Boosting CO2 Electroreduction over a Covalent Organic Framework in the Presence of Oxygen

Herein, we propose an oxygen-containing species coordination strategy to boost CO2 electroreduction in the presence of O2. A two-dimensional (2D) conjugated metal-covalent organic framework (MCOF), denoted as NiPc-Salen(Co)2-COF that is composed of the Ni-phthalocyanine (NiPc) unit with well-defined Ni-N4-O sites and the salen(Co)2 moiety with binuclear Co-N2O2 sites, is developed and synthesized for enhancing the CO2RR under aerobic condition. In the presence of O2, one of the Co sites in the NiPc-Salen(Co)2-COF that coordinated with the intermediate of *OOH from ORR could decrease the energy barrier of the activation of CO2 molecules and stabilize the key intermediate *COOH of the CO2RR over the adjacent Co center. Besides, the oxygen species axially coordinated Ni-N4-O sites can favor in reducing the energy barrier of the intermediate *COOH formation for the CO2RR. Thus, NiPc-Salen(Co)2-COF exhibits high oxygen-tolerant CO2RR performance and achieves outstanding CO Faradaic efficiency (FECO) of 97.2 % at -1.0 V vs. the reversible hydrogen electrode (RHE) and a high CO partial current density of 40.3 mA cm-2 at -1.1 V in the presence of 0.5 % O2, which is superior to that in pure CO2 feed gas (FECO=94.8 %, jCO=19.9 mA cm-2). Notably, the NiPc-Salen(Co)2-COF achieves an industrial-level current density of 128.3 mA cm-2 in the flow-cell reactor with 0.5 % O2 at -0.8 V, which is higher than that in pure CO2 atmosphere (jCO=104.8 mA cm-2). It is worth noting that an excellent FECO of 86.8 % is still achieved in the presence of 5 % O2 at -1.0 V. This work provides an effective strategy to enable the CO2RR under O2 atmosphere by utilizing the *OOH intermediates of ORR to boost CO2 electroreduction.

Catalytic removal of gaseous pollutant NO using CO: Catalyst structure and reaction mechanism

Carbon monoxide (CO) has recently been considered an ideal reducing agent to replace NH3 in selective catalytic reduction of NOx (NH3-SCR). This shift is particularly relevant in diesel engines, coal-fired industry, the iron and steel industry, of which generate substantial amounts of CO due to incomplete combustion. Developing high-performance catalysts remain a critical challenge for commercializing this technology. The active sites on catalyst surface play a crucial role in the various microscopic reaction steps of this reaction. This work provides a comprehensive overview and insights into the reaction mechanism of active sites on transition metal- and noble metal-based catalysts, including the types of intermediates and active sites, as well as the conversion mechanism of active molecules or atoms. In addition, the effects of factors such as O2, SO2, and alkali metals, on NO reduction by CO were discussed, and the prospects for catalyst design are proposed. It is hoped to provide theoretical guidance for the rational design of efficient CO selective catalytic denitration materials based on the structure-activity relations.

Hard-Target Reflection Laser Spectroscopy of Carbon Monoxide Gas Concentration for the Early Detection of Spontaneous Combustion of Coal

We report on the hard-target reflection spectroscopy of carbon monoxide (CO) gas based on the technique of infrared tunable diode laser absorption spectroscopy aiming at developing a low-cost yet sensitive sensor for the early detection of spontaneous coal combustion. A narrow-band distributed feedback laser emitting around 2333.7 nm is used to monitor CO gas molecules contained in a 5 cm gas cell. The light diffusely backscattered from the surface of a lump of coal placed at the end of a 50 cm light path is detected with a photodiode in the coaxial transmitter/receiver setup. From the variation of the detected signal profile with the CO partial pressure in the cell, the detection limit of the current system is estimated to be about 30 parts per million per meter (ppm·m), which meets the sensitivity required for monitoring the self-heating of coal in mines, silos, or stockpiles.

Study of the Chemical Activities of Carbon Monoxide, Carbon Dioxide, and Oxygen Traces as Critical Inhibitors of Polypropylene Synthesis

This study outlines the investigation into how the compounds CO2, CO, and O2 interact with the active center of titanium (Ti) on the surface of MgCl2 and how these interactions impact the productivity of the Ziegler-Natta catalyst, ultimately influencing the thermal stability of the produced polypropylene. The calculations revealed that the adsorption energies of Ti-CO2-CO and O2 were -9.6, -12.5, and -2.32 Kcal/mol, respectively. Using the density functional theory in quantum calculations, the impacts of electronic properties and molecular structure on the adsorption of CO, O2, and CO2 on the Ziegler-Natta catalyst were thoroughly explored. Additionally, the Gibbs free energy and enthalpy of adsorption were examined. It was discovered that strong adsorption and a significant energy release (-16.2 kcal/mol) during CO adsorption could explain why this gas caused the most substantial reductions in the ZN catalyst productivity. These findings are supported by experimental tests showing that carbon monoxide has the most significant impact on the ZN catalyst productivity, followed by carbon dioxide, while oxygen exerts a less pronounced inhibitory effect.

Recent Advances in Hydrogenation of CO2 to CO with Heterogeneous Catalysts Through the RWGS Reaction

With the continuous increase in CO2 emissions, primarily from the combustion of coal and oil, the ecosystem faces a significant threat. Therefore, as an effective method to minimize the issue, the Reverse Water Gas Shift (RWGS) reaction which converts CO2 towards CO attracts much attention, is an environmentally-friendly method to mitigate climate change and lessen dependence on fossil fuels. Nevertheless, the inherent thermodynamic stability and kinetic inertness of CO2 is a big challenge under mild conditions. In addition, it remains another fundamental challenge in RWGS reaction owing to CO selectivity issue caused by CO2 further hydrogenation towards CH4 . Up till now, a series of catalysis systems have been developed for CO2 reduction reaction to produce CO. Herein, the research progress of the well-performed heterogeneous catalysts for the RWGS reaction were summarized, including the catalyst design, catalytic performance and reaction mechanism. This review will provide insights into efficient utilization of CO2 and promote the development of RWGS reaction.

Crystalline-Amorphous Interfaces Engineering of CoO-InOx for Highly Efficient CO2 Electroreduction to CO

As a fundamental product of CO2 conversion through two-electron transfer, CO is used to produce numerous chemicals and fuels with high efficiency, which has broad application prospects. In this work, it has successfully optimized catalytic activity by fabricating an electrocatalyst featuring crystalline-amorphous CoO-InOx interfaces, thereby significantly expediting CO production. The 1.21%CoO-InOx consists of randomly dispersed CoO crystalline particles among amorphous InOx nanoribbons. In contrast to the same-phase structure, the unique CoO-InOx heterostructure provides plentiful reactive crystalline-amorphous interfacial sites. The Faradaic efficiency of CO (FECO ) can reach up to 95.67% with a current density of 61.72 mA cm-2 in a typical H-cell using MeCN containing 0.5 M 1-Butyl-3-methylimidazolium hexafluorophosphate ([Bmim]PF6 ) as the electrolyte. Comprehensive experiments indicate that CoO-InOx interfaces with optimization of charge transfer enhance the double-layer capacitance and CO2 adsorption capacity. Theoretical calculations further reveal that the regulating of the electronic structure at interfacial sites not only optimizes the Gibbs free energy of *COOH intermediate formation but also inhibits HER, resulting in high selectivity toward CO.

Study on CO source identification and spontaneous combustion warning concentration in the return corner of working face in shallow buried coal seam

Coal spontaneous combustion is a common problem faced by many coal mines. Spontaneous combustion in goaf releases a large amount of harmful gases, polluting the environment while causing a large amount of wasted resources, and even endangering the lives of workers. Due to the collapse of the interior of the mining area, it is impossible to measure the internal gas composition directly. In order to more accurately predict the spontaneous combustion state inside the mining airspace, this paper obtains the CO generation law and the main source of the working face through the combination of laboratory experiments and on-site monitoring. The CO concentration prediction model of the return corner is established with CO as the index gas. Finally, the safe concentration and warning concentration of the working face are calculated according to the example, which provides theoretical basis for the prediction of spontaneous combustion of coal.

