Carbon Dioxide Variations Research Articles

The Influence of Tourism on the UAE’s Energy-Related Climate Goals: Cointegration Analysis

ABSTRACT Recently, one of the most important highlighted topics is the vulnerability and interaction of tourism and climate change. In this context, the present paper focuses on how variations in tourism development impact carbon dioxide (CO2) emissions, which are the main contributors to global warming and climate change by using the Fourier Autoregressive Distributed Lagged (FADL) approach and the impact of the number of tourists and tourism expenditures on CO2 was analyzed with two separate Bootstrap Quantile regressions in the case of the United Arab Emirates (UAE) spanning 1995–2022. The study further applied the Fourier Toda Yamamoto Causality analysis. The results indicate that both the number of tourists and their spending positively impact CO2 and these two models verify one another. The number of tourists, tourism spending, and CO2 have a one-way causal relationship.

Widespread Autonomic Physiological Coupling Across the Brain-Body Axis.

The brain is closely attuned to visceral signals from the body's internal environment, as evidenced by the numerous associations between neural, hemodynamic, and peripheral physiological signals. We show that these brain-body co-fluctuations can be captured by a single spatiotemporal pattern. Across several independent samples, as well as single-echo and multi-echo fMRI data acquisition sequences, we identify widespread co-fluctuations in the low-frequency range (0.01 - 0.1 Hz) between resting-state global fMRI signals, neural activity, and a host of autonomic signals spanning cardiovascular, pulmonary, exocrine and smooth muscle systems. The same brain-body co-fluctuations observed at rest are elicited by arousal induced by cued deep breathing and intermittent sensory stimuli, as well as spontaneous phasic EEG events during sleep. Further, we show that the spatial structure of global fMRI signals is maintained under experimental suppression of end-tidal carbon dioxide (PETCO2) variations, suggesting that respiratory-driven fluctuations in arterial CO2 accompanying arousal cannot explain the origin of these signals in the brain. These findings establish the global fMRI signal as a significant component of the arousal response governed by the autonomic nervous system.

Spatiotemporal heterogeneity of lake carbon dioxide flux leads to substantial uncertainties in regional upscaling estimates

Limited field samplings result in significant uncertainties in regional and global estimates of lake carbon dioxide (CO2) emissions. However, quantitative analysis of uncertainty in regional lake CO2 emission estimates remains unclear. In this study, we utilized satellite data to estimate carbon dioxide flux from 113 eastern China lakes, revealing substantial spatial and temporal variations in flux, averaging 18.07 ± 81.83 mg m−2 d−1. Additionally, satellite-estimated total CO2 effluxes indicated previous upscaling studies had overestimated total CO2 effluxes from these studied lakes by approximately 3–11 times, primarily due to substantial variations in lake CO2 fluxes. Insufficient sampling resolution resulted in considerable uncertainty in upscaling estimations. Temporal variations in carbon dioxide contributed greater upscaling uncertainties than spatial variations in carbon dioxide. To capture the dynamics of lake CO2, increasing the number of sampling points and events is necessary as lake size decreases and trophic state increases. Finally, we propose a prediction for the optimal sampling resolution based on lake area and trophic state, recommending an average of 5 points per lake and bi-monthly sampling as the ideal resolution for similar shallow eutrophic lakes. This approach has been validated as effective in lakes across North America and Europe. We believe that future global-scale lake carbon budget estimates would benefit from field observations conducted at more reasonable sampling points and frequency.

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).

Spatial variation of methane oxidation and carbon dioxide sequestration in landfill biogeochemical cover

ABSTRACT The study investigated the spatial variation of potential methane (CH4) oxidation and residual carbon dioxide (CO2) sequestration in biogeochemical cover (BGCC) system designed to remove CH4, CO2, and hydrogen sulfide (H2S) from landfill gas (LFG) emissions. A 50 cm x 50 cm x 100 cm tank simulated BGCC system, comprising a biochar-amended soil (BAS) layer for CH4 oxidation, a basic oxygen furnace (BOF) slag layer for CO2 and H2S sequestration, and an upper topsoil layer. Synthetic LFG was flushed through the system in five phases, with each corresponding to different compositions and flow rates. Following monitoring, the system was dismantled, and samples were extracted from different depths and locations to analyze spatial variations, focusing on moisture content (MC), organic content (OC), pH, and electrical conductivity (EC). Additionally, batch tests on selected samples from BAS and BOF slag layers were performed to assess potential CH4 oxidation and residual carbonation capacity. The aim of study was to evaluate the BGCC's effectiveness in LFG mitigation, however this study focused on assessing spatial variations in physico-chemical properties, CH4 oxidation in the BAS layer, and residual carbonation in the BOF slag layer. Findings revealed CH4 oxidation in the BAS layer varied between 22.4 and 277.9 µg CH4/g-day, with higher rates in the upper part, and significant spatial variations at 50 cm below ground surface (bgs) compared to 85 cm bgs. The BOF slag layer showed a residual carbonation capacity of 40-49.3 g CO2/kg slag, indicating non-uniform carbonation. Overall, CH4 oxidation and CO2 sequestration capacities varied spatially and with depth in the BGCC system.

Large greenhouse gases emissions from lakes in Inner Mongolia, China

Lakes are important component of the regional carbon cycle and a significant sources of greenhouse gases (GHGs) to the atmosphere. However, the regional variations in carbon dioxide (CO2) and methane (CH4) emissions, as well as the factors regulating these emissions are poorly constrained. To investigate the regional GHG emission from lakes and their potential influencing factors, we conducted field measurements in 13 lakes in Inner Mongolia from July to August 2020. We found that the studied lakes were predominantly sources of atmosphere CO2 and CH4. The CO2 partial pressure (pCO2) exhibited supersaturation in 80 % of samplings, but all samplings of CH4 partial pressure (pCH4) showed supersaturation. Moreover, the average pCH4 is 40 times greater than that in the atmosphere. The lakes emitted substantial amounts CO2 and CH4 with average values of 25.8 ± 4.9 mmol m−2 d−1 and 2.1 ± 0.3 mmol m−2 d−1, respectively. At the regional scale, the dynamics of pCO2 and pCH4 are regulated by combination of various environmental factors. CO2 emissions from studied lakes decreased with the catchment net primary productivity (NPP), normalized difference vegetation index (NDVI), and nighttime lights which is indicative of urbanization. Conversely, CH4 fluxes increased with NPP, NDVI, and nighttime lights. We conclude that terrestrial carbon-cycling related variables and human activities significantly affect CO2 and CH4 emissions from lakes by transporting different nutrients, but they show opposite trends. Our results also exhibited that the freshwater lakes are the main contributors of CH4, while saline lakes are the main contributors of CO2. We suggest that increased human activity leads to changes in terrestrial carbon-cycle related processes which affects lake carbon emissions by altering the amount of nutrients input to the lakes.

A Comparison of Greenhouse Gas Emission Patterns in Different Water Levels in Peatlands

Peatlands store large amounts of carbon in wetland ecosystems. The hydrological conditions within peatlands are important factors that affect the biochemical cycle and patterns of greenhouse gas emissions in these peatlands. This study was carried out in Changbai Mountain Jinchuan peatland to investigate variations in carbon dioxide and methane emissions in peat swamps that have undergone distinct saturation conditions. Three peatland types (high water levels (S1); medium water levels (S2); low water levels (S3)) at different flood depths were selected as specific sampling points. The static box and gas chromatography methods were used at different time periods (6:00; 12:00; and 18:00) from July to September. The discharge flux of CO2 and CH4 slowly increased with the increase in the water level. The results indicate similarity in the fluctuation trends between the fluxes of CO2 and CH4 in S1 and S2 to the fluctuations of water levels. During the entire growth season, the flux range of CO2 and CH4 was −695.329~859.907 mg m2h−1 and 259.981~147.155 mg m2h−1, respectively. Furthermore, there was variation in mutation characteristics between two gases, the CO2 exhibited larger mutation range (−7.08~3.40) than CH4 (−1.79~1.26). In terms of daily flux changes, CO2 showed an upward trend, while CH4 had a downward trend. These results indicate variations in saturation conditions tend to affect discharge of greenhouse gases, with subsequent effects on climate change. This study highlights potential theoretical support to reduce anthropogenic activities on peatlands. This can be achieved by undertaking measures to conserve peatlands and explore mitigation measures to minimize greenhouse gas emissions and hence impacts of climate change.

Winter Carbon Dioxide Measurement in Honeybee Hives

Sensor technologies have sufficiently advanced to provide low-cost devices that can quantify carbon dioxide levels in honeybee hives with high temporal resolution and in a small enough package for hive deployment. Recent publications have shown that summer carbon dioxide levels vary throughout the day and night over ranges that typically exceed 5000 ppm. Such dramatic changes in a measurable parameter associated with bee physiology are likely to convey information about the colony health. In this work, we present data from four UK-based hives collected through the winter of 2022/2023, with a focus on seeing if carbon dioxide can indicate when colonies are at risk of failure. These hives have been fitted with two Sensirion SCD41 photoacoustic non-dispersive infrared (NDIR) carbon dioxide sensors, one in the queen excluder, at the top of the brood box, and one in the crown board, at the top of the hive. Hive scales have been used to monitor the hive mass, and internal and external temperature sensors have been included. Embedded accelerometers in the central frame of the brood box have been used to measure vibrations. Data showed that the high daily variation in carbon dioxide continued throughout the coldest days of winter, and the vibrational data suggested that daily fanning may be responsible for restoring lower carbon dioxide levels. The process of fanning will draw in colder air to the hive at a time when the bees should be using their energy to maintain the colony temperature. Monitoring carbon dioxide may provide feedback, prompting human intervention when the colony is close to collapse, and a better understanding may contribute to discussions on future hive design.

Breath-hold BOLD fMRI without CO2 sampling enables estimation of venous cerebral blood volume: potential use in normalization of stimulus-evoked BOLD fMRI data

BOLD fMRI signal has been used in conjunction with vasodilatory stimulation as a marker of cerebrovascular reactivity (CVR): the relative change in cerebral blood flow (CBF) arising from a unit change in the vasodilatory stimulus. Using numerical simulations, we demonstrate that the variability in the relative BOLD signal change induced by vasodilation is strongly influenced by the variability in deoxyhemoglobin-containing cerebral blood volume (CBV), as this source of variability is likely to be more prominent than that of CVR. It may, therefore, be more appropriate to describe the relative BOLD signal change induced by an isometabolic vasodilation as a proxy of deoxygenated CBV (CBVdHb) rather than CVR. With this in mind, a new method was implemented to map a marker of CBVdHb, termed BOLD-CBV, based on the normalization of voxel-wise BOLD signal variation by an estimate of the intravascular venous BOLD signal from voxels filled with venous blood. The intravascular venous BOLD signal variation, recorded during repeated breath-holding, was extracted from the superior sagittal sinus in a cohort of 27 healthy volunteers and used as a regressor across the whole brain, yielding maps of BOLD-CBV. In the same cohort, we demonstrated the potential use of BOLD-CBV for the normalization of stimulus-evoked BOLD fMRI by comparing group-level BOLD fMRI responses to a visuomotor learning task with and without the inclusion of voxel-wise vascular covariates of BOLD-CBV and the BOLD signal change per mmHg variation in end-tidal carbon dioxide (BOLD-CVR). The empirical measure of BOLD-CBV accounted for more between-subject variability in the motor task-induced BOLD responses than BOLD-CVR estimated from end-tidal carbon dioxide recordings. The new method can potentially increase the power of group fMRI studies by including a measure of vascular characteristics and has the strong practical advantage of not requiring experimental measurement of end-tidal carbon dioxide, unlike traditional methods to estimate BOLD-CVR. It also more closely represents a specific physiological characteristic of brain vasculature than BOLD-CVR, namely blood volume.

Modeling China's terrestrial ecosystem gross primary productivity with BEPS model: Parameter sensitivity analysis and model calibration

Terrestrial ecosystems are the largest sink for carbon, and their ecosystem gross primary productivity (GPP) regulates variations in atmospheric carbon dioxide (CO2) concentrations. Current process-based ecosystem models used for estimating GPP are subject to large uncertainties due to poorly constrained parameter values. In this study, we implemented a global sensitivity analysis (GSA) on parameters in the Boreal Ecosystem Productivity Simulator (BEPS) considering the parameters’ second-order impacts. We also applied the generalized likelihood estimation (GLUE) method, which is flexible for a multi-parameter calibration, to optimize the GPP simulation by BEPS for 10 sites covering 7 plant functional types (PFT) over China. Our optimized results significantly reduced the uncertainty of the simulated GPP over all the sites by 17 % to 82 % and showed that the GPP is sensitive to not only the photosynthesis-related parameters but also the parameters related to the soil water uptake as well as to the energy balance. The optimized GPP across South China showed that the mix forest, shrub, and grass have a higher GPP and are more controlled by the soil water availability. This study showed that the GLUE method together with the GSA scheme could constrain the ecosystem model well when simulating GPP across multiple ecosystems and provide a reasonable estimate of the spatial and temporal distribution of the ecosystem GPP over China. We call for more observations from more sites, as well as data on plant traits, to be collected in China in order to better constrain ecosystem carbon cycle modeling and understand its response to climate change.

CO2, CH4, and N2O emissions from dredged material exposed to drying and zeolite addition under field and laboratory conditions

Dredging, the removal of sediment from water courses, is generally conducted to maintain their navigability and to improve water quality. Recent studies indicate that dredging can significantly reduce aquatic greenhouse gas (GHG) emissions. These studies, however, do not consider the potential emission from the dredged material (sludge) in the depot. In addition, it is unknown if and how GHG emissions from sludge depots can be reduced. Here we present spatiotemporal variations of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes, as well as environmental variables from a sludge depot located in the Netherlands. Measurements were conducted monthly from the time the depot was filled until the sludge was dry and the depot was abolished. We also experimentally assessed the GHG mitigation potential of 1) keeping the sludge permanently inundated, and 2) the addition of different amounts of zeolite to increase sludge nitrogen binding capacity to reduce N2O emissions. In the depot and in the laboratory, a decrease in moisture content coincided with increased CO2 and N2O emissions while CH4 emissions decreased. We observed that permanent inundation reduced emissions (∼4 times less CO2-eq than in drying sludge). Adding zeolite lowered N2O fluxes from permanently inundated sludge but did not reduce total GHG emissions. During the depot's operational period, average CO2, CH4, and N2O fluxes were 5078, 27, and 5 mg m−2 d−1, respectively. GHG emissions from drying sludge occurred mainly in the form of CO2 (73% of the total CO2-eq emissions), with average GHG emission rates comparable to those reported for ditches and ponds. We estimate that approximately 14 tons of CO2-eq were emitted from the 0.011 km2 depot, which contained ∼20,000 m3 of sludge, during its entire operational period, and we argue that more studies are needed, considering different sludge origins, to expand our understanding of sludge depots.

Climate shifts orchestrated hominin interbreeding events across Eurasia.

When, where, and how often hominin interbreeding happened is largely unknown. We study the potential for Neanderthal-Denisovan admixture using species distribution models that integrate extensive fossil, archaeological, and genetic data with transient coupled general circulation model simulations of global climate and biomes. Our Pleistocene hindcast of past hominins' habitat suitability reveals pronounced climate-driven zonal shifts in the main overlap region of Denisovans and Neanderthals in central Eurasia. These shifts, which influenced the timing and intensity of potential interbreeding events, can be attributed to the response of climate and vegetation to past variations in atmospheric carbon dioxide and Northern Hemisphere ice-sheet volume. Therefore, glacial-interglacial climate swings likely played an important role in favoring gene flow between archaic humans.

Dual titration of minute ventilation and sweep gas flow to control carbon dioxide variations in patients on venovenous extracorporeal membrane oxygenation

BackgroundThe implantation of venovenous extracorporeal membrane oxygenation (VV-ECMO) support to manage severe acute respiratory distress syndrome generates large variations in carbon dioxide partial pressure (PaCO2) that are associated with intracranial bleeding. We assessed the feasibility and efficacy of a pragmatic protocol for progressive dual titration of sweep gas flow and minute ventilation after VV-ECMO implantation in order to limit significant PaCO2 variations.Patients and methodsA protocol for dual titration of sweep gas flow and minute ventilation following VV-ECMO implantation was implemented in our unit in September 2020. In this single-centre retrospective before-after study, we included patients who required VV-ECMO from March, 2020 to May, 2021, which corresponds to two time periods: from March to August, 2020 (control group) and from September, 2020 to May, 2021 (protocol group). The primary endpoint was the mean absolute change in PaCO2 in consecutive arterial blood gases samples drawn over the first 12 h following VV-ECMO implantation. Secondary endpoints included large (> 25 mmHg) initial variations in PaCO2, intracranial bleedings and mortality in both groups.ResultsFifty-one patients required VV-ECMO in our unit during the study period, including 24 in the control group and 27 in the protocol group. The protocol was proved feasible. The 12-h mean absolute change in PaCO2 was significantly lower in patients of the protocol group as compared with their counterparts (7 mmHg [6–12] vs. 12 mmHg [6–24], p = 0.007). Patients of the protocol group experienced less large initial variations in PaCO2 immediately after ECMO implantation (7% vs. 29%, p = 0.04) and less intracranial bleeding (4% vs. 25%, p = 0.04). Mortality was similar in both groups (35% vs. 46%, p = 0.42).ConclusionImplementation of our protocol for dual titration of minute ventilation and sweep gas flow was feasible and associated with less initial PaCO2 variation than usual care. It was also associated with less intracranial bleeding.

Large Degree of Variation in Sorption Properties within a System of Isoreticular, Mixed-Ligand Ni- and Co-Based 2-Periodic Metal–Organic Frameworks

Two Ni-based and two Co-based mixed-ligand metal–organic frameworks (MOFs), which are all isoreticular with each other, are shown to have a large variation in nitrogen, carbon dioxide, hydrogen, and water vapor sorption properties, despite their similar structures. The MOFs have 1,2-bis(4-pyridyl)ethane (bpe) as the common ligand with the second ligand being either 2-nitroterephthalate (2-nta) or 2-bromoterephthalate (2-bta) for the Ni-based MOFs or 2-nta or 2-aminoterephthalate (2-ata) for the Co-based MOFs. The four MOFs have the formula [Ni(2-nta)(bpe)(H2O)2]n·2(DMA)n (1), [Ni(2-bta)(bpe)(H2O)2]n·2.8(DMF)n (2), [Co(2-nta)(bpe)(H2O)2]n·2(DMA)n (3), and [Co(2-ata)(bpe)(H2O)2]n·3(DMA)n·(H2O)n (4), respectively, where DMA = N,N′-dimethylacetamide and DMF = N,N′-dimethylformamide. Variable-temperature powder X-ray diffraction (VT-PXRD) studies indicate that the activated MOF structures are different from those of the as-synthesized MOFs, showing that the 2-periodic layers are dynamic upon desolvation. For the same metal ion, the MOF involving the 2-nta ligand has higher sorption, while sorption for the Ni-based MOFs is higher than for the Co-based MOFs. MOF 1 has the highest sorption within the isoreticular series and also has the highest sorption (the highest for water vapor) compared to other MOFs with the same or related ligands.

Variations in CO2 and CH4 Exchange in Response to Multiple Biophysical Factors from a Mangrove Wetland Park in Southeastern China

