Proposed Method for Determining Lead and Copper Concentrations in Water Using Low Cost Colorimetric Water Quality Testing Strips and a 14-bit Digital Camera

Date
2018
Authors
Flynn, Alyssa
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Abstract

Safe drinking water is still not guaranteed to everyone in the world. Places that continue to find themselves in poverty need a way to determine what sources are safe to drink from, while taking into consideration the cost to do so. Heavy metals such as lead and copper are of concern, especially in areas with large concentrations of children. Water quality testing strips alone, although inexpensive, may not be reliable enough to detect small incremental changes in water that could be encountered. The purpose of this study was to provide a cost-effective and easy-to-use process to better measure lead and copper in water supplies by using water quality testing strips, digital cameras and an open source software available for free to any user.

For this study, various lead and copper concentrations were examined using Merck Millipore Water Test Strips for lead and Hach Water Test Strips for Copper (colorimetric test strips). The test strips were dipped in spiked samples of water and compared to a color chart to conclude rough estimates of levels of contaminants found in the water.

Cameras come in a range of bit output files. The higher the number of bits, the more zeros and ones that are stored for each pixel in the photograph. When more digits are stored (i.e. eight-bit vs fourteen-bit), the tonal information for each pixel will be better. A fourteen-bit camera was used to take images of the strips that had been dipped in both distilled water and spiked distilled water to document the color changes observed. Means of red values, green values and blue values were compared at different concentrations to determine if any significant difference in the values were observed. The initial plan was to create a red, green and blue (RGB) signature for both lead and copper using increasing concentrations, but after finding no significant difference between mean color values, this was not performed.

The hope was that the images of the test strips would be able to detect smaller amounts of change in the lead level than the human eye would be able to detect. The result of this study concluded that this method of water quality testing would not be suitable at present time as a low-cost and user friendly method for aiding in determining drinking-water quality in areas lacking resources to pay for expensive water quality testing for their public health.

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Department
Civil and Environmental Engineering