of the productivity of polar systems a more detailed model that includes temporal effects of photosynthetic parameters will be required. [ABSTRACT FROM AUTHOR]

We report global long-term trends in surface ocean pH using a new pH data set computed by combining fCO2 observations from the Surface Ocean CO2 Atlas (SOCAT) version 2 with surface alkalinity estimates based on temperature and salinity. Trends were determined over the periods 1981-2011 and 1991-2011 for a set of 17 biomes using a weighted linear least squares method. We observe significant decreases in surface ocean pH in ~ 70% of all biomes and a global mean rate of decrease of -0.0018±0.0004 yr-1 for 1991-2011.We are not able to calculate a global trend for 1981-2011 because too few biomes have enough data for this. In two-thirds of the biomes, the rate of change is commensurate with the trends expected based on the assumption that the surface ocean pH change is only driven by the surface ocean carbon chemistry remaining in a transient equilibrium with the increase in atmospheric CO2 . In the remaining biomes deviations from such equilibrium may reflect changes in the trend of surface ocean fCO2, most notably in the equatorial Pacific Ocean, or changes in the oceanic buffer (Revelle) factor. We conclude that well-planned and long- term sustained observational networks are key to reliably document the ongoing and future changes in ocean carbon chemistry due to anthropogenic forcing. [ABSTRACT FROM AUTHOR]

Headwater streams export CO2 as lateral downstream export and vertical evasion from the stream surface. CO2 in boreal headwater streams generally originates from adjacent terrestrial areas, so determining the sources and rate of CO2 transport along the hillslope-riparian-stream continuum could improve estimates of CO2 export via the aquatic pathway, especially by quantifying evasion at higher temporal resolutions. Continuous measurements of dissolved CO2 concentrations and water table were made along the hillslope-riparian-stream continuum in the Västrabäcken sub-catchment of the Krycklan Catchment, Sweden. Daily water and CO2 export from the hillslope and riparian zone were estimated over one hydrological year (October 2012-September 2013) using a flow-concentration model and compared with measured lateral downstream CO2 export. Total water export over the hydrological year from the hillslope was 230mmyr-1 compared with 270mmyr-1 from the riparian zone. This corresponds well (proportional to the relative upslope contributing area) to the annual catchment runoff of 265mmyr-1. Total CO2 export from the riparian zone to the stream was 3.0 gCO2-C m-2 yr-1. A hotspot for riparian CO2 export was observed at 30-50 cm depth (accounting for 71%of total riparian export). Seasonal variability was high with export peaks during the spring flood and autumn storm events. Downtream lateral CO2 export (determined from stream water dissolved CO2 concentrations and discharge) was 1.2 gCO2-C m-2 yr-1. Subtracting downstream lateral export from riparian export (3.0 gCO2-Cm-2 yr-1) gives 1.8 gCO2-Cm-2 yr-1 which can be attributed to evasion losses (accounting for 60% of export via the aquatic pathway). The results highlight the importance of terrestrial CO2 export, especially from the riparian zone, for determining catchment aquatic CO2 losses and the importance of the CO2 evasion component to carbon export via the aquatic conduit. [ABSTRACT FROM AUTHOR]

Quantifying water vapor and carbon dioxide (CO 2) exchange dynamics between the land and the atmosphere through observations and modeling is necessary in order to reproduce and project near-surface climate in coupled land–atmosphere models. The exchange of water and CO 2 occurs at the leaf surface (leaf level) and in a net manner through exchanges at all the leaf surfaces composing the vegetation canopy and at the soil surface (canopy level). These exchanges depend on the meteorological forcings imposed by the overlying atmosphere (atmospheric boundary layer level). In this paper, we investigate the effect of four canopy environmental variables (photosynthetic active radiation (PAR), water vapor pressure deficit (VPD), air temperature (T), and atmospheric CO 2 concentration (Ca)) on the local individual leaf exchange and canopy exchange of water and CO 2 at hourly timescales. Additionally, we investigate the effect of atmospheric boundary layer (ABL) processes on the local exchange. To that end, we simultaneously investigated the exchanges of water and CO 2 at leaf level and canopy level for an alfalfa field in northern Spain over 1 day in summer 2021. We used comprehensive observations ranging from stomatal conductance to ABL measurements collected during the Land Surface Interactions with the Atmosphere in the Iberian Semi-Arid Environment (LIAISE) experiment. To support the observational analysis, we used a coupled land–atmosphere model (CLASS model) that has representations at all levels considered. To relate how temporal changes of the four environmental variables modify the fluxes of water and CO 2 , we studied tendency equations of the leaf gas exchange. These mathematical expressions quantify the temporal evolution of the leaf gas exchange as a function of the temporal evolution of PAR, VPD, T , and Ca. To investigate the effects of ABL processes on the local exchange, we developed three modeling experiments that impose surface radiative perturbations by a cloud passage (which perturbed PAR, T , and VPD), entrainment of dry air from the free troposphere (which perturbed VPD), and advection of cold air (which perturbed T and VPD). The model results and observations matched the leaf gas exchange (r2 between 0.23 and 0.67) and canopy gas exchange (r2 between 0.90 and 0.95). The tendency equations of the modeled leaf gas exchange during the study day revealed that the temporal dynamics of PAR were the main contributor to the temporal dynamics of the leaf gas exchange, with atmospheric CO 2 temporal dynamics being the least important contributor. From the three modeling experiments with ABL perturbations, the surface radiative changes induced by a cloud perturbed the CO 2 exchange the most, whereas all of them perturbed the water exchange to a similar extent. Second-order effects on the dynamics of the leaf gas exchange were also identified using the tendency equations. For instance, the decrease in the net CO 2 assimilation rate during the cloud passage caused by a decrease in surface radiation was further enhanced due to the decrease in air temperature also associated with the cloud. With this research we showcase that the proposed tendency equations can disentangle the effect of environmental variables on the leaf exchange of water and CO 2 with the atmosphere, as represented in land–surface parameterization schemes. As such, this framework can become a useful tool with which to analyze these schemes in weather and climate models. [ABSTRACT FROM AUTHOR]

The Atmospheric Environment Monitoring Satellite (DQ-1) was successfully launched in April 2022, with the capability of providing continuous multi-sensor spatial and optical simultaneous observations of carbon dioxide, aerosols and clouds. The primary payload carried on DQ-1 is an Aerosol and Carbon dioxide Detection Lidar (ACDL). The instrument comprises a high-spectral-resolution channel at 532 nm, elastic channels at 532 nm and 1064 nm, and integrated-path differential absorption (IPDA) channel at 1572 nm. The optical properties of aerosols and clouds measured by the ACDL promote a quantitative characterization of the uncertainties in the global climate system, hence the precise calibrations for the ACDL are necessary. This paper outlines the algorithms employed for calibrating the nighttime 532 nm measurements for the first spaceborne high-spectral-resolution lidar with an iodine vapor absorption filter. The nighttime calibrations of the 532 nm data are fundamental to the ACDL measurement procedure, as they are utilized to derive the calibrations over daytime orbits and the calibrations of the 1064 nm channel relative to the 532 nm channel. This paper provides a review of the theoretical foundations for molecular normalization techniques as applied to spaceborne lidar measurements, includes a detailed discussion of auxiliary data and theoretical parameters used in ACDL calibrations, as well as a comprehensive description of the calibration algorithm procedure. To mitigate large errors stemming from high-energy events during calibration, a data filter is designed to obtain valid calibration signals. The paper also assesses the results of the calibration procedure, by analysing the errors of calibration coefficients and validating the attenuated backscatter coefficient results. The results indicate that the relative error of the calibrated attenuated backscatter coefficients is lower than 2 % in the calibration area, and the uncertainty of the pure-molecule attenuated scattering ratio was within anticipated range of 5 %. [ABSTRACT FROM AUTHOR]

The quantification of emissions of greenhouse gases and air pollutants through the inversion of plumes in satellite images remains a complex problem that current methods can only assess with significant uncertainties. The anticipated launch of the CO2M (Copernicus Anthropogenic Carbon Dioxide Monitoring) satellite constellation in 2026 is expected to provide high-resolution images of CO2 (carbon dioxide) column-averaged mole fractions (XCO2), opening up new possibilities. However, the inversion of future CO2 plumes from CO2M will encounter various obstacles. A challenge is the low CO2 plume signal-to-noise ratio due to the variability in the background and instrumental errors in satellite measurements. Moreover, uncertainties in the transport and dispersion processes further complicate the inversion task. To address these challenges, deep learning techniques, such as neural networks, offer promising solutions for retrieving emissions from plumes in XCO2 images. Deep learning models can be trained to identify emissions from plume dynamics simulated using a transport model. It then becomes possible to extract relevant information from new plumes and predict their emissions. In this paper, we develop a strategy employing convolutional neural networks (CNNs) to estimate the emission fluxes from a plume in a pseudo- XCO2 image. Our dataset used to train and test such methods includes pseudo-images based on simulations of hourly XCO2 , NO2 (nitrogen dioxide), and wind fields near various power plants in eastern Germany, tracing plumes from anthropogenic and biogenic sources. CNN models are trained to predict emissions from three power plants that exhibit diverse characteristics. The power plants used to assess the deep learning model's performance are not used to train the model. We find that the CNN model outperforms state-of-the-art plume inversion approaches, achieving highly accurate results with an absolute error about half of that of the cross-sectional flux method and an absolute relative error of ∼ 20 % when only the XCO2 and wind fields are used as inputs. Furthermore, we show that our estimations are only slightly affected by the absence of NO2 fields or a detection mechanism as additional information. Finally, interpretability techniques applied to our models confirm that the CNN automatically learns to identify the XCO2 plume and to assess emissions from the plume concentrations. These promising results suggest a high potential of CNNs in estimating local CO2 emissions from satellite images. [ABSTRACT FROM AUTHOR]

As the vegetation in the Arctic changes, tundra ecosystems along the southern border of the Arctic are becoming greener and gradually giving way to boreal ecosystems. This change is affecting local populations, wildlife, energy exchange processes between environmental compartments, and the carbon cycle. To understand the progression and the implications of this change in vegetation, satellite measurements and surface models can be employed. However, in situ observational data are required to validate these measurements and models. This paper presents observational data from two nearby sites in the forest–tundra ecotone in the Tasiapik Valley near Umiujaq in Northern Quebec, Canada. One site is on a mixture of lichen and shrub tundra. The associated data set comprises 9 years of meteorological, soil and snow data as well as 3 years of eddy covariance data. The other site, 850 m away, features vegetation consisting mostly of tall shrubs and black spruce. For that location, 6 years of meteorological, soil and snow data are available. In addition to the data from the automated stations, profiles of snow density and specific surface area were collected during field campaigns. The data are available at 10.1594/PANGAEA.964743 (Domine et al., 2024). [ABSTRACT FROM AUTHOR]

Carbon (C) sequestration in the soil is considered as a potential important mechanism to mitigate greenhouse gas (GHG) emissions of the agricultural sector. It can be quantified by the net ecosystem carbon budget (NECB) describing the change of soil C as the sum of all relevant import and export fluxes. NECB was investigated here in detail for an intensively grazed dairy pasture in Switzerland. Two budget approaches with different system boundaries were applied: NECBtot for system boundaries including the grazing cows and NECBpast for system boundaries excluding the cows. CO2 and CH4 exchange induced by soil/vegetation processes as well as direct emissions by the animals were derived from eddy covariance measurements. Other C fluxes were either measured (milk yield, concentrate feeding) or derived based on animal performance data (intake, excreta). For the investigated year, both approaches resulted in a small non-significant C loss: NECBtot - 13 ± 61 g C m-2 yr-1 and NECBpast - 17 ± 81 g C m-2 yr-1. The considerable uncertainties, depending on the approach, were mainly due to errors in the CO2 exchange or in the animal related fluxes. The associated GHG budget revealed CH4 emissions from the cows to be the major contributor, but with much lower uncertainty compared to NECB. Although only one year of data limit the representativeness of the carbon budget results, they demonstrated the important contribution of the non-CO2 fluxes depending on the chosen system boundaries and the effect of their propagated uncertainty in an exemplary way. The simultaneous application and comparison of both NECB approaches provides a useful consistency check for the carbon budget determination and can help to identify and eliminate systematic errors. [ABSTRACT FROM AUTHOR]

Savanna ecosystems cover 20% of the global land surface and account for 25% of global terrestrial carbon uptake. They support one fifth of the world's human population and are one of the most important ecosystems on our planet. Savanna productivity is a product of the interplay between trees and grass that co-dominate savanna landscapes and are maintained through interactions with climate and disturbance (fire, land use change, herbivory). In this study, we evaluate the temporally dynamic partitioning of overstory and understory carbon dioxide fluxes in Australian tropical savanna using overstory and understory eddy covariance measurements. Over a two year period (September 2012 to October 2014) the overall net ecosystem productivity (NEP) of the savanna was 506.2 (±22 SE) g C m-2 yr-1. The total gross primary productivity (GPP) was 2267.1 (±80 SE) g C m-2 yr-1, of which the understory contributed 32%. The understory contribution was strongly seasonal, with most GPP occurring in the wet season (40% of total ecosystem in the wet season and 18% in the dry). This study is the first to elucidate the temporal dynamics of savanna understory and overstory carbon flux components explicitly using observational information. Understanding grass productivity is crucial for evaluating fuel loads, as is tree productivity for quantifying the tree carbon sink. This information will contribute to a significant refinement of the representation of savannas in models, as well as improved understanding of relative tree-grass productivity and competition for resources. [ABSTRACT FROM AUTHOR]

Sunlight induces photochemical mineralisation of chromophoric dissolved organic matter (CDOM) to dissolved inorganic carbon (DIC) in inland waters, resulting in carbon dioxide (CO2) emissions to the atmosphere. Photochemical rate modelling is used to determine sunlight-induced CO2 emissions on large spatial and temporal scales. A sensitive model parameter is the wavelength-specific photochemical CDOM reactivity, the apparent quantum yield (AQY). The modelling studies so far assume that AQY spectra determined for single lakes and on single occasions represent larger spatial and temporal scales. Here, we studied a humic boreal lake in Sweden. We measured AQY spectra for photochemical DIC production monthly between June and November 2014 and parameterised a photochemical rate model. Photochemical reactivity increased slightly during the open water period, likely due to a high rainfall event with consecutive mixing in autumn that increased availability of highly photoreactive CDOM. However, the variability in AQY spectra over time was much smaller than previously reported variability in AQY spectra across lakes. Yet, using either the AQY spectrum from the least or from the most photoreactive water sample resulted in a 5-fold difference in simulated annual DIC photoproduction (2.0 ± 0.1 and 10.3 ± 0.7 g C m-2 yr-1, respectively). Using the monthly measured AQY spectrum to simulate DIC photoproduction for month-long time periods resulted in an apparent time lag between irradiance and DIC photoproduction. This suggested that temporal variability in AQY spectra occurs on shorter time scales. Therefore, we parameterised the model with the pooled AQY spectrum of six monthly measurements. Simulated DIC photoproduction for three years (2012-2014) averaged 4.5 ± 0.2 g C m-2 yr-1, which represented 3% of the mean CO2 emissions from this lake. We conclude that (1) it may be recommendable to conduct repeated AQY measurements across the season for more accurate simulation of annual photochemical DIC production in lakes and (2), in agreement with previous studies, direct CDOM photomineralisation makes only a minor contribution to mean CO2 emissions from Swedish humic lakes. [ABSTRACT FROM AUTHOR]

One of the strategies to reduce carbon dioxide (CO2) emissions from the energy sector is to increase the use of renewable energy sources such as bioenergy crops. Bioenergy is not necessarily carbon neutral because of greenhouse gas (GHG) emissions during biomass production, field management and transportation. The present study focuses on the cultivation of reed canary grass (RCG, Phalaris arundinaceae L.), a perennial bioenergy crop, on a mineral soil. To quantify the CO2 exchange of this RCG cultivation system, and to understand the key factors controlling its CO2 exchange, the net ecosystem CO2 exchange (NEE) was measured during three years using the eddy covariance (EC) method. The RCG cultivation thrived well producing yields of 6200 and 6700 kg DW ha-1 in 2010 and 2011, respectively. Gross photosynthesis (GPP) was controlled mainly by radiation from June to September. Vapour pressure deficit (VPD), air temperature or soil moisture did not limit photosynthesis during the growing season. Total ecosystem respiration (TER) increased with soil temperature, green area index and GPP. Annual NEE was -262 and -256 g C m-2 in 2010 and 2011, respectively. Throughout the studied period, cumulative NEE was -575 g C m-2. When compared to the published data for RCG on an organic soil, the cultivation of this crop on a mineral soil had higher capacity to take up CO2 from the atmosphere. [ABSTRACT FROM AUTHOR]

The ongoing increase in anthropogenic carbon dioxide (CO2) emissions is changing the global marine environment and is causing warming and acidification of the oceans. Reduction of CO2 to a sustainable level is required to avoid further marine change. Many studies investigate the potential of marine carbon sinks (e.g. seagrass) to mitigate anthropogenic emissions, however, information on storage by coralline algae and the beds they create is scant. Calcifying photosynthetic organisms, including coralline algae, can act as a CO2 sink via photosynthesis and CaCO3 dissolution and act as a CO2 source during respiration and CaCO3 production on short-term time scales. Long-term carbon storage potential might come from the accumulation of coralline algae deposits over geological time scales. Here, the carbon storage potential of coralline algae is assessed using meta-analysis of their global organic and inorganic carbon production and the processes involved in this metabolism. Organic and inorganic production were estimated at 330 g C m-2 yr-1 and 880 g CaCO3 m-2 yr-1 respectively giving global organic/inorganic C production of 0.7/1.8 × 109 t C yr-1. Calcium carbonate production by free-living/crustose coralline algae (CCA) corresponded to a sediment accretion of 70/450 mm kyr-1. Using this potential carbon storage by coralline algae, the global production of free-living algae/CCA was 0.4/1.2 × 109 t C yr-1 suggesting a total potential carbon sink of 1.6 × 109 t C yr-1. Coralline algae therefore have production rates similar to mangroves, saltmarshes and seagrasses representing an as yet unquantified but significant carbon store, however, further empirical investigations are needed to determine the dynamics and stability of that store. [ABSTRACT FROM AUTHOR]

By recreating a range of geologically relevant concentrations of dissolved inorganic carbon (DIC) in the laboratory, we demonstrate that the magnitude of the vital effects in both carbon and oxygen isotopes of coccolith calcite of multiple species relates to ambient DIC concentration. Under high DIC levels, all the examined coccoliths lacked any offset from inorganic calcite, whereas in low (present-day) DIC concentrations, these vital effects and interspecies differences become substantial. These laboratory observations support the recent hypothesis from field observations that the appearance of interspecific vital effect in coccolithophores coincides with the long-term Neogene decline of atmospheric CO2 concentrations. The present study brings further valuable constraints on coccolith isotopic compositions by demonstrating the threshold for the absence of vital effects under high DIC regimes. From a mechanistic viewpoint, we show that the vital effect is determined by physiology; growth rate, cell size and relative rates of photosynthesis and calcification, and a modulation of these parameters with ambient carbon availability. This study provides palaeoceanographers with a biogeochemical framework that can be utilised to further develop the use of calcareous nannofossils in palaeoceanography to derive sea surface temperature and pCO2 levels. [ABSTRACT FROM AUTHOR]

The use of eddy covariance CO2 flux measurements in data assimilation and other applications requires an estimate of the random uncertainty. In previous studies, the two-tower approach has yielded robust uncertainty estimates, but care must be taken to meet the often competing requirements of statistical independence (non-overlapping footprints) and ecosystem homogeneity when choosing an appropriate tower distance. The role of the tower distance was investigated with help of a roving station separated between 8m and 34 km from a permanent EC grassland station. Random uncertainty was estimated for five separation distances with an extended two-tower approach which removed systematic differences of CO2 fluxes measured at two EC towers. This analysis was made for a dataset where (i) only similar weather conditions at the two sites were included and (ii) an unfiltered one. The extended approach, applied to weather-filtered data for separation distances of 95m and 173m gave uncertainty estimates in best correspondence with the independent reference method The introduced correction for systematic flux differences considerably reduced the overestimation of the two-tower based uncertainty of net CO2 flux measurements, e.g. caused by different environmental conditions at both EC towers. It is concluded that the extension of the two-tower approach can help to receive more reliable uncertainty estimates because systematic differences of measured CO2 fluxes which are not part of random error are filtered out. [ABSTRACT FROM AUTHOR]