Energy and emission data are crucial to climate change research and mitigation efforts. The accuracy of energy statistics is essential for mitigation strategies and evaluating the performance of low carbon energy transition efforts. This study provides the most up‐to‐date emission inventories for China and its provinces for 2018 and 2019. We also update the carbon dioxide (CO₂) emission inventories of China and 30 provinces since 2012 based on the newly revised energy statistics. The inventories are compiled in a combined accounting approach of scope 1 (Intergovernmental Panel on Climate Change territorial emissions from 17 types of fossil fuel combustion and cement production by 47 socioeconomic sectors) and scope 2 (emissions from purchased electricity and heat consumption). The most recent energy revision led to an increase in reported national CO₂ emissions by an average of 0.3% from 2014 to 2017. The results show that data revisions raised China's carbon intensity mitigation baseline (in 2005) by 5.1%–10.8% and thus made it more challenging to fulfill the mitigation pledges. However, the 2020 carbon intensity mitigation target was achieved ahead of schedule in 2018. A preliminary estimate of China's national emissions for 2020 shows that the COVID‐19 pandemic and lockdown was not able to offset China's annual increase in CO₂ emissions. These emissions inventories provide an improved evidence base for China's policies toward net‐zero emissions.

For the past decade, observations of carbonyl sulfide (OCS or COS) have been investigated as a proxy for carbon uptake by plants. OCS is destroyed by enzymes that interact with CO₂ during photosynthesis, namely carbonic anhydrase (CA) and RuBisCO, where CA is the more important one. The majority of sources of OCS to the atmosphere are geographically separated from this large plant sink, whereas the sources and sinks of CO₂ are co-located in ecosystems. The drawdown of OCS can therefore be related to the uptake of CO₂ without the added complication of co-located emissions comparable in magnitude. Here we review the state of our understanding of the global OCS cycle and its applications to ecosystem carbon cycle science. OCS uptake is correlated well to plant carbon uptake, especially at the regional scale. OCS can be used in conjunction with other independent measures of ecosystem function, like solar-induced fluorescence and carbon and water isotope studies. More work needs to be done to generate global coverage for OCS observations and to link this powerful atmospheric tracer to systems where fundamental questions concerning the carbon and water cycle remain.

Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO₂ estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO₂ growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001–2015 was 0. 17 ± 0. 11 PgC yr⁻¹ with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.

We present inverse modelling (top down) estimates of European methane (CH₄) emissions for 2006–2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH₄ emissions of 26.8 (20.2–29.7) Tg CH₄ yr⁻¹ (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH₄ emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH₄ yr⁻¹ (2006) to 18.8 Tg CH₄ yr⁻¹ (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH₄ Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3–8.2) Tg CH₄ yr⁻¹ from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH₄ emissions with maxima in summer, while anthropogenic CH₄ emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH₄ compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions, as well as to validate and improve observations from space-based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near-IR solar spectra and to generate the associated data products. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to the conversion of the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc air mass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements. All TCCON data are available through https://tccondata.org/ (last access: 22 April 2024) and are hosted on CaltechDATA (https://data.caltech.edu/, last access: 22 April 2024). Each TCCON site has a unique DOI for its data record. An archive of all the sites' data is also available with the DOI https://doi.org/10.14291/TCCON.GGG2020 (Total Carbon Column Observing Network (TCCON) Team, 2022). The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than 1 year after acquisition. Full details of data locations are provided in the “Code and data availability” section.

We developed and field-tested an unmanned aerial vehicle (UAV)-based active AirCore for atmospheric mole fraction measurements of CO₂, CH₄, and CO. The system applies an alternative way of using the AirCore technique invented by NOAA. As opposed to the conventional concept of passively sampling air using the atmospheric pressure gradient during descent, the active AirCore collects atmospheric air samples using a pump to pull the air through the tube during flight, which opens up the possibility to spatially sample atmospheric air. The active AirCore system used for this study weighs ∼ 1.1 kg. It consists of a ∼ 50 m long stainless-steel tube, a small stainless-steel tube filled with magnesium perchlorate, a KNF micropump, and a 45 µm orifice working together to form a critical flow of dried atmospheric air through the active AirCore. A cavity ring-down spectrometer (CRDS) was used to analyze the air samples on site not more than 7 min after landing for mole fraction measurements of CO₂, CH₄, and CO. We flew the active AirCore system on a UAV near the atmospheric measurement station at Lutjewad, located in the northwest of the city of Groningen in the Netherlands. Five consecutive flights took place over a 5 h period on the same morning, from sunrise until noon. We validated the measurements of CO₂ and CH₄ from the active AirCore against those from the Lutjewad station at 60 m. The results show a good agreement between the measurements from the active AirCore and the atmospheric station (N = 146; R²CO₂: 0.97 and R²CH₄: 0.94; and mean differences: ΔCO₂: 0.18 ppm and ΔCH₄: 5.13 ppb). The vertical and horizontal resolution (for CH₄) at typical UAV speeds of 1.5 and 2.5 m s⁻¹ were determined to be ±24.7 to 29.3 and ±41.2 to 48.9 m, respectively, depending on the storage time. The collapse of the nocturnal boundary layer and the buildup of the mixed layer were clearly observed with three consecutive vertical profile measurements in the early morning hours. Besides this, we furthermore detected a CH₄ hotspot in the coastal wetlands from a horizontal flight north to the dike, which demonstrates the potential of this new active AirCore method to measure at locations where other techniques have no practical access.