Trends in Prenatal Sex Selection and Girls' Nutritional Status in India
In: CESifo economic studies: a joint initiative of the University of Munich's Center for Economic Studies and the Ifo Institute, Volume 58, Issue 2, p. 348-372
ISSN: 1612-7501
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In: CESifo economic studies: a joint initiative of the University of Munich's Center for Economic Studies and the Ifo Institute, Volume 58, Issue 2, p. 348-372
ISSN: 1612-7501
The Qin-Ba Ecological Functional Zone is a component of China's ecological security pattern designed to protect the regional ecosystem and maintain biodiversity. However, due to the impact of mining and urban encroachment, the plight of a sustainable ecosystem in the Qin-Ba mountainous area is deteriorating. This paper has used a remote sensing and geographic information system (GIS) to examine the impacts of mining and urban encroachment on the environment in the Qin-Ba mountainous area. The results indicate that the total mined area in 2013 was 22 km² and is predicted to escalate. Results also show that the ecosystems in Fengxian County, Shaanxi Province and Baokang County, Hubei Province were most severely affected by mining. Urbanization in the Qin-Ba mountainous area has seen an increase of 85.58 km² in urban land use from 2010 to 2013. In addition, infrastructure development including airport construction, tourism resorts and real estate development in the Qin-Ba mountainous area has intensified environmental and biodiversity disturbances since large areas of forest have been cleared. Our results should provide insight and assistance to city planners and government officials in making informed decisions. ; Xinliang Xu, Hongyan Cai, Daowei Sun, Lan Hu and Kwamina E. Banson
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In: Materials and design, Volume 160, p. 48-57
ISSN: 1873-4197
49 pags, 10 figs, 2 tabs. -- Supplementary data is available at the Publisher's web ; The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty. ; A portion of the work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the NASA Aeronautics and Space Administration. A portion of the work was carried out the National Center for Atmospheric Research, which is operated by the University Corporation for Atmospheric Research under sponsorship of the National Science Foundation. PY acknowledges support from the Faculty of Science and Technology, Lancaster University. JB and UI acknowledge NordForsk under the Nordic Programme on Health and Welfare Project #75007: Understanding the link between air pollution and distribution of related health impacts and welfare in the Nordic countries (Nordic Welf Air); and the H2020-LCE project: Role of technologies in an energy efficient economy – model based analysis policy measures and transformation pathways to a sustainable energy system (REEEM), Grant agreement no.: 691739. GZ acknowledges the New Zealand Government's Strategic Science Investment Fund (SSIF) through the NIWA programme CACV. This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/N027736/1] and the Natural Environment Research Council [grant number NE/N003411/1]. ; Peer reviewed
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53 pags., 19 figs., 1 tab. ; Our understanding of the processes that control the burden and budget of tropospheric ozone has changed dramatically over the last 60 years. Models are the key tools used to understand these changes, and these underscore that there are many processes important in controlling the tropospheric ozone budget. In this critical review, we assess our evolving understanding of these processes, both physical and chemical. We review model simulations from the International Global Atmospheric Chemistry Atmospheric Chemistry and Climate Model Intercomparison Project and Chemistry Climate Modelling Initiative to assess the changes in the tropospheric ozone burden and its budget from 1850 to 2010. Analysis of these data indicates that there has been significant growth in the ozone burden from 1850 to 2000 (approximately 43 ± 9%) but smaller growth between 1960 and 2000 (approximately 16 ± 10%) and that the models simulate burdens of ozone well within recent satellite estimates. The Chemistry Climate Modelling Initiative model ozone budgets indicate that the net chemical production of ozone in the troposphere plateaued in the 1990s and has not changed since then inspite of increases in the burden. There has been a shift in net ozone production in the troposphere being greatest in the northern mid and high latitudes to the northern tropics, driven by the regional evolution of precursor emissions. An analysis of the evolution of tropospheric ozone through the 21st century, as simulated by Climate Model Intercomparison Project Phase 5 models, reveals a large source of uncertainty associated with models themselves (i.e., in the way that they simulate the chemical and physical processes that control tropospheric ozone). This structural uncertainty is greatest in the near term (two to three decades), but emissions scenarios dominate uncertainty in the longer term (2050¿2100) evolution of tropospheric ozone. This intrinsic model uncertainty prevents robust predictions of near-term changes in the tropospheric ozone burden, and we review how progress can be made to reduce this limitation. ; ATA and PTG would like to acknowledge support from National Centre for Atmospheric Science. YE would like to acknowledge support from the National Science Foundation Atmospheric and Geospace Sciences awards # 1900795 and 1929368. TW acknowledges support from the Hong Kong Research Grants Council (T24-504/17-N) and the National Natural Science Foundation of China (91844301). ASL thanks European Executive Agency under the European Union's Horizon 2020 Research Innovation programme (Project "ERC-2016-COG 726349 CLIMAHAL"). RH is supported by an NERC Independent Research Fellowship (NE/N014375/1). YMS is supported by an NERC PhD studentship. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
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The Montreal Protocol (MP) controls the production and consumption of carbon tetrachloride (CCl4 or CTC) and other ozone-depleting substances (ODSs) for emissive uses. CCl4 is a major ODS, accounting for about 12% of the globally averaged inorganic chlorine and bromine in the stratosphere, compared to 14% for CFC-12 in 2012. In spite of the MP controls, there are large ongoing emissions of CCl4 into the atmosphere. Estimates of emissions from various techniques ought to yield similar numbers. However, the recent WMO/UNEP Scientific Assessment of Ozone Depletion [WMO, 2014] estimated a 2007-2012 CCl4 bottom-up emission of 1-4 Gg/year (1-4 kilotonnes/year), based on country-by-country reports to UNEP, and a global top-down emissions estimate of 57 Gg/ year, based on atmospheric measurements. This 54 Gg/year difference has not been explained. In order to assess the current knowledge on global CCl4 sources and sinks, stakeholders from industrial, governmental, and the scientific communities came together at the "Solving the Mystery of Carbon Tetrachloride" workshop, which was held from 4-6 October 2015 at Empa in Dübendorf, Switzerland. During this workshop, several new findings were brought forward by the participants on CCl4 emissions and related science. • Anthropogenic production and consumption for feedstock and process agent uses (e.g., as approved solvents) are reported to UNEP under the MP. Based on these numbers, global bottom-up emissions of 3 (0-8) Gg/year are estimated for 2007-2013 in this report. This number is also reasonably consistent with this report's new industry-based bottom-up estimate for fugitive emissions of 2 Gg/year. • By-product emissions from chloromethanes and perchloroethylene plants are newly proposed in this report as significant CCl4 sources, with global emissions estimated from these plants to be 13 Gg/year in 2014. • This report updates the anthropogenic CCl4 emissions estimation as a maximum of ~25 Gg/year. This number is derived by combining the above fugitive and by-product emissions (2 Gg/year and 13 Gg/year, respectively) with 10 Gg/year from legacy emissions plus potential unreported inadvertent emissions from other sources. • Ongoing atmospheric CCl4 measurements within global networks have been exploited for assessing regional emissions. In addition to existing emissions estimates from China and Australia, the workshop prompted research on emissions in the U.S. and Europe. The sum of these four regional emissions is estimated as 21±7.5a Gg/year, but this is not a complete global accounting. These regional top-down emissions estimates also show that most of the CCl4 emissions originate from chemical industrial regions, and are not linked to major population centres. • The total CCl4 lifetime is critical for calculating top-down global emissions. CCl4 is destroyed in the stratosphere, oceans, and soils, complicating the total lifetime estimate. The atmospheric lifetime with respect to stratospheric loss was recently revised to 44 (36-58) years, and remains unchanged in this report. New findings from additional measurement campaigns and reanalysis of physical parameters lead to changes in the ocean lifetime from 94 years to 210 (157-313) years, and in the soil lifetime from 195 years to 375 (288-536) years. • These revised lifetimes lead to an increase of the total lifetime from 26 years in WMO [2014] to 33 (28-41) years. Consequently, CCl4 is lost at a slower rate from the atmosphere. With this new total lifetime, the global top-down emissions calculation decreases from 57 (40-74) Gg/year in WMO [2014] to 40 (25-55) Gg/year. This estimate is relatively consistent with the independent gradient top-down emissions of 30 (25-35) Gg/year, based upon differences between atmospheric measurements of CCl4 in the Northern and Southern Hemispheres. In addition, this new total lifetime implies an upper limit of 3-4 Gg/year of natural emissions, based upon newly reported observations of old air in firn snow. These new CCl4 emissions estimates from the workshop make considerable progress toward closing the emissions discrepancy. The new industrial bottom-up emissions estimate (15 Gg/year total) includes emissions from chloromethanes plants (13 Gg/year) and feedstock fugitive emissions (2 Gg/year). When combined with legacy emissions and unreported inadvertent emissions, this could be up to 25 Gg/year. Top-down emissions estimates are: global 40 (25-55) Gg/year, gradient 30 (25-35) Gg/year, and regional 21 (14-28) Gg/year. While the new bottom-up value is still less than the aggregated top-down values, these estimates reconcile the CCl4 budget discrepancy when considered at the edges of their uncertainties. ; Peer reviewed
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The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project. ; Google; NumFOCUS; Python Software Foundation; Space Telescope Science Institute; Harvard-Smithsonian Center for Astrophysics; South African Astronomical Observatory; National Aeronautics and Space Administration through the Smithsonian Astrophysical Observatory [SV3-73016]; National Aeronautics Space Administration [NAS8-03060]; UW eScience Institute via Moore Foundation; Sloan Foundation; Washington Research Foundation; NASA's Planetary Astronomy Program; NASA [NAS8-03060, NAS 5-26555]; NASA through Hubble Fellowship - Space Telescope Science Institute [51316.01]; Giacconi Fellowship; FONDECYT [1170618]; MINEDUC-UA [ANT 1655, ANT 1656]; German Research Foundation (DFG) [SFB 881]; German Research Foundation (DFG); NSF [AST-1313484]; Spanish government [AYA2016-75808-R]; Gemini Observatory; Korea Astronomy and Space Science Institute, under the RD program ; The Astropy community is supported by and makes use of a number of organizations and services outside the traditional academic community. We thank Google for financing and organizing the Google Summer of Code (GSoC) program, that has funded several students per year to work on Astropy related projects over the summer. These students often turn into longterm contributors. We also thank NumFOCUS and the Python Software Foundation for financial support. Within the academic community, we thank institutions that make it possible for astronomers and other developers on their staff to contribute their time to the development of Astropy projects. We acknowledge the support of the Space Telescope Science Institute, Harvard-Smithsonian Center for Astrophysics, and the South African Astronomical Observatory.r The following individuals would like to recognize support for their personal contributions. H.M.G. was supported by the National Aeronautics and Space Administration through the Smithsonian Astrophysical Observatory contract SV3-73016 to MIT for Support of the Chandra X-Ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of the National Aeronautics Space Administration under contract NAS8-03060. J.T.V. was supported by the UW eScience Institute via grants from the Moore Foundation, the Sloan Foundation, and the Washington Research Foundation. S.M.C. acknowledges the National Research Foundation of South Africa. M.V.B. was supported by NASA's Planetary Astronomy Program. T.L.A. was supported by NASA contract NAS8-03060. Support for E.J.T. was provided by NASA through Hubble Fellowship grant No. 51316.01 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS 5-26555, as well as a Giacconi Fellowship. M.B. was supported by the FONDECYT regular project 1170618 and the MINEDUC-UA projects codes ANT 1655 and ANT 1656. D.H. was supported through the SFB 881 "The Milky Way System" by the German Research Foundation (DFG). W.E.K was supported by an ESO Fellowship. C.M. is supported by NSF grant AST-1313484. S.P. was supported by grant AYA2016-75808-R (FEDER) issued by the Spanish government. J.E.H.T. was supported by the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., on behalf of the international Gemini partnership of Argentina, Brazil, Canada, Chile, and the United States of America. Y.P.B was supported by the Korea Astronomy and Space Science Institute, under the R&D program supervised by the Ministry of Science, ICT, and Future Planning.
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The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project.© 2018. The American Astronomical Society. ; The Astropy community is supported by and makes use of a number of organizations and services outside the traditional academic community. We thank Google for financing and organizing the Google Summer of Code (GSoC) program, that has funded several students per year to work on Astropy related projects over the summer. These students often turn into longterm contributors. We also thank NumFOCUS and the Python Software Foundation for financial support. Within the academic community, we thank institutions that make it possible for astronomers and other developers on their staff to contribute their time to the development of Astropy projects. We acknowledge the support of the Space Telescope Science Institute, Harvard-Smithsonian Center for Astrophysics, and the South African Astronomical Observatory.r The following individuals would like to recognize support for their personal contributions. H.M.G. was supported by the National Aeronautics and Space Administration through the Smithsonian Astrophysical Observatory contract SV3-73016 to MIT for Support of the Chandra X-Ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of the National Aeronautics Space Administration under contract NAS8-03060. J.T.V. was supported by the UW eScience Institute via grants from the Moore Foundation, the Sloan Foundation, and the Washington Research Foundation. S.M.C. acknowledges the National Research Foundation of South Africa. M.V.B. was supported by NASA's Planetary Astronomy Program. T.L.A. was supported by NASA contract NAS8-03060. Support for E.J.T. was provided by NASA through Hubble Fellowship grant No. 51316.01 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS 5-26555, as well as a Giacconi Fellowship. M.B. was supported by the FONDECYT regular project 1170618 and the MINEDUC-UA projects codes ANT 1655 and ANT 1656. D.H. was supported through the SFB 881 >The Milky Way System> by the German Research Foundation (DFG). W.E.K was supported by an ESO Fellowship. C.M. is supported by NSF grant AST-1313484. S.P. was supported by grant AYA2016-75808-R (FEDER) issued by the Spanish government. J.E.H.T. was supported by the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., on behalf of the international Gemini partnership of Argentina, Brazil, Canada, Chile, and the United States of America. Y.P.B was supported by the Korea Astronomy and Space Science Institute, under the R&D program supervised by the Ministry of Science, ICT, and Future Planning.
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Background: The COVID-19 pandemic has disrupted routine hospital services globally. This study estimated the total number of adult elective operations that would be cancelled worldwide during the 12 weeks of peak disruption due to COVID-19. Methods: A global expert response study was conducted to elicit projections for the proportion of elective surgery that would be cancelled or postponed during the 12 weeks of peak disruption. A Bayesian β-regression model was used to estimate 12-week cancellation rates for 190 countries. Elective surgical case-mix data, stratified by specialty and indication (surgery for cancer versus benign disease), were determined. This case mix was applied to country-level surgical volumes. The 12-week cancellation rates were then applied to these figures to calculate the total number of cancelled operations. Results: The best estimate was that 28 404 603 operations would be cancelled or postponed during the peak 12 weeks of disruption due to COVID-19 (2 367 050 operations per week). Most would be operations for benign disease (90·2 per cent, 25 638 922 of 28 404 603). The overall 12-week cancellation rate would be 72·3 per cent. Globally, 81·7 per cent of operations for benign conditions (25 638 922 of 31 378 062), 37·7 per cent of cancer operations (2 324 070 of 6 162 311) and 25·4 per cent of elective caesarean sections (441 611 of 1 735 483) would be cancelled or postponed. If countries increased their normal surgical volume by 20 per cent after the pandemic, it would take a median of 45 weeks to clear the backlog of operations resulting from COVID-19 disruption. Conclusion: A very large number of operations will be cancelled or postponed owing to disruption caused by COVID-19. Governments should mitigate against this major burden on patients by developing recovery plans and implementing strategies to restore surgical activity safely.
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