Monumental heritage exposure to urban black carbon pollution

In this study, aerosol light-absorption measurements obtained at three sites during a winter campaign were used to analyse and identify the major sources of Black Carbon (BC) particles in and around the Alhambra monument, a UNESCO World Heritage Site that receives over 2 million visitors per year. The Conditional Bivariate Probability Function and the Aethalometer model were employed to identify the main sources of BC particles and to estimate the contributions of biomass burning and fossil fuel emissions to the total Equivalent Black Carbon (EBC) concentrations over the monumental complex. Unexpected high levels of EBC were found at the Alhambra, comparable to those measured in relatively polluted European urban areas during winter. EBC concentrations above 3.0 μg/m3, which are associated with unacceptable levels of soiling and negative public reactions, were observed at Alhambra monument on 13 days from 12 October 2015 to 29 February 2016, which can pose a risk to its long-term conservation and may cause negative social and economic impacts. It was found that road traffic emissions from the nearby urban area and access road to the Alhambra were the main sources of BC particles over the monument. However, biomass burning emissions were found to have very small impact on EBC concentrations at the Alhambra. The highest EBC concentrations were observed during an extended stagnant episode associated with persistent high-pressure systems, reflecting the large impact that can have these synoptic conditions on BC over the Alhambra.European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 654109, ACTRIS-2.Spanish Ministry of Economy and Competitiveness and FEDER through project CGL2013-45410-R, CGL2016-81092-R 598 and CGL2012-30729.Andalusia Regional Government through project P12- RNM-2409 and P12-FQM-1889

Drop the Likelihood Ratio A Novel Non-electronic Tool for Interpreting Diagnostic Test Results

Objective: To present a geometric ruler to determine predictive values of binary diagnostic test results from prevalence, sensitivity and specificity without calculation. Methods: On logarithmic scale the relationships between pre-/post-test odds and the likelihood ratio as well as sensitivity, specificity and the likelihood ratio appear as simple linear (additive) equations. Results: Each of these additive equations can be solved geometrically in form of a ruler with three scales. By amalgamation we devise a novel non-electronic tool which omits the intermediate step of likelihood ratio determination. Conclusions: We propose a simple geometric method to aid in interpretation of diagnostic test results for both practical and educational purposes

Drop the Likelihood Ratio

Objective: To present a geometric ruler to determine predictive values of binary diagnostic test results from prevalence, sensitivity and specificity without calculation. Methods: On logarithmic scale the relationships between pre-/post-test odds and the likelihood ratio as well as sensitivity, specificity and the likelihood ratio appear as simple linear (additive) equations. Results: Each of these additive equations can be solved geometrically in form of a ruler with three scales. By amalgamation we devise a novel non-electronic tool which omits the intermediate step of likelihood ratio determination. Conclusions: We propose a simple geometric method to aid in interpretation of diagnostic test results for both practical and educational purposes

Source apportionment of PM10, organic carbon and elemental carbon at Swiss sites: An intercomparison of different approaches

International audienc

Overview of the impact of wood burning emissions on carbonaceous aerosols and PM in large parts of the Alpine region

International audienc