88 research outputs found
Detectability of gravitational wave events by spherical resonant-mass antennas
We have calculated signal-to-noise ratios for eight spherical resonant-mass
antennas interacting with gravitational radiation from inspiralling and
coalescing binary neutron stars and from the dynamical and secular bar-mode
instability of a rapidly rotating star. We find that by using technology that
could be available in the next several years, spherical antennas can detect
neutron star inspiral and coalescence at a distance of 15 Mpc and the dynamical
bar-mode instability at a distance of 2 Mpc.Comment: 39 pages, 4 EPS Figures, some additional SNRs for secular
instabilities, some changes to LIGO SNRs, Appendix added on the asymptotic
expansion of energy sensitivity, corrected supernova rates. Results available
at http://www.physics.umd.edu/rgroups/gen_rel_exp/snr.html Submitted to Phys.
Rev.
Comparison of advanced gravitational-wave detectors
We compare two advanced designs for gravitational-wave antennas in terms of
their ability to detect two possible gravitational wave sources. Spherical,
resonant mass antennas and interferometers incorporating resonant sideband
extraction (RSE) were modeled using experimentally measurable parameters. The
signal-to-noise ratio of each detector for a binary neutron star system and a
rapidly rotating stellar core were calculated. For a range of plausible
parameters we found that the advanced LIGO interferometer incorporating RSE
gave higher signal-to-noise ratios than a spherical detector resonant at the
same frequency for both sources. Spheres were found to be sensitive to these
sources at distances beyond our galaxy. Interferometers were sensitive to these
sources at far enough distances that several events per year would be expected
Ambient particulate matter air pollution exposure and mortality in the NIH-AARP diet and health cohort
BACKGROUND: Outdoor fine particulate matter (†2.5 ÎŒm; PM2.5) has been identified as a global health threat, but the number of large U.S. prospective cohort studies with individual participant data remains limited, especially at lower recent exposures. OBJECTIVES: We aimed to test the relationship between long-term exposure PM2.5 and death risk from all nonaccidental causes, cardiovascular (CVD), and respiratory diseases in 517,041 men and women enrolled in the National Institutes of Health-AARP cohort. METHODS: Individual participant data were linked with residence PM2.5 exposure estimates across the continental United States for a 2000â2009 follow-up period when matching census tractâlevel PM2.5 exposure data were available. Participants enrolled ranged from 50 to 71 years of age, residing in six U.S. states and two cities. Cox proportional hazard models yielded hazard ratio (HR) estimates per 10 ÎŒg/m3 of PM2.5 exposure. RESULTS: PM2.5 exposure was significantly associated with total mortality (HR = 1.03; 95% CI: 1.00, 1.05) and CVD mortality (HR = 1.10; 95% CI: 1.05, 1.15), but the association with respiratory mortality was not statistically significant (HR = 1.05; 95% CI: 0.98, 1.13). A significant association was found with respiratory mortality only among never smokers (HR = 1.27; 95% CI: 1.03, 1.56). Associations with 10-ÎŒg/m3 PM2.5 exposures in yearly participant residential annual mean, or in metropolitan area-wide mean, were consistent with baseline exposure model results. Associations with PM2.5 were similar when adjusted for ozone exposures. Analyses of California residents alone also yielded statistically significant PM2.5 mortality HRs for total and CVD mortality. CONCLUSIONS: Long-term exposure to PM2.5 air pollution was associated with an increased risk of total and CVD mortality, providing an independent test of the PM2.5âmortality relationship in a new large U.S. prospective cohort experiencing lower post-2000 PM2.5 exposure levels. CITATION: Thurston GD, Ahn J, Cromar KR, Shao Y, Reynolds HR, Jerrett M, Lim CC, Shanley R, Park Y, Hayes RB. 2016. Ambient particulate matter air pollution exposure and mortality in the NIH-AARP Diet and Health cohort. Environ Health Perspect 124:484â490; http://dx.doi.org/10.1289/ehp.150967
Comprehensive evidence implies a higher social cost of CO2
The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in beneftâcost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer refect the latest research. The report provided a series of recommendations for improving the scientifc basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively refect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is 44â51âper tCO2. Our estimates incorporate updated scientifc understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefts of greenhouse gas mitigation and thereby increase the expected net benefts of more stringent climate policies
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