Comparative reductions of norovirus, echovirus, adenovirus, Campylobacter jejuni and process indicator organisms during water filtration in alluvial sand.

Sand filtration is a cost-effective means of reducing microbial pathogens in drinking-water treatment. Our understanding of pathogen removal by sand filtration relies largely on studies of process microbial indicators, and comparative data from pathogens are sparse. In this study, we examined the reductions of norovirus, echovirus, adenovirus, bacteriophage MS2 and PRD1, Campylobacter jejuni, and Escherichia coli during water filtration through alluvial sand.

Achieving unbiased predictions of national-scale groundwater redox conditions via data oversampling and statistical learning.

An important policy consideration for integrated land and water management is to understand the spatial distribution of nitrate attenuation in the groundwater system, for which redox condition is the key indicator. This paper proposes a methodology to accommodate the computational demands of large datasets, and presents national-scale predictions of groundwater redox class for New Zealand. Our approach applies statistical learning methods to relate the redox class determined on groundwater samples to spatially varying attributes.