State of the Science: Review of Quantitative Tools to Determine Wastewater Soil Treatment Unit Performance (häftad, eng)

This literature review focused on STU performance, key conditions or factors potentially affecting STU performance, and the current best practices for using models and other available tools to predict expected STU performanceThe information gained during this literature review will guide the future direction of the project. Constituents of interest include nitrogen (N), phosphorus (P), microbial pollutants, and emerging organic wastewater contaminants (OWCs). Based on this literature review, it is clear that due to the variability of data collected at field sites, simple binary relationships (e.g., C/Co versus depth for various soil types) for statistical predictions of the attenuation of N, P, microorganisms or OWCs cannot be justified.

Specific to N, hydraulic loading rate appears to be more important than soil texture or soil depth within the first 30-60 cm, although both soil depth and texture remain important variables.

Most of the reported results related to the interaction of P with soil appear to be from laboratory batch tests Similarly, field-scale evaluations of pathogen removal are limited. Finally, most of the existing OWC work has focused on the occurrence and concentrations of selected compounds in streams, lakes, and groundwater impacted by wastewater treatment plant effluents. Currently very few models have been developed for movement and treatment processes of N or P in OWTS.

However, adapting the CW2D model for STUs that will predict the effect of different soil types (texture, structure, and drainage class) appears promising. CW2D is a module of the well known HYDRUS model designed to simulate nitrogen treatment in a sand filter. This model incorporates most of the features one might consider, including a comprehensive treatment of microbial growth, the impact of oxygen mass transfer on nitrogen transformation, and variable rates of denitrification due to changes in dissolved oxygen concentrations, dissolved organic matter, and microbial growth.

The review of existing models demonstrates that simulation of microbial characteristics in OWTS is still largely uncharted territory.