Exploring Carbon Monoxide and Carbon Dioxide Adsorption on (5,5) Aluminum Nitride Nanotubes for Enhanced Sensor Applications: A DFT Study

This study examined the sensitivity of single-walled (5,5) aluminium nitride nanotubes ((5,5) AlNNTs) to carbon monoxide (CO) and carbon dioxide (CO2) gas molecules by performing DFT calculations using a hybrid functional, specifically, B3LYP (Becke's three-parameter, Lee-Yang-Parr) exchange-correlation functional at a 6-31G* basis set. This research investigates the adsorption behavior of CO2 and CO molecules on pristine and silicon-doped aluminum nitride nanotubes (AlNNTs) and examines their implications for sensor applications. The study assesses each system's adsorption energy, sensing potential, and recovery time to gain insights into their binding strength and practical viability. For CO2 adsorption on (5,5) AlNNT, significant adsorption energy of -24.36 kcal/mol was observed, indicating a strong binding to the nanotube surface, with a sensing potential of 8.95%. However, the slow recovery time of approximately 4.964 days may limit its real-time application. Si-(5,5) AlNNT exhibited a CO2 adsorption energy of -19.69 kcal/mol, a sensing potential of 5.40%, and a relatively short recovery time of approximately 2.978 min, making it a promising candidate for CO2 sensing. CO adsorption on (5,5) AlNNT showed an adsorption energy of -25.20 kcal/mol, a sensing potential of 9.095%, but a longer recovery time of approximately 20.130 days. Si-(5,5) AlNNT displayed a high CO adsorption energy of -20.78 kcal/mol, a sensing potential of 4.29%, and a recovery time of approximately 18.320 min. These findings provide insights into the adsorption characteristics of carbon molecules on AlNNTs, highlighting their potential for CO2 and CO sensing applications.

Electrocatalytic activity of CO2 reduction to CO on cadmium sulfide enhanced by chloride anion doping

The electrocatalytic CO2 reduction (ECR) to produce valuable fuel is a promising process for addressing atmospheric CO2 emissions and energy shortages. In this study, Cl-anion doped cadmium sulfide structures were directly fabricated on a nickel foam surface (Cl/CdS-NF) using an in situ hydrothermal method. The Cl-anion doping could significantly improve ECR activity for CO production in ionic liquid and acetonitrile mixed solution, compared to pristine CdS. The highest Faradaic efficiency of CO is 98.1 % on a Cl/CdS-NF-2 cathode with an excellent current density of 137.0 mA cm-2 at -2.25 V versus ferrocene/ferrocenium (Fc/Fc+ , all potentials are versus Fc/Fc+ in this study). In particular, CO Faradaic efficiencies remained above 80 % in a wide potential range of -2.05 V to -2.45 V and a maximum partial current density (192.6 mA cm-2 ) was achieved at -2.35 V. The Cl/CdS-NF-2, with appropriate Cl anions, displayed abundant active sites and a suitable electronic structure, resulting in outstanding ECR activity. Density functional theory calculations further demonstrated that Cl/CdS is beneficial for increasing the adsorption capacities of *COOH and *H, which can enhance the activity of the ECR toward CO and suppress the hydrogen evolution reaction.

Stabilizing Undercoordinated Zn Active Sites through Confinement in CeO2 Nanotubes for Efficient Electrochemical CO2 Reduction

Zn-based catalysts hold great potential to replace the noble metal-based ones for CO2 reduction reaction (CO2 RR). Undercoordinated Zn (Znδ+ ) sites may serve as the active sites for enhanced CO production by optimizing the binding energy of *COOH intermediates. However, there is relatively less exploration into the dynamic evolution and stability of Znδ+ sites during CO2 reduction process. Herein, we present ZnO, Znδ+ /ZnO and Zn as catalysts by varying the applied reduction potential. Theoretical studies reveal that Znδ+ sites could suppress HER and HCOOH production to induce CO generation. And Znδ+ /ZnO presents the highest CO selectivity (FECO 70.9 % at -1.48 V vs. RHE) compared to Zn and ZnO. Furthermore, we propose a CeO2 nanotube with confinement effect and Ce3+ /Ce4+ redox to stabilize Znδ+ species. The hollow core-shell structure of the Znδ+ /ZnO/CeO2 catalyst enables to extremely expose electrochemically active area while maintaining the Znδ+ sites with long-time stability. Certainly, the target catalyst affords a FECO of 76.9 % at -1.08 V vs. RHE and no significant decay of CO selectivity in excess of 18 h.

Fast and Sensitive Detection of CO by Bi-MOF-Derived Porous In2O3/Fe2O3 Core-Shell Nanotubes

In2O3 is an optimal material for sensitive detection of carbon monoxide (CO) gas due to its low resistivity and high catalytic activity. Yet, the gas response dynamics between the CO gas molecules and the surface of In2O3 is limited by its solid structure, resulting in a weak gas response value and sluggish electron transport. Herein, we report a strategy to synthesize porous In2O3/Fe2O3 core-shell nanotubes derived from In/Fe bimetallic organic frameworks. The fabricated porous In2O3/Fe2O3-4 core-shell nanotubes present outstanding gas sensitivities, including a response value 3.8 times (33.7 to 200 ppm CO at 260 °C) higher than that of monometallic-derived In2O3 (8.7), ultrashort response and recovery times (23/76 s) to 200 ppm CO, low detection limit (1 ppm), promising selectivity, and long-term stability. The enhanced sensing mechanisms are clarified by the combination of experiment and first-principles calculations, showing that the synergetic strategy of higher adsorption energy, increased electrical conductivity, higher electron transfer numbers, and larger specific surface area of porous core-shell structures promotes the surface activity and charge transfer efficiency. The present work paves a way to tune gas-sensing materials with special morphologies for the development of high-performance CO sensors.

pH-Responsive Multifunctional Nanoplatforms with Reactive Oxygen Species-Controlled Release of CO for Enhanced Oncotherapy

Recently, various nanomaterials have drawn increasing attention for enhanced tumor therapy. However, a lack of tumor uptake and insufficient generation of cytotoxic agents have largely limited the antitumor efficacy in vivo. Herein, a multifunctional nanoplatform (IL@CPPor(CO)) was constructed with pH-responsive copper peroxide nanoparticles (CPNP) that are capable of self-supplying H2O2, a radical-sensitive carbonic oxide (CO) donor (Fe3(CO)12), photosensitizer Iridium(III) meso-tetra (N-methyl-4-pyridyl)porphyrin pentachloride (IrPor), and ionic liquid (IL) for enhanced oncotherapy. Under acidic conditions, the CPNP could decompose to release H2O2 and Cu2+. The concomitant generation of H2O2 could efficiently trigger Fe3(CO)12 to release the CO in situ. On the other hand, Cu2+ possesses both glutathione depletion and Fenton-like properties. In addition, IrPor has both peroxidase-like activity and photosensitizer properties to produce reactive oxygen species (ROS) in tumors. The released ROS could trigger the rapid intracellular release of CO. More importantly, released CO and ROS could promote cell apoptosis and improve the therapeutic efficacy. Moreover, due to the pH-dependent ROS generation property, the IL@CPPor(CO) exhibited high tumor accumulation, low toxicity, and good biocompatibility, which enabled effective tumor growth inhibition with minimal side effects in vivo. This work provides a novel multifunctional nanoplatform that combined photodynamic therapy with CDT and CO to improve therapeutic efficacy.

Cd/Cd(OH)2 Nanosheets Enhancing the Electrocatalytic Activity of CO2 Reduction to CO

Electric-driven conversion of carbon dioxide (CO2 ) to carbon monoxide (CO) under mild reaction conditions offers a promising approach to mitigate the greenhouse effect and the energy crisis. Surface engineering is believed to be one of the prospective methods for enhancing the electrocatalytic activity of CO2 reduction. Herein, hydroxyl (OH) groups were successfully introduced to cadmium nanosheets to form cadmium and cadmium hydroxide nanocomposites (i. e. Cd/Cd(OH)2 nanosheets) via a facile two-step method. The as-prepared Cd/Cd(OH)2 /CP (CP indicates carbon paper) electrode displays excellent electrocatalytic activity for CO2 reduction to produce CO. The Faradaic efficiency of CO reaches 98.3 % and the current density achieves 23.8 mA cm-2 at -2.0 V vs. Ag/Ag+ in a CO2 -saturated 30 wt% 1-butyl-3-methylimidazole hexafluorophosphate ([Bmim]PF6 )-65 wt% acetonitrile (CH3 CN)-5 wt% water (H2 O) electrolyte. And the CO partial current density can reach up to 71.6 mA cm-2 with the CO Faradaic efficiency of more than 85 % at -2.3 V vs. Ag/Ag+ , which stands out against Cd/CP, Cd(OH)2 /CP, and Cd/CdO/CP electrodes. The excellent electrocatalytic performance of the Cd/Cd(OH)2 /CP electrode can be attributed to its unique structural properties, suitable OH groups, perfect interaction with electrolyte, abundant active sites and fast electron transfer rate.

Detection of forest fires and pollutant plume dispersion using IoT air quality sensors

The widespread adoption of Internet of Things (IoT) sensors has revolutionized our understanding of the formation and mitigation of air pollution, significantly improving the accuracy of predictions related to air quality and emission sources. This study demonstrates the use of IoT air quality sensors to detect forest fire incidents by focusing on an area affected by forest fires in Tak Province, Thailand, from January to May 2021. We employed PM2.5 and carbon monoxide measurements from IoT sensors for forest fire detection and utilized the number of hotspots reported through satellite and human observations to identify forest fire incidents. Our data analysis revealed three distinct periods with forest fires and three periods without fires (non-forest fires). For model training, two forest fire and non-forest fire periods were selected and the remaining periods were set aside for validation. J48, a computer algorithm that helps make decisions by organizing information into a tree-like structure based on key characteristics, was used to construct the decision-tree model. Our model achieved an accuracy rate of 72% when classifying forest fire incidents using the training data and a solid accuracy of 69% on the validation data. In addition, we investigated the dispersion of PM2.5 plumes using a regression model. Notably, our findings highlighted the robust explanatory power of the lag time in PM2.5, for predicting PM2.5, in the next 15 min. Our analysis highlights the potential of IoT-based air quality sensors to enhance forest fire detection and predict pollution plume dispersion once fires are detected.

Recent Advances in the Reverse Water-Gas Conversion Reaction

The increase in carbon dioxide emissions has significantly impacted human society and the global environment. As carbon dioxide is the most abundant and cheap C1 resource, the conversion and utilization of carbon dioxide have received extensive attention from researchers. Among the many carbon dioxide conversion and utilization methods, the reverse water-gas conversion (RWGS) reaction is considered one of the most effective. This review discusses the research progress made in RWGS with various heterogeneous metal catalyst types, covering topics such as catalyst performance, thermodynamic analysis, kinetics and reaction mechanisms, and catalyst design and preparation, and suggests future research on RWGS heterogeneous catalysts.

Carbon monoxide intoxication with a CO-Hb of 30% while smoking waterpipe: a case report

Carbon monoxide (CO) poisoning is a significant public health issue and a considerable economic burden in developed countries. While the majority of non-fire-related CO poisonings are attributed to gas heating, there are several other less recognized sources that should be considered in the initial differential diagnosis.The patient in this case was a 21-year-old who experienced a brief episode of loss of consciousness and was subsequently admitted to the Emergency department. Upon evaluation, the patient was diagnosed with CO poisoning, which necessitated hyperbaric oxygen therapy to mitigate the effects of this toxic exposure.Despite exhibiting harmful symptoms initially, the patient stated in a phone interview two and a half years post-incident that they have not experienced any enduring effects such as cardiac arrhythmia or concentration deficits. While their understanding of the risks associated with waterpipe smoking has increased, it has not influenced any major changes in their waterpipe smoking habits.

Heme oxygenase-1: The roles of both good and evil in neurodegenerative diseases

Heme oxygenase-1 (HO-1) is the only way for cells to decompose heme. It can cleave heme to produce carbon monoxide (CO), ferrous iron (Fe2+ ), and biliverdin (BV). BV is reduced to bilirubin (BR) by biliverdin reductase(BVR). In previous studies, HO-1 was considered to have protective effects because of its anti-inflammatory, anti-apoptosis, and antiproliferation functions. However, emerging experimental studies have found that the metabolites derived from HO-1 can cause increase iin intracellular oxidative stress, mitochondrial damage, iron death, and autophagy. Because of its particularity, it is very meaningful to understand its exact mechanism. In this review, we summarized the protective and toxic effects of HO-1, its potential mechanism, its role in neurodegenerative diseases and related drug research. This knowledge may be beneficial to the development of new therapies for neurodegenerative diseases and is crucial to the development of new therapeutic strategies and biomarkers.

Classification and concentration estimation of CO and NO2 mixtures under humidity using neural network-assisted pattern recognition analysis

This study addresses the concerns regarding the cross-sensitivity of metal oxide sensors by building an array of sensors and subsequently utilizing machine earning techniques to analyze the data from the sensor arrays. Sensors were built using In2O3, Au-ZnO, Au-SnO2, and Pt-SnO2 and they were operated simultaneously in the presence of 25 different concentrations of nitrogen dioxide (NO2), carbon monoxide (CO), and their mixtures. To investigate the effects of humidity, experiments were conducted to detect 13 distinct CO and NO2 gas combinations in atmospheres with 40% and 90% relative humidity. Principal component analysis was performed for the normalized resistance variation collected for a particular gas atmosphere over a certain period, and the results were used to train deep neural network-based models. The dynamic curves produced by the sensor array were treated as pixelated images and a convolutional neural network was adopted for classification. An accuracy of 100% was achieved using both models during cross-validation and testing. The results indicate that this novel approach can eliminate the time-consuming feature extraction process.

Role of air pollutants in dengue fever incidence: evidence from two southern cities in Taiwan

Air pollution may be involved in spreading dengue fever (DF) besides rainfalls and warmer temperatures. While particulate matter (PM), especially those with diameter of 10 μm (PM10) or 2.5 μm or less (PM25), and NO2 increase the risk of coronavirus 2 infection, their roles in triggering DF remain unclear. We explored if air pollution factors predict DF incidence in addition to the classic climate factors. Public databases and DF records of two southern cities in Taiwan were used in regression analyses. Month order, PM10 minimum, PM2.5 minimum, and precipitation days were retained in the enter mode model, and SO2 minimum, O3 maximum, and CO minimum were retained in the stepwise forward mode model in addition to month order, PM10 minimum, PM2.5 minimum, and precipitation days. While PM2.5 minimum showed a negative contribution to the monthly DF incidence, other variables showed the opposite effects. The sustain of month order, PM10 minimum, PM2.5 minimum, and precipitation days in both regression models confirms the role of classic climate factors and illustrates a potential biological role of the air pollutants in the life cycle of mosquito vectors and dengue virus and possibly human immune status. Future DF prevention should concern the contribution of air pollution besides the classic climate factors.

Structure transformation from Sierpiński triangles to chains assisted by gas molecules

Reversible transformations between fractals and periodic structures are of fundamental importance for understanding the formation mechanism of fractals. Currently, it is still a challenge to controllably achieve such a transformation. We investigate the effect of CO and CO2 molecules on Sierpiński triangles (STs) assembled from Fe atoms and 4,4″-dicyano-1,1':3',1″-terphenyl (C3PC) molecules on Au surfaces. Using scanning tunneling microscopy, we discover that the gas molecules induce a transition from STs into 1D chains. Based on density functional theory modeling, we propose that the atomistic mechanism involves the transformation of a stable 3-fold coordination Fe(C3PC)3 motif to Fe(C3PC)4 with an axially bonded CO molecule. CO2 causes the structural transformation through a molecular catassembly process.

