Greenlandic water and sanitation systems—identifying system constellation and challenges

A good water supply and wastewater management is essential for a local sustainable community development. This is emphasized in the new global goals of the UN Sustainable Development, where the sixth objective is to: “Ensure availability and sustainable management of water and sanitation for all” (United Nations 2015). This obviously raises the question of how this can be achieved considering the very different conditions and cultures around the globe. This article presents the Greenlandic context and elucidates the current Greenland water supply system and wastewater management system from a socio-technical approach, focusing on the geographic, climatic and cultural challenges. The article identifies a diverse set of system constellations in different parts of Greenland and concludes with a discussion of health and quality of life implications.     

The search for an alternative to piped water and sewer systems in the Alaskan Arctic

Forty-two communities in rural Alaska are considered unserved or underserved with water and sewer infrastructure. Many challenges exist to provide centralized piped water and sewer infrastructure to the homes, and they are exacerbated by decreasing capital funding. Unserved communities in rural Alaska experience higher rates of disease, supporting the recommendation that sanitation infrastructure should be provided. Organizations are pursuing alternative solutions to conventional piped water and sewer in order to maximize water use and reuse for public health. This paper reviews initiatives led by the State of Alaska, the Alaska Native Tribal Health Consortium, and the Yukon Kuskokwim Health Corporation to identify and develop potential long-term solutions appropriate and acceptable to rural communities. Future developments will likely evolve based on the lessons learned from the initiatives. Recommendations include Alaska-specific research needs, increased end-user participation in the design process, and integrated monitoring, evaluation, and information dissemination in future efforts.     

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.     

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.