Search results for: sampler

Authors: Sapan Bhatnagar, Danish Akhtar, Salman Ahmed, Asif Ekbal, Gufran Beig

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Particulates are the solid and liquid droplets present in the atmosphere, they have serious negative effects on human health and environment. PM10 and PM2.5 are so small that they can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Air Quality Index is an index tells us how clean or polluted our air is, and what associated health effects might be a concern for us. The AQI focuses on health affects you may experience within a few hours or days after breathing polluted air. The quality rating for each pollutant was calculated. The geometric mean of these quality ratings gives the Air Quality Index. The existing concentrations of pollutants were compared with ambient air quality standards.

Keywords: air quality index, particulate, respirable dust sampler, dust sampler

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Jeremie Coullon, Robert J. Webber

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We introduce a Markov chain Monte Carlo (MCMC) sam-pler for infinite-dimensional inverse problems. Our sam-pler is based on the affine invariant ensemble sampler, which uses interacting walkers to adapt to the covariance structure of the target distribution. We extend this ensem-ble sampler for the first time to infinite-dimensional func-tion spaces, yielding a highly efficient gradient-free MCMC algorithm. Because our ensemble sampler does not require gradients or posterior covariance estimates, it is simple to implement and broadly applicable. In many Bayes-ian inverse problems, Markov chain Monte Carlo (MCMC) meth-ods are needed to approximate distributions on infinite-dimensional function spaces, for example, in groundwater flow, medical imaging, and traffic flow. Yet designing efficient MCMC methods for function spaces has proved challenging. Recent gradi-ent-based MCMC methods preconditioned MCMC methods, and SMC methods have improved the computational efficiency of functional random walk. However, these samplers require gradi-ents or posterior covariance estimates that may be challenging to obtain. Calculating gradients is difficult or impossible in many high-dimensional inverse problems involving a numerical integra-tor with a black-box code base. Additionally, accurately estimating posterior covariances can require a lengthy pilot run or adaptation period. These concerns raise the question: is there a functional sampler that outperforms functional random walk without requir-ing gradients or posterior covariance estimates? To address this question, we consider a gradient-free sampler that avoids explicit covariance estimation yet adapts naturally to the covariance struc-ture of the sampled distribution. This sampler works by consider-ing an ensemble of walkers and interpolating and extrapolating between walkers to make a proposal. This is called the affine in-variant ensemble sampler (AIES), which is easy to tune, easy to parallelize, and efficient at sampling spaces of moderate dimen-sionality (less than 20). The main contribution of this work is to propose a functional ensemble sampler (FES) that combines func-tional random walk and AIES. To apply this sampler, we first cal-culate the Karhunen–Loeve (KL) expansion for the Bayesian prior distribution, assumed to be Gaussian and trace-class. Then, we use AIES to sample the posterior distribution on the low-wavenumber KL components and use the functional random walk to sample the posterior distribution on the high-wavenumber KL components. Alternating between AIES and functional random walk updates, we obtain our functional ensemble sampler that is efficient and easy to use without requiring detailed knowledge of the target dis-tribution. In past work, several authors have proposed splitting the Bayesian posterior into low-wavenumber and high-wavenumber components and then applying enhanced sampling to the low-wavenumber components. Yet compared to these other samplers, FES is unique in its simplicity and broad applicability. FES does not require any derivatives, and the need for derivative-free sam-plers has previously been emphasized. FES also eliminates the requirement for posterior covariance estimates. Lastly, FES is more efficient than other gradient-free samplers in our tests. In two nu-merical examples, we apply FES to challenging inverse problems that involve estimating a functional parameter and one or more scalar parameters. We compare the performance of functional random walk, FES, and an alternative derivative-free sampler that explicitly estimates the posterior covariance matrix. We conclude that FES is the fastest available gradient-free sampler for these challenging and multimodal test problems.

Keywords: Bayesian inverse problems, Markov chain Monte Carlo, infinite-dimensional inverse problems, dimensionality reduction

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Authors: Johnson Joseph Kwabina Arhinful, Owusu-Ansah Emmanuel Degraft Johnson, Okyere Gabrial Asare, Adebanji Atinuke Olusola

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This paper proposes a model to describe the blood types distribution of new Coronavirus (COVID-19) cases using the Bayesian Poisson - Hidden Markov Model (BP-HMM). With the help of the Gibbs sampler algorithm, using OpenBugs, the study first identifies the number of hidden states fitting European (EU) and African (AF) data sets of COVID-19 cases by blood type frequency. The study then compares the state-dependent mean of infection within and across the two geographical areas. The study findings show that the number of hidden states and infection rates within and across the two geographical areas differ according to blood type.

