Accurate determination of the size and the number of nanoparticles plays an important role in many different environmental studies of nanomaterials, such as fate, toxicity, and occurrence in general. This work presents an accurate model that estimates the number of nanoparticles from the mass and molar concentration of gold nanoparticles (AuNPs) in water. Citrate-capped AuNPs were synthesized and characterized using transmission electron microscopy (TEM) and ultraviolet–visible spectroscopy (UV-vis). A mimic of environmental matrices was achieved by spiking sediments with AuNPs, extracted with leachate, and separated from the bulk matrix using centrifuge and phase transfer separation techniques. The quantification of AuNPs’ molar concentration on the extracted residues was achieved by inductively coupled plasma optical emission spectroscopy (ICP-OES). The molar concentrations, an average diameter of 27 nm, and the colloidal suspension volumes of AuNPs enable the calculation of the number of nanoparticles in separated residues. The plot of the number of AuNPs against the mass of AuNPs yielded a simple linear model that was used to estimate the number of nanoparticles in the sample using ICP-OES. According to the authors’ knowledge, this is the first adaptation of the gravimetric method to ICP-OES for estimating the number of nanoparticles after separation with phase transfer.

This study reports a simple, fast, and low-cost detection of noradrenaline (NA) in wastewater using citrate-capped colloidal gold nanoparticles (AuNPs). The addition of NA to citrate-capped colloidal AuNPs generates a colour modulation that the bare eye can detect due to the aggregation of the colloidal AuNPs. The relationship between the NA concentration and colloidal AuNPs aggregation was further monitored by ultraviolet–visible light (UV–vis) spectroscopy in an aqueous solution. The method displayed a linear range of 0–500 μM with R2 = 0.99 and an LOD and LOQ of 42.2 and 140.5 μM. Application in an environmental sample collected from the Darville Wastewater Treatment Plant shows that this work provided a cost-effective and spectrophotometric method that could be used for monitoring contamination in wastewater.

Cyanobacteria, an algae bloom that is responsible for the creation of deadly toxins. These toxins have the potential to adversely impact human and animal health. Microcystins (MC’s), are harmful toxins that are produced by cyanobacteria species. These deadly toxins are the most investigated toxins worldwide. However, in South Africa their occurrence statistics are deficient due to inaccessibility of reliable, sensitive, and precise analytical methods to investigate them in water surfaces. Thus, a development of analytical methods for the detection and accurate quantification of algal toxins is crucial to consider the health risk of exposure to toxins in wastewater and surface waters. This study recommends an analytical method for the detection and quantification of algal toxins using solid phase extraction (SPE) and high-performance liquid chromatography (HPLC) coupled with photodiode detector (PDA). The developed method was validated based on linearity which ranged from 3–2500 µg L− 1, recoveries at 99.6–113.9%, the limit of detection (LOD) ranging from 0.2–480 µg L− 1, and limit of quantification (LOQ) at 0.7–160 µg L− 1 and the regression coefficients obtained were above 0.9880 in all analytes. The developed method was applied to Darvill Wastewater Treatment Plant, Umgeni water, Durban surface waters, University of KwaZulu-Natal (UKZN) sport centre tap water and UKZN Westville two ponds), South Africa. MC-RR was the most detected analyte at concentration ranging from 0.069–30.521 ng L− 1 compared to other targeted MCs. The developed method is simple and cheap, which can consent developing countries to monitor these deadly MC toxins in water surfaces.