US Environmental Protection Agency, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA.
Published: April 2007
AI Article Synopsis
Article Abstract
Three different polyvinyl chloride (PVC) pipe types were subjected to de-ionized water exposures over the course of at least 180 days. Water exposed to the pipe was analyzed for organotin speciation and concentration. Organotin concentrations were the highest during the first 1-5 days. The species and concentrations of organotins leached varied by pipe type. Data were normalized by surface area in order to compare laboratory results with results from a residential pipe system. For one pipe type, the lowest non-zero concentrations from the laboratory tests overestimated organotin concentrations in solution when compared with water samples from the same pipe type in a residence. For organotin exposure estimates, a range of 0.1 ng m(-2) to 10 ng m(-2) could be used for mature pipes (e.g. in use for 1 year). These estimates should be refined with more field study, however, due to the high variation in organotin species and concentrations leached as a function of pipe type, accuracy within an order of magnitude may be optimal as, in many instances, the type of pipe installed or buried may be unknown. X-ray absorption spectroscopy (XAS) was used to identify organic and inorganic tin species in reference materials and the PVC samples. Monobutyl tin was identified as the primary organotin species in the pipes. Results from the XAS analyses also indicate that the technique shows promise for distinguishing between inorganic tin and organotins. Furthermore, organotins may be distinguished between mono-, di-, and tri-ligand species using XAS.
The maintenance and inspection of sewer pipes are essential to urban infrastructure but remain predominantly manual, resource-intensive, and prone to human error. Advancements in artificial intelligence (AI) and computer vision offer significant potential to automate sewer inspections, improving reliability and reducing costs. However, the existing vision-based inspection robots fail to provide data quality sufficient for training reliable deep learning (DL) models.
Background: Oesophago-gastric cancer surgery negatively affects quality of life with a high postoperative symptom burden. Several conditions that may be diagnosed and treated after surgery are recognised. However, consensus regarding their definition and management is lacking.
Iron oxide-impregnated filter papers (FeO) facilitate the study of soil phosphorus (P) desorption, availability and dynamics. However, many studies use homogenized and saturated shaking FeO soil systems, hindering opportunities to resolve environmentally relevant experimental objectives. This study created and evaluated a static microcosm to study soil P dynamics with FeO papers.
In this work, we employed experimental technique to study the issue of particle erosion and deposition in multiphase flows involving both particles of micro/meso- and nanoscale (sand particles and iron oxide particles). Especially, liquids with immersed nanoparticles gained a lot of interest in the recent years due to their enhanced thermal properties. At the same time, this type of fluids is still not widely used in practical and engineering applications, and one of the reasons is a risk of leading to erosion and deposition on, for instance, pipe walls.
