Original article can be found at: http://www.atmos-chem-phys.net/10/issue10.html Copyright - the authors. Authors grant any third party the right to use the article freely as long as its original authors and citation details are identified. The article and any associated published material is distributed under the Creative Commons Attribution 3.0 License.Aerosol particle size distributions were measured below and above a tropical rainforest canopy in Borneo, Malaysia, in June/July 2008 using the WIBS-3: a single particle dual channel fluorescence spectrometer. Material in the size range 0.8???20 ??m was characterized according to optical equivalent diameter (DP), morphology and fluorescence at 310???400 nm and 400???600 nm following excitation at 280 nm and 370 nm respectively. Particles fluorescent after both excitations are likely to be fluorescent primary biological aerosol particles (FBAP). Measured FBAP number concentration (NFBAP) at both sites exhibited clear diurnal cycles. The largest variability was observed in the understorey, where NFBAP reached a minimum of 50???100 L???1 in late morning. In mid afternoon it exhibited strong transient fluctuations as large as 4000 L???1 that were followed by sustained concentrations of 1000???2500 L???1 that reduced steadily between midnight and sunrise. Above the canopy FBAP number ranged from 50???100 L???1 during the daytime to 200???400 L???1 at night but did not exhibit the transient enhancements seen in the understorey. The strong FBAP fluctuations were attributed to the release of fungal spores below the canopy and appeared to be linked to elevated relative humidity. The mean FBAP number fraction in the size range 0.8 ??m

We describe a prototype low-cost multi-channel aerosol fluorescence sensor designed for unattended deployment in medium to large area bio-aerosol detection networks. Individual airborne particles down to ~1mum in size are detected and sized by measurement of light scattered from a continuous-wave diode laser (660nm). This scatter signal is then used to trigger the sequential firing of two xenon sources which irradiate the particle with UV pulses at ~280 nm and ~370 nm, optimal for excitation of bio-fluorophores tryptophan and NADH (nicotinamide adenine dinucleotide) respectively. For each excitation wavelength, fluorescence is detected across two bands embracing the peak emissions of the same bio-fluorophores. Current measurement rates are up to ~125 particles/s, corresponding to all particles for concentrations up to 1.3 x 104 particles/l. Developments to increase this to ~500 particles/s are in hand. Device sensitivity is illustrated in preliminary data recorded from aerosols of E.coli, BG spores, and a variety of non-biological materials.

Abstract. UV-LIF measurements were performed on ambient aerosol in Manchester, UK (urban city centre, winter) and Borneo, Malaysia (remote, tropical) using a Wide Issue Bioaerosol Spectrometer, version 3 (WIBS3). These sites are taken to represent environments with minor and significant primary biological aerosol (PBA) influences respectively, and the urban dataset describes the fluorescent background aerosol against which PBA must be identified by researchers using LIF. The ensemble aerosol at both sites was characterised over 2–3 weeks by measuring the fluorescence intensity and optical equivalent diameter (DP) of single particles sized 0.8 ≤ DP ≤ 20 μm. Filter samples were also collected for a subset of the Manchester campaign and analysed using energy dispersive X-Ray (EDX) spectroscopy and environmental scanning electron microscopy (ESEM), which revealed mostly non-PBA at D ≤ 1 μm. The WIBS3 features three fluorescence channels: the emission following a 280 nm excitation is recorded at 310–400 nm (channel F1) and 400–600 nm (F2), and fluorescence excited at 350 nm is detected at 400–600 nm (F3). In Manchester the primary size mode of fluorescent and non-fluorescent material was present at 0.8–1.2 μm, with a secondary fluorescent mode at 2–4 μm. In Borneo non-fluorescent material peaked at 0.8–1.2 μm and fluorescent at 3–4 μm. Agreement between fluorescent number concentrations in each channel differed at the two sites, with F1 and F3 reporting similar concentrations in Borneo but F3 outnumbering F1 by a factor of 2–3 across the size spectrum in Manchester. The fluorescence intensity in each channel generally rose with DP at both sites with the exception of F1 intensity in Manchester, which peaked at DP = 4 μm, causing a divergence between F1 and F3 intensity at larger DP. This divergence and the differing fluorescent particle concentrations demonstrate the additional discrimination provided by the F1 channel in Manchester. The relationships between fluorescence intensities in different pairs of channels were also investigated as a function of DP. Differences between these metrics were apparent at each site and provide some distinction between the two datasets. Finally, particle selection criteria based on the Borneo dataset were applied to identify a median concentration of 10 "Borneo-like" fluorescent particles per litre in Manchester.

Abstract. Characterisation of bioaerosols has important implications within environment and public health sectors. Recent developments in ultraviolet light-induced fluorescence (UV-LIF) detectors such as the Wideband Integrated Bioaerosol Spectrometer (WIBS) and the newly introduced Multiparameter Bioaerosol Spectrometer (MBS) have allowed for the real-time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal spores and pollen.This new generation of instruments has enabled ever larger data sets to be compiled with the aim of studying more complex environments. In real world data sets, particularly those from an urban environment, the population may be dominated by non-biological fluorescent interferents, bringing into question the accuracy of measurements of quantities such as concentrations. It is therefore imperative that we validate the performance of different algorithms which can be used for the task of classification.For unsupervised learning we tested hierarchical agglomerative clustering with various different linkages. For supervised learning, 11 methods were tested, including decision trees, ensemble methods (random forests, gradient boosting and AdaBoost), two implementations for support vector machines (libsvm and liblinear) and Gaussian methods (Gaussian naïve Bayesian, quadratic and linear discriminant analysis, the k-nearest neighbours algorithm and artificial neural networks).The methods were applied to two different data sets produced using the new MBS, which provides multichannel UV-LIF fluorescence signatures for single airborne biological particles. The first data set contained mixed PSLs and the second contained a variety of laboratory-generated aerosol.Clustering in general performs slightly worse than the supervised learning methods, correctly classifying, at best, only 67.6 and 91.1 % for the two data sets respectively. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 82.8 and 98.27 % of the testing data, respectively, across the two data sets.A possible alternative to gradient boosting is neural networks. We do however note that this method requires much more user input than the other methods, and we suggest that further research should be conducted using this method, especially using parallelised hardware such as the GPU, which would allow for larger networks to be trained, which could possibly yield better results.We also saw that some methods, such as clustering, failed to utilise the additional shape information provided by the instrument, whilst for others, such as the decision trees, ensemble methods and neural networks, improved performance could be attained with the inclusion of such information.

Abstract. The behaviour of primary biological aerosols (PBAs) at an elevated, un-polluted North American forest site was studied using an ultra violet-light induced fluorescence (UV-LIF) measurement technique in conjunction with hierarchical agglomerative cluster analysis (HA-CA). Contemporaneous UV-LIF measurements were made with two wide-band integrated bioaerosol spectrometers, WIBS-3 and WIBS-4, which sampled close to the forest floor and via a continuous vertical profiling system, respectively. Additionally, meteorological parameters were recorded at various heights throughout the forest and used to estimate PBAP (Primary Biological Aerosol Particle) fluxes. HA-CA using data from the two, physically separated WIBS instruments independently yielded very similar cluster solutions.All fluorescent clusters displayed a diurnal minimum at midday at the forest floor with maximum concentration occurring at night. Additionally, the number concentration of each fluorescent cluster was enhanced, to different degrees, during wet periods. A cluster that displayed the greatest enhancement and highest concentration during sustained wet periods appears consistent with behaviour reported for fungal spores. A cluster that appears to be behaviourally consistent with bacteria dominated during dry periods. Fluorescent particle concentrations were found to be greater within the forest canopy than at the forest floor, indicating that the canopy was the main source of these particles rather than the minimal surface vegetation, which appeared to contribute little to overall PBA concentrations at this site.Fluorescent particle concentration was positively correlated with relative humidity (RH), and parameterisations of the aerosol response during dry and wet periods are reported. The aforementioned fungal spore-like cluster displayed a strong positive response to increasing RH. The bacteria-like cluster responded more strongly to direct rain-fall events than other PBA types. Peak concentrations of this cluster are shown to be linearly correlated to the log of peak rainfall rates.Parallel studies by and Prenni et al. (2013) showed that the fluorescent particle concentrations correlated linearly with ice nuclei (IN) concentrations at this site during rain events. We discuss this result in conjunction with our cluster analysis to appraise the candidate IN.