Molecular Cues for Phenological Events in the Flowering Cycle in Avocado

Reproductively mature horticultural trees undergo an annual flowering cycle that repeats each year of their reproductive life. This annual flowering cycle is critical for horticultural tree productivity. However, the molecular events underlying the regulation of flowering in tropical tree crops such as avocado are not fully understood or documented. In this study, we investigated the potential molecular cues regulating the yearly flowering cycle in avocado for two consecutive crop cycles. Homologues of flowering-related genes were identified and assessed for their expression profiles in various tissues throughout the year. Avocado homologues of known floral genes FT, AP1, LFY, FUL, SPL9, CO and SEP2/AGL4 were upregulated at the typical time of floral induction for avocado trees growing in Queensland, Australia. We suggest these are potential candidate markers for floral initiation in these crops. In addition, DAM and DRM1, which are associated with endodormancy, were downregulated at the time of floral bud break. In this study, a positive correlation between CO activation and FT in avocado leaves to regulate flowering was not seen. Furthermore, the SOC1-SPL4 model described in annual plants appears to be conserved in avocado. Lastly, no correlation of juvenility-related miRNAs miR156, miR172 with any phenological event was observed.

Highly Efficient and Selective Visible-light Photocatalytic CO2 Reduction to CO Using a 2D Co(II)-Imidazole MOF as Cocatalyst and Ru(bpy)3Cl2 as Photosensitizer

The first application of an imidazole MOF, the 2D Co(II)- imidazole framework, {[Co(TIB)2(H2O)4]SO4} (TIB stands for 1,3,5-tris(1-imidazolyl) benzene) (CoTIB) in photocatalytic CO2 reduction was carried out, and compared with that of ZIF-67. The CO2/CoTIB (5.0 mg)/Ru(bpy)3Cl2 (bpy = 2,2'-bipyridine) (11.3 mg)/CH3CN (40 mL)/TEOA (10 mL)/H2O (400 μL) system produced 0.195 mmol of CO in 9 h, corresponding to the efficiency of 9.4 mmol g-1 h-1 (TOF: 7.3 h-1) with a > 99% selectivity. Its catalytic activity is even higher than that of ZIF-67 based on TOF values. However, CoTIB is non-porous and has a very poor CO2 adsorption capacity and poor conductivity. Extensive photocatalytic experiments and energy-level diagrams suggest that the reduction did not depend on the CO2 adsorption by the cocatalyst, but can occur by the direct electron transfer from conduction-band maximum (CBM) of the cocatalytst to the zwitterionic alkylcarbonate adduct formed by the reaction of TEOA and CO2. In addition, the process utilizes the short-lived singlet state (1MLCT), not the long-lived triplet state (3MLCT) of Ru(bpy)3Cl2 to transfer electrons to the CBM of CoTIB. We found that the efficiency of a cocatalyst, a photosensitizer, or a photocatalytic system depends on the matching of all related energy levels.

Diffuse reflectance infrared spectroscopy of adsorbates in liquid phase

Infrared spectroscopy is widely used to analyse the surface of solid materials central to modern chemical processes. For liquid phase experiments, the attenuated total reflection mode (ATR-IR) requires the use of waveguides that can limit a broader applicability of the technique for catalysis studies. Here, we demonstrate that high quality spectra of the solid-liquid interface can be collected in diffuse reflectance mode (DRIFTS) thus opening future applications of infrared spectroscopy.

Considerably Increased Dynamics of CO-Water Complexes over CO and Water Alone

Solvents are increasingly known to influence chemical reactivity. However, the microscopic origin of solvent effects is scarcely understood, particularly at the individual molecule level. To shed light on this, we explored a well-defined model system of water (D₂O) and carbon monoxide on a single-crystal copper surface with time-lapsed low-temperature scanning tunneling microscopy (STM) and ab initio calculations. Through detailed measurements on a time scale of minutes to hours at the limit of single-molecule solvation, we find that at cryogenic temperatures CO-D₂O complexes are more mobile than individual CO or water molecules. We also obtain detailed mechanistic insights into the motion of the complex. In diffusion-limited surface reactions, such a solvent-triggered increase in mobility would substantially increase the reaction yield.

Spatial variability of trace gases (NO2, O3 and CO) over Indian region during 2020 and 2021 COVID-19 lockdowns

COVID-19 lockdown has given us an opportunity to investigate the pollutant concentrations in response to the restricted anthropogenic activities. The atmospheric concentration levels of nitrogen dioxide (NO₂), carbon monoxide (CO) and ozone (O₃) have been analysed for the periods during the first wave of COVID-19 lockdown in 2020 (25th March-31st May 2020) and during the partial lockdowns due to second wave in 2021 (25th March-15th June 2021) across India. The trace gas measurements from Ozone Monitoring Instrument (OMI) and Atmosphere InfraRed Sounder (AIRS) satellites have been used. An overall decrease in the concentration of O₃ (5-10%) and NO₂ (20-40%) have been observed during the 2020 lockdown when compared with business as usual (BAU) period in 2019, 2018 and 2017. However, the CO concentration increased up to 10-25% especially in the central-west region. O₃ and NO₂ slightly increased or had no change in 2021 lockdown when compared with the BAU period, but CO showed a mixed variation prominently influenced by the biomass burning/forest fire activities. The changes in trace gas levels during 2020 lockdown have been predominantly due to the reduction in the anthropogenic activities, whereas in 2021, the changes have been mostly due to natural factors like meteorology and long-range transport, as the emission levels have been similar to that of BAU. Later phases of 2021 lockdown saw the dominant effect of rainfall events resulting in washout of pollutants. This study reveals that partial or local lockdowns have very less impact on reducing pollution levels on a regional scale as natural factors like atmospheric long-range transport and meteorology play deciding roles on their concentration levels.

Improving Hazardous Gas Detection Behavior with Palladium Decorated SnO2 Nanobelts Networks

Transparent Conductive Oxides (TCOs) have been widely used as sensors for various hazardous gases. Among the most studied TCOs is SnO₂, due to tin being an abundant material in nature, and therefore being accessible for moldable-like nanobelts. Sensors based on SnO₂ nanobelts are generally quantified according to the interaction of the atmosphere with its surface, changing its conductance. The present study reports on the fabrication of a nanobelt-based SnO₂ gas sensor, in which electrical contacts to nanobelts are self-assembled, and thus the sensors do not need any expensive and complicated fabrication processes. The nanobelts were grown using the vapor-solid-liquid (VLS) growth mechanism with gold as the catalytic site. The electrical contacts were defined using testing probes, thus the device is considered ready after the growth process. The sensorial characteristics of the devices were tested for the detection of CO and CO₂ gases at temperatures from 25 to 75 °C, with and without palladium nanoparticle deposition in a wide concentration range of 40-1360 ppm. The results showed an improvement in the relative response, response time, and recovery, both with increasing temperature and with surface decoration using Pd nanoparticles. These features make this class of sensors important candidates for CO and CO₂ detection for human health.

Inferred vehicular emissions at a near-road site: Impacts of COVID-19 restrictions, traffic patterns, and ambient air temperature

Vehicles are a major source of anthropogenic emissions of carbon monoxide (CO), nitrogen oxides (NO_x), and black carbon (BC). CO and NO_x are known to be harmful to human health and contribute to ozone formation, while BC absorbs solar radiation that contributes to global warming and also has negative impacts on human health and visibility. Travel restrictions implemented during the COVID-19 pandemic provide researchers the opportunity to study the impact of large, on-road traffic reductions on local air quality. Traffic counts collected along Interstate-95, a major eight-lane highway in Maryland (US), reveal a 60% decrease in passenger car totals and an 8.6% (combination-unit) and 21% (single-unit) decrease in truck traffic counts in April 2020 relative to prior Aprils. The decrease in total on-road vehicles led to the near-elimination in stop-and-go traffic and a 14% increase in the mean vehicle speed during April 2020. Ambient near-road (NR) BC, CO, NO_x, and carbon dioxide (CO₂) measurements were used to determine vehicular emission ratios (ΔBC/ΔCO, ΔBC/ΔCO₂, ΔNO_x/ΔCO, ΔNO_x/ΔCO₂, and ΔCO/ΔCO₂), with each ratio defined as the slope value of a linear regression performed on the concentrations of two pollutants within an hour. A decrease of up to a factor of two in ΔBC/ΔCO, ΔBC/ΔCO₂, ΔNO_x/ΔCO₂, and in the fraction of on-road diesel vehicles from weekdays to weekends shows diesel vehicles to be the dominant source of BC and NO_x emissions at this NR site. We estimate up to a 70% reduction in BC emissions in April 2020 compared to earlier years, and attribute much of this to lower diesel BC emissions resulting from improvements in traffic flow and fewer instances of acceleration and braking. Future efforts to reduce vehicular BC emissions should focus on improving traffic flow or turbocharger lag within diesel engines. Inferred BC emissions from the NR site also depend on ambient temperature, with an increase of 54% in ΔBC/ΔCO from -5 to 20 °C during the cold season, similar to previous studies that reported increasing BC emissions with rising temperature. The default setting of MOVES3, the current version of the mobile emission model used by the US EPA, does not adjust hot-running BC emissions for ambient temperature. Future work will focus on improving the accuracy of mobile emissions in air quality modeling by incorporating the effects of temperature and traffic flow in the system used to generate mobile emissions input for commonly used air quality models.

Nicotine Free Herbal Composition for Smoking De-Addiction - A Placebo Controlled, Double Blind, Randomized, Multicentric Clinical Study

Background

Smoking is a major predisposing factor for many health problems including cancers, vascular disorders, etc., To quit smoking is the only solution to prevent them. Various medicinal and non-medicinal methods are used worldwide for the same. The present study evaluates the effect of a nicotine free herbal formulation containing ingredients like Mucuna pruriens, Withania somnifera, Bacopa monnieri, etc., for cessation of smoking and its effects on other health parameters related to smoking.

Materials and Methods

The present study was a placebo controlled, double blind, randomized, and multi-centric clinical study conducted at three clinical sites in India. After ethical approval and informed consent, all participants were given Smotect Tablets or Placebo tablets in a dose of 2 tablets twice daily for 90 days. A total of 103 participants (52 in trial group and 51 in placebo group) completed the study. Evaluation of cessation of smoking was done along with other parameters like measurement of lung capacity, clinical assessment, and laboratory investigations before and after the study.

Results

A significant reduction in smoking as well as in the alveolar Carbon monoxide (p < 0.05) and Carboxyhemoglobin levels (p < 0.05) were observed with the use of Smotect tablets as compared to placebo over a period of 90 days. Significant improvement was also observed in quality of life, energy and stamina levels, and reduction of stress level. Smotect tablets were found to be safe without causing any adverse effects.

Conclusion

Smotect Tablets is an effective and safe remedy for cessation of smoking and reducing other effects related to smoking.

Short-Term Effects of Carbon Monoxide on Morbidity of Chronic Obstructive Pulmonary Disease With Comorbidities in Beijing

The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. Over-dispersed generalized additive model was adopted to quantity the associations between CO and COPD with T2DM or hypertension. Based on principal diagnosis, COPD cases were identified according to the International Classification of Diseases (J44), and a history of T2DM and hypertension was coded as E12 and I10-15, O10-15, P29, respectively. A total of 459,258 COPD cases were recorded from 2014 to 2019. Each interquartile range uptick in CO at lag 03 corresponded to 0.21% (95%CI: 0.08%-0.34%), 0.39% (95%CI: 0.13%-0.65%), 0.29% (95%CI: 0.13%-0.45%) and 0.27% (95%CI: 0.12%-0.43%) increment in admissions for COPD, COPD with T2DM, COPD with hypertension and COPD with both T2DM and hypertension, respectively. The effects of CO on COPD with T2DM (Z = 0.77, P = 0.444), COPD with hypertension (Z = 0.19, P = 0.234) and COPD with T2DM and hypertension (Z = 0.61, P = 0.543) were insignificantly higher than that on COPD. Stratification analysis showed that females were more vulnerable than males except for T2DM group (COPD: Z = 3.49, P < 0.001; COPD with T2DM: Z = 0.176, P = 0.079; COPD with hypertension: Z = 2.48, P = 0.013; COPD with both T2DM and hypertension: Z = 2.44, P = 0.014); No statistically significant difference could be found between age groups (COPD: Z = 1.63, P = 0.104; COPD with T2DM: Z = 0.23, P = 0.821; COPD with hypertension: Z = 0.53, P = 0.595; COPD with both T2DM and hypertension: Z = 0.71, P = 0.476); Higher effects appeared in cold seasons than warm seasons on COPD (Z = 0.320, P < 0.001). This study demonstrated an increased risk of COPD with comorbidities related to CO exposure in Beijing. We further provided important information on lag patterns, susceptible subgroups, and sensitive seasons, as well as the characteristics of the exposure-response curves.

Multi-output machine learning model for regional air pollution forecasting in Ho Chi Minh City, Vietnam

Air pollution concentrations in Ho Chi Minh City (HCMC) have been found to surpass the WHO standard, which has become a very serious problem affecting human health and the ecosystem. Various machine learning algorithms have recently been widely used in air quality forecasting studies to predict possible impacts. Training and constructing several machine learning models for different air pollutants, such as NO₂, SO₂, O₃, and CO forecasts, is a time-consuming process that necessitates additional effort for deployment, maintenance, and monitoring. In this paper, an effort has been made to develop a multi-step multi-output multivariate model (a global model) for air quality forecasting, taking into account various parameters such as meteorological conditions, air quality data from urban traffic, residential, and industrial areas, urban space information, and time component for the prediction of NO₂, SO₂, O₃, CO hourly (1 h to 24 h) concentrations. The global forecasting model can anticipate multiple air pollutant concentrations concurrently, based on past concentrations of covariate characteristics. The datasets on air pollution time series were gathered from six HealthyAir air quality monitoring sites in HCMC between February 2021 and August 2022. Darksky weather provided the hourly concentrations of meteorological conditions for the same period. This is the first model built using real-time air quality data for NO₂, SO₂, CO, and O₃ forecasting in HCM city. To assess the effectiveness of the proposed model, it was evaluated using real data from HealthyAir stations and quantified using Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and correlation indices. The results show that the global air quality forecasting model beats earlier models built for air quality forecasting of each specific pollutant in HCMC.

Mechanisms for Catalytic CO Oxidation on SiAu(n) (n = 1-5) Cluster

Significant progress has been made in understanding the reactivity and catalytic activity of gas-phase and loaded gold clusters for CO oxidation. However, little research has focused on mixed silicon/gold clusters (SiAu_n) for CO oxidation. In the present work, we performed density function theory (DFT) calculations for a SiAu_n (n = 1-5) cluster at the CAM-B3LYP/aug-cc-pVDZ-PP level and investigated the effects on the reactivity and catalytic activity of the SiAu_n cluster for CO oxidation. The calculated results show that the effect is very low for the activation barriers for the formation of OOCO intermediates on SiAu clusters, SiAu₃ clusters, and SiAu₅ clusters in the catalytic oxidation of CO and the activation energy barriers for the formation of OCO intermediates on OSiAu₃, OSiAu₄, and OSiAu₅. Our calculations show that, compared with the conventional small Au cluster, the incorporation of Si enhances the catalytic performance towards CO oxidation.

Boosting Electroreduction of CO2 over Cationic Covalent Organic Frameworks: Hydrogen Bonding Effects of Halogen Ions

We present the first example of charged imidazolium functionalized porphyrin-based covalent organic framework (Co-iBFBim-COF-X) for electrocatalytic CO₂ reduction reaction, where the free anions (e.g., F^- , Cl^- , Br^- , and I^- ) of imidazolium ions nearby the active Co sites can stabilize the key intermediate *COOH and inhibit hydrogen evolution reaction. Thus, Co-iBFBim-COF-X exhibits higher activity than the neutral Co-BFBim-COF, following the trend of F^- <Cl^- <Br^- <I^- . Particularly, the Co-iBFBim-COF-I^- showed nearly 100 % CO₂ selectivity at a low full-cell voltage of 2.3 V, and achieved a high CO₂ partial current density of 52 mA cm^-2 with a turnover frequency of 3018 h^-1 at 2.4 V in the anion membrane electrode assembly, which is 3.57 times larger than that of neutral Co-BFBim-COF. This work provides new insight into the importance of free anions in the stabilization of intermediates and decreasing the local binding energy of H₂ O with active moiety to enhance CO₂ reduction reaction.

