Continuously optimizing a groundwater remediation system in complex fractured media

Former chemical plant, groundwater monitoring, 3D finite elements numerical model

On the Redox-Activity and Health-Effects of Atmospheric Primary and Secondary Aerosol: Phenomenology

The RHAPS (Redox-Activity And Health-Effects Of Atmospheric Primary And Secondary Aerosol) project was launched in 2019 with the major objective of identifying specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g., number size distributions, refractory chemical components, elemental composition) and low-time resolution analyses (e.g., oxidative potential, toxicological assays, chemical composition). Preliminary results indicate that, at the real atmospheric conditions observed (i.e., daily PM1 from less than 4 to more than 50 ug m-3), high/low mass concentrations of PM1, as well as black carbon (BC) and water soluble Oxidative Potential (WSOP,) do not necessarily translate into high/low toxicity. Notably, these findings were observed during a variety of atmospheric conditions and aerosol properties and with different toxicological assessments. Findings suggest a higher complexity in the relations observed between atmospheric aerosol and toxicological endpoints that go beyond the currently used PM1 metrics. Finally, we provide an outlook to companion papers where data will be analyzed in more detail, with the focus on source apportionment of PM1 and the role of source emissions on aerosol toxicity, the OP as a predictive variable for PM1 toxicity, and the related role of SOA possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity