Grantee Research Project Results

2016 Progress Report: Smart Turbidimeters for Remote Monitoring of Water Quality

EPA Grant Number: SU835732
Title: Smart Turbidimeters for Remote Monitoring of Water Quality
Investigators: Ball, William P. , Kelley, Chris , Majithia, Vishwesh , Backer, Andrew , He, Ziwei
Current Investigators: Ball, William P. , Kelley, Chris , Backer, Andrew , Brunner, Logan , Burkland, Alison , Farhat, Michelle , He, Ziwei , Majithia, Vishwesh , Murphy, Sushant , Kahn, Daniel
Institution: The Johns Hopkins University
EPA Project Officer: Page, Angela
Phase: II
Project Period: October 1, 2014 through August 31, 2017
Project Period Covered by this Report: October 1, 2015 through September 30,2016
Project Amount: $89,995
RFA: P3 Awards: A National Student Design Competition for Sustainability Focusing on People, Prosperity and the Planet - Phase 2 (2014) Recipients Lists
Research Category: P3 Challenge Area - Safe and Sustainable Water Resources , P3 Challenge Area - Sustainable and Healthy Communities , Sustainable and Healthy Communities

Objective:

The unaided eye can distinguish cloudy water from clear water, but even visibly clear samples of water can have dangerous quantities of pathogens. Commonly, a chemical or physical disinfectant (such as chlorine, or ultraviolet light) is applied to water during treatment to inactivate pathogens so the water may be safely consumed. However, natural water sources typically contain suspended sediments (such as clay, silt, organic matter) which can interfere with drinking water disinfection by reducing chemical disinfectants in redox reactions (or by reflecting UV light) and by providing micro‐refuges in which pathogens can be shielded from disinfecting light or chemicals. It is crucial that suspended sediments be removed to the best practicable extent during drinking water treatment, and that suspended sediment levels are taken into consideration when selecting disinfectant dosage levels. 

The removal of suspended sediment is most commonly accomplished through the addition of coagulant chemicals which help to cluster many small suspended sediment particles into fewer, larger sediment particles which can be more easily removed later. The physics and chemistry of these coagulation processes are sufficiently complex in real‐world applications that empirical methods must be employed to assess the proper dosage of a given coagulant for a given body of water (with such assessments typically updated at least seasonally). To help determine coagulant dosage, engineers will typically employ a tool known as a jar tester (essentially a power mixer with multiple mixing chambers and variable speed) to examine the effects of varying coagulant doses in parallel. There is, to date, no published record of a jar tester that may be constructed from basic components, operated in field conditions (without AC mains), or easily repaired and maintained by the user. Commercial jar testers cost thousands of dollars, placing this crucial tool beyond the need small‐scale water treatment operations around the world.

To assess suspended sediment levels in water, engineers typically use a proxy measure of the turbidity, or “cloudiness” that these suspended sediments cause. The device for such measurement is known as a turbidimeter. The modern commercial turbidimeter is a complex piece of equipment that costs several hundred dollars, largely because it is designed to be an extremely accurate, general‐purpose laboratory tool. This price is beyond the reach of many low‐resource communities around the world. Without access to more affordable turbidimeters, such communities are unable to proactively assess the microbial risk of their drinking water or confirm levels of treatment they are hoping to achieve. Alternative measures, such as microbial culturing, require equally great expense and time, such that they are impractical for daily use and real‐time information processing. By contrast, turbidity measurements (once equipment is available) can be assessed in seconds and at negligible cost per measurement. An affordable, open‐source turbidimeter designed specifically for water quality monitoring would therefore broaden access to the principal quality‐assurance procedure in the drinking water treatment sector and remove a major roadblock to the sustainability of programs that seek to expand global access to treated drinking water.

During Phase II of this project, the Johns Hopkins “Smart” Turbidimeters team continued development of the low‐cost, open‐source inline and handheld turbidimeters developed the previous year. The durability and accuracy of the submersible inline turbidimeter was significantly improved through hardware and software modifications, while the per‐unit cost reduced (to $40/unit). A photodiodebased prototype of an open‐source low‐cost ($40) handheld turbidimeter was developed; while somewhat more complicated in design than the monolithic sensor‐based turbidimeter developed last year (based on the TSL230RD light‐to‐frequency sensor), the photodiode‐based prototype offers multiple potential advantages in low‐light detection and statistical evaluation of turbidity readings. The team developed a prototype open‐source low‐cost ($150) battery‐powered jar tester, and thus has now completed at least one prototype of each device specified in the project goals. And, the partnership with the AguaClara drinking water infrastructure design program at Cornell University to develop a mobile app (targeting affordable, low‐end Android smartphones) to interface with the prototype handheld and inline turbidimeters via Bluetooth. After successful implementation, this mobile app will be expanded to interface with the prototype jar tester.

Progress Summary:

In the second year of the Phase II project, the handheld and inline turbidimeter design have iteratively improved without increasing costs, and we have completed a prototype of an open‐source jar tester. 

Casing: We reached the limits of what we could reasonably accomplish with 3D‐printed (filament deposition) cases – 3D printing is a time‐consuming process, and as we have improved the optical instrumentation of our handheld turbidimeters, the slight (thermal and shear) deformability of our 3Dprinted cases became increasingly problematic. We have always considered it a key piece of this project is to build water quality monitoring tools that are not only affordable and open‐source, but to use lowcost, commonly available manufacturing tools and methods. Our previous cases were built using an open‐source RepRap 3D printer that can be built for roughly $700. We have begun building cases with a desktop 3‐axis CNC mill, which can be purchased for $1100. To test the limits of low‐cost manufacturing, we have also undertaken to machine cases and internal optical instrumentation holders for our handheld turbidimeters using just a drill press ($80) and a band saw ($100). This process should help us to better understand how affordably small‐scale manufacturing centers could be set up in developing countries to produce the devices developed in this project.

Inline turbidimeter: The resolution of the inline turbidimeter has been greatly improved by increasing the number of IR LEDs from two to four (arranged in a rectangle around the central sensor) and implementing the “stretchy” sampling window times and turbidity‐dependent sample batch sizes that we earlier successfully implemented in the prototype handheld turbidimeter. To summarize the “stretchy” sampling windows:  For a given sample measurement, multiple readings are taken – each with a different fractional multiplier applied to a standard one‐second reading interval (this multiplier then divided from the numerical reading). This “time stretching” of the sampling window is comparable to adding noise to the signal received by the sensor, and yields a significantly better averaged result at low turbidities than would be obtained from simple replicate sampling. (We have tried using equalinterval sampling window fractions (e.g. 9/8, 10/8, 11/8… seconds) and coprime sampling window fractions (e.g. 8/7, 6/5, 4/3… seconds); so far, these appear to perform equally well.) With these improvements we have been able to lower the linear turbidity detection threshold to below 2 NTU. 

New optics for handheld turbidimeters: While the light‐to‐frequency sensor (TSL230RD) we have incorporated in previous handheld and inline turbidimeters provides a simple, hassle‐free optical setup, we decided to develop an alternative optical setup using silicon‐based photodiodes and an analog signal processing front‐end to take advantage of the speed and low‐light sensitivity of amplified silicon photodiodes (which are mainstays of high‐speed fiber‐optics communications systems). In addition to reduced sampling times, this new sensing paradigm makes a ratio turbidimetric sensing setup (utilizing a second photodiode measuring attenuated light through a sample to improve resolution and linearity) more feasible, and offers the ability to increase the number of replicates in a single read by an order of magnitude, making practical the calculation of confidence intervals for turbidity measurements and the statistical detection of potential hardware errors (such as optical drift, or intermittent light leakage in the cuvette chamber). In the coming year we intend to adapt this setup for the inline turbidimeter – with the addition of a chopper driver (to transform the constant brightness of the LED driver in the current optical setup into a modulated square wave) and synchronization of the chopper driver and the photodetector, the inline backscatter turbidimeter can completely compensate for the presence of significant background light. This is particularly useful as it is infeasible to completely shield the inline turbidimeter sampling window from stray light, and the current solution for ambient light filtering (visible light‐blocking film) has a limited life span and does not block IR light from the sun. 

Smartphone‐based user interface: The first version of the smartphone app developed in collaboration with AguaClara is available in the Google Play Store

Broader Context: According to UN estimates roughly 660 million people lack access to “improved” sources of drinking water, with some form of protection from contamination. Recent research however suggests that upwards of two billion may be regularly consuming drinking water that is contaminated with fecal bacteria. Further, the number of people drinking water that is not regularly monitored for such contamination is unknown but likely much higher than two billion. There is an urgent and vastly underappreciated need for extremely low‐cost water quality monitoring technology, particularly for technology that has both low upfront and per‐test costs, and a testing time that is sufficiently short that water may be regularly tested before it is consumed. 

This project began with the aim of providing a very low‐cost platform for turbidity detection to help water treatment plants manage their treatment processes, since turbidity is one of the most important real‐time water quality indicators. Initial prototypes of a low‐cost turbidimeter were sufficiently promising to motivate further iteration, and the handheld turbidimeter models we produced last year were admirably compact and power‐conscious. We noticed however that field testing data was not as promising as lab testing data, and upon further testing we saw the need to improve detection of very low turbidity levels, reduce the influence of ambient temperature on device performance, speed up the recalibration process, and deliver more statistical data (such as the standard deviation and confidence interval) to reflect the inherent uncertainty of turbidity measurements. All of the work described above was motivated by these needs.

Future Activities:

The Johns Hopkins “Smart” Turbidimeter team has built on the work produced during the first year of Phase II of this P3 grant. We have significantly improved upon our previous device designs, and have now completed prototypes of all Phase II deliverables. This work takes steps towards the ready availability of affordable, responsive, remotely accessible, real‐time water quality monitoring with wide potential ramifications for the sustainability and public health of water treatment projects in developing regions around the world. We greatly appreciate the one‐year timeline extension granted to this project, and look forward to fully ground‐testing our devices, user interface tools, and communications network during this final year.

Journal Articles:

No journal articles submitted with this report: View all 2 publications for this project

Supplemental Keywords:

Turbidity, chlorine residual, water quality monitoring, open‐source, low‐cost technology, sustainable development

Relevant Websites:

Design repository for AWQUA Exit

Progress and Final Reports:

Original Abstract

2015 Progress Report

Final Report

P3 Phase I:

"Smart" Turbidimeters for Remote Monitoring of Water Quality  | Final Report