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In this study, the trajectory mapping domain-filling technology, which can provide more reliable statistical estimates of long-lived gas concentrations in a broader geographical area based on limited station data, is used to map the CO2 concentration data of six ground observation stations to the entire Shanxi Province. The technology combines a dynamical model of the atmosphere with trace gas observations, combining forward and backward trajectories to greatly expand the information on long-lived CO2 gas concentrations over a trajectory path. The mapped results show good agreement with the observation results, which reveals the generalizability of the trajectory mapping domain-filling technology. The results show that the spatio-temporal distribution characteristics of CO2 concentration in the entire Shanxi region is significant: during the five years, the provincial average CO2 concentration exhibits an overall increasing trend. The CO2 concentration increases from the north to the south across the province. Influenced by the economic growth rate and COVID-19, there are differences in the annual variation characteristics of the CO2 concentration across the entire province, with the highest year-on-year growth in 2019 and a year-on-year decrease in 2020. The increasing rate of the CO2 concentration in the northern low-value areas is faster than that in the southern high-value areas. Overall, there is a decreasing trend in the CO2 concentration growth from the north to the south in the entire province. There are seasonal differences in the CO2 concentration distribution across the entire province. The CO2 concentration and amplitude are higher in autumn and winter than they are in spring and summer. This study can provide scientific support and methodological reference for the spatio-temporal distribution characteristics analysis of GHGs at the provincial–regional scale, as well as at the national and global scales.

Comparing satellite retrieval with high-precision ground observations is an essential component for the validation of CO2 satellite products. The initial stage of assessing the bias in retrieval products from satellite and ground sources involves establishing a geographical connection between observations that are temporally and spatially proximate. The primary aim of this paper is to evaluate the influence of variations in neighborhood definitions and colocation methods on the assessment of satellite products and provide quantitative references. To achieve this, a series of experiments were conducted involving the Global Total Column Carbon Observation Network (TCCON) and the OCO-2 satellite. Various spatial-temporal neighborhoods and colocation methods were considered in these experiments. The results indicate that spatial neighborhoods exert a more substantial influence on bias compared to temporal neighborhoods. In the mid-latitudes of the Northern Hemisphere, there is an observed linear increase trend between the difference of OCO-2 and TCCON observations and the spatial neighborhood, with an average increase of 0.32 ppm as the neighborhood size changes from 1° to 10°. Regarding colocation methods, the simple spatiotemporal geographic constraints tend to overlook changes in the atmospheric state to a certain extent. The target geographic constraint method reduces the bias by 2% to 5% by increasing the proportion of OCO-2 observations targeting TCCON while the method of introducing T700 potential temperature reduces by 2% to 13% by screening the gradient of CO2 concentration change. Moreover, an evident correlation exists between the bias and their corresponding latitudes, with a 0.20 ppm increase in bias observed for every 10° increment in latitudes in the Northern Hemisphere. The bias of TCCON and OCO-2 shows a pronounced seasonal regularity, with the highest in summer. The study also discusses the selection of spatiotemporal matching with low satellite coverage, the bias distribution, and the attribution of bias to the natural wind field.

The relationship between the source and sink of atmospheric CO2 has always been a widely discussed issue in global climate change research. Recent studies revealed that the chemical weathering of carbonate rocks contributed to 1/3 (~0.5 Pg C/yr) of the missing carbon sinks (MCS) globally, and there are still 2/3 of MCS (~0.5 Pg C/yr) that need to be explored. As one of the main overburdened parts of the earth, loess is one of the important driving factors for atmospheric CO2 consumption. Here, we elaborated on the dissolution process and the carbon sink effect from carbonate and silicate minerals in loess. The relationship between carbonate dissolution and carbon source/sink is elucidated, and the mechanism of carbon sink formation from secondary carbonates in loess is clarified. Additionally, the commonly used methods for the identification of primary and secondary carbonates are summarized, and the methods for the study of loess carbon sinks and the influencing factors of loess carbon sinks are also revealed. Based on the research results and progress interpretations, the prospects of loess carbon sinks are discussed to provide a scientific basis for further research on loess carbon sinks.

The increase in CO2 concentration in the atmosphere has prompted the research community to find solutions for this environmental problem, which causes climate change and global warming. CO2 removal through the use of negative emissions technologies could lead to global emission levels becoming net negative towards the end of this century. Among these negative emissions technologies, direct air capture (DAC), in which CO2 is captured directly from the atmosphere, could play an important role. The captured CO2 can be removed in the long term and through its storage can be used for chemical processes, allowing closed carbon cycles in the short term. For DAC, different technologies have been suggested in the literature, and an overview of these is proposed in this work. Absorption and adsorption are the most studied and mature technologies, but others are also under investigation. An analysis of the main key performance indicators is also presented here and it is suggested that more efforts should be made to develop DAC at a large scale by reducing costs and improving efficiency. An additional discussion, addressing the social concern, is indicated as well.

We use data on the following climate variables for the period of the last 798 thousand years: global ice volume (Icet), atmospheric carbon dioxide level (CO2,t), and Antarctic land surface temperature (Tempt). Those variables are cyclical and are driven by the following strongly exogenous orbital variables: eccentricity of the Earth’s orbit, obliquity, and precession of the equinox. We introduce score-driven ice-age models which use robust filters of the conditional mean and variance, generalizing the updating mechanism and solving the misspecification of a recent climate–econometric model (benchmark ice-age model). The score-driven models control for omitted exogenous variables and extreme events, using more general dynamic structures and heteroskedasticity. We find that the score-driven models improve the performance of the benchmark ice-age model. We provide out-of-sample forecasts of the climate variables for the last 100 thousand years. We show that during the last 10–15 thousand years of the forecasting period, for which humanity influenced the Earth’s climate, (i) the forecasts of Icet are above the observed Icet, (ii) the forecasts of CO2,t level are below the observed CO2,t, and (iii) the forecasts of Tempt are below the observed Tempt. The forecasts for the benchmark ice-age model are reinforced by the score-driven models.

Photorespiration, or C2 photosynthesis, is generally considered a futile cycle that potentially decreases photosynthetic carbon fixation by more than 25%. Nonetheless, many essential processes, such as nitrogen assimilation, C1 metabolism, and sulfur assimilation, depend on photorespiration. Most studies of photosynthetic and photorespiratory reactions are conducted with magnesium as the sole metal cofactor despite many of the enzymes involved in these reactions readily associating with manganese. Indeed, when manganese is present, the energy efficiency of these reactions may improve. This review summarizes some commonly used methods to quantify photorespiration, outlines the influence of metal cofactors on photorespiratory enzymes, and discusses why photorespiration may not be as wasteful as previously believed.

We describe and implement a data selection algorithm aimed at identifying background atmospheric CO2 observations from in situ continuous measurements. Several selection criteria for detecting the background data have been developed and are currently used: the main objective of this work was to define a common methodology to extract the atmospheric background signal minimizing heterogeneities due to the use of different selection algorithms. The algorithm used in this study, (BaDS, Background Data Selection) was tested and optimized using data (from 2014 to 2018) from four Italian stations characterized by markedly different environmental conditions (i.e., mountain, coastal and marine): Plateau Rosa (PRS), Mt. Cimone (CMN), Capo Granitola (CGR) and Lampedusa (LMP). Their locations extend from the Alps to the central Mediterranean. The adopted algorithm proved to be effective in separating the local/regional from the background signal in the CO2 time series. About 6% of the data at LMP, 11% at PRS, 20–38% at CMN and 65% at CGR were identified as non-background. LMP and PRS can be used as reference sites for the central Mediterranean, while CMN and CGR were more impacted by regional sources and sinks. Finally, we discuss a possible application of BaDS screened data.

Changes in the stomatal aperture in response to CO2 levels allow plants to manage water usage, optimize CO2 uptake and adjust to environmental stimuli. The current study reports that sub-ambient CO2 up-regulated the low temperature induction of the C-repeat Binding Factor (CBF)-dependent cold signaling pathway in Arabidopsis (Arabidopsis thaliana) and the opposite occurred in response to supra-ambient CO2. Accordingly, cold induction of various downstream cold-responsive genes was modified by CO2 treatments and expression changes were either partially or fully CBF-dependent. Changes in electrolyte leakage during freezing tests were correlated with CO2′s effects on CBF expression. Cold treatments were also performed on Arabidopsis mutants with altered stomatal responses to CO2, i.e., high leaf temperature 1-2 (ht1-2, CO2 hypersensitive) and β-carbonic anhydrase 1 and 4 (ca1ca4, CO2 insensitive). The cold-induced expression of CBF and downstream CBF target genes plus freezing tolerance of ht1-2 was consistently less than that for Col-0, suggesting that HT1 is a positive modulator of cold signaling. The ca1ca4 mutant had diminished CBF expression during cold treatment but the downstream expression of cold-responsive genes was either similar to or greater than that of Col-0. This finding suggested that βCA1/4 modulates the expression of certain cold-responsive genes in a CBF-independent manner. Stomatal conductance measurements demonstrated that low temperatures overrode low CO2-induced stomatal opening and this process was delayed in the cold tolerant mutant, ca1ca4, compared to the cold sensitive mutant, ht1-2. The similar stomatal responses were evident from freezing tolerant line, Ox-CBF, overexpression of CBF3, compared to wild-type ecotype Ws-2. Together, these results indicate that CO2 signaling in stomata and CBF-mediated cold signaling work coordinately in Arabidopsis to manage abiotic stress.

This paper demonstrates the role of meteorology and air transport in influencing the South African atmospheric CO2 distribution. CO2 data from December 2004 to December 2009 acquired by the Tropospheric Emission Spectrometer (TES) instrument onboard the Aura satellite were used to establish the CO2 vertical distribution at selected regions in South Africa. The Hybrid Single-Particle Lagrangian Integrated Trajectories (HYSPLIT) atmospheric model backward trajectories were used to determine the long-range air transport impacting on South African CO2 atmospheric distribution and to detect the source areas of air masses impacting on South Africa’s atmosphere. The study found that long-range air transport can result in the accumulation or dilution of atmospheric CO2 at various sites in South Africa, depending on the source region and type of air flow. The long-range air transport from different source regions at the upper air level between the 700 and 500 hPa stable layers and the layer above 500 hPa strengthens the inhomogeneity in the vertical distribution of CO2, which is caused by the decoupling effect of the upper air stable layers. This long-range air transport also involves intercontinental air transport.

We have previously demonstrated a pulsed direct detection IPDA lidar to measure range and the column concentration of atmospheric CO2. The lidar measures the atmospheric backscatter profiles and samples the shape of the 1,572.33 nm CO2 absorption line. We participated in the ASCENDS science flights on the NASA DC-8 aircraft during August 2011 and report here lidar measurements made on four flights over a variety of surface and cloud conditions near the US. These included over a stratus cloud deck over the Pacific Ocean, to a dry lake bed surrounded by mountains in Nevada, to a desert area with a coal-fired power plant, and from the Rocky Mountains to Iowa, with segments with both cumulus and cirrus clouds. Most flights were to altitudes >12 km and had 5–6 altitude steps. Analyses show the retrievals of lidar range, CO2 column absorption, and CO2 mixing ratio worked well when measuring over topography with rapidly changing height and reflectivity, through thin clouds, between cumulus clouds, and to stratus cloud tops. The retrievals shows the decrease in column CO2 due to growing vegetation when flying over Iowa cropland as well as a sudden increase in CO2 concentration near a coal-fired power plant. For regions where the CO2 concentration was relatively constant, the measured CO2 absorption lineshape (averaged for 50 s) matched the predicted shapes to better than 1% RMS error. For 10 s averaging, the scatter in the retrievals was typically 2–3 ppm and was limited by the received signal photon count. Retrievals were made using atmospheric parameters from both an atmospheric model and from in situ temperature and pressure from the aircraft. The retrievals had no free parameters and did not use empirical adjustments, and >70% of the measurements passed screening and were used in analysis. The differences between the lidar-measured retrievals and in situ measured average CO2 column concentrations were 6 km.

To circumvent the thermodynamic limitation of the synthesis of oxazolidinones starting from 2-aminoethanols and CO2 and realize incorporation CO2 under atmospheric pressure, a protic ionic liquid-facilitated three-component reaction of propargyl alcohols, CO2 and 2-aminoethanols was developed to produce 2-oxazolidinones along with equal amount of α-hydroxyl ketones. The ionic liquid structure, reaction temperature and reaction time were in detail investigated. And 15 mol% 1,5,7-triazabicylo[4.4.0]dec-5-ene ([TBDH][TFE]) trifluoroethanol was found to be able to synergistically activate the substrate and CO2, thus catalyzing this cascade reaction under atmospheric CO2 pressure. By employing this task-specific ionic liquid as sustainable catalyst, 2-aminoethanols with different substituents were successfully transformed to 2-oxazolidinones with moderate to excellent yield after 12 h at 80 °C.

In this paper, we estimate the trends and variability in Advanced Very High Resolution Radiometer (AVHRR)-derived terrestrial net primary productivity (NPP) over India for the period 1982–2006. We find an increasing trend of 3.9% per decade (r = 0.78, R2 = 0.61) during the analysis period. A multivariate linear regression of NPP with temperature, precipitation, atmospheric CO2 concentration, soil water and surface solar radiation (r = 0.80, R2 = 0.65) indicates that the increasing trend is partly driven by increasing atmospheric CO2 concentration and the consequent CO2 fertilization of the ecosystems. However, human interventions may have also played a key role in the NPP increase: non-forest NPP growth is largely driven by increases in irrigated area and fertilizer use, while forest NPP is influenced by plantation and forest conservation programs. A similar multivariate regression of interannual NPP anomalies with temperature, precipitation, soil water, solar radiation and CO2 anomalies suggests that the interannual variability in NPP is primarily driven by precipitation and temperature variability. Mean seasonal NPP is largest during post-monsoon and lowest during the pre-monsoon period, thereby indicating the importance of soil moisture for vegetation productivity.

Active remote sensing of atmospheric XCO2 has several advantages over existing passive remote sensors, including global coverage, a smaller footprint, improved penetration of aerosols, and night observation capabilities. China is planning to launch a multi-functional atmospheric observation satellite equipped with a CO2-IPDA (integrated path differential absorption Lidar) to measure columnar concentrations of atmospheric CO2 globally. As space and power are limited on the satellite, compromises have been made to accommodate other passive sensors. In this study, we evaluated the sensitivity of the system’s retrieval accuracy and precision to some critical parameters to determine whether the current configuration is adequate to obtain the desired results and whether any further compromises are possible. We then mapped the distribution of random errors across China and surrounding regions using pseudo-observations to explore the performance of the planned CO2-IPDA over these regions. We found that random errors of less than 0.3% can be expected for most regions of our study area, which will allow the provision of valuable data that will help researchers gain a deeper insight into carbon cycle processes and accurately estimate carbon uptake and emissions. However, in the areas where major anthropogenic carbon sources are located, and in coastal seas, random errors as high as 0.5% are predicted. This is predominantly due to the high concentrations of aerosols, which cause serious attenuation of returned signals. Novel retrieving methods must, therefore, be developed in the future to suppress interference from low surface reflectance and high aerosol loading.

This paper presents the comparison of two CO2 datasets from the National Institute for Environmental Studies (NIES) of Japan and the Atmospheric CO2 Observations from Space (ACOS) of NASA for three years (2010 to 2012). Both CO2 datasets are retrieved from the Greenhouse gases Observing SATellite (GOSAT) short-wavelength infrared spectra over High gain surface land. In this three-year period, the yield of the NIES CO2 column averaged dry air mole fractions (XCO2) is about 71% of ACOS retrievals. The overall bias is 0.21 ± 1.85 ppm and −0.69 ± 2.13 ppm for ACOS and NIES XCO2, respectively, when compared with ground-based Fourier Transform Spectrometer (FTS) observations from twelve Total Carbon Column Observing Network (TCCON) sites. The differences in XCO2 three-year means and seasonal means are within about 1 to 2 ppm. Strong consistency is obtained for the ACOS and NIES XCO2 monthly averages time series over different regions, with the greatest mean difference of ACOS to NIES monthly means over China (1.43 ± 0.60 ppm) and the least over Brazil (−0.03 ± 0.64 ppm). The intercomparison between the two XCO2 datasets indicates that the ACOS XCO2 is globally higher than NIES by about 1 ppm and has smaller bias and better consistency than NIES data.

Photorespiration, or C 2 photosynthesis, is generally considered a futile cycle that potentially decreases photosynthetic carbon fixation by more than 25%. Nonetheless, many essential processes, such as nitrogen assimilation, C 1 metabolism, and sulfur assimilation, depend on photorespiration. Most studies of photosynthetic and photorespiratory reactions are conducted with magnesium as the sole metal cofactor despite many of the enzymes involved in these reactions readily associating with manganese. Indeed, when manganese is present, the energy efficiency of these reactions may improve. This review summarizes some commonly used methods to quantify photorespiration, outlines the influence of metal cofactors on photorespiratory enzymes, and discusses why photorespiration may not be as wasteful as previously believed.