Variations In CO2 Concentration Research Articles

Variation of CO2 concentration and its provenance in alpine on the south slope of Tomur Peak, Tianshan Mountains.

This study analyzes the characteristics of near-surface atmospheric CO2 concentrations on the southern slope of Tomur Peak from 2013 to 2022. Utilizing the Boughton two-parameter algorithm, we determined the CO2 background and non-background concentrations. Additionally, the Hysplit model was employed to investigate the potential contributing areas of the CO2 non-background concentration. Our findings that the CO2 concentration in the study area was approximately 17% lower than the global average, with an annual growth rate that was only about 47% of the global rate. The CO2 non-background concentration accounted for only 6.25% of the observed concentration, but was largely unaffected by near-ground meteorological factors. The source of the CO2 non-background was mainly controlled by the westerly belt, with potential source area mainly located in Central Asia. However, the WPSCF values in the modern ice and snow distribution area south of Tomur Peak and west of the monitoring station were significantly elevated, suggesting a strong wind transport of CO2 after accumulation under the influence of the elevated terrain. The local supplying path accounted for only 12.87%, indicating that human activities in the oasis areas of the Tarim Basin had a limited influence on the study area. Due to the blocking effect of the Baikal high-pressure system and the towering topography of the Tianshan Mountains, the influence of human emissions from higher latitudes was likely negligible.

Spatial Variation in CO2 Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere

Spatial Variation in CO2 Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere

Assessment of airborne viral transmission risks in a large-scale building using onsite measurements and CFD method

Screening patients for potential respiratory infections through nucleic acid sampling was a critical non-pharmacologic intervention during a respiratory infectious disease pandemic. Evaluating the cross-infection risk of crowded activities conducted indoors is necessary. We conducted a field study of this event in a large-scale stadium and measured the variation in CO2 concentrations. We conducted simulations on the stadium's flow field, CO2 and N2O concentration distribution using the CFD method, which was validated by the on-site measured data. We simulated the diffusion of virus aerosols exhaled by the sampled individuals under an all-fresh and primary return air system, respectively. It was found that space morphology and airflow pattern are the main factors influencing the concentration distribution of human exhaled contaminants. Primary return air systems can reduce the infection risk for sampled individuals by the filtration system and improve the airflow pattern. With the ratio of fresh air to return air of 1.2, the primary return air systems with 70 %, 85 %, and 95 % filtration levels can reduce the infection risk by an average of 54.5 %, 58.3 %, and 62.1 %, respectively, compared to all-fresh air system. It is necessary to optimize the processes and queue setups for nucleic acid sampling activities in the room based on the room airflow characteristics and the return air system using an efficient filtration system.

Exploring how the heterogeneous urban landscape influences CO2 concentrations: The case study of the Metropolitan Area of Barcelona

Monitoring CO2 concentrations in urban areas is crucial for determining the efficacy of climate change mitigation policies. However, highly heterogeneous land use, local geography, and local convection patterns, which vary throughout the urban landscape, complicate this task. To establish continuous monitoring programs, it is important to first determine the heterogeneity of urban landscapes on the ground. To understand the role these factors play in the distribution of CO2 over an urban area, we conducted a CO2 measurement campaign over the Metropolitan Area of Barcelona (AMB) over four urban land uses: impervious, green, forest, and agricultural. There is a clear tendency for CO2 mixing ratios to decrease as the degree of urban vegetation increases, even in the midst of a developed boundary layer. For example, CO2 concentrations were 429 and 427 ppm at forest and agricultural sites, respectively, while 485 ppm was reported at urban sites. A decrease in atmospheric CO2 was observed from 458 to 428 ppm in the gradient from urban to suburban areas, in which the biosphere component increased. The biosphere component of the CO2 signal was significant and was observed in the gradient from urban to suburban areas, which averaged a reduction from 458 to 428 ppm. Our findings show that the large spatial variability in CO2 concentrations (ranging from 410 to 495 ppm) is best explained by anthropogenic activity. We propose increasing the spatiotemporal resolution of CO2 monitoring in the AMB to determine these trends more precisely over longer periods of time.

Characterizing the Regional Differences in Carbon Dioxide Concentration Based on Satellite Observations in the Beijing-Tianjin-Hebei Region during 2015–2021

The regional differences in carbon dioxide (CO2) variations from the Orbiting Carbon Observatory-2 (OCO-2) over the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 2015 to 2021 are analyzed in this study. This study shows an annual increase and a seasonal cycle; the CO2 annual growth rate was about 2.63 ppm year−1, with the highest value being in spring and the lowest in summer. The spatial distribution is unbalanced, regional differences are prominent, and the CO2 concentration is lower in the north of the Jing-Jin-Ji region (like Zhangjiakou, Chengde, and Qinhuangdao). Land-type structures and population economy distributions are the key factors affecting CO2 concentration. By analyzing the land-type structures over Jing-Jin-Ji in 2020, we find that cropland, woodland, and grassland (CWG) are the main land cover types in Jing-Jin-Ji; the proportion of these three types is about 83.3%. The woodland areas in Zhangjiakou, Chengde, and Qinhuangdao account for about 65% of the total woodland areas in Jing-Jin-Ji; meanwhile, the grassland areas in these three regions account for 62% of the total grassland areas in Jing-Jin-Ji. CO2 concentration variation shows a high negative correlation with CWG land areas (coefficient of determination (R2) > 0.76). The regions with lower population and GDP secondary industry (SI) density also have lower CO2 concentration (like Zhangjiakou, Chengde, and Qinhuangdao), and the regions with higher population and GDP SI density also have higher CO2 concentration (like the southeast of Jing-Jin-Jin).

Carbon dioxide fluxes in Alpine grasslands at the Nivolet Plain, Gran Paradiso National Park, Italy 2017–2023

We introduce a georeferenced dataset of Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER) and meteo-climatic variables (air and soil temperature, air relative humidity, soil volumetric water content, pressure, and solar irradiance) collected at the Nivolet Plain in Gran Paradiso National Park (GPNP), western Italian Alps, from 2017 to 2023. NEE and ER are derived by measuring the temporal variation of CO2 concentration obtained by the enclosed chamber method. We used a customised portable non-steady-state dynamic flux chamber, paired with an InfraRed Gas Analyser (IRGA) and a portable weather station, measuring CO2 fluxes at a number of points (around 20 per site and per day) within five different sites during the snow-free season (June to October). Sites are located within the same hydrological basin and have different geological substrates: carbonate rocks (site CARB), gneiss (GNE), glacial deposits (GLA, EC), alluvial sediments (AL). This dataset provides relevant and often missing information on high-altitude mountain ecosystems and enables new comparisons with other similar sites, modelling developments and validation of remote sensing data.

Effects of CO2 Geosequestration on Opalinus Clay

CO2 geosequestration is an important contributor to United Nations Sustainable Development Goal 13, i.e., Climate Action, which states a global Net-Zero CO2 emissions by 2050. A potential impact of CO2 geosequestration in depleted oil and gas reservoirs is the variations in induced pressure across the caprocks, which can lead to significant local variations in CO2 saturation. A detailed understanding of the relationship between the pressure gradient across the caprock and local CO2 concentration is of utmost importance for assessing the potential of CO2 geosequestration. Achieving this through experimental techniques is extremely difficult, and thus, we employ a coupled Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) based solver to mimic sub-critical CO2 injection in Opalinus Clay under various pressure gradients across the sample. The geomechanical and multiphase flow modelling utilising Darcy Law helps evaluate local variations in CO2 concentration in Opalinus Clay. Well-validated numerical results indicate favourable sub-critical CO2 geosequestration under a positive pressure gradient across Opalinus Clay. In the absence of a positive pressure gradient, a peak CO2 concentration of 5% has been recorded, which increases substantially (above 90%) as the pressure gradient across the sample increases.

Interspecific variation in Rubisco CO2/O2 specificity along the leaf economic spectrum across 23 woody angiosperm plants in the Pacific islands.

The coordinated interspecific variation in leaf traits and leaf lifespan is known as the leaf economic spectrum (LES). The limitation of CO2 diffusion to chloroplasts within the lamina is significant in C3 photosynthesis, resulting in a shortage of CO2 for Rubisco. Although Rubisco CO2/O2 specificity (SC/O) should be adaptively adjusted in response to the interspecific variation in CO2 concentrations [CO2] associated with Rubisco, SC/O variations across species along the LES remain unknown. We investigated the coordination among leaf traits, including SC/O, CO2 conductance, leaf protein content, and leaf mass area, across 23 woody C3 species coexisting on an oceanic island through phylogenetic correlation analyses. A high SC/O indicates a high CO2 specificity of Rubisco. SC/O was negatively correlated with [CO2] at Rubisco and total CO2 conductance within lamina, while it was positively correlated with leaf protein across species, regardless of phylogenetic constraint. A simulation analysis shows that the optimal SC/O for maximizing photosynthesis depends on both [CO2] at Rubisco sites and leaf protein per unit leaf area. SC/O is a key parameter along the LES axis and is crucial for maximizing photosynthesis across species and the adaptation of woody plants.

Potential of using CO2 observations over India in a regional carbon budget estimation by improving the modelling system

Abstract. Devising effective national-level climate action plans requires a more detailed understanding of the regional distribution of sources and sinks of greenhouse gases. Due to insufficient observations and modelling capabilities, India's current carbon source–sink estimates are uncertain. This study uses a high-resolution Lagrangian transport model to examine the potential of available CO2 observations over India for inverse estimation of regional carbon fluxes. We use four different sites in India that vary in the measurement technique, frequency and spatial representation. These observations exhibit substantial seasonal (7.5 to 9.2 ppm) and intra-seasonal (2 to 12 ppm) variability. Our modelling framework, a high-resolution Weather Research and Forecasting Model combined with the Stochastic Time-Inverted Lagrangian Transport model (WRF–STILT), performs better in simulating seasonal (R2=0.50 to 0.96) and diurnal (R2=0.96) variability (for the Mohali station) of observed CO2 than the current-generation global models (CarboScope, CarbonTracker and ECMWF EGG4). The seasonal CO2 concentration variability in Mohali, associated with crop residue burning, is largely underestimated by the models. WRF–STILT captures the seasonal biospheric variability over Nainital better than the global models but underestimates the strength of the CO2 uptake by crops. The choice of emission inventory in the modelling framework alone leads to significant biases in simulations (5 to 10 ppm), endorsing the need for accounting for emission fluxes, especially for non-background sites. Our study highlights the possibility of using the CO2 observations from these Indian stations for deducing carbon flux information at regional (Nainital) and suburban to urban (Mohali, Shadnagar and Nagpur) scales with the help of a high-resolution model. On accounting for observed variability in CO2, the global carbon data assimilation system can benefit from the measurements from the Indian subcontinent.

CO2 adsorption and storage over FAU-zeolites for environmental remediation: Understanding the role of oxygen vacancy and promotor loading

The CO2 level is rising in the atmosphere and has reached well above 400 ppm. Thus, there is growing concern about increasing CO2 levels in the atmosphere as it is a greenhouse gas, constituting 20–25 % of total greenhouse gas emissions. CO2 is quite a resilient molecule and is a by-product of any combustion-driven process. The CO2 conversion is a non-spontaneous process due to its strong stability. The IEA and IPCC constantly mandate laws to monitor and regulate CO2 emissions in the atmosphere. One efficient way is to scrub off CO2 coming out of the exhaust. Several technologies have been developed around this concept, like adsorption and absorption. In this work, we have used zeolite for CO2 adsorption. Four different zeolites with a Si/Al ratio of one, which possess varied pore diameters of 3 Å, 4 Å, 5 Å and 10 Å are tested for CO2 adsorption. The zeolite with the pore diameter of 5 Å exhibited the best performance, which adsorbed 0.3 mmol/g (13.203 mg/g) of CO2. The adsorption capacity of zeolites is further enhanced by creating oxygen vacant sites and loading sodium (Na) promotor. The creation of oxygen vacancy ∼11 % for MZE600 sample raises the CO2 adsorption by 1.6 times compared to the ZE. Various concentrations of Na promotor are loaded on zeolite namely 5,10,15,20,25,35 %. About 11.97 mmol/g (527 mg/g) of CO2 adsorption was observed for 25 % loading of Na promotor on zeolite (M25NaZE). With the sequential increase in promotor loading (up to 25 %), CO2 adsorption increases. Further increase in loading reduces the CO2 adsorption, attributed to blockage of pores on sorbent and plausible agglomeration of the promotor. The M25NaZE sample is stable for a minimum of 10 regeneration cycles and exhibits linear response to variation in CO2 concentration from 2.5 % to 16 % and feed flow rate of 50–500 mL/min.

Satellite derived trends and variability of CO2 concentrations in the Middle East during 2014–2023

The Middle East has major sources of anthropogenic carbon dioxide (CO2) emissions, but a dearth of ground-based measurements precludes an investigation of its regional and temporal variability. This is achieved in this work with satellite-derived estimates from the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 missions from September 2014 to February 2023. The annual maximum and minimum column (XCO2) concentrations are generally reached in spring and autumn, respectively, with a typical seasonal cycle amplitude of 3–8 ± 0.5 ppmv in the Arabian Peninsula rising to 8–10 ± 1 ppmv in the mid-latitudes. A comparison of the seasonal-mean XCO2 values with the CO2 emissions estimated using the divergence method stresses the role played by the sources and transport of CO2 in the spatial distribution of XCO2, with anthropogenic emissions prevailing in arid and semi-arid regions that lack persistent vegetation. In the 8-year period 2015–2022, the XCO2 concentration in the United Arab Emirates (UAE) increased at a rate of about 2.50 ± 0.04 ppmv/year, with the trend empirical orthogonal function technique revealing a hotspot over northeastern UAE and southern Iran in the summer where anthropogenic emissions peak and accumulate aided by low-level wind convergence. A comparison of the satellite-derived CO2 concentration with that used to drive climate change models for different emission scenarios in the 8-year period revealed that the concentrations used in the latter is overestimated, with maximum differences exceeding 10 ppmv by 2022. This excess in the amount of CO2 can lead to an over-prediction of the projected increase in temperature in the region, an aspect that needs to be investigated further. This work stresses the need for a ground-based observational network of greenhouse gas concentrations in the Middle East to better understand its spatial and temporal variability and for the evaluation of remote sensing observations as well as climate models.

Climate Change Impact on Corrosion of Reinforced Concrete Bridges and Their Seismic Performance

As a consequence of climate change impact, a significant variation in terms of temperature, atmospheric humidity, and carbon dioxide concentration levels is happening. This condition leads to several negative effects on the safety and the life cycle of existing concrete structures, such as the increase in the rate of material degradation, due to corrosion phenomena. In fact, the presence of carbonation and corrosion phenomena significantly influence the load-bearing capacity of existing reinforced concrete (RC) structures, under both static and dynamic loads. Among the wide range of existing RC constructions, bridges stand out for their importance. Furthermore, as structures directly exposed to the weather effects, they are more susceptible to these phenomena. In this paper, the influence of corrosion on existing RC motorway viaducts’ seismic behavior, considering the impact of climate change, is investigated, by means of an efficient procedure based on the implementation of 3D simplified finite element models and the use of analytical relations to obtain the amount of reduction in the steel reinforcement area as a function of the age of the bridge and of the different corrosion scenarios analyzed. Several scenarios for the expected variations in CO2 concentrations, temperature, and relative humidity are evaluated, considering that most of the viaducts present in the Italian motorway network were built between the 1960s and the 1970s. The results obtained using the projection of climate change impacts are compared with those calculated considering the corrosion scenarios resulting from the DuraCrete research project, to understand if the evolution of climate change leads to worse scenarios than those previously assessed.

Diel variability of carbon dioxide concentrations and emissions in a largest urban lake, Central China: Insights from continuous measurements

Accurately quantifying the carbon dioxide (CO2) emissions from lakes, especially in urban areas, remains challenging due to constrained temporal resolution in field monitoring. Current lake CO2 flux estimates primarily rely on daylight measurements, yet nighttime emissions is normally overlooked. In this study, a non-dispersive infrared CO2 sensor was applied to measure dissolved CO2 concentrations over a 24-h period in a largest urban lake (Tangxun Lake) in Wuhan City, Central China, yielding extensive data on diel variability of CO2 concentrations and emissions. We showed the practicality and efficiency of the sensor for real-time continuous measurements in lakes. Our findings revealed distinct diurnal variations in CO2 concentrations (Day: 38.58 ± 23.8 μmol L−1; Night: 42.01 ± 20.2 μmol L−1) and fluxes (Day: 7.68 ± 10.34 mmol m−2 d−1; Night: 9.68 ± 9.19 mmol m−2 d−1) in the Tangxun Lake. The balance of photosynthesis and respiration is of utmost importance in modulating diurnal CO2 dynamics and can be influenced by nutrient loadings and temperature. A diel variability correction factor of 1.14 was proposed, suggesting that daytime-only measurements could underestimate CO2 emissions in urban lakes. Our data suggested that samplings between 11:00 and 12:00 could better represent the average diel CO2 fluxes. This study offered valuable insights on the diel variability of CO2 fluxes, emphasizing the importance of in situ continuous measurements to accurately quantify CO2 emissions, facilitating selections of sampling strategies and formulation of management strategies for urban lakes.

Quantitative analysis of diurnal CO2 flux variations above an alkaline playa

AbstractThe alkaline playas at Atlin, BC, provide a unique opportunity for studying the carbonate–bicarbonate system and carbonate mineral stability at the Earth's surface. In this study, dynamic closed chambers (DCCs) and pore‐gas sampling were used to directly quantify carbon dioxide (CO2) emission rates and characterize processes governing the CO2 exchange across the playa‐atmosphere interface. Data were collected at the Atlin site continuously over 27 days in 2020 and 14 days in 2021. Results indicate minimal net exchange of CO2 across the playa‐atmosphere interface during the monitoring periods, with average fluxes over the two periods of −0.03 and 0.09 µmol m−2 s−1 in 2020 and 2021, respectively. However, distinct diurnal oscillations of CO2 fluxes were measured with average daytime fluxes of 0.15 ± 0.34 µmol m−2 s−1 (2020) and 0.15 ± 0.19 µmol m−2 s−1 (2021) and nighttime fluxes of −0.24 ± 0.31 µmol m−2 s−1 (2020) and 0.04 ± 0.18 µmol m−2 s−1 (2021). These observations, supported by reactive transport modeling, indicate that CO2 exchange is predominantly governed by changes in CO2 solubility in alkaline porewater related to diurnal temperature fluctuations and variations in CO2 concentrations in ambient air above the ground surface. Even though CO2 concentrations exceed 8000 ppmv at 1‐m depth, CO2 emissions to the atmosphere were found to be minimal, likely due to high moisture contents, low connectivity, and tortuosity, limiting upward CO2 migration. These findings provide insights into CO2 flux dynamics in alkaline arid regions and show promise for the application of the DCC method for monitoring ex situ carbon mineralization at sites with enhanced mineral weathering.

A modified decay method based on a proposed uniformity index for measuring air change rates in non-uniform air mixed spaces

Building ventilation is essential during COVID-19 to reduce airborne viral transmission risks, while accurately estimating air change rates remains quite challenging. Due to the tracer gas method's assumption of uniform air mixing in a space, which is often not the case. However, the existing mixing models such as mixing factor (K) and zone distribution effectiveness (Ez) are limited to decrease the uncertainty of this assumption since their reported data are subjective, rough estimates, and inconsistent across different standards (e.g., ASHRAE and AIHA). Therefore, in this study, a novel modified decay method (MDM) is developed, where a proposed uniformity index (Ui) is integrated into the original decay method (ODM) to quantify the non-uniform air mixing and thereby improve the estimation of air change rates. We validated the proposed method in a real classroom using CO2 as a tracer gas. Wherein, the spatial variations of CO2 concentrations were measured at various locations using an automated system of a mass spectrometer with a 16-position valve. Later, the estimated air change rates using both the ODM and MDM were compared with the measured ones. It was found that the proposed Ui significantly decreased the error caused by the uniform-mixing assumption of estimated air change rates using ODM from 25.6 % to 3.4 % estimated by MDM at the outlet location. Similarly, the average concentrations of 16 distributed sensors at the breathing level also showed a decrease in error from 25.0 % to 2.5 %. This study can be applied to improve ventilation performance in buildings.

Effects of Temperature, Precipitation, and CO2 on Plant Phenology in China: A Circular Regression Approach

Leveraging circular regression, this study analyzed phenological data from China spanning the period 2003 to 2015, meticulously examining the effects of temperature, precipitation, and CO2 concentrations on the phenological patterns of woody and herbaceous plants. For woody plants, the results showed that rising temperatures and increased precipitation notably advanced early growth phases, such as budburst, leaf unfolding, and first flowering (p < 0.001). Specifically, CO2 concentrations had a pronounced impact on the leaf unfolding phase (p < 0.001). In contrast, autumnal events, particularly fruit maturity, autumn coloring, and leaf fall, were delayed by warmer temperatures and higher precipitation (p < 0.001), Of these events, only fruit maturity demonstrated sensitivity to CO2 concentration variations. In the realm of herbaceous plants, elevated temperatures and precipitation collectively hastened the budburst phase (p < 0.001), which is an effect further accentuated by high CO2 levels (p < 0.001). Moreover, rising temperatures and augmented precipitation were instrumental in advancing the flowering phase (p < 0.001). Conversely, warmer conditions slowed down the fruiting process (p < 0.001), with this delay somewhat mitigated by the effects of increased precipitation. Interestingly, while CO2 concentrations had negligible influence on the flowering and fruiting stages, they noticeably delayed seed dispersal and the initiation of senescence (p < 0.001). Overall, the prevailing trend suggests that plants, whether woody or herbaceous in nature, tend to prolong their growth season under warmer and more humid conditions. The influence of CO2 concentration, however, is contingent upon the specific phenological phase and plant type. Our findings emphasize the nuanced and stage-specific responses of plant phenology to temperature, precipitation, and CO2, highlighting the value of using circular regression in ecological studies.

Modeling of a Rotary Adsorber for Continuous Capture of Indoor Carbon Dioxide

Removing indoor CO2 as a pollutant via solid sorbents is a promising solution to maintaining acceptable indoor air quality while minimizing the energy consumption of ventilation. Compared to fixed-bed and fluidized-bed configurations, which require at least two beds to allow for continuous operation, a rotary adsorber is more compact and suitable to be integrated into the ventilation systems of buildings. In the present study, a regenerative rotary adsorber based on temperature swing adsorption was modeled to investigate continuous CO2 capture in an indoor environment. The governing equations of heat and mass transfer processes associated with the capture were established and coded in ANSYS Fluent software. The spatiotemporal variations of CO2 concentration and temperature in gas and solid phases within the rotary adsorber were obtained. The key findings are: (1) adjusting the speed mainly affects circumferential concentration and temperature distribution, but has little impact on axial concentration and temperature; (2) Increasing desorption inlet flow rate has little impact on adsorption outlet concentration, but significantly decreases desorption outlet concentration; (3) Raising desorption inlet temperature can increase both adsorption and desorption outlet average concentrations; (4) Reducing the volume proportion of the desorption sector will slightly increase adsorption outlet concentration and slightly decrease desorption outlet concentration, but barely affects average adsorption and desorption outlet temperatures.

Large methane emission during ice-melt in spring from thermokarst lakes and ponds in the interior Tibetan Plateau

The magnitudes of annual CO2 and CH4 emissions from thermokarst lakes and ponds are uncertain due to scarce measurements on the Tibetan Plateau (TP) and limited data on emissions during ice-melt. To evaluate the importance of CO2 and CH4 emissions during late winter and spring among the whole year, surface water CO2 and CH4 concentrations were measured with the headspace method in ten thermokarst lakes and ponds in 2020–2021 on the TP. The concentrations of CH4 and CO2 under ice in winter (CH4, 1.05–127.16 μmol/L, CO2, 13.24–95.57 μmol/L) were 3–4 orders of magnitude and several times higher than those in summer (CH4, 0.02–2.34 μmol/L, CO2, 7.26–49.18 μmol/L), respectively. The CH4 concentrations and fluxes during ice-melt increased with as the depth of the thermokarst lakes and ponds increased. However, the variation in CO2 concentration was not significant in depth. Snowfall events played an important role in influencing gas exchange during ice-melt. In the ten lakes researched, 42.2% and 19.2% of the annual CH4 and CO2 fluxes occurred during ice-melt, respectively. Our results indicated that CH4 and CO2 accumulation in winter should be considered when evaluating annual carbon budgets in thermokarst lakes and ponds on the TP and similarly high fluxes during ice-melt might occur in other thermokarst lakes and ponds.

Low frequency changes in CO2 concentration in East Asia related to Pacific decadal oscillation and Atlantic multi-decadal oscillation for mid-summer and early fall

The climatological seasonal maximum and minimum CO2 concentrations in East Asia for 1987–2020 have been recorded at April and August, respectively. We found that the CO2 concentration in East Asia during July, August, and September (JAS) is lower than normal before the late 1990s and after the early 2010s (Low_CO2 period), and higher than normal from the late 1990s to the early 2010s (High_CO2 period). The low-frequency variability of CO2 concentration in East Asia during JAS correlates with both Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO)-related sea surface temperatures (SSTs). We analyzed atmospheric and oceanic conditions during JAS between the two periods, finding that precipitation in East Asia decreased during JAS in High_CO2 period than that in Low_CO2 period, possibly due to PDO and AMO-related SST forcing, which decreases vegetation's photosynthetic activity. This may lead to a higher CO2 concentration than normal in East Asia in High_CO2 period through reduced uptake of CO2 from the atmosphere. This implies that terrestrial vegetation activity influenced by remote SST forcings should be monitored to better understand regional carbon cycles in East Asia.

Satellite observation of atmospheric CO2 and water storage change over Iran

Like many other Middle East countries, Iran has been suffering from severe water shortages over the last two decades, as evidenced by significant decline in surface water and groundwater levels. The observed changes in water storage can be attributed to the mutually reinforcing effects of human activities, climatic variability, and of course the climate change. The objective of this study is to analyze the dependency of atmospheric CO2 increase on the water shortage of Iran, for which we investigate the spatial relationship between water storage change and CO2 concentration using large scale satellite data. We conduct our analysis using water storage change data from GRACE satellite and atmospheric CO2 concentration from GOSAT and SCIAMACHY satellites during 2002–2015. To analyze the long-term behavior of time series we benefit from Mann-Kendal test and for the investigation of the relationship between atmospheric CO2 concentration and total water storage we use Canonical Correlation Analysis (CCA) and Regression model. Our Results show that the water storage change anomaly and CO2 concentration are negatively correlated especially in northern, western, southwest (Khuzestan province), and also southeast (Kerman, Hormozgan, Sistan, and Baluchestan provinces) of Iran. CCA results reveal that in the most of northern regions, the decrease in water storage is significantly influenced by the increase of CO2 concentration. The results further show that precipitation in the highland and peaks does not seem to be influenced by the long and short-term variation in CO2 concentration. Besides, our results show that the CO2 concentration is slightly correlated with a weak positive trend in evapotranspiration over agricultural areas. Thus, the indirect effect of CO2 on increasing evapotranspiration is observed spatially in the whole of Iran. The results of the regression model between total water storage change and carbon dioxide (R2 = 0.91)/water discharge/water consumption show that carbon dioxide has the highest effect on total water storage change at large scale. The results of this study will contribute to both water resource management and mitigation plans to achieve the goal of CO2 emission reduction.