Analytics 4.0: Online wastewater monitoring by GC and HPLC.

We present an automatically and autonomously operating online laboratory equipped with laboratory chromatographs as an example of Analytics 4.0. At BASF's largest production site in Ludwigshafen, Germany, multiple GC, HPLC, and IC systems are used in a mostly unstaffed laboratory for automated wastewater monitoring.

Direct aqueous injection with backflush thermal desorption for wastewater monitoring by online GC-MS.

A gas chromatography-mass spectrometry system with a novel injector type, which is designed for direct aqueous injection of wastewater, is presented. The system is used for online monitoring of the influent of the wastewater treatment plant at BASF's main chemical production site in Ludwigshafen, Germany. The purpose of monitoring is to protect the biological treatment process and the receiving water body, the Rhine.

Monitoring industrial wastewater by online GC-MS with direct aqueous injection.

An online GC-MS-system for automated monitoring of crude wastewater at a complex chemical production site is presented. The modular system is, in principal, based on commercial equipment, but utilizes a special, two-stage injector, which consists of a splitless vaporization chamber on top of a PTV injector filled with Tenax. This set-up enables direct injection of wastewater.

Rapid assays for environmental and biological monitoring.

Rapid, inexpensive, sensitive, and selective enzyme-linked immunosorbent assays (ELISAs) now are utilized in environmental science. In this laboratory, many ELISAs have been developed for pesticides and other toxic substances and also for their metabolites. Compounds for which ELISAs have recently been devised include insecticides (organophosphates, carbaryl, pyrethroids, and fenoxycarb), herbicides (s-triazines, arylureas, triclopyr, and bromacil), fungicides (myclobutanil), TCDD, and metabolites of naphthalene and toluene.

Application of the bootstrap to calibration experiments.

In calibration experiments, a number of samples of known concentration are used to establish the relationship between a measured response and sample concentration; this relationship is then used to estimate the unknown concentration of further samples from their measured responses. In addition to the estimates themselves, it is useful to have available some measure of their precision, usually given in the form of confidence limits. The standard method of inverting prediction limits is found to work well in simple situations, but in nonlinear multivariate calibration it becomes intractable.