Keywords: BP-HMM, COVID-19, blood types, GIBBS sampler

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Authors: Turki M. Habeebullah, Atef M. F. Mohammed, Essam A. Morsy

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In recent decades, particulate matter (PM10) have received much attention due to its potential adverse health impact and the subsequent need to better control or regulate these pollutants. The aim of this paper is focused on study risk assessment of PM10 in four different districts (Shebikah, Masfalah, Aziziyah, Awali) in Makkah, Saudi Arabia during the period from 1 Ramadan 1434 AH - 27 Safar 1435 AH. samples was collected by using Low Volume Sampler (LVS Low Volume Sampler) device and filtration method for estimating the total concentration of PM10. The study indicated that the mean PM10 concentrations were 254.6 (186.1 - 343.2) µg/m3 in Shebikah, 184.9 (145.6 - 271.4) µg/m3 in Masfalah, 162.4 (92.4 - 253.8) µg/m3 in Aziziyah, and 56.0 (44.5 - 119.8) µg/m3 in Awali. These values did not exceed the permissible limits in PME (340 µg/m3 as daily average). Furthermore, health assessment is carried out using AirQ2.2.3 model to estimate the number of hospital admissions due to respiratory diseases. The cumulative number of cases per 100,000 were 1534 (18-3050 case), which lower than that recorded in the United States, Malaysia. The concentration response coefficient was 0.49 (95% CI 0.05 - 0.70) per 10 μg/m3 increase of PM10.

Keywords: air pollution, respiratory diseases, airQ2.2.3, Makkah

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Authors: Dzmitry Misiulia, Sergiy Antonyuk

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Small-scale cyclone separators are widely used in aerosol sampling. The flow field in a cyclone sampler is very complex, especially the vortex behavior. Most of the existing models for calculating cyclone efficiency use the same stable vortex structure while the vortex demonstrates dynamic variations rather than the steady-state picture. It can spontaneously ‘end’ at some point within the body of the separator. Natural vortex length is one of the most critical issues when designing and operating gas cyclones and is crucial to proper cyclone performance. The particle transport along the wall to the grid pot is not effective beyond this point. The flow field and vortex behavior inside the aerosol sampler have been investigated for a wide range of Reynolds numbers using Large Eddy Simulations. Two characteristics types of vortex behavior have been found with simulations. At low flow rates the vortex created in the cyclone dissipates in free space (without attaching to a surface) while at higher flow rates it attaches to the cyclone wall. The effects of the Reynolds number on the natural vortex length and the rotation frequency of the end of the vortex have been revealed.

Keywords: cyclone, flow field, natural vortex length, pressure drop

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Authors: Hamidreza Sharifan, Audra Morse

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Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: A. Burakowska, M. Piotrowski, M. Kubicki, H. Trzaskowska, R. Sosnowiec, B. Myslek-Laurikainen

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The most important source of atmospheric radioactivity are radionuclides generated as a result of the impact of primary and secondary cosmic radiation, with the nuclei of nitrogen oxygen and carbon in the upper troposphere and lower stratosphere. This creates about thirty radioisotopes of more than twenty elements. For organisms, the four of them are most important: ³H, ⁷Be, ²²Na, ¹⁴C. The natural radionuclides, which are present in Earth crust, also settle on dust and particles of water vapor. By this means, the derivatives of uranium and thorium, and long-life 40K get into the air. ¹³⁷Cs is the most widespread isotope, that is implemented by humans into the environment. To determine the concentration of radionuclides in the atmosphere, high volume air samplers were used, where the aerosol collection took place on a special filter fabric (Petrianov filter tissue FPP-15-1.5). In 2002 the high volume air sampler AZA-1000 was installed at the Polish Polar Observatory of the Polish Academy of Science in Hornsund, Spitsbergen (77°00’N, 15°33’E), designed to operate in all weather conditions of the cold polar region. Since 1991 (with short breaks) the ASS-500 air sampler has been working, which is located in Swider at the Kalinowski Geophysical Observatory of Geophysics Institute of the Polish Academy of Science (52°07’N, 21°15’E). The following results of radionuclides concentrations were obtained from both stations using gamma spectroscopy analysis: ⁷Be, ¹³⁷Cs, ¹³⁴Cs, ²¹⁰Pb, ⁴⁰K. For gamma spectroscopy analysis HPGe (High Purity Germanium) detector were used. These data were compared with each other. The preliminary results gave evidence that radioactivity measured in aerosols is not proportional to the amount of dust for both studied regions. Furthermore, the results indicate annual variability (seasonal fluctuations) as well as a decrease in the average activity of ⁷Be with increasing latitude. The content of ⁷Be in surface air also indicates the relationship with solar activity cycles.

