ENVIRONMENTAL MONITORING FOR MICROPOLLUTANTS USING HIGH-RESOLUTION MASS SPECTROMETRY AND DATA-DRIVEN METHODS

Abstract

Currently monitored contaminants represent only a fraction of the total chemicals present in natural water resources. There are over 100,000 chemicals used today and population growth has amplified global chemical manufacturing and production. The human and ecological exposome, a total measure of exposures over a lifetime, is poorly understood – particularly with respect to micropollutant exposure. Micropollutants are trace organic contaminants and represent a diverse set of chemicals such as pharmaceuticals, personal care products, pesticides, and industrial compounds. Many micropollutants were designed to be persistent and bioactive, and as a result, they can accumulate in the environment far away from their sources and their toxicological effects can be severe (e.g., carcinogenic, interfere with endocrine systems, and cause anti-bacterial resistance). Micropollutants often occur at low concentrations in water resources (ng·L-1 to µg·L 1 range), which poses challenges for modern analytical technologies. The sources and spatiotemporal dynamics of micropollutants in the environment are also poorly understood, which presents challenges for developing regulations and mitigation strategies. The recent development of high-resolution mass spectrometry (HRMS) allows for the simultaneous detection of potentially thousands of known and unknown micropollutants by allowing extremely precise and accurate measurements at low concentrations. However, HRMS techniques have not often been utilized for environmental micropollutant monitoring, partly due to the lack of universal standard methods. Additionally, covariates such as geospatial features and spatiotemporal environmental conditions are infrequently coupled with monitoring data to improve our understanding of the processes that control spatiotemporal micropollutant dynamics. Three micropollutant monitoring studies were designed to more fully characterize and understand the surface water exposome by coupling broad micropollutant characterization afforded by HRMS with data-driven methods to further our understanding of micropollutant sources, fate, and transport. The first study incorporates spatially distributed sampling throughout a large watershed to discover links between the occurrence and concentrations of micropollutants, geospatial features of the watershed, and micropollutant sources. The second study incorporates highly resolved temporal sampling and utilizes micropollutant occurrence trend patterns to prioritize analytical data for identification of unknown micropollutants. The third study couples highly resolved micropollutant concentration trends with a set of environmental covariates to further our understanding of how environmental processes control micropollutant dynamics in surface waters as a means to predict peak events and inform intermittent sampling strategies. These environmental monitoring techniques and their results will aid future micropollutant monitoring campaigns to obtain more representative results and enable better management of micropollutants in surface water systems.