Understanding the environmental impacts of biogas utilization for energy production through life cycle assessment: An action towards reducing emissions.

Unlike renewable energy sources, burning fossil fuels has severe environmental impacts, such as greenhouse gas (GHG) emissions and climate change. Therefore, this study was conducted to assess and compare the environmental impacts of three biogas utilization scenarios for energy production. The life cycle assessment (LCA) method was used to compare (i) biogas combustion in combined heat and power (CHP) unit, (ii) biogas burning in a steam boiler, and (iii) biogas upgrading using pressure swing adsorption (PSA) unit to determine the most sustainable option. The results revealed that the upgrading scenario was the best option, achieving emission savings in 8 out of 10 investigated impact categories. Among them, the emission saving was the highest in the marine aquatic ecotoxicity category (-4276.97 kg 1,4-DB eq./MJ). The CHP scenario was the second-best option, followed by the boiler scenario (worst option), and both had the most beneficial performance in the ozone depletion potential category with 6.29E-08 and 9.88E-08 kg CFC-11-eq./MJ, respectively. The environmental burdens of the boiler scenario were the highest in the marine aquatic ecotoxicity category (248.92 kg 1,4-DB eq./MJ). Although the CHP and boiler scenarios contributed to environmental burdens in all impact categories, they achieved beneficial performances compared to fossil fuel-based systems.

Multiway PCA for Early Leak Detection in a Pipeline System of a Steam Boiler-Selected Case Studies.

In the paper the usability of the Multiway PCA (MPCA) method for early detection of leakages in the pipeline system of a steam boiler in a thermal-electrical power plant is presented. A long segment of measurements of selected process variables was divided into a series of "batches" (representing daily recordings of normal behavior of the plant) and used to create the MPCA model of a "healthy" system in a reduced space of three principal components (PC). The periodically updated MPCA model was used to establish the confidence ellipsoid for the "healthy" system in the PC coordinates. [d=replaced]The staff's decision of the probable leak detection is supported by comparison of the current location of the operating point (on the "fault trajectory") with the boundaries of the confidence ellipsoid.The location of the process operating point created the "fault trajectory," which (if located outside the confidence ellipsoid) supported the decision of probable leak detection. It must be emphasized that due to daily and seasonal changes of heat/electricity demands, the process variables have substantially greater variability than in the examples of batch processes studied in literature. Despite those real challenges for the MPCA method, numerical examples confirmed that the presented approach was able to foresee the leaks earlier than the operator, typically 3-5 days before the boiler shutdown. The presented methodology may be useful in implementation of an on-line system, developed to improve safety and maintenance of boilers in a thermal-electrical power plant.