Addressing barriers to the wide-scale implementation of roof runoff and stormwater collection and use projects for non-potable end uses in the U.S.
Date
2023
Authors
Alja'fari, Jumana Hamdi Mahmoud, author
Sharvelle, Sybil, advisor
Arabi, Mazdak, committee member
De Long, Susan, committee member
Nelson, Tracy, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
Roof runoff and stormwater have the potential to serve as important local water sources and diversify the water budget portfolio in regions with dwindling water supplies and increasing populations. Due to the lack of guidance regulating the use of roof runoff for non-potable end uses, characterizing its microbial quality is necessary to promote roof runoff use across the U.S. Similarly, the degree of stormwater microbial contamination is still not well understood, and uncertainty about the required treatment is a barrier for the implementation of stormwater capture and use (SCU) projects. Stormwater runoff could become contaminated with human fecal matter in areas with aging infrastructure where raw wastewater exfiltrate from sewer networks to stormwater collection networks, areas with homeless encampments, or areas with sanitary sewer overflows (SSOs). Stormwater practitioners wanting to benefit from stormwater to augment the available water resources struggle with the selection and design of efficient stormwater treatment trains that are protective of public health for the designated end use. Knowledge of the degree to which stormwater is contaminated with human fecal matter, termed here as the human fecal contamination analog (HFCA), is critical for the design process and estimating the required pathogen log reduction targets (LRTs).To address the barrier to wide-scale implementations of roof runoff collection and use projects, a 2-year research study was designed to examine roof runoff microbial quality in four U.S. cities: Fort Collins, CO; Tucson, AZ; Baltimore, MD; and Miami, FL. Sample collection was conducted as part of a citizen science approach. The occurrence and concentrations of indicator organisms (E. coli and enterococci) and potentially human-infectious pathogens (PHIPs) including Salmonella spp., Campylobacter spp., Giardia duodenalis, and Cryptosporidium parvum in roof runoff were determined using culture methods and digital droplet polymerase chain reaction (ddPCR), respectively. E. coli and enterococci were detected in 73.4% and 96.2% of the analyzed samples, respectively. Concentrations of both E. coli and enterococci ranged from <0 log10 to >3.38 log10 MPN/100 mL. Salmonella spp. invA, Campylobacter spp. ceuE, and G. duodenalis β – giardin gene targets were detected in 8.9%, 2.5%, and 5.1% of the analyzed samples, respectively. Campylobacter spp. mapA and C. parvum 18S rRNA gene targets were not detected in any of the analyzed samples. This dataset represents the largest-scale study to date of enteric pathogens in U.S. roof runoff collections and will inform treatment targets for different non-potable end uses for roof runoff. To address barriers to the wide-scale implementation of SCU projects for non-potable end uses, stormwater microbial contamination originating from human fecal matter was examined using the detection frequencies and concentrations of human microbial source tracking (MST) markers and PHIPs observed in stormwater. Measurements of human MST markers in wet weather flows, dry weather flows, and influent wastewater in addition to measurements of viral and protozoan pathogens in wet weather flows and influent wastewater were compiled through a systematic review. Human MST marker and PHIP datasets were statistically analyzed and used to estimate HFCAs based on relative concentrations of microbial contaminants in stormwater compared to municipal wastewater. Analytical statistical distributions of the original data, unpaired Monte Carlo simulation, and paired Monte Carlo simulation were applied for the estimates of HFCAs in wet and dry weather flows. Estimates of human MST-based HFCAs are more reliable than PHIP-based HFCAs because the current PHIP datasets are limited by detection limits and the range of data observed within the statistical distributions. Unpaired Monte Carlo simulations and analytical statistical distributions were found to be the best methods for the estimation of human MST-based HFCAs in wet and dry weather flows which ranged from <10-7.0 to 10-1.5 and 10-12 to 10-2.6, respectively. Pathogen LRTs were determined in this study using HFCAHuman MST Markers and previously published quantitative microbial risk assessments (QMRAs) to guide the selection of stormwater treatment process trains based on the intended end use (e.g., unrestricted irrigation or indoor use) of stormwater. Combinations of stormwater treatment trains at varying HFCA levels were evaluated based on complexity and reliability of the suggested trains. To use stormwater safely for unrestricted irrigation and indoor uses, treatment trains containing both filtration and disinfection unit processes are required. The HFCA threshold beyond which the complexity of stormwater trains becomes considerably higher is 10-4. Performance evaluation of the suggested stormwater treatment trains revealed that trains consisting of membrane filtration and at least two disinfection unit treatment processes, specifically ultraviolet (UV) and ozone (O3) or UV and chloramine are recommended at HFCA values of 10-3, 10-2, and 10-1. At HFCA value of 10-4, a treatment train consisting of membrane filtration and O3 or chloramine is recommended. The use of free chlorination at all HFCA levels is not recommended due to the high continuous monitoring requirements associated with the use of free Cl2.
Description
Rights Access
Embargo Expires: 05/26/2025
Subject
microbial source tracking markers
stormwater capture and use
potentially human-infectious pathogens
human fecal contamination analog