Trends and inferred emissions of atmospheric high molecular weight perfluorocarbons

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 115-119).Atmospheric observations and atmospheric observation-based global emission estimates are presented for the five high molecular weight perfluorocarbons (PFCs): decafluorobutane (C 4 F 1 0 ), dodecafluoropentane (C5 F1 2 ), tetradecafluorohexane (C 6 F14 ), hexadecafluoroheptane (C 7F 16 ) and octadecafluorooctane (C8 F 18 ). Their atmospheric histories are based on measurements of 36 Northern Hemisphere and 46 Southern Hemisphere archived air samples, collected between 1973 and 2011, using two of the "Medusa" cryogenic preconcentration gas chromatography-mass spectrometry instruments, which are part of the Advanced Global Atmospheric Gases Experiment (AGAGE). A new calibration scale was prepared for each PFC, with estimated accuracies of 6.8% for C4Fi0 , 7.8% for C5F12 , 4.0% for CF 14 , 6.6% for C7FE16 and 7.9% for CF8i . Based on our observations, the 2011 globally averaged dry air mole fractions of these high molecular weight PFCs are: 0.17 parts-per-trillion (ppt, i.e., parts per 1012) for C4 F 10 , 0.12 ppt for C5 F 1 2 , 0.27 ppt for CF 1 4 , 0.12 ppt for CFE16 and 0.09 ppt for CF 18 . Newly measured infrared absorption spectra are presented for C7F 16 and CF 1 8 , and using these, their radiative efficiencies and global warming potentials (GWPs) are estimated. We find that the radiative efficiency of C8 F 18 at 0.57Wm- 2 ppb-' is similar to that of trifluoromethyl sulfur pentafluoride's (SF 5 CF 3 ), which has the highest radiative efficiency of any known atmospheric species (Forster et al., 2007). Using their radiative efficiencies, the 2011 observed globally averaged atmospheric mole fractions of the above five high molecular weight PFCs combine to contribute a global average radiative forcing of 0.35 mW m-2, which is 6% of the total anthropogenic PFC radiative forcing (Montzka et al., 2011; Oram et al., 2012). Global emissions for C4 Fio, C5F 12 , C6 F 14 , C7 F 16 and CF 18 were estimated from the observations using a 3-dimensional chemical transport model and a Bayseian inverse method that included a constraint on the annual growth rate of their emissions, consistent with the knowledge of the relevant industries emitting them (Rigby et al., 2011). The derived so-called "top-down" emission estimates show that global emission rates were largest in the 1980s and 1990s for C4 F 10 and C5 F 12 and in the 1990s for C6F 14 , C7F16 and C8F1 . After a subsequent decline, emission rates have remained relatively stable, within ±20 % year-to-year variation, for the last 5 years. Using their calculated 100-year time horizon GWPs, the high molecular weight perfluorocarbons studied here contributed up to 15.4 % of the total PFC emissions expressed in carbon dioxide (C0 2)-equivalents in 1997 and 6 % of the total PFC emissions in 2009. Furthermore, we compare our atmospheric observation-based global emissions to the available so-called "bottom-up" inventories, which are based on production information and end usage. Bottom-up emission estimates are available from the Emission Database for Global Atmospheric Research version 4.2 (EDGARv4.2) for C4F1o, C5 F1 2, C6 F 1 4 and C7F16 , and emission inventories of C4Fio, C5 F1 2 and C6 F14 are also reported to the United Nations' Framework Convention on Climate Change (UNFCCC) by Annex 1 countries that have ratified the Kyoto Protocol (European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL), 2009; United National Framework Convention on Climate Change Secretariat, 2011). The atmospheric observation-based emission estimates are 20 times larger than EDGARv4.2 for C4F10 and over three orders of magnitude larger for C5F1 2 . In contrast, the top-down emission estimates for C6F14 largely agree with the bottom-up estimates from EDGARv4.2. Moreover, the top-down C7 F16 emission estimates are comparable to those of EDGARv4.2 at their peak in the 1990s, albeit with significant underestimation by EDGARv4.2 for the other time periods. There are no bottom-up emission estimates for C8Fi8 , thus the emission rates reported here are the first for this gas. In general, the emission inventories for C4Fio, C5F1 2 and C6F 14 reported to the UNFCCC are five to ten times lower than those estimated in this study from observations. This underreporting to the UNFCCC may be due to only Annex 1 countries reporting inventories and also that some of these countries report a total PFC mixture in C0 2-equivalents, instead of individual PFC emissions rates.by Diane Jean Ivy.Ph.D

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Public COAPI Toolkit of Open Access Policy Resources

The Coalition of Open Access Policy Institutions (COAPI, https://sparcopen.org/coapi ) is committed to sharing information and resources to assist in the development and implementation of institutional Open Access (OA) policies. The COAPI Toolkit includes a diverse collection of resources that COAPI members have developed in the course of their OA policy initiatives. These resources are openly accessible and published here under Creative Commons Attribution 4.0 licenses, unless otherwise noted on the resources themselves

Paediatric COVID-19 mortality: a database analysis of the impact of health resource disparity

Background The impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries.Methods The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria.Results A total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)).Conclusion Mortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities