Airborne Emissions from 1961 to 2004 of Benzo[a]pyrene from U.S. Vehicles per km of Travel Based on Tunnel Studies

We identified 13 historical measurements of polycyclic aromatic hydrocarbons (PAHs) in U.S. vehicular traffic tunnels that were either directly presented as tailpipe emission factors in μg per vehicle-kilometer or convertible to such a form. Tunnel measurements capture fleet cruise emissions. Emission factors for benzo[a]pyrene (BaP) for a tunnel fleet operating under cruise conditions were highest prior to the 1980s and fell from more than 30-μg per vehicle-km to approximately 2-μg/km in the 1990s, an approximately 15-fold decline. Total annual U.S. (cruise) emissions of BaP dropped by a lesser factor, because total annual km driven increased by a factor of 2.7 during the period. Other PAH compounds measured in tunnels over the 40-year period (e.g., benzo[ghi]perylene, coronene) showed comparable reduction factors in emissions. PAH declines were comparable to those measured in tunnels for carbon monoxide, volatile organic compounds, and particulate organic carbon. The historical PAH “source terms” determined from the data are relevant to quantifying the benefits of emissions control technology and can be used in epidemiological studies evaluating the health effects of exposure, such as those undertaken with breast cancer in New York State

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines

Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes

Abstract: Purpose: This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science. Methods: Web of Science and Google Scholar were used to review published papers spanning the period 2013–2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018–2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017. Scope: Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing. Conclusions: The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach