Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation

The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by∼10% because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions and even led to substantial increases in O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over the NCP, which contributed 90 % of the PM2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM2.5 emissions, were the main drivers of the unexpected PM2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.

The stock market and NO2 emissions effects of COVID‐19 around the world

In this paper, we study the impact of the coronavirus disease 2019 pandemic in estimated panel vector autoregression models for 92 countries. The large cross‐section of countries allows us to shed light on the heterogeneity of the responses of stock markets and nitrogen dioxide emissions as high‐frequency measures of economic activity. We quantify the effect of the number of infections and four dimensions of policy measures: (1) containment and closure, (2) movement restrictions, (3) economic support, and (4) adjustments of health systems. Our main findings show that a surprise increase in the number of infections triggers a drop in our two measures of economic activity. Propping up economic support measures, in contrast, raises stock returns and emissions and, thus, contributes to the economic recovery. We also document vast differences in the responses across subsets of countries and between the first and the second wave of infections.

Gastrointestinal symptoms and disorders related to COVID-19. Lessons learned from gastroenterologists

COVID-19 is mainly a respiratory illness caused by the SARS-CoV-2 but can also lead to GI symptoms. The primary host receptor which mediates the mechanism as SARS-CoV-2 enters the cell is the ACE2 receptor. Therefore, GI symptoms can be common in COVID-19, and in some cases, they are the first manifestation even before fever and respiratory symptoms. In addition, the liver function tests alteration often is related to a worse prognosis. The exact incidence of GI symptoms is a matter of debate. Moreover, wide variation concerning GI symptoms frequency exists, but the predominant ones seem to be diarrhea, anorexia, nausea, vomiting, and abdominal pain or discomfort.This review summarizes the most relevant findings of COVID-19 on the digestive system, including the liver, biliary tract, pancreas, the most common GI symptoms, and the atypical clinical GI manifestations.Copyright © 2022 Sociedad Medica del Hospital General de Mexico. Published by Permanyer.

"Fortune amidst misfortune”: The impact of Covid-19 city lockdowns on air quality

Air pollution is one of the major causes of health risks as it leads to widespread disease and death each year. Countries have invested heavily in fighting air pollution, arguably without convincing results. The outbreak of the highly infectious disease COVID-19 in December 2019 has been declared a pandemic and a worldwide health crisis by World Health Organization (WHO). Countries resorted to city lockdowns that sternly curtailed personal mobility and economic activities to control the spread of this deadly coronavirus disease. This paper examines the impact of Covid-19 city lockdowns on air quality. The researchers adopted a comprehensive interpretative document analysis for this study, which guided the careful but rigorous examination of air quality and coronavirus data. This method affirmed the authenticity of the information examined and interpreted in the US, Italy and China, the study areas. The study found that Covid-19 city lockdowns have contributed to a significant improvement in air quality within the first four months of the outbreak of Covid-19. National Aeronautics and Space Administration (NASA) had reported that NO2 concentrations in the study areas had reduced significantly using evidence from their Sentinel-5P instrument. Air quality in Covid-19 cities' lockdowns also improved because of the enforcement of other types of measures enacted to battle the virus. WHO still believes that the amount of NO2 concentration in the atmosphere is still high per their standards and regulations. Based on this, the researchers recommend that governments and other stakeholders put in much effort in terms of legislation to "win the war” against air pollution.

Analyses of kidney biomarkers in patients with sars-cov-2 (Covid-19)

The new coronavirus was first reported in China and caused a widespread global outbreak of pneumonia that spread rapidly across this country and many other countries. Acute kidney injury is one of the important complications of COVID-19, which has been shown in some cases. Exploring the diagnostic features of biomarkers of kidney function in COVID-19 patients may lead to better patient management. We collected laboratory data from 206 people with confirmed COVID-19 disease and evaluated their renal biomarkers, Blood Urea Nitrogen (BUN), and creatinine. The age range of the patients was almost 62 years old. The mean age in the dead patients and recovered patients was 71 and 54 years old, respectively. The average LDH value was 755 U/L, and creatine phosphokinase (CPK) was 267 U/L in the patients. The average BUN was 59.1 U/L, and creatinine was 1.5 U/L in COVID-2019 patients. Among all 193 patients, laboratory results revealed that 163 (85.4%) patients had an elevated BUN level. Based on creatinine levels for total patients, laboratory results revealed that 49 (25.4%) patients had an elevated value. The average BUN value in dead patients was 85 mg/dL, while in recovered patients was 40.5 mg/dL (P<0.0001). Also, the average creatinine level in dead patients was 1.86 mg/dL, while in recovered patients was 1.24 mg/dL (P=0.0004). Inflammation following COVID-19 disease causes kidney damage and elevated urea and creatinine levels, which may increase the risk of death in these patients.Copyright © 2023 Tehran University of Medical Sciences.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models.

