Unrevealing the coupling coordination degree between atmospheric CO2 concentration and human activities from geospatial and temporal perspectives.

Anthropogenic activities exhibit intricate and significant relationships with atmospheric CO2 concentration. Dissecting the spatiotemporal patterns and potential drivers of their coupling coordination relationships from geospatial and temporal perspectives contributes to the benign coordinating development between the two. The coupling coordination degree (D) and types, and their potential influencing factors in China were explored using a coupling coordination model, emerging hotspot analysis, and Multiscale Geographically Weighted Regression model. Results revealed D was dominated by basic coordination in China with notable spatial disparities. Generally, D exhibited higher values in the eastern regions and lower values in the western regions divided by the Hu Line. Furthermore, Central and East China exhibited lower coordination degrees compared to other eastern regions. A total of 15 spatiotemporal dynamic patterns were identified across China. Hot spot patterns were concentrated in the eastern regions of the Hu Line, while cold spots were mainly observed in the western regions. The coupling coordination types exhibited a distinct pattern of "coordination in the east and incoherence in the west, divided by the Hu Line". Over time, there was a shift from lower-level to more benign coordinated types. Additionally, the D and coupling coordination types demonstrated significant spatial agglomeration characteristics, and intercity alliances and enhanced collaborations are essential for sustaining low-carbon improvements. The mechanisms and intensities of various factors on D exhibited spatiotemporal differences. The key drivers influencing coupling coordination types varied depending on the specific type. Additionally, the scales of these drivers affecting D changed over time. It is essential to consider natural and meteorological factors and their scaling effects when developing policies to enhance coupling coordination level. These results have significant implications for assessing the relationship between atmospheric CO2 and human activities and provide guidance for implementing effective low-carbon development policies.

Half of the 18O enrichment of leaf sucrose is conserved in leaf cellulose of a C3 grass across atmospheric humidity and CO2 levels.

The 18O enrichment (Δ18O) of cellulose (Δ18OCel) is recognized as a unique archive of past climate and plant function. However, there is still uncertainty regarding the proportion of oxygen in cellulose (pex) that exchanges post-photosynthetically with medium water of cellulose synthesis. Particularly, recent research with C3 grasses demonstrated that the Δ18O of leaf sucrose (Δ18OSuc, the parent substrate for cellulose synthesis) can be much higher than predicted from daytime Δ18O of leaf water (Δ18OLW), which could alter conclusions on photosynthetic versus post-photosynthetic effects on Δ18OCel via pex. Here, we assessed pex in leaves of perennial ryegrass (Lolium perenne) grown at different atmospheric relative humidity (RH) and CO2 levels, by determinations of Δ18OCel in leaves, Δ18OLGDZW (the Δ18O of water in the leaf growth-and-differentiation zone) and both Δ18OSuc and Δ18OLW (adjusted for εbio, the biosynthetic fractionation between water and carbohydrates) as alternative proxies for the substrate for cellulose synthesis. Δ18OLGDZW was always close to irrigation water, and pex was similar (0.53 ± 0.02 SE) across environments when determinations were based on Δ18OSuc. Conversely, pex was erroneously and variably underestimated (range 0.02-0.44) when based on Δ18OLW. The photosynthetic signal fraction in Δ18OCel is much more constant than hitherto assumed, encouraging leaf physiological reconstructions.

18 O enrichment of sucrose and photosynthetic and nonphotosynthetic leaf water in a C3 grass-atmospheric drivers and physiological relations.

The 18 O enrichment (Δ18 O) of leaf water affects the Δ18 O of photosynthetic products such as sucrose, generating an isotopic archive of plant function and past climate. However, uncertainty remains as to whether leaf water compartmentation between photosynthetic and nonphotosynthetic tissue affects the relationship between Δ18 O of bulk leaf water (Δ18 OLW ) and leaf sucrose (Δ18 OSucrose ). We grew Lolium perenne (a C3 grass) in mesocosm-scale, replicated experiments with daytime relative humidity (50% or 75%) and CO2 level (200, 400 or 800 µmol mol-1 ) as factors, and determined Δ18 OLW , Δ18 OSucrose and morphophysiological leaf parameters, including transpiration (Eleaf ), stomatal conductance (gs ) and mesophyll conductance to CO2 (gm ). The Δ18 O of photosynthetic medium water (Δ18 OSSW ) was estimated from Δ18 OSucrose and the equilibrium fractionation between water and carbonyl groups (εbio ). Δ18 OSSW was well predicted by theoretical estimates of leaf water at the evaporative site (Δ18 Oe ) with adjustments that correlated with gas exchange parameters (gs or total conductance to CO2 ). Isotopic mass balance and published work indicated that nonphotosynthetic tissue water was a large fraction (~0.53) of bulk leaf water. Δ18 OLW was a poor proxy for Δ18 OSucrose , mainly due to opposite Δ18 O responses of nonphotosynthetic tissue water (Δ18 Onon-SSW ) relative to Δ18 OSSW , driven by atmospheric conditions.

[Simulation of Anthropogenic CO2 Emissions in the Yangtze River Delta Based on Different Emission Inventories].

Nowadays, great uncertainty still exists on the urban- and regional-scale anthropogenic CO2 emission estimation based on emission inventories. In order to achieve the carbon peaking and neutrality targets for China, it is urgent to accurately estimate anthropogenic CO2 emissions at regional scales, especially in large urban agglomerations. Using two inventories (EDGAR v6.0 inventory and a modified inventory combining EDGAR v6.0 with GCG v1.0) as prior anthropogenic CO2 emission datasets andtaking themas input data respectively, this study utilized the WRF-STILT atmospheric transport model to simulate atmospheric CO2 concentration in the Yangtze River Delta region from December 2017 to February 2018. The simulated atmospheric CO2 concentrations were further improved by referencing atmospheric CO2 concentration observation at a tall tower in Quanjiao County of Anhui Province and using the scaling factors obtained from the Bayesian inversion method. An estimation of anthropogenic CO2 emission flux in the Yangtze River Delta regionwas finally accomplished. The results indicated that:①in winter, in comparison to the atmospheric CO2 concentration simulated based on EDGAR v6.0, the atmospheric CO2 concentration simulated based on the modified inventory was more consistent with observed values. ②The simulated atmospheric CO2 concentration was higher than observation at night and lower than observation during the daytime. The CO2 emission data of emission inventories could not fully reflect the diurnal variation in anthropogenic emissions, andtheoverestimation, caused by the simulated low-atmospheric boundary layer height at night, of the contribution from point sources with higher emission height near the observation station were the main reasons. ③The simulation performance on atmospheric CO2 concentration was greatly affected by the emission bias of the EDGAR grid points that significantly contributed to concentrations of the observation station, and this indicated that the uncertainty in the spatial distribution in EDGAR emission was the main factor influencing the simulation accuracy. ④The posterior anthropogenic CO2 emission flux in the Yangtze River Delta from December 2017 to February 2018 was around (0.184±0.006) mg·(m2·s)-1and (0.183±0.007) mg·(m2·s)-1 based on EDGAR and the modified inventory, respectively. It is suggested that the inventories with higher temporal and spatial resolutions and more accurate spatial emission distribution should be selected as the prior emissions to obtain a more accurate estimation of the regional anthropogenic CO2 emissions.

Respiratory and Photosynthetic Responses of Antarctic Vascular Plants Are Differentially Affected by CO2 Enrichment and Nocturnal Warming.