Keywords: aerosols, air filters, atmospheric beryllium, environmental radionuclides, gamma spectroscopy, mid-latitude regions radionuclides, polar regions radionuclides, solar cycles

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Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

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An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

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Authors: Golnaz Shahtahmassebi, Jose Maria Sarabia

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In this talk, we introduce a new class of conjugate prior distributions obtained from conditional specification methodology. We illustrate the application of such distribution in Bayesian change point detection in Poisson processes. We obtain the posterior distribution of model parameters using a general bivariate distribution with gamma conditionals. Simulation from the posterior is readily implemented using a Gibbs sampling algorithm. The Gibbs sampling is implemented even when using conditional densities that are incompatible or only compatible with an improper joint density. The application of such methods will be demonstrated using examples of simulated and real data.

Keywords: change point, bayesian inference, Gibbs sampler, conditional specification, gamma conditional distributions

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Authors: Shigenori Togashi, Kei Takenaka

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We developed new processes which can collect and detect rapidly airborne pathogens such as the avian flu virus for the pandemic prevention. The fluorescence antibody technique is known as one of high-sensitive detection methods for viruses, but this needs up to a few hours to bind sufficient fluorescence dyes to viruses for detection. In this paper, we developed a mist-labeling can detect substitution viruses in a short time to improve the binding rate of fluorescent dyes and substitution viruses by the micro reaction process. Moreover, we developed the rapid detection system with the above 'mist labeling'. The detection system set with a sampling bag collecting patient’s breath and a cartridge can detect automatically pathogens within 10 minutes.

Keywords: viruses, sampler, mist, detection, fluorescent dyes, microreaction

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Authors: F. Fernandes, C. Poleto

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This paper aims at assessing the concentrations of heavy metals and the isotopic composition of lead ²¹⁰Pb in different fractions of sediment produced in the watershed that makes up the Mãe d'água dam and thus characterizing the distribution of metals along the sedimentary column and inferencing in the urbanization of the same process. Sample collection was carried out in June 2014; eight sediment cores were sampled in the lake of the dam. For extraction of the sediments core, a core sampler “Piston Core” was used. The trace metal concentrations were determined by conventional atomic absorption spectrophotometric methods. The samples were subjected to radiochemical analysis of ²¹⁰Po. ²¹⁰Pb activity was obtained by measuring ²¹⁰Po activity. The chronology was calculated using the constant rate of supply (CRS). ²¹⁰Pb is used to estimate the sedimentation rate.

Keywords: ²¹⁰Pb dating method, heavy metal, lakes urban, pollution history

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Authors: Katarzyna Zięba, Hajnalka Szentgyörgyi, Paweł Miśkowiec, Agnieszka Moos-Matysik

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Bees are effective pollinators of plants using by humans. However, there is a concern about the fate different species due to their recently decline. Pollution of the environment is described in the literature as one of the causes of this phenomenon. Due to human activities, heavy metals and aromatic hydrocarbons can occur in bee organisms in high concentrations. The presented study aims to provide information on how pollution affects bee quality, taking into account, also the biological differences between various groups of bees. Understanding the consequences of environmental pollution on bees can help to create and promote bee friendly habitats and actions. The analyses were carried out using two contamination gradients with 5 sites on each. The first, mainly heavy metal polluted gradient is stretching approx. 30km from the Bukowno Zinc smelter near Olkusz in the Lesser Poland Voivodship, to the north. The second cuts through the agglomeration of Kraków up to the southern borders of the Ojców National Park. The gradient near Olkusz is a well-described pollution gradient contaminated mainly by zinc, lead, and cadmium. The second gradient cut through the agglomeration of Kraków and end below the Ojców National Park. On each gradient, two bee species were installed: red mason bees (Osmia bicornis) and honey bees (Apis mellifera). Red mason bee is a polylectic, solitary bee species, widely distributed in Poland. Honey bees are a highly social species of bees, with clearly defined casts and roles in the colony. Before installing the bees in the field, samples of imagos of red mason bees and samples of pollen and imagos from each honey bee colony were analysed for zinc, lead cadmium, polycyclic and monocyclic hydrocarbons levels. After collecting the bees from the field, samples of bees and pollen samples for each site were prepared for heavy metal, monocyclic hydrocarbon, and polycyclic hydrocarbon analysis. Analyses of aromatic hydrocarbons were performed with gas chromatography coupled with a headspace sampler (HP 7694E) and mass spectrometer (MS) as detector. Monocyclic compounds were injected into column with headspace sampler while polycyclic ones with manual injector (after solid-liquid extraction with hexane). The heavy metal content (zinc, lead and cadmium) was assessed with flame atomic absorption spectroscopy (FAAS AAnalyst 300 Perkin Elmer spectrometer) according to the methods for honey and bee products described in the literature. Pollution levels found in bee bodies and imago body masses in both species, and proportion of sex in case of red mason bees were correlated with pollution levels found in pollen for each site and colony or trap nest. An attempt to pinpoint the most important form of contamination regarding bee health was also be undertaken based on the achieved results.

Keywords: heavy metals, aromatic hydrocarbons, bees, pollution

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Authors: A. Szabó Nagy, J. Szabó, Zs. Csanádi, J. Erdős

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An assessment of the air quality of Győr (Hungary) was performed by determining the ambient concentrations of PM10-bound carcinogenic polycyclic aromatic hydrocarbons (cPAHs) in different seasons. A high volume sampler was used for the collection of ambient aerosol particles, and the associated cPAH compounds (benzo[a]pyrene (BaP), benzo[a]anthracene, benzofluoranthene isomers, indeno[123-cd]pyrene and dibenzo[ah]anthracene) were analyzed by a gas chromatographic method. Higher mean concentrations of total cPAHs were detected in samples collected in winter (9.62 ng/m³) and autumn (2.69 ng/m³) compared to spring (1.05 ng/m³) and summer (0.21 ng/m³). The calculated BaP toxic equivalent concentrations have also reflected that the local population appears to be exposed to significantly higher cancer risk in the heating seasons. Moreover, the concentration levels of cPAHs determined in this study were compared to other Hungarian urban sites.

Keywords: air, carcinogenic, polycyclic aromatic hydrocarbons (PAH), PM10

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Authors: Yuichi Kida, Takuro Kida

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In a new smart society supported by the recent development of 5G and 6G Communication systems, the im- portance of wireless power transmission is increasing. These systems contain discrete sampling systems in the middle of the transmission path and equivalent circuit representation of lossless or lossy power transmission through these systems is an important issue in circuit theory. In this paper, for the given weight function, we show that a lossless power transmission system with the given weight is expressed by an equivalent circuit representation of the Kida’s optimal signal prediction system followed by a reactance multi-port circuit behind it. Further, it is shown that, when the system is lossy, the system has an equivalent circuit in the form of connecting a multi-port positive-real circuit behind the Kida’s optimal signal prediction system. Also, for the convenience of the reader, in this paper, the equivalent circuit expression of the reactance multi-port circuit and the positive- real multi-port circuit by Cauer and Ohno, whose information is currently being lost even in the world of the Internet.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, power transmission

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Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

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As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

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Authors: M. P. Raju, P. D. Safai, P. S. P. Rao, P. C. S. Devara, C. V. Naidu

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In order to study the Physical and chemical characteristics of aerosols, samples of Total Suspended Particulates (TSP) were collected using a high volume sampler at Pune, a semi-urban location in SW India during March 2009 to February 2010. TSP samples were analyzed for water soluble components like F, Cl, NO3, SO4, NH4, Na, K, Ca, and Mg and acid soluble components like Al, Zn, Fe and Cu using Ion-Chromatograph and Atomic Absorption Spectrometer. Analysis of the data revealed that the monthly mean TSP concentrations varied between 471.3 µg/m3 and 30.5 µg/m3 with an annual mean value of 159.8 µg/m3. TSP concentrations were found to be less during post-monsoon and winter (October through February), compared to those in summer and monsoon (March through September). Anthropogenic activities like vehicular emissions and dust particles originated from urban activities were the major sources for TSP. TSP showed good correlation with all the major ionic components, especially with SO4 (R= 0.62) and NO3 (R= 0.67) indicating the impact of anthropogenic sources over the aerosols at Pune. However, the overall aerosol nature was alkaline (Ave pH = 6.17) mainly due to the neutralizing effects of Ca and NH4. SO4 contributed more (58.8%) to the total acidity as compared to NO3 (41.1%) where as, Ca contributed more (66.5%) to the total alkalinity than NH4 (33.5%). Seasonality of acid soluble component Al, Fe and Cu showed remarkable increase, indicating the dominance of soil source over the man-made activities. Overall study on TSP indicated that aerosols at Pune were mainly affected by the local sources.

Keywords: chemical composition, acidic and neutralization potential, radiative forcing, urban station

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Authors: Ahmed Aboforn

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Butene-1 product is consider effectively raw material in Polyethylene production, however Oxygenates impurities existing will be effected ethylene/butene-1 copolymers synthesized through titanium-magnesium-supported Ziegler-Natta catalysts. Laterally, Petrochemical industries are challenge against poor quality of Butene-1 and other C4 mix – feedstock that reflected on business impact and production losing. In addition, propylene product suffering from contamination by oxygenates components and causing for lose production and plant upset of Polypropylene process plants. However, Multidimensional gas chromatography (MDGC) innovative analytical methodology is a chromatography technique used to separate complex samples, as mixing different functional group as Hydrocarbon and oxygenates compounds and have similar retention factors, by running the eluent through two or more columns instead of the customary single column. This analytical study striving to enhance the quality of Oxygenates analytical method, as monitoring the concentration of oxygenates with accurate and precise analytical method by utilizing multidimensional GC supported by Backflush technique and Flame Ionization Detector, which have high performance separation of hydrocarbon and Oxygenates; also improving the minimum detection limits (MDL) to detect the concentration <1.0 ppm. However different types of oxygenates as (Alcohols, Aldehyde, Ketones, Ester and Ether) may be determined in other Hydrocarbon streams asC3, C4-mix, until C12 mixture, supported by liquid injection auto-sampler.

Keywords: analytical chemistry, gas chromatography, petrochemicals, oxygenates

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Authors: Sidali Khedidji, Noureddine Yassaa, Riad Ladji

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In this study, n-alkanes which are hazardous for the environment and human health were investigated in Sour El Ghozlane suburban atmosphere at a sampling point from April 2013 to Mai 2013. Ambient concentration measurements of n-Alkanes were carried out at a regional study of the cement industry in Sour El Ghozlane. During sampling, the airborne particulate matter was enriched onto PTFE filters by using a two medium volume samplers with or without a size-selective inlet for PM10 and TSP were used and each sampling period lasted approximately 24 h. The organic compounds were characterized using gas chromatography coupled with mass spectrometric detection (GC-MS). Total concentrations for n-Alkanes recorded in Sour El Ghozlane suburban ranged from 42 to 69 ng m-3. Gravimeter method was applied to the black smoke concentration data for Springer seasons. The 24 h average concentrations of n-alkanes contain the PM10 and TSP of Sour El Ghozlane suburban atmosphere were found in the range 0.50–7.06 ng/m3 and 0.29–6.97 ng/m3, respectively, in the sampling period. Meteorological factors, such as (relative humidity and temperature) were typically found to be affecting PMs, especially PM10. Air temperature did not seem to be significantly affecting TSP and PM10 mass concentrations. The guide value fixed by the European Community, 40 μg/m3 was not to exceed 35 days, was exceeded in some samples. However, it should be noted that the value limit fixed by the Algerian regulations 80 μg/m3 has been exceeded in 1 sampler during the period study.

Keywords: n-alkanes, PM10, TSP, particulate matter, cement industry

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Authors: A. Szabó Nagy, J. Szabó, Zs. Csanádi, J. Erdős

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In Hungary, the measurement of ambient PM10-bound polycyclic aromatic hydrocarbon (PAH) concentrations is great importance for a number of reasons related to human health, the environment and compliance with European Union legislation. However, the monitoring of PAHs associated with PM2.5 aerosol fraction is still incomplete. Therefore, the main aim of this study was to investigate the concentration levels of PAHs in PM2.5 urban aerosol fraction. PM2.5 and associated PAHs were monitored in November 2014 in an urban site of Győr (Northwest Hungary). The aerosol samples were collected every day for 24-hours over two weeks with a high volume air sampler provided with a PM2.5 cut-off inlet. The levels of 19 PAH compounds associated with PM2.5 aerosol fraction were quantified by a gas chromatographic method. Polluted air quality for PM2.5 (>25 g/m3) was indicated in 50% of the collected samples. The total PAHs concentrations ranged from 2.1 to 37.3 ng/m3 with the mean value of 12.4 ng/m3. Indeno(123-cd)pyrene (IND) and sum of three benzofluoranthene isomers were the most dominant PAH species followed by benzo(ghi)perylene and benzo(a)pyrene (BaP). Using BaP-equivalent approach on the concentration data of carcinogenic PAH species, BaP, and IND contributed the highest carcinogenic exposure equivalent (1.50 and 0.24 ng/m3 on average). A selected number of concentration ratios of specific PAH compounds were calculated to evaluate the possible sources of PAH contamination. The ratios reflected that the major source of PAH compounds in the PM2.5 aerosol fraction of Győr during the study period was fossil fuel combustion from automobiles.

Keywords: air, PM2.5, benzo(a)pyrene, polycyclic aromatic hydrocarbon

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Authors: P. S. Seboletswe, Z. Mkhize, L. M. Katata-Seru

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Protorhus longifolia is known as a medicinal plant that has been used traditionally to treat various ailments such as hemiplegic paralysis, blood clotting related diseases, diarrhoea, heartburn, etc. The study reports a High-Performance Thin Layer Chromatography (HPTLC) fingerprint profile of Protorhus longifolia methanolic extract and its qualitative analysis of gallic acid, rutin, and quercetin. HPTLC analysis was achieved using CAMAG HPTLC system equipped with CAMAG automatic TLC sampler 4, CAMAG Automatic Developing Chamber 2 (ADC2), CAMAG visualizer 2, CAMAG Thin Layer Chromatography (TLC) scanner and visionCATS CAMAG HPTLC software. Mobile phase comprising toluene, ethyl acetate, formic acid (21:15:3) was used for qualitative analysis of gallic acid and revealed eight peaks while the mobile phase containing ethyl acetate, water, glacial acetic acid, formic acid (100:26:11:11) for qualitative analysis of rutin and quercetin revealed six peaks. HPTLC sillica gel 60 F254 glass plates (10 × 10) were used as the stationary phase. Gallic acid was detected at the R_f = 0.35; while rutin and quercetin were not evident in the extract. Further studies will be performed to quantify gallic acid in Protorhus longifolia leaves and also identify other biomarkers.

Keywords: biomarkers, fingerprint profiling, gallic acid, HPTLC, Protorhus longifolia

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Authors: Aukse Miskinyte, Audrius Dedele

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The impact of urban air pollution on human health effects has been revealed in epidemiological studies, which have assessed the associations between various types of gases and particles and negative health outcomes. The percentage of population living in urban areas is increasing, and the assessment of air pollution in certain zones in the city (like street canyons) that have higher level of air pollution and specific dispersion conditions is essential as these places tend to contain a lot of people. Street canyon is defined as a street surrounded by tall buildings on both sides that trapes traffic emissions and prevents pollution dispersion. The aim of this study was to determine the pollution of nitrogen dioxide in street canyons in Kaunas city during cold and warm seasons. The measurements were conducted using passive sampling technique during two-week period in two street canyon sites, whose axes are approximately north-south and north-northeast‒south-southwest. Both of these streets are two-lane roads of 7 meters width, one is in the central part of the city, and other is in the Old Town. The results of two-week measurements showed that the concentration of nitrogen dioxide was higher in summer season than in winter in both street canyon sites. The difference between the level of NO2 in winter and summer seasons was 5.1 and 19.4 µg/m3 in the first and in the second street canyon sites, respectively. The higher concentration of NO2 was determined in the second street canyon site than in the first, although there was calculated lower traffic intensity. These results could be related to the certain street canyon characteristics.

Keywords: air pollution, nitrogen dioxide, passive sampler, street canyon

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Authors: Laura X. Martinez, Andrés F. Rodríguez, Ruth A. Catacoli

Abstract:

One of the most important factors for air pollution is that the concentrations of PM₁₀ maintain a constant trend, with the exception of some places where that frequently surpasses the allowed ranges established by Colombian legislation. The community that surrounds the Universidad Libre Bogotá is inhabited by a considerable number of students and workers, all of whom are possibly being exposed to PM₁₀ for long periods of time while on campus. Thus, the chemical characterization of PM₁₀ found in the ambient air at the Universidad Libre Bogotá was identified as a problem. A Hi-Vol sampler and EPA Test Method 5 were used to determine if the quality of air is adequate for the human respiratory system. Additionally, quartz fiber filters were utilized during sampling. Samples were taken three days a week during a dry period throughout the months of November and December 2015. The gravimetric analysis method was used to determine PM₁₀ concentrations. The chemical characterization includes non-conventional carcinogenic pollutants. Atomic absorption spectrophotometry (AAS) was used for the determination of metals and VOCs were analyzed using the FTIR (Fourier transform infrared spectroscopy) method. In this way, concentrations of PM₁₀, ranging from values of 13 µg/m³ to 66 µg/m³, were obtained; these values were below standard conditions. This evidence concludes that the PM₁₀ concentrations during an exposure period of 24 hours are lower than the values established by Colombian law, Resolution 610 of 2010; however, when comparing these with the limits set by the World Health Organization (WHO), these concentrations could possibly exceed permissible levels.

Keywords: air quality, atomic absorption spectrophotometry, gas chromatography, particulate matter

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Authors: Helen Yetunde Omoboye, Adebukola Adenike Adedeji, Israel Funso Adeniyi

Abstract:

This study of the biodiversity, community structure, and production capacity of the zooplankton community is an aspect of bio-monitoring of the aquatic ecosystem. Samples were selected horizontally and vertically from Esa-Odo Reservoir using improvised Meyer’s water sampler. Planktonic samples were collected at two months intervals for two years. Net and total plankton were sampled by filtration and sedimentation methods. Planktonic samples were preserved as 5% formalin and 1% Lugol’s solution. Measurement, enumeration, and scaled pictures of the recorded zooplankton were taken using a photomicrograph. The taxonomic composition of zooplankton biota was determined using identification keys. Eighty three (83) species of zooplankton recorded in this study belong to 4 groups: Rotifera, Cladocera, Copepoda, and Insecta. Rotifera was the most represented group (61.21%). Horizontally, 24 species with the highest mean abundance characterized the lacustrine; while 12 species and 10 species were unique to the transition and riverine zones, respectively. Vertically, most species had their mean abundance decreased from the surface to the bottom of the reservoir. A total of nine (9), two (2), and one (1) species were peculiar to the surface, bottom and mid-depth, respectively. Zooplankton was most abundant during the dry season. In conclusion, Esa-Odo Reservoir comprised highly diversified zooplankton fauna with great potential to support a rich aquatic community and fishery production. The reservoir can be classified as fairly clean based on the abundance of the rotifer group. However, the lake should be subjected to regular proper monitoring because of the presence of some pollution tolerant copepod species identified among the zooplankton fauna.

Keywords: zooplankton, spatial, temporal, abundance, biodiversity, reservoir

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Authors: R. Kerbachi, S. Chikhi, M. Boughedaoui

Abstract:

The study presents an analysis of the Algerian vehicle fleet and resultant emissions. The emission measurement of air pollutants emitted by road transportation (CO, THC, NOX and CO2) was conducted on 17 light duty vehicles in real traffic. This sample is representative of the Algerian light vehicles in terms of fuel quality (gasoline, diesel and liquefied petroleum gas) and the technology quality (injection system and emission control). The experimental measurement methodology of unit emission of vehicles in real traffic situation is based on the use of the mini-Constant Volume Sampler for gas sampling and a set of gas analyzers for CO2, CO, NOx and THC, with an instrumentation to measure kinematics, gas temperature and pressure. The apparatus is also equipped with data logging instrument and data transfer. The results were compared with the database of the European light vehicles (Artemis). It was shown that the technological injection liquefied petroleum gas (LPG) has significant impact on air pollutants emission. Therefore, with the exception of nitrogen oxide compounds, uncatalyzed LPG vehicles are more effective in reducing emissions unit of air pollutants compared to uncatalyzed gasoline vehicles. LPG performance seems to be lower under real driving conditions than expected on chassis dynamometer. On the other hand, the results show that uncatalyzed gasoline vehicles emit high levels of carbon monoxide, and nitrogen oxides. Overall, and in the absence of standards in Algeria, unit emissions are much higher than Euro 3. The enforcement of pollutant emission standard in developing countries is an important step towards introducing cleaner technology and reducing vehicular emissions.

Keywords: on-board measurements of unit emissions of CO, HC, NOx and CO2, light vehicles, mini-CVS, LPG-fuel, artemis, Algeria

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Authors: K. Rumchev, S. Gilbey

Abstract:

Airborne particulate matter is a known hazard to human health, with a considerable body of evidence linking agricultural dust exposures to adverse human health effects in exposed populations. It is also known that agricultural workers are exposed to high levels of soil dust and other types of airborne particulate matter within the farming environment. The aim of this study was to examine exposure to agricultural dust among farm workers during the seeding season. Twenty-one wheat-belt farms consented to participate in the study with 30 workers being monitored for dust exposure whilst seeding or undertaking seeding associated tasks. Each farm was visited once and farmers’ were asked to wear a personal air sampler for a 4-hour sampling period. Simultaneous, real-time, tractor cabin air quality monitoring was also undertaken. Data for this study was collected using real-time aerosol dust monitors to determine in-tractor cabin PM exposure to five size fractions (total, PM10, respirable, PM2.5 and PM1), and personal sampling was undertaken to establish individual exposure to inhalable and respirable dust concentrations. The study established a significant difference between personal exposures and simultaneous real-time in-cabin exposures for both inhalable and respirable fractions. No significant difference was shown between in-cabin and personal inhalable dust concentrations during seeding and spraying tasks, although both in-cabin and personal concentrations were two times greater for seeding than spraying. Future research should focus on educating and providing farm owners and workers with more information on adopting safe work practices to minimise harmful exposures to agricultural dust.

Keywords: agriculture, air quality, Australia, particulate matter

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Authors: Sultan Haji Shube

Abstract:

Woodland ecosystems of semiarid rift valley of Ethiopia play a significant role in climate change mitigation by sequestering and storing more carbon. This study was conducted in Gidabo river sub-basins southeastern rift-valley escarpment of Ethiopian. It aims to estimate biomass and carbon stocks of woodlands and its implications for climate change mitigation. A total of 44 sampling plots (900m²each) were systematically laid in the woodland for vegetation and environmental data collection. A composite soil sample was taken from five locations main plot. Both disturbed and undisturbed soil samples were taken at two depths using soil auger and core-ring sampler, respectively. Allometric equation was used to estimate aboveground biomass while root-to-shoot ratio method and Walkley-Black method were used for belowground biomass and SOC, respectively. Result revealed that the totals of the study site was 17.05t/ha, of which 14.21t/ha was belonging for AGB and 2.84t/ha was for BGB. Moreover, 2224.7t/ha total carbon stocks was accumulated with an equivalent carbon dioxide of 8164.65t/ha. This study also revealed that more carbon was accumulated in the soil than the biomass. Both aboveground and belowground carbon stocks were decreased with increase in altitude while SOC stocks were increased. The AGC and BGC stocks were higher in the lower slope classes. SOC stocks were higher in the higher slope classes than in the lower slopes. Higher carbon stock was obtained from woody plants that had a DBH measure of >16cm and situated at plots facing northwest. Overall, study results will add up information about carbon stock potential of the woodland that will serve as a base line scenario for further research, policy makers and land managers.

Keywords: allometric equation, climate change mitigation, soil organic carbon, woodland

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Authors: Himanshu Lal, Bipasha Ghosh, Arun Srivastava

Abstract:

A pilot study of indoor air quality in terms of bioaerosol (fungus and bacteria) and few selective microbial volatile organic compounds (MVOCs) was carried out in different indoor sections of a library for two seasons, namely monsoon and post monsoon. Bioaerosol sampling was carried out using Anderson six stage viable sampler at a flow rate of 28.3 L/min while MVOCs were collected on activated charcoal tubes ORBOTM 90 Carboxen 564.Collected MVOCs were desorbed using carbon disulphide (CS2) and analysed by GC-FID. Microscopic identification for fungus was only carried out. Surface dust was collected by sterilised buds and cultured to identify fungal contaminants. Unlike bacterial size distribution, fungal bioaerosol concentration was found to be highest in the fourth stage in different sections of the library. In post monsoon season both fungal bioaerosol (710 to 3292cfu/m3) and bacterial bioaerosol (298 to 1475cfu/m3) were fund at much greater concentration than in monsoon. In monsoon season unlike post monsoon, I/O ratio for both the bioaerosol fractions was more than one. Rain washout could be the reason of lower outdoor concentration in monsoon season. On the contrary most of the MVOCs namely 1-hexene, 1-pentanol and 1-octen-3-ol were found in the monsoon season instead of post monsoon season with the highest being 1-hexene with 7.09µg/m3 concentration. Among the six identified fungal bioaerosol Aspergillus, Cladosporium and Penicillium were found in maximum concentration while Aspergillus niger, Curvuleria lunata, Cladosporium cladosporioides and Penicillium sp., was indentified in surface dust samples. According to regression analysis apart from environmental factors other factors also played an important role. Thus apart from outdoor infiltration and human sources, accumulated surface dust mostly on organic materials like books, wooden furniture and racks can be attributed to being one of the major sources of both fungal bioaerosols as well as MVOCs found in the library.

Keywords: bacteria, Fungi, indoor air, MVOCs

Procedia PDF Downloads 279