EAGER: PPER: Enable Crowdsourcing in Microbial Water Quality Monitoring in Water Distribution Networks

点击翻译按钮获取中文摘要

Microbial contamination of drinking water within the distribution networks can occur at unspecified locations, at unspecified times, and due to diverse reasons, causing significant public health problems and uncertainties. The final critical control point against microbial contamination within the water distribution networks is at the tap where human water consumption occurs, yet water quality monitoring at the tap represents a major operational challenge to water utilities. This challenging problem, however, is an excellent opportunity for involving and motivating the public in water quality engineering research, as water customers are perfectly situated and often interested and motivated in knowing water microbial quality at their own homes. If enabling, low-cost tools are available to water customers, this could become an excellent example of how citizen science can be cultivated and harnessed to solve a complex and otherwise intractable water quality engineering problem. Two major technology gaps for involving citizens in this crowdsourcing approach include: (1) collecting reliable water microbial quality data within households and low-cost tools, and (2) encouraging and facilitating voluntary and efficient data sharing. The research goal of this project is to enable crowdsourcing by specifically and effectively addressing these two technology gaps. This project uses an iterative citizen consultation process to optimize a crowdsourcing approach that enables low-cost and high-quality measurements of total coliform and E. coli in drinking water samples by water consumers. Specifically, a commonly used EPA method is being adopted and modified for home implementation using commonly available household tools. The two research objectives are (1) to define, test, and optimize the proposed crowdsourcing approach, and (2) to investigate the feasibility of using an integrated device for one-step water sample collection and subsequent processing. The project involves a large group of undergraduate students at a largely commuter campus with diverse backgrounds as citizen scientists. Their participation not only provides feedback to the design, test, and optimization of the crowdsourcing approach, but also provides the participants with a great opportunity to understand the importance and complexity of water quality data collection in the distribution networks.