Changes In CO2 Concentration Research Articles

Comparison of PBL Heights from Ceilometer Measurements and Greenhouse Gases Concentrations in São Paulo

This paper presents a study conducted in São Paulo, Brazil, where the planetary boundary layer height (PBLH) was determined using ceilometer data and the wavelet covariance transform method. The retrieved PBLH values were subsequently compared with the concentrations of CO2 and CH4 measured at three distinct experimental sites in the city. The period of study was July 2021. This study also included a comparison between ceilometer data and lidar data, which demonstrated the favorable applicability of the ceilometer data for PBLH estimation. An examination of the correlation between changes in average CO2 concentrations and PBLH values revealed stronger correlations for the IAG and UNICID stations, with correlation coefficients (ρ) of approximately −0.86 and −0.85, respectively, in contrast to the Pico do Jaraguá station, which exhibited a lower correlation coefficient of −0.42. When assessing changes in CH4 concentrations against variations in PBL height, the retrieved correlation coefficients were approximately −0.78 for IAG, −0.66 for UNICID, and −0.38 for Pico do Jaraguá. The results indicated that CO2/CH4 concentrations are negatively correlated with PBL heights, with CO2 concentrations showing more significant correlation than CH4. Additionally, among the three measurement stations, IAG measurements displayed the most substantial correlation. The results from this study contribute to the understanding of the relationship between PBLH and greenhouse gas concentrations, emphasizing the potential of remote sensing systems like ceilometers in monitoring and studying atmospheric processes.

Concentration of carbon dioxide in products of combustion of GTE NK-16ST and NK-16-18ST

This paper considers the design of two combustion chambers of a gas turbine engine running on natural gas. One combustion chamber has 32 burners, and the other has 136 nozzles located in two rows in the flame tube head. A major contributor to global warming is considered to be the significant emissions of greenhouse gases, primarily CO2, including those emitted by gas turbine engines and power plants. The reduction of carbon dioxide levels by developing a set of structural measures in the combustion chamber is one of the urgent tasks of engine construction which requires a solution in order to meet modern environmental requirements for gas turbine engines serving as blower drives for gas compressor units. The presented research is dedicated to the analysis of influence of changes in combustion chamber design on reduction of СО2 level in exhaust gases of gas turbine engine NK-16ST. Two modifications of the combustion chamber are considered. The first one was a serial combustion chamber with diffusion combustion, the second one was a modernized combustion chamber with a modified front device. Each of the chambers considered was tested as part of the engine. During the study, combustion products were sampled directly in the exhaust shaft and their concentrations, including the CO2 content, were determined. As a result of this work, it was confirmed that there is a possibility to reduce the concentration of CO2 in the engine combustion products up to 20 % without affecting the engine parameters. This reduction in carbon dioxide content was made possible by reducing the completeness of fuel combustion in the combustion chamber. The obtained data on changes in CO2 concentration can be useful in selecting the most suitable mode of engine operation, and the presented approaches to combustion processes organization can be used by developers in designing combustion chambers of natural gas-fired gas turbine engines.

Impacts of Biomass Burning in Southeast Asia on Tropospheric CO2 Concentration Over South China

AbstractThe field observations imply that the long‐range transport of carbon dioxide (CO2) emitted by biomass burning (BB) in Southeast Asia might impact the atmospheric CO2 in South China, while the transboundary path and the contributions of long‐range transport on atmospheric CO2 concentrations in South China remain poorly understood. In this study, a regional air quality model system (RAQMS) was developed by incorporating the atmospheric process of CO2 to investigate the impacts of BB in Southeast Asia on tropospheric CO2 concentration over South China in spring during 2009–2018. CO2 emissions from BB in Southeast Asia in spring varied greatly from 2009 to 2018, and high monthly mean emissions were concentrated in the west of Myanmar, the border between Myanmar, Thailand and Laos, the north of Laos, and Cambodia, with the maximum reaching 1.0 g m−2 hr−1. Higher monthly mean concentrations of near surface CO2 and tropospheric CO2 produced by BB were mainly distributed in the source regions of Southeast Asia and South China. The monthly mean tropospheric CO2 concentrations produced by BB in Southeast Asia were higher in March 2010, 2014, and 2015, which were obviously related to the interannual variation of BB emission, and affected by the atmospheric circulation as well. The contribution of BB emission in Southeast Asia to the net change of tropospheric CO2 concentration in South China presented a belt distribution from the southwest to the northeast, with a domain average of 5.7%–38.6% over South China in March 2009–2018.

Large spread in interannual variance of atmospheric CO2 concentration across CMIP6 Earth System Models

Numerical Earth System Models (ESMs) are our best tool to predict the evolution of atmospheric CO2 concentration and its effect on Global temperature. However, large uncertainties exist among ESMs in the variance of the year-to-year changes of atmospheric CO2 concentration. This prevents us from precisely understanding its past evolution and from accurately estimating its future evolution. Here we analyze various ESMs simulations from the 6th Coupled Model Intercomparison Projects (CMIP6) to understand the origins of the inter-model uncertainty in the interannual variability of the atmospheric CO2 concentration. Considering the observed period 1986-2013, we show that most of this uncertainty is coming from the simulation of the land CO2 flux internal variability. Although models agree that those variations are driven by El Niño Southern Oscillation (ENSO), similar ENSO-related surface temperature and precipitation teleconnections across models drive different land CO2 fluxes, pointing to the land vegetation models as the dominant source of the inter-model uncertainty.

Temperate grassland vegetation restoration influenced by grazing exclusion and climate change

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003–0.0319 year−1. The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration.

Quantifying the Impact of COVID‐19 Pandemic on the Spatiotemporal Changes of CO2 Concentrations in the Yangtze River Delta, China

AbstractWhile the reduction in anthropogenic emissions due to Coronavirus disease 2019 (COVID‐19) lockdown in China and its impact on air quality have been reported extensively, its impact on ambient carbon dioxide (CO2) concentrations is still yet to be assessed. In this study, the impact of emission reductions on spatiotemporal changes of CO2 concentrations during the COVID‐19 pandemic was quantified in the Yangtze River Delta region (YRD), using high‐resolution dynamic emission inventory and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF‐VPRM). The simulated CO2 concentrations from dynamic emission inventory shows a better agreement with surface observations compared with the Open‐source Data Inventory for Anthropogenic CO2 and Emission Database for Global Atmospheric Research emission, providing confidence in the quantification of CO2 concentrations variations. Our results show that emission reductions during the COVID‐19 pandemic lead to a CO2 decrease by 4.6 ppmv (−1.1%) in Shanghai and 3.1 ppmv (−0.7%) in YRD region. For the column‐averaged CO2 concentrations (denoted as XCO2), it also decreases by 0.20 ppmv (−0.05%) in Shanghai and 0.15 ppmv (−0.04%) in YRD region. Furthermore, emission reductions from transportation and industry are major contributors to the decline in CO2 concentrations at the near surface, accounting for 45.8% (41.1%) and 34.9% (41.0%) in Shanghai (YRD). Our study deepens the understanding of the response of CO2 concentrations to different sectors, which is helpful for emission management and climate adaption policies.

The Influence of Validation Colocation on XCO2 Satellite–Terrestrial Joint Observations

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.

An Optical Micro/Nano Fiber Sensor for Monitoring Respiration

In the field of clinical medicine, the real-time monitoring of carbon dioxide (CO2) gas exhaled by the human body is of great significance. At present, the detection devices on the market mainly work by sucking a small amount of gas from the nasal cavity into the detection device, and they present some problems such as overly long sampling tubes, easy blockage or distortion, and an abnormal gas dispersion. In this paper, a micro/nano optical fiber sensor that can directly detect respiration is proposed and is characterized by the relative change in CO2 concentration. The measurement is achieved by using the principle of high evanescent field absorption, and the operating band is 2.004 μm. The sensing effects of micro/nano fibers with different diameters are compared, and the experiment proves that a micro/nano fiber with a diameter of 1 μm can be measured. The light intensity change over 30 s was measured, and the breathing rate was 10–11 times/min. The sensor can achieve a rapid real-time response to CO2 gas detection and is small in size, low-cost, and easy to replace. It has a great application potential in clinical scenarios such as in gastrointestinal endoscopes that require real-time monitoring of human respiration.

The Influence of Bedroom CO2 Concentration on Sleep Quality

A person spends about a third of their life sleeping, and high sleep quality is very important for health. Environmental factors are one of the most important factors affecting sleep quality, and indoor carbon dioxide (CO2) concentration while sleeping has a significant effect on sleep quality. In an indoor bedroom with no open windows and no fresh air system, different numbers of people sleeping will lead to changes in indoor CO2 concentration. In order to study the changes in sleep quality caused by differences in CO2 concentration, experimental research was performed. Objective sleep quality data are collected with polysomnography (PSG) and a subjective questionnaire. The sleep quality of the subjects is tested under three different CO2 concentration levels; the average carbon dioxide concentration of three conditions is 680, 920, and 1350 ppm, which simulate a room with 1, 2, and 3 people sleeping, respectively. Other environment parameters are controlled as follows: test environment temperature is 26 ± 0.5 °C, relative humidity is 50 ± 5%, there is no obvious heat source in the test room, and the radiation temperature and air temperature difference is less than 1 °C. A total of 30 subjective tests were carried out with 10 subjects; the test lasted more than one month. The data subsequently underwent statistical analysis to determine the influence of CO2 concentration on sleep quality. The results show that as the CO2 concentration level increased, the sleep quietness and satisfaction of the subjects gradually decreased, the sleep duration gradually decreased, and symptoms such as throat discomfort, dyspnea, dry and itchy skin, difficulty falling asleep, difficulty waking up, congested nose and bad air smell become more obvious. The PSG test results showed that CO2 concentration has a significant impact on the proportion of the N3 period. According to the group of CO2 concentration conditions, the mean of the N3 period proportion under the conditions of one person, two persons, and three persons is 20.4%, 17.3%, and 14.4%, respectively. Finally, there was also an increase in turning over or awakening during sleep, indicating that sleep quality was reduced under higher CO2 concentrations.

The Impact of Model Resolution on the Southern Hemisphere in Community Climate System Model Version 4 Idealized Climate Simulations

Model resolution plays a large role in accurately simulating the Southern Hemisphere circulation in both the ocean and atmosphere. Resolving the mesoscale field is important as it has been shown to have a significant impact on the large-scale climate in eddy-rich regions, which are regions of large CO2 absorption. The presence of ocean and atmospheric mesoscale features can affect sea surface temperatures, the strength and location of storm tracks, and many other air-sea processes. Additionally, with an improvement in resolution, the eddy kinetic energy in the ocean can be expected to change considerably. The significance model resolution has on the Southern Hemisphere is examined using the Community Climate System Model, Version 4, eddy-parameterizing and eddy-resolving simulations. The CO2 concentrations and ozone levels are specified independently to better understand how the mesoscale field responds to extreme changes in external forcing and the resulting climate impacts. Overall, in the eddy-parameterizing simulations, the ozone forcing is found to be more important than the changes in CO2 concentrations. However, in the case of the eddy-resolving simulations, the CO2 concentrations are found to be more dominant, especially in eddy-rich regions. These results demonstrate the need for an increase in model resolution for climate prediction.

Seasonal variations in source-sink balance of CO2 in subtropical earthen aquaculture ponds: Implications for carbon emission management

Aquaculture ponds serve as focal points for carbon cycling and act as anthropogenic contributors to the emission of carbon dioxide (CO2). To understand the seasonal CO2 dynamics within the ponds, we measured the CO2 concentrations in sediment porewater and the water column in aquaculture ponds in the Shanyutan Wetland in China. Subsequently, the sediment-to-water and water-to-air CO2 fluxes were calculated based on the gas transfer coefficient model. Our results showed that that CO2 flux ranged 0.01–4.58 mmol m−2h−1 across the sediment-to-water interface and −0.08 to 0.45 mmol m−2h−1 across the water-to-air interface throughout the farming period. Photosynthetic activity was the key driver of the temporal variations in water column CO2 concentration and water-to-air CO2 flux, while the change in porewater CO2 concentration and sediment-to-water CO2 flux were governed by sediment temperature which drive the microbial decomposition of organic matter. Based on a simple mass balance approach, the apparent CO2 consumption (ACC) in the water column across all seasons ranged from 0.24 to 2.32 mmol m−2h−1, indicating that the pond water body had a high capacity to “consume” the excess CO2. Our results highlight that the contrasting roles between the sediment compartment and water column compartment in CO2 dynamics, and the possibility to manipulate ACC to reduce the aquaculture carbon footprint.

Prediction and Comparison of In-Vehicle CO2 Concentration Based on ARIMA and LSTM Models

An increase in the carbon dioxide (CO2) concentration within a vehicle can lead to a decrease in air quality, resulting in numerous adverse effects on the human body. Therefore, it is very important to know the in-vehicle CO2 concentration level and to accurately predict a concentration change. The purpose of this research is to investigate in-vehicle concentration levels of CO2, comparing the accuracy of an autoregressive integrated moving average (ARIMA) model and a long short-term memory (LSTM) model in predicting the change in CO2 concentration. We conducted a field test to obtain in-vehicle original concentration data of CO2 while driving, establishing a prediction model of CO2 concentration with ARIMA and LSTM. We selected mean absolute percentage error (MAPE) and root mean squared error (RMSE) as the evaluation indicators. The findings indicate the following: (1) With the vehicle windows closed and recirculation ventilation mode activated, in-vehicle CO2 concentration increases rapidly. During testing, CO2 accumulation rates were measured at 1.43 ppm/s for one occupant and 3.52 ppm/s for three occupants within a 20 min driving period. Average concentrations exceeded 1000 ppm, so it is recommended to improve ventilation promptly while driving. (2) The MAPE of ARIMA and LSTM prediction results are 0.46% and 0.56%, respectively. The RMSE results are 19.62 ppm and 22.76 ppm, respectively. The prediction results demonstrate that both models effectively forecast changes in a vehicle’s interior environment CO2, but the prediction accuracy of ARIMA is better than that of LSTM. The research findings provide theoretical guidance to traffic safety managers in selecting suitable models for predicting in-vehicle CO2 concentrations and establish an effective in-vehicle ventilation warning control system.

Stalagmite-based long-term and multi-centennial hydroclimatic variations in southwestern China during the Holocene and relations to global climate change

Knowing the behavior of the Asian summer monsoon (ASM) and its global correlation help understand roles of the ASM in global climate change. Here we synthesize a stalagmite δ18O record, based on a new record and an available nearby record, both covering the nearly entire Holocene. The synthesized δ18O record correlates with meridional migration of the Intertropical Convergence Zone (ITCZ), and with change in inter-subtropical insolation contrast throughout the Holocene. However, its correlation with the Atlantic meridional overturning circulation (AMOC) broken down during the period of the strongest ASM, when the AMOC weakened. This scenario points to a persistent influence of the ITCZ and subtropical insolation contrast on the change in ASM throughout the Holocene. Our record also correlates with a change in atmospheric CO2 concentration on the multi-millennial scale. These correlations of our cave record with variations in the ITCZ, subtropical insolation contrast, and CO2 level indicate that changes in low-latitude climates, including the ASM, were involved in the evolution of the Holocene CO2 concentration. These changes in the low-latitude climates were likely connected with variation in the Holocene southern westerly wind, which modulated upwelling of carbon-enriched deep ocean water around Antarctica. On the multi-centennial scale, seven weak ASM events are identified, with the magnitudes of the Younger Dryas and the events at 9.8 ka and 8.2 ka event broadly three and two times larger than the other ones. These events have a quasi-period of approximately 1.463 ka. This period in the monsoon regime probably arose from solar activity, but involving the feedback of ENSO. In summary, our study provides insights into the connection of the Holocene ASM with tropical climate, and into the involvement of the ASM in the change of the Holocene CO2 concentration.

Emission of greenhouse gas from urban polluted river during different rainfall events: Typhoon and storm will promote stronger evasions

Urban rivers have been recognized as significant hotspots for greenhouse gas (GHG) emissions. However, the impact of storms or typhoons on GHG emissions from urban rivers is not well understood. Suzhou Creek located in the highly developed urban area of Shanghai was selected to investigate of changes in CO2, CH4, and N2O concentrations and diffusive fluxes during different rainfall events from May to October 2021. The findings showed that urban rivers were sources of GHG emissions during various events. The average diffusive fluxes of CO2, CH4, and N2O during typhoon events were 1 to 2 orders of magnitude higher than those during non–typhoon period, revealing that typhoon greatly promote GHG evasion. GHG CO2–equivalents were ranked as follows: during typhoon (3.93 g m–2h−1) > post–typhoon (0.89 g m–2h−1) > high precipitation (0.33 g m–2h−1) > non–precipitation (0.29 g m–2h−1) > small precipitation (0.25 g m–2h−1). Rainfall dilution, pump station drainage, sediment disturbance, and a high gas transfer coefficient induced by typhoons were the main factors affecting GHG emissions. Nutrients, chlorophyll-a, and dissolved oxygen in river water were important control parameters for GHG production. Overall, typhoon would release large amounts of GHG from urban rivers. Given the projected increase in the frequency and complexity of extreme weather events, this study highlights the importance of better understanding the dynamic response of urban river GHG to rainfall and typhoons.

Changes in CO2 concentration and degassing of eutrophic urban lakes associated with algal growth and decline

Urban lakes are numerous in the world, but their role in carbon storage and emission is not well understood. This study aimed to answer the critical questions: How does algal growing season influence carbon dioxide concentration (cCO2) and exchange flux (FCO2) in eutrophic urban lakes? We investigated trophic state, seasonality of algal productivity, and their association with CO2 dynamics in four urban lakes in Central China. We found that these lightly-to moderately-eutrophic urban lakes showed a shifting pattern of CO2 source-sink dynamics. In the non-algal bloom phase, the moderately-eutrophic lakes outgassed on average of 12.18 ± 24.37 mmol m−2 d−1 CO2; but, during the algal bloom phase, the lakes sequestered an average 1.07 ± 6.22 mmol m−2 d−1 CO2. The lightly-eutrophic lakes exhibited lower CO2 emission in the algal bloom (0.60 ± 10.24 mmol m−2 d−1) compared to the non-algal bloom (3.84 ± 12.38 mmol m−2 d−1). Biological factors such as Chl-a (chlorophyll a) and AOU (apparent oxygen utilization), were found to be important factors to potentially affect the shifting pattern of lake CO2 source-sink dynamics in moderately-eutrophic lakes, explaining 48% and 34% of the CO2 variation in the non-algal and algal bloom phases, respectively. Moreover, CO2 showed positive correlations with AOU, and negative correlations with Chl-a in both phases. In the lightly-eutrophic lakes, biological factors explained a higher proportion of CO2 variations (29%) in the non-algal bloom phase, with AOU accounting for 19%. Our results indicate that algal growth and decline phases largely affect dissolved CO2 level and exchange flux by regulating in-lake respiration and photosynthesis. Based on the findings, we conclude that shallow urban lakes can act as both sources and sinks of CO2, with algal growth seasonality and trophic state playing pivotal roles in controlling their carbon dynamics.

Tracing Low‐CO2 Fluxes in Soil Incubation and 13C Labeling Experiments: A Simplified Gas Sampling System for Respiration and Photosynthesis Measurements

AbstractQuantifying carbon dioxide (CO2) fluxes between soil and atmosphere is key in understanding net ecosystem C exchange and biogeochemical C cycling in plant‐soil systems. In ecosystems with low primary production and sparse vegetation, for example, dry lands or subpolar regions where C fluxes are small, measurement sensitivity is key—even so when measurements are combined with isotopic labeling. Here, we present a simplified gas sampling system developed to facilitate sampling and measurement of low soil CO2 fluxes as well as in situ 13CO2 labeling in the same setup. The capacity of the system was tested in a set of feature tests along with gas measurements of dryland soil‐biocrust systems. The system's sensitivity to capture minor changes in CO2 concentration was confirmed in respiration and photosynthesis measurements of soil‐biocrust systems, where fluxes down to 0.1 μmol CO2 m−2 s−1 were quantified. A balloon, implemented to counterbalance underpressure build‐up during gas withdrawal, mitigated 72% of pressure differences at sampling. The overall system volume was reduced to a minimum to limit contamination caused by residual air, and the design enabled one‐step flushing and evacuation of system compartments and gas sample bags, successfully ruling out cross‐contamination between samples. Ultimately, this system offers a flexible and accessible solution for CO2 measurements that can be applied not only on arid soils with low biological activity and turnover rates, but also on plant‐soil systems. The modifications enabled larger, and thereby more representative, sample volumes to be collected while limiting incubation, contamination, and pressure effects on the intact soil system.

Reversible decentralized ventilation: Experimental determination of efficiency by carbon dioxide level

We studied decentralized ventilation devices based on a regenerative heat exchanger with a reverse mode of operation. These devices are capable of recovering up to 90% of the heat used for ventilation of premises. They are a cheaper alternative to central units, and can solve the problem of high heat consumption for ventilation of buildings. Such devices are of little use in practice, since their efficiency concerning providing the required air exchange is poorly studied. The reverse mode of operation is not typical for room ventilation, since the same device constantly changes its purpose between supply and exhaust, which constantly changes the air distribution pattern in the room and can affect the efficiency of dilution and removal of harmful substances. Taking this fact into account makes the study original. The aim of the study is to experimentally determine the efficiency of ventilation in the premises of civil buildings when using such devices. The efficiency criterion was the level of carbon dioxide concentration in the room with a specified limit value of 1000 ppm. People were the source of carbon dioxide. Ventilation was represented by two decentralized devices. The experiment consisted in determining the level of carbon dioxide concentration in natural conditions with a different number of people in the room and different ventilation performance. The results of the experiment were verified by analytical determination of the level of carbon dioxide in the room. As a result of the experiment, dependences of changes in CO2 concentration over time were obtained when one, two and five people were in a room with and without ventilation. To ensure the level of carbon dioxide concentration below the limit (1000 ppm), the required ventilation capacity for one person was 40 m3/h, for two people – 80 m3/h, for five people – more than 160 m3/h. The results allow us to make conclusions about the efficiency of decentralized ventilation devices with reversible mode for premises with a small number of people.

Activated Carbon Electrodes with Enhanced Supercapacitive Swing Adsorption of Carbon Dioxide

