PCB exposure and potential future cancer incidence in Slovak children: an assessment from molecular finger printing by Ingenuity Pathway Analysis (IPA®) derived from experimental and epidemiological investigations

The risk of cancer due to PCB exposure in humans is highly debated. In eastern Slovakia, high exposure of the population to organochlorines (especially PCBs) was associated with various disease and disorder pathways, viz., endocrine disruption, metabolic disorder & diabetes, and cancer, thereby disturbing several cellular processes, including protein synthesis, stress response, and apoptosis. We have evaluated a Slovak cohort (45-month children, at lower and higher levels of PCB exposure from the environment) for disease and disorder development to develop early disease cancer biomarkers that could shed new light on possible mechanisms for the genesis of cancers under such chemical exposures, and identify potential avenues for prevention.

Microarray studies of global gene expression were conducted from the 45-month-old children on the Affymetrix platform followed by Ingenuity Pathway Analysis (IPA®) to associate the affected genes with their mechanistic pathways. High-throughput qRT-PCR TaqMan low-density array (TLDA) was performed to further validate the selected genes on the whole blood cells of the most highly exposed children from the study cohort (n = 71).

TP53, MYC, BCL2, and LRP12 differential gene expressions suggested strong relationships between potential future tumor promotion and PCB exposure in Slovak children. The IPA analysis further detected the most important signaling pathways, including molecular mechanism of cancers, prostate cancer signaling, ovarian cancer signaling, P53 signaling, oncostatin M signaling, and their respective functions (viz., prostate cancer, breast cancer, progression of tumor, growth of tumor, and non-Hodgkin’s disease). The results suggest that PCB exposures, even at the early age of these children, may have lifelong consequences for the future development of chronic diseases.

     

The probabilistic tsunami hazard assessment along Karnataka Coast from Makran Subduction Zone,west coast of India

Coastal tsunami amplitudes were calculated to identify areas susceptible to tsunami hazard at selected locations of the coast of Karnataka, west of India, due to earthquakes in the Makran Subduction Zone. This is the first time that the probabilistic tsunami hazard assessment along this study area has been attempted. A series of earthquake source scenarios with magnitudes of Mw 8.0, Mw 8.5, and a mega thrust of Mw 9.1 were modeled by using the Community Model Interface for Tsunami interface with the MOST model of Titov and Synolakis (J. Waterway, Port, Coastal and Ocean Engineering, 121(6), 308–316, 1995). As per the previous occurrences, the two least magnitudes are probable, while Mw 9.1 is a worst-case scenario as described by Heidarzadeh et al. (Ocean Engineering, 36(5), 368–376, 2009) and the same is reported by Burbidge et al. (Geoscience Australia Professional Opinion No. 2009/11) as high magnitude. These are not at all historical earthquakes or specifically from historical catalogues. The results of modeling show that all the seven coastal locations are inundated barely in our worst-case scenario with maximum water levels in the range of 100–200 cm. The first tsunami wave strikes the coast within 4–5 h of earthquake occurrence.     

An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP

Green vegetation cover fraction (VCF) is an important indicator of vegetation status in ecology and agronomy. Digital image analysis (DIA) has been widely accepted as a new VCF measurement technique. In this study, we present a novel fully automatic threshold segmentation algorithm for VCF measurements, which is named as upper inflection point plus mean gradient magnitude of edge pixels (UIP-MGMEP). The algorithm performs VCF estimation upon the vegetation index Excess Green (EXG). UIP-MGMEP optimizes the EXG threshold by searching the upper inflection point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of the boundary pixels between vegetation and background is larger than the variance of the background. Five typical sample images are used to illustrate how ground complexity reduces the distinctness of the UIP. Three controlled experiments are illustrated to test the robustness of UIP-MGMEP to resolution, exposure, and ground complexity. The results show that UIP-MGMEP is a promising algorithm for automatic VCF estimation upon digital images. Compared to broad-leaved grass, narrow-leaved grass is more sensitive to resolution and exposure. To reduce ground complexity, smaller footprint size while more images to cover the same area may be better than one image with large footprint size. UIP-MGMEP is fully automatic, making it promising for batch processing of VCF measurements that is very difficult in any wide-range field survey in the past. UIP-MGMEP algorithm can only extract green vegetation and is not suitable for non-green (even grayish-green) vegetation, due to the limits of vegetation index EXG. In addition, UIP-MGMEP is not recommended for images with VCF less than 0.5% or greater than 99.5%.     

Real<Emphasis Type="Bold">-</Emphasis>time water quality monitoring using Internet of Things in SCADA

Water pollution is the root cause for many diseases in the world. It is necessary to measure water quality using sensors for prevention of water pollution. However, the related works remain the problems of communication, mobility, scalability, and accuracy. In this paper, we propose a new Supervisory Control and Data Acquisition (SCADA) system that integrates with the Internet of Things (IoT) technology for real-time water quality monitoring. It aims to determine the contamination of water, leakage in pipeline, and also automatic measure of parameters (such as temperature sensor, flow sensor, color sensor) in real time using Arduino Atmega 368 using Global System for Mobile Communication (GSM) module. The system is applied in the Tirunelveli Corporation (Metro city of Tamilnadu state, India) for automatic capturing of sensor data (pressure, pH, level, and energy sensors). SCADA system is fine-tuned with additional sensors and reduced cost. The results show that the proposed system outperforms the existing ones and produces better results. SCADA captures the real-time accurate sensor values of flow, temperature, and color and turbidity through the GSM communication.     

Urban tracer dispersion experiments during the second DAPPLE field campaign in London 2004

As part of the DAPPLE programme two large scale urban tracer experiments using multiple simultaneous releases of cyclic perfluoroalkanes from fixed location point sources was performed. The receptor concentrations along with relevant meteorological parameters measured are compared with a three screening dispersion models in order to best predict the decay of pollution sources with respect to distance. It is shown here that the simple dispersion models tested here can provide a reasonable upper bound estimate of the maximum concentrations measured with an empirical model derived from field observations and wind tunnel studies providing the best estimate. An indoor receptor was also used to assess indoor concentrations and their pertinence to commonly used evacuation procedures.     

Assessment of the uncertainty of using an inverse-dispersion technique to measure methane emissions from animals in a barn and in a small pen

Dispersion techniques are useful for assessing the effectiveness of management practices in mitigating methane (CH₄) emissions from animal operations. In this paper, the accuracy of an inverse-dispersion technique was examined for two common situations: 1) emissions from animals in a barn and 2) emissions from animals in a pen. For both situations, the accuracy of emission estimates generally increased with increasing fetch (scaled to barn height, h, or to pen width, X_s) between the source and the concentration measurement. The gas recovery ratio increased from 0.66 at 5 h to 0.93–1.03 at 10 h–25 h for the barn, and decreased from 1.59 at 0 X_s to 0.99 at 5 X_s and from 1.54 at 0 X_s to 1.09 at 5 X_s for the two small pen scenarios, due to the declining sensitivity of the dispersion model to errors in wind complexity and errors in the assumed source configuration. However, the relative uncertainty of the measured concentration increased with fetch due to the decreasing gas concentrations. Hence, improving the accuracy of emission estimates is a compromise between the source configuration sensitivity and the concentration measurement sensitivity. Fetches of about twice the size of the pen and about 10 times the height of the barn are suggested.     

Verification of diffusive and pumped samplers for volatile organic compounds using a controlled atmosphere test facility

There is a requirement to verify the performance of sorbent-based passive or active samplers and to extend their use, where possible, to monitor volatile organic compounds (VOCs) that are known to be photochemical ozone pre-cursors or are relevant to the activities of the petrochemical industry. We report measurements of the 14-day diffusive uptake rates for the VOCs: i-butane (2-methyl propane), n-butane, i-pentane (2-methyl butane), n-pentane, n-hexane, benzene, toluene, and m-xylene (at environmental level concentrations) for industry standard axial samplers (Perkin–Elmer-type samplers) containing the sorbents Carbopack-X, -Z, -B or Tenax-TA. We also present data on back-diffusion, blank levels, and storage for the above sorbents, and describe the simultaneous use of the sorbent Carbopack-X for pumped sampling of certain VOCs. The results were obtained by dosing samplers in a controlled atmosphere test facility (CATFAC) operating under well-defined conditions of concentration, nominal temperature of 20 °C, wind speed of 0.5 m s^?1, and relative humidities of 0% and 80%. Field measurements were also obtained to provide supplementary data to support the laboratory study. Results are compared to existing published data, where these are available.     

Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.     

Economic damages of ozone air pollution to crops using combined air quality and GIS modelling

This study aims at presenting a combined air quality and GIS modelling methodological approach in order to estimate crop damages from photochemical air pollution, depict their spatial resolution and assess the order of magnitude regarding the corresponding economic damages. The analysis is conducted within the Greater Thessaloniki Area, Greece, a Mediterranean territory which is characterised by high levels of photochemical air pollution and considerable agricultural activity. Ozone concentration fields for 2002 and for specific emission reduction scenarios for the year 2010 were estimated with the Ozone Fine Structure model in the area under consideration. Total economic damage to crops turns out to be significant and estimated to be approximately 43 M€ for the reference year. Production of cotton presents the highest economic loss, which is over 16 M€, followed by table tomato (9 M€), rice (4.2 M€), wheat (4 M€) and oilseed rape (2.8 M€) cultivations. Losses are not spread uniformly among farmers and the major losses occur in areas with valuable ozone-sensitive crops. The results are very useful for highlighting the magnitude of the total economic impacts of photochemical air pollution to the area’s agricultural sector and can potentially be used for comparison with studies worldwide. Furthermore, spatial analysis of the economic damage could be of importance for governmental authorities and decision makers since it provides an indicative insight, especially if the economic instruments such as financial incentives or state subsidies to farmers are considered.