Analysis and Forecasting of PM2.5, PM4, and PM10 Dust Concentrations, Based on In Situ Tests in Hard Coal Mines

The method of analyzing the results of dust concentration measurements in mine workings that was conducted within the ROCD (Reducing risks from Occupational exposure to Coal Dust) European project using the developed dust prediction algorithm is presented. The analysis was based on the measurements of average dust concentration with the use of the CIP-10R gravimetric dust meters, for the respirable PM4 dust concentration, and IPSQ analyzer for instantaneous concentration measurements (including PM2.5 dust) and with the use of Pł-2 optical dust meters for instantaneous concentration measurements of PM10 dust. Based on the analyses of the measurement results, the characteristics of the distribution of PM10, PM4, and PM2.5 dust particles were developed for the tested dust sources. Then, functional models based on power functions were developed. The determined models (functions) allow predicting the dust distribution in such conditions (and places) for which we do not have empirical data. The developed models were implemented in a specially developed online tool, which enables predicting the concentration of PM10, PM4, and PM2.5 dust (on the basis of dust concentration of one source) at any distance from the dust source.

Development and Evaluation of a Fluctuating Plume Model for Odor Impact Assessment

For environmental odor nuisance, it is extremely important to identify the instantaneous concentration statistics. In this work, a Fluctuating Plume Model for different statistical moments is proposed. It provides data in terms of mean concentrations, variance, and intensity of concentration. The 90th percentile peak-to-mean factor, R90, was tested here by comparing it with the experimental results (Uttenweiler field experiment), considering different Probability Distribution Functions (PDFs): Gamma and the Modified Weibull. Seventy-two percent of the simulated mean concentration values fell within a factor 2 compared to the experimental ones: the model was judged acceptable. Both the modelled results for standard deviation, σC, and concentration intensity, Ic, overestimate the experimental data. This evidence can be due to the non-ideality of the measurement system. The propagation of those errors to the estimation of R90 is complex, but the ranges covered are quite repeatable: the obtained values are 1–3 for the Gamma, 1.5–4 for Modified Weibull PDF, and experimental ones from 1.4 to 3.6.

The Performance of Olfactory Receptor Neurons: The Rate of Concentration Change Indicates Functional Specializations in the Cockroach Peripheral Olfactory System

Slow and continuous changes in odor concentration were used as a possible easy method for measuring the effect of the instantaneous concentration and the rate of concentration change on the activity of the olfactory receptor neurons (ORNs) of basiconic sensilla on the cockroach antennae. During oscillating concentration changes, impulse frequency increased with rising instantaneous concentration and this increase was stronger the faster concentration rose through the higher concentration values. The effect of the concentration rate on the ORNs responses to the instantaneous concentration was invariant to the duration of the oscillation period: shallow concentration waves provided by long periods elicited the same response to the instantaneous concentration as steep concentration waves at brief periods. Thus, the double dependence remained unchanged when the range of concentration rates varied. This distinguishes the ORNs of basiconic sensilla from those of trichoid sensilla (Tichy and Hellwig, 2018) which adjust their gain of response according to the duration of the oscillating period. The precision of the ORNs to discriminate increments of slowly rising odor concentration was studied by applying gradual ramp-like concentration changes at different rates. While the ORNs of the trichoid sensilla perform better the slower the concentration rate, those of the basiconic sensilla show no preference for a specific rate of concentration increase. This suggests that the two types of sensilla have different functions. The ORNs of the trichoid sensilla may predominately analyze temporal features of the odor signal and the ORNs of the basiconic sensilla may be involved in extracting information on the identity of the odor source instead of mediating the spatial-temporal concentration pattern in an odor plume.

Towards Fast Plume Source Estimation with a Mobile Robot

The estimation of the parameters of an odour source is of high relevance for multiple applications, but it can be a slow and error prone process. This work proposes a fast particle filter-based method for source term estimation with a mobile robot. Two strategies are implemented in order to reduce the computational cost of the filter and increase its accuracy: firstly, the sampling process is adapted by the mobile robot in order to optimise the quality of the data provided to the estimation process; secondly, the filter is initialised only after collecting preliminary data that allow limiting the solution space and use a shorter number of particles than it would be normally necessary. The method assumes a Gaussian plume model for odour dispersion. This models average odour concentrations, but the particle filter was proved adequate to fit instantaneous concentration measurements to that model, while the environment was being sampled. The method was validated in an obstacle free controlled wind tunnel and the validation results show its ability to quickly converge to accurate estimates of the plume’s parameters after a reduced number of plume crossings.

Evaluation of statistical distributions to analyze the pollution of Cd and Pb in urban runoff

Heavy metal pollution in urban runoff causes severe environmental damage. Identification of these pollutants and their statistical analysis is necessary to provide management guidelines. In this study, 45 continuous probability distribution functions were selected to fit the Cd and Pb data in the runoff events of an urban area during October 2014–May 2015. The sampling was conducted from the outlet of the city basin during seven precipitation events. For evaluation and ranking of the functions, we used the goodness of fit Kolmogorov–Smirnov and Anderson–Darling tests. The results of Cd analysis showed that Hyperbolic Secant, Wakeby and Log-Pearson 3 are suitable for frequency analysis of the event mean concentration (EMC), the instantaneous concentration series (ICS) and instantaneous concentration of each event (ICEE), respectively. In addition, the LP3, Wakeby and Generalized Extreme Value functions were chosen for the EMC, ICS and ICEE related to Pb contamination.

Relationship Between Diffusing-Material Lumps and Organized Structures in Turbulent Flow

When a material spreads in the turbulent flow, its instantaneous concentration distribution becomes not homogenous in space, and areas with high concentration containing sudden change of the concentration are formed by the local intense turbulence. In this study, we extracted such localized high-concentration areas by a conditional sampling technique, and observed the behavior of the areas. In order to realize the scalar diffusion in quasi homogeneous isotropic turbulent flow, a model experiment was performed in a water channel flow. Fluorescent dye was introduced from a nozzle located at the center of the channel, and the concentration images of the dye were obtained at several downstream positions by PLIF measurement. To extract areas of high concentration containing a sudden change of the concentration, three types of analysis techniques including the conditional sampling technique were applied to PLIF images. By the conditional sampling technique, we can extract areas of high concentration, which cannot be identified by the other two kind methods, and the effectiveness of this technique was proved. It was found that the areas extracted by the conditional sampling technique appear as lumps. The spanwise numerical probability distribution of the lumps roughly follows the Gaussian distribution, and the peak of the distribution decreases while its standard variation increases as streamwise distance increases. This result implies that performing extraction of areas with high concentration appropriately would enable to realize the material diffusing process as a Lagrange particle and provide a prediction method about the material diffusion source and the damage of the pollutant.