Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)

Reactive gases and aerosols are produced by terrestrial ecosystems, processed within plant canopies, and can then be emitted into the above-canopy atmosphere. Estimates of the above-canopy fluxes are needed for quantitative earth system studies and assessments of past, present and future air quality and climate. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) is described and used to quantify net terrestrial biosphere emission of isoprene into the atmosphere. MEGAN is designed for both global and regional emission modeling and has global coverage with ~1 km² spatial resolution. Field and laboratory investigations of the processes controlling isoprene emission are described and data available for model development and evaluation are summarized. The factors controlling isoprene emissions include biological, physical and chemical driving variables. MEGAN driving variables are derived from models and satellite and ground observations. Tropical broadleaf trees contribute almost half of the estimated global annual isoprene emission due to their relatively high emission factors and because they are often exposed to conditions that are conducive for isoprene emission. The remaining flux is primarily from shrubs which have a widespread distribution. The annual global isoprene emission estimated with MEGAN ranges from about 500 to 750 Tg isoprene (440 to 660 Tg carbon) depending on the driving variables which include temperature, solar radiation, Leaf Area Index, and plant functional type. The global annual isoprene emission estimated using the standard driving variables is ~600 Tg isoprene. Differences in driving variables result in emission estimates that differ by more than a factor of three for specific times and locations. It is difficult to evaluate isoprene emission estimates using the concentration distributions simulated using chemistry and transport models, due to the substantial uncertainties in other model components, but at least some global models produce reasonable results when using isoprene emission distributions similar to MEGAN estimates. In addition, comparison with isoprene emissions estimated from satellite formaldehyde observations indicates reasonable agreement. The sensitivity of isoprene emissions to earth system changes (e.g., climate and land-use) demonstrates the potential for large future changes in emissions. Using temperature distributions simulated by global climate models for year 2100, MEGAN estimates that isoprene emissions increase by more than a factor of two. This is considerably greater than previous estimates and additional observations are needed to evaluate and improve the methods used to predict future isoprene emissions

Technical Note: Fast two-dimensional GC-MS with thermal extraction for anhydro-sugars in fine aerosols

A fast two-dimensional gas chromatography (GC-MS) method that uses heart-cutting and thermal extraction (TE) and requires no chemical derivatization was developed for the determination of anhydro-sugars in fine aerosols. Evaluation of the TE-GC-GC-MS method shows high average relative accuracy (≥90%), reproducibility (≤10% relative standard deviation), detection limits of less than 3 ng/μL, and negligible carryover for levoglucosan, mannosan, and galactosan markers. TE-GC-GC-MS- and solvent extraction (SE)-GC-MS-measured levoglucosan concentrations correlate across several diverse types of biomass burning aerosols. Because the SE-GC-MS measurements were taken 8 years prior to the TE-GC-GC-MS ones, the stability of levoglucosan is established for quartz filter-collected biomass burning aerosol samples stored at ultra-low temperature (−50 °C). Levoglucosan concentrations (w/w) in aerosols collected following atmospheric dilution near open fires of varying intensity are similar to those in biomass burning aerosols produced in a laboratory enclosure. An average levoglucosan-mannosan-galactosan ratio of 15:2:1 is observed for these two aerosol sets. TE-GC-GC-MS analysis of atmospheric aerosols from the US and Africa produced levoglucosan concentrations (0.01–1.6 μg/m<sup>3</sup>) well within those reported for aerosols collected globally and examined using different analytical techniques (0.004–7.6 μg/m<sup>3</sup>). Further comparisons among techniques suggest that fast TE-GC-GC-MS is among the most sensitive, accurate, and precise methods for compound-specific quantification of anhydro-sugars. In addition, an approximately twofold increase in anhydro-sugar determination may be realized when combining TE with fast chromatography

Towards Emotion Recognition: A Persistent Entropy Application

Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (calm, happy, sad, angry, fearful, disgust and surprised)

