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We analysed gross primary productivity (GPP), total ecosystem respiration (TER) and the resulting net ecosystem exchange (NEE) of carbon dioxide (CO2) by the terrestrial biosphere during the summer of 2018 through observed changes across the Integrated Carbon Observation System (ICOS) network, through biosphere and inverse modelling, and through remote sensing. Highly correlated yet independently-derived reductions in productivity from sun-induced fluorescence, vegetative near-infrared reflectance, and GPP simulated by the Simple Biosphere model version 4 (SiB4) suggest a 130–340 TgC GPP reduction in July–August–September (JAS) of 2018. This occurs over an area of 1.6 × 106 km2 with anomalously low precipitation in northwestern and central Europe. In this drought-affected area, reduced GPP, TER, NEE and soil moisture at ICOS ecosystem sites are reproduced satisfactorily by the SiB4 model. We found that, in contrast to the preceding 5 years, low soil moisture is the main stress factor across the affected area. SiB4's NEE reduction by 57 TgC for JAS coincides with anomalously high atmospheric CO2 observations in 2018, and this is closely matched by the NEE anomaly derived by CarbonTracker Europe (52 to 83 TgC). Increased NEE during the spring (May–June) of 2018 (SiB4 −52 TgC; CTE −46 to −55 TgC) largely offset this loss, as ecosystems took advantage of favourable growth conditions. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'. [ABSTRACT FROM AUTHOR]

Understanding climate controls on gross primary productivity (GPP) is crucial for accurate projections of the future land carbon cycle. Major uncertainties exist due to the challenge in separating GPP and respiration from observations of the carbon dioxide (CO2) flux. Carbonyl sulfide (COS) has a dominant vegetative sink, and plant COS uptake is used to infer GPP through the leaf relative uptake (LRU) ratio of COS to CO2 fluxes. However, little is known about variations of LRU under changing environmental conditions and in different phenological stages. We present COS and CO2 fluxes and LRU of Scots pine branches measured in a boreal forest in Finland during the spring recovery and summer. We find that the diurnal dynamics of COS uptake is mainly controlled by stomatal conductance, but the leaf internal conductance could significantly limit the COS uptake during the daytime and early in the season. LRU varies with light due to the differential light responses of COS and CO2 uptake, and with vapor pressure deficit (VPD) in the peak growing season, indicating a humidity-induced stomatal control. Our COS-based GPP estimates show that it is essential to incorporate the variability of LRU with environmental variables for accurate estimation of GPP on ecosystem, regional, and global scales. [ABSTRACT FROM AUTHOR]

Carbonyl sulfide (COS) has been suggested as a useful tracer for gross primary production as it is taken up by plants in a similar way as CO2. To explore and verify the application of this novel tracer, it is highly desired to develop the ability to perform continuous and high-precision in situ atmospheric measurements of COS and CO2. In this study we have tested a quantum cascade laser spectrometer (QCLS) for its suitability to obtain accurate and high-precision measurements of COS and CO2. The instrument is capable of simultaneously measuring COS, CO2, CO and H2O after including a weak CO absorption line in the extended wavelength range. An optimal background and calibration strategy was developed based on laboratory tests to ensure accurate field measurements. We have derived water vapor correction factors based on a set of laboratory experiments and found that for COS the interference associated with a water absorption line can dominate over the effect of dilution. This interference can be solved mathematically by fitting the COS spectral line separately from the H2O spectral line. Furthermore, we improved the temperature stability of the QCLS by isolating it in an enclosed box and actively cooling its electronics with the same thermoelectric chiller used to cool the laser. The QCLS was deployed at the Lutjewad atmospheric monitoring station (60 m; 6°21′ E, 53°24′ N; 1 m a.s.l.) in the Netherlands from July 2014 to April 2015. The QCLS measurements of independent working standards while deployed in the field showed a mean difference with the assigned cylinder value within 3.3 ppt COS, 0.05 ppm for CO2 and 1.7 ppb for CO over a period of 35 days. The different contributions to uncertainty in measurements of COS, CO2 and CO were summarized and the overall uncertainty was determined to be 7.5 ppt for COS, 0.23 ppm for CO2 and 3.3 ppb for CO for 1-minute data. A comparison of in situ QCLS measurements with those from concurrently filled flasks that were subsequently measured by the QCLS showed a difference of −9.7 ± 4.6 ppt for COS. Comparison of the QCLS with a cavity ring-down spectrometer showed a difference of 0.12 ± 0.77 ppm for CO2 and −0.9 ± 3.8 ppb for CO. [ABSTRACT FROM AUTHOR]

Carbonyl sulfide (COS) flux measurements with the eddy covariance (EC) technique are becoming popular for estimating gross primary productivity. To compare COS flux measurements across sites, we need standardized protocols for data processing. In this study, we analyze how various data processing steps affect the calculated COS flux and how they differ from carbon dioxide (CO2) flux processing steps, and we provide a method for gap-filling COS fluxes. Different methods for determining the time lag between COS mixing ratio and the vertical wind velocity (w) resulted in a maximum of 15.9 % difference in the median COS flux over the whole measurement period. Due to limited COS measurement precision, small COS fluxes (below approximately 3 pmol m -2 s -1) could not be detected when the time lag was determined from maximizing the covariance between COS and w. The difference between two high-frequency spectral corrections was 2.7 % in COS flux calculations, whereas omitting the high-frequency spectral correction resulted in a 14.2 % lower median flux, and different detrending methods caused a spread of 6.2 %. Relative total uncertainty was more than 5 times higher for low COS fluxes (lower than ±3 pmol m -2 s -1) than for low CO2 fluxes (lower than ±1.5 µ mol m -2 s -1), indicating a low signal-to-noise ratio of COS fluxes. Due to similarities in ecosystem COS and CO2 exchange, we recommend applying storage change flux correction and friction velocity filtering as usual in EC flux processing, but due to the low signal-to-noise ratio of COS fluxes, we recommend using CO2 data for time lag and high-frequency corrections of COS fluxes due to the higher signal-to-noise ratio of CO2 measurements. [ABSTRACT FROM AUTHOR]

Carbonyl sulfide (COS) flux measurements with the eddy covariance (EC) technique are growing in popularity with the recent development in using COS to estimate gross photosynthesis at the ecosystem scale. Flux data intercomparison would benefit from standardized protocols for COS flux data processing. In this study, we analyze how various data processing steps affect the final flux and provide a method for gap-filling COS fluxes. Different methods for determining the lag time between COS mixing ratio and the vertical wind velocity (w) resulted in a maximum of 12 % difference in the cumulative COS flux. Due to limited COS measurement precision, small COS fluxes (below approximately 3 pmol m−2 s−1) could not be detected when the lag time was determined from maximizing the covariance between COS and w. We recommend using a combination of COS and carbon dioxide (CO2) lag times in determining the COS flux, depending on the flux magnitude compared to the detection limit of each averaging period. Different high frequency spectral corrections had a maximum effect of 10 % on COS flux calculations and different detrending methods only 1.2 %. Relative total uncertainty was more than five times higher for low COS fluxes (absolute flux lower than 3 pmol m−2 s−1) than for low CO2 fluxes (lower than 1.5 μmol m−2 s−1), indicating a low signal-to-noise ratio of COS fluxes. Due to similarities in ecosystem COS and CO2 exchange, and the low signal-to-noise ratio of COS fluxes that is similar to methane, we recommend a combination of CO2 and methane flux processing protocols for COS EC fluxes. [ABSTRACT FROM AUTHOR]

We present the CarbonTracker Europe High-Resolution (CTE-HR) system that estimates carbon dioxide (CO2) exchange over Europe at high resolution (0.1 × 0.2 ∘) and in near real time (about 2 months' latency). It includes a dynamic anthropogenic emission model, which uses easily available statistics on economic activity, energy use, and weather to generate anthropogenic emissions with dynamic time profiles at high spatial and temporal resolution (0.1×0.2 ∘ , hourly). Hourly net ecosystem productivity (NEP) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEP is downscaled to 0.1×0.2 ∘ using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. Ocean CO2 fluxes are included in our product, based on Jena CarboScope ocean CO2 fluxes, which are downscaled using wind speed and temperature. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe. We assess the skill of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 European drought, (b) to capture the reduction of anthropogenic emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ECMWF-IFS, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city center of Amsterdam (the Netherlands). We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and anthropogenic emissions (COVID-19 pandemic in 2020). After applying transport of emitted CO2 , the CTE-HR fluxes have lower median root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor person's inversion). RMSEs are close to those of the reanalysis with the CTE data assimilation system. This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE. We furthermore compare CO2 concentration observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different emission sectors in summer and winter. Interestingly, in periods where synoptic-scale transport variability dominates CO2 concentration variations, the CTE-HR fluxes perform similarly to low-resolution fluxes (5– 10× coarsened). The remaining 10 % of the simulated CO2 mole fraction differs by >2 ppm between the low-resolution and high-resolution flux representation and is clearly associated with coherent structures ("plumes") originating from emission hotspots such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely populated region like the Amsterdam city center, our modeled fluxes underestimate the magnitude of measured eddy covariance fluxes but capture their substantial diurnal variations in summertime and wintertime well. We conclude that our product is a promising tool for modeling the European carbon budget at a high resolution in near real time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near-real-time monitoring and modeling, for example, as an a priori flux product in a CO2 data assimilation system. The data are available at 10.18160/20Z1-AYJ2. [ABSTRACT FROM AUTHOR]