Science and Industry Updates
admin 17 Jun, 2013
TweetMyron L Meters provides introductory as well as professional level material on water quality and water treatment. Did you know that Myron L Meters carries a meter specifically for testing RO systems (see below)? Water purification systems have purified brackish water and sea water for the military, businesses and farms in many different locations on […]
Myron L Meters provides introductory as well as professional level material on water quality and water treatment. Did you know that Myron L Meters carries a meter specifically for testing RO systems (see below)?
Water purification systems have purified brackish water and sea water for the military, businesses and farms in many different locations on planet Earth. Reverse osmosis water purification will create clean drinkable water when used on your drinking water.
Reverse osmosis will generally remove salt, manganese, iron, fluoride, lead, and calcium (Binnie et. al., 2002). Most mineral constituents of water are physically larger than water molecules and they are trapped by the semi-permeable membrane and removed from drinking water when filtered through an RO system (AllAboutWater.org, 2004). Meanwhile, consumers are concerned about the removal of minerals from their drinking water.
Reverse Osmosis (RO) removed 90-99.99% of all the contaminants including minerals from the drinking water supply (see Figure 1). RO removes minerals because they have larger molecules than water. The subject of minerals and RO created controversy and disagreement among water and health professionals. The World Health Organization (WHO) made clarification that majority of healthy minerals are needed for human body is from food or dietary supplementary sources and not from drinking tap water. In addition, minerals found in water can be harmful to human health. The evidence is strong that calcium and magnesium are essential elements for human body (WQA, 2011). However, its a weak argument to suggest that we should make up this deficiency through water consumption (WQA, 2011). Tap water presents a variety of inorganic minerals which the human body has difficulty absorbing (Misner, 2004). Their presence is suspect in a wide array of degenerative diseases, such as hardening of the arteries, arthritis, kidney stones, gall stones, glaucoma, cataracts, hearing loss, emphysema, diabetes, and obesity. What minerals are available, especially in “hard” tap water, are poorly absorbed, or rejected by cellular tissue sites, and, if not evacuated, their presence may cause arterial obstruction, and internal damage (Dennison, 193; Muehling, 1994; Banik, 1989).
Figure 1. Reverse Osmosis Membrane (Source:DOI-BUR, 2009)
Organic Minerals vs. Inorganic Minerals
There are two types of minerals in water, organic and inorganic. Human physiology has a biological affinity for organic minerals. Most organic minerals for our body functions come from dietary plant foods (Misner, 2004). A growing plant converts the inorganic minerals from the soils to a useful organic mineral (Misner, 2004). When an organic mineral (from a plant food) enters the stomach it must attach itself to a specific protein-molecule (chelation) in order to be absorbed, then it gains access to the tissue sites where it is needed (Misner, 2004). Once a plant mineral is divested within the body, it is utilized as a coenzyme for composing body fluids, forming blood and bone cells, and the maintaining of healthy nerve transmission (Balch & Balch 1990).
Reverse Osmosis has Little Effect on Water pH
Water pH levels will automatically change when water is ingested and comes into contact with the food in your stomach (Wise, 2011). Even on an empty stomach, your stomach acid alone is already several times more acidic than RO water (pH 6-8) with a pH level of 2 (Wise, 2011). The human body regulates pH levels constantly to find balance and equilibrium (see Figure 2). Therefore under normal conditions it will always maintain a neutral 7.4 pH balance (Wise, 2011). The healthy body is very robust and it will restore homeostatic pH fairly quickly and easily (Wise 2011). Soft drinks and sports drinks typically have a pH level of 2.5, orange juice has a 3 pH and coffee has a 4 pH level and we drink these beverages all the time without problems (Wise, 2011).
Figure 2. Comparison of pH Levels (Source: Wise, 2011)
Water filtered or treated by reverse osmosis is generally pure, clean, and healthy. A reverse osmosis treatment system is currently the only technology that can remove most of the emerging contaminants (i.e., prescription drugs and perchlorate) including other contaminants (i.e., arsenic, cyanide, and fluoride) that are difficult to remove by other treatment methods. No more ingesting of harmful inorganic minerals means the body will no longer be stressed with trying to absorb something that wasn’t supposed to be there in the first place (Wise, 2011). Consumers should not be concerned about the removal of minerals by RO system. As the WHO (2009) and WQA (2011) pointed out, the human body obtains the vast majority of minerals from food or supplements, not from drinking water.
One of the downsides to the reverse osmosis process is that it is so effective in removing particles, it will also remove minerals from your water that may be beneficial. The body needs certain minerals, such as calcium and magnesium, to function properly. In addition, some people believe minerals such as this actually add flavor to the water, so that will be missing if you filter the water. Some find a certain acidic taste to water that has been purified by reverse osmosis. A reverse osmosis system also wastes a certain amount of water. For every gallon of purified water, three or four gallons have to be processed. If water is scarce or expensive in your area, this is a strong consideration.
The Myron L RO-1 was developed years ago specifically for Culligan, and is designed for testing RO systems.
The choice of professionals for years, this compact instrument has been designed specifically to demonstrate and test Point of Use (POU) reverse osmosis or distillation systems. By measuring electrical conductivity, it will quickly determine the parts per million/Total Dissolved Solids (ppm/TDS) of any drinking water.
With a single ‘before and after’ test, this handy device effectively demonstrates how your RO or distillation system eliminates harmful dissolved solids. It will also service test systems, including membrane evaluation programs. Find out more about the RO-1 meter HERE.
admin 10 Jun, 2013
TweetWastewater is treated in 3 phases: primary (solid removal), secondary (bacterial decomposition), and tertiary (extra filtration). fig. 1 Origins of Sewage Sewage is generated by residential and industrial establishments. It includes household waste liquid from toilets, baths, showers, kitchens, sinks, and so forth that is disposed of via sewers. In many areas, sewage also includes […]
Wastewater is treated in 3 phases: primary (solid removal), secondary (bacterial decomposition), and tertiary (extra filtration).
Origins of Sewage
Sewage is generated by residential and industrial establishments. It includes household waste liquid from toilets, baths, showers, kitchens, sinks, and so forth that is disposed of via sewers. In many areas, sewage also includes liquid waste from industry and commerce. The separation and draining of household waste into greywater and blackwater is becoming more common in the developed world. Greywater is water generated from domestic activities such as laundry, dishwashing, and bathing, and can be reused more readily. Blackwater comes from toilets and contains human waste.
Sewage may include stormwater runoff. Sewerage systems capable of handling storm water are known as combined sewer systems. This design was common when urban sewerage systems were first developed, in the late 19th and early 20th centuries. Combined sewers require much larger and more expensive treatment facilities than sanitary sewers. Heavy volumes of storm runoff may overwhelm the sewage treatment system, causing a spill or overflow. Sanitary sewers are typically much smaller than combined sewers, and they are not designed to transport stormwater. Backups of raw sewage can occur if excessive infiltration/inflow (dilution by stormwater and/or groundwater) is allowed into a sanitary sewer system. Communities that have urbanized in the mid-20th century or later generally have built separate systems for sewage (sanitary sewers) and stormwater, because precipitation causes widely varying flows, reducing sewage treatment plant efficiency.
As rainfall travels over roofs and the ground, it may pick up various contaminants including soil particles and other sediment, heavy metals, organic compounds, animal waste, and oil and grease. (See urban runoff.) Some jurisdictions require stormwater to receive some level of treatment before being discharged directly into waterways. Examples of treatment processes used for stormwater include retention basins, wetlands, buried vaults with various kinds of media filters, and vortex separators (to remove coarse solids).
Sewage treatment is done in three stages: primary, secondary and tertiary treatment (Figure 1).
In primary treatment, sewage is stored in a basin where solids (sludge) can settle to the bottom and oil and lighter substances can rise to the top. These layers are then removed and then the remaining liquid can be sent to secondary treatment. Sewage sludge is treated in a separate process called sludge digestion.
Secondary treatment removes dissolved and suspended biological matter, often using microorganisms in a controlled environment. Most secondary treatment systems use aerobic bacteria, which consume the organic components of the sewage (sugar, fat, and so on). Some systems use fixed film systems, where the bacteria grow on filters, and the water passes through them. Suspended growth systems use “activated” sludge, where decomposing bacteria are mixed directly into the sewage. Because oxygen is critical to bacterial growth, the sewage is often mixed with air to facilitate decomposition.
Tertiary treatment (sometimes called “effluent polishing”) is used to further clean water when it is being discharged into a sensitive ecosystem. Several methods can be used to further disinfect sewage beyond primary and secondary treatment. Sand filtration, where water is passed through a sand filter, can be used to remove particulate matter. Wastewater may still have high levels of nutrients such as nitrogen and phosphorus. These can disrupt the nutrient balance of aquatic ecosystems and cause algae blooms and excessive weed growth. Phosphorus can be removed biologically in a process called enhanced biological phosphorus removal. In this process, specific bacteria, called polyphosphate accumulate organisms that store phosphate in their tissue. When the biomass accumulated in these bacteria is separated from the treated water, these biosolids have a high fertilizer value. Nitrogen can also be removed using nitrifying bacteria. Lagooning is another method for removing nutrients and waste from sewage. Water is stored in a lagoon and native plants, bacteria, algae, and small zooplankton filter nutrients and small particles from the water.
Sludge Digestion & Disposal
Sewage sludge scraped off the bottom of the settling tank during primary treatment is treated separately from wastewater. Sludge can be disposed of in several ways. First, it can be digested using bacteria; bacterial digestion can sometimes produce methane biogas, which can be used to generate electricity. Sludge can also be incinerated, or condensed, heated to disinfect it, and reused as fertilizer.
When a liquid sludge is produced, further treatment may be required to make it suitable for final disposal. Sewage sludge scraped off the bottom of the settling tank during primary treatment is treated separately from wastewater. Sludge can be disposed of in several ways. First, it can be digested using bacteria; bacterial digestion can sometimes produce methane biogas, which can be used to generate electricity. Sludge can also be incinerated, or condensed, heated to disinfect it, and reused as fertilizer.
Typically, sludges are thickened (dewatered) to reduce the volumes transported off-site for disposal. There is no process which completely eliminates the need to dispose of biosolids. There is, however, an additional step some cities are taking to superheat sludge and convert it into small pelletized granules that are high in nitrogen and other organic materials. In New York City, for example, several sewage treatment plants have dewatering facilities that use large centrifuges along with the addition of chemicals such as polymer to further remove liquid from the sludge. The removed fluid, called “centrate,” is typically reintroduced into the wastewater process. The product which is left is called “cake,” and that is picked up by companies which turn it into fertilizer pellets. This product is then sold to local farmers and turf farms as a soil amendment or fertilizer, reducing the amount of space required to dispose of sludge in landfills. Much sludge originating from commercial or industrial areas is contaminated with toxic materials that are released into the sewers from the industrial processes. Elevated concentrations of such materials may make the sludge unsuitable for agricultural use and it may then have to be incinerated or disposed of to landfill.
Notably, throughout the development of excreta, wastewater, wastewater sludge and biosolids management – from the least developed to the most developed countries – there are inevitable public concerns about how best to manage this “waste” that is also a resource. Putting biosolids to their best uses in each local situation is the goal of most of the programs discussed in the following reports. That is the goal of many sanitation and water quality experts. But the general public has other goals: avoiding the waste and the odors it can produce.There is a natural aversion to fecal matter and anything associated with it. Conflicts arise when experts propose recycling this “waste,” usually in a treated and tested form commonly called “biosolids,” back to soils in communities.
Managing excreta and wastewater sludge to produce recyclable biosolids involves many technical challenges. But equally significant are these social, cultural, and political challenges. Funding is required to build infrastructure – and, around the world, the public is the source of funding, either through taxes or sewer usage fees. In order for proper sanitation to be built and operated, complex community sanitation agencies with support from state, provincial, and national governments are needed.
Wastewater quality indicators are laboratory tests to assess suitability of wastewater for disposal or re-use. Tests selected and desired test results vary with the intended use or discharge location. Tests measure physical, chemical, and biological characteristics of the wastewater.
Aquatic organisms cannot survive outside of specific temperature ranges. Irrigation runoff and water cooling of power stations may elevate temperatures above the acceptable range for some species. Temperature may be measured with a calibrated thermometer.
Solid material in wastewater may be dissolved, suspended, or settleable. Total dissolved solids or TDS (sometimes called filtrable residue) is measured as the mass of residue remaining when a measured volume of filtered water is evaporated. The mass of dried solids remaining on the filter is called total suspended solids (TSS) or nonfiltrable residue. Settleable solids are measured as the visible volume accumulated at the bottom of an Imhoff cone after water has settled for one hour. Turbidity is a measure of the light scattering ability of suspended matter in the water. Salinity measures water density or conductivity changes caused by dissolved materials.
Virtually any chemical may be found in water, but routine testing is commonly limited to a few chemical elements of unique significance.
Water ionizes into hydronium (H3O) cations and hydroxyl (OH) anions. The concentration of ionized hydrogen (as protonated water) is expressed as pH.
Most aquatic habitats are occupied by fish or other animals requiring certain minimum dissolved oxygen concentrations to survive. Dissolved oxygen concentrations may be measured directly in wastewater, but the amount of oxygen potentially required by other chemicals in the wastewater is termed an oxygen demand. Dissolved or suspended oxidizable organic material in wastewater will be used as a food source. Finely divided material is readily available to microorganisms whose populations will increase to digest the amount of food available. Digestion of this food requires oxygen, so the oxygen content of the water will ultimately be decreased by the amount required to digest the dissolved or suspended food. Oxygen concentrations may fall below the minimum required by aquatic animals if the rate of oxygen utilization exceeds replacement by atmospheric oxygen.
The reaction for biochemical oxidation may be written as:
Oxidizable material + bacteria + nutrient + O2 → CO2 + H2O + oxidized inorganics such as NO3 or SO4
Oxygen consumption by reducing chemicals such as sulfides and nitrites is typified as follows:
S– + 2 O2 → SO4–
NO2- + ½ O2 → NO3-
Since all natural waterways contain bacteria and nutrient, almost any waste compounds introduced into such waterways will initiate biochemical reactions (such as shown above). Those biochemical reactions create what is measured in the laboratory as the biochemical oxygen demand (BOD).
Oxidizable chemicals (such as reducing chemicals) introduced into a natural water will similarly initiate chemical reactions (such as shown above). Those chemical reactions create what is measured in the laboratory as the chemical oxygen demand (COD).
Both the BOD and COD tests are a measure of the relative oxygen-depletion effect of a waste contaminant. Both have been widely adopted as a measure of pollution effect. The BOD test measures the oxygen demand of biodegradable pollutants whereas the COD test measures the oxygen demand of biogradable pollutants plus the oxygen demand of non-biodegradable oxidizable pollutants.
The so-called 5-day BOD measures the amount of oxygen consumed by biochemical oxidation of waste contaminants in a 5-day period. The total amount of oxygen consumed when the biochemical reaction is allowed to proceed to completion is called the Ultimate BOD. The Ultimate BOD is too time consuming, so the 5-day BOD has almost universally been adopted as a measure of relative pollution effect.
There are also many different COD tests. Perhaps, the most common is the 4-hour COD.
There is no generalized correlation between the 5-day BOD and the Ultimate BOD. Likewise, there is no generalized correlation between BOD and COD. It is possible to develop such correlations for a specific waste contaminant in a specific wastewater stream, but such correlations cannot be generalized for use with any other waste contaminants or wastewater streams.
The laboratory test procedures for the determining the above oxygen demands are detailed in the following sections of the “Standard Methods For the Examination Of Water and Wastewater” available at www.standardmethods.org:
5-day BOD and Ultimate BOD: Sections 5210B and 5210C
COD: Section 5220
Nitrogen is an important nutrient for plant and animal growth. Atmospheric nitrogen is less biologically available than dissolved nitrogen in the form of ammonia and nitrates. Availability of dissolved nitrogen may contribute to algal blooms. Ammonia and organic forms of nitrogen are often measured as Total Kjeldahl Nitrogen, and analysis for inorganic forms of nitrogen may be performed for more accurate estimates of total nitrogen content.
Chlorine has been widely used for bleaching, as a disinfectant, and for biofouling prevention in water cooling systems. Remaining concentrations of oxidizing hypochlorous acid and hypochlorite ions may be measured as chlorine residual to estimate effectiveness of disinfection or to demonstrate safety for discharge to aquatic ecosystems.
Water may be tested by a bioassay comparing survival of an aquatic test species in the wastewater in comparison to water from some other source. Water may also be evaluated to determine the approximate biological population of the wastewater. Pathogenic micro-organisms using water as a means of moving from one host to another may be present in sewage. Coliform index measures the population of an organism commonly found in the intestines of warm-blooded animals as an indicator of the possible presence of other intestinal pathogens.
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admin 4 Jun, 2013
Tweet MyronLMeters.com brings you the latest in conductivity measurement research like the article below. Please click here for accurate, reliable, conductivity meters. Abstract Assessment of seed vigor has long been an important tool of seed quality control programs. The conductivity test is a promising method for assessment of seed vigor, but proper protocols for its […]
MyronLMeters.com brings you the latest in conductivity measurement research like the article below. Please click here for accurate, reliable, conductivity meters.
Assessment of seed vigor has long been an important tool of seed quality control programs. The conductivity test is a promising method for assessment of seed vigor, but proper protocols for its execution have yet to be established. The objective of this study was to assess the efficiency of electrical conductivity (EC) testing as a means of assessing the viability of freshly collected Kielmeyera Coriacea Mart. seeds. The test was performed on individual seeds rather than in a bulk configuration. Seeds were soaked for different periods (30 min, 90 min, 120 min., 180 min, and 240 min) at a constant temperature of 25°C. Conductivity was then measured with a benchtop EC meter.
Seeds are the primary factor of the seedling production process, despite their minor contribution to the end cost of each seedling. In order to estimate the success rate of seedling production, it is essential that seed characteristics such as vigor and germinability be known .
The importance of knowing the characteristics of Brazilian forest species to safer and more objective management of seedling production cannot be overstated. However, such studies are scarce, particularly in light of the vast number of species with this potential . Given the intensity of anthropogenic pressure and the importance of rehabilitating disrupted or degraded environments, in-depth research of forest species is warranted.
Routine methods used for determination of seed quality and viability include germination testing and the tetrazolium test. Methods such as measurement of soak solution pH, electrical conductivity, and potassium content of leachate, all based on the permeability of the cell membrane system, are increasingly being employed in the assessment of seed vigor, as they are reliable and fast and can thus speed the decision making process.
Electrical conductivity testing, as applied to forest seeds, has yet to be standardized. Studies conducted thus far have focused on assessment of seed soaking times, which may range from 4 to 48 hours. Even at 48 hours, the conductivity test is considered a rapid technique as compared to the germination test, which, despite its status as a widespread and firmly established method, can take anywhere from 30 to 360 days to yield results (depending on species), and is limited by factors such as dormant seeds.
The total concentration of electrolytes leached by seeds during soaking has long been assessed indirectly, mostly through the conductivity test, which takes advantage of the fact that inorganic ions make up a substantial portion of these electrolytes [3–5].
Rapid assessment of seed quality allows for preemptive decision-making during harvest, processing, sale and storage operations, thus optimizing use of financial resources throughout these processes.
K. coriacea Mart. is a species of the Clusiaceae (Guttiferae) family popularly known in Brazil as pau-santo (Portuguese for “holy wood”), due to its properties as a medicinal and melliferous plant and as a source of cork. In traditional Brazilian medicine, the leaves are used as an emollient and antitumor agent, and the resin as a tonic and in the treatment of toothache and various infections. The fruits are used in regional crafts and flower arrangements. Even if the dye is of the leaves and bark. The trunk provides cork .
K. coriaceae specimens grow to approximately 4 meters in height. The flowering period extends from January to April and the fruiting period from May to September, and seed collection can take place from September onwards. Leaves are alternate, simple, oval to elliptical, coriaceous, and clustered at the end of the branches, and feature highly visible, pink midribs. A white to off-white latex is secreted in small amounts upon removal of leaves. Flowers are white to pale pink in color, large, fragrant, with many yellow stamens and are borne in short clusters near the apex of the branches. Seedling production requires that seeds be sown shortly after collection.
In the fruit are found 60 to 80 seeds with anemochoric. The seed varies from round to oblong, winged at the ends, light brown color, has integument thin and fragile, with smooth texture, the sizes range from 4.3 to 5.6 cm long, 1.3 to 1.9 cm wide, and 0.2 to 0.5 centimeter thick. The individual weight of the seeds ranges from. 112 to.128 grams. Nursery radicle emission occurred at 7 days and the germination rate was 90%. Germination occurs within 7 to 10 days. The species is slow growing, both in the field and in a nursery setting .
The present study sought to assess the applicability of the conductivity test to freshly collected K. coriacea Mart. seeds by determining the optimal soak time for performance of the test and comparing results obtained with this method against those obtained by tetrazolium and germination testing of seeds from the same batch.
2. Materials and Methods
2.1. Seed Collection
Seeds were collected in the cerrado sensu stricto, in SCA (Clean Water Farm), area of study at the University of Brasília (UNB) in August 2010, matrixes marked with the aid of GPS, after the period of physiological maturation of the seeds. The collection of fruits was directly from the tree, with the help of trimmer, then the seeds were processed and stored in paper bags at room temperature in the laboratory.
2.2. Conductivity Test
The development of tests to evaluate the physiological quality of seeds, as well as the standardization of these is essential for the establishment of an efficient quality control . One of the main requirements for the seed vigor refers to obtain reliable results in a relatively short period of time, allowing the speed of decision making especially as regards the operations of collection, processing, and marketing . The literature indicates that rapid tests are most studied early events related to the deterioration of the sequence proposed by Delouche and Baskin  as the degradation of cell membranes and reduced activity, and biosynthetic respiratory . The measurement of electrical conductivity through the electrolyte amount released by soaking seeds in water has been applied by the individual method where each seed is a sample or more often, a sample of seed representative of a population (mass method). For this case, the results represent the average conductivity of a group of seeds, may a small amount of dead seeds affect the conductivity of a batch with many high-quality seed generating a read underestimated. To minimize this problem, we recommend choosing the seeds, excluding the damaged seeds.
The electrical conductivity is based on the principle that the deterioration process is the leaching of the cells of seeds soaked in water due to loss of integrity of cellular systems. Thus, low conductivity means a high-quality seed and high conductivity, that is, greater output seed leachate, suggests that less force .
The electrical conductivity is not yet widely used in Brazil, its use is restricted to activities related to research (Krzyzanowski et al., 1991). There are common jobs using this test to determine the physiological quality of tree seeds. However, it is a promising vigor test for possible standardization of the methodology, at least within a species. However, it is a promising vigor test for possible standardization of the methodology, at least within a species. However, there are factors which influence the conductivity values as the size, the initial water content, temperature and time of soaking, the number of seeds per sample, and genotype .
Five treatments were carried out to test the efficiency of the conductivity test as a means of evaluating the viability of freshly collected K. coriacea Mart. seeds.
Five runs of 20 seeds were tested for each treatment. Seeds were individually placed into containers holding 50 mL of distilled water and left to soak for 30, 90, 120, 180, and 240 minutes in a germination chamber set to a constant temperature of 25°C. The minimum time taken for the soaking of 30 minutes was adopted by the same authors and Amaral and peske , Fernandes et al. , and Matos  who concluded that the period of 30 minutes of soaking is more effective to estimate the germination of the seeds. After each period, the conductivity of the soak solution was immediately tested with a benchtop EC meter precise to +/−1% (Quimis). Readings were expressed as μS·cm−1/g−1 seed .
Data thus obtained were subjected to analysis of variance with partitioning into orthogonal polynomials for analysis of the effect of soaking times on electrical conductivity.
2.3. Tetrazolium Test
The tetrazolium test, also known as biochemical test for vitality, is a technique used to estimate the viability and seed germination. A fundamental condition for ensuring the efficiency of the test is the direct contact of the tetrazolium solution with the tissues of the seed to be tested. Due to the impermeability of the coats of most forest tree seeds, it is necessary to adopt a previous preparation of the seeds that were tested. This preparation is based on facilitating entry of the solution in the seed. Among the preparations that precede the test we have cutting the seed coat, seed coat removal, scarification by sandpaper scarification by soaking in hot water and water . In the previous preparation of the seeds, factors such as concentration of the solution or even the time of the staining solution can affect the efficiency of the test in the evaluation of seed quality. The time required for the development of appropriate color according to the Rules for Seed Analysis  varies depending on each species, can be between 30 and 240 minutes.
The tetrazolium test has been widely used in seeds of various species due to the speed and efficiency in the characterization of the viability and vigor, and the possibility of damage to the same distinction, assisting in the process of quality control from the steps of harvest storage (GRIS et al, 2007).
The tetrazolium test was also applied to freshly collected K. coriacea Mart. seeds, for a total of three runs and 20 seeds. Seeds were soaked in a 0.5% solution of 2,3,5-triphenyl-2H-tetrazolium for 24 hours in a germination chamber set to a constant temperature of 25°C. After each run, seeds were washed, bisected, and the half-containing the embryonic axis placed under a stereo viewer for examination of staining patterns .
2.4. Germination Test
The standard germination test is the official procedure to evaluate the ability of seeds to produce normal seedlings under favorable conditions in the field, but does not always reveal differences in quality and performance among seed lots, which can manifest in storage or in the field .
During the germination test optimum conditions are provided and controlled for seeds to encourage the resumption of metabolic activity which will result in the seedlings. The main objective of the germination test is the information about the quality of seeds, which is used in the identification of lots for storage and sowing .
Freshly collected K. coriacea Mart. seeds were placed in a germination chamber at a constant temperature of 25°C (Treatment 1) or an alternating temperature of 20–30°C (Treatment 2), on a standard cycle of 8 hours of light and 16 hours of dark. Each test consisted of five runs and was performed on 20 seeds.
Germination was defined as emergence of at least 2.0 mm of the primary root . Assessment was conducted daily, and emergence was observed between day 6 and day 7. At the end of the 14-day test period, the germination percentage was calculated on the basis of radicle emergence .
3.1. Conductivity Test
Different soaking times were not associated with any significant differences in conductivity results in K. coriacea Mart. seeds (Table 1).
Table 1: Conductivity ranges of freshly collected Kielmeyera coriacea Mart. seeds after soaking for different periods.
Seeds with a leachate conductivity range of 7–17.99 μS·cm·g were considered nonviable, confirming the hypothesis behind conductivity testing, which is the nonviable seeds that have higher soaking solution conductivity values (Table 2).
Table 2: Percentage of viable Kielmeyera coriacea Mart. seeds according to EC range.
Analysis of variance revealed a low coefficient of variation (20.26%), which suggests good experimental control (Table 3).
Table 3: Analysis of variance of various soaking times for electrical conductivity testing of Kielmeyera coriacea Mart. seeds.
After analysis of variance, the correlation between the soaking time and electrical conductivity variables was assessed. The cubic model yielded
which is indicative of a positive correlation between the study variables.
The following equation was obtained on the basis of the cubic model:
Analysis of a plot of the above function in the GeoGebra 2007 software package shows that variation in electrical conductivity as a function of soaking time is minor and approaches a constant, which is consistent with the study results, in which changes in soaking time had no influence on conductivity (Figure 1).
Figure 1: Leachate conductivity as a function of soaking time in Kielmeyera coriaceaMart. seeds.
Matos  reported that a 30-minute soak was enough for assessment of Anadenanthera falcata, Copaifera langsdorffii, and Enterolobium contortisiliquum seeds by the soaking solution pH method—that is, the amount of matter leached after this period sufficed for measurement.
Although the principle of conductivity is the same used for the test pH of exudate, the soaking time needed to analyze the differential seeds through the conductivity may be explained by the fact that this technique is quantitative, while pH in the art exudate analyzes are qualitative. In other words to the technique of pH values of the exudate it is important to detect the acidity of imbibition while on the electrical conductivity we draw a comparison between the analyzed values to separate viable from nonviable samples. To determine a value of electrical conductivity as a reference to determine viable seeds are to be considered the values obtained for fresh seeds and seeds stored.
The thickness of the K. coriacea Mart. seed coat may also have affected the soaking procedure; this species has very thin seed coats, which makes soaking a very fast process.
These results are consistent with those reported by Rodrigues , who subjected stored K. coriaceaMart. seeds to the conductivity test and found that 90 minutes is an appropriate soaking time for analysis.
Therefore, it can be inferred that for seed Kielmeyera coriacea Mart. the soaking time of 90 minutes can be applied to obtain satisfactory results.
3.2. Tetrazolium Test
Table 4 shows the results of tetrazolium testing of K. coriacea Mart. seeds in our sample. The mean viability rate was 96.6%. The testing procedure was based on Brazilian Ministry of Agriculture recommendations .
Table 4: Tetrazolium testing of Kielmeyera coriacea Mart. seeds.
The results of the tetrazolium test were quite similar to those obtained with the conductivity method, thus confirming the efficiency of the latter method as a means for assessing the viability of K. coriaceaMart. seeds.
3.3. Germination Test
The germination test results of freshly collected K. coriacea Mart. seeds are shown in Table 5. Regardless of temperature, both test batches exhibited good viability, and no seed dormancy was detected.
Table 5: Germination test results of Kielmeyera coriacea Mart. seeds.
Radicle emergence was observed between day 7 and day 9 of the test, according to the analysis criteria proposed by Labouriau .
These findings are consistent with those of Melo et al.,  who reported high and relatively rapid germination rates for K. coriacea seeds kept at 25°C on paper towels, with emergence of a perfect radicle on the 7th day of assessment.
The electrical conductivity can be used as an indicator of seed viability and presents two advantages: to provide rapid and reliable results and the technique is not destructive and can use the seeds after the conductivity test, so they can be used to produce seedlings.
The present study showed that different soaking times had no effect on the results of conductivity testing of freshly collected K. coriacea Mart. seeds, suggesting that the amount of leached matter was never below the threshold required for adequate testing.
Electrical conductivity testing proved to be a feasible option for viability testing of K. coriacea Mart. seeds, as the results obtained with conductivity testing were confirmed by germination testing and by the tetrazolium test.
- J. M. M. Matos, Evaluation of pH test on exudate check feasibility of forest seeds, dissertation, University of Brasília, Brasília, Brazil, 2009.
- F. Poggiani, S. Bruni, and E. S. Q. Barbos, “Effect of shading on seedling growth of three species forest,” in National conference on native plants, vol. 2, pp. 564–569, Institute of Forestry, 1992.
- M. B. Mcdonald Jr. and D. O. Wilson, “ASA-610 ability to detect changes in soybean seed quality,” Journal of Seed Technology, vol. 5, no. 1, pp. 56–66, 1980.
- S. Matthews and A. Powell, “A eletrical conductivity test,” in Handbook of Vigor Test Methods, D. A. Perry, Ed., pp. 37–42, International Seed Testing Associaty, Zurich, Switzerland, 1981.
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- A. S. Amaral and S. T. Peske, “Exudate pH to estimate, in 30 minutes seed viability of soybeans,”Journal of seeds, vol. 6, no. 3, pp. 85–92, 1984.
- E. J. Fernandes, R. Sader, and N. M. Carvalho, “seed viability beans (Phaseolus vulgaris L.) estimated by the pH of the exudate,” in Congress Brazil’s Seeds, Gramado, Brazil, 1987.
- F. C. Krzyzanowski and R. D. Vieira, “Electrical conductivity test,” in Seed Vigor: Concepts and Tests, F. C. Krzyzanowski, R. D. Vieira, and J. B. France Neto, Eds., pp. 4.1–4.26, Abrates, London, UK, 1999.
- Ministry of Agriculture, Livestock and Supply, Rule for seed testing, SNPA/DNPV/CLAV, Brasilia, Brazil, 1992.
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Research article by: Kennya Mara Oliveira Ramos,1 Juliana M. M. Matos,1 Rosana C. C. Martins,1 and Ildeu S. Martins2
1Seed Technology Laboratory of Forestry, Department of Forestry, University of Brasilia, CP 04357, 70919970 Campus Asa Norte, DF, Brazil
2Department of Forestry, University of Brasilia, CP 04357, 70919970 Campus Asa Norte, DF, Brazil
Received 17 December 2011; Accepted 14 February 2012
Academic Editors: A. Berville, C. Gisbert, J. Hatfield, and Y. Ito
Copyright © 2012 Kennya Mara Oliveira Ramos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
admin 26 May, 2013
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://188.8.131.52/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:
-McFadden’s Pond (site A)*:
-McFadden’s Pond (site B)*:
Spring (May): (with ph/conductivity probe) -Quarry Pond:
-McFadden’s Pond (Site A):
-McFadden’s Pond (Site B):
Spring (May): (LoggerPro Data) -Quarry Pond:
-McFadden’s Pond (Site A):
-McFadden’s Pond (Site B):
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
admin 17 Apr, 2013
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
|Column volume, V
||30, 60, 90
|Surface Loading Rate, SLR= Q/A
||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: email@example.com
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
Shared via Creative Commons Attribution 3.0 Unported license
admin 11 Apr, 2013
Tweet Myron L Meters Myron L Meters sells the most accurate, reliable conductivity instruments in the water treatment industry. You can find some of our most popular meters here: http://www.myronlmeters.com/SearchResults.asp?Search=conductivity&x=-1345&y=-145 Introduction Along with the development of more and more complex integrated models for urban water systems the need of sufficient data bases grows as well. […]
Myron L Meters
Myron L Meters sells the most accurate, reliable conductivity instruments in the water treatment industry. You can find some of our most popular meters here:
Along with the development of more and more complex integrated models for urban water systems the need of sufficient data bases grows as well. It is even complicated to measure relevant parameters,e.g. dissolved nitrogen or COD, for their use in Waste Water Treatment Plants and sewer models to describe the influence of catchments to the receiving water.
This poster presents a method regarding the possibility of substituting an online ammonia measurement by conductivity measurements in the inflow of a Waste Water Treatment Plant . The aim was the description of the dynamics in wet weather flow through storm water events for modelling purposes.
The conductivity of an aqueous solution is the measure of its ability to conduct electricity. Responsible for that phenomenon are ions of dissolved salts. In natural and drinking water these are mainly carbonates, chlorides and sulphates of calcium, magnesium, sodium and potassium. Conducted experiences and measurements in combined sewers showed a relation between conductivity in Waste Water Treatment Plant inflow and the concentration of dissolved components, e.g. ammonia, in case of rainfall events. The data for different 3 Waste Water Treatment Plant are shown in Figure 1. Rainwater has nearly no ions that cause conductivity to be measured. Therefore, diluted wastewater flowing into the Waste Water Treatment Plant can be detected by a conductivity probe. The measure and quality of linear regression between ammonia concentration and conductivity can be found in Table 1 for all data from Figure 1.
Material and Methods
With this knowledge a simple regression-based inflow model for use in activated sludge modelling of Waste Water Treatment Plant was defined to use conductivity beside available composite samples as a measure for dynamics in ammonia concentration as one of the most dynamic measure.
Results and Discussion
For one of the considered Waste Water Treatment Plants (WWTP) the resulting quality for the inflow model is shown in Figure 2 for a time series of a week.
Furthermore, the inflow model was used as a source for a retention tank model at the inlet of another Waste Water Treatment Plant to describe the impact of different management strategies (storage or flow through) on receiving water and Waste Water Treatment Plant (Figure 3).
A long-term modelling of 9 storm water events was used to show the predictive capacity of the model. The regression parameters were fitted by an optimisation routine to get best fit for all concentrations (also for COD, not presented here). Figure 3 shows the fit for all events. A good prediction of dynamics and absolute values for ammonia can be seen.
The results of different Goodness-of-fit measures are summarized in Table 2 for both presented WWTP inflows. Especially the values for the modified Coefficient of Efficiency, as a well-known and used measure for model quality in hydrological sciences, show the degree of predicting of the used method and the usability of conductivity for description of influent dynamics to Waste Water Treatment Plant in storm water cases.
This simple and easy-to-use method is well suited for implementation in Waste Water Treatment Plant models to describe the inflow dynamics regarding a more realistic behavior e.g. for optimization of process control.
by Markus Ahnert*, Norbert Günther*, Volker Kuehn*, University of Dresden
Ahnert, M., Blumensaat, F., Langergraber, G., Alex, J., Woerner, D., Frehmann, T., Halft, N., Hobus, I., Plattes, M., Spering, V. und Winkler, S. (2007), Goodness-of-fit measures for numerical modelling in urban water management – a summary to support practical applications., paper presented at 10th IWA Specialised Conference on “Design, Operation and Economics of Large Wastewater Treatment Plants”, 9-13 September 2007, Vienna, Austria, 9-13 September 2007.
Nash, J. E. und Sutcliffe, J. V. (1970), River flow forecasting through conceptual models part I – A discussion of principles, Journal of Hydrology, 10, 282.
admin 3 Apr, 2013
TweetThe thermal conductivity enhancement of nanofluids Abstract Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal […]
The thermal conductivity enhancement of nanofluids
Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal conductivity of a variety of nanofluids. The base fluids used included those that are most employed heat transfer fluids, such as deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG. Various nanoparticles (NPs) involving Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives. Our findings demonstrated that the thermal conductivity enhancements of nanofluids could be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed.
More efficient heat transfer systems are increasingly preferred because of the accelerating miniaturization, on the one hand, and the ever-increasing heat flux, on the other. In many industrial processes, including power generation, chemical processes, heating or cooling processes, and microelectronics, heat transfer fluids such as water, mineral oil, and ethylene glycol always play vital roles. The poor heat transfer properties of these common fluids compared to most solids is a primary obstacle to the high compactness and effectiveness of heat exchangers. An innovative way of improving the thermal conductivities of working media is to suspend ultrafine metallic or nonmetallic solid powders in traditional fluids since the thermal conductivities of most solid materials are higher than those of liquids. A novel kind of heat transfer enhancement fluid, the so-called nanofluid, has been proposed to meet the demands .
“Nanofluid” is an eye-catching word in the heat transfer community nowadays. The thermal properties, including thermal conductivity, viscosity, specific heat, convective heat transfer coefficient, and critical heat flux have been studied extensively. Several elaborate and comprehensive review articles and books have addressed thermal transport properties of nanofluids [1,3-6]. Among all these properties, thermal conductivity is the first referred one, and it is believed to be the most important parameter responsible for the enhanced heat transfer. Investigations on the thermal conductivity of nanofluids have been drawing the greatest attention of the researchers. A variety of physical and chemical factors, including the volume fraction, the size, the shape, and the species of the nanoparticles (NPs), pH value and temperature of the fluids, the Brownian motion of the NPs, and the aggregation of the NPs, have been proposed to play their respective roles on the heat transfer characteristics of nanofluids [7-19]. Extensive efforts have been made to improve the thermal conductivity of nanofluids [7-19] and to elucidate the thermal transport mechanisms in nanofluids [20-23].
The authors have carried out a series of studies on the heat transfer enhancement performance of nanofluids. A variety of nanofluids have been produced by the one- or two-step method. The base fluids used include deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG (DW-EG). Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs (DNPs), and carbon nanotubes (CNTs) with different pretreatments have been used as additives. The thermal conductivities of these nanofluids have been measured by transient hot wire (THW) method or short hot wire (SHW) technique. In this article, the experimental results that elucidate the influencing factors for thermal conductivity enhancement of nanofluids are presented. The thermal transport mechanisms in nanofluids and promising approaches for optimizing the thermal conductivity of nanofluids are further presented.
Preparation of nanofluids
Two techniques have been applied to prepare nanofluids in our studies: two- and one-step techniques. Most of the studied nanofluids were prepared by the two-step technique. During the procedure of two-step technique, the dispersed NPs were prepared by chemical or physical methods first, and then the NPs were added into a specified base fluid, with or without pretreatment and surfactant based on the need. In the preparation of nanofluids containing metallic NPs, one-step technique was employed.
The process was quite simple in the preparation of nanofluids containing oxide NPs like Al2O3, ZnO, MgO, TiO2, and SiO2 NPs. The NPs were obtained commercially and were dispersed into a base fluid in a mixing container. The NPs were deagglomerated by intensive ultrasonication after being mixed with the base fluid, and then the suspensions were homogenized by magnetic force agitation.
Two-step method was used to prepare graphene nanofluids. The first step was to prepare graphene nanosheets. Functionalized graphene was gained through a modified Hummers method as described elsewhere . Graphene nanosheets were obtained by exfoliation of graphite in anhydrous ethanol. The product was a loose brown powder, and it had good hydrophilic nature. The graphene nanosheets could be dispersed well in polar solvents, like DW and EG, without the use of surfactant. For liquid paraffin (LP)-based nanofluid, oleylamine was used as the surfactant. The fixed quality of graphene nanosheets with different volume fractions was dispersed in the base fluids.
Severe aggregation always takes place in the as-prepared CNTs (pristine CNTs: PCNTs) because of the non-reactive surfaces, intrinsic Von der Waals forces, and very large specific surface areas, and aspect ratios . In CNT nanofluid preparations, surfactant addition is an effective way to enhance the dispersibility of CNTs [26-28]. However, surfactant molecules attaching on the surfaces of CNTs may enlarge the thermal resistance between the CNTs and the base fluid , which limits the enhancement of the effective thermal conductivity. The steps involved in the preparation of surfactant-free CNT nanofluids include (1) disentangling the nanotube entanglement and introducing hydrophilic functional groups on the surfaces of the nanotubes by chemical treatments; (2) cutting the treated CNTs (TCNTs) to optimal length by ball milling; and (3) dispersing the treated and cut CNTs into base fluids. CNTs including single-walled CNTs (SWNTs), double-walled CNTs (DWNTs), and multi-walled CNTs (MWNTs) were obtained commercially. Two chemical routes for treating CNTs were used for this study. One is oxidation with concentrated acid, and the other is mechanochemical reaction with potassium hydroxide (KOH). The detailed treatment processes have been described elsewhere [8,30].
Phase transfer method was used to prepare stable kerosene-based Fe3O4 magnetic nanofluid. The first step is to synthesize Fe3O4 NPs in water by coprecipitation. Oleic acid was added to modify the NPs. When kerosene is added to the mixture with slow stirring, the phase transfer process took place spontaneously. There was a distinct phase interface between the aqueous and kerosene. After the removal of the aqueous phase using a pipette, the kerosene-based Fe3O4 nanofluid was obtained .
Nanofluids containing copper NPs were prepared using direct chemical reduction method. Stable nanofluids were obtained with the addition of poly(vinylpyrrolidone) (PVP). The diameters of copper NPs prepared by chemical reduction procedure are in the range of 5-10 nm, and copper NPs disperse well with no clear aggregation .
Surface modification is always used to enhance the dispersibility of NPs in the preparation of nanofluids. For example, diamond NPs (DNPs) were purified and surface modified by acid mixtures of perchloric acid, nitric acid and hydrochloric acid according to the literature  before being dispersed into the base fluids. SiC NPs were heated in air to remove the excess free carbon and their surfaces modified to enhance their dispersibility.
Consideration on the thermal conductivity measurement
Inconsistent experimental results and controversial arguments arise unceasingly from different groups conducting research on nanofluids, indicating the complexity of the thermal transport in nanofluids. Through an investigation, a large degree of randomness and scatter have been observed in the experimental data published in the open literature. Given the inconsistency in the data, it is impossible to develop a convincing and comprehensive physical-based model that can predict all the trends. To clarify the suspicion on the scattered and wide-ranging experimental results of the thermal conductivity obtained by different groups, it is preferred to screen the measurement technique and procedure to guarantee the accuracy of the obtained results.
Several researchers observed the “time-dependent characteristic” of thermal conductivity [34-36], that is to say, thermal conductivity was the highest right after nanofluid preparation, and then it decreased considerably with elapsed time. We believe that the “time-dependent characteristic” does not represent the essence of thermal conduction capability of nanofluids. The following two factors may account for this phenomenon. The first one is the motion of the remained particle caused by the agitation during the nanofluid preparation. To make a nanofluid homogeneous and long-term stable, it is always subjected to intensive agitation including magnetic stirring and sonication to destroy the aggregation of the suspended NPs. In very short time after nanofluid preparation, the NPs still keep moving in the base fluid (different from Brownian motion). The motion of the remained particle would cause convection and enhance the energy transport in the nanofluids. Second, when a nanofluid is subjected to long-time sonication, its temperature would be increased. The temperature goes down gradually to the surrounding temperature (thermal conductivity measurement temperature). In very short time after the sonication stops, the process has been remaining. Although the temperature decrease is not severe, the thermal conductivity obtained is very sensitive to the temperature decrease when the transient hot-wire technique is used to measured the thermal conductivity. In our measurements, this phenomenon would be observed. When measuring the thermal conductivity at an unequilibrium state, it was found that the measured data might be very different for a nanofluid even at a specific temperature (see 25°C) if the process to reach this temperature is different. If the temperature is increasing, then the datum obtained of the thermal conductivity would be lower than the true value. While the temperature is decreasing, the datum obtained of the thermal conductivity would be higher than the true value. Therefore, keeping a nanofluid stable and initial equilibrium is very important to obtain accurate thermal conductivity data in measurements.
A transient short hot-wire method was used to measure the thermal conductivities of the base fluids (k0) and the nanofluids (k). The detailed measurement principle, procedure, and error analysis have been described in . In our measurements, a platinum wire with a diameter of 50 μm was used for the hot wire, and it served both as a heating unit and as an electrical resistance thermometer. The platinum wire was coated with an insulation layer of 7-μm thickness. Initially the platinum wire immersed in media was kept at equilibrium with the surroundings. When a regulation voltage was supplied to initiate the measurement, the electrical resistance of the wire changed proportionally with the rise in temperature. The thermal conductivity was calculated from the slope of the rise in the wire’s temperature against the logarithmic time interval. The uncertainty of this measurement is estimated to be within ± 1.0%. A temperature-controlled bath was used to maintain different temperatures of the nanofluids. Instead of monitoring the temperature of the bath, a thermocouple was positioned inside the sample to monitor the temperature on the spot. When the temperature of the sample reached a steady value, the authors waited for further 20 min to make sure that the initial state is at equilibrium. At every tested temperature, measurements were made three times and the average values were taken as the final results. A 20-min interval was needed between two successive measurements. After the above-mentioned careful check on the measurement condition and procedure, the authors could gain confidence on the experimental results.
Influencing factors of thermal conductivity enhancement
In the experiment of the study, it was found that the thermal conductivity enhancements of nanofluids might be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The effects of these factors are presented in this section.
The idea of nanofluid application originated from the fact that the thermal conductivity of a solid is much higher than that of a liquid. For example, the thermal conductivity of the most used conventional heat transfer fluid, water, is about 0.6 W/m · K at room temperature, while that of copper is higher than 400 W/m · K. Therefore, particle loading would be the chief factor that influences the thermal transport in nanofluids. As expected, the thermal conductivities of the nanofluids have been increased over that of the base fluid with the addition of a small amount of NPs. Figure 1 shows the enhanced thermal conductivity ratios of the nanofluids with NPs at different volume fractions [7,8,38-42]. (k - k0)/k0 and φ refer to the thermal conductivity enhancement ratio of nanofluids and the volume fraction of NPs, respectively, in this article. Figure1a presents oxide nanofluids, while Figure 1b presents nonoxide nanofluids. The results show that all the nanofluids have noticeable higher thermal conductivities than the base fluid without NPs. In general, the thermal conductivity enhancement increases monotonously with the volume fraction. For the graphene nanofluid with a volume fraction of 0.05, the thermal conductivity can be enhanced by more than 60.0%. There is an approximate linear relationship between the thermal conductivity enhancement ratios and the volume fraction of graphene nanosheets. The nanofluids containing graphene nanosheets show larger thermal conductivity enhancement than those containing oxide NPs. It demonstrates that graphene nanosheet is a good additive to enhance the thermal conductivity of base fluid. However, the enhancement ratios of nanofluids containing graphene nanosheets are less than those of CNTs with the same loading. Many factors have direct influence on the thermal conductivity of the nanofluid. One of the important factors is the crystal structure of the inclusion in the nanofluid. Graphene is a one-atom-thick planar sheet of sp2-bonded carbon atoms that are densely packed in a honeycomb crystal lattice. The perfect structure of graphene is damaged when graphite is chemically oxidized by treatment with strong oxidants. There is no doubt that the high thermal conductivity is diminished by defects, and the defects have direct influence on the heat transport along the 2-D structure.
Figure 1. Thermal conductivity enhancement ratios of the nanofluids as a function of nanoparticle loading. (a) Oxide nanofluids: MgO-EG ; Al2O3-EG ; ZnO-EG ; (b) Nonoxide nanofluids: CNT-EG ; DNP-EG ; Graphene-EG ; Cu-EG .
Some studies have demonstrated that the temperature has a great effect on the enhancement of the thermal conductivity for nanofluids. However, there is considerable disagreement in the literature with respect to the temperature dependence of their thermal conductivity. For example, Das et al. reported strong temperature-depended thermal conductivity for water-based Al2O3 and CuO nanofluids . The thermal conductivity enhancements of nanofluids containing Bi2Te3nanorods in FC72 and in oil had been experimentally found to decrease with increasing temperature . Micael et al. measured the thermal conductivities of EG-based Al2O3 nanofluids at temperatures ranging from 298 to 411 K. A maximum in the thermal conductivity was observed at all mass fractions of NPs .
Figure 2 shows our measured temperature-depended thermal conductivity enhancements of nanofluids [8,38-42]. For EG-based nanofluids containing MgO, ZnO, SiO2, and graphene NPs, the thermal conductivity enhancements almost remain constant when the tested temperature changes (see Figure 2a), which means that the thermal conductivity of the nanofluid tracks the thermal conductivities of the base liquid in the experimented temperature range of this study. The thermal conductivity enhancements of DW-EG-based nanofluids containing MgO, ZnO, SiO2, Al2O3, Fe2O3, TiO2, and graphene NPs also appear to have the same behavior. It was further found that kerosene-based Fe3O4 nanofluids presented temperature-independent thermal conductivity enhancements. Patel et al.  reported that the thermal conductivity enhancement ratios of Cu nanofluids are enhanced considerably when the temperature increases. The experimental results of this study shown in Figure 2b demonstrated similar tendency. At 10°C, the thermal conductivity enhancement of EG based Cu nanofluid with 0.5% nanoparticle loading is less than 15.0%. When the temperature is increased to 60°C, the enhancement reaches as large as 46.0%. Brownian motion of the NPs has been proposed as the dominant factor for this phenomenon. For the EG-based CNT nanofluids, cylindrical nanotubes with large aspect ratios were used as additions. The effect of Brownian motion will be negligible. Typical conduction-based models will give (k - k0)/k0, independent of the temperature. However, results shown in Figure 2b illustrate that (k - k0)/k0increases, though not drastically, with the temperature. CNT aggregation kinetics may contribute to the observed differences . It is worthy of bearing in mind that the temperatures of the base fluid and the nanofluid should be the same when compared with the thermal conductivities between them. Comparison of the thermal conductivities between the nanofluid at one temperature and the base at another one is meaningless.
Figure 2. Thermal conductivity enhancement varying with the tested temperatures. (a) Oxide nanofluids: MgO-EG ; ZnO-EG; Graphene-EG ; (b) Nonoxide nanofluids: Cu-EG ; CNT-EG; DNP-EG .
Figure 3 shows the relation between the enhanced thermal conductivity ratios of the nanofluids and the thermal conductivities of the base fluids [7,8,40,41]. It is clearly seen that no matter what kind of nanoparticle was used, the thermal conductivity enhancement decreases with an increase in the thermal conductivity of the base fluid. For pump oil (PO)-based Al2O3 nanofluid with 5.0% nanoparticle loading, the thermal conductivity can be enhanced by more than 38% compared to that of PO. When the base fluid is substituted with water, the thermal conductivity enhancement achieved is only about 22.0% . A greater dramatic improvement in thermal conductivity of CNT nanofluid is seen for a base fluid with lower thermal conductivity. At 1.0% nanoparticle loading, the thermal conductivity enhancements are 19.6, 12.7, and 7.0% for CNT nanofluids in decene, EG, and DW, respectively. No matter what kind of base fluid is used, the thermal conductivity enhancement of CNT nanofluids is much higher than that for Al2O3 nanoparticle suspensions  at the same volume fraction. The reason would lie in the substantial difference in thermal conductivity and morphology between alumina nanoparticle and carbon nanotube.
Figure 3. Thermal conductivity enhancement ratios as a function of the thermal conductivities of the base fluids: Al2O3 NFs ; CNT NFs ; Graphene NFs ; DNP NFs .
Figure 4 presents the thermal conductivity enhancement of the nanofluids as a function of the specific surface area (SSA) of the suspended particles . It is seen that the thermal conductivity enhancement increases first, and then decreases with an increase in the SSA, with the largest thermal conductivity at a particle SSA of 25 m2 · g-1. We ascribe the thermal conductivity change behavior to twofold factors. First, as particle size decreases, the SSA of the particle increases proportionally. Heat transfer between the particle and the fluid takes place at the particle-fluid interface. Therefore, a dramatic enhancement in thermal conductivity is expected because a reduction in particle size can result in large interfacial area. Second, the mean free path in polycrystalline Al2O3 is estimated to be around 35 nm, which is comparable to the size of the particle that was used. The intrinsic thermal conductivity of nanosized Al2O3 particle may be reduced compared to that of bulk Al2O3 due to the scattering of the primary carriers of energy (phonon) at the particle boundary. It is expected that the suspension’s thermal conductivity is reduced with an increase in the SSA. Therefore, for a suspension containing NPs at a particle size much different from the mean free path, the thermal conductivity increases when the particle size decreases because the first factor is dominant. However, when the size of the dispersed NPs is close to or smaller than the mean free path, the second factor will govern the mechanism of the thermal conductivity behavior of the suspension.
Figure 4. Enhanced thermal conductivity ratios as a function of the SSAs: Al2O3-EG ; Al2O3-PO .
Figure 5 depicts the thermal conductivity enhancements of nanofluids containing CNTs with different sizes . The base fluid is DW, and the volume fraction of the CNTs is 0.0054. It is observed from Figure 5 that the thermal conductivity enhancements show differences among these three kinds of nanofluids containing SWNTs, DWNTs, and MWNTs as the volume fraction of CNTs is the same. Two influencing factors may be addressed. The first one is the intrinsic heat transfer performance of the CNTs. It is reported that the thermal conductivity of CNTs decreases with an increase in the number of the nanotube layer. The tendency of the thermal conductivity enhancement of the obtained CNT nanofluids accords with that of the heat transfer performance of the three kinds of CNTs. The second one is the alignment of the liquid molecules on the surface of CNTs. There are greater number of water molecules close to the surfaces of CNTs with smaller diameter due to the larger SSA if the volume fractions of CNTs are the same. These water molecules can form an interfacial layer structure on the CNT surfaces, increasing the thermal conductivity of the nanofluid .
Figure 5. Thermal conductivity enhancements of nanofluids containing CNTs with different sizes: SWNT-DW ; DWNT-DW; MWNT-DW .
In the preparation of nanofluids, solid additives are always subjected to various pretreatment procedures. The initial incentive is to tailor the surfaces of the NPs to enhance their dispersibility, thereby to enhance the stability of the nanofluids. The morphologies would be significantly changed when CNTs were subjected to chemical or mechanical treatments. Theoretical research into the thermal conductivity of composites containing cylindrical inclusions has demonstrated that the morphologies, including the aspect ratio, have influence on the effective thermal conductivity of the composites. Therefore, it can be expected that the thermal conductivity of CNT contained nanofluids would be affected by the pretreatment process.
Figure 6 shows the dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids . From theoretical prediction, the thermal conductivity of a composite increases with the aspect ratio of the included solid particles [49-51]. Intuition suggests that increasing the milling time should therefore decrease (k - k0)/k0 because of the reduced aspect ratio. Figure 6, however, shows clear peak and valley values in the thermal conductivity enhancement with respect to the milling time for all the studied CNT loadings. For nanofluid at a volume fraction of 0.01, the thermal conductivity enhancements present a peak value of 27.5% and a valley value of 10.4% when the milling times are 10 and 28 h, respectively. The maximal enhancement is intriguingly more than two and half times as the minimal one. Interestingly, when further increased the milling time from 28 to 38 h, (k - k0)/k0 increases from the valley value of 10.4 to 12.8%. Though the increment is not pronounced, it illustrates a difference in tendency from that in the milling time range from 10 to 28 h. Temperature-dependent thermal conductivity enhancement data further indicate that, at all the measured temperatures, nanofluid with CNTs milled for 10 h has the largest increment in thermal conductivity. Glory et al.  reported that the enhancement of the thermal conductivity noticeably increases when the nanotube aspect ratio increases. However, the thermal conductivity enhancement behavior of our CNT nanofluid is very different and cannot be explained only by the effect of the aspect ratio.
Figure 6. Dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids .
The above results suggest other dominant factors that have the influence over the thermal conductivity of the CNT nanofluids. The authors proposed that the nonstraightness and the aggregation would play significantly roles. As is known, the walls of CNTs have similar structure of graphene sheet, and the thermal conductivity of CNTs shows greatly anisotropic behavior. Heat transports substantially quicker through axial direction than through radial direction . For a nonstraight CNT, the high thermal anisotropy of CNTs induces a unique property that individual CNTs are nearly perfect one-dimensional thermal passages with negligibly small heat flux losses during long distance heat conductions . For a nonstraight CNT with length L under a two-end temperature difference, the heat flux q goes through a curled passage. This CNT can be regarded as an equivalent straight thermal passage with a distance of Le. The same heat flux q is conducted between the two ends of this straight passage. Obviously, the equivalent length Le depends on the curvature of the actual nanotube in the nanofluid. A concept, straightness ratio η (η = Le/L), can be adopted to describe the straightness of a curled CNT. The lowest straightness ratio arises when a suspended nanotube forms ring closure .
When subjected to ball milling, CNTs were broken and cut short with appropriate average length. The straightness ratio was significantly increased and heat transports more effectively through the CNTs and across the interfaces between the CNT tips and the base fluid, resulting in the highest thermal conductivity enhancement in a nanofluid containing CNTs milled for 10 h. For nanofluids containing relatively straight nanotubes, the influence of the aspect ratio will surpass that of straightness ratio. Therefore, by further treatment on nanotubes with relatively high straightness ratio, the excessive deterioration of the aspect ratio would decrease the thermal conductivity of nanofluids, causing (k - k0)/k0 decrease from 10 to 28 h. Recent theoretical analysis has revealed that the aggregation of nanoparticle plays a significant role in deciding (k - k0)/k0 . Percolation effects in the aggregates, as highly conducting nanotubes touch each other in the aggregate, help in increasing the thermal conductivity. Our experiments demonstrate that aggregates are the dominant appearance of CNTs when the ball-milling time is increased to 38 h. The aggregation accounts for the increment of thermal conductivity enhancement when the ball-milling time is increased from 28 to 38 h. This result implies that the positive influence of the aggregation surpasses the negative influence of the aspect ratio deterioration.
For some nanofluids, the pH values of the suspensions have direct effects on the thermal conductivity enhancement. Figure 7 presents the thermal conductivity enhancement ratios at different pH values [7,40]. The results show that the enhanced thermal conductivity increases with an increase in the difference between the pH value of aqueous suspension and the isoelectric point of Al2O3 particle . When the NPs are dispersed into a base fluid, the overall behavior of the particle-fluid interaction depends on the properties of the particle surface. For Al2O3 particles, the isoelectric point (pHiep) is determined to be 9.2, i.e., the repulsive forces among Al2O3 particles is zero, and Al2O3 particles will coagulate together under this pH value. Therefore, when pH value is equal or close to 9.2, Al2O3 particle suspension is unstable according to DLVO theory . The hydration forces among particles increase with the increasing difference of the pH value of a suspension from the pHiep, which results in the enhanced mobility of NPs in the suspension. The microscopic motions of the particles cause micro-convection that enhances the heat transport process. Wensel’s study showed that the thermal conductivity of nanofluids containing oxide NPs and CNTs with very low percentage loading decreased when the pH value is shifted from 7 to 11.45 under the influence of a strong outside magnetic field .
Figure 7. Thermal conductivity enhancement ratios at different pH values: Al2O3-DW ; DNP-EG .
For DNP-EG nanofluids, it is observed from Figure 7 that the thermal conductivity enhancement increases with pH values in the range of 7.0-8.0. When pH value is above 8.0, there is no obvious relationship between pH value and the thermal conductivity enhancement. In our opinion, the influence of pH value on thermal conductivity is that pH value has a direct effect on the stability of nanofluids. When pH value is below 8.5, the suspension is not very stable, and DNPs are easy to form aggregations. The alkalinity of the solution is helpful to the dispersion and the stability of the nanofluids. In order to verify the above statement, the influence of settlement time on the thermal conductivity enhancement was further investigated. It is found that the thermal conductivity enhancement decreases with elapsed time for DNP-EG nanofluid when pH is 7.0. However, for the stable DNP-EG nanofluids with pH of 8.5, there is no obvious thermal conductivity decrease for 6 months .
Surfactant addition is an effective way to enhance the stability of nanofluids. Kim’s study revealed that the thermal conductivity decreased rapidly for the instable nanofluids without surfactants after preparation. However, no obvious changes in the thermal conductivity of the nanofluids with sodium dodecyl sulfate (SDS) as surfactant were observed even after 5-h settlement . Assael et al. investigated the thermal conductivities of the aqueous suspension of CNTs. When Sodium dodecyl sulfate (SDS) was employed as the dispersant, the maximum thermal conductivity enhancement obtained was 38.0% for a nanofluid with 0.6 vol% CNT loadings . When the surfactant is substituted with hexadecyltrimethyl ammonium bromide (CTAB), the maximum thermal conductivity enhancement obtained was 34.0% for same fraction of CNT loading . Liu et al. reported that the thermal conductivity of carbon nanotube-synthetic engine oil suspensions is higher compared with that of same suspensions without the addition of surfactant. The presence of surfactant as stabilizer has positive effect on the carbon nanotube-synthetic engine oil suspensions.
We used cationic gemini surfactants (12-3(4,6)-12,2Br-1) to stabilize water-based MWNT nanofluids. These surfactants were prepared following the process described in . Figure 8presents the thermal conductivity enhancement ratios of the CNT-contained nanofluids with different surfactant concentrations. The volume fraction of the dispersed CNTs is 0.1%. The critical micelle concentration of 12-3-12, 2Br-1 is reported as 9.6 ± 0.3 × 10-4 mol/l . Ten times critical micelle concentration of 12-3-12, 2Br-1 is 0.6 wt%. Solutions of 12-3-12, 2Br-1 with different concentrations (0.6, 1.8, and 3.6 wt% at room temperature) were selected to prepare CNT nanofluids. It is observed that at all the measured temperatures the thermal conductivity enhancement decreases with the surfactant addition. The surfactant added in the nanofluids acts as stabilizer which improves the stability of the CNT nanofluids. However, excess surfactant addition might hinder the improvement of the thermal conductivity enhancement of the nanofluids.
Figure 8. Thermal conductivity enhancement ratios with different surfactant concentrations.