Galaxy And Mass Assembly: Galaxy Zoo spiral arms and star formation rates

Understanding the effect spiral structure has on star formation properties of galaxies is important to complete our picture of spiral structure evolution. Previous studies have investigated connections between spiral arm properties and star formation, but the effect that the number of spiral arms has on this process is unclear. Here, we use the Galaxy And Mass Assembly (GAMA) survey paired with the citizen science visual classifications from the Galaxy Zoo project to explore galaxies’ spiral arm number and how it connects to the star formation process. We use the votes from the GAMA-Kilo Degree Survey Galaxy Zoo classification to investigate the link between spiral arm number and stellar mass, star formation rate, and specific star formation rate (sSFR). We find that galaxies with fewer spiral arms have lower stellar masses and higher sSFRs, while those with more spiral arms tend towards higher stellar masses and lower sSFRs, and conclude that galaxies are less efficient at forming stars if they have more spiral arms. We note how previous studies’ findings may indicate a cause for this connection in spiral arm strength or opacity

Estimations of isoprenoid emission capacity from enclosure studies: measurements, data processing, quality and standardized measurement protocols

The capacity for volatile isoprenoid production under standardized environmental conditions at a certain time (ES, the emission factor) is a key characteristic in constructing isoprenoid emission inventories. However, there is large variation in published ES estimates for any given species partly driven by dynamic modifications in ES due to acclimation and stress responses. Here we review additional sources of variation in ES estimates that are due to measurement and analytical techniques and calculation and averaging procedures, and demonstrate that estimations of ES critically depend on applied experimental protocols and on data processing and reporting. A great variety of experimental setups has been used in the past, contributing to study-to-study variations in ES estimates. We suggest that past experimental data should be distributed into broad quality classes depending on whether the data can or cannot be considered quantitative based on rigorous experimental standards. Apart from analytical issues, the accuracy of ES values is strongly driven by extrapolation and integration errors introduced during data processing. Additional sources of error, especially in meta-database construction, can further arise from inconsistent use of units and expression bases of ES. We propose a standardized experimental protocol for BVOC estimations and highlight basic meta-information that we strongly recommend to report with any ES measurement. We conclude that standardization of experimental and calculation protocols and critical examination of past reports is essential for development of accurate emission factor databases.JRC.H.7-Climate Risk Managemen

Measurement and interpretation of isoprene fluxes and isoprene, methacrolein, and methyl vinyl ketone mixing ratios at the PROPHET site during the 1998 Intensive

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95460/1/jgrd8697.pd

On predicting the outcomes of chemotherapy treatments in Breast cancer

Chemotherapy is the main treatment commonly used for treating cancer patients. However, chemotherapy usually causes side effects some of which can be severe. The effects depend on a variety of factors including the type of drugs used, dosage, length of treatment and patient characteristics. In this paper, we use a data extraction from an oncology department in Scotland with information on treatment cycles, recorded toxicity level, and various observations concerning breast cancer patients for three years. The objective of our paper is to compare several different techniques applied to the same data set to predict the toxicity outcome of the treatment. We use a Markov model, Hidden Markov model, Random Forest and Recurrent Neural Network in our comparison. Through analysis and evaluation of the performance of these techniques, we can determine which method is more suitable in different situations to assist the medical oncologist in real-time clinical practice. We discuss the context of our work more generally and further work.Postprin

Galaxy And Mass Assembly:Galaxy Zoo spiral arms and star formation rates

Understanding the effect spiral structure has on star formation properties of galaxies is important to complete our picture of spiral structure evolution. Previous studies have investigated connections between spiral arm properties and star formation, but the effect that the number of spiral arms has on this process is unclear. Here, we use the Galaxy And Mass Assembly (GAMA) survey paired with the citizen science visual classifications from the Galaxy Zoo project to explore galaxies’ spiral arm number and how it connects to the star formation process. We use the votes from the GAMA-Kilo Degree Survey Galaxy Zoo classification to investigate the link between spiral arm number and stellar mass, star formation rate, and specific star formation rate (sSFR). We find that galaxies with fewer spiral arms have lower stellar masses and higher sSFRs, while those with more spiral arms tend towards higher stellar masses and lower sSFRs, and conclude that galaxies are less efficient at forming stars if they have more spiral arms. We note how previous studies’ findings may indicate a cause for this connection in spiral arm strength or opacity