TweetPlease note: These procedures apply to Ultrameters, Pool Pros, Tech Pros, and D-4 and D-6 dialysate meters. Measuring Conductivity & TDS 1. Rinse cell cup 3 times with sample to be measured. (This conditions the temperature compensation network and prepares the cell.) 2. Refill cell cup with sample. 3. Press COND or TDS. 4. Take […]
Please note: These procedures apply to Ultrameters, Pool Pros, Tech Pros, and D-4 and D-6 dialysate meters.
Measuring Conductivity & TDS
1. Rinse cell cup 3 times with sample to be measured. (This conditions
the temperature compensation network and prepares the cell.)
2. Refill cell cup with sample.
3. Press COND or TDS.
4. Take reading. A display of [- – – -] indicates an over range condition.
Resistivity is for low conductivity solutions. In a cell cup the value may drift from trace contaminants or absorption from atmospheric gasses, so measuring a flowing sample is recommended.
1. Ensure pH protective cap is secure to avoid contamination.
2. Hold instrument at 30° angle (cup sloping downward).
3. Let sample flow continuously into conductivity cell with no aeration.
4. Press RES key; use best reading.
NOTE: If reading is lower than 10 kilohms display will be dashes: [ – – – – ]. Use Conductivity.
If you have further questions, please watch our Ultrameter 6P product overview video here: http://blog.myronlmeters.com/ultrameter-ii-product-review/
IV. AFTER USING THE ULTRAMETER II
Maintenance of the Conductivity Cell
Rinse out the cell cup with clean water. Do not scrub the cell. For oily films, squirt in a foaming non-abrasive cleaner and rinse. Even if a very active chemical discolors the electrodes, this does not affect the accuracy; leave it alone.
Myron L Meters is the premier internet retailer of Myron L meters, solutions, parts and accessories. Save 10% on the Ultrameter II 6PFCe when you order online at MyronLMeters.com.
TweetElectrical conductivity indicates solution concentration and ionization of the dissolved material. Since temperature greatly affects ionization, conductivity measurements are temperature dependent and are normally corrected to read what they would be at 25°C. A. How It’s Done Once the effect of temperature is removed, the compensated conductivity is a function of the concentration (TDS). Temperature […]
Electrical conductivity indicates solution concentration and ionization of the dissolved material. Since temperature greatly affects ionization, conductivity measurements are temperature dependent and are normally corrected to read what they would be at 25°C.
A. How It’s Done
Once the effect of temperature is removed, the compensated conductivity is a function of the concentration (TDS). Temperature compensation of the conductivity of a solution is performed automatically by the internal processor with data derived from chemical tables. Any dissolved salt at a known temperature has a known ratio of conductivity to concentration. Tables of conversion ratios referenced to 25°C have been published by chemists for decades.
B. Solution Characteristics
Real world applications have to measure a wide range of materials and mixtures of electrolyte solutions. To address this problem, industrial users commonly use the characteristics of a standard material as a model for their solution, such as KCl, which is favored by chemists for its stability.
Users dealing with sea water, etc., use NaCl as the model for their concentration calculations. Users dealing with freshwater work with mixtures including sulfates, carbonates and chlorides, the three predominant components (anions) in freshwater that Myron L calls “Natural Water”. These are modeled in a mixture called “442™” which Myron L uses as a calibration standard, as it does standard KCl and NaCl solutions.
The Ultrameter II contains algorithms for these 3 most commonly referenced compounds. The solution type in use is displayed on the left. Besides KCl, NaCl, and 442, there is the User choice. The benefit of the User solution type is that one may enter the temperature compensation and TDS ratio by hand, greatly increasing accuracy of readings for a specific solution. That value remains a constant for all measurements and should be reset for different dilutions or temperatures.
C. When does it make a lot of difference?
First, the accuracy of temperature compensation to 25°C determines the accuracy of any TDS conversion. Assume we have industrial process water to be pretreated by RO. Assume it is 45°C and reads 1500 µS uncompensated.
1. If NaCl compensation is used, an instrument would report 1035 µS compensated, which corresponds to 510 ppm NaCl.
2. If 442 compensation is used, an instrument would report 1024 µS compensated, which corresponds to 713 ppm 442.
The difference in values is 40%.
In spite of such large error, some users will continue to take data in the NaCl mode because their previous data gathering and process monitoring was done with an older NaCl referenced device.
Selecting the correct Solution Type on the Ultrameter II will allow the user to attain true TDS readings that correspond to evaporated weight.
If none of the 3 standard solutions apply, the User mode must be used.
TEMPERATURE COMPENSATION (Tempco) and TDS DERIVATION
The Ultrameter II contains internal algorithms for characteristics of the 3 most commonly referenced compounds. The solution type in use is displayed on the left. Besides KCl, NaCl, and 442, there is the User choice. The benefit of User mode is that one may enter the tempco and TDS conversion values of a unique solution via the keypad.
A. Conductivity Characteristics
When taking conductivity measurements, the Solution Selection determines the characteristic assumed as the instrument reports what a measured conductivity would be if it were at 25°C. The characteristic is represented by the tempco, expressed in %/°C. If a solution of 100 µS at 25°C increases to 122 µS at 35°C, then a 22% increase has occurred over this change of 10°C. The solution is then said to have a tempco of 2.2 %/°C. Tempco always varies among solutions because it is dependent on their individual ionization activity, temperature and concentration. This is why the Ultrameter II features mathematically generated models for known salt characteristics that also vary with concentration and temperature.
B. Finding the Tempco of an Unknown Solution
One may need to measure compensated conductivity of some solution unlike any of the 3 standard salts. In order to enter a custom fixed tempco for a limited measurement range, enter a specific value through the User function. The tempco can be determined by 2 different methods:
1. Heat or cool a sample of the solution to 25°C, and measure its conductivity. Heat or cool the solution to a typical temperature where it is normally measured. After selecting User function, set the tempco to 0 %/°C as in Disabling Temperature Compensation, pg. 15 (No compensation). Measure the new conductivity and the new temperature. Divide the % decrease or increase by the 25°C value. Divide that difference by the temperature difference.
2. Heat or cool a sample of the solution to 25°C, and measure its conductivity. Change the temperature to a typical measuring temperature. Set the tempco to an expected value as in User Programmable Temperature Compensation, pg. 15. See if the compensated value is the same as the 25°C value. If not, raise or lower the tempco and measure again until the 25°C value is read.
C. Finding the TDS Ratio of an Unknown Solution
Once the effect of temperature is removed, the compensated conductivity is a function of the concentration (TDS).
There is a ratio of TDS to compensated conductivity for any solution, which varies with concentration. The ratio is set during calibration in User mode as in User Programmable Conductivity to TDS Ratio, pg. 16.
A truly unknown solution has to have its TDS determined by evaporation and weighing. Then the solution whose TDS is now known can be measured for conductivity and the ratio calculated. Next time the same solution is to be measured, the ratio is known.
ph and ORP (6PFCE)
1. pH as an Indicator (6PFCE)
pH is the measurement of Acidity or Alkalinity of an aqueous solution. It is also stated as the Hydrogen Ion activity of a solution. pH measures the effective, not the total, acidity of a solution.
A 4% solution of acetic acid (pH 4, vinegar) can be quite palatable, but a 4% solution of sulfuric acid (pH 0) is a violent poison. pH provides the needed quantitative information by expressing the degree of activity of an acid or base. In a solution of one known component, pH will indicate concentration indirectly. However, very dilute solutions may be very slow reading, just because the very few ions take time to accumulate.
2. pH Units (6PFCE)
The acidity or alkalinity of a solution is a measurement of the relative availabilities of hydrogen (H+) and hydroxide (OH-) ions. An increase in (H+) ions increases acidity, while an increase in (OH-) ions increases alkalinity. The total concentration of ions is fixed as a characteristic of water, and balance would be 10-7 mol/liter (H+) and (OH-) ions in a neutral solution (where pH sensors give 0 voltage).
pH is defined as the negative logarithm of hydrogen ion concentration. Where (H+) concentration falls below 10-7, solutions are less acidic than neutral, and therefore are alkaline. A concentration of 10-9 mol/liter of (H+) would have 100 times less (H+) ions than (OH-) ions and be called an alkaline solution of pH 9.
3. The pH Sensor (6PFCE)
The active part of the pH sensor is a thin glass surface that is selectively receptive to hydrogen ions. Available hydrogen ions in a solution will accumulate on this surface and a charge will build up across the glass interface. The voltage can be measured with a very high impedance voltmeter circuit; the dilemma is how to connect the voltmeter to solution on each side.
The glass surface encloses a captured solution of potassium chloride holding an electrode of silver wire coated with silver chloride. This is the most inert connection possible from a metal to an electrolyte. It can
still produce an offset voltage, but using the same materials to connect to the solution on the other side of the membrane causes the 2 equal offsets to cancel.
The problem is, on the other side of the membrane is an unknown test solution, not potassium chloride. The outside electrode, also called the Reference Junction, is of the same construction with a porous plug in place of a glass barrier to allow the junction fluid to contact the test solution without significant migration of liquids through the plug material. Figure 33 shows a typical 2 component pair. Migration does occur, and this limits the lifetime of a pH junction from depletion of solution inside the reference junction or from contamination. The junction may be damaged if dried out because insoluble crystals may form in a layer, obstructing contact with test solutions.
4. The Myron L Integral pH Sensor (6PFCE)
The sensor in the Ultrameter II (see Figure 34) is a single construction in an easily replaceable package. The sensor body holds an oversize solution supply for long life. The reference junction “wick” is porous to provide a very stable, low permeable interface, and is located under the glass pH sensing electrode. This construction combines all the best features of any pH sensor known.
5. Sources of Error (6PFCE)
The most common sensor problem will be a clogged junction because a sensor was allowed to dry out. The symptom is a drift in the “zero” setting at 7 pH. This is why the Ultrameter II 6PFCE does not allow more than 1 pH unit of offset during calibration. At that point the junction is unreliable.
b. Sensitivity Problems
Sensitivity is the receptiveness of the glass surface. A film on the surface can diminish sensitivity and cause a long response time.
c. Temperature Compensation
pH sensor glass changes its sensitivity slightly with temperature, so the further from pH 7 one is, the more effect will be seen. A pH of 11 at 40°C would be off by 0.2 units. The Ultrameter II 6PFCE senses the sensor well temperature and compensates the reading.
B. ORP/Oxidation-Reduction Potential/REDOX (6PFCE)
1. ORP as an Indicator (6PFCE)
ORP is the measurement of the ratio of oxidizing activity to reducing activity in a solution. It is the potential of a solution to give up electrons (oxidize other things) or gain electrons (reduce).
Like acidity and alkalinity, the increase of one is at the expense of the other, so a single voltage is called the Oxidation-Reduction Potential, with a positive voltage showing, a solution wants to steal electrons (oxidizing agent). For instance, chlorinated water will show a positive ORP value.
2. ORP Units (6PFCE)
ORP is measured in millivolts, with no correction for solution temperature. Like pH, it is not a measurement of concentration directly, but of activity level. In a solution of only one active component, ORP indicates concentration. Also, as with pH, a very dilute solution will take time to accumulate a readable charge.
3. The ORP Sensor (6PFCE)
An ORP sensor uses a small platinum surface to accumulate charge without reacting chemically. That charge is measured relative to the solution, so the solution “ground” voltage comes from a reference junction – same as the pH sensor uses.
4. The Myron L ORP Sensor (6PFCE)
Figure 34, pg. 45, shows the platinum button in a glass sleeve. The same reference is used for both the pH and the ORP sensors. Both pH and ORP will indicate 0 for a neutral solution. Calibration at zero compensates for error in the reference junction. A zero calibration solution for ORP is not practical, so the Ultrameter II 6PFCE uses the offset value determined during calibration to 7 in pH calibration (pH 7 = 0 mV). Sensitivity of the ORP surface is fixed, so there is no gain adjustment either.
5. Sources of Error (6PFCE)
The basics are presented in pH and ORP, pg. 44, because sources of error are much the same as for pH. The junction side is the same, and though the platinum surface will not break like the glass pH surface, its protective glass sleeve can be broken. A surface film will slow the response time and diminish sensitivity. It can be cleaned off with detergent or acid, as with the pH glass.
C. Free Chlorine
1. Free Chlorine as an Indicator of Sanitizing Strength Chlorine, which kills bacteria by way of its power as an oxidizing agent, is the most popular germicide used in water treatment. Chlorine is not only used as a primary disinfectant, but also to establish a sufficient residual level of Free Available Chlorine (FAC) for ongoing disinfection.
FAC is the chlorine that remains after a certain amount is consumed by killing bacteria or reacting with other organic (ammonia, fecal matter) or inorganic (metals, dissolved CO2, Carbonates, etc) chemicals in solution. Measuring the amount of residual free chlorine in treated water is a well accepted method for determining its effectiveness in microbial control.
The Myron L FCE method for measuring residual disinfecting power is based on ORP, the specific chemical attribute of chlorine (and other oxidizing germicides) that kills bacteria and microbes.
2. FCE Free Chlorine Units
The 6PIIFCE is the first handheld device to detect free chlorine directly, by measuring ORP. The ORP value is converted to a concentration reading (ppm) using a conversion table developed by Myron L Company through a series of experiments that precisely controlled chlorine levels and excluded interferants.
Other test methods typically rely on the user visually or digitally interpreting a color change resulting from an added reagent-dye. The reagent used radically alters the sample’s pH and converts the various chlorine species present into a single, easily measured species. This ignores the effect of changing pH on free chlorine effectiveness and disregards the fact that some chlorine species are better or worse sanitizers than others.
The Myron L 6PIIFCE avoids these pitfalls. The chemistry of the test sample is left unchanged from the source water. It accounts for the effect of pH on chlorine effectiveness by including pH in its calculation. For these reasons, the Ultrameter II’s FCE feature provides the best reading-to-reading picture of the rise and fall in sanitizing effectivity of free available chlorine.
The 6PIIFCE also avoids a common undesirable characteristic of other ORP-based methods by including a unique Predictive ORP value in its FCE calculation. This feature, based on a proprietary model for ORP sensor behavior, calculates a final stabilized ORP value in 1 to 2 minutes rather than the 10 to 15 minutes or more that is typically required for an ORP measurement.
The Myron L Ultrameter II 6PFCe is available at MyronLMeters.com, the premier internet retailer of Myron L products. Save 10% on the Myron L Ultrameter II6 PFCe when you order online here: http://www.myronlmeters.com/Myron-L-6P-Ultrameter-II-Multiparameter-Meter-p/dh-umii-6pii.htm
TweetConductivity/TDS/Resistivity The conductivity cell cup should be kept as clean as possible. Flushing with clean water following use will prevent buildup on electrodes. However, if very dirty samples — particularly scaling types — are allowed to dry in the cell cup, a film will form. This film reduces accuracy. When there are visible films of […]
The conductivity cell cup should be kept as clean as possible. Flushing with clean water following use will prevent buildup on electrodes. However, if very dirty samples — particularly scaling types — are allowed to dry in the cell cup, a film will form. This film reduces accuracy. When there are visible films of oil, dirt, or scale in the cell cup or on the electrodes, use isopropyl alcohol or a foaming non-abrasive household cleaner. Rinse out the cleaner and your Ultrameter II is again ready to use.
The unique pH/ORP sensor in your Ultrameter II is a nonrefillable combination type that features a porous liquid junction. It should not be allowed to dry out. To keep it from drying out and to prolong the life of the sensor, use SS sensor storage solution found here: http://www.myronlmeters.com/Myron-L-pH-ORP-Sensor-Storage-Solutions-32-oz-p/s-ssq.htm. However, if this occurs, the sensor may sometimes be rejuvenated by first cleaning the sensor well with Isopropyl alcohol or a liquid spray cleaner such as Windex™ or Fantastic™ and rinsing well. Do not scrub or wipe the pH/ORP sensor.
Then use one of the following methods:
1. Pour a HOT salt solution ~60°C/140°F — a potassium chloride (KCI) solution such as Myron L pH/ORP Sensor Storage Solution is preferable, but HOT tap water with table salt (NaCl) will work fine — in the sensor well and allow to cool. Retest.
2. Pour DI water in the sensor well and allow to stand for no more than 4 hours (longer can deplete the reference solution and damage the glass bulb). Retest. If neither method is successful, the sensor must be replaced.
“Drifting” can be caused by a film on the pH sensor bulb and/or reference. Use isopropyl alcohol (IPA) or spray a liquid cleaner such as Windex™ or Fantastic™ into the sensor well to clean it. The sensor bulb is very thin and delicate. Do not scrub or wipe the pH/ORP sensor. Leaving high pH (alkaline) solutions in contact with the pH sensor for long periods of time is harmful and will cause damage. Rinsing such liquids from the pH/ORP sensor well and refilling it with Myron L Storage Solution, a saturated KCl solution, pH 4 buffer, or a saturated solution of table salt and tap water, will extend the useful life.
Samples containing chlorine, sulfur, or ammonia can “poison” any pH electrode. If it is necessary to measure the pH of any such sample, thoroughly rinse the sensor well with clean water immediately after taking the measurement. Any sample element that reduces (adds an electron to) silver, such as cyanide, will attack the reference electrode.
Replacement sensors are available here: http://www.myronlmeters.com/Myron-L-RPR-Ultrameter-pH-ORP-Sensor-p/a-rpr.htm
Myron L Meters is your best internet source for Ultrameter 6P parts and accessories. You can always save 10% on Myron L meters when you order online at MyronLMeters.com.
TweetWhen disaster strikes, people are scared and disorganized. They need resources — safe water and proper sanitation — that aren’t easy to come by in the aftermath. Without the help of humanitarian organizations to provide assistance, large populations of survivors are subject to epidemics of cholera, diarrhea, meningitis, and other diseases as they struggle to […]
When disaster strikes, people are scared and disorganized. They need resources — safe water and proper sanitation — that aren’t easy to come by in the aftermath. Without the help of humanitarian organizations to provide assistance, large populations of survivors are subject to epidemics of cholera, diarrhea, meningitis, and other diseases as they struggle to meet these basic needs.
Dr. Roddy Tempest, a leading designer and manufacturer of water purification systems has headed the efforts of public and private aid organizations, such as the United Nations and AmeriCares, in responding to people in crisis all over the world for over 15 years.
Dr. Tempest contributed his expertise and experience in such situ- ations as the aftermath of Hurricane Andrew in 1992, the Kosovar refugee crisis in the Balkans, the devastating earthquakes in Tur- key and the flood and mudslides that ravaged the coastal states of Venezuela in 1999. He has assisted in disaster relief efforts in Japan, Africa, Central America, and Taiwan, as well.
So when AmeriCares launched its water purification program for the inhabitants of Sri Lanka following the devastation of the tsunami on December 26, 2004, it turned to Dr. Tempest.
For this heroic effort, Dr. Tempest used two Ultrameter II 6P portable, handheld water testing instruments. Dr Tempest said the instruments gave him “a good, quick first-brush assessment of the possible water sources.”
The Ultrameter II reported and recorded instant precise measurements of Conductivity, Resistivity, TDS, ORP (REDOX), pH, and Temperature. But creating a livable situation for hundreds of thousands of displaced survivors wasn’t as easy as testing the water.
Water Doctor to the Rescue
From his offices in the United States, Dr. Tempest responded to the call for help by first reviewing satellite maps that showed the location of potential water sources in relation to groups of survivors, or Internally Displaced Persons (IDPs). He assessed the total situation of the potential water sources, trying at a glance to deter- mine possible contamination by flooding or infiltration of seawater. Upon his arrival in Sri Lanka, Dr. Tempest worked 24 hours a day to determine a suitable survival supply of water for the IDPs. As indicated in the World Health Organization’s Environmental Health in Emergencies and Disasters, the required water per person per day is 15 liters / 3.963 gallons.
Faced with this daunting task, Dr. Tempest surveyed the land via helicopter and fixed wing aircraft to record the extent of the damage, the location of IDPs, and the viability of potential water sources. Some of the photographs reveal the mammoth challenge he had ahead of him. Debris lay everywhere, indicating the likelihood of surface water and well contamination. Filtration was a must.
Dr. Tempest then combined satellite imagery, the photographs and sketches of water sources from his survey and a list of supplies to determine which water sources would be targeted for testing.
Following World Health Organization guidelines, Dr. Tempest considered as many potential water sources as possible, not just the most obvious ones. These included surface and groundwater near the groups of IDPs and tankered or bottled water brought in from a distance – though this would not be suitable for the long- term supply. The preferred source would have been groundwater, especially for the long-term.
Ultrameter II in Action
Dr. Tempest used the Ultrameter II 6P to screen these sources for their potential disinfection and filtering.
First, Dr. Tempest considered whether or not potential water sources could be protected from pollution and secured. Any potential source water had to be filterable and sanitizable. If the water was brackish, it would require a certain treatment method. If it was high in turbidity, then it would require another. If the pH needed adjusting, then yet another. If the source water was not easily treatable, then the source had to be discarded as an option and a better alternative found.
The Ultrameter II provided Dr. Tempest with fast, reliable, accurate initial information on whether or not to pursue further testing and treatment of a potential source. Dr. Tempest used a multiparameter approach and tested for Total Dissolved Solids (TDS), pH, ORP (REDOX), and temperature (recorded with every reading taken.) He also tested for turbidity and bacteria using other instrumentation.
Initially, Dr. Tempest used a measurement of the mineral salt concentration using TDS calibrated to a sodium chloride solution and TDS calibrated to a natural water standard.
Right away Dr. Tempest knew whether or not the water was too saline or saturated to be filtered economically. If the TDS is too high, filtration systems that work by reverse osmosis can be overwhelmingly expensive to operate in a disaster area, especially considering electrical costs alone. At the very least, the systems become less efficient as the TDS increases and a burden in operation and maintenance costs. This is critical for the short-term disaster response, where Dr. Tempest has to get as much safe water to IDPs in as short amount of time as possible.
High TDS can also indicate an unacceptable level of specifically known inorganic contaminants caused by industrial pollution.
And though it is not a health consideration, high TDS water often has an unpleasant taste that deters people from using it. People may try to return to old wells or other sources of previously safe drinking water that have been contaminated in the disaster. The old source may be more trusted than one that tastes “polluted.” So even though TDS is a secondary water quality standard, it can profoundly impact whether or not the new source is acceptable.
Dr. Tempest also took instant electronic pH readings using the Ultrameter II. The pH directly affects the potential to disinfect the water. pH levels beyond 8 will require substantial increases in the amount of disinfectant required or the length of time the water must be disinfected before safe consumption. And at a pH beyond 9, a residual disinfectant is extremely difficult to maintain.
pH is also critical in the long-term disaster recovery planning. pH that is too low or too high affects water balance, as well, and can contribute to either corrosion or scaling of filtration and disinfection system components and plumbing. An electronic meter is the best choice in this application as compared to colored strips or solutions or other colorimetric methods that do not produce the accuracy required to consistently and correctly balance water and maintain proper disinfection levels. The more precisely the pH is maintained, the less costly safe water production is.
Dr. Tempest also took quick ORP (REDOX) measurements using the Ultrameter II. ORP (REDOX) is the oxidation reduction potential of the water and indicates the state of the water for gaining or losing electrons. Unlike pH, which measures the water’s ability to donate or receive hydrogen ions, ORP (REDOX) values reflect the presence of all oxidizing and reducing agents — not just acids and bases. Initially, the ORP (REDOX) value gave Dr. Tempest a rough idea of the organic load in the water. A reading of 650 mV or greater indicated good water quality that could effectively be sanitized by a minimal amount of free chlorine. A value like 250 mV indicated that the organic contaminants would significantly increase chlorine demand and thereby significantly increase operation and management costs.
ORP (REDOX) is not only a good first indicator about the viability of a water source, but it also is the best way of measuring the disinfectant present in the water after treatment has begun.
Putting It All Together
Using all of the results from these parameters and based on his knowledge of the location of IDPs in relation to potential water sources, Dr. Tempest decided which source would satisfy the needs of each specific location of groups of IDPs. Where possible, water treatment technology would be designed around the quality of the source waters tested where IDPs had gathered, since it was not practical to re-locate large groups of people to distant water sources. Unfortunately, in the case of the Tsunami in Sri Lanka, oftentimes the water closest to IDPs could not be filtered and relocation was necessary.
Dr. Tempest found after his first quick assessment of potential water sources that it was not practical to supply the IDPs in parts of the Batticoloa and Ampara Districts along the eastern coast, because the source water was too saline from seawater intrusion. With limited electricity, this
made the use of reverse osmosis or desalination equipment impractical.
He ended up settling on sites that were more inland, using source waters from man-made reservoirs. IDPs were then settled inland near the cleaner water source.
However, the water in the man-made reservoirs was heavily contaminated with toxic blue-green algae.
Dr. Tempest chose microfiltration and ultrafiltration water treatment systems in the eastern district locations, taking algae-infested water over the salt-saturated, so that treatment and operation costs would be significantly less. Dr. Tempest designed, built and commissioned 4 large transportable water treatment systems, each capable of producing over 500,000 liters/day.
Plans then continued to follow through with long-term water treatment using the Tempest Environmental Systems equipment for the Sri Lankan Ministry of Urban Development and Water Supply and their National Water Supply & Drain- age Board (NWSDB). The NWSDB has 14 Ultrameter II 6Ps in current use in Sri Lanka, which are providing continuing confidence checks to ensure system equipment remains up and running properly.
The Ultrameter II 6P is an excellent multiparameter water quality meter used by thousands of water treatment professionals. The instrument can test for pH, total dissolved solids, conductivity, resistivity, oxidation reduction potential, temperature, and has the capability of testing for free chlorine. This meter handles the job of SIX single parameter testers using one single water sample. Save 10% on the Ultrameter II 6P at MyronLMeters.com.
TweetFeatures • Handheld meters measure TDS and/or pH • Monitor measures TDS • All instruments are easy to operate and calibrate • High degree of accuracy • Immediate results • Kit comes with solutions required to calibrate • Temperature compensated readings TDS Monitoring The nutrient solution and its management are the foundation of a successful […]
• Handheld meters measure TDS and/or pH
• Monitor measures TDS
• All instruments are easy to operate and calibrate
• High degree of accuracy
• Immediate results
• Kit comes with solutions required to calibrate
• Temperature compensated readings
The nutrient solution and its management are the foundation of a successful hydroponics system. The function of a hydroponics nutrient solution is to supply the plant roots with water, oxygen and essential mineral elements in soluble form.
A test of the Total Dissolved Solids (TDS) using the DS Meter or pDS Meter or continuous monitoring with the HYDRO-STIK gives the grower accurate measurements of the concentration of nutrients in solution. If the concentration drops below the optimum level required to sustain and grow the plants, add more nutrient- rich solution until the desired concentration level is achieved. This prevents haphazard dosing and wasted solution, which minimizes costs to the grower.
pH of the nutrient solution is also critical to successful plant growth. All elements have a specific solubility pH range. This means that mineral elements dissolve and can become more concentrated in solution within certain pH ranges. Roots absorb only the dissolved nutrients, so this is critical to plant growth.
The TH1H and the pDS Meter quickly and easily measure pH.
Monitoring the addition of a pH balancing solution with the proper meter lets the grower precisely adjust the pH level.
Beyond affecting nutrient availability, extremely low or high pH can even damage or kill plants.
All Myron L TDS and pH meters give lab-accurate results in the field.
All Myron L meters use advanced Temperature Compensation (TC) circuitry and equations to give you the best TC correction available.
Tweet Myron l Meters Ultrameter III 9PTKA from Myron L Meters
Tweet Myron l Meters Ultrapen PT-1 from Myron L Meters
TweetHypothesis: Does the time of year affect the conductivity of stagnant water in a given location? Abstract: We decided to test the conductivity levels of the water at Flat Rock Brook. If the conductivity levels are higher, it might imply higher total dissolved solid levels. We would like to see if the conductivity level changes during seasons […]
Hypothesis: Does the time of year affect the conductivity of stagnant water in a given location? Abstract: We decided to test the conductivity levels of the water at Flat Rock Brook. If the conductivity levels are higher, it might imply higher total dissolved solid levels. We would like to see if the conductivity level changes during seasons with snowfall versus seasons without snowfall. Background:
- Independent Variable: Time of Year (Season)
- Independent Variable: Location
- Dependent Variable: Conductivity Level (mg/L TDS)
The purpose of the experiment is to test the change in conductivity level throughout the year (on a seasonal basis) in various locations. While doing this experiment, it is important to keep in mind these three things:
- How does conductivity vary at any of the given sites during a given season.(1)
- What human influence might have an impact on the conductivity of the water at any given part of the year.(1)
- Why might this change affect the ability of organisms to live in the given test sites.(1)
This is important to Flat Rock Brook because the data could be used to do several things. For example, the change in conductivity may change the organic life in the water, thus changing the ability to safely drink it. The change may impact the ability of organisms to grow in the water, and it may change the reactive nature of the water. Conductivity can be measured by the total dissolved solids in the water. Total Dissolves Solids include the number of mineral and salt impurities in the water. (1) Ultimately, the number of minerals and salts determines how many ions in mg/L. The impurities in the water can include runoff from roads, wastewater from industrial plants, and soils and rocks. (1) The amount of total dissolved solids in the water can have a physiological effect on plants and animals living in the ponds. (2) Conductivity can be used as a way of noting changes in water conditions over short periods of time. (2) Also, the level of total dissolved solvents in water can have an effect of the ability of habitat-forming plants to grow, thus disrupting the presence of certain species. (2) Materials:
- GPS Navigator by Magellan: We used the GPS as a way to mark off specific testing sites at McFadden’s Pond and Quarry Pond, in order to test in a precise and consistent location
- pH/Conductivity Probe: We used the pH/Conductivity Probe to test the level of conductivity in the various locations. The conductivity was measured in mg/L (TDS), and microsiemens (µS), but due to the difficult nature of working with microsiemens, we chose to work primarily with mg/L(TDS).
- Distilled Water: We used the distilled water to wash off the probe in between tests in order to maintain accurate readings without tainted results.
- Map of Flat Rock Brook: We used the map of Flat Rock Brook in order to find locations from which we could test conductivity levels of water.
- Vernier conductivity probe used with a Lab Pro interface: We used this for our May data in order to get a more accurate reading. By taking samples from Flat Rock Brook, we connected this probe to Logger Pro and recorded the conductivity which was also measured in TDS. NOTE: We used the conductivity data from these readings in our graphs and overall analysis because it provided a more accurate measurement
Methods: *Adapted from Electrical Conductivity Protocol Used by University Corporation for Atmospheric Research, Colorado State University, and NASA. (Water Temperature was not recorded.)
- Record water temperature
- Pour water sample into two containers (or measure in water body)
- Rinse electrodes with distilled water, blot dry
- Place meter in first container, 2-3 seconds
- Remove meter, shake gently, and place in second
container, 1 minute (Do not rinse with distilled water)
- Record value when stabilized
- Repeat measurement with new sample water, twice
- Average three measurements and check for accuracy
Original Protocol can be found at this link*: http://126.96.36.199/search?q=cache:tpTXJUjpiHgJ:globe.ucar.edu/trr-
Cleaning off the conductivity probe before testing the water. (Figure 2)
Testing the conductivity of the pond (Figure 3)
Results: Fall (November) : -Quarry Pond:
- .9 mg/L
-McFadden’s Pond (site A)*:
- 3.1 mg/L
-McFadden’s Pond (site B)*:
- 3.05 mg/L
Spring (May): (with ph/conductivity probe) -Quarry Pond:
- .83 mg/L
-McFadden’s Pond (Site A):
- 2.95 mg/L
-McFadden’s Pond (Site B):
- 2.02 mg/L
Spring (May): (LoggerPro Data) -Quarry Pond:
- .8 mg/L
-McFadden’s Pond (Site A):
- 3.1 mg/L
-McFadden’s Pond (Site B):
- 2.1 mg/L
Data Graph for Quarry Pond (Figure 4)
Data Graph for McFadden’s Pond Site A (Figure 5)
Data Graph for McFadden’s Pond Site B (Figure 6)
Data Graph for all three locations (Figure 7)
Discussion: Throughout our research, there was a general shift in the conductivity level in each site we tested. At Quarry Pond, the total dissolved solids reduced from .9 mg/L to .8 mg/L from November to May. This shift can be seen in the graph shown in Figure 4. McFadden’s Pond Site B also showed a substantial shift between the November and May readings, from 3.05 mg/L to 2.1 mg/L, as seen in Figure 6. Despite these significant changes, Site A at McFadden’s Pond did not change. This could potentially be due to its close proximity to moving water. A subtle, unnoticed under-current may have existed which may have caused the water to be mixed, and therefore diluted. The figures for this measurement can be seen in Figure 5.
The changes in conductivity at Quarry Pond may be the result of runoff from the parking lot and the roads in close proximity to it. Quarry Pond, unlike the other locations was close enough to a road that run-off affects the level of total dissolved solids. Although there was a significant change in conductivity between readings, the total dissolved solids were much lower than that of McFadden’s Pond. This may explain why the presence of algae was much higher in Quarry Pond than in McFadden’s Pond. McFadden’s Pond’s conductivity may have been higher due to a larger level of mineral deposits from soil runoff. One possible explanation for this shift in conductivity is the dilution of total dissolved solids in pond water due to rainfall and melting water from snow.
Conclusion: When comparing conductivity of water at a given point of time during the year, it is clear that there are noticeable differences. During the Fall and Winter, when there is more soil and road runoff, the conductivity level is higher. Conversely, during the spring, when there is more rainwater and melted snow and ice to dilute the ponds, the conductivity level drops. This would suggest that during fall and winter, the conditions of the pond are noticeably different. This suggests the possibility that there may be a shift in population from one group of organisms to another on a seasonal basis. Knowledge of these changes may help to explain why animals would migrate to a different habitat during different seasons. Because of the nature of soil runoff and road runoff, the level of Total Dissolved Solids in the water changes on a seasonal basis, and with that, the conductivity changes as well. In conclusion, conductivity does change over time of year in stagnant water, primarily because of external conditions such as runoff and wastewater.
(1)The GLOBE Program, “Electrical Conductivity Protocol.” Hydro-Electrical Conductivity. Ed. UCAR, Colorado State University, NASA.
We used the Power Point file linked to this page as our primary source of background information as well as a standard protocol for our field tests.
(2)Conductivity And Water Quality.
<[[http://kywater.org/ww/ramp/rmcond.htm%3C/span%3E%3Cspan|http://kywater.org/ww/ramp/rmcond.htm<span]] We used this website as our second source of data for finding out environmental impacts of change in conductivity and overall water quality. (Note: No Author, Publisher or Editor could be found for this web page.) __ *Site A is to the right of Mystery Bridge *Site B is to the left of Mystery Bridge *Note, this protocol was implemented both in the field and in a lab dependent on the time the data was collected *If the web page is difficult to view, a link to a .ppt file is available at the top of the page. The protocol can be found on slide #12.
Study authors: Margot Bennett and Rob Schwartz
Contributions to http://d-e-science11.wikispaces.com/ are licensed under a Creative Commons Attribution Share-Alike 3.0 License
Peat Water Treatment Using Combination of Cationic Surfactant Modified Zeolite, Granular Activated Carbon, and Limestone
Tweet MyronLMeters.com attempts to provide its customers with the latest in water quality research and industry updates. Find more at https://www.myronlmeters.com/. Abstract This research was conducted essentially to treat fresh peat water using a series of adsorbents. Initially, the characterization of peat water was determined and five parameters, including pH, colour, COD, turbidity, and iron ion […]
MyronLMeters.com attempts to provide its customers with the latest in water quality research and industry updates. Find more at https://www.myronlmeters.com/.
This research was conducted essentially to treat fresh peat water using a series of adsorbents. Initially, the characterization of peat water was determined and five parameters, including pH, colour, COD, turbidity, and iron ion exhibited values that exceeded the water standard limit. There were two factors influencing the adsorption capacity such as pH, and adsorbent dosages that were observed in the batch study. The results obtained indicated that the majority of the adsorbents were very efficient in removing colour, COD, turbidity at pH range 2-4 and Fe at pH range 6-8. The optimum dosage of cationic surfactant modified zeolite (CSMZ) was found around 2 g while granular activated carbon (GAC) was exhibited at 2.5 g. In column study, serial sequence of CSMZ, GAC, and limestone showed that the optimal reduction on the 48 hours treatment were found pH = 7.78, colour = 12 TCU, turbidity = 0.23 NTU, COD = 0 mg/L, and Fe= 0.11 mg/L. Freundlich isotherm model was obtained for the best description on the adsorption mechanisms of all adsorbents.
Keywords: cationic surfactant modified zeolite, granular activated carbon, limestone, peat water
Water is essential and fundamental to all living forms and is spread over 70.9% of the earth’s surface. However, only 3% of the earth’s water is found as freshwater, of which 97% is in ice caps, glaciers and ground water (Bhatmagar & Minocha, 2006). In Malaysia, more than 90% of fresh water supply comes from rivers and streams. The demand for residential and industrial water supply has grown rapidly coupled with an increase in population and urban growth (WWF Malaysia, 2004). Water demand in affected populations such as rural areas also demands that attention is paid to providing more sustainable solutions rather than transporting bottled water (Loo et al., 2012). For this reason, it is essential to ensure availability of local sources of water supply and even develop new potential sources of water such as from peat swamp forest to overcome future water shortages.
River water surrounded by peat swamp forest is defined as peat water and is commonly available as freshwater since it has a low concentration of salinity. The previous study shows that peat swamp forest has high levels of acidity and organic material depending on its region and vegetation types (Huling et al., 2001). Under natural conditions, tropical peat lands serve as reservoirs of fresh water, moderate water levels, reduce storm-flow and maintain river flows, even in the dry season, and they buffer against saltwater intrusion (Wosten et al., 2008).
Due to the acidity and high concentration of organic material, selective treatment of peat water must be conducted prior to its use as water supply. Recently, many methods have been designed and have proven their effectiveness in treating raw water such as coagulation and flocculation (Franceschi et al., 2002; Liu et al., 2011; Syafalni et al., 2012a), absorption (Ćurković et al., 1997), filtration (Paune et al., 1998) and combining (Hidaka et al., 2003). Careful consideration of the most suitable method is important to ensure that the adsorption process is the most beneficial, economically feasible method as well as easy to operate for producing high quality of water in a particular location.
Many researchers have shown that activated carbon is an effective adsorbent for treating water with high concentrations of organic compounds (Eltekova et al., 2000; Syafalni et al., 2012b). Its usefulness derives mainly from its large micropore and mesopore volumes and the resulting high surface area (Fu & Wang, 2011). However, its high initial cost makes it less economically viable as an adsorbent. Low cost adsorbent such as zeolite nowadays has been explored for its ability in many fields especially in water treatment. Natural zeolite has negative surface charge which gives advantages in absorbing unwanted positive ions in water such heavy metal. These ions and water molecules can move within the large cavities allowing ionic exchange and reversible rehydration (Jamil et al., 2010). The effectiveness of zeolite has been improvised by modified zeolite with surfactant in order to achieve higher performance in removing organic matter (Li & Bowman, 2001). Among tested cationic surfactants, hexa-decyl-tri-methyl ammonium (HDTMA) ions adsorbed onto adsorbent surfaces are particularly useful for altering the surface charge from negative to positive (Chao & Chen, 2012). Surfactant modified zeolite has been shown to be an effective adsorbent for multiple types of contaminants (Zhaohu et al., 1999).
Zeolite is modified to improve its capability of exchanging the anion by cationic surfactants, called CSMZ. CSMZ adsorbs all major classes of water contaminants (anions, cations, organics and pathogens), thus making it reliable for a variety of water treatment applications (Bowman, 2003). Nowadays, interest in the adsorption of anions and neutral molecules by surfactant modified zeolite has increased (Zhang et al., 2002). Modification of zeolite by surfactant is commonly done by cationic or amphoteric surfactants. By introducing surfactant to the zeolite, an organic layer is developed on the external surfaces and the charge is reversed to positive (Li et al., 1998). However, the present study used zeolite that had been modified using Uniquat (QAC-50) as cationic surfactant (CSMZ) and their performance towards the removal of color, COD, turbidity and iron ion from peat water were investigated.
Four adsorbents were used in these experiments which are natural zeolite, zeolite modified by cationic surfactant, activated carbon and limestone. All adsorbents were prepared with equivalent sizes of 1.18 mm – 2.00 mm. Hydrochloric acid (HCl) and sodium hydroxide (NaOH) were used for polishing zeolite during the preparation phase and for pH adjustment of the sample. Furthermore, potassium dichromate (K2CrO7), silver sulphate (Ag2SO4), sulphuric acid (H2SO4) and mercury (II) sulphate (HgSO4) were used as digestion solution reagents and acid reagents for COD analysis. Lastly, Uniquat (QAC-50) was used as cationic surfactant to modify the zeolite.
2.1 Preparation of Surfactant Modified Zeolite
In these studies, 100 g of prewashed natural zeolite was contacted with 5.6 ml/l Uniquat (QAC-50) as cationic surfactant (CSMZ). The mixture was then stirred at room temperature for 4 hours at 300 rpm (Karadag et al., 2007). The zeolite then was filtered and washed with distilled water several times. After that, the absorbent was dried in an oven at a temperature of 105 °C for 15 hours.
2.2 est Procedures
2.2.1 Batch Studies
Serial batch studies were conducted at room temperature (28 ± 1 °C) to investigate the influence of pH and dosage for removing colour, COD, turbidity and iron ion from peat water. Shaking speed of 200 rpm for 20 minutes were fixed and operated respectively. A working volume of 150ml peat water sample was set up in 250 ml conical flasks. Preceding the batch studies, initial concentration for those parameters was determined. The optimum pH and dosage of absorbent were determined. Subsequently, the percentage of removal was finally determined, plotted, and compared.
2.2.2 Batch Column Studies
Column studies were carried out using a plastic column with dimensions: 5.4 cm diameter and 48 cm length. Three adsorbents were filled inside the column at a specific depth with the supporting layers of marbles, cotton wool, and perforated net. Total volume of 2000 ml peat water was pumped in the up flow mode from the vessel into the column by using a Masterflex peristaltic pump at a minimum flow rate of (30, 60, 90) ml/min. In this study, however, column studies were performed un-continuously (batch) due to limitations of time. All parameters related to the column design are summarized in the following Table 1.
Table 1. Column studies parameters
|Horizontal Surface Area, A||cm2||
|Column volume, V||cm3||1099.3|
|Flowrate, Q||ml/min||30, 60, 90|
|Surface Loading Rate, SLR= Q/A||cm/min||1.31, 2.62, 3.93|
The serial sequence arrangements of adsorbents were conducted as shown in Figure 1 below. Effluent samples were collected at various time intervals, whilst maintaining room temperature, and analysed.
Figure 1. Schematic diagrams of lab-scale column studies
3. Results and Discussion
3.1 eat Water Characterization
Surface water originating from the peat swamp forest was taken from Beriah peat swamp river along the Kerian River on several occasions as the main sample. The characterization of peat water was carried out at the sampling point (in-situ measurement) using a multi-parameter probe as well as in the environmental laboratory of civil engineering, USM. Fundamentally, the characterization procedures were based on the Standard Methods for the Examination of Water and Wastewater (APHA, 1992). Table 2 represents the peat water characteristics in average value and the comparison to the standard drinking water quality in Malaysia.
Table 2. The characteristics of peat water sample from Beriah Peat Swamp Forest
|4.67 – 4.98|
Thirteen parameters were successfully determined where the first six parameters, including pH, temperature, TDS, DO, conductivity, and salinity were measured at the sampling point, whilst the rest of the parameters, including colour, turbidity, COD, iron ion, Ammoniacal Nitrogen, NH3-N, Ammonia (NH3), and Ammonium (NH4+) were examined from the sample brought to the environmental laboratory on the same day.
Acidic pH of the peat water was predicted due to the composition of the surrounding peat soil itself which had been formed by decaying material possessing humic substances (Rieley, 1992). Besides that, humic substances also lead to the high organic content as humic substances are comprised of numerous oxygen containing functional group and fractions (humic acid, fulvic acids and humin) with different molecular weights which mean yielding high concentration of turbidity and COD as well as coloured water (Torresday et al., 1996). Moreover, composition of peat soil may also have an impact on the iron ion concentration of peat water (Botero et al., 2010).
From the thirteen parameters, five parameters were indicated exceeding the standard limit. These parameters were pH, colour, turbidity, COD, and iron ion that showed values of 4.67 – 4.98, 224.7 TCU, 20.8 NTU, 33.3 mg/l, and
1.24 mg/l respectively while the standard limit of these parameters are 6.5 – 9.0, 15 TCU, 5 NTU, 10 mg/l, and 0.3 mg/l accordingly.
3.2 Effect of Initial pH on the Efficiency of Colour, COD, Turbidity, and Iron Ion (Fe) Removal
Influence of initial pH on the adsorption capacity for removing colour, COD, turbidity, and iron ion were investigated.
Figure 2(a) to Figure 2(d) below, displayed the percentage removal of colour, COD, turbidity, and iron ion against pH of adsorbents respectively.
Figure 2(a) shows the maximum removal percentage of colour that was removed by natural zeolite, CSMZ, and granular activated carbon (GAC) which were 79%, 90%, 82% respectively. This adsorption is depended on the characteristic of adsorbents itself. For zeolite and CSMZ were related to the amount of cationic ions (Al3+) increased, resulting in high reaction activity and GAC was related to the adsorption capacity. It was observed that the adsorption capacity was highly dependent on the pH of the solution, and indicated that the colour removal efficiencies decreased with the increase of solution pH.
The pH of the system exerts profound influence on the adsorptive uptake of adsorbate molecules presumably due to its influence on the surface properties of the adsorbent and ionization or dissociation of the adsorbate molecule. Figure 2(b) represents the percentage removal of natural zeolite and CSMZ where they reach optimum efficiency in removing organic compound (COD) at pH 2 with efficiency of 53% and 60% respectively. Meanwhile, the highest percentage removal of COD for GAC was achieved at pH 4 with efficiency obtained about 61%. Identical trends in colour removal were exhibited in percentage removal of COD for natural zeolite, CSMZ and GAC. In fact, this result also reveals that GAC has the highest percentage removal among natural zeolite and CSMZ yet optimum in difference pH solution. Neutralization mechanism occurs in low pH makes color removal, COD removal and Turbidity removals at pH 2 are higher for most of absorbents in this process.
In Figure 2(c), percentage turbidity removal against pH for each adsorbent revealed that optimal reduction of turbidity was obtained in an acidic environment with efficiency removal of 96%, 98%, 95% for natural zeolite, CSMZ, and GAC respectively. When the pH of the solution was adjusted above pH 6 to pH 12, the tendencies of all adsorption performances were gradually decreased. Moreover, it also showed that the lowest efficiency for the three adsorbents were identified at pH 12 with percentage values removal 55%, 61%, and 59% for natural zeolite, CSMZ, and GAC respectively.
Figure 2(d) demonstrates the removal efficiencies of iron ion as a function of the influent pH. The maximum removal of iron ion was observed at pH 8 for both natural zeolite and CSMZ whereas GAC had its optimum removal at pH 6. Natural zeolite and CSMZ only yielded 73% and 62% removal efficiency while GAC had more significant removal with removal efficiency of 80% to the iron ion concentration. Further, it is evident from the graph that gradual increment of removal efficiency for natural zeolite, CSMZ, and GAC occurred when the initial pH of the solution was increased to higher values. Somehow, at pH values greater than 6 the removal efficiency of GAC reduced slightly while for natural zeolite and CSMZ the reduction occurred from pH values above 8.
3.3 Effect of Adsorbent Dosage on the Efficiency of Colour, COD, Turbidity, and Iron Ion (Fe) Removal
The effect of adsorbent dosage was studied for all adsorbents employed on colour, COD, turbidity, and iron ion removal by varying the dosage of adsorbent and keeping all other experimental conditions constant. The pH was set to acidic conditions which were most favourable in obtaining the highest removal efficiency. In this study, to find optimal adsorbent dosage of natural zeolite and CSMZ, the appropriate experiments were carried out at adsorbent dosages in the range of 0.5 g to 5.0 g while for GAC, the adsorbent dosage was varied from 0.01 g to 4.0
- The experimental results for all the adsorbents are represented by Figure 3(a) to Figure 4(d).
Figure 3. Percentage of color (a), COD (b), turbidity (c), and Fe (d) removal against pH for NZ, and CSMZ
Figure 3(a) displays the relationship between the amount of adsorbent mass (dosage) and adsorption efficiency for natural zeolite and CSMZ in terms of removing colour. The colour removal of peat water increased from about 25% to 52% with increasing adsorbent dosage of natural zeolite from 0.5 g to 3.5 g whereas for CSMZ, removal percentage increased from 41% to 53% with increasing adsorbent dosage from 0.5 g to 2.0 g. However, further increase in adsorbent dosage to 5.0 g only led to slight degradation of removal efficiency to 50% and 41% for natural zeolite and CSMZ respectively. This degradation with further increases in adsorbent dosage was due to the unsaturated adsorption active sites during the adsorption process since the adsorbates in the vessel were only shaken for 20 minutes (insufficient time). Besides, modification of zeolite by cationic surfactant had proven to have better colour removal as presented in the graph.
Percentage removal of COD against the adsorbent dosage is shown in Figure 3(b). It was observed that the highest percentage removal for both natural zeolite and CSMZ to remove COD were 51% and 59%, achieved at adsorbent dosage 3.5 g and 2.0 g respectively.
The variations in removal of turbidity of peat water at various system pH are shown in Figure 3(c). The removal rate of turbidity was highest at the adsorbent dosage of 0.5 g with 70% and 93% removal efficiency for respective natural zeolite and CSMZ. The removal rate showed a smooth downward trend with the increase in adsorbent dosage. Concurrently, the adsorption capacity gradually decreased with the increasing adsorbent dosage. The least efficient removal of turbidity was noted at dosage 5.0 g with percentage removal recorded for natural zeolite and CSMZ only 57% and 70% respectively.
Figure 3(d) demonstrates the percentage iron ion removal of natural zeolite and CSMZ with respect to their dosage. The result shows that there was a significant difference trend in iron ion adsorption efficiencies between natural zeolite and CSMZ. For natural zeolite, it was shown that the removal percentage of iron ion had increased until it reached 1.0g of dosage with 72% of removal efficiency. On the other hands, CSMZ was only able to remove about 63% of iron ion when its dosage was increased to 2.5 g. The lowest percentage removals were 47% and 57% recognized at the adsorbent dosage 5.0 g for respective natural zeolite and CSMZ.
Figure 4. Percentage of color (a), COD (b), turbidity (c), and Fe (d) removal against dosage for GAC
The result illustrated in Figure 4(a) shows the maximum removal percentage of colour for GAC at 2.5 g dosage was 62%. Moderate increment in colour removal was identified along with the addition dosage of 2.5 g whilst abatement of removal efficiency began subsequently at adsorbent dosage of 3.0 g to 4.0 g.
The results from Figure 4(b) indicated that increasing the GAC dosage would increase the efficiency in removing COD respectively. The optimum dosage was recorded at 3.0 g with 72% of removal efficiency. Meanwhile, increasing the dosage above 3.0 g exhibited a slight decrease in removal efficiency with 67% to 61% for COD removal. A better result in removing COD was also shown by GAC compared to the natural zeolite and CSMZ.
The percentage of turbidity removed by GAC in different dosages is described in Figure 4(c). The highest removal was indicated at adsorbent dosage 2.5 g with removal efficiency of 70% while the minimum removal was 52% recorded at the adsorbent dosage 0.01 g. However, starting from adsorbent dosage of 3.0 to 4.0 g, removal efficiency began to decrease to 68%, 67%, and 69% respectively.
The result of percentage removal of iron ion by GAC in peat water is presented in Figure 4(d). It was found that the rate of removal was rapid in the initial dosage between 0.01 g to 3.0 g at which the removal efficiency increased from 28% to 71% accordingly. Subsequently, a few significant changes in the rate of removal were observed. Possibly, at the beginning, the solute molecules were absorbed by the exterior surface of adsorbent particles, so the adsorption rate was rapid. However, after the optimum dose was reached, the adsorption of the exterior surface becomes saturated and thereby the molecules will need to diffuse through the pores of the adsorbent into the interior surface of the particle (Ahmad & Hameed, 2009).
3.4 Batch Column Experiment
On the first running, the column was packed with natural zeolite (1st layer), limestone (2nd layer), and GAC (3rd layer) as shown in Figure 5(a). Removal efficiency for colour, COD, turbidity, and iron ion was recognized to be increased when the contact time was increased. At the time interval 1 hour to 6 hours, however, the increment was not so significant. The removal efficiency at 1 hour treatment was 39%, 21%, 54%, 36% while at 6 hours treatment was 77%, 65%, 73%, 60% recorded for respective colour, COD, turbidity, and iron ion. Poor removal efficiency at 1 hour treatment indicated that the required time to remove all parameters were insufficient. It is evident that if the adsorption process is allowed to run for 24 hours on the column, the removal efficiency shows notable removal. Percentage removals of colour, COD, turbidity, and iron ion at 24 hours were 83%, 72%, 76%, 65% respectively. Furthermore, the highest removal for respective colour, COD, turbidity, and iron ion were obtained at 48 hours treatment with 87%, 81%, 86%, and 79% of removal efficiency.
Figure 5. Percentage removal of color, COD, turbidity, and Fe for 1st run(a), 2nd run(b), and 3rd run (c) at flowrate 30 ml/min
On the second running, the column was packed with CSMZ (1st layer), limestone (2nd layer), and GAC (3rd layer) as presented in Figure 5(b). The removal percentages of colour, COD, turbidity, and iron ion were noticed after 1 hour to be 52%, 49%, 71%, and 30% respectively. The time of contact between adsorbate and adsorbent is proven to play an important role during the uptake of pollutants from peat water samples by adsorption process. In addition, the development of charge on the adsorbent surface was governed by contact time and hence the efficiency and feasibility of an adsorbent for its use in water pollution control can also be predicted by the time taken to attain its equilibrium (Sharma, 2003). Removal efficiency of 90% for colour, 81% for COD, 91% for turbidity, and 57% for iron ion were obtained at 24 hours of contact time.
On the third running, the column was packed with a difference sequence of CSMZ (1st layer), GAC (2nd layer), and limestone (3rd layer) demonstrated in Figure 5(c). It can be seen that the adsorption of these four parameters were slightly rapid at time interval 1 hour to 6 hours treatment. Further gradual increment with the prolongation of contact time form 24 hours to 48 hours has also occurred. Observation at 1 hour treatment recorded the removal efficiency of 62%, 58%, 87%, and 48% for respective colour, COD, turbidity, and iron ion. Whereby, 6 hours treatment had yielded higher removal percentage removal of 75%, 77%, 93%, and 58% respectively for colour, COD, turbidity, and iron ion. Further removal of colour, COD, turbidity, and iron ion was recorded when the treatment was run for 24 hours which exhibited 92%, 91%, 98%, 77% of removal efficiency respectively. Prolonged time to 48 hours indeed showed better removal of colour, COD, turbidity, iron ion with percentage removal of 95%, 100%, 99%, and 89% respectively. It can be seen that the arrangement of CSMZ, GAC, and limestone has the highest removal efficiency for all parameters at the flow rate influent of 30 ml/min.
Figure 6. Percentage removal of color, COD, turbidity, and Fe against contact time for 2nd run(a) at flow rate 60 mL/min and at flowrate 90 mL/min (b)
The experimental adsorption behaviour was further seen for its adsorption capacity during 60 ml/min and 90 ml/min flow rate. In addition, the flow rate adjustment had also resulted in differences in surface loading rate in which the sample going through the surface area of adsorbent bed (horizontal surface area, A= 22.9 cm2) for 30 ml/min equals to 1.31 cm/min while the flow rate of 60ml/min equals to 2.62 cm/min, and the flow rate of 90 ml/min equals to 3.93 cm/min. The percentage removal for both flow rate adjustments of CSMZ, GAC, and limestone arrangement were exhibited in Figure 6 (a) and Figure 6 (b). Based on these Figures, lower removal efficiencies were indicated at 1 hour time interval of 6 hours of contact time. The percentage removals for both 60 ml/min and 90 ml/min flow rate at 1 hour were 57%, 56%, 80%, 38% and 49%, 58%, 61%, 35% for colour, COD, turbidity, and iron ion respectively. Subsequently, when the contact time was at 6 hours, the removal percentage were 70%, 79%, 88%, 56%, and 60%, 77%, 70%, 47%. However, the maximum removal efficiency at 48 hours for both flow rates was not much different from the 30ml/min flow rate.
3.5 Adsorption Isotherm
In the present investigation, the experimental data were tested with respect to both Freundlich and Langmuir isotherms. Based on the linearized Freundlich isotherm models for natural zeolite, CSMZ, GAC in terms of adsorptive capacity to remove colour, COD, turbidity, and iron ion, the majority of them exhibited fits for all adsorbate with regression value (R2) above 0.6, except for iron ion and turbidity for respective CSMZ, and GAC. On the other hand, the linearized Langmuir isotherm models for natural zeolite, CSMZ, GAC in terms of adsorptive capacity to remove colour, COD, turbidity, and iron ion, had exhibited fits for all adsorbate with regression value (R2) was at range of 0.242 to 0.912. The Langmuir isotherm model for all adsorption mechanisms were identified to have smaller R2 values compared to the Freundlich isotherm model. Thereby, it can be concluded that the Freundlich isotherm model was more applicable in determining the adsorption mechanisms for this study.
3.6 Peat Water Quality Post Column Treatment
Peat water treatment in column with serial sequence of natural zeolite, CSMZ, and limestone had exhibited the highest removal with percentage removal at 48 hours at 95%, 100%, 99%, and 89% for colour, COD, turbidity, and iron ion respectively. Final readings at 48 hours treatment on pH, TDS, DO, conductivity, salinity, colour, turbidity, COD, and iron ion were 7.78, 74 mg/l, 4.03 mg/l, 137 uS/cm, 0.05 ppt, 12 TCU, 0.23 NTU, 0 mg/l, and 0.11 mg/l respectively (see Table 3). These findings, on the other hand, have indicated that peat water treatment had successfully produced water which satisfied the standard drinking water quality.
Table 3. The characteristics of results of peat water treatment from Beriah Peat Swamp Forest
Note: 1. *)Malaysian standard for drinking water quality;2. NA = Not analyzed.
From the results presented in this paper, the following conclusions can be drawn:
1) The optimum removal of colour, COD, and turbidity for all adsorbents were observed to occur during acidic conditions at pH range 2 – 4 whereas for iron ion, the maximum removal was noted at pH range 6 – 8.
2) At pH 2, CSMZ yielded the highest removal for colour and turbidity with removal efficiency of 90% and 98% respectively. Meanwhile, GAC has the highest percentage removal of COD at pH 4 with removal efficiency obtained about 61% while at pH 6, GAC exhibited the best removal of iron ion with percentage removal around 80%.
3) CSMZ revealed stronger adsorptive capacity for colour, COD, and turbidity compared to natural zeolite.
4) The optimal removal was achieved for the serial sequence of CSMZ (1st layer), GAC (2nd layer), and Limestone (3rd layer) with the adsorbent media at 30 ml/min of flow rate.
5) Freundlich isotherm was more reliable to describe the adsorption mechanisms of colour, COD, turbidity, and iron ion for natural zeolite, CSMZ, and GAC.
The authors wish to acknowledge the financial support from the School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia and Universiti Sains Malaysia (Short Term Grant No. 304/PAWAM/60312015).
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Modern Applied Science; Vol. 7, No. 2; 2013
ISSN 1913-1844 E-ISSN 1913-1852
Published by Canadian Center of Science and Education
S. Syafalni1, Ismail Abustan1, Aderiza Brahmana1, Siti Nor Farhana Zakaria1 & Rohana Abdullah1
1 School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia. Correspondence: S. Syafalni, School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia,
Nibong Tebal 14300, Penang, Malaysia. E-mail: firstname.lastname@example.org
Received: December 3, 2012 Accepted: January 14, 2013 Online Published: January 22, 2013 doi:10.5539/mas.v7n2p39 URL: http://dx.doi.org/10.5539/mas.v7n2p39
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