Carbon Monitor Europe near-real-time daily CO2 emissions for 27 EU countries and the United Kingdom.

With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO2 emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO2 emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.

Inpatient antibacterial use trends and patterns, China, 2013-2021.

Objective: To analyse trends and patterns in inpatient antibacterial use in China's tertiary and secondary hospitals between 2013 and 2021. Methods: The analysis involved quarterly data from hospitals covered by China's Center for Antibacterial Surveillance. We obtained information on hospital characteristics (e.g. province, a de-identified hospital code, hospital level and inpatient days) and antibacterial characteristics (e.g. generic name, drug classification, dosage, administration route and usage volume). We quantified antibacterial use as the number of daily defined doses per 100 patient-days. The analysis took into account the World Health Organization's (WHO's) Access, Watch, Reserve classification of antibiotics. Findings: Between 2013 and 2021, overall antibacterial use in inpatients decreased significantly from 48.8 to 38.0 daily defined doses per 100 patient-days (P < 0.001). In 2021, the variation between provinces was almost twofold: 29.1 daily defined doses per 100 patient-days in Qinghai versus 55.3 in Tibet. The most-used antibacterials in both tertiary and secondary hospitals throughout the study period were third-generation cephalosporins, which comprised around one third of total antibacterial use. Carbapenems entered the list of most-used antibacterial classifications in 2015. The most frequently used antibacterials in WHO's classification belonged to the Watch group: usage increased significantly from 61.3% (29.9/48.8) in 2013 to 64.1% (24.4/38.0) in 2021 (P < 0.001). Conclusion: Antibacterial use in inpatients decreased significantly during the study period. However, the rising proportion of last-resort antibacterials used is concerning, as is the large gap between the proportion of antibacterials used belonging to the Access group and WHO's global target of no less than 60%.

Sustainable production of dimethyl-protected cyclic lysine over Pd/m-Al2O3-Si catalysts and its application in synthesis of antibacterial nylon‑6 copolymers

• Pd/ m- Al 2 O 3 -Si catalyst exhibited high efficiency in converting α- amino -ε- caprolactam (α- ACL) to dimethyl-protected cyclic lysine (DMCL). • The lack of Brönsted acid sites on Pd/ m- Al 2 O 3 -Si surface facilitated the formation of DMCL and suppressed undesirable reaction process. • Pd/ m- Al 2 O 3 -Si catalyst with microspherical morphology performed excellent stability and physical strength during the catalytic process. • The nylon‑6 copolymers produced from the as-synthesized DMCL exhibited a great potential in the synthesis of self-cleaning antibacterial materials. Antibacterial monomers are prerequisites for synthesizing antibacterial polymers, especially during the current COVID-19 pandemic. Dimethyl-protected cyclic lysine (DMCL) is a promising functional monomer for nylon-6 based self-cleaning antibacterial polymers. However, the production of DMCL still faces formidable challenges, such as harsh reaction conditions and low catalyst activities. In this study, we developed a Pd/ m -Al 2 O 3 -Si catalyst, which exhibited high efficiency in converting α -amino- ε -caprolactam (α -ACL) to DMCL, affording a yield of as high as 97.1% at 100 °C and 1 MPa H 2. The lack of Brönsted acid sites on the catalyst surface facilitated the formation of DMCL and suppressed undesirable hydrolysis or cracking by-products from the lactam-based reactant. The recycled experiments showed that Pd/ m -Al 2 O 3 -Si performed excellent stability and physical strength with essentially no damage to its microspheres after the reaction. The nylon‑6 copolymers produced from the as-synthesized DMCL exhibited similar structure and thermal stability with pure nylon-6, showing great potential in synthesizing the self-cleaning antibacterial polymers. This work provides a sustainable and efficient method for producing DMCL and other lysine-based antibacterial monomers, showing a great prospect for the utilization of bio-based chemicals in synthesizing functional polymers. [ FROM AUTHOR] Copyright of Chemical Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic.

BACKGROUND: From March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic. METHODS: Data on COVID-19 cases were collected from the Shanghai Municipal Health Commission during the period from 20th February to 1st June. The effective reproductive number (Rt) and transmission distance between cases were calculated. An age-structured SEIR model with social contact patterns was developed to reconstruct the transmission dynamics and evaluate age-specific transmission characteristics. Least square method was used to calibrate the model. Basic reproduction number (R0) was estimated with next generation matrix. RESULTS: R0 of Omicron variant was 7.9 (95% CI: 7.4 to 8.4). With strict interventions, Rt had dropped quickly from 3.6 (95% CI: 2.7 to 4.7) on 4th March to below 1 on 18th April. The mean transmission distance of the Omicron epidemic in Shanghai was 13.4 km (95% CI: 11.1 to 15.8 km), which was threefold longer compared with that of epidemic caused by the wild-type virus in Wuhan, China. The model estimated that there would have been a total 870,845 (95% CI: 815,400 to 926,289) cases for the epidemic from 20th February to 15th June, and 27.7% (95% CI: 24.4% to 30.9%) cases would have been unascertained. People aged 50-59 years had the highest transmission risk 0.216 (95% CI: 0.210 to 0.222), and the highest secondary attack rate (47.62%, 95% CI: 38.71% to 56.53%). CONCLUSIONS: The Omicron variant spread more quickly and widely than other variants and resulted in about one third cases unascertained for the recent outbreak in Shanghai. Prioritizing isolation and screening of people aged 40-59 might suppress the epidemic more effectively. Routine surveillance among people aged 40-59 years could also provide insight into the stage of the epidemic and the timely detection of new variants. TRIAL REGISTRATION: We did not involve clinical trial.

Wetland emission and atmospheric sink changes explain methane growth in 2020.

Atmospheric methane growth reached an exceptionally high rate of 15.1 ± 0.4 parts per billion per year in 2020 despite a probable decrease in anthropogenic methane emissions during COVID-19 lockdowns1. Here we quantify changes in methane sources and in its atmospheric sink in 2020 compared with 2019. We find that, globally, total anthropogenic emissions decreased by 1.2 ± 0.1 teragrams of methane per year (Tg CH4 yr-1), fire emissions decreased by 6.5 ± 0.1 Tg CH4 yr-1 and wetland emissions increased by 6.0 ± 2.3 Tg CH4 yr-1. Tropospheric OH concentration decreased by 1.6 ± 0.2 per cent relative to 2019, mainly as a result of lower anthropogenic nitrogen oxide (NOx) emissions and associated lower free tropospheric ozone during pandemic lockdowns2. From atmospheric inversions, we also infer that global net emissions increased by 6.9 ± 2.1 Tg CH4 yr-1 in 2020 relative to 2019, and global methane removal from reaction with OH decreased by 7.5 ± 0.8 Tg CH4 yr-1. Therefore, we attribute the methane growth rate anomaly in 2020 relative to 2019 to lower OH sink (53 ± 10 per cent) and higher natural emissions (47 ± 16 per cent), mostly from wetlands. In line with previous findings3,4, our results imply that wetland methane emissions are sensitive to a warmer and wetter climate and could act as a positive feedback mechanism in the future. Our study also suggests that nitrogen oxide emission trends need to be taken into account when implementing the global anthropogenic methane emissions reduction pledge5.

Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak.

BACKGROUND: From 20 July to 26 August 2021, local outbreaks of COVID-19 occurred in Nanjing City and Yangzhou City (Jiangsu Province, China). We analyzed the characteristics of these outbreaks in an effort to develop specific and effective intervention strategies. METHODS: Publicly available data on the characteristics of the COVID-19 outbreaks in Jiangsu Province were collected. Logistic regression was used to assess the association of age and sex with clinical severity. Analysis of onset dates, generation time distributions, and locations were used to estimate the mean transmission distance. A branching process model was used to evaluate different management strategies. RESULTS: From 20 July to 26 August 2021, 820 patients were diagnosed with COVID-19 in Jiangsu Province, with 235 patients (28.7%) from Nanjing, 570 (69.5%) from Yangzhou, and 15 (1.8%) from other cities. Overall, 57.9% of the patients were female, 13.7% were under 20 years-old, and 58.3% had moderate disease status. The mean transmission distance was 4.12 km, and closed-loop management of the area within 2.23 km of cases seemed sufficient to control an outbreak. The model predicted that the cumulative cases in Yangzhou would increase from 311 to 642 if the interval between rounds of nucleic acid amplification testing (NAAT) increased from 1 to 6 days. It also predicted there would be 44.7% more patients if the NAAT started 10 days (rather than 0 days) after diagnosis of the first case. The proportion of cases detected by NAAT would increase from 11.16 to 44.12% when the rounds of NAAT increased from 1 to 7 within 17 days. When the effective vaccine coverage was 50%, the outbreak would be controlled even when using the most relaxed non-pharmaceutical interventions. CONCLUSIONS: The model predicted that a timely closed-loop management of a 2.23 km area around positive COVID-19 cases was sufficient to control the outbreak. Prompt serial NAAT is likely to contain an outbreak quickly, and our model results indicated that three rounds of NAAT sufficiently controlled local transmission. Trial registration We did not involve clinical trial.

Publication trends of research on COVID-19 and host immune response: A bibliometric analysis

Introduction As the first bibliometric analysis of COVID-19 and immune responses, this study will provide a comprehensive overview of the latest research advances. We attempt to summarize the scientific productivity and cooperation across countries and institutions using the bibliometric methodology. Meanwhile, using clustering analysis of keywords, we revealed the evolution of research hotspots and predicted future research focuses, thereby providing valuable information for the follow-up studies. Methods We selected publications on COVID-19 and immune response using our pre-designed search strategy. Web of Science was applied to screen the eligible publications for subsequent bibliometric analyses. GraphPad Prism 8.0, VOSviewer, and CiteSpace were applied to analyze the research trends and compared the contributions of countries, authors, institutions, and journals to the global publications in this field. Results We identified 2,200 publications on COVID-19 and immune response published between December 1, 2019, and April 25, 2022, with a total of 3,154 citations. The United States (611), China (353), and Germany (209) ranked the top three in terms of the number of publications, accounting for 53.3% of the total articles. Among the top 15 institutions publishing articles in this area, four were from France, four were from the United States, and three were from China. The journal Frontiers in Immunology published the most articles (178) related to COVID-19 and immune response. Alessandro Sette (31 publications) from the United States were the most productive and influential scholar in this field, whose publications with the most citation frequency (3,633). Furthermore, the development and evaluation of vaccines might become a hotspot in relevant scope. Conclusions The United States makes the most indispensable contribution in this field in terms of publication numbers, total citations, and H-index. Although publications from China also take the lead regarding quality and quantity, their international cooperation and preclinical research need to be further strengthened. Regarding the citation frequency and the total number of published articles, the latest research progress might be tracked in the top-ranking journals in this field. By analyzing the chronological order of the appearance of retrieved keywords, we speculated that vaccine-related research might be the novel focus in this field.

Patterns of human social contact and mask wearing in high-risk groups in China.

BACKGROUND: The pandemic of coronavirus disease 2019 (COVID-19) has changed human behavior in areas such as contact patterns and mask-wearing frequency. Exploring human-human contact patterns and mask-wearing habits in high-risk groups is an essential step in fully understanding the transmission of respiratory infection-based diseases. This study had aims to quantify local human-human (H-H) contacts in high-risk groups in representative provinces of China and to explore the occupation-specific assortativity and heterogeneity of social contacts. METHODS: Delivery workers, medical workers, preschoolers, and students from Qinghai, Shanghai, and Zhejiang were recruited to complete an online questionnaire that queried general information, logged contacts, and assessed the willingness to wear a mask in different settings. The "group contact" was defined as contact with a group at least 20 individuals. The numbers of contacts across different characteristics were assessed and age-specific contact matrices were established. A generalized additive mixed model was used to analyze the associations between the number of individual contacts and several characteristics. The factors influencing the frequency of mask wearing were evaluated with a logistic regression model. RESULTS: A total of 611,287 contacts were reported by 15,635 participants. The frequency of daily individual contacts averaged 3.14 (95% confidence interval: 3.13-3.15) people per day, while that of group contacts was 37.90 (95% CI: 37.20-38.70). Skin-to-skin contact and long-duration contact were more likely to occur at home or among family members. Contact matrices of students were the most assortative (all contacts q-index = 0.899, 95% CI: 0.894-0.904). Participants with larger household sizes reported having more contacts. Higher household income per capita was significantly associated with a greater number of contacts among preschoolers (P50,000-99,999 = 0.033) and students (P10,000-29,999 = 0.017). In each of the public places, the frequency of mask wearing was highest for delivery workers. For preschoolers and students with more contacts, the proportion of those who reported always wearing masks was lower (P < 0.05) in schools/workplaces and public transportation than preschoolers and students with fewer contacts. CONCLUSIONS: Contact screening efforts should be concentrated in the home, school, and workplace after an outbreak of an epidemic, as more than 75% of all contacts, on average, will be found in such places. Efforts should be made to improve the mask-wearing rate and age-specific health promotion measures aimed at reducing transmission for the younger demographic. Age-stratified and occupation-specific social contact research in high-risk groups could help inform policy-making decisions during the post-relaxation period of the COVID-19 pandemic.

Empirical study and model simulation of global stock market dynamics during COVID-19.

At the beginning of 2020, COVID-19 swept the world and changed various aspects of human society, such as economy and finance, life and health, migration and population. We first empirically study how the dynamic behaviors of stock markets are affected by COVID-19, and focus on the large volatility dynamics, variation-fluctuation correlation function and epidemic-fluctuation correlation function. Then we generalize the Heston model to simulate the global stock market dynamics, and an epidemic index computed from empirical data is directly taken as the external force in the modelling.

Thymosin-α1 binds with ACE and downregulates the expression of ACE2 in human respiratory epithelia.

BACKGROUND: Thymosin-α1 has been implicated into the treatment of novel respiratory virus Coronavirus Disease 2019 (COVID-19), but the underlying mechanisms are still disputable. AIM: Herein we aimed to reveal a previously unrecognized mechanism that thymosin-α1 prevents COVID-19 by binding with angiotensin-converting enzyme (ACE), which was inspired from the tool of network pharmacology. METHODS: KEGG pathway enrichment of thymosin-α1 treating COVID-19 was analyzed by Database of Functional Annotation Bioinformatics Microarray Analysis, then core targets were validated by ligand binding kinetics assay and fluorometric detection of ACE and ACE2 enzymatic activity. The production of angiotensin I, angiotensin II, angiotensin (1-7) and angiotensin (1-9) were detected by enzyme linked immunosorbent assay. RESULTS: We found that thymosin-α1 impaired the expressions of angiotensin-converting enzyme 2 and angiotensin (1-7) of human lung epithelial cells in a dose-dependent way (p < 0.001). In contrast, thymosin-α1 had no impact on their ACE and angiotensin (1-9) expressions but significantly inhibited the enzymatic activity of ACE (p > 0.05). CONCLUSION: The bioinformatic findings of network pharmacology and the corresponding pharmacological validations have revealed that thymosin-α1 treatment could decrease ACE2 expression in human lung epithelial cells, which strengthens the potential clinical applications of thymosin-α1 to prevent severe acute respiratory syndrome coronavirus 2 infection.

Exploring agreement and feasibility between virtual home visits and in-person home visits for peritoneal dialysis patients-a paired study.

INTRODUCTION: Virtual home visits may improve chronic disease management. However, whether they are suitable for peritoneal dialysis (PD) patients has not yet been fully investigated. This study aimed to compare the agreement and acceptance of virtual home visits and in-person home visits in PD patients. METHODS: This was a paired, single center, noninferiority trial. Participants received a virtual home visit and an in-person home visit simultaneously. A home visit checklist was built for standardization visits. The content was divided into three parts: domestic habits (57 items), bag exchange procedures (56 items), and exit site care (53 items). Satisfaction questionnaires for both patients and nurses were designed to assess attitudes toward home visits and socioeconomic effects. RESULTS: A total of 30 PD patients were enrolled in a single center. The information collected from virtual home visits and in-person home visits was found to be highly consistent. The perfect agreement was found in 52/57, 49/56, and 44/53 items (Cohen's kappa 0.81-1.00), substantial agreement in 4/57, 7/56, and 8/53 items (Cohen's kappa 0.61-0.80). Patients reported almost identical satisfaction for virtual home visits and in-person home visits (Z = 0.39, p = 0.70). PD nurses reported similar feasibility and patient cooperation for the two visit types (Z = 0.99, p = 0.33; Z = 1.65, p = 0.10, respectively). In addition, virtual home visits were found to be more cost-effective than in-person home visits. CONCLUSIONS: Virtual home visits information collection was similar to in-person home visits in PD. There were no differences in participant satisfaction and feasibility between the two visit types.

Global Research Status of Multiple Organ Dysfunction Syndrome During 2001-2021: A 20-Year Bibliometric Analysis.

Background: Multiple Organ Dysfunction Syndrome (MODS) is a major cause of high morbidity and mortality among patients in intensive care units (ICU). Although numerous basic and clinical researches on MODS have been conducted, there is still a long way to go to prevent patients from entering this stage. To our knowledge, no bibliometric analyses of MODS have been reported, this study, therefore, was conducted to reveal MODS research status and trends during 2001-2021. Methods: All relevant literature covering MODS during 2001-2021 were extracted from Web of Science. An online analysis platform of literature metrology was used to analyze the publication trends. VOSviewer software was used to collect and analyze the keywords and research hotspots related to MODS. Results: As of July 31, 2021, a total of 994 MODS-related articles from 2001 to 2021 were identified. The United States accounted for the largest number of publications (31.1%), followed by China and Germany, with 186 and 75 publications, respectively. Among all the institutions, the University of Pittsburgh published the most papers related to MODS (21). Critical Care Medicine published the most papers in this field (106). Professor Moore EE, who had the most citation frequency (1847), made great achievements in MODS research. Moreover, analysis of the keywords identified three MODS research hotspot clusters: "mechanism-related research," "clinical research," and "diagnostic research." Conclusions: The United States maintained a top position worldwide and made the most outstanding contribution in the MODS field. In terms of publication, China was next only to the United States, but there was a disproportion between the quantity of publications and citation frequency. The institution University of Pittsburgh and journal Critical Care Medicine represent the highest level of research in this field. During the 20 years from 2001 to 2021, basic MODS research has been in-depth yet progressed relatively slowly recently, but the outbreak of COVID-19 has to some extent set off an upsurge of clinical research in MODS field.

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts.

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO2 emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO2 fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

Cluster randomised controlled trial to assess a tailored intervention to reduce antibiotic prescribing in rural China: study protocol.

INTRODUCTION: Up to 80% of patients with respiratory tract infections (RTI) attending healthcare facilities in rural areas of China are prescribed antibiotics, many of which are unnecessary. Since 2009, China has implemented several policies to try to reduce inappropriate antibiotic use; however, antibiotic prescribing remains high in rural health facilities. METHODS AND ANALYSIS: A cluster randomised controlled trial will be carried out to estimate the effectiveness and cost effectiveness of a complex intervention in reducing antibiotic prescribing at township health centres in Anhui Province, China. 40 Township health centres will be randomised at a 1:1 ratio to the intervention or usual care arms. In the intervention group, practitioners will receive an intervention comprising: (1) training to support appropriate antibiotic prescribing for RTI, (2) a computer-based treatment decision support system, (3) virtual peer support, (4) a leaflet for patients and (5) a letter of commitment to optimise antibiotic use to display in their clinic. The primary outcome is the percentage of antibiotics (intravenous and oral) prescribed for RTI patients. Secondary outcomes include patient symptom severity and duration, recovery status, satisfaction, antibiotic consumption. A full economic evaluation will be conducted within the trial period. Costs and savings for both clinics and patients will be considered and quality of life will be measured by EuroQoL (EQ-5D-5L). A qualitative process evaluation will explore practitioner and patient views and experiences of trial processes, intervention fidelity and acceptability, and barriers and facilitators to implementation. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Biomedical Research Ethics Committee of Anhui Medical University (Ref: 20180259); the study has undergone due diligence checks and is registered at the University of Bristol (Ref: 2020-3137). Research findings will be disseminated to stakeholders through conferences and peer-reviewed journals in China, the UK and internationally. TRIAL REGISTRATION NUMBER: ISRCTN30652037.

Near-real-time global gridded daily CO2 emissions.

Precise and high-resolution carbon dioxide (CO2) emission data is of great importance in achieving carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO2 Emissions Dataset (GRACED) from fossil fuel and cement production with a global spatial resolution of 0.1° by 0.1° and a temporal resolution of 1 day. Gridded fossil emissions are computed for different sectors based on the daily national CO2 emissions from near-real-time dataset (Carbon Monitor), the spatial patterns of point source emission dataset Global Energy Infrastructure Emissions Database (GID), Emission Database for Global Atmospheric Research (EDGAR), and spatiotemporal patters of satellite nitrogen dioxide (NO2) retrievals. Our study on the global CO2 emissions responds to the growing and urgent need for high-quality, fine-grained, near-real-time CO2 emissions estimates to support global emissions monitoring across various spatial scales. We show the spatial patterns of emission changes for power, industry, residential consumption, ground transportation, domestic and international aviation, and international shipping sectors from January 1, 2019, to December 31, 2020. This gives thorough insights into the relative contributions from each sector. Furthermore, it provides the most up-to-date and fine-grained overview of where and when fossil CO2 emissions have decreased and rebounded in response to emergencies (e.g., coronavirus disease 2019 [COVID-19]) and other disturbances of human activities of any previously published dataset. As the world recovers from the pandemic and decarbonizes its energy systems, regular updates of this dataset will enable policymakers to more closely monitor the effectiveness of climate and energy policies and quickly adapt.

New Insights into Unexpected Severe PM2.5 Pollution during the SARS and COVID-19 Pandemic Periods in Beijing.

During the SARS period in 2003 and COVID-19 pandemic period in 2020, unexpected severe particulate matter pollution occurred in northern China, although the anthropogenic activities and associated emissions have assumed to be reduced dramatically. This anomalistic increase in PM2.5 pollution raises a question about how source emissions impact the air quality during these pandemic periods. In this study, we investigated the stable Cu and Si isotopic compositions and typical source-specific fingerprints of PM2.5 and its sources. We show that the primary PM2.5 emissions (PM2.5 emitted directly from sources) actually had no reduction but redistribution during these pandemic periods, rather than the previous thought of being greatly reduced. This finding provided critical evidence to interpret the anomalistic PM2.5 increase during the pandemic periods in north China. Our results also suggested that both the energy structure adjustment and stringent regulations on primary emissions should be synergistically implemented in a regional scale for clean air actions in China.

Clinical and epidemiological characteristics of nine cases of clustered Chlamydia psittaci pneumonia

OBJECTIVE: To explore the clinical characteristics of nine cases of clustered Chlamydia psittaci pneumonia under the COVID-19 pandemic. METHODS: Total of nine cases diagnosed with C. psittaci pneumonia during Dec 2020 were enrolled in the study, of whom eight cases were treated in the Department of Miyun District of Peking University First Hospital and one case were from TCM Hospital of Beijing Miyun Traditional Chinese Medicine Hospital. The clinical data of the patients were retrospectively analyzed, and the clinical characteristics of the disease and treatment were summarized. RESULTS: The onset time of nine patients was concentrated, and all of them had activities or living history in pigeon breeding area. All patients had different degrees of fever, 77.80% of whom were high fever, accompanied by cough and expectoration. The white blood cell count was normal and the neutrophils were increased. C-reactive protein level in 8 cases was increased and D-dimer was elevated in six cases. Chest CT scanning showed high-density consolidation in unilateral lungs, with bronchial inflatable signs, especially in lower lungs, but bilateral lung changes were not common. One death was reported as multiple variations in ground-glass opacity of bilateral lungs. Eight patients were treated and recovered with no observable inflammatory lesions and esidual fibrosis. Two patients' specimens were detected with C. psittaci nucleic acid by metagenomics next-generation sequencing(mNGS) technology. Seven patients underwent serum antibody test for C. psittaci, all of which were positive. Six patients were under respiratory tract pathogenic testing, all of which were the combined infection of Klebsiella. Quinolone antibiotics were used in the treatment of eight patients, either alone or in combination with other drugs. Two patients were treated with tetracyclines. Eight patients were cured, and one died clinically. CONCLUSION: Patients should be inquired their contact history in detail when encountering an unexpected clustered outbreak of pneumonia. The mNGS is efficient in identifying the pathogenic bacteria, which can help to reduce the burden of disease ultimately. Except for tetracyclines, quinolones have shown good therapeutic effects in the treatment of C. psittaci pneumonia.

Abrupt decline in tropospheric nitrogen dioxide over China after the outbreak of COVID-19.

China's policy interventions to reduce the spread of the coronavirus disease 2019 have environmental and economic impacts. Tropospheric nitrogen dioxide indicates economic activities, as nitrogen dioxide is primarily emitted from fossil fuel consumption. Satellite measurements show a 48% drop in tropospheric nitrogen dioxide vertical column densities from the 20 days averaged before the 2020 Lunar New Year to the 20 days averaged after. This decline is 21 ± 5% larger than that from 2015 to 2019. We relate this reduction to two of the government's actions: the announcement of the first report in each province and the date of a province's lockdown. Both actions are associated with nearly the same magnitude of reductions. Our analysis offers insights into the unintended environmental and economic consequences through reduced economic activities.

Global Gridded Daily CO2 Emissions (preprint)

Precise and high-resolution carbon dioxide (CO2) emission data is of great importance of achieving the carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO2 Emission Datasets (called GRACED) from fossil fuel and cement production with a global spatial-resolution of 0.1{\deg} by 0.1{\deg} and a temporal-resolution of 1-day. Gridded fossil emissions are computed for different sectors based on the daily national CO2 emissions from near real time dataset (Carbon Monitor), the spatial patterns of point source emission dataset Global Carbon Grid (GID), Emission Database for Global Atmospheric Research (EDGAR) and spatiotemporal patters of satellite nitrogen dioxide (NO2) retrievals. Our study on the global CO2 emissions responds to the growing and urgent need for high-quality, fine-grained near-real-time CO2 emissions estimates to support global emissions monitoring across various spatial scales. We show the spatial patterns of emission changes for power, industry, residential consumption, ground transportation, domestic and international aviation, and international shipping sectors between 2019 and 2020. This help us to give insights on the relative contributions of various sectors and provides a fast and fine-grained overview of where and when fossil CO2 emissions have decreased and rebounded in response to emergencies (e.g. COVID-19) and other disturbances of human activities than any previously published dataset. As the world recovers from the pandemic and decarbonizes its energy systems, regular updates of this dataset will allow policymakers to more closely monitor the effectiveness of climate and energy policies and quickly adapt