Development and characterization of an aircraft aerosol time-of-flight mass spectrometer.

Vertical and horizontal profiles of atmospheric aerosols are necessary for understanding the impact of air pollution on regional and global climate. To gain further insight into the size-resolved chemistry of individual atmospheric particles, a smaller aerosol time-of-flight mass spectrometer (ATOFMS) with increased data acquisition capabilities was developed for aircraft-based studies. Compared to previous ATOFMS systems, the new instrument has a faster data acquisition rate with improved ion transmission and mass resolution, as well as reduced physical size and power consumption, all required advances for use in aircraft studies. In addition, real-time source apportionment software allows the immediate identification and classification of individual particles to guide sampling decisions while in the field. The aircraft (A)-ATOFMS was field-tested on the ground during the Study of Organic Aerosols in Riverside, CA (SOAR) and aboard an aircraft during the Ice in Clouds Experiment-Layer Clouds (ICE-L). Initial results from ICE-L represent the first reported aircraft-based single-particle dual-polarity mass spectrometry measurements and provide an increased understanding of particle mixing state as a function of altitude. Improved ion transmission allows for the first single-particle detection of species out to approximately m/z 2000, an important mass range for the detection of biological aerosols and oligomeric species. In addition, high time resolution measurements of single-particle mixing state are demonstrated and shown to be important for airborne studies where particle concentrations and chemistry vary rapidly.

Real-time, single-particle measurements of oligomers in aged ambient aerosol particles.

Unique high mass negative ions in the -200 to -400 mass/charge range with repetitive spacings of 12, 14, and 16 units, representative of oligomeric species, have been detected in single ambient submicrometer aerosol particles using real-time single-particle mass spectrometry during the Study of Organic Aerosols field campaign conducted in Riverside, CA (SOAR) in August and November 2005. These oligomer-containing particles represented 33-40% of the total detected particles and contained other indicators of aging including oxidized organic carbon, amine, nitrate, and sulfate ion markers. Overall, the highest mass oligomeric patterns were observed in small acidic 140-200 nm particles in the summer. Also during the summer, increased oligomer intensities were observed when the particles were heated with a thermodenuder. We hypothesize that heat removed semivolatile species, thereby increasing particle acidity, while concentrating the oligomeric precursors and accelerating oligomer formation. Differences in oligomer behavior with respect to particle size and heating can be attributed to seasonal differences in photochemical oxidation, the relative amount of ammonium, and particle acidity.

Aerosol time-of-flight mass spectrometry data analysis: a benchmark of clustering algorithms.

Airborne particulate matter is an important component of atmospheric pollution, affecting human health, climate, and visibility. Modern instruments allow single particles to be analyzed one-by-one in real time, and offer the promise of determining the sources of individual particles based on their mass spectral signatures. The large number of particles to be apportioned makes clustering a necessary step. The goal of this study is to compare using mass spectral data the accuracy and speed of several clustering algorithms: ART-2a, several variants of hierarchical clustering, and K-means. Repeated simulations with various algorithms and different levels of data preprocessing suggest that hierarchical clustering methods using derivatives of Ward's algorithm discriminate sources with fewer errors than ART-2a, which itself discriminates much better than point-wise hierarchical clustering methods. In most cases, K-means algorithms do almost as well as the best hierarchical clustering. These efficient algorithms (clustering derived from Ward's algorithm, ART-2a and K-means) are most accurate when the relative peak areas have been pre-scaled by taking the square root. Analysis times vary within a factor of 30, and when accuracy above 95% is required, run times scale up as the square of the number of particles. Algorithms derived from Ward's remain the most accurate under a wide range of conditions and conversely, for an equal accuracy, can deliver a shorter list of clusters, allowing faster and maybe on-the-fly classification.

Image-dependent interaction of imagery and vision.

The influence of imagery on perception depends on the content of the mental image. Sixty-three students responded to the location of the 2 hands of a clock while visualizing the correct or an incorrect clock. Reaction time was shorter with valid cueing. Could this have resulted from visual acquisition strategies such as planning visual saccades or shifting covert attention? No. In this study, a crucial control condition made participants look at rather than visualize the cue. Acquisition strategies should have affected equally both types of cueing, but we observed that the effect of the visual cue was smaller and limited to a particular subcase in which one expects visual acquisition strategies. Thus, what matters is the similarity of the content of the mental image with the visual scene. In addition, an interaction involving the hand used for responding supports the notion that composite imagery is lateralized.