Mangrove ecosystems can be both significant sources and sinks of greenhouse gases. The restoration of mangrove forests is increasingly used as a natural climate solution tool to mitigate climate change. However, the estimates of carbon exchanges remain unclear, especially from restored mangroves. In this study, we observed the temporal variations in carbon dioxide (CO2) and methane (CH4) fluxes and their biophysical controls for 4 years, based on a closed-path eddy covariance (EC) system. The measurements were conducted in a mangrove wetland park with 14-year-old restored mangroves surrounded by open waters in Guangdong Province, China. The EC measurements showed that the mangrove ecosystem acted as a CO2 source with a net CO2 ecosystem exchange (NEE) of 305 g C m−2 from January 2019 to May 2020 by the 5-m tower measurement. After the tower was adjusted to 10 m, the mangrove showed a CO2 sink with an NEE of −345 g C m−2 from June 2020 to December 2022. The change in tower height influenced the interpretation of interannual trends on NEE. There were no significant interannual trends in the gross primary productivity (GPP) and the ecosystem respiration (Re) values. The change from CO2 source to sink may be attributed to the decrease in land surface proportion by the tower replacement, which reduces the proportion of the mangrove canopy respiration and, therefore, captures lower CO2 fluxes from open waters. The restored mangroves indicated strong CH4 sources of 23.2–26.3 g C m−2 a−1. According to the random forest analysis, the land surface proportion, radiation, and relative humidity were the three most important predictors of NEE, while the CH4 flux was most sensitive to air temperature. Compared to the natural and long-term restored mangroves, this 14-year-old restored mangrove had not yet achieved a maximum carbon sequestration capability. Our study highlights the need for the careful design of long-term observations from restored mangroves and proposes future needs in the context of carbon neutrality.

CO2 flux from Acer saccharum logs: sources of variation and the influence of silvicultural treatments

Several aspects of the forest carbon cycle have not been examined in detail, including sources of variation in carbon dioxide (CO2) emissions from coarse woody material (CWM). To address this knowledge gap, we examined CO2 emissions from Acer saccharum Marshall logs within four harvesting treatments, using closed chambers fitted to the logs. We found that CO2 emissions were highest for logs in small (31.8 ± 20.4 µmol·CO2·m−3·s−1) and large gaps (29.6 ± 24.4 µmol·CO2·m−3·s−1) compared to those in control (13.9 ± 8.3 µmol·CO2·m−3·s−1) and thinned matrix (13.6 ± 8.0 µmol·CO2·m−3·s−1) treatments. CO2 flux rates did not differ between gap sizes, but they increased with temperature, which was higher in the small gap treatment. In addition, two individual logs fitted with multiple closed chambers revealed significant within-log variability in CO2 emissions. On a subset of logs repeatedly sampled throughout the day, we found that log surface temperature generally peaked at midday and was positively correlated with CO2 emissions, although this relationship was weak in one log. This study provides insight into sources of variation in CO2 emissions from CWM while improving our understanding of the forest carbon cycle.

Atmospheric Variations in Summertime Column Integrated CO2 on Synoptic Scales Over the U.S.

AbstractPast studies have demonstrated that synoptically active weather systems play an important role in the spatial and temporal variations of atmospheric carbon dioxide (CO2) within and above the planetary boundary layer. For the first time, we investigate the spatial variability of column‐averaged dry‐air mole fractions of () due to the impact of synoptic scale transport using retrievals from the Orbiting Carbon Observatory‐2 (OCO‐2) for 66 summer cold front passage cases over the conterminous U.S. and Mexico from 2015 to 2019. differences across cold fronts in summer were found to be in good agreement with observations obtained from the Atmospheric Carbon and Transport (ACT‐America) field campaign, though with a reduced magnitude due the flat averaging kernel representing fairly uniform vertical sensitivity in the troposphere as opposed to in situ measurements. OCO‐2 observed frontal differences are statistically distinct from north‐south climatological spatial variations on similar spatial‐scales on synoptically benign days, implying that the frontal passages contribute to enhanced spatial contrasts. An exploratory analysis finds no evidence of a linkage between the temperature differences and differences, but a more thorough exploration is left as future work.

Temporal Dynamics of CO2 Fluxes Measured with Eddy Covariance System in Maize, Winter Oilseed Rape and Winter Wheat Fields

The full understanding of variation and temporal changes in carbon dioxide (CO2) fluxes in cropland may contribute to a reduction in CO2 emissions from agriculture. The aim of this study was to determine the CO2 exchange intensity in the three most popular crops in Poland. The CO2 fluxes in summer maize, winter oilseed rape and winter wheat fields were measured using the eddy covariance system. The seasonal dynamics of CO2 fluxes for all studied crops varied from each other due to individual dynamics in atmospheric CO2 assimilation of each species through the growing season. The weighted average values of CO2 fluxes calculated for the entire vegetation period were −22.22 µmol CO2 m−2 s−1, −14.27 µmol CO2 m−2 s−1 and −11.95 µmol CO2 m−2 s−1 for maize, oilseed rape and wheat, respectively. All the studied agro-ecosystems were carbon sinks during the growing season. The highest negative values of CO2 fluxes (−36.31 µmol CO2 m−2 s−1 and −33.56 µmol CO2 m−2 s−1) were observed in the maize field due to the high production of biomass. However, the maize field was also the most significant carbon source due to slow growth of plants at the beginning of the growing season, and due to leaving the field fallow after harvest until the next sowing. In these two periods, the CO2 fluxes ranged from 0.59 µmol CO2 m−2 s−1 to 3.72 µmol CO2 m−2 s−1. CO2 exchange over wheat and oilseed rape fields was less intense, but more even throughout the growing season. In the wheat field, the CO2 fluxes ranged from −1.70 µmol CO2 m−2 s−1 to −23.49 µmol CO2 m−2 s−1 and in the oilseed rape field they ranged from −1.40 µmol CO2 m−2 s−1 to −22.08 µmol CO2 m−2 s−1. In addition, the catch crop in the oilseed rape field contributed to the intensive absorption of CO2 after harvesting the main crop.

The Effect of Sectorial Contributions to GDP on Environmental Degradation: A Verification of the Environmental Kuznets Curve Hypothesis in Nigeria

This paper empirically verifies the validity of the Environmental Kuznets Curve (EKC) hypothesis in Nigeria by focusing on the relationship between key sectors of the Nigerian economy and environmental degradation. The study adopted the Autoregressive Distributed Lag (ARDL) model using time series data for the period 1981-2018. The bounds-testing approach proposed by Pesaran, Shin and Smith, (2001) was adopted to test for cointegration. The results show a long-run relationship between economic growth (disaggregated into key sectors) and environmental degradation measured by carbon dioxide emissions. In the short run, agriculture, industry and services sectors significantly explained the variation in carbon dioxide (CO2) emissions, while the construction sector does not have any significant effect on Carbon emissions both in the current and the future periods. Specifically, the industrial sector has a positive effect on CO2 emissions which confirms the short-run EKC hypothesis; while agriculture and services though were significant, have a negative effect on CO2 emissions, invalidating the short-run EKC hypothesis. In the long run, industry and services sectors were significant in explaining variation in CO2 emission. However, while the services sector shows a negative relationship with CO2 emission in line with the long-run EKC Hypothesis, the industrial sector invalidates the hypothesis with a positive effect. These results imply that the key sectors of the economy have varied effects on environmental degradation, hence the hypothesis is inconclusive. Nigeria is therefore advised to pursue economic growth via industrial and services sectors with an emphasis on environmental sustainability, which could be achieved through the use of renewable and cleaner technology in nation-building.

Abrupt permafrost thaw accelerates carbon dioxide and methane release at a tussock tundra site

ABSTRACT Abrupt thaw could cause permafrost ecosystems to release more carbon than is predicted from gradual thaw alone. However, thermokarst feature mapping is limited in scope, and observed responses of carbon fluxes to abrupt thaw are variable. We developed a thermokarst detection algorithm that identifies thermokarst features from a single elevation dataset with 71.5 percent accuracy and applied it in Healy, Alaska. Additionally, we investigated the landscape-level variation in carbon dioxide and methane fluxes by extent of abrupt thaw using eddy covariance. Seven percent of the site was classified as thermokarst. Water tracks were the most extensive form of thermokarst, although small pits were much more numerous. Abrupt thaw was positively correlated with carbon uptake during the growing season, when increases in gross primary productivity outpaced increases in ecosystem respiration in vegetation-dense water tracks. However, this was outweighed by higher carbon release in thermokarst features during the nongrowing season. Additionally, abrupt thaw was positively correlated with methane production nearly year-round. Our findings support the hypothesis that abrupt thaw of permafrost carbon will contribute to the permafrost climate feedback above and beyond that associated with gradual thaw and highlights the need to map thermokarst and incorporate abrupt thaw into Earth System Models.