The effect of the structures of cationic gemini surfactant molecules on the thermal conductivity enhancement is shown in Figure 9. The fractions of the dispersed CNTs and the cationic gemini surfactants is 0.1 vol% and 0.6 wt%, respectively. The spacer chain length of the cationic gemini surfactant increase from 3 methylenes to 6 methylenes. It is seen that the thermal conductivity enhancement ratio increases with the decrease of spacer chain length of cationic gemini surfactant. Zeta potential analysis indicates that the CNT nanofluids stabilized by gemini surfactant with short spacer chain length have better stabilities. Increase of spacer chain length of surfactant might give rise to sediments of CNTs in the nanofluids, resulting in the decrease of thermal conductivity enhancement of the nanofluids.
Figure 9. Effect of surfactant structures on the thermal conductivity enhancement ratio.
Nanofluids have great potential for heat transfer enhancement and are highly suited to application in practical heat transfer processes. This provides promising ways for engineers to develop highly compact and effective heat transfer equipments. More and more researchers have paid their attention to this exciting field. When addressing the thermal conductivity of nanofluids, it is foremost important to guarantee the accuracy in the measurement of the thermal conductivity of nanofluids. Two aspects should be considered. The first one is to prepare homogeneous and long-term stable nanofluids. The second one is to keep the initial equilibrium before measuring the thermal conductivity. In general, the thermal conductivity enhancement increases monotonously with the particle loading. The effect of temperature on the thermal conductivity enhancement ratio is somewhat different for different nanofluids. It is very important to note that the temperatures of the base fluid and the nanofluid should be the same while comparing the thermal conductivities between them. With an increase in the thermal conductivity of the base fluid, the thermal conductivity enhancement ratio decreases. Considering the effect of the size of the inclusion, there exists an optimal value for alumina nanofluids, while for the CNT nanofluid, the thermal conductivity increases with a decrease of the average diameter of the included CNTs. The thermal characteristics of nanofluids might be manipulated by means of controlling the morphology of the inclusions, which also provide a promising way to conduct investigation on the mechanism of heat transfer in nanofluids. The additives like acid, base, or surfactant play considerable roles on the thermal conductivity enhancement of nanofluids.
CNTs: carbon nanotubes; DNPs: diamond NPs; DW: deionized water; DWNTs: double-walled CNTs; EG: ethylene glycol; KOH: potassium hydroxide; LP: liquid paraffin; MWNTs: multi-walled CNTs; NPs: nanoparticles; PVP: poly(vinylpyrrolidone); SDS: sodium dodecyl sulfate; SHW: short hot wire; SSA: specific surface area; SWNTs: single-walled CNTs; THW: transient hot wire; TCNTs: treated CNTs.
The authors declare that they have no competing interests.
HQ supervised and participated all the studies. He wrote this paper. WY carried out the studies on the nanofluids containing copper nanoparticles, graphene, diamond nanoparticles, and several kinds of oxide nanoparticles. YL carried out the studies on the nanofluids containing other oxide nanoparticles. LF carried out the studies on the nanofluids containing carbon nanotubes.
This study was supported by the National Science Foundation of China (50876058), Program for New Century Excellent Talents in University (NCET-10-883), and the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning.
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Langmuir 1991, 7:1072-1075. Publisher Full Text
Huaqing Xie*, Wei Yu, Yang Li and Lifei Chen
School of Urban Development and Environmental Engineering, Shanghai Second Polytechnic University, Shanghai 201209, China
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Nanoscale Research Letters 2011, 6:124 doi:10.1186/1556-276X-6-124
The electronic version of this article is the complete one and can be found online at:http://www.nanoscalereslett.com/content/6/1/124
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© 2011 Xie et al; licensee Springer.
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Tweet Microporous Silica Based Membranes for Desalination Abstract: This review provides a global overview of microporous silica based membranes for desalination via pervaporation with a focus on membrane synthesis and processing, transport mechanisms and current state of the art membrane performance. Most importantly, the recent development and novel concepts for improving the hydro-stability and separating […]
Microporous Silica Based Membranes for Desalination
Abstract: This review provides a global overview of microporous silica based membranes for desalination via pervaporation with a focus on membrane synthesis and processing, transport mechanisms and current state of the art membrane performance. Most importantly, the recent development and novel concepts for improving the hydro-stability and separating performance of silica membranes for desalination are critically examined. Research into silica based membranes for desalination has focussed on three primary methods for improving the hydro-stability. These include incorporating carbon templates into the microporous silica both as surfactants and hybrid organic-inorganic structures and incorporation of metal oxide nanoparticles into the silica matrix. The literature examined identified that only metal oxide silica membranes have demonstrated high salt rejections under a variety of feed concentrations, reasonable fluxes and unaltered performance over long-term operation. As this is an embryonic field of research several target areas for researchers were discussed including further improvement of the membrane materials, but also regarding the necessity of integrating waste or solar heat sources into the final process design to ensure cost competitiveness with conventional reverse osmosis processes.
Keywords: desalination; pervaporation; microporous silica; metal oxide silica; hybrid silica; carbon template silica
Water is essential for life and the rapid increase in the global population, and corresponding urbanization has seen the demand for both the quantity and quality of fresh water increase dramatically. One of the major challenges of the 21st century, if not the most important of all, is water scarcity, with the security of social and economic development of a country closed linked to its water resources. Nearly every industrial sector is dependent upon the availability of water, and water shortages have a resounding impact on all levels of society from the general public to health and politics. Indeed, the major problems encountered by water shortages include drought and famine, loss of production in primary industries, loss of job opportunities, poor health and hygiene as well as an increase in the cost of fresh water. This situation is made more complex by the fact that, according to the World Health Organization, more than 15% of the world’s population have no access to potable water and more than 37% have no access to sanitation . Against this backdrop, desalination is becoming an increasingly important tool in the fight to the global demand for clean water.
Membrane technologies have long been an attractive approach to separation in industry, because they are fast and relatively energy efficient processes. In addition, they frequently offer high operational stability, low operating costs and are simple to integrate and control within larger industrial process trains. Indeed, they have been successfully applied to the desalination industry with such vigor that they have long overtaken traditional thermal processes to become the gold standard . In general, there are three main types of membrane processes that are currently applied including reverse osmosis (RO), membrane distillation (MD) and pervaporation (PV) . RO depends on the ability of the ‘dense’ membrane to repel salt ions whilst allowing the passage of water molecules. The transport is governed by a solution-diffusion mechanism with the driving force being an external pressure difference large enough to overcome the osmotic pressure of the salt water. On the other hand, MD is a thermal process that requires a porous, hydrophobic membrane wherein the passage of water vapour only is permissible. PV, by contrast, uses molecular sieve type of membranes that allows only passage to water molecules but relies on a water vapour pressure difference. Both of these desalination processes require very different types of membranes with vastly different properties and configurations. Currently, there are two main types of membranes for water desalination, namely polymeric (e.g., polyamide-, polysulfone-, polyfurane- and cellulose-based for RO and polytetrafluoroethylene for MD) and inorganic composite or ceramic membranes (alumina-, zirconia-, titania-, zeolite-, silica- and carbon-based). Between these two classes of membranes, polymeric membranes are the most mature and well-established in the desalination industry due to their low cost, manufacturability, simple module design and improved permeability and selectivity [4,5]. However, these membranes suffer from swelling phenomenon, a short life-span due to biofouling as well as poor thermal and chemical resistance .
Inorganic membranes, on the other hand, are more resistant to process conditions. In addition, they are by their very nature, porous and hence desalinate via different transport mechanisms to polymeric membranes, based primarily on their pore size. In particular, zeolites and amorphous silica based membranes are attractive candidates for water desalination due to the advantages of their tunable pore sizes and morphology thereby offering higher selectivity. Furthermore, interest in amorphous silica based membranes is gaining momentum because of their simple fabrication techniques, relatively low cost and excellent molecular sieving properties as demonstrated in studies where they are utilized to separate gas molecules [6–9]. In these cases, microporous silica membranes have molecular-sieving structures with pore sizes on the order of the kinetic diameter of the species to be separated (dp = 3–5 Å) and therefore the membrane acts via PV as selective barrier between the water molecule (dk = 2.6 Å) and the hydrated salt ions (e.g., Na+: dk = 7.2 Å and Cl−: dk = 6.6 Å) [10,11], thus allowing the separation of water and salt. However, due to the amorphous nature of the silica material, when exposed to water the silica matrix may undergo dissolution and/or densification . This is a major problem for using silica based membranes in desalination as the effect decreases the overall separation performance and ultimately the quality of the desalinated water. Therefore, a concerted effort has been devoted to improving the hydro-stability of these membranes for various industrial applications.
Many recent reviews have been published for membrane desalination and desalination technologies which are both exhaustive and comprehensive [2,4,5,13–16]. Amongst them, polymeric membranes and zeolites have played a major role. Thus, the contribution of this review is to cover recent studies of non-crystalline microporous silica based membranes for desalination and the new strategies focusing on improving hydro-stability and membrane properties for potential water desalination applications.
2. Membrane Processing and Transport Mechanisms for Water Desalination
Water desalination is a process in which fresh water is extracted from aqueous solutions such as seawater, brackish water and brine, which contain dissolved salts and other minerals. For water molecules to diffuse through a membrane, a driving force must be established, otherwise water molecules will remain mixed in the aqueous salt solution. The driving force is associated with concentration, pressure and temperature difference between the feed and permeate sides of the membrane. In the case of RO processes, the water molecules must overcome the osmotic pressure to diffuse through dense polymeric membranes. As the osmotic pressure of typical saline solutions ranges from 0.2 MPa to 3 MPa for brackish water to seawater respectively, RO desalination processes are generally pressure intensive with pressures of between 6 MPa and 8 MPa commonly used for seawater applications . In contrast, MD does not attempt to overcome the osmotic pressure and so does not require a pressurised feed, although being a thermal process the water flux is proportional to the vapour pressure difference across the membrane. MD generally uses porous hydrophobic membranes, where pore size ranges between 1 µm and 100 Å, and the water vapour permeating via the pores is subsequently condensed downstream to produce fresh water . MD operates at lower temperatures (up to 70 °C) when compared to conventional thermal process such as multi-stage flash or multi-effect distillation. Finally, the PV process, when applied to desalination, employs molecular-sieving (dp = 3–5 Å) ceramic membranes with a narrow pore distribution smaller than the diameter of the hydrated salt ions (>6 Å). Therefore they have the potential to completely reject salt ions while permitting water molecules to permeate. MD and PV are similar processes that can be chiefly identified by the way in which the membrane functions. If the membrane is simply a support structure that allows a meniscus to form on the feed side and plays no role in separation then the process is MD. If however, the membrane actively participates in the separation process then the process is PV. To further provide clarity between these three membrane processes, Figure 1 shows a diagram as comparison of RO, MD and PV in desalination processes.
Figure 1. Schematic representation of transport mechanism through a membrane via
(A) reverse osmosis, (B) membrane distillation and (C) pervaporation for seawater desalination .
PV is a well-established water separation technique particularly in alcohol dehydration, although under those circumstances dense polymeric membranes are typically employed . In PV separation processes, the transport resistance is governed by the sorption equilibrium and mobility of water molecules in the silica membrane based on a molecular sieving mechanism [3,15,16,19,20]. Therefore, the transport of the larger hydrated salt ions is excluded through the membrane . In a typical PV process, the membrane acts as a molecular scale selective barrier between the two phases which consist of the liquid phase in the feed and the vapour phase in the permeate side. In order to create a driving force, vacuum is applied on the permeate side of the membrane while the feed side is kept at atmospheric pressure and temperature. The water molecules permeate through the membrane to the exclusion of the salt ions, evaporate on the permeate side and are then convectively transported to the condenser. Fundamentally, the condenser functions to reduce the water vapour pressure on the permeate side by changing the water phase from vapour to liquid. This function allows for a steady state driving force to be maintained throughout the PV operation.
Similar to MD, PV can operate in several different arrangements. The most common MD operational arrangements have been well reviewed elsewhere . The most common PV arrangements are shown in Figure 2 to provide context and include: (i) vacuum; (ii) air gap and (iii) sweep flow. PV can operate using any setup that allows a vapour pressure gradient to form but does not allow the permeate to flow back into the feed.
Figure 2. Pervaporation (PV) processes in various operational arrangements.
The PV process variables that are commonly investigated include temperature, pressure, total dissolved solids concentration and the ionic strength of the feed solution. The effect of these variables on water transport through the membrane is measured by two important factors which determine the overall membrane performance: (1) flux of the water and (2) selectivity or rejection of the salt ions. The permeate water is captured in a condenser and the flux (kg m−2 h−1), F, of water during a given period of time is calculated using Equation (1):
where M is the permeate mass (kg), S is the membrane surface area (m2) and t is the testing time (h). The salt rejection (%), R, of the membrane is determined by using Equation (2):
R = (Cf – Cp/ Cf) ×100%
where Cf and Cp are the salt concentrations in the feed and permeate solutions, respectively, measured from solution conductivity. Both of the equations are used prolifically in the literature to provide comparison measure for the overall membrane performance in both MD and PV experiments for water desalination. Based on the theory of MD and PV, the salt rejection should equate to 100% since the salt ions will not vapourise under the typical testing conditions. Instead they will crystallize on the inner surface of the membrane on the permeate side if they also find passage across the membrane. There are several reasons that this could occur, but for silica-based membranes this is primarily the result of imperfections in the top layer as a result of poor membrane preparation or silica disintegration in the aqueous environment. Therefore, several research groups have taken this into account by flushing the permeate salt when determining the overall salt rejection [19,22].
As previously alluded to, amorphous silica membranes present an interesting classification problem for membrane desalination technologies, because despite being porous, the water transport through the membrane cannot be described as a conventional MD. One of the major reasons is that in PV using silica based membranes, the pore sizes are too small to effectively form a meniscus associated with a liquid surface tension as it is the case in MD processes. In this case, the Kelvin equation for the liquid-vapour equilibrium is not applicable, as the pure liquid saturation pressure above a convex liquid surface is essentially the same as the pressure above a flat surface. In other words, the pressure of the water molecules at the pore entrance is possibly the same as in the feed bulk liquid phase (i.e., hydrostatic pressure). Having said that, silica based membranes for PV desalination cannot truly be described as activated transport either, as is the case for these membranes in gas separation . Increasing feed bulk liquid pressure results in almost no water flux changes  as expected because changing the bulk feed pressure has a negligible effect on the vapour pressure of the feed; yet changing the vapour pressure of the feed, by increasing its temperature, delivers water flux improvements. Hence, in this case PV closely complies with Darcy’s law (N = K ΔP°) where the water flux (N) is proportional to the water vapour pressure (ΔP°) and coefficient K, which are in turn temperature dependent. Silica derived membranes are hydrophilic materials and the water transport can be described by a sorption-diffusion mechanism. In the case of silica-based membranes for PV, water molecules must preferentially access the pore entrances of the silica matrix to permeate through the membrane, a surface adsorption process. Hence, the water transport can be summarised in four successive steps, namely, (1) selective surface adsorption from the bulk liquid mixture, (2) selective access of water to the pore entrance at the membrane interface on the feed side, (3) diffusion of water from the feed side to the permeate side, (4) desorption of water into vapour phase at the membrane interface of the permeate side. Therefore, the physico-chemical properties of the silica membranes as well as their interaction with the water molecules are equally influential.
3. Features of Silica Based Membranes for Desalination
3.1. Features of Silica Based Membranes for Desalination
Amorphous silica materials that can be tailored to pore sizes in the range of 3–5 Å are highly suitable for selective membranes in water desalination applications. Several techniques have been widely developed to effectively control the pore size of silica derived membranes, including sol-gel methods [24–31] and chemical vapour deposition (CVD) [32–35]. Although remarkable progress in gas separation applications have been reported using both methods, to date only silica membranes derived via sol-gel processes have been investigated for desalination applications. One of the major reasons is that the sol-gel method is one of the most simple and cost effective routes, which still offers the flexibility to tailor the required porosity. Traditionally, the sol-gel method is a wet chemical process to fabricate metal oxide powders starting from a chemical solution which acts as a precursor for an integrated network (gel). This method is frequently adopted in membrane synthesis or membrane pore modification due to its controllability and homogeneity [24,30,36–38], and it includes various steps such as sol preparation, gel formation, drying and thermal treatment. Many types of silicon alkoxide precursors have been utilized, but the clear majority of research describes work using tetraethoxysilane (TEOS) [39–41]. The sol gel synthesis has been well described in a variety of reference materials , and so briefly it involves the hydrolysis (Equation (3)) and condensation reactions (Equations (4) and (5)) of a metal alkoxides to form a network. In the hydrolysis reaction, the alkoxide groups (OR, where R is an alkyl group, CxH2x+1) are replaced with hydroxyl groups (OH). The silanol groups (Si-OH) are subsequently involved in the condensation reaction producing siloxane bonds (Si-O-Si), alcohols (R-OH) and water. The desired microporous structure of the silica layer is thus partially determined by both the reactivity and the size of the precursors, but also by the appropriate selection of the precursor, water, alcohol and catalyst concentrations.
|≡Si-OR + H2O ↔ ≡Si-OH + ROH
|≡Si-OR + HO-Si≡ ↔ ≡Si-O-Si≡ + ROH
|≡Si-OH + HO-Si≡ ↔ ≡Si-O-Si≡ + H2O
Hydrolysis and condensation reactions are commonly catalysed by the use of a mineral base or acid. In the case of a silicon alkoxide, acidic conditions usually produce sols with fractal-like structures which have been shown to be more favorable for the formation of microporous silica with smaller pore sizes . Indeed, when the fractal dimension of those species is low enough, their interpenetration is not restricted during the gelation stage, which gives rise to the formation of weakly-branched structures with small pores . By contrast, basic conditions will otherwise favour the production of highly branched fractal structures and/or colloidal particles. This leads to the production of networks with larger pore sizes and is generally not used to prepare molecular sieveing silica membranes.
3.2. Membrane Preparation
Silica membranes are ultra-thin films (~250 nm) that are traditionally prepared on top of a support for mechanical strength to form an asymmetric structure (as depicted in Figure 3). The support quality plays a major role in the final morphology of the silica derived films as its homogeneity is fundamental in preparing thin films without defects. To achieve this aim, the substrate must have (i) small pore sizes, (ii) low surface roughness and (iii) low defect or void concentration . Substrates with large pores, voids and rough surfaces tend to induce mechanical stress in the films resulting in micro-cracks or pin-hole defects. In order to overcome support roughness, interlayers with smaller pores sizes are typically employed. According to the literature, only a few combinations of support and interlayers have been explored for silica-based membranes for PV desalination. Indeed, supports prepared from α-Al2O3 powders are currently the substrates of choice due to their high porosity and relatively low cost and high mechanical stability. Mesoporous γ-Al2O3, consisting of much smaller pore sizes of ~4 nm are as used in 2 μm thick intermediate layers, and are able to minimize the defect rate observed . However, γ-Al2O3 exhibits low hydrothermal stability , which is of concern if these materials are to be used in applications containing water vapour. Alternate intermediate layers include silica-zirconia composites developed by Tsuru and co-workers [46,47], which are typically more hydro-stable than γ-Al2O3 layers.
The coating of the substrate (or support) using the sol-gel process can be carried out by dip coating, spin coating and the pendulum method. Due to its flexibility to coat both flat and tubular geometries, in addition to small or large substrates, dip coating has been the preferred process to prepare silica based membranes. Scriven  extensively reviewed the dip coating process and proposed five stages: immersion, start-up, deposition, drainage and evaporation. Upon immersion of a substrate to a silica sol, the sol starts adhering to the surface of the substrate. During the withdrawal step, the sol deposits on the surface of the substrate leading to drainage of excess liquid and evaporation of the sol to forming a gel on the support surface. Brinker et al.  proposed that there is a sequential order of structural development that results from drainage accompanied by solvent evaporation, continued condensation reactions and capillary collapse. According to Brinker et al.  the concentration of the deposited film increases 18–36 fold due to evaporation. This causes the formed film to undergo very fast gelation and drying, thus suggesting structural reorganization of the film matrix.
Figure 3. SEM micrograph of the cross-section of a high quality asymmetric membrane structure—Reproduced by permission of The Royal Society of Chemistry (http://dx.doi.org/10.1039/B924327E) .
The withdrawal speed of the substrate from a sol, in addition to the viscosity of the sol, plays an important role in determining the silica thin film formation. Generally, withdrawal speeds reported by several research groups vary between 1 and 20 cm min−1, whilst prepared sols are diluted with ethanol up to 20 times the original sol volume. In this case (low withdrawal speed and low viscosity), the thickness of a film (h) is proportional to U2/3 (where U is the product of the viscosity and withdrawal speed), in accordance to the Landau and Levich equation . Hence, increasing the speed of withdrawal in the dip coating process will yield thicker films and vice versa. As the production of thicker films tends to lead to cracking upon evaporation and gelation, thinner sols of low viscosity with low withdrawal speeds are preferred.
Upon film coating, the membranes are calcined at high temperatures, generally up to 600 °C, in order to fix the silica structure. Higher temperatures tend to densify the silica film, resulting in extremely low fluxes. The calcination process can lead to thermal stresses between the substrate and the thin silica film, possibly causing film cracking and defects. Hence the heating ramp rate is of considerable importance and is typically low at around 1 °C min−1, although recent developments in rapid thermal processing for silica membranes in other applications are challenging this long held view [53,54]. As the thickness of the silica films are generally in the region of 30–50 nm, and possibly a single film may contain defects caused by either inhomogeneity in the support or interlayers, or calcination stresses, or environmental dust; the dip coating and calcination process is generally repeