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 benefit-cost 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 reflect the latest research. The report provided a series of recommendations for improving the scientific 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 reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific 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 benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

Bayesian probabilistic projections of life expectancy for all countries.

We propose a Bayesian hierarchical model for producing probabilistic forecasts of male period life expectancy at birth for all the countries of the world to 2100. Such forecasts would be an input to the production of probabilistic population projections for all countries, which is currently being considered by the United Nations. To evaluate the method, we conducted an out-of-sample cross-validation experiment, fitting the model to the data from 1950-1995 and using the estimated model to forecast for the subsequent 10 years. The 10-year predictions had a mean absolute error of about 1 year, about 40 % less than the current UN methodology. The probabilistic forecasts were calibrated in the sense that, for example, the 80 % prediction intervals contained the truth about 80 % of the time. We illustrate our method with results from Madagascar (a typical country with steadily improving life expectancy), Latvia (a country that has had a mortality crisis), and Japan (a leading country). We also show aggregated results for South Asia, a region with eight countries. Free, publicly available R software packages called bayesLife and bayesDem are available to implement the method.

Good short-term but not long-term reproducibility of the antiplatelet efficacy laboratory assessment.

BACKGROUND: The antiplatelet effect of acetylsalicylic acid (ASA) varies among individual patients. We assessed the short-term reproducibility (STR) and long-term reproducibility (LTR) of light transmission aggregometry (LTA). METHODS: Residual platelet reactivity was measured twice using LTA in a group of 207 consecutive patients (56 females, mean age 67 ± 9 years) on ASA therapy in 10 ± 6 months interval. The STR was assessed in 15 patients (6 females, mean age 61 ± 7 years) with 10 measurements on 2 consecutive days. RESULTS: There was no correlation between both measurements in the long-term part of the study, and also Bland-Altman plot showed a diverging pattern. However, LTA STR was good with a correlation coefficient of .800 (P < .05) confirmed by Bland-Altman plot. CONCLUSIONS: Although short-term intraindividual reproducibility of LTA assessment of platelet reactivity is very good, in the long-term perspective the antiplatelet ASA effectivity may be influenced by additional variables and repeated measurements are warranted.