BACKGROUND: A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE: We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS: Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS: The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 µg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 µg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 µg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION: In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.

The Impact of Serum Levels of Reactive Oxygen and Nitrogen Species on the Disease Severity of COVID-19.

Elucidation of the redox pathways in severe coronavirus disease 2019 (COVID-19) might aid in the treatment and management of the disease. However, the roles of individual reactive oxygen species (ROS) and individual reactive nitrogen species (RNS) in COVID-19 severity have not been studied to date. The main objective of this research was to assess the levels of individual ROS and RNS in the sera of COVID-19 patients. The roles of individual ROS and RNS in COVID-19 severity and their usefulness as potential disease severity biomarkers were also clarified for the first time. The current case-control study enrolled 110 COVID-19-positive patients and 50 healthy controls of both genders. The serum levels of three individual RNS (nitric oxide (NO•), nitrogen dioxide (ONO-), and peroxynitrite (ONOO-)) and four ROS (superoxide anion (O2•-), hydroxyl radical (•OH), singlet oxygen (1O2), and hydrogen peroxide (H2O2)) were measured. All subjects underwent thorough clinical and routine laboratory evaluations. The main biochemical markers for disease severity were measured and correlated with the ROS and RNS levels, and they included tumor necrosis factor-alpha (TNF-alpha), interleukin-6 (IL-6), the neutrophil-to-lymphocyte ratio (NLR), and angiotensin-converting enzyme 2 (ACE2). The results indicated that the serum levels of individual ROS and RNS were significantly higher in COVID-19 patients than in healthy subjects. The correlations between the serum levels of ROS and RNS and the biochemical markers ranged from moderate to very strongly positive. Moreover, significantly elevated serum levels of ROS and RNS were observed in intensive care unit (ICU) patients compared with non-ICU patients. Thus, ROS and RNS concentrations in serum can be used as biomarkers to track the prognosis of COVID-19. This investigation demonstrated that oxidative and nitrative stress play a role in the etiology of COVID-19 and contribute to disease severity; thus, ROS and RNS are probable innovative targets in COVID-19 therapeutics.

Changes in Tropospheric Nitrogen Dioxide Vertical Column Densities over Japan and Korea during the COVID-19 Using Pandora and MAX-DOAS

We investigated the impact of human activity during COVID-19 on the tropospheric nitrogen dioxide vertical column density (NO2 TropVCD) at three urban sites (Gwangju and Busan in Korea and Yokosuka in Japan) and one remote site (Cape Hedo in Japan) from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) and Pandora. Compared to the monthly mean NO2 TropVCD from 2015 to 2018 and in 2019, the values were lower in 2020 due to social distancing in Korea and Japan. High negative relative changes were observed from May to September (-30% to -18%) at the three urban sites;Cape Hedo, a remote site, did not show a significant difference in relative changes between previous years and 2020, suggesting that only anthropogenic emission sources decreased dramatically. In the case of Yokosuka, the 15-day moving average of the NO2 TropVCD exhibited a good relationship with transportation (R = 0.48) and industry (R = 0.54) mobility data. In contrast, the NO2 TropVCD at the Korean sites showed a moderate to low correlation with the industrial sector and insignificant correlations with transportation. The differences in correlations might be caused by the different social distancing policies in Korea (voluntary) and Japan (mandatory). By applying generalized boosted models to exclude meteorological and seasonal effects associated with NO2 TropVCD variations, we revealed that the decreasing trend from 2019 to 2020 was much steeper than that from 2015 to 2020 (a factor of two), and a significant change was identified in January 2020, when the first cases of COVID-19 were observed in both Korea and Japan. This result confirmed that the reduction in NO2 can be largely explained by the NOx emission reduction resulting from social distancing for COVID-19 rather than annual meteorological differences;however, in December 2020, NO2 recovered suddenly to its previous level due to an increase in human activities.

Air quality changes in Shijiazhuang during COVID-19 outbreak

[Background] The coronavirus disease 2019 (COVID-19) was first detected in December 2019. To combat the disease, a series of strict measures were adopted across the country, which led of improved air quality. This provides an opportunity to discuss the impact of human activities on air quality. [Objective] This study investigates the air quality changes in Shijiazhuang, and analyzes the impacts of epidemic prevention and control measures on air quality, so as to provide reference and ideas for further improving air quality and prevention and control measures. [Methods] The air quality data were collected online from https://www.zq12369.com/ and https://aqicn.org/city/shijiazhuang/cn/. Comparisons in air quality index (AQI) and the concentrations of air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) were made between the period from December 2019 to June 2020 (reference) and the same period from 2016 to 2019 by t-test and chi-square test. [Results] The daily average AQI dropped by 25.38% in Shijiazhuang during the COVID-19 prevention and control compared with the some period from 2016 to 2019 (t=6.28, P < 0.05). The proportions of pollution days during the COVID-19 outbreak in Shijiazhuang were PM2.5 (44.56%), O3 (31.09%), PM10 (23.83%), and NO2 (2.59%) successively, the pollution days of PM10 decreased significantly (chi2=3.86, P < 0.05) compared with 2016-2019, but during traffic lockdown the numbers of pollution days of PM2.5 and in the mid stage of prevention the number of pollution days of O3 increased (P < 0.05). Compared with the control period, the concentrations of the six air pollutants decreased to varying degrees (P < 0.05), especially SO2 dropped by 55.36%. [Conclusion] The measures taken for COVID-19 control and prevention have reduced the pollution sources and emissions, which resulted in better general air quality of Shijiazhuang City, but have aggravated the pollution of O3 and other pollutants. It is necessary to further explore the causes for the aggravation of O3 pollution in order to formulate reasonable air quality control strategies.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Can CO2 be used as an indicator of the probability of cross-infection?

The validity of using CO2 as an indicator of airborne infection probability was studied. Tracer gas measurements were conducted in a field lab with two breathing thermal manikins resembling "infected” and "susceptible” persons seated at desks. The room was ventilated with a mixing air distribution. Experiments were performed at three ventilation rates. CO2 gas was dosed into the air exhaled by the manikins to simulate the metabolic CO2 generation by people. Simultaneously, nitrous oxide (N2O) tracer gas was dosed into the air exhaled by one of the manikins ("infected person”) to simulate the emission of exhaled infectious particles. CO2 and N2O concentrations were measured at several points. The probability of infection was calculated based on the concentration of CO2 and N2O measured in the air inhaled by the exposed manikin ("susceptible person”). The results did not confirm that CO2 can be used as a proxy to assess the infection probability. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Impact of COVID-19-Related Travel Restrictions on the Environment and Travel Time Reliability

This study analyzes the effect of the restrictions in traffic movement enforced in order to combat the spread of coronavirus on air quality and travel time reliability under heterogeneous and laneless traffic conditions. A comparative analysis was conducted to examine quantity of pollutants, average travel time distributions (TTD), and their associated travel time reliability (TTR) metrics during the COVID-19 pandemic, postpandemic, and during partial restrictions. Pollutants data (PM2.5, NO2, and NOX) and travel time data for selected locations from Chennai City in India were collected for a sample period of one week using Wi-Fi sensors and state-run air quality monitoring stations. It was observed that the average quantity of PM2.5, NO2, and NOX were increased by 433.1%, 681.4%, and 99.2%, respectively, during the postlockdown period. Correlation analysis also indicated that all considered air pollutants are moderately correlated to Wi-Fi hits, albeit to varied degrees. From the analysis, it was also found that average TTD mean and interquartile range values were increased by 47.2% and 105.2%. In addition, the buffer time index, planning time index, travel index, and capacity buffer index associated with these TTD metrics were increased by 148.1%, 63.7%, 42.8%, and 202.9%, respectively, soon after relaxing travel restrictions. © 2023 American Society of Civil Engineers.

Enhanced performance of algal-bacterial aerobic granular sludge in comparison to bacterial aerobic granular sludge for treating surfactant-containing wastewater

Increasing amounts of surfactants are used and emitted into the environment due to the COVID-19 pandemic, posing potential threats to ecological health. Algal-bacterial aerobic granular sludge (A-BAGS), with the advantages of compact structure, high-efficient nutrient uptake, and high tolerance to harsh conditions, was attempted in this study to treat surfactant-containing wastewater at relatively high concentrations. The treatment performance was also compared to bacterial AGS (BAGS). Results showed that A-BAGS is preferable for treating wastewater containing a high SDS concentration (30 mg/L), achieving nutrient removal efficiency of 86.3 % for organic carbon, 60.5 % for total nitrogen, and 58.7 % for total phosphorus within a short duration, compared to 70.1 %, 52.8 % and 42.3 % in BAGS reactor. Besides, the removal rate of ammonia nitrogen by A-BAGS was much faster than that of BAGS. The above results confirmed that A-BAGS is a promising technology for treating surfactant-containing wastewater with high nutrient removal efficiency being maintained.Copyright © 2023 Elsevier Ltd

Two years of volatile organic compound online in situ measurements at the Site Instrumental de Recherche par Télédétection Atmosphérique (Paris region, France) using proton-transfer-reaction mass spectrometry

Volatile organic compounds (VOCs) have direct influences on air quality and climate. They indeed play a key role in atmospheric chemistry as precursors of secondary pollutants, such as ozone (O3) and secondary organic aerosols (SOA). In this respect, long-term datasets of in situ atmospheric measurements are crucial for characterizing the variability of atmospheric chemical composition, its sources, and trends. The ongoing establishment of the Aerosols, Cloud, and Trace gases Research InfraStructure (ACTRIS) allows implementation of the collection and provision of such high-quality datasets. In this context, online and continuous measurements of O3, nitrogen oxides (NOx), and aerosols have been carried out since 2012 at the SIRTA (Site Instrumental de Recherche par Télédétection Atmosphérique) observatory, located in the Paris region, France. Within the last decade, VOC measurements were conducted offline at SIRTA, until the implementation of real-time monitoring which started in January 2020 using a proton-transfer-reaction quadrupole mass spectrometer (PTR-Q-MS).The dataset acquired during the first 2 years of online VOC measurements provides insights into their seasonal and diurnal variabilities. The additional long-term datasets obtained from co-located measurements (NOx, aerosol physical and chemical properties, meteorological parameters) are used to better characterize the atmospheric conditions and to further interpret the obtained results. Results also include insights into VOC main sources and the influence of meteorological conditions and air mass origin on their levels in the Paris region. Due to the COVID-19 pandemic, the year 2020 notably saw a quasi-total lockdown in France in spring and a lighter one in autumn. Therefore, the focus is placed on the impact of these lockdowns on the VOC variability and sources. A change in the behaviour of VOC markers for anthropogenic sources was observed during the first lockdown, reflecting a change in human activities. A comparison with gas chromatography data from the Paris city centre consolidates the regional representativity of the SIRTA station for benzene, while differences are observed for shorter-lived compounds with a notable impact of their local sources. This dataset could be further used as input for atmospheric models and can be found at 10.14768/f8c46735-e6c3-45e2-8f6f-26c6d67c4723 (Simon et al., 2022a).

Ground-Based MAX-DOAS Observation of Trace Gases from 2019 to 2021 in Huaibei, China

With the spread of the COVID-19 pandemic and the implementation of closure measures in 2020, population mobility and human activities have decreased, which has seriously impacted atmospheric quality. Huaibei City is an important coal and chemical production base in East China, which faces increasing environmental problems. The impact of anthropogenic activities on air quality in this area was investigated by comparing the COVID-19 lockdown in 2020 with the normal situation in 2021. Tropospheric NO2, HCHO and SO2 column densities were observed by ground-based multiple axis differential optical absorption spectroscopy (MAX-DOAS). In situ measurements for PM2.5, NO2, SO2 and O3 were also taken. The observation period was divided into four phases, the pre-lockdown period, phase 1 lockdown, phase 2 lockdown and the post-lockdown period. Ground-based MAX-DOAS results showed that tropospheric NO2, HCHO and SO2 column densities increased by 41, 14 and 14%, respectively, during phase 1 in 2021 vs. 2020. In situ results showed that NO2 and SO2 increased by 59 and 11%, respectively, during phase 1 in 2021 vs. 2020, but PM2.5 and O3 decreased by 15 and 17%, respectively. In the phase 2 period, due to the partial lifting of control measures, the concentration of pollutants did not significantly change. The weekly MAX-DOAS results showed that there was no obvious weekend effect of pollutants in the Huaibei area, and NO2, HCHO and SO2 had obvious diurnal variation characteristics. In addition, the relationship between the column densities and wind speed and direction in 2020 and 2021 was studied. The results showed that, in the absence of traffic control in 2021, elevated sources in the Eastern part of the city emitted large amounts of NO2. The observed ratios of HCHO to NO2 suggested that tropospheric ozone production involved NOX-limited scenarios. The correlation analysis between HCHO and different gases showed that HCHO mainly originated from primary emission sources related to SO2. © 2023 by the authors.

Association of nitrogen-balance trajectories with clinical outcomes in critically ill COVID-19 patients : A retrospective cohort study

Introduction et but de l'etude: The intensity and duration of the catabolic phase in COVID-19 patients might differ between survivors and non-survivors. The purpose of the study was to assess the association between nitrogen-balance trajectories and outcome in critically ill COVID-19 patients. Materiel et methodes: It is a retrospective monocentric observational study, achieved into the intensive care unit of the University Hospital of Clermont-Ferrand, France. Patients admitted to intensive care from January 2020 to May 2021 for COVID-19 pneumonia were included. Patients were excluded if referred from another ICU, if their ICU length of stay was < 72 h, or if they were treated with renal replacement therapy during the first seven days after ICU admission. Data were collected prospectively at admission and during ICU stay. Death was recorded at the end of ICU stay. Comparisons of nitrogen-balance time course according to outcome were made using two-way ANOVA. At days 3, 5, 7, 10 and 14, uni and multivariate logistic regression analyses were achieved to assess the impact of a non-negative nitrogen-balance on ICU death. At Days 3, 5 and 7, to represent the relationship between nitrogen-balance and protein intakes, linear and non-nonlinear models were run and the protein intakes necessary to reach a zero nitrogen-balance were determined. Subgroup analyses were carried out by BMI, age, and sex. Resultats et analyses statistiques: Ninety-nine patients were included. At Day 3, similar negative nitrogen-balances were observed in survivors and non-survivors: -16.4 g/d [-26.5, -3.3] and -17.3 g/d [-22.2, -3.8] (P = 0.54). The trajectories of nitrogen-balance over time thus differed between survivors and non-survivors (P = 0.01). In survivors, nitrogen-balance increased over time, whereas in non-survivors, nitrogen-balance decreased from Day 2 to Day 6, and thereafter increased slowly up to Day 14. At Day 5 and 7, a non-negative nitrogen-balance was protective from death. Administering higher protein amounts was associated with higher nitrogen-balances. Conclusion(s): We report a prolonged catabolic state in COVID patients that seemed more pronounced in non-survivors than in survivors. Our study underlines the need for monitoring urinary nitrogen excretion to guide protein intakes in COVID-19 patients.Copyright © 2023

A foundational theoreticalAl12E12(E = N, P) adsorption and quinolone docking study: cage-quinolone pairs, optics and possible therapeutic and diagnostic applications.

This combined Al12E12 (E = N, P) surface adsorption and docking study describes the new possibility of prospective potential probing(photophysical/optical) and therapy(medicinal/biochemical) with these adsorbent conjugates. DFT investigations were undertaken herein to help generate geometrical models and better understand the possible favorable adsorption energetics. We attempt to explain their adsorption behaviors and docking involving SARS-CoV-2 viruses (PDB)to assess their possible pharmaceutical potential against the pandemic virus (COVID-19). The adsorption behavior of 8-hydroxy-2-methylquinoline (MQ) and its halogenated derivatives, 5,7-diiodo-8-hydroxy-2-methylquinoline (MQI), 5,7-dichloro-8-hydroxy-2-methylquinoline (MQCl), and 5,7-dibromo-8-hydroxy-2-methylquinoline (MQBr), with aluminum-nitrogen (AlN), and aluminum-phosphorous (AlP) fullerene-like nanocages is reported. A decrease in the hardness of the nanoclusters when adsorbed with drug molecules resulted in an incrementally improved chemical softness (see e.g., Hard-Soft Acid Base theory) indicating that reactivity of the drug molecule in the resulting complex increases upon cluster chemical adsorption. The energy gap is found to be maximized for AlN-MQ and minimized for AlP-MQI; the reduced density gradient (RDG) iso-surfaces and AIM studies also corroborated this. Therefore, these two were found, respectively, to be the least and most electrically conductive of the species under study. We selected a simple medicinal building block (chelator)in addition to selecting the cluster based on previous literature reports. Important parameters such as gap energies and global indices were determined. We assessed NLO properties. The SARS-CoV-2 virus PDB docking data for 6VW1, 6VYO, 6WKQ, 7AD1, 7AOL, 7B3C, were enlisted as ligand targets for studies of docking (PatchDock Server) using the requisite PDB geometries (For the structure of 6VW1, kindly see reference, 2020; For the structure of 6VYO kindly see reference, 2020; For the structure of 6WKQ kindly see reference, 2020; For the structure of 7AD1 kindly see reference, 2021; For the structure of 7AOL kindly see reference, 2021; For the structure of 7B3C kindly see reference, 2021). Such findings indicate that the AlN-drug conjugation have inhibitory effect against these selected receptors.

