Abstract

Wastewater from car washers and lubricators contain high levels of hydrocarbons. These are discharged into the public sewer system without proper treatment and not complying with the regulations. In this study was evaluated the process of bioremediation of total hydrocarbons in Puyango’s wastewater, using bioaugmentation treatment, which means, applying hydrocarbons-degrading microorganisms. First, a characterization of the wastewater was carried out, and the content of total petroleum hydrocarbons (TPH) and the flow rate was determined for seven days. A mixture of bacteria: Acinetobacter sp., Pseudomonas sp. y Mycobacterium sp was applied in solid form (80 g tablet) with a minimum concentration of 4 x 108 CFU / ml soluble in water, using 2 tablets during 30 days of treatment. The concentration of the TPH was determined weekly, plotting the temporal variation and quantifying the % of removal. The results indicate that the technique of bioaugmentation was effective (p = 0.003) in the removal of the TPH, obtaining percentages above 86 %. The time of greatest removal of TPH was obtained in the third week of treatment with 92 %. In addition, COD removals were obtained –40 %, Oils and fats - 50%, Surfactants –43 % thus fulfilling the current regulations for discharge to the public sewer system for the TPH.

Abstract

Safety and reliability of hydrocarbon transportation lines (pipelines) around the world represents a critical aspect for industry, operators and population. Lines failures caused by external agents, corrosion, inadequate designs, among others, generate impacts on population, environment, infrastructure and economy, besides it may be catastrophically. Therefore, it is essential to constantly monitor operating conditions and hydraulic lines to faults and thus to take measures to mitigate the failure. Localization of leakage is more than comparison between simulated and measured flows, from the dynamic of these flows it can be inferred the localization of the leakage, and even its magnitude. One option is to develop an inverse Transient Model (TM) able to calculate parameters of the pipeline by using the measured flow. However, if the calculation of flows is computational expensive, the inverse calculation is even more. These phenomenological models reproduce as closely the response (flow and pressure) of the pipeline. The simulation contains information to optimize the pumping rate, the momentum and energy including a high number of inputs and constraints to consider that growing exponentially with the level of detail to get in the pipeline. Therefore, this method has a high computational cost. The other option is to simulate several scenarios by using TM and train some kind of classifier or predictor with the simulated measurements. The first phase of our complete proposed methodology under development is presented in this work. We have focused on carrying out simulations of pressure along a pipeline using TM and applying Principal Component Analysis (PCA) as a tool to recognize hided patterns which allow classify leakages in different locations and different magnitudes. doi: 10.12783/SHM2015/292 Document type: Conference object