CO2 Values Research Articles

Assessment of some toxic elements (Co, Cr, Mn, Se, and As) in muscle, offal, hair, and blood of camels (Camelus dromedaries) and their risk assessment.

Camel meat tainted with heavy metals or trace elements may pose a health risk to consumers. Heavy metal contamination poses a severe danger due to both their toxicity and bioaccumulation in the food chain. To estimate the residual levels of heavy metals (Co, Cr, Mn, Se, and As) in muscle, liver, kidney, hair, and serum of three camel breeds (Magaheem, Maghateer, and Wadha) collected from Al-Omran abattoir, Al-Ahsa, Saudi Arabia. A total of 225 tissue samples (muscles, liver, kidney, serum, and hair) were taken and analyzed using an Atomic Absorption Spectrophotometer. Health risk assessment was assessed using the guidelines set by the US Environmental Protection Agency. Camel breed significantly (p < 0.05) influences Co, Cr, Mn, and Se accumulation and distribution in organs and muscle; however, arsenic accumulation was not significantly affected (p < 0.05) by camel breeds. The highest values of Co, Cr, Se, and Mn in all examined samples were detected in the liver samples of Maghateer and Magaheem breeds. Furthermore, significant strong positive correlation between serum and liver cobalt, chromium, manganese, and arsenic. The estimated daily intake owing to camel meat consumption was less than the tolerated daily intake. Heavy metals were distributed among different breeds of camel. Trace elements (Pb and Cd) in meat and offal were below the international maximum permissible limit. The correlation between samples reflects the role of hair as a good tool for the identification of heavy metal pollution.

Comparative study of combustion and thermal performance of a meso-scale combustor under co- and counter-rotating fuel and oxidizer swirling flows for micro power generators

Direct energy conversion systems, such as thermophotovoltaic and thermoelectric generators, have received increasing attention in micro power generation. Micro and meso-scale combustors are one of the most core components in these systems. So, developing combustion stabilization technologies for micro or meso-scale combustors is of great importance. In these systems, a hydrocarbon fuel with high energy density is burned in a micro or meso-scale combustor. Many studies have been conducted to explore various combustion stabilization techniques, but as a novelty, in this work, we study the combustion and thermal performance of a meso-scale micro power generator powered by a swirling fuel jet discharging into a co- or counter-rotating air coflow. To do so, we used 3D-printed axial swirlers with double annulus to form the swirling co- and counter-rotating fuel (methane) jet-air coflow configurations at various air and fuel flow rates. Blow-out limit, flame characteristics, combustor mean outer wall temperature, pollutant emissions, emitter efficiency, and normalized temperature standard deviation are investigated in this study. The results show that swirl addition enhances the blow-out limit significantly and co-rotating swirling flows generally enhances the flame blow-out limit when compared with the counter-rotating swirling flows mode at high fuel flow rates. Moreover, the combustor with co-rotating swirling flows has shorter lift-off height and longer flame length. The sensitivity of the flame lift-off height to an increment of the fuel mass flow rate is smaller in co-rotating than in counter-rotating swirling flows (more than 40%). Furthermore, it is observed that under the same operating conditions, co-rotating swirling flows exhibit lower values of CO and NOx in the flue gas and higher values of mean outer wall temperature, combustion efficiency, emitter efficiency, and normalized temperature standard deviation. The enhancement of the emitter efficiency by implementing co-swirl configuration is about 35%, 26%, and 8% for the methane flow rates of 0.050, 0.100, and 0.150slpm, respectively when compared with the counter-swirl mode. The results of this work can provide useful information to choose between co- and counter-rotating flows for combustors of combustion-based micro power generators.

Mechanical Improvement of Gas Monitoring System in Monoplace Hyperbaric Chamber to Advance the Safety and Efficacy.

A Monoplace hyperbaric chamber delivers oxygen to the patient's tissues through breathing. Gas monitoring inside the chamber is important because oxygen (O2) is consumed, and carbon dioxide (CO2) is increased because treatment is performed in a closed volume. This study aimed to advance the safety and efficacy of the monoplace hyperbaric chamber (MHC) through mechanical improvement in a gas monitoring system (GMS). First, as the oxygen supply method was changed to the direction of the patient's face, it was compared the values of O2, CO2, humidity, and temperature were measured in the MHC and the GMS when operating at 2.0 atmosphere absolute (ATA) and 3.0 ATA. Second, to evaluate the effects of variables across measuring time, it was analyzed in a 3-way repeated measure ANOVA (10 min.×20 min.×30 min.). Lastly, the values before and after the optimization of the MHC were compared by applying a cooler to prevent temperature rise inside the MHC. In 2.0 ATA, the average humidity was higher in the MHC than in the GMS (p<0.001). Also, the average temperature was lower in the MHC than in the GMS (p<0.001). In 3.0 ATA, the average CO2 and humidity were higher in the MHC than in the GMS, respectively (p<0.001, p=0.004). The 3-way repeated measures ANOVA revealed a significant difference in most main and interacted factors (p<0.05). O2 and temperature, comparing before and after MHC optimization, revealed a significant difference (p<0.05). Few studies have verified safety and effectiveness by evaluating the pressure, oxygen concentration, etc. of a monoplace hyperbaric chamber. Further research is expected to verify the effectiveness of providing comfort to patients receiving hyperbaric oxygen treatment and increase the treatment effect.

A prediction model for CO2/CO adsorption performance on binary alloys based on machine learning.

Despite the rapid development of computational methods, including density functional theory (DFT), predicting the performance of a catalytic material merely based on its atomic arrangements remains challenging. Although quantum mechanics-based methods can model 'real' materials with dopants, grain boundaries, and interfaces with acceptable accuracy, the high demand for computational resources no longer meets the needs of modern scientific research. On the other hand, Machine Learning (ML) method can accelerate the screening of alloy-based catalytic materials. In this study, an ML model was developed to predict the CO2 and CO adsorption affinity on single-atom doped binary alloys based on the thermochemical properties of component metals. By using a greedy algorithm, the best combination of features was determined, and the ML model was trained and verified based on a data set containing 78 alloys on which the adsorption energy values of CO2 and CO were calculated from DFT. Comparison between predicted and DFT calculated adsorption energy values suggests that the extreme gradient boosting (XGBoost) algorithm has excellent generalization performance, and the R-squared (R2) for CO2 and CO adsorption energy prediction are 0.96 and 0.91, respectively. The errors of predicted adsorption energy are 0.138 eV and 0.075 eV for CO2 and CO, respectively. This model can be expected to advance our understanding of structure-property relationships at the fundamental level and be used in large-scale screening of alloy-based catalysts.

Production of green hydrogen from sewage sludge / algae in agriculture diesel engine: Performance Evaluation

Alternative fuel opportunities can satisfy energy security and reduce carbon emissions. In this regard, the hydrogen fuel is derived from the source of environmental pollutants like sewage and algae wastewater through hydrothermal gasification technique using a KOH catalyst with varied gasification process parameters of duration and temperature of 6–30 min and 500-800 °C. The novelty of the work is to identify the optimum gasification process parameter for obtaining the maximum hydrogen yield using a KOH catalyst as an alternative fuel for agricultural engine applications. Influences of gasification processing time and temperature on H2 selectivity, Carbon gasification efficiency (CE), Lower heating value (LHV), Hydrogen yield potential (HYP), and gasification efficiency (GE) were studied. Its results showed that the gasifier operated at 800 °C for 30 min, offering maximum hydrogen yield (26 mol/kg) and gasification efficiency (58 %). The synthesized H2 was an alternative fuel blended with diesel fuel/TiO2 nanoparticles. It was experimentally studied using an internal combustion engine. Influences of H2 on engine performance, like brake-specific fuel consumption, brake thermal efficiency and emission performances, were measured and compared with diesel fuel. The results showed that DH20T has the least (420g/kWh) brake-specific fuel consumption (BSFC) and superior brake thermal efficiency of about 25.2 %. The emission results revealed that the DH20T blend showed the NOX value increased by almost 10.97 % compared to diesel fuel, whereas the CO, UHC, and smoke values reduced by roughly 31.25, 28.34, and 42.35 %. The optimum fuel blend (DH20T) result is recommended for agricultural engine applications.

Investigation of effects on fuel consumption and exhaust emissions by using bioethanol gasoline mixture in an engine with ultrasonic fuel system

This study compared the fuel consumption and exhaust emissions of a spark-ignition engine using a carburetor fuel system, an injection fuel system, and an ultrasonic fuel system. When using gasoline only, the ultrasonic fuel system showed a 31% decrease in fuel consumption compared to the carburetor system and a 15% decrease compared to the injection system. When adding 10% bioethanol to the gasoline, fuel consumption increased in all three systems, with the ultrasonic system showing the largest increase of 10%. Exhaust emissions were also measured, and the ultrasonic system showed a significant decrease in CO, HC, and NOx compared to the carburetor and injection systems, with the largest decrease in CO emissions. The addition of bioethanol to the fuel resulted in reducing exhaust emission values in all three systems, with the ultrasonic system showing the largest decrease in CO and HC emissions compared to the carburetor and injection systems, but with an increase in NOx emissions compared to the injection system. When comparing three fuel systems, it was observed that injection fuel systems have the highest CO2 values. Although the addition of alcohol to the fuel does not cause a significant change in CO2 emission values for injection and ultrasonic fuel systems, an increase is observed in the carburetor fuel system. Overall, the ultrasonic fuel system showed promising results for reducing fuel consumption and improving exhaust emissions.

Measurement of Motor Vehicle Emissions Based on Low-cost Sensors

One of Indonesia's primary causes of air pollution is the significant level of human activity, particularly the continued use of fossil-fuel-powered vehicles. The incomplete combustion of fossil fuels can lead to gas and particle pollutants forming, impacting the environment. However, the instruments utilized for detecting environmental pollutants are relatively expensive. Therefore, motor vehicle emission tests use low-cost sensors with parameters such as CO, CO2, NO2, PM2.5, temperature, and RH. The flow rate measures the emission gas flow extracted from a vehicle's exhaust into the testing chamber and then released into the air for disposal. The flow rate utilized in these tests ranges from 12 to 15 lpm. The tests are conducted over 10 minutes to ensure accuracy, obtaining average readings for the measured parameters. For the measurement results using a low-cost sensor, the average value for CO is 383.891 ppm, NO2 is 10.7237 ppm, CO2 is 5,254 ppm, PM2.5 is 50.25 ?g/m3, temperature and RH is 28.9 °C and 76%. The official test results obtained a CO value of 1,200 ppm, CO2 of 140,000 ppm, and a temperature of 80 °C. This difference is because the reading range of low-cost sensors is relatively small but has a stable data trend.

Off-Gassing and Oxygen Depletion in Headspaces of Solid Biofuels Produced from Forest Residue Biomass

As living standards improve worldwide, the demand for energy increases. However, climate changes and decreasing fossil fuel deposits have increased interest in renewable energy sources, including pellets produced from forest residues. This study aimed to compare changes in concentration of gases (CO, CO2, O2, volatile organic compounds—VOCs) in enclosed headspaces above pellets produced from deciduous (oak OA, birch BI) and coniferous (pine PI, spruce SP) dendromass and selected types of commercial pellets during their storage. The experiment measured the concentration of gas released from the pellets in storage daily for 14 days. The highest mean CO concentration was found for PI pellets (1194 ppm), and the lowest was for OA (63.3 ppm). Likewise, the highest CO2 concentration was noted for PI pellets (4650 ppm), and the lowest was for BI (1279 ppm). The largest VOC amount was released in the headspace above PI (88.8 ppm), and the smallest was above BI (4.6 ppm). The oxygen concentration was the lowest as measured for PI (minimum 16.1% v/v) and for SP (19.3% v/v). The threshold limit value (8 h) for CO was exceeded for all the pellets under analysis and, in the case of CO2, only for PI after day 10 of incubation. The study findings are extremely important from a scientific (but mainly from a practical) perspective because of the safety of storing and transporting wood pellets. The knowledge of autooxidation processes in those biofuels can help organize their logistics and storage and result in proper warehouse ventilation and monitoring of noxious gases.

Impacts of varied industrial activities within southern Nigeria on air environment and human health

The contamination of air environment by industrial activities is a global problem mostly in the underdeveloped and developing Nations where environmental issues are handled with levity. This research investigated the impact of industrial activities on air environment at the following companies; Crude Oil processing (COPC), beer processing (BPC), asphalt processing (APC), metal processing (MPC), and construction Company machinery Yard (CCMY) in Southern Nigeria. Air Monitors were employed to quantify nitrogen (IV) oxide (NO2), sulphur (IV) oxide (SO2), hydrogen sulphide (H2S), cabon (II) Oxide CO, total volatile organic carbon (TVOC), and suspended particulate matter (SPM) at the studied locations. The mean values of NO2, SO2, H2S, and CO obtained at all the industrial locations were higher than their recommended limits by the Federal Environmental and protection Agency (FEPA) except at BPC. The mean levels of TVOC were higher than the limit at all the locations apart from BPC and CCMY. However, the mean levels of SPM at all locations were higher than the permissible limit. The general trend for the discharge of air pollutants indicated that, COPC and BPC were rated the highest and lowest, respectively. The air quality index (AQI) values obtained revealed that, all the air pollutants at all the locations except BPC were harmful to human health. Nevertheless, the mean AQI value of SPM at BPC was also in the hazardous class. The Principal component analysis (PCA) confirmed that, industrial activities at the studied locations were responsible for the accumulation of these toxic substances in the adjoining air environment. Hierarchical cluster analysis (HCA) for the air pollutants corroborated that most of the parameters were from a common source. HCA for the studied locations indicated similarities between BPC and CCMY, APC and MPC, while COPC was in a separate cluster. Thus, this study has shown the effects of untreated gases released from industries into the air on the environment and appropriate measures should be adopted to ameliorate the trend.

Bioaccumulation, biomagnification, and ecological risk of trace metals in the ecosystem around oilfield production area: A case study in Shengli Oilfield.

The production for crude oil usually leads to contamination of the soil with trace metals and organic contaminants from spilled petroleum. Organic contaminants were generally paid more attention than trace metals in the oilfield pollution. Many studies have investigated the impacts of some petroleum hydrocarbon pollutants, however, the impacts and risk assessment of trace metals remain largely unexplored. Moreover, under some circumstances, the risks associated with trace metals are not necessarily lower than those associated with organic contaminants. This study aimed to investigate methods to evaluate the possible risks associated with 11 trace metals (Ti, Ba, Sr, Rb, V, Li, Mo, Co, Cs, Bi, and Tl) in soil and biota samples from the Shengli Oilfield using ICP-MS. The results showed that 11 trace metals in the surface soils exceeded the local background levels. The geo-accumulation index (Igeo) indicated that the soils had light-moderate to moderate contamination levels, with higher Igeo value of Ba, V, Li, Mo, Co, and Cs. The individual potential ecological risk indices ([Formula: see text]) demonstrated moderate Bi and Tl pollution in soils. Comparatively, the [Formula: see text] is recommended for the risk assessment of trace metals on the ecosystem around the oilfield area. Mo, Bi, and Sr easily accumulate in plants, as reflected by their bioaccumulation factor. Ti, Ba, V, Li, Co, Cs, Bi, and Tl exhibited considerable biomagnification, particularly in birds. In this study, trace metals showed considerable bioaccumulation and biomagnification, and the risks of these trace metals on the ecosystem around oilfield production area need more attention.

In situ simultaneous measuring method for the determination of key processes of soil organic carbon cycling: Soil microbial respiration using laser spectrometry.

Soil microbial heterotrophic C-CO2 respiration is important for C cycling. Soil CO2 differentiation and quantification are vital for understanding soil C cycling and CO2 emission mitigation. Presently, soil microbial respiration (SR) quantification models are based on native soil organic matter (SOM) and require consistent monitoring of δ13C and CO2. We present a new apparatus for achieving in situ soil static chamber incubation and simultaneous CO2 and δ13C monitoring by cavity ring-down spectroscopy (CRDS) coupled with a soil culture and gas introduction module (SCGIM) with multi-channel. After a meticulous five-point inter-calibration, the repeatability of CO2 and δ13C values by using CRDS-SCGIM were determined, and compared with those obtained using gas chromatography (GC) and isotope ratio mass spectrometry (IRMS), respectively. We examined the method regarding quantifying SR with various concentrations and enrichment of glucose and then applied it to investigate the responses of SR to the addition of different exogenous organic materials (glucose and rice residues) into paddy soils during a 21-day incubation. The CRDS-SCGIM CO2 and δ13C measurements were conducted with high precision (<1.0µmol/mol and 1‰, respectively). The optimal sampling interval and the amount added were not exceeded 4 h and 200mg C/100g dry soil in a 1 L incubation bottle, respectively; the 13C-enrichment of 3%-7% was appropriate. The total SR rates observed were 0.6-4.2µL/h/g and the exogenous organic materials induced -49%-28% of priming effects in native SOM mineralisation. Our results show that CRDS-SCGIM is a method suitable for the quantification of soil microbial CO2 respiration, requiring less extensive lab resources than GC/IRMS.

Late Oligocene atmospheric carbon dioxide concentrations reconstructed from fossil leaves using stomatal index

Ancient atmospheric CO2 can be reconstructed using various climate proxies; stomata from fossil leaves are one of the climate proxies that provide critical information about past climatic conditions of the Earth. Exceptionally well–preserved fossil leaves found in overbank deposits in Chilga of Northwest Ethiopia were used to estimate late Oligocene atmospheric CO2 values using stomatal index. The age of the fossils, 206Pb/238U: 27.23 ± 0.03 Ma, was determined from zircons in an ash deposit comprising the matrix deposited contemporaneously with the fossil leaves. Stomatal indices were calculated from both the fossil leaves and nearest living relatives of the fossils. Corresponding atmospheric CO2 values for the nearest living relatives of the fossils were assigned from historical records from the Mauna Loa Observatory. This produces a calibrating curve that shows variation of atmospheric CO2 over time, and late Oligocene atmospheric CO2 values were quantified from the calibrating curve. The quantified late Oligocene atmospheric CO2 values are about 343 ± 11 ppm which show a 12 % decrease when they are quantified using a leaf gas exchange method. This is consistent with the idea that stomatal–index method underestimates CO2 values compared to the leaf gas exchange method. The late Oligocene was colder than both its preceding Eocene and its following Miocene epochs, and the results are incongruent with the cold Oligocene period. These results for this particular geologic time provide opportunity to examine how plants responded to climate changes in the past and have important implications for the study of current and future climate changes.

VISITATION SHELTERS FOR THE LONG-TERM CARE SETTING DURING THE PANDEMIC: AN EXPLORATORY STUDY

Abstract In 2020, the province of Manitoba in Canada devised a plan to provide external visitation shelters for long-term care (LTC) facilities. The intent of the shelters was to alleviate the problems with visitor restrictions due to the COVID-19 pandemic. Dozens of visitation shelters, which were re-purposed shipping containers, were installed at facilities across the province. The purpose of this research was to: examine the experiences of the users through online surveys; make field measurements of the conditions (CO2 values, lighting, acoustics); and conduct an environmental scan of documents (government, media, etc.). Media and government documents provided insights into: design considerations; timing of installation/use; policies and procedures; how much they were utilized; as well as constraints. Survey findings from family/friends (n=20), LTC staff (n=9) and a resident (n=1) revealed that while many agreed that the shelters made a difference for their emotional well-being, many felt that the shelters did not support meaningful connections between residents and visitors. Furthermore, many respondents described the shelters as institutional/sterile and suggested that the décor should be improved to make them homier. Field measurements showed that the ventilation system ensured that CO2 values remained low, indicating that substantial fresh air exchange occurred. Acoustic values indicated that there could be challenges with residents hearing visitors. Lighting values demonstrated that color temperature was appropriate, but lux values were relatively low depending on the specific location in the shelter. Overall, this study was able to outline the advantages and disadvantages to using external visitation shelters in a pandemic situation.

CFD-based multi-objective optimization of indoor air quality and thermal comfort in a classroom

Comfort conditions and air quality in educational buildings can affect students’ performance, achievement and productivity, but they can also threaten their health. In this study, a sample classroom in Trakya University, Edirne, which lacks a ventilation system, is discussed. Depending on the determined parameters, an optimization study was performed using computational fluid dynamics. Predicted mean vote (PMV) for general thermal comfort, draught rate (DR) for local thermal comfort and the carbon dioxide (CO2) level for indoor air quality are selected as target functions. Outdoor air temperature, heating/ventilation system, insulation thickness, number of people in the classroom and clothing factor were identified as parameters that could affect the target functions. According to the numerical results, the rank of importance of the parameters affecting the target functions was calculated using the Taguchi method. The effect percentages of the parameters were determined using the analysis of variance. Then, all target functions were optimized with the grey relational analysis. The best case obtained as a result of the optimization has PMV, CO2 and DR values of −0.12, 511 ppm and 5.37%, respectively. When the general results are evaluated, a comfortable and healthy environment is provided in the classroom with the underfloor air distribution system operating at 100% fresh air and a reduced number of occupants.

Numerical Simulations of Gasification of Low-Grade Coal and Lignocellulosic Biomasses in Two-Stage Multi-Opposite Burner Gasifier

Thermochemical processes utilizing biomass demonstrate promising prospects for the generation of syngas. In this work, a gasification process employing combination of an indigenous low-grade coal with two distinct biomass sources, namely rice husk (RH) and wood sawdust (WS), was explored. The gasification of the selected feedstock was performed using a double-staged multi-opposite burner (MOB) gasifier. A 3D computational fluid dynamics (CFD) model was employed to analyze the effect of kinetic and diffusion rates on the overall gasification performance of an entrained flow biomass gasifier. DPM was employed to track the particles’ trajectory, while the gas phase was treated as the continuous phase, and its behavior was predicted using a standard k-epsilon turbulent model. To calculate both the homogeneous and heterogeneous reaction rates, the finite rate/eddy dissipation model was implemented. The findings indicate that the char conversion efficiency exceeded 95% across all instances. Among the different reaction schemes, scheme E (which involved complete volatile and char combustion reactions) produced better results in comparison with published results, with less than 1% error. Hence, scheme E was validated and utilized for the rest of the simulated cases. The feeding rate has an inverse effect on the overall performance of the gasifier. An increase in feed rate decreases the CO and H2 composition in syngas. The maximum CO value was observed to be 57.59% at a 1.0 O/C ratio with a 0.005 kg/s feed rate, and the maximum H2 value was observed to be 16.58% in the same conditions for Lakhra coal samples. In summary, Lakhra coal exhibited better performance than other biomass samples due to its better fixed carbon and volatiles in its composition.