Association between nitrogen dioxide concentration and hypertension hospitalization: A multicenter time-series analysis in Xinxiang, China

Hypertension is a common chronic disease, and air pollution is strongly associated with hypertension hospitalization. However, the association between nitrogen dioxide (NO2)1 concentration and hypertension hospitalization has rarely been studied. We collected daily data on hypertension hospitalizations, air pollutants, and meteorology from January 1, 2016 to October 31, 2021. After controlling for the effects of seasonal and long-term trends, weather conditions, weekdays, holidays, and during the novel coronavirus crown epidemic, a generalized additive model with over discrete Poisson regression was used to simulate the association between NO2 concentration and hypertension hospitalizations while quantifying hypertension hospitalizations, hospital stays, and hospital costs attributable to NO2. The results showed that each 10 μg/m3 increase in NO2 concentration was significantly associated with the relative risk (RR) of hypertension admission in Xinxiang, with the greatest effect at lag04 (RR = 1.107;95% confidence interval, 1.046–1.172). Hypertension hospitalizations attributed to NO2 during the study period accounted for 9.70% (484) of the total hypertension hospitalizations, equivalent to 4202 hospital days and 338.55 thousand United States dollars (USD). Increased NO2 concentration increases the risk of hypertension hospitalization in Xinxiang, which poses a significant health and economic burden to society and patients. The findings of this study provide a basis for developing stricter environmental pollutant standards.

Atmospheric pollution during the Covid-19 pandemics in Slovakia

The changes in the particle pollution in eight Slovak regions were evaluated by a paired t-test to verify the significance of the concn. changes during, before and after the lockdowns introduced in 2020 as compared with those of 2019. The obsd. air quality improvement was not flat-rate and rather momentary, and it did not last even through the whole restriction period. Significant decreases were recorded only for NO 2 concn. The European Commission limits of particulate pollution were exceeded in Slovakia. A concise literature rev. was also included.

Effect of vegetation and land surface temperature on NO2 concentration: A Google Earth Engine-based remote sensing approach

With the increasing tension on the global sustainable environment in the urban areas, it is essential to monitor the airborne pollutants and understand the underlying factors that can trigger the situation in a worst-case scenario. Because of its cramped living conditions, excessive coal and fuel usage, and rapid deforestation, the southeast Asian region has historically had worse air quality than the rest of the world. The economic hubs of India and Bangladesh, in particular, have drawn so much attention away from rural regions that unrestrained urbanization is becoming controversial for planners, engineers, and stakeholders in sustainable development. This research combines the two main Asian capital regions, Delhi and Dhaka. It analyzes the change in nitrogen dioxide (NO2) concentration, land surface temperature (LST), and vegetation dynamics across three years (2019-2021) for summer and winter. The NO2 concentration data from Sentinel-5P has been extracted using Google Earth Engine (GEE), and Landsat-8 imagery was utilized for LST, Normalizer Vegetation Index (NDVI), and Enhance Vegetation Index (EVI). The statistical analysis has been carried out by dividing the research regions into one sq. km grid (1512 grids for Delhi and 1485 grids for Dhaka). According to descriptive research, Dhaka's condition is worse than Delhi's, with significant vegetation loss with LST and NO2 concentrations rising. In both research regions, the NO2 concentration is high throughout the winter. The Pearson correlation value demonstrates a negative association between total NO2 concentration and mean NDVI and EVI values and a positive relationship between total NO2 concentration and mean LST. The data have been further assessed using linear regression, which overlaps the correlation result with a maximum R-squared value of 0.2998 for NO2 and EVI in winter 2019.