Projected rises in atmospheric CO2 concentration and minimum night-time temperatures may have important effects on plant carbon metabolism altering the carbon balance of the only two vascular plant species in the Antarctic Peninsula. We assessed the effect of nocturnal warming (8/5 °C vs. 8/8 °C day/night) and CO2 concentrations (400 ppm and 750 ppm) on gas exchange, non-structural carbohydrates, two respiratory-related enzymes, and mitochondrial size and number in two species of vascular plants. In Colobanthus quitensis, light-saturated photosynthesis measured at 400 ppm was reduced when plants were grown in the elevated CO2 or in the nocturnal warming treatments. Growth in elevated CO2 reduced stomatal conductance but nocturnal warming did not. The short-term sensitivity of respiration, relative protein abundance, and mitochondrial traits were not responsive to either treatment in this species. Moreover, some acclimation to nocturnal warming at ambient CO2 was observed. Altogether, these responses in C. quitensis led to an increase in the respiration-assimilation ratio in plants grown in elevated CO2. The response of Deschampsia antarctica to the experimental treatments was quite distinct. Photosynthesis was not affected by either treatment; however, respiration acclimated to temperature in the elevated CO2 treatment. The observed short-term changes in thermal sensitivity indicate type I acclimation of respiration. Growth in elevated CO2 and nocturnal warming resulted in a reduction in mitochondrial numbers and an increase in mitochondrial size in D. antarctica. Overall, our results suggest that with climate change D. antarctica could be more successful than C. quitensis, due to its ability to make metabolic adjustments to maintain its carbon balance.

Negative emissions technologies: A complementary solution for climate change mitigation.

Carbon dioxide (CO2) is the main greenhouse gas (GHG) and its atmospheric concentration is currently 50% higher than pre-industrial levels. The continuous GHGs emissions may lead to severe and irreversible consequences in the climate system. The reduction of GHG emissions may be not enough to mitigate climate change. Consequently, besides carbon capture from large emission sources, atmospheric CO2 capture may be also required. To meet the target defined for climate change mitigation, the removal of 10 Gt·yr-1 of CO2 globally by mid-century and 20 Gt·yr-1 of CO2 globally by the end of century. The technologies applied with this aim are known as negative emission technologies (NETs), as they lead to achieve a negative balance of carbon in atmosphere. This paper aims to present the recent research works regarding NETs, focusing the research findings achieved by academic groups and projects. Besides several advantages, NETs present high operational cost and its scale-up should be tested to know the real effect on climate change mitigation. With current knowledge, no single process should be seen as a solution. Research efforts should be performed to evaluate and reduce NETs costs and environmental impact.

An Assessment of Anthropogenic CO2 Emissions by Satellite-Based Observations in China.

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas and its concentration in atmosphere has been increasing rapidly due to the increase of anthropogenic CO2 emissions. Quantifying anthropogenic CO2 emissions is essential to evaluate the measures for mitigating climate change. Satellite-based measurements of greenhouse gases greatly advance the way of monitoring atmospheric CO2 concentration. In this study, we propose an approach for estimating anthropogenic CO2 emissions by an artificial neural network using column-average dry air mole fraction of CO2 (XCO2) derived from observations of Greenhouse gases Observing SATellite (GOSAT) in China. First, we use annual XCO2 anomalies (dXCO2) derived from XCO2 and anthropogenic emission data during 2010⁻2014 as the training dataset to build a General Regression Neural Network (GRNN) model. Second, applying the built model to annual dXCO2 in 2015, we estimate the corresponding emission and verify them using ODIAC emission. As a results, the estimated emissions significantly demonstrate positive correlation with that of ODIAC CO2 emissions especially in the areas with high anthropogenic CO2 emissions. Our results indicate that XCO2 data from satellite observations can be applied in estimating anthropogenic CO2 emissions at regional scale by the machine learning. This developed method can estimate carbon emission inventory in a data-driven way. In particular, it is expected that the estimation accuracy can be further improved when combined with other data sources, related CO2 uptake and emissions, from satellite observations.

[Effects of elevated atmospheric CO2 concentration on the stability of soil organic carbon in different layers of a paddy soil.] / 大气CO2浓度升高对不同层次水稻土有机碳稳定性的影响.

It is vital to study the effects of elevated atmospheric CO2 concentration on the soil orga-nic carbon (SOC) stability in different soil layers for better understanding the mechanism of SOC transformation under the elevated atmospheric CO2 concentration. The paddy soil in a long-term FACE (Free Air Carbon-dioxide Enrichment) experiment was selected as the research object. Through the SOC physical fractionation and soil mineralization incubation, the effects of elevated atmospheric CO2 concentration on the soil organic carbon (SOC) content, particle organic matter (POM) content, SOC mineralization intensity, and enzyme activities were measured. Then, the effects of elevated atmospheric CO2 concentration on the SOC stability in different layers were exa-mined. The results showed that the elevated atmospheric CO2 concentration had no significant effect on SOC content, but significantly increased the POM-C content by 93.7% and the invertase and polyphenol oxidase activities by 61.1% and 83.7% in the topsoil layer, respectively. These results indicated that SOC stability of topsoil was reduced under the elevated atmospheric CO2 concentration. However, the elevated atmospheric CO2 concentration had no significant effect on the SOC stability of deep soil layer. Our results would help assess the capacity of soil sequestrated and accumulated organic carbon and provide basis for scientific management of farmland under greenhouse effect in the future.

The response of ecosystem water-use efficiency to rising atmospheric CO2 concentrations: sensitivity and large-scale biogeochemical implications.

Ecosystem water-use efficiency (WUE) is an important metric linking the global land carbon and water cycles. Eddy covariance-based estimates of WUE in temperate/boreal forests have recently been found to show a strong and unexpected increase over the 1992-2010 period, which has been attributed to the effects of rising atmospheric CO2 concentrations on plant physiology. To test this hypothesis, we forced the observed trend in the process-based land surface model JSBACH by increasing the sensitivity of stomatal conductance (gs ) to atmospheric CO2 concentration. We compared the simulated continental discharge, evapotranspiration (ET), and the seasonal CO2 exchange with observations across the extratropical northern hemisphere. The increased simulated WUE led to substantial changes in surface hydrology at the continental scale, including a significant decrease in ET and a significant increase in continental runoff, both of which are inconsistent with large-scale observations. The simulated seasonal amplitude of atmospheric CO2 decreased over time, in contrast to the observed upward trend across ground-based measurement sites. Our results provide strong indications that the recent, large-scale WUE trend is considerably smaller than that estimated for these forest ecosystems. They emphasize the decreasing CO2 sensitivity of WUE with increasing scale, which affects the physiological interpretation of changes in ecosystem WUE.

[Investigation on effects of elevated atmospheric CO2 concentration on plant-soil system carbon cycling: Based on stable isotopic technique]. / åŸºäºŽç¨³å®šç¢³åŒä½ç´ æŠ€æœ¯ç ”ç©¶å¤§æ°”CO2浓度升高对植物-土壤系统碳循环的影响.

Elevated atmospheric CO2 affects plant photosynthesis process and biomass accumulation, furthermore alters the distribution of photosynthetic carbon (C) above- and below-ground. The formation and turnover of soil organic carbon (SOC) depends on the input of photosynthetic C, so the change of plant physiology and metabolism caused by increasing CO2 concentration will further affect the balance of SOC pool. Therefore, stable isotope 13C technique is powerful for clarifying the influence of elevated atmospheric CO2 on C cycling in plant-soil system, including the distribution of photosynthetic C among plant organs, and the transformation and accumulation of photosynthetic C in soil. This review summarized research focused on the effects of elevated atmospheric CO2 on C cycling in terrestrial ecosystems based on 13C natural abundance or 13C tracing technique, including: 1) isotopic fractionation effect in plant photosynthesis; 2) the distribution of photosynthetic C in plant organs; 3) the transformation and stabilization of photosynthetic C in SOC driven by microbial process. Clarifying the above processes and controlling mechanisms is essential to predict long-term influence of elevated CO2 on C cycling and evaluate the source-sink function of SOC in terrestrial ecosystems.

Does Size Matter? Atmospheric CO2 May Be a Stronger Driver of Stomatal Closing Rate Than Stomatal Size in Taxa That Diversified under Low CO2.

One strategy for plants to optimize stomatal function is to open and close their stomata quickly in response to environmental signals. It is generally assumed that small stomata can alter aperture faster than large stomata. We tested the hypothesis that species with small stomata close faster than species with larger stomata in response to darkness by comparing rate of stomatal closure across an evolutionary range of species including ferns, cycads, conifers, and angiosperms under controlled ambient conditions (380 ppm CO2; 20.9% O2). The two species with fastest half-closure time and the two species with slowest half-closure time had large stomata while the remaining three species had small stomata, implying that closing rate was not correlated with stomatal size in these species. Neither was response time correlated with stomatal density, phylogeny, functional group, or life strategy. Our results suggest that past atmospheric CO2 concentration during time of taxa diversification may influence stomatal response time. We show that species which last diversified under low or declining atmospheric CO2 concentration close stomata faster than species that last diversified in a high CO2 world. Low atmospheric [CO2] during taxa diversification may have placed a selection pressure on plants to accelerate stomatal closing to maintain adequate internal CO2 and optimize water use efficiency.

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis.

Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (Vcmax ). Estimating this parameter using A-Ci curves (net photosynthesis, A, vs intercellular CO2 concentration, Ci ) is laborious, which limits availability of Vcmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO2 concentration (Asat ) measurements, from which Vcmax can be extracted using a 'one-point method'. We used a global dataset of A-Ci curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate Vcmax from Asat via this 'one-point method'. If leaf respiration during the day (Rday ) is known exactly, Vcmax can be estimated with an r(2) value of 0.98 and a root-mean-squared error (RMSE) of 8.19 µmol m(-2) s(-1) . However, Rday typically must be estimated. Estimating Rday as 1.5% of Vcmax, we found that Vcmax could be estimated with an r(2) of 0.95 and an RMSE of 17.1 µmol m(-2) s(-1) . The one-point method provides a robust means to expand current databases of field-measured Vcmax , giving new potential to improve vegetation models and quantify the environmental drivers of Vcmax variation.

Drought × CO2 interactions in trees: a test of the low-intercellular CO2 concentration (Ci ) mechanism.

Models of tree responses to climate typically project that elevated atmospheric CO2 concentration (eCa ) will reduce drought impacts on forests. We tested one of the mechanisms underlying this interaction, the 'low Ci effect', in which stomatal closure in drought conditions reduces the intercellular CO2 concentration (Ci ), resulting in a larger relative enhancement of photosynthesis with eCa , and, consequently, a larger relative biomass response. We grew two Eucalyptus species of contrasting drought tolerance at ambient and elevated Ca for 6-9 months in large pots maintained at 50% (drought) and 100% field capacity. Droughted plants did not have significantly lower Ci than well-watered plants, which we attributed to long-term changes in leaf area. Hence, there should not have been an interaction between eCa and water availability on biomass, and we did not detect one. The xeric species did have higher Ci than the mesic species, indicating lower water-use efficiency, but both species exhibited similar responses of photosynthesis and biomass to eCa , owing to compensatory differences in the photosynthetic response to Ci . Our results demonstrate that long-term acclimation to drought, and coordination among species traits may be important for predicting plant responses to eCa under low water availability.

A new positive relationship between pCO2 and stomatal frequency in Quercus guyavifolia (Fagaceae): a potential proxy for palaeo-CO2 levels.

BACKGROUND AND AIMS: The inverse relationship between atmospheric CO2 partial pressure (pCO2) and stomatal frequency in many species of plants has been widely used to estimate palaeoatmospheric CO2 (palaeo-CO2) levels; however, the results obtained have been quite variable. This study attempts to find a potential new proxy for palaeo-CO2 levels by analysing stomatal frequency in Quercus guyavifolia (Q. guajavifolia, Fagaceae), an extant dominant species of sclerophyllous forests in the Himalayas with abundant fossil relatives. METHODS: Stomatal frequency was analysed for extant samples of Q. guyavifolia collected from17 field sites at altitudes ranging between 2493 and 4497 m. Herbarium specimens collected between 1926 and 2011 were also examined. Correlations of pCO2-stomatal frequency were determined using samples from both sources, and these were then applied to Q. preguyavaefolia fossils in order to estimate palaeo-CO2 concentrations for two late-Pliocene floras in south-western China. KEY RESULTS: In contrast to the negative correlations detected for most other species that have been studied, a positive correlation between pCO2 and stomatal frequency was determined in Q. guyavifolia sampled from both extant field collections and historical herbarium specimens. Palaeo-CO2 concentrations were estimated to be approx. 180-240 ppm in the late Pliocene, which is consistent with most other previous estimates. CONCLUSIONS: A new positive relationship between pCO2 and stomatal frequency in Q. guyavifolia is presented, which can be applied to the fossils closely related to this species that are widely distributed in the late-Cenozoic strata in order to estimate palaeo-CO2 concentrations. The results show that it is valid to use a positive relationship to estimate palaeo-CO2 concentrations, and the study adds to the variety of stomatal density/index relationships that available for estimating pCO2. The physiological mechanisms underlying this positive response are unclear, however, and require further research.

Impacts of climate change drivers on C4 grassland productivity: scaling driver effects through the plant community.

Climate change drivers affect plant community productivity via three pathways: (i) direct effects of drivers on plants; (ii) the response of species abundances to drivers (community response); and (iii) the feedback effect of community change on productivity (community effect). The contribution of each pathway to driver-productivity relationships depends on functional traits of dominant species. We used data from three experiments in Texas, USA, to assess the role of community dynamics in the aboveground net primary productivity (ANPP) response of C4 grasslands to two climate drivers applied singly: atmospheric CO2 enrichment and augmented summer precipitation. The ANPP-driver response differed among experiments because community responses and effects differed. ANPP increased by 80-120g m(-2) per 100 µl l(-1) rise in CO2 in separate experiments with pasture and tallgrass prairie assemblages. Augmenting ambient precipitation by 128mm during one summer month each year increased ANPP more in native than in exotic communities in a third experiment. The community effect accounted for 21-38% of the ANPP CO2 response in the prairie experiment but little of the response in the pasture experiment. The community response to CO2 was linked to species traits associated with greater soil water from reduced transpiration (e.g. greater height). Community effects on the ANPP CO2 response and the greater ANPP response of native than exotic communities to augmented precipitation depended on species differences in transpiration efficiency. These results indicate that feedbacks from community change influenced ANPP-driver responses. However, the species traits that regulated community effects on ANPP differed from the traits that determined how communities responded to drivers.

Trends in plant carbon concentration and plant demand for N throughout this century.

Atmospheric CO2 concentration has increased by 25% over the preindustrial level. A parallel increase in C concentration and decreases in N concentration and δ13C of plants grown throughout this century have been observed in plant specimens stored in herbaria. We tested our previous results in a study of 12 more species collected in the western Mediterranean throughout this century (1920-1930, 1945-1955, and 1985-1990) and tree rings of Quercus pubescens from the same area. These changes were accompanied by apparent increases in condensed tannin concentration. A decreasing trend in δ15N both in herbarium material and tree rings was also found, indicating that ecosystems might cope with higher plant N demand by decreasing N losses and increasing N fixation and mineralization. These results may contribute to a better understanding of the effects of global change on carbon and nitrogen cycling.