Establishment of Monitoring Methods and Risk Assessment for Microcystis and Microcystins in the Ambient Air near Eutrophic Surface Water Bodies

Abstract

Inhalation is a potential pathway for human exposure to cyanotoxins However research about measurement of microcystin in ambient air and inhalation exposure is limited Therefore this study is aimed to establish the sampling and analytical methods for microcystins in air and to estimate the exposure and health risk for the people living/working near studied lakes/reservoirs with cyanobacteria issues Three different types of air samplers including inhalable dust sampler (IOM) BioSampler? and steam-jet aerosol collector (SJAC) were chosen and studied to optimize sample collection of Microcystis and microcystins Quantitative PCR (qPCR) was used to quantify the genes for Microcystis and enzyme-linked immunosorbent assay (ELISA) and liquid chromatography-mass spectrometry/ mass spectrometry (LC/MS/MS) were used to quantify microcystins Field sampling were condudcted and the data were further used to determine the inhalation exposure of micricystins and to assess the human health risk For IOM the results show that cell-bound 16S rRNA gene and mcyB gene were not significantly degraded in the sampling time of 8 hrs However for the extra-cellular DNA on the filtrate only less than 0 1% of 16S rRNA gene and mcyB gene remained after 8 hrs of sampling For BioSampler? flow of pump is not the reason for the loss of genes in the process of pretreatment The optimal recovery efficiency was 40% and 50% for 16S rRNA gene and mcyB gene respectively Among the three media tested to improve collection efficiency ASM was chosen due primarily due to collection efficiency and ease to analyze Among the field sampling activities the highest concentration of microcystins detected was collected with BioSampler? in Hulupi (HLP) pond sampling The data were then used to evaluate the highest risk of inhalion for the people workng near HLP The hazard index (HI) was less 1 0 124 and no significant risk was expected

Date of Award	2019
Original language	English
Supervisor	Tsair-Fuh Lin (Supervisor)