Super-Branched PdCu Alloy for Efficiently Converting Carbon Dioxide to Carbon Monoxide

The alloying of noble metals with Cu is one of the most effective strategies for improving catalytic performance and reducing cost in electrocatalytic carbon dioxide reduction reactions (CO₂RR). Previous works usually focused on the influence of morphology and composition on the catalytic activity, but lacked the study of the valence state ratio of metals and the electron transfer behavior on alloys. In this work, PdCu-2 alloy (Pd/Cu molar ratio is 1:2) was obtained by a simple one-step solvothermal method, which can effectively convert CO₂ to CO with a maximum Faradaic efficiency (FE) of 85% at -0.9 V (vs. RHE). Then, the effect of the chemical state of Pd and Cu on the catalytic performance was investigated. The X-ray photoelectron spectroscopy (XPS) shows that the binding energy of Pd in PdCu alloy has a negative shift, which has affected the adsorption of key intermediates. When the proportion of oxidized state and zero-valent metal in the alloy is about 1:2, the PdCu alloy shows the best catalytic activity. In addition, the transient photovoltage (TPV) measurements further demonstrate that due to the introduction of Cu, the electron transfer rate of PdCu-2 becomes the slowest, which helps the accumulation of electrons on PdCu-2 and leads to the improvement of catalytic performance for electrocatalytic CO₂RR. This work can provide more insights into the alloy catalysts of electrocatalytic CO₂RR.

Partially Nitrided Ni Nanoclusters Achieve Energy-Efficient Electrocatalytic CO2 Reduction to CO at Ultralow Overpotential

Electrocatalytic CO₂ reduction reaction (CO₂ RR) offers a promising strategy to lower CO₂ emission while producing value-added chemicals. A great challenge facing CO₂ RR is how to improve energy efficiency by reducing overpotentials. Herein, partially nitrided Ni nanoclusters (NiN_x ) immobilized on N-doped carbon nanotubes (NCNT) for CO₂ RR are reported, which achieves the lowest onset overpotential of 16 mV for CO₂ -to-CO and the highest cathode energy efficiency of 86.9% with CO Faraday efficiency >99.0% to date. Interestingly, NiN_x /NCNT affords a CO generation rate of 43.0 mol g^-1  h^-1 at a low potential of -0.572 V (vs RHE). DFT calculations reveal that the NiN_x nanoclusters favor *COOH formation with lower Gibbs free energy than isolated Ni single-atom, hence lowering CO₂ RR overpotential. As NiN_x /NCNT is applied to a membrane electrode assembly system coupled with oxygen evolution reaction, a cell voltage of only 2.13 V is required to reach 100 mA cm^-2 , with total energy efficiency of 62.2%.

Effect of reduction pretreatments on PdAg/Al2O3 for HCHO and CO oxidation

PdAg/Al₂O₃ were pretreated by CO and H₂ reduction pretreatments, respectively. The reduced catalysts were tested for HCHO and CO oxidation and characterized by Brunner Emmet Teller (BET), X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and oxygen temperature programmed desorption (O₂-TPD). These results indicate that the pretreatments have effect on PdAg reconstruction, PdAg particle size and active oxygen species, which are responsible for the catalytic performance. Compared with H₂ reduction method, CO reduction is more suitable for PdAg/Al₂O₃ pretreatment. PdAg/Al₂O₃-CO exhibited better catalytic performance.

Acetate augmentation boosts the ethanol production rate and specificity by Clostridium ljungdahlii during gas fermentation with pure carbon monoxide

Recycling waste gases from industry is vital for the transition toward a circular economy. The model microbe Clostridium ljungdahlii reduces carbon from syngas and primarily produces acetate and ethanol. Here, a gas fermentation experiment is presented in chemostats with C. ljungdahlii and pure carbon monoxide (CO) as feedstock while entirely omitting yeast extract. A maximum ethanol production rate of 0.07 ± 0.01 g L^-1 h^-1 and a maximum average ethanol/acetate ratio of 1.41 ± 0.39 was observed under steady-state conditions. This confirmed that CO as the sole feedstock pushes the metabolism toward more reduced fermentation products. This effect was even more pronounced when 15 mM sodium acetate was added to the feed medium. An ethanol production rate of 0.23 ± 0.01 g L^-1 h^-1 was achieved, representing an increase of more than 240%. This increase was accompanied by an increase in cell density and selectivity toward ethanol, with a maximum average ethanol/acetate ratio of 92.96 ± 28.39. Oxygen contaminations voided this effect, although the cultures were still able to maintain a stable biomass concentration and ethanol production rate. These findings highlight the potential of CO-fermentation with acetate augmentation and the importance of preventing oxygen contaminations.

BIN2 phosphorylates the Thr280 of CO to restrict its function in promoting Arabidopsis flowering

CONSTANS (CO) is a central regulator of floral initiation in response to photoperiod. In this study, we show that the GSK3 kinase BIN2 physically interacts with CO and the gain-of-function mutant bin2-1 displays late flowering phenotype through down-regulation of FT transcription. Genetic analyses show that BIN2 genetically acts upstream of CO in regulating flowering time. Further, we illustrate that BIN2 phosphorylates the Thr280 residue of CO. Importantly, the BIN2 phosphorylation of Thr280 residue restricts the function of CO in promoting flowering through affecting its DNA-binding activity. Moreover, we reveal that the N-terminal part of CO harboring the B-Box domain mediates the interaction of both CO-CO and BIN2-CO. We find that BIN2 inhibits the formation of CO dimer/oligomer. Taken together, this study reveals that BIN2 regulates flowering time through phosphorylating the Thr280 of CO and inhibiting the CO-CO interaction in Arabidopsis.

Association between air pollution exposure and coronary heart disease hospitalization in a humid sub-tropical region of China: A time-series study

Objective

Emerging evidence has highlighted the possible links of environmental pollution with several cardiovascular diseases (CVDs). The current study aimed to explore the impact of short-term air pollution exposure on CHD hospitalization in Hefei.

Methods

Data about the daily number of CHD admissions (from 2014 to 2021) were retrieved from the First Affiliated Hospital of Anhui Medical University. Air pollutants and meteorological data were obtained from the China Environmental Monitoring Station and the China Meteorological Data Service Center, respectively. The correlation between air pollution and CHD hospitalization was assessed using distributed lag non-linear model (DLNM) and Poisson generalized linear regression.

Results

In the single-pollutant model, NO₂, O₃, and CO strongly correlated with CHD hospitalization rate. Specifically, exposure to NO₂ (lag0, relative risk [RR]: 1.013, 95%CI: 1.002-1.024, per 10 μg/m³ increase) and CO (lag13, RR: 1.035, 95%CI: 1.001-1.071, per 1 μg/m³ increase) revealed a positive correlation with an increased rate of CHD hospitalization. Interestingly, O₃ had a protective association with hospitalization of CHD (lag0, RR: 0.993, 95%CI: 0.988-0.999, per 10 μg/m³ increase). Similar results, to those of the single-pollutant model, were revealed following verification using two-pollutant models. Subgroup analyses indicated that young people, women, and people in hot seasons were more susceptible to NO₂ exposure, while the elderly, women, and people in cold seasons were more susceptible to O₃. Furthermore, the elderly were more susceptible to CO exposure.

Conclusion

Overall, exposure to NO₂ and CO increases the rate of CHD hospitalization, but exposure to O₃ shows a protective association with the rate of CHD hospitalization. Therefore, early preventive measures against air pollutants should be applied to protect vulnerable patients with CHD.

Palladium-Catalyzed Aminocarbonylation of Aryl Halides

Palladium-catalyzed organic reactions are ubiquitous due to their high efficiency in coupling reactions and have wide applications in synthetic chemistry. Their widespread use in organic synthesis has been attributed to moderate conditions associated with reactions and tolerance to different types of functional groups. Palladium-catalysts are extensively used in aminocarbonylation of aryl halides for the synthesis of amides and have found a wide variety of applications in pharmaceuticals, agrochemicals, petrochemicals, materials, polymers, etc. In this review, we summarize the recent advances in the synthesis of amides via palladium-catalyzed aminocarbonylation of aryl halides, and cover literature from 2010 to 2021.

Observations of atmospheric CO2 and CO based on in-situ and ground-based remote sensing measurements at Hefei site, China

The characteristics of long time series of CO₂ and CO surface concentrations, tropospheric and total column dry-air mole fractions (DMF) from May 2015 to December 2019 were investigated. Both CO₂ and CO show different seasonality for the three datasets. The annual increasing trend of CO₂ is similar for all three datasets. However, the annual decreasing trend of CO for surface concentration is high compared to the other two measurements, mainly due to the improved combustion efficiency from power generation in recent years. The correlation between the tropospheric and total atmospheric CO₂ and CO is higher than that between the surface concentration and tropospheric CO₂ and CO. This is because the tropospheric and total atmospheric results both have common vertical profiles for CO₂ and CO respective mole fractions that were observed in troposphere. Furthermore, the enhancement ratios of CO₂ to CO derived from the three datasets during the period from 2016 to 2019 were compared. The ratio of ∆CO₂ to ∆CO has an obvious increase with altitude each year, which means that the combustion efficiencies obtained from the three datasets are different. All ratios for the three datasets showed a slight increasing trend in recent years, which is attributed to increased combustion efficiency due to governmental measures for energy savings and emission reductions.

Electroplating Cobalt Films on Silicon Nanostructures for Sensing Molecules

In this study, we electroplated Co and Cu on nano-spiked silicon substrates that were treated with femtosecond laser irradiations. With energy-dispersive X-ray (EDX) analysis by a scanning electron microscope (SEM), it was found that both Co and Cu are primarily coated on the spike surfaces without changing the morphology of the nanospikes. We also found that nanoscale bridges were formed, connecting the Co-coated silicon spikes. The formation of these bridges was studied and optimized through a series of time-controlled electroplating and oxidizing processes. The bridges are related to the oxidation of Co in the air. When it is irradiated with visible light, this special structure has shown a capability of interactions with carbon monoxide and carbon dioxide molecules. The electroplated cobalt may be used for gas sensors.

Evaluation of the CAMS reanalysis for atmospheric black carbon and carbon monoxide over the north China plain

Black carbon (BC) and carbon monoxide (CO) at different model levels from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis were comprehensively evaluated against observations performed simultaneously on both surface and mountain sites in winter and summer in the North China Plain for the first time. CAMS could capture the seasonal difference in BC and CO emission on both sites but showed significant and persistent biases. Biases were high on the surface site and low on the mountain site for both seasons, implying the uncertainties in emission inventories used in the CAMS reanalysis which may have more influence near source. Biases were reduced and the correlation coefficient of CAMS BC with observed BC increased when two datasets were compared on a daily basis, which suggests daily or longer time averaged CAMS BC could be more suitable for trend analysis. Although CAMS could generally reproduce the distinct diurnal variation of BC and CO on both sites, the inaccurate representation of the daily evolution of planetary boundary layer (PBL) in model may bring more uncertainties to the concentration biases on surface from midnight to early morning. BC hydrophilic ratio from CAMS displayed large biases compared to observations with no seasonal difference on both sites, which was probably resulted from the initial emission state of BC hygroscopicity for all source types in model. Uncertainties in the removal processes and the simplified aging processes in model could further induce uncertainty in modelling BC hydrophilic ratio in the CAMS. These results could not only be referenced for the improvement on CAMS reanalysis but also facilitate model or trend analysis of BC and CO pollution by utilizing the CAMS reanalysis product from both short- and long-term perspectives, which will be beneficial to both the mitigation and policy-making on primary emissions in China.

Adsorption and Gas-Sensing Properties of Agn (n = 1-4) Cluster Doped GeSe for CH4 and CO Gases in Oil-Immersed Transformer

The adsorption mechanism of CO and CH₄ on GeSe, modified with the most stable 1-4 Ag-atom clusters, is studied with the help of density functional theory. Adsorption distance, adsorption energy, total density of states (TDOS), projected density of states (PDOS), and molecular orbital theory were all used to analyze the results. CO was found to chemisorb exothermically on GeSe, independent of Ag cluster size, with Ag₄-GeSe representing the optimum choice for CO gas sensors. CH₄, in contrast, was found to chemisorb on Ag-GeSe and Ag₂-GeSe and to physisorb on Ag₃-GeSe and Ag₄-GeSe. Here, Ag GeSe was found to be the optimum choice for CH₄ gas sensors. Overall, our calculations suggest that GeSe modified by Ag clusters of different sizes could be used to advantage to detect CO and CH₄ gas in ambient air.

The migration of CO and PM under different working conditions of trackless rubber-tyred vehicle and health risk assessment of underground personnel

Trackless rubber-tyred vehicles are among the most widely used underground auxiliary transportation equipment in major coal mines at present. The migration of exhaust gas that threaten human health varies with the working conditions of trackless rubber-tyred vehicles. In order to better evaluate the health risks faced by underground personnel in the process of exhaust emission from underground diesel vehicles, in this paper, the migration of carbon monoxide (CO) and particulate matter (PM) emitted by trackless rubber-tyred vehicle under three working conditions was analyzed by using the method of CFD (Computational Fluid Dynamics) numerical simulation and field measurement. It can be concluded that the concentrations of CO and PM changed with the change of airflow field under different working conditions, and their distribution tended to be consistent on the whole. Although the migration of CO and PM were different under different working conditions, CO with high concentration (C ≥ 44.74 ppm) and PM with high concentration (C ≥ 89.47 mg/m³) were mainly distributed in the area near the exhaust pipe of trackless rubber-tyred vehicle. Therefore, the drivers of trackless rubber-tyred vehicle and underground personnel need to comprehensively consider the risk factors under different working conditions when carrying out personal protection.

Health effects of exposure to sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide between 1980 and 2019: A systematic review and meta-analysis

The burden of disease attributed to the indoor exposure to sulfur dioxide (SO₂ ), nitrogen dioxide (NO₂ ), ozone (O₃ ), and carbon monoxide (CO) is not clear, and the quantitative concentration-response relationship is a prerequisite. This is a systematic review to summarize the quantitative concentration-response relationships by screening and analyzing the polled effects of population-based epidemiological studies. After collecting literature published between 1980 and 2019, a total of 19 health outcomes in 101 studies with 182 health risk estimates were recruited. By meta-analysis, the leave-one-out sensitivity analysis and Egger's test for publication bias, the robust and reliable effects were found for SO₂ (per 10 μg/m³ ) with chronic obstructive pulmonary diseases (COPD) (pooled relative risks [RRs] 1.016, 95% CI: 1.012-1.021) and cardiovascular diseases (CVD) (RR 1.012, 95%CI: 007-1.018), respectively. NO₂ (per 10 μg/m³ ) had the pooled RRs for childhood asthma, preterm birth, lung cancer, diabetes, and COPD by 1.134 (1.084-1.186), 1.079 (1.007-1.157), 1.055 (1.010-1.101), 1.019 (1.009-1.029), and 1.016 (1.012-1.120), respectively. CO (per 1 mg/m³ ) was significantly associated with Parkinson's disease (RR 1.574, 95% CI: 1.069-2.317) and CVD (RR 1.024, 95% CI: 1.011-1.038). No robust effects were observed for O₃ . This study provided evidence and basis for further estimation of the health burden attributable to the four gaseous pollutants.

VUV-VIS FT spectroscopy of the rare 13C18O isotopologue of carbon monoxide: Analysis of the A1Π(v = 1) multiply-perturbed level

Ro-vibronic spectra of the ¹³C¹⁸O carbon monoxide isotopologue were obtained with (i) emission spectroscopy in the visible region using a Bruker IFS 125HR spectrometer (University of Rzeszów) and (ii) vacuum-ultraviolet absorption spectroscopy using the wave-front-division spectrometer on the DESIRS beamline of the SOLEIL synchrotron. A deperturbation analysis of the ¹³C¹⁸O A¹Π(v = 1) level was conducted from 598 observed transitions from the B¹Σ⁺ - A¹Π(0, 1), C¹Σ⁺ - A¹Π(0, 1), A¹Π - X¹Σ⁺(1, 0), B¹Σ⁺ - X¹Σ⁺(0, 0), C¹Σ⁺ - X¹Σ⁺(0, 0), I¹Σ^- - X¹Σ⁺(2, 0) bands and five further nominally forbidden bands. An effective Hamiltonian and term-value fitting analysis was implemented. Consequently, 135 parameters were floated: 23 molecular parameters, including molecular constants for A¹Π(v = 1), I¹Σ^-(v = 2), d³Δ(v = 6), e³Σ^-(v = 3) and D¹Δ(v = 1); rotation-electronic (L-uncoupling) mixing of A¹Π(v = 1) ∼ [D¹Δ(v = 1), I¹Σ^-(v = 1), I¹Σ^-(v = 2)] and spin-orbit interaction parameters for A¹Π(v = 1) ∼ [d³Δ(v = 6), e³Σ^-(v = 3), a'³Σ⁺(v = 11)]; the spin-orbit/spin-electronic/L-uncoupling a³Π(v = 12) ∼ d³Δ(v = 5) and spin-orbit a³Π(v = 12) ∼ [D¹Δ(v = 1), I¹Σ^-(v = 2)] perturbation parameters; as well as 112 ro-vibronic term values of B¹Σ⁺(v = 0) up to J = 50 and C¹Σ⁺(v = 0) up to J = 60. The significant, indirect a³Π(v = 12) ∼ [e³Σ^-(v = 2, 3), d³Δ(v = 5, 6)] ∼ A¹Π(v = 1) spin-orbit/spin-electronic/L-uncoupling interaction and a³Π(v = 12) ∼ [I¹Σ^-(v = 2), D¹Δ(v = 1)] ∼ A¹Π(v = 1) spin-orbit/L-uncoupling interaction were detected and analysed. Thus, this study, using modern experimental methods and deperturbation analysis, leads to a much improved description in terms of molecular constants and interaction parameters, compared to previous studies of the A¹Π(v = 1) energy region in the ¹³C¹⁸O isotopologue. This research is a continuation of the studies on the A¹Π state and its numerous perturbers in the CO isotopologues made by our team.

On reducing the emissions of CO, HC, and NOx from gasoline blended with hydrogen peroxide and ethanol: Optimization study aided with ANN-PSO

The use of ethanol blending for gasoline has been found to have a significant effect in reducing emissions without any loss in the performance of a spark ignition engine. However, an increase in the emissions of oxides of nitrogen (NO_x) may be seen due to the increased oxygen content in the fuel. On the contrary, emulsifying fuel with hydrogen peroxide (H₂O₂) has shown a substantial effect in reducing all the emissions, including NO_x in a compression ignition (CI) engine. In this study, 10% ethanol is blended with gasoline (E10) and further emulsified with H₂O₂ up to 1.5%. When compared to neat gasoline, a 4.8% increase in brake thermal efficiency (BTE) is obtained with 10% ethanol and 1.5% H₂O₂. The corresponding average decrease in the emissions of carbon monoxide (CO), hydrocarbons (HC), and NO_x were 80%, 43%, and 17%, respectively. The results of the experimental trials are used to model an artificial neural network (ANN) to derive a relationship between the input factors of ethanol concentration, H₂O₂ concentration, and engine speeds with the output responses of BTE, CO, HC, and NO_x. The ANN models of each response are optimized using a multi-objective particle swarm optimization (PSO) for maximizing BTE and minimizing emissions of CO, HC, and NO_x. The PSO results showed that operating the engine at 2000 rpm using ethanol blending between 4 and 6% and H₂O₂ emulsification of 1.5% are the best optimal conditions.

Evaluation of Effect of Zirconia Surface Treatment with CO2 and Nd:YAG Lasers on Shear Bond Strength between Zirconia Frameworks and Porcelain Veneers

AIM

The purpose of this study was to evaluate the effect of zirconia surface treatment with CO2 and Nd:YAG laser on shear bond strength (SBS) between the zirconia framework and porcelain veneering.

MATERIALS AND METHODS

In this in vitro study, zirconia blocks were converted to 50 cubes and were divided randomly into 5 groups. After sintering (S), porcelain was applied in the control group. The surface treatment of the second to fifth groups included CO2 laser + (S), (S + CO2), Nd:YAG laser + (S), and (S + Nd), respectively. The SBS test was done, and data were analyzed by SPSS16 software. One sample was randomly chosen from each group and the type of failure was examined under scanning electron microscope (SEM). To compare the pairs of means, the least significant difference test was used and the determined significance level was 5% (p < 0.05).

RESULTS

The SBS of S + Nd group was significantly higher than the other ones, except for S + CO2 group. The least amount of SBS belonged to CO2 + S and the highest to S + Nd group. There were no significant differences between the other groups.

CONCLUSION

The bond strength of veneering porcelain to zirconia can be altered by surface treatments. It can also be affected by the type and sequence of laser and sintering application. The effect of Nd:YAG laser on the surface of zirconia, in order to create roughness to increase SBS, is better than that of CO2 laser.

CLINICAL SIGNIFICANCE

Surface treatment of zirconia by certain types of lasers reduces the chipping of the ceramic veneer and increases the success rate of all-ceramic restorations.

Ambient gaseous pollutant exposure and incidence of visual impairment among children and adolescents: findings from a longitudinal, two-center cohort study in China

Evidence on the effects of exposure to ambient gaseous pollutants on children's vision was consistently scarce. We aimed to explore the effect of ambient gaseous pollutant exposure on the incidence of visual impairment (VI) in children. From 2005 to 2018, a total of 340,313 children without VI participated in a longitudinal and two-center dynamic cohort. The logMAR acuity was used to assess visual function. The space-time extremely randomized trees model was used to estimate SO₂ and CO exposures levels. The association between SO₂ and CO and VI risks among children was assessed using a proportional hazards model with a restricted cubic spline. Subgroup analyses stratified by gender and grades were used to investigate the differences in an association of SO₂ and CO exposures with childhood VI. A total of 158381 (46.54%) children experienced an new incident VI. A ten-unit (10 μg/m³) increase in SO₂ exposure concentrations was significantly associated with a 1.70 times higher risk of childhood VI. In addition, a 0.1-unit (0.1 mg/m³) increase in CO exposure was significantly associated with a 1.22 times higher risk of childhood VI. The positive association between ambient gaseous pollutants (including SO₂ and CO exposures) and childhood VI risks remained even after adjusting for other environmental variables. An increase in the incidence of VI in children was positively linked to SO₂ and CO exposure. Such evidence might aid governments in developing strategies to interfere with children's eyesight by decreasing air pollution and changing school curricula.

Advanced Biofuels from ABE (Acetone/Butanol/Ethanol) and Vegetable Oils (Castor or Sunflower Oil) for Using in Triple Blends with Diesel: Evaluation on a Diesel Engine

From a technical and economic point of view, our aim is to provide viable solutions for the replacement of fossil fuels which are currently used in internal combustion diesel engines. In this research, two new biofuels composed of second-generation vegetable oils (SVO),used oil sunflower (SO) or castor oil (CO), and the ABE blend (acetone/butanol/ethanol) were evaluated. ABE is an intermediate product from the fermentation of carbohydrates to obtain bio-butanol. Besides, the ABE blend exhibits suitable properties as biofuel, such asvery low kinematic viscosity, reasonable energy density, low autoignition temperature, and broad flammability limits. Diesel/ABE/SVO triple blends were prepared, characterized and then, tested on a diesel engine, evaluating power output, consumption, and exhaust emissions. The power output was slightly reduced due to the low heating values of ABE blend. Also, engine consumed more fuel with the triple blends than with diesel under low engine loads whereas, at medium and high loads, the fuel consumption was very similar to that of diesel. Regarding exhaust gas emissions, soot wasnotably reduced, and nitrogen oxides (NO_x) and carbon monoxide (CO₂) emissions were lower or comparable to that of diesel, while the CO emissions increased. The use of these biofuels allows the replacement of high percentagesof diesel without compromising engine power and achievinga significant reduction in pollution emissions. Furthermore, a notable improvement in cold flow properties of the fuel blends is obtained, in comparison with diesel.