CO2 Trends Research Articles

Indoor air quality assessment of an existing apartment located in Indian tropical city, Bhubaneswar

Introduction: A proper investigation on indoor pollution level in economical apartments is important, where the provision for ventilation is limited. A series of experiments were conducted in the houses within an existing economical apartment in Bhubaneswar, India to evaluate various pollutant levels. Materials and methods: Temperature, relative humidity, CO, CO2, Particulate Matter (PM10 and PM2.5), Formaldehyde and Total volatile organic compounds in the bedrooms and kitchens are measured by pollution meters. The experiments were conducted with doors and windows closed conditions. The readings were taken on a four consecutive working day in February 2023 at an interval of 3 h (9:00 am to 9:00 pm). Results: The day wise temperature and humidity variations inside the bedroom and kitchen shows a reverse trend. At the afternoon, the indoor temperature becomes high, while during the night time humidity becomes the highest. The day wise indoor CO2 and CO variation trend is pretty similar. Both CO2 and CO concentrations in bedrooms are the highest in the evening. In contrast to that CO2 and CO concentrations in kitchens becomes maximum during noon time. High particulate matter concentration at outdoor and indoor is observed at the evening time. Higher formaldehyde (HCHO) and Total Volatile Organic Compounds (TVOCs) concentration at the indoor is observed at noon and afternoon time. Conclusion: The results obtained were compared with the recommended values of World Health Organization (WHO) and National Ambient Air Quality Standards (NAQIS). The results revealed that all measured parameters are at a higher level than the recommended values except the indoor CO2 concentrations.

Anthropic-Induced Variability of Greenhouse Gasses and Aerosols at the WMO/GAW Coastal Site of Lamezia Terme (Calabria, Southern Italy): Towards a New Method to Assess the Weekly Distribution of Gathered Data

The key to a sustainable future is the reduction in humankind’s impact on natural systems via the development of new technologies and the improvement in source apportionment. Although days, years and seasons are arbitrarily set, their mechanisms are based on natural cycles driven by Earth’s orbital periods. This is not the case for weeks, which are a pure anthropic category and are known from the literature to influence emission cycles and atmospheric chemistry. For the first time since it started data gathering operations, CO (carbon monoxide), CO2 (carbon dioxide), CH4 (methane) and eBC (equivalent black carbon) values detected by the Lamezia Terme WMO/GAW station in Calabria, Southern Italy, have been evaluated via a two-pronged approach accounting for weekly variations in absolute concentrations, as well as the number of hourly averages exceeding select thresholds. The analyses were performed on seven continuous years of measurements from 2016 to 2022. The results demonstrate that the analyzed GHGs (greenhouse gasses) and aerosols respond differently to weekly cycles throughout the seasons, and these findings provide completely new insights into source apportionment characterization. Moreover, the results have been combined into a new parameter: the hereby defined WDWO (Weighed Distribution of Weekly Outbreaks) normalizes weekly trends in CO, CO2, CH4 and eBC on an absolute scale, with the scope of providing regulators and researchers alike with a new tool meant to better evaluate anthropogenic pollution and mitigate its effects on the environment and human health.

Tree stem-atmosphere greenhouse gas fluxes in a boreal riparian forest

Tree stems exchange greenhouse gases with the atmosphere but the magnitude, variability and drivers of these fluxes remain poorly understood. Here, we report stem fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in a boreal riparian forest, and investigate their spatiotemporal variability and ecosystem level importance. For two years, we measured CO2 and CH4 fluxes on a monthly basis in 14 spruces (Picea abies) and 14 birches (Betula pendula) growing near a headwater stream affected by historic ditching. We also measured N2O fluxes on three occasions. All tree stems were net emitters of CO2 and CH4, while N2O fluxes were around zero. CO2 fluxes correlated strongly with air temperature and peaked in summer. CH4 fluxes correlated modestly with air temperature and solar radiation and peaked in late winter and summer. Trees with larger stem diameter emitted more CO2 and less CH4 and trees closer to the stream emitted more CO2 and CH4. The CO2 and CH4 fluxes did not differ between spruce and birch, but correlations of CO2 fluxes with stem diameter and distance to stream differed between the tree species. The absence of vertical trends in CO2 and CH4 fluxes along the stems and their low correlation with groundwater levels and soil CO2 and CH4 partial pressures suggest tree internal production as the primary source of stem emissions. At the ecosystem level, the stem CO2, CH4 and N2O emissions represented 52 ± 16 % of the forest floor CO2 emissions and 3 ± 1 % and 11 ± 40 % of the forest floor CH4 and N2O uptake, respectively, during the snow-free period (median ± SE). The six month snow-cover period contributed 11 ± 45 % and 40 ± 29 % to annual stem CO2 and CH4 emissions, respectively. Overall, the stem gas fluxes were more typical for upland rather than wetland ecosystems likely due to historic ditching and subsequent groundwater level decrease.

Mapping high-resolution XCO2 concentrations in China from 2015 to 2020 based on spatiotemporal ensemble learning model

High-resolution column-averaged dry air mole fraction of CO2 (XCO2) data is crucial for understanding the spatiotemporal patterns of XCO2 and for mitigating carbon emissions. Due to the limited scanning range of sensors and strict inversion conditions, satellite-retrieved XCO2 data are often significantly incomplete. Machine learning models are widely used to fill these gaps in satellite XCO2 data. However, the limitations of individual machine learning models and the complexity of the spatial distribution of XCO₂ mean that the accuracy of XCO2 predictions still needs improvement. In this study, a new spatiotemporal stacked ensemble learning model (STEL) was developed by combining random forest (RF), extremely randomized trees (ERT), extreme gradient boosting (XGBoost), optical gradient boosting (LightGBM), and categorical boosting (CatBoost) using the stacking ensemble learning methodology. Considering the spatiotemporal heterogeneity of XCO2, a novel spatiotemporal weighting feature was constructed as part of the model's input parameters. Finally, the XCO2 observed by Orbiting Carbon Observatory 2 (OCO-2) was reconstructed using STEL, and a monthly mean XCO2 dataset covering China from 2015 to 2020 was generated at a spatial resolution of 0.1°. The results show that STEL exhibits superior performance and generalization capabilities compared to individual machine-learning models. R2 RMSE and MAPE were 0.9624, 1.0023 ppm, and 0.1583 % on the test set, and 0.8970, 1.4213 ppm, and 0.2475 % for R2, RMSE, and MAPE in ground validation, respectively. In 10-fold cross-validation, STEL's RMSE was reduced by 9.52 % compared to the best-performing single model (RF). The spatiotemporal trend of CO2 in China from 2015 to 2020 was analyzed using STEL XCO2 data. The results indicate that this dataset accurately reflects the spatiotemporal heterogeneity of XCO2 distribution at a fine scale. Overall, XCO2 exhibited a spatiotemporal pattern of “high in the east and low in the west” and “high in spring and low in summer.” Except in summer, high XCO₂ values were mainly distributed in the North China Plain. XCO2 trends and hotspots showed considerable spatial variation. The Pearl River Delta and Yangtze River Delta urban agglomerations have the fastest XCO2 growth rates, and the distribution of XCO2 hotspots is consistent with the distribution of population and economic centers. In the sparsely populated northwest of China, XCO2 is growing rapidly due to increased thermal power generation and coal mining. XCO2 hotspots in Northwest China are mainly located in Xinjiang, Ningxia, and Inner Mongolia. The methodology and data presented are useful for further research on carbon emissions, carbon sinks, and climate change.

Long- and short-term coupling of sea surface temperature and atmospheric CO2 during the late Paleocene and early Eocene

The late Paleocene and early Eocene (LPEE) are characterized by long-term (million years, Myr) global warming and by transient, abrupt (kiloyears, kyr) warming events, termed hyperthermals. Although both have been attributed to greenhouse (CO2) forcing, the longer-term trend in climate was likely influenced by additional forcing factors (i.e., tectonics) and the extent to which warming was driven by atmospheric CO2 remains unclear. Here, we use a suite of new and existing observations from planktic foraminifera collected at Pacific Ocean Drilling Program Sites 1209 and 1210 and inversion of a multiproxy Bayesian hierarchical model to quantify sea surface temperature (SST) and atmospheric CO2 over a 6-Myr interval. Our reconstructions span the initiation of long-term LPEE warming (~58 Ma), and the two largest Paleogene hyperthermals, the Paleocene-Eocene Thermal Maximum (PETM, ~56 Ma) and Eocene Thermal Maximum 2 (ETM-2, ~54 Ma). Our results show strong coupling between CO2 and temperature over the long- (LPEE) and short-term (PETM and ETM-2) but differing Pacific climate sensitivities over the two timescales. Combined CO2 and carbon isotope trends imply the carbon source driving CO2 increase was likely methanogenic, organic, or mixed for the PETM and organic for ETM-2, whereas a source with higher δ13C values (e.g., volcanic degassing) is associated with the long-term LPEE. Reconstructed emissions for the PETM (5,800 Gt C) and ETM-2 (3,800 Gt C) are comparable in mass to future emission scenarios, reinforcing the value of these events as analogs of anthropogenic change.

Trends in carbon emissions and renewable energy usage

The purpose of carrying out this study was to explore the trends and inter-linkages between CO2 emission and RE share of total energy between 1990 and 2015. The United Nations’ Sustainable Development Goal 7 is to ensure access to affordable, reliable, sustainable, and modern energy for all. With these targets in mind, we have tried to answer questions like how has the global RE share of total energy changed over time, does the pattern of RE change over time affect CO2 emissions, and has access to clean energy changed significantly over time? The findings of this study has established that there is a general increasing trend in RE and that is associated with diminished trend in CO2. Looking at the access to clean energy between rural and urban sectors and they presented starkly different time trend with almost twice as large a percentage of population with access to clean energy in the urban areas than the rural. Journal of Statistical Research 2024, Vol. 58, No. 1, pp. 221-242.

Unveiling the fate of metal leaching in bimetal-catalyzed Fenton-like systems: pivotal role of aqueous matrices and machine learning prediction

Metal-based catalytic materials exhibit exceptional properties in degrading emerging pollutants within Fenton-like systems. However, the potential risk of metal leaching has become pressing environmental concern. This study addressed scientific issues pertaining to the leaching behavior and control strategies for metal-based catalytic materials. Innovative cobalt-aluminum hydrotalcite (CoAl-LDH) triggered peroxymonosulfate (PMS) activation system was constructed and achieved near-complete removal of Ciprofloxacin (CIP) across diverse water quality environments. Notably, it was found that the tunable ion exchange and Al3+ stabilization of CoAl-LDH occurred due to the particularity of neutral water quality, resulting in significantly lower Co2+ leaching levels (0.321 mg/L) compared to acidic conditions (5.103 mg/L). In light of this, machine learning technology was then employed for the first time to simulate the dynamic trend of Co2+ leaching and elucidated the critical regulatory roles and mechanisms of Al3+, aqueous matrix, and reaction rate. Furthermore, degradation systems based on different water quality and metal leaching levels regulated the generation levels of SO4.- and O2∙-, and the unique advantages of free radical attack paths were clarified through CIP degradation products and ecotoxicity analysis. These findings introduced novel insights and approaches for engineering application and pollution control in metal-based Fenton-like water treatment.

Modeling CO2 Adsorption in a Thin Discrete Packing.

Local dynamics of CO2 adsorption in a discrete packing contained in a thin tube was assessed by 3D modeling. Thin tube packed bed adsorbers are currently used over tube structures in thermochemical energy storage systems and atmospheric revitalization of confined spaces. Driven by the interplay between key factors such as the exothermicity and the fluid flow, the advective transport was found less effective than the diffusive one on the breakthrough trends of CO2 which displayed significant concentration gradients at both inter- and intraparticle scales. The lack of angular symmetry inside the particles by the reduction in resistance to mass transfer in the area of solid particles exposed to high velocities led to greater convective transports from the bulk of the gaseous phase to the pores. The result of the modeling agreed with the experimental data obtained at the exit of the adsorber, helping reduction in reliance on the empirical dispersion models used in the one-dimensional modeling.

Seasonal variability of coastal pH and CO2 using an oceanographic buoy in the Canary Islands

Ocean acidification, caused by the absorption of carbon dioxide (CO2) from the atmosphere into the ocean, ranks among the most critical consequences of climate change for marine ecosystems. Most studies have examined pH and CO2 trends in the open ocean through oceanic time-series research. The analysis in coastal waters, particularly in island environments, remains relatively underexplored. This gap in our understanding is particularly important given the profound implications of these changes for coastal ecosystems and the blue economy. The present study focuses on the ongoing monitoring effort that started in March 2020 along the east coast of Gran Canaria, within the Gando Bay, by the CanOA-1 buoy. This monitoring initiative focuses on the systematic collection of multiple variables within the CO2 system, such as CO2 fugacity (fCO2), pH (in total scale, pHT), total inorganic carbon (CT), and other hydrographic variables including sea surface salinity (SSS), sea surface temperature (SST) and wind intensity and direction. Accordingly, the study allows the computation of the CO2 flux (FCO2) between the surface waters and the atmosphere. During the study period, stational (warm and cold periods) behavior was found for all the variables. The lowest SST values were recorded in March, with a range of 18.8-19.3°C, while the highest SST were observed in September and October, ranging from 24.5-24.8°C. SST exhibited an annual increase with a rate of 0.007°C yr-1. Warmer months increased SSS, while colder periods, influenced by extreme events like tropical storms, led to lower salinity (SSS=34.02). The predominant Trade Winds facilitated the arrival of deeper water, replenishing seawater. The study provided insights into atmospheric CO2. Atmospheric fCO2 averaged 415 ± 4 µatm (2020-2023). Surface water fCO2sw presented variability, with the highest values recorded in September and October, peaking at 437 µatm in September 2021. The lowest values for fCO2sw were found in February 2021 (368 µatm). From 2020 to 2023, surface water fCO2sw values displayed an increasing rate of 1.9 µatm yr-1 in the study area. The assessment of fCO2sw decomposition into thermal and non-thermal processes revealed the importance of SST on the fCO2sw. Nevertheless, in the present study, it is crucial to remark the impact of non-thermal factors on near-shallow coastal regions. Our findings highlight the influence of physical factors such as tides, and wind effect to horizontal mixing in these areas. The CT showed a mean concentration of 2113 ± 8 μmol kg-1 and pH at in-situ temperature (pHT,IS) has a mean value of 8.05 ± 0.02. The mean FCO2 from 2020 to 2023 was 0.34 ± 0.04 mmol m-2 d-1 (126 ± 13 mmol m-2 yr-1) acting as a slight CO2 source. In general, between May and December were the months when the area was a source of CO2. Extrapolating to the entire 6 km2 of Gando Bay, the region sourced 33 ± 4 Tons of CO2 yr-1.

Implications of Russia-Ukraine war on land surface temperature and air quality: long-term and short-term analysis.

The world is currently witnessing the military operations of Russia invading Ukraine, leading to missile bombing and shelling on various parts. Although the economic ill effects are more conspicuous and much talked about, the environmental impacts are grimmer and more devastating but ironically are less in the news. Hence, in this work, we focused on the environmental impact of the Russia-Ukraine war by quantifying the long-term(2001 to 2023) and short-term temperature changes using land surface temperature (LST) and air temperature (AT) as proxies and monitoring changes in air quality, mainly methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2), between 2021 and 2022. We used NASA MODIS FIRMS fire points from 24th February 2022 to 08th September 2023 to prepare the heat map for identifying the regions heavily devastated by bombing. Thus, parts of Kiev, Lviv, Luhansk, Odesa, Donetsk, Kherson, etc., in Ukraine were chosen for assessing the LST, AT variations during the peak season of war along with analysis of long-term and short-term changes. We used MODIS Terra LST and Emissivity, ERA 5 AT, CH4, CO2 from AIRS and CO from Sentinel 5P. The results of the LST showed an average increase of around 2.32°C (2022-2023), 3.44°C (2021 and 2022) in parts of Ukraine and an increase of about 2°C from COVID time, whilst a decrease of about 1°C during COVID. This increase in LST will cause enhanced warming, thus changing the regional climate in a shorter time frame. A consistent upward trend in CH4, CO and CO2 is seen from 2019 to 2023. These heat waves and pollution will grip Ukraine and cause menace due to the cumulative effect of heat waves, changing climate and the aftermaths of war. This would be catastrophic as it might lead to a widespread impact on human health, agricultural yield and infrastructure, to name a few.

Declining coupling between vegetation and drought over the past three decades

AbstractDroughts have been implicated as the main driver behind recent vegetation die‐off and are projected to drive greater mortality under future climate change. Understanding the coupling relationship between vegetation and drought has been of great global interest. Currently, the coupling relationship between vegetation and drought is mainly evaluated by correlation coefficients or regression slopes. However, the optimal drought timescale of vegetation response to drought, as a key indicator reflecting vegetation sensitivity to drought, has largely been ignored. Here, we apply the optimal drought timescale identification method to examine the change in coupling between vegetation and drought over the past three decades (1982–2015) with long‐term satellite‐derived Normalized Difference Vegetation Index and Standardized Precipitation‐Evapotranspiration Index data. We find substantial increasing response of vegetation to drought timescales globally, and the correlation coefficient between vegetation and drought under optimal drought timescale overall declines between 1982 and 2015. This decrease in vegetation–drought coupling is mainly observed in regions with water deficit, although its initial correlation is relatively high. However, vegetation in water‐surplus regions, with low coupling in earlier stages, is prone to show an increasing trend. The observed changes may be driven by the increasing trend of atmospheric CO2. Our findings highlight more pressing drought risk in water‐surplus regions than in water‐deficit regions, which advances our understanding of the long‐term vegetation–drought relationship and provides essential insights for mapping future vegetation sensitivity to drought under changing climate conditions.

Synergistic effect and volatile emission characteristics during co-combustion of biomass and low-rank coal

Mass loss behaviours, volatile emissions (NO, HCN, NH3, CO, and CO2), and the O2 consumption characteristics during co-combustion of Naomaohu coal (NMH coal) and pine sawdust (PS) are studied using a TG-FTIR and a specially designed fixed-bed reactor. The results reveal that the trends of CO and CO2 in the TG-FTIR and fixed bed reactor results were similar, while the NO trends showed opposite behavior. In an inert atmosphere, there was no significant interaction during co-combustion of NMH coal and PS. However, a synergistic effect was observed under air atmosphere, leading to enhanced oxidation reactions and a notable reduction in ignition time. Specifically, the ignition time of NMH coal reduced from 5 s to 0.5 s when PS was added in the proportion of 75 %. Furthermore, the replacement of 25 % NMH coal with PS resulted in an 8.9 % reduction in NO emissions. This research provides a valuable framework for the thermal conversion of blends consisting of lignocellulosic biomass and low-rank coal.

Distinguishing the combined vegetation and soil component of δ13C variation in speleothem records from subsequent degassing and prior calcite precipitation effects

Abstract. The carbon isotopic signature inherited from soil and epikarst processes may be modified by degassing and prior calcite precipitation (PCP) before its imprint on speleothem calcite. Despite laboratory demonstration of PCP effects on carbon isotopes and increasingly sophisticated models of the governing processes, to date, there has been limited effort to deconvolve the dual PCP and soil–epikarst components in measured speleothem isotopic time series. In this contribution, we explore the feasibility, advantages, and disadvantages of using trace element ratios and δ44Ca to remove the overprinting effect of PCP on measured δ13C to infer the temporal variations in the initial δ13C of drip water prior to degassing and PCP. In nine examined stalagmites, the most widely utilized PCP indicators Mg/Ca and δ44Ca covary as expected. However, Sr / Ca does not show consistent relationships with δ44Ca so PCP is not the dominant control on Sr / Ca. From δ44Ca and Mg/Ca, our calculation of PCP as fCa, the fraction of initial Ca remaining in solution at the time the stalagmite layer is deposited, yields multiple viable solutions depending on the assumed δ44Ca fractionation factor and inferred variation in DMg. Uncertainty in the effective fractionation of δ13C during degassing and precipitation contributes to uncertainty in the absolute value of estimated initial δ13C. Nonetheless, the trends in initial δ13C are less sensitive to these uncertainties. In coeval stalagmites from the same cave spanning the 94 to 82 ka interval, trends in calculated initial δ13C are more similar than those in measured δ13C and reveal a common positive-anomaly initial δ13C during a stadial cooling event. During deglaciations, calculated initial δ13C implies a trend of greater respiration rates and higher soil CO2, although the higher interglacial drip water saturation favors more extensive PCP. Initial δ13C can be estimated for active and fossil speleothems from a range of settings, wherever there is confidence that Mg/Ca and/or δ44Ca provides a quantitative indication of past changes in PCP. Further study of Mg partitioning in speleothems will improve the robustness of Mg/Ca as a PCP proxy.

Multi-Source Satellite and WRF-Chem Analyses of Atmospheric Pollution from Fires in Peninsular Southeast Asia

Atmospheric pollutant gases emitted from straw burning and forest fires can lead to air quality and human health problems. This work explored the evolutionary trends of atmospheric CO2 and other pollutant gases in five countries of Peninsular Southeast Asia (PSEA) over a long time series using various satellite remote sensing data. The research results indicate that a considerable number of fires occur in the region every spring, which negatively affects air quality. The concentration of CO2 increased every year, indicating a correlation coefficient of 0.57 with the number of fire points. The concentration of CO and NO2, respectively, showed a correlation coefficient of 0.87 and 0.95 with the number of fire points as well. Additionally, the AOD reflects the relationship between fire points and air quality. The study also used the meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) to simulate the fire season in March 2016. In this sensitivity study, we examined the impact of air pollutant gases on air quality in PSEA under a hypothetical scenario with and without fire emissions. The simulation results were also compared with satellite observations, which showed that the WRF-Chem model and the FINN (Fire INventory from NCAR) inventory could effectively simulate the spatial distribution and spatial–temporal variability characteristics of CO concentration in the fire, but the simulation result of NO2 was not satisfactory. This study suggests that spring wildfires affect not only air quality, but also short-term weather in the region.

Modeling, simulation and techno-economic evaluation of a micro-grid system based on steam gasification of organic municipal solid waste

The annual increase in population has led to rapid industrialization, urbanization, and economic growth over the years, becoming the lead cause of increased municipal solid waste (MSW) generation worldwide. In this study, MSW of 50 kg sampled by quartering method from Dandora dumpsite in Nairobi, Kenya is physically characterized and a sample of organic waste taken through proximate and ultimate analyses. Data obtained is used as input to a gasification model developed using advanced simulation and process engineering (Aspen) Plus software to provide characteristics of the yielded syngas. The obtained results are used to design a real gasification system and evaluate its techno-economic performance using HOMER® Pro as the tool for analysis. The techno-economic feasibility of the designed 60 kW gasification system is assessed considering a 165.59 kWh/day community-based load demand, with 11.5 % self-electricity consumption and 88.5 % grid feed. Results show organic and inorganic waste contents of 64.2 % and 35.8 %, respectively. The proximate and ultimate analyses reveal a high volatile matter content of 76.10 %, as well as fixed carbon content of 17.03 % in the biomass- rich-organic MSW. The simulated results show good agreement with experimental data and other simulation findings in literature. The study’s simulation output reveals 61.15 % H2, 1.42 % CH4, 24.12 % CO, 13.30 % CO2 contents following steam gasification at 700 °C. At 100 kg/h waste charge rate, a syngas yield of 2.39 m3/kg, gasification ratio of 2.2705 kg/kg and a lower heating value of 10,150 kJ/Nm3 (24.26 MJ/kg) are obtained. The sensitivity analysis results show increasing trend in CO2 and H2 syngas constituents from 0.4 to 1.0 steam-to-biomass ratio increase at 900 °C constant temperature: CO decrease is observed while CH4 values remain negligible and unaffected. The techno-economic findings reveal that the grid sales serve to offset the system’s annual costs by 39.34 %, obtaining a net present value (NPV) of $1.43 M, levelized cost of electricity (LCoE) of 0.155 $/kWh and 93.5 kg/yr. CO2 carbon footprint. An Organic MSW steam gasification micro grid is thus financially feasible in grid connected mode and is 99 % more carbon neutral compared to the Kenyan grid.

How will increased atmospheric CO2 and climate change-induced wind trends alter the probability of tree failures from wind gusts

Trees provide numerous benefits to communities, but pose a risk when they are damaged. The likelihood that trees will be damaged in a windstorm is increasing due to climate change, as wind trends are changing as the climate warms, and rising atmospheric CO2 concentrations could alter the resistance of trees to wind damage.To address these concerns, we created a tree damage model that integrates results from a meta-analysis about the effects of elevated CO2 concentrations on tree growth and an analysis of the return period of damaging winds in Toronto, Canada from 1990 to 2080. This joint analysis is applied for a simulated silver birch (Betula pendula) tree. Our model predicts that by 2080, due both to a high CO2-induced decrease in tree resilience and an increased likelihood of more frequent and intense windstorms, damaging windstorms will occur about twice as frequently as they do today.

Transcutaneous CO2 Monitoring in Extremely Low Birth Weight Premature Infants.

Extremely low birth weight (ELBW) premature infants are particularly susceptible to hypocarbia and hypercarbia, which are associated with brain and lung morbidities. Transcutaneous CO2 (TcCO2) monitoring allows for continuous non-invasive CO2 monitoring during invasive and non-invasive ventilation and is becoming more popular in the NICU. We aimed to evaluate the correlation and agreement between CO2 levels measured by a TcCO2 monitor and blood gas CO2 (bgCO2) among ELBW infants. This was a prospective observational multicenter study. All infants < 1000 g admitted to the participating NICUs during the study period were monitored by a TcCO2 monitor, if available. For each bgCO2 measured, a simultaneous TcCO2 measurement was documented. In total, 1828 pairs of TcCO2-bgCO2 values of 94 infants were collected, with a median (IQR) gestational age of 26.4 (26.0, 28.3) weeks and birth weight of 800 (702, 900) g. A moderate correlation (Pearson: r = 0.64) and good agreement (bias (95% limits of agreement)):(2.9 [-11.8, 17.6] mmHg) were found between the TcCO2 and bgCO2 values in the 25-70 mmHg TcCO2 range. The correlation between the TcCO2 and bgCO2 trends was moderate. CO2 measurements by TcCO2 are in good agreement (bias < 5 mmHg) with bgCO2 among premature infants < 1000 g during the first week of life, regardless of day of life, ventilation mode (invasive/non-invasive), and sampling method (arterial/capillary/venous). However, wide limits of agreement and moderate correlation dictate the use of TcCO2 as a complementary tool to blood gas sampling, to assess CO2 levels and trends in individual patients.

Two-dimensional modeling of CO2 mineral trapping through the oxalate‑carbonate pathway: Influence of the root system model

Two-dimensional reactive transport models, one with a simplified root system and the other accounting for dynamically evolving root architecture, were constructed to examine the influence of model complexity on capturing the effect of soil-root dynamics relating to the Oxalate Carbonate Pathway (OCP) of the Iroko tree over 170 years. Oxidation of oxalate from fallen tree tissue by soil bacteria enables local soil pH increase, leading to the sequestration of atmospheric carbon in carbonate minerals (calcite) in the shallow soil surrounding the tree. Simulations of both root models corroborate previous one-dimensional models of the OCP focused on Ca and C mass balance, where high weathering rates of Ca-containing silicate minerals in bedrock, along with contributions from groundwater, provided sufficient Ca for precipitation of observed quantities of calcite. Both simulations demonstrate the development of a distinct high pH zone where oxalate is oxidized, Ca accumulates, and calcite precipitates (OCP zone); and a low pH zone where roots collect Ca, later returned to the top soil as calcium oxalate (Total Root Extent/TRE zone) via litterfall. While the extent of OCP zone development near the ground surface was very similar between simulations, differences in localized root water uptake between the two approaches resulted in variation in water and solute transport and influenced the geometry of the OCP zone at depth, with implications for calcite precipitation in the soil. Trends in CO2 and O2 partial pressures in the OCP zone were mirrored in the TRE zone, suggesting linkage between the two zones with regard to gas transport. Near the end of the tree's lifespan, results indicate that soil permeability decreases due to calcite precipitation may limit O2 ingress and availability in the shallow soil, while trapping CO2 released from the oxidation of organics in the shallow soil, with implications for the long-term sustainability of the OCP itself.

Modeling the dynamics of changes in CO2 emissions from Polish road transport in the context of COVID-19 and decarbonization requirements

Emissions from transport account for 20%–25% of global carbon dioxide emissions, with more than 70% coming from road transport, making it an extremely important topic in the context of decarbonization. The aim of the article is to analyze the trend of CO2 generated from road transport, taking into account the its various sources, and also to examine the manner in which reduced mobility during the pandemic affected the emissions at the time. For this purpose, a time series containing observations up to the pandemic outbreak and a time series containing additional observations from the pandemic period were analyzed. For each time series, a trend was determined and described by a polynomial and then verified to see if the pandemic phenomenon significantly affects a parameter of the proposed model, using appropriate statistical tests.

Comparative measurement of CO2, CH4 and CO at two traffic interjunctions having inflated vehicular flow in Delhi

Vehicular emissions are considered one of the major anthropogenic sources of greenhouse gases and poor air quality in metropolitan cities. This study aims to see the correlation of CO2, CH4, and CO through monitoring over a period from December 2020 to October 2021 covering three seasons’ winter, summer, and monsoon at two different traffic locations of Delhi having different traffic volumes, road patterns, and traffic management. The annual average morning concentration of CO2, CH4 and CO was found (533 ± 105), (7.3 ± 3.1), (10.7 ± 3.0) ppm at Najafgarh and (480 ± 70), (5.2 ± 1.8), (7.8 ± 2.8) ppm at Rajendra Place, respectively. A relationship between concentration of all three gases and meteorological parameters such as temperature, humidity, wind speed and wind direction has also been investigated using Pearson correlation coefficient and pollution rose diagram. A comparable pattern in concentration was observed for all three gases in spatial (location) and temporal (diurnal) distribution. The concentration trend of CO2 in different seasons is winter > summer > monsoon, while in the case of CH4 winter = summer > monsoon but not any seasonal trend was noted in CO case. It is observed that CO2 has a good relation with CO (a tracer for vehicular emission) in terms of diurnal variation, whereas, CH4 does not represent a relation with CO and CO2 diurnally, suggesting that vehicles are the source of CO2 but not much contributing to other greenhouse gases like CH4.