Table of ContentsIntroductionMethodsDiscussionConclusionIntroductionWater testing has many facets and parts, based on its classification according to the Department of Environmental Protection of Florida. Some of the criteria analyzed by surface water supplies include industrial and agricultural discharges, concentrations of silver, lindane and lead, carcinogens and mutagens, to name a few. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay. One item that is not normally included in these reports is water hardness. Water hardness is normally defined as the measurement of the concentrations of calcium and magnesium ions in water. It is known to have no adverse health effects due to the body's use of intestinal absorption to avoid excessive calcium intake, but it is known to cause accumulation of calcium carbonate in the pipes, the water system and even on dishes in the form of “water stains”. As a result, there are many methods for removing ions from hard water to reduce its hardness. Examples include ion exchange, using exchange resins to react to remove Ca2+ ions from solution, with more natural methods such as Moringa oleifera (drumstick tree) seeds, which are ground into a powder and added to water. In this experiment, we tested a water sample from a lake on the University of South Florida campus while also testing 3 random water samples and using 2 different filtration systems, to determine what method resulted in “softer” water. These two systems will be a cross-linked cationic resin and a mixed deionization resin. To determine water hardness, a titration using EDTA (ethylenediaminetetraacetic acid), a calmagite indicator and a pH buffer. EDTA reacts with calcium according to the equation Ca+2 + EDTA-4 ---> CaEDTA-2, which is an extremely stable molecule in water6. A calmagite indicator is used for its ability to bind with calcium to form a red color. However, because EDTA is a more potent ligand than calmagite, Ca2+ ions are absorbed by EDTA, resulting in a blue tint indicating that all the calcium has reacted. Finally, the ammonium buffer serves to neutralize the pH of the acid and maintain a pH of 10, the optimal pH for “blue” monoprotic calmagite, which allows the indicator to function. After filtration, another titration will be performed to help determine the Ca2+ concentration, which needs to be lowered. Additionally, we will use a conductivity meter to measure the conductivity before and after filtration. Since Ca2+ contributes to the overall conductivity of the water, the post-water filter should have less conductivity than after the filter. As for the filter system which I think will work better, I think the cation resin should work better to specifically do the cations in line and all the ions don't like the deionization resin, which also has an effect on the ions negative. Methods Standardization of the solution: The first step of the entire process was to create a standardized solution of EDTA that can be used in the rest of the experiments and to determine the reaction rate that the solution has with the calcium solutions. The goal was to create a 0.1 M solution of EDTA which can then be diluted to a 0.01 M solution in order to titrate the water samples later and, as mentioned previously, find the reaction rate. and fill in the formula nM1V1=M2V2 and find “n”. The first step was to use themolar mass of EDTA, which is 372.238 grams per mole, to determine the amount of EDTA needed to create 250 ml of 0.1 M EDTA solution. Additionally, a 0.1 M solution was needed to be created using calcium nitrate to titrate using EDTA, in order to fill the other side of the equation, however as it was for single use only 50 mL was prepared . Once again, the molar mass of calcium nitrate (Ca(NO3)2) was found, which was 164.088 grams per mol. From there, the calcium solution was buffered to pH 10 using the ammonium buffer and a pH meter, and 5 to 7 drops of calmagite indicator were added to the calcium solution. Once the calcium is prepared, the burette can be filled with EDTA solution and passed around a little to remove excess and clean the tip. From there, the calcium solution is placed on the magnetic stirrer and the titration can begin. During the titration, it was important to monitor the calcium pH and add ammonium buffer if necessary to keep the pH within range. Once the solution changed from a reddish pink color to a blue violet color, the titration had reached the end point and was complete. If the ammonium buffer is not added or is added continuously, then the indicator will not change and will remain the same color as shown by our first trail. With this data, the “n” value could be determined and used for water calculations. hardness of random samples and collected sample. Water hardness for a set of samples, before and after filtration: Now that EDTA has been standardized, it was possible to accurately determine the water hardness of the samples. The first step in this process is to take the 3 random water samples. The purpose of these is to help determine the accuracy of the EDTA solution when titrating solutions. As in the previous part, the pH meter and ammonium were used to buffer 50 ml of each sample to pH 10. From there, the 5-7 drops of indicator were added to each solution and mixed well. Then the samples were divided into 15 ml portions, creating 9 samples in total, 3 trials for each. Now that the calcium samples were prepared, the EDTA needed to be diluted in order to create a more accurate titration. It was best to dilute part of the 250 ml of 0.1 M in 250 ml of 0.01 M EDTA. This was achieved by adding 225 ml of water to 25 ml of EDTA solution. Now that both solutions were prepared, all 9 samples were titrated until the indicator changed, adding buffer during the titration to maintain the pH. Once the 3 random samples have been taken, the collected sample is tested. For the collected sample, the first step was to measure its conductivity in mS. From there, the sample was split into 3 sets, one set was left alone and set aside, while the other 2 were filtered. This was achieved by adding either the cation stream or the DI resin to a filtration column, then adding the water to the column and filtering it through the bottom. Once the two samples were filtered with both types of filters, their conductivity was measured again. Then, the 3 samples were buffered to pH 10 using ammonium buffer, then the indicator was added. Finally, all three samples were titrated to their end points and from there the water hardness could be determined, before and after filtration. Unfortunately, due to time, only one test could be performed for each of the 3 samples, instead of 2 or 3. DiscussionPart 1: The goal of this part of the process was to be able to determine the reaction rate of the EDTA solution, and use it tostandardize the solution. Even if the EDTA was not exactly 0.1 M, by determining the value of "n" in the equation of nM1V1 = M2V2, the error is corrected and therefore as long as n is still on the same side as the value with EDTA, the final calculated values ​​of Ca2+ concentration should not be affected. As for why this had to be done, it was due to the imprecision involved in creating said solution. As for why we decided to make 0.1M EDTA instead of 0.01M EDTA, it was purely for ease of storage and the number we found, n, was completely unrelated of the molarity of EDTA. Part 2: Unlike Part 1, Part 2 was not as simple and involves a lot more data. From the first data table, all EDTA values ​​listed correspond to the point at which the indicator changed color from red to blue. As explained previously, this is the time when all the calcium has been absorbed by the EDTA and therefore the titration is complete. From there, using the “n” calculation from week 1, the molar concentrations of all calcium samples could be determined much more accurately. Once the molarity was determined, the ppm of calcium could be calculated according to the formulas above. Although all of these samples had relatively low calcium molarity, the water was well above the limit for "very hard" water, showing how few Ca2+ ions it takes to create hard water. As for the collected sample, the conductivity was taken before and after filtration to determine how many ions each filtration system removed. However, the ions removed and the amount of Ca2+ filtered do not appear to be the same. Although flow did not have much effect on conductivity, it had a much greater reduction in calcium molarity and ppm. Post-filter 1 water was the only sample to fall into the “slightly hard” category, which is the lowest. This incongruity is likely because DI resin not only only targets cations like flux, but also removes anions. If the lake water was composed mainly of anions like Cl- or F-, it is very possible that their elimination would have a much greater effect on the conductivity than on the cations alone. Sources of Error: The largest source of error in this entire document. the experience was the time constraints. There are only a few elements in the entire experiment that were not interrupted by time and therefore many data sets are left without multiple trials. The most important of these is the collected sample, with which we were only able to carry out one test. Another fairly large source of error was a little bit of EDTA that was left out when the initial solution was developed. This is 100% why our "n" is 1.36 instead of something much closer to 1. In order to eliminate these errors, the most important thing would be to be more careful when adding the solids to water to start the solution. Another important thing is to allocate a little more time to the experience. Probably 15 more minutes and we could have done all the testing on the collected sample. Conclusion Coming back to the original goal, it was to determine the hardness of the local water here and choose a filtration system that would best reduce its hardness. hardness. My hypothesis was that ion flow would do a better job because it specifically targets cations unlike DI resin which targets any ion. Although it may appear that the data supports this hypothesis and assertion, I will assert that the hypothesis cannot be supported by..