A detailed molecular dynamics simulation and experimental investigation of CO2 adsorption on graphene oxide-polyaniline nanocomposite

The study investigated the sorption and diffusion of carbon dioxide on Graphene oxide-polyaniline (GO-PANI) using volumetric method and molecular dynamics simulations. The experimental results showed that GO-PANI was more effective at adsorbing CO2 than either of the individual materials alone. Simulations supported this trend in CO2 adsorption and provided additional insights into the structural information of the adsorbents and the dynamics of CO2 molecules. The Langmuir adsorption model was employed to fit sorption isotherms computed using Grand Canonical Monte Carlo (GCMC) method. The GO-PANI nanocomposite compound exhibited a superior adsorption rate compared to pure structures. The isosteric heat for CO2 adsorption was 27.59 kJ/mol. The interaction energy of single molecules of CO2 on GO-PANI surface was −38.075 kcal/mol. Diffusion coefficient value for CO2 was 41.2 × 10 −9 m2/s, lower than that of the pure polymer. FT-IR, FE-SEM, and BET techniques were used to analyze synthesized GO-PANI structure. The highest CO2 adsorption was observed at a temperature of 283 K. Isosteric heat adsorption decreased with uniform surface charge. This research provides critical microscopic information on gas adsorption in polymer nanocomposites and demonstrates the effectiveness of GO-PANI as an efficient adsorbent for carbon dioxide, which could be useful in various industrial applications.

Stratigraphic distributions of biomarkers and carbon isotopes in coals constrain the Permo-Carboniferous climatic changes and floral turnovers in the north China block

The intricate relationship between climate and vegetation dynamics, particularly during the late Paleozoic ice age marked by multiple icehouse-greenhouse transitions, is a compelling aspect in Earth's historical narrative. In this study, we decipher the interactions between the Permo-Carboniferous climate fluctuations and floral turnovers within the North China Craton, based on the stratigraphic distributions of biomarkers and carbon isotopes from cored coals in Huainan coalfield, North China. Our findings reveal that the changes in n-alkane, terpane, sterane, and polycyclic aromatic hydrocarbon (PAH) distributions result from a confluence of maturation, depositional environment, and organofacies effects. Molecular maturity-sensitive ratios align with the maturity stage determined by Rock-Eval pyrolysis and petrography, categorizing the coals as high volatile bituminous A/B with a composite organic matter derived from terrestrial plants and marine algae. Notably, the 18α-22,29,30-trisnorneohopane (Ts) to 17α-trisnorhopane ratio (Ts/(Ts + Tm)), as well as C31–C34 22S/(22S + 22R) hopanes and C29 20S/(20S + 20R) steranes ratios exhibit moderate correlations with %Ro, indicative of epimerization reactions induced by maturation processes. The stratigraphic variations in pristane to phytane ratios (Pr/Ph), Pr/n-C17, Ph/n-C18, C30 αβ/(αβ+βα) hopanes, and organofacies sensitive PAH indices collectively capture a paleoenvironmental shift from reducing to oxic conditions attributed to marine regression. The systematic changes in PAH concentrations and their maturity indices reflect condensation and dealkylation reactions during the maturation process. The δ13C signature manifests a negative excursion in coals of the Artinskian Shanxi Formation and a subsequent positive excursion in the Capitanian Upper Shihezi Formation coals, respectively, reflecting changes in the δ13C values of contemporaneous atmospheric CO2 in response to regional aridity fluctuations.

Postsynaptic cell type and synaptic distance do not determine efficiency of monosynaptic rabies virus spread measured at synaptic resolution.

Retrograde monosynaptic tracing using glycoprotein-deleted rabies virus is an important component of the toolkit for investigation of neural circuit structure and connectivity. It allows for the identification of first-order presynaptic connections to cell populations of interest across both the central and peripheral nervous system, helping to decipher the complex connectivity patterns of neural networks that give rise to brain function. Despite its utility, the factors that influence the probability of transsynaptic rabies spread are not well understood. While it is well established that expression levels of rabies glycoprotein used to trans-complement G-deleted rabies can result in large changes in numbers of inputs labeled per starter cell (convergence index [CI]), it is not known how typical values of CI relate to the proportions of synaptic contacts or input neurons labeled. And it is not known whether inputs to different cell types, or synaptic contacts that are more proximal or distal to the cell body, are labeled with different probabilities. Here, we use a new rabies virus construct that allows for the simultaneous labeling of pre- and postsynaptic specializations to quantify the proportion of synaptic contacts labeled in mouse primary visual cortex. We demonstrate that with typical conditions about 40% of first-order presynaptic excitatory synapses to cortical excitatory and inhibitory neurons are labeled. We show that using matched tracing conditions there are similar proportions of labeled contacts onto L4 excitatory pyramidal, somatostatin (Sst) inhibitory, and vasoactive intestinal peptide (Vip) starter cell types. Furthermore, we find no difference in the proportions of labeled excitatory contacts onto postsynaptic sites at different subcellular locations.

Orbital CO2 reconstruction using boron isotopes during the late Pleistocene, an assessment of accuracy

Abstract. Boron isotopes in planktonic foraminifera are a widely used proxy to determine ancient surface seawater pH and by extension atmospheric CO2 concentration and climate forcing on geological timescales. Yet, to reconstruct absolute values for pH and CO2, we require a δ11Bforam-borate to pH calibration and independent determinations of ocean temperature, salinity, a second carbonate parameter, and the boron isotope composition of seawater. Although δ11B-derived records of atmospheric CO2 have been shown to perform well against ice-core-based CO2 reconstructions, these tests have been performed at only a few locations and with limited temporal resolution. Here we present two highly resolved CO2 records for the late Pleistocene from Ocean Drilling Program (ODP) Sites 999 and 871. Our δ11B-derived CO2 record shows a very good agreement with the ice core CO2 record with an average offset of 13±46 (2σ) and an RMSE of 26 ppm, with minor short-lived overestimations of CO2 (of up to ∼50 ppm) occurring during some glacial onsets. We explore potential drivers of this disagreement and conclude that partial dissolution of foraminifera has a minimal effect on the CO2 offset. We also observe that the general agreement between δ11B-derived and ice core CO2 is improved by optimising the δ11Bforam-borate calibration. Despite these minor issues, a strong linear relationship between relative change in climate forcing from CO2 (from ice core data) and pH change (from δ11B) exists over the late Pleistocene, confirming that pH change is a robust proxy of climate forcing over relatively short (&lt;1 million year) intervals. Overall, these findings demonstrate that the boron isotope proxy is a reliable indicator of CO2 beyond the reach of the ice cores and can help improve determinations of climate sensitivity for ancient time intervals.

Detailed Gaseous and Particulate Emissions of an Allison 250-C20B Turboshaft Engine

Abstract Aviation is known to be one of the most significant contributors to air pollutants. This includes gaseous emissions, like carbon dioxide (CO2) and nitrogen oxides (NOx), and also particulate matter (PM), especially in the form of soot. This study conducted emission measurements on an Allison 250-C20B turboshaft engine operating on Jet A-1 fuel with a focus on gaseous compounds (e.g., ozone precursors) and PM. The different engine loading points were chosen based on the percentage thrust ratios of the International Civil Aviation Organization LTO-Cycle. A standard FTIR/O2/FID system to measure general gaseous combustion compounds, e.g., CO2, carbon monoxide (CO), unburned hydrocarbons (UHC), and NOx. For the investigation of the volatile organic compounds (VOC), which are known to act as ozone precursors, a gas chromatograph was applied. Different measurement methods were used to characterize the PM emissions. For the particle size distribution (PSD), we used two types of electrical mobility analyzers and an aerodynamic aerosol classifier. All measurement systems yielded comparable PSD results, indicating reliable results. The particle measurement methods all show increasing aerosol diameter modes (electrical and aerodynamic) with increased engine loading. The aerosol diameter modes were shifting from 29 nm to 65 nm. The size and shape of different individual particles were evaluated with a scanning electron microscope. A correlation between the injection system and the particle formation was established. Gaseous turboshaft engine emissions show high CO and UHC values at Ground Idle level. NOx levels were the highest at Take-Off conditions. Acetylene and ethylene were the most significant contributors to ozone formation.