Activated carbon electrodes with enhanced supercapacitive swing adsorption of carbon dioxide The necessity to achieve net-zero emission of anthropogenic CO2 by the end of the twenty first century has recently raised interest among researchers to develop electrochemical CO2 capture technologies due to their high selectivity, low energy consumption, and ease to be powered with renewable electricity. Currently, most of these technologies rely on the use of expensive adsorbing electrode materials, and ion-selective membranes.1 Supercapacitive swing adsorption (SSA) is a technique that only requires activated carbon electrodes, a separator, and an aqueous electrolyte to capture and concentrate CO2 during the capacitive charging and discharging of carbon electrodes, making it attractive from the cost and environmental perspective.2 Recent studies on SSA focused on improving the energetic and adsorptive performance by tuning the electrolyte concentration, composition, and electrode charging protocols.3 However, the adsorption capacity stayed around 100 mmol/kg (compared to ∼1000 mmol/kg for amine scrubbing) even at higher electrolyte concentrations and extended voltage windows.2,4 Herein, we report high surface area activated carbon electrodes derived from biomass, coke, coal, and carbide for SSA. We find a strong correlation between capacitance and CO2 adsorption capacity and quantitatively analyze the energetic and adsorptive performance of different electrode materials. Biomass-derived garlic roots-derived activated carbon (GR-AC) electrodes show 4-fold enhanced adsorption capacity (270 mmol/kg) and 3.2-fold enhanced adsorption rate (84 μmol.kg-1.s-1) compared to state-of-the-art coal-derived carbon. However, GR-AC electrodes showed an energy consumption of 179 kJ/mol. Modifying the activation treatment from KOH-based two-step process to K2CO3-based one-step process yielded micro-mesoporous activated carbon. Warm-pressed electrodes from this carbon showed lower energy consumption (72 kJ/mol) and improved gravimetric/volumetric adsorption capacity (312 mmol/kg and 86 mol/m3). Increasing the voltage window from 1 V to 1.6 V resulted in even higher adsorption capacity (524 mmol/kg at -1.4 V and 578 mmol/kg at -1.6 V) as well as improved gas purity (Figure 1). Cyclic voltammetry and electrochemical impedance spectroscopy confirmed the capacitive-type behavior of electrodes up to 1.4 V.Figure 1 Voltage response (black) and CO2 concentration changes (blue) at different voltage windows References R. Sharifian, R. M. Wagterveld, I. A. Digdaya, C. Xiang, and D. A. Vermaas, Energy Environ. Sci., 14, 781–814 (2021).S. Zhu, J. Li, A. Toth, and K. Landskron, ACS Appl. Energy Mater., 2, 7449–7456 (2019).M. Rahimi, A. Khurram, and T. A. Hatton, Chem Soc Rev (2022).T. B. Binford, G. Mapstone, I. Temprano, and A. C. Forse, Nanoscale (2022). Figure 1

Relationship between CO2 Fertilization Effects, and Stand Age, Stand Type, and Site Conditions

The CO2 fertilization effect (CFE) plays a crucial role in the amelioration of climate change. Many physiological and environmental factors, such as stand age, stand type, and site conditions, may affect the extent of the CFE. However, the relationship between the CFE and these factors remains elusive. In this study, we used the emerging gross primary production (GPP) remote sensing products, with GPP predicted using eddy covariance–light use efficiency models (EC-LUE GPP) based on satellite near-infrared reflectance of vegetation (NIRv GPP) and assessed with a random forest model to explore the CFE trends with stand age in a coniferous forest and a broad-leaved forest in Heilongjiang Province, China. We additionally compared the differences among the CFEs under different site conditions. The CFEs in coniferous forests and broad-leaved forests both showed a rapid increase in stands of 10 to 20 years of age, followed by a decline after reaching a maximum, with the rate of decline reducing with age. Eventually, CFE remained stable in stands near 100 years of age. However, the CFE in coniferous forests exhibited more extended periods of rapid increase and a higher maximum than in broad-leaved forests. Moreover, in this study, we used the site class index (SCI) to grade site conditions. The results demonstrate that the CFE differed significantly under different levels of site conditions, and these differences gradually decreased with age. The site with the highest SCI had fewer environmental restrictions on the CFE, and consequently, the CFE rate of decline was faster. Our results are of significance in understanding the CFE and adapting to future changes in atmospheric CO2 concentration.

Effects of paleogeographic changes and CO2 variability on northern mid-latitudinal temperature gradients in the Cretaceous

The Cretaceous ‘greenhouse’ period (~145 to ~66 million years ago, Ma) in Earth’s history is relatively well documented by multiple paleoproxy records, which indicate that the meridional sea surface temperature (SST) gradient increased (non-monotonically) from the Valanginian (~135 Ma) to the Maastrichtian (~68 Ma). Changes in atmospheric CO2 concentration, solar constant, and paleogeography are the primary drivers of variations in the spatiotemporal distribution of SST. However, the particular contribution of each of these drivers (and their underlying mechanisms) to changes in the SST distribution remains poorly understood. Here we use data from a suite of paleoclimate simulations to compare the relative effects of atmospheric CO2 variability and paleogeographic changes on mid-latitudinal SST gradient through the Cretaceous. Further, we use a fundamental model of wind-driven ocean gyres to quantify how changes in the Northern Hemisphere paleogeography weaken the circulation in subtropical ocean gyres, leading to an increase in extratropical SSTs.