An Optical Sampling System for Distributed Atmospheric Particulate Matter

The atmospheric particulate matter is considered one of the most dangerous pollutants because of its effects on the climate and human health. Particulate concentration changes largely with spatial position and time, and thus, a distributed real-time monitoring would be mandatory, especially in densely populated areas. The proposed optical sampling system has a negligible cost with respect to the already available instruments and can be used for deploying a capillary particulate monitoring network thanks to its wireless capability based on the LoRa protocol. The proposed solution employs an optical method for the atmospheric particulate detection and the estimation of its concentration and size distribution. The air is sampled by a small pump which forces a known flux through a commercial glass-fiber filter, where the particulate is captured. A low-cost digital camera coupled with a multi-wavelength lighting system takes periodical photographs of the filter surface, and a small PC-on-single-board processes the acquired images in order to identify the particles and to estimate their size. The system can work unattended for a long time and transmit remotely measurement data with a typical range of few kilometers

Full correction of scattering effects by using the radiative transfer theory for improved quantitative analysis of absorbing species in suspensions

Sample-to-sample photon path length variations that arise due to multiple scattering can be removed by decoupling absorption and scattering effects by using the radiative transfer theory, with a suitable set of measurements. For samples where particles both scatter and absorb light, the extracted bulk absorption spectrum is not completely free from nonlinear particle effects, since it is related to the absorption cross-section of particles that changes nonlinearly with particle size and shape. For the quantitative analysis of absorbing-only (i.e., nonscattering) species present in a matrix that contains a particulate species that absorbs and scatters light, a method to eliminate particle effects completely is proposed here, which utilizes the particle size information contained in the bulk scattering coefficient extracted by using the Mie theory to carry out an additional correction step to remove particle effects from bulk absorption spectra. This should result in spectra that are equivalent to spectra collected with only the liquid species in the mixture. Such an approach has the potential to significantly reduce the number of calibration samples as well as improve calibration performance. The proposed method was tested with both simulated and experimental data from a four-component model system

Extraction of chemical information of suspensions using radiative transfer theory to remove multiple scattering effects : application to a model two-component system

An approach for removing multiple light scattering effects using the radiative transfer theory (RTE) in order to improve the performance of multivariate calibration models is proposed. This approach is then applied to the problem of building calibration models for predicting the concentration of a scattering (particulate) component. Application of this approach to a simulated four component system showed that it will lead to calibration models which perform appreciably better than when empirically scatter corrected measurements of diffuse transmittance (Td) or reflectance (Rd) are used. The validity of the method was also tested experimentally using a two-component (Polystyrene-water) system. While the proposed method led to a model that performed better than that built using Rd, its performance was worse compared to when Td measurements were used. Analysis indicates that this is because the model built using Td benefits from the strong secondary correlation between particle concentration and pathlength travelled by the photons which occurs due to the system containing only two components. On the other hand, the model arising from the proposed methodology uses essentially only the chemical (polystyrene) signal. Thus this approach can be expected to work better in multi-component systems where the pathlength correlation would not exist

Ash plume properties retrieved from infrared images: a forward and inverse modeling approach

We present a coupled fluid-dynamic and electromagnetic model for volcanic ash plumes. In a forward approach, the model is able to simulate the plume dynamics from prescribed input flow conditions and generate the corresponding synthetic thermal infrared (TIR) image, allowing a comparison with field-based observations. An inversion procedure is then developed to retrieve ash plume properties from TIR images. The adopted fluid-dynamic model is based on a one-dimensional, stationary description of a self-similar (top-hat) turbulent plume, for which an asymptotic analytical solution is obtained. The electromagnetic emission/absorption model is based on the Schwarzschild's equation and on Mie's theory for disperse particles, assuming that particles are coarser than the radiation wavelength and neglecting scattering. [...] Application of the inversion procedure to an ash plume at Santiaguito volcano (Guatemala) has allowed us to retrieve the main plume input parameters, namely the initial radius $b_0$, velocity $U_0$, temperature $T_0$, gas mass ratio $n_0$, entrainment coefficient $k$ and their related uncertainty. Moreover, coupling with the electromagnetic model, we have been able to obtain a reliable estimate of the equivalent Sauter diameter $d_s$ of the total particle size distribution. The presented method is general and, in principle, can be applied to the spatial distribution of particle concentration and temperature obtained by any fluid-dynamic model, either integral or multidimensional, stationary or time-dependent, single or multiphase. The method discussed here is fast and robust, thus indicating potential for applications to real-time estimation of ash mass flux and particle size distribution, which is crucial for model-based forecasts of the volcanic ash dispersal process.Comment: 41 pages, 13 figures, submitted pape

Optical and morphological properties of Cirrus clouds determined by the high spectral resolution lidar during FIRE

Cirrus clouds reflect incoming solar radiation and trap outgoing terrestrial radiation; therefore, accurate estimation of the global energy balance depends upon knowledge of the optical and physical properties of these clouds. Scattering and absorption by cirrus clouds affect measurements made by many satellite-borne and ground based remote sensors. Scattering of ambient light by the cloud, and thermal emissions from the cloud can increase measurement background noise. Multiple scattering processes can adversely affect the divergence of optical beams propagating through these clouds. Determination of the optical thickness and the vertical and horizontal extent of cirrus clouds is necessary to the evaluation of all of these effects. Lidar can be an effective tool for investigating these properties. During the FIRE cirrus IFO in Oct. to Nov. 1986, the High Spectral Resolution Lidar (HSRL) was operated from a rooftop site on the campus of the University of Wisconsin at Madison, Wisconsin. Approximately 124 hours of fall season data were acquired under a variety of cloud optical thickness conditions. Since the IFO, the HSRL data set was expanded by more than 63.5 hours of additional data acquired during all seasons. Measurements are presented for the range in optical thickness and backscattering phase function of the cirrus clouds, as well as contour maps of extinction corrected backscatter cross sections indicating cloud morphology. Color enhanced images of range-time indicator (RTI) displays a variety of cirrus clouds with approximately 30 sec time resolution are presented. The importance of extinction correction on the interpretation of cloud height and structure from lidar observations of optically thick cirrus are demonstrated

Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes

The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of re!ectance at 710 and 670 nm (R2=0.832; RMSE=29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R2=0.984; RMSE=3.98 mg m−3). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R2=0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R2=0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales

Error in total ozone measurements arising from aerosol attenuation

A generalized least squares method for deducing both total ozone and aerosol extinction spectrum parameters from Dobson spectrophotometer measurements was developed. An error analysis applied to this system indicates that there is little advantage to additional measurements once a sufficient number of line pairs have been employed to solve for the selected detail in the attenuation model. It is shown that when there is a predominance of small particles (less than about 0.35 microns in diameter) the total ozone from the standard AD system is too high by about one percent. When larger particles are present the derived total ozone may be an overestimate or an underestimate but serious errors occur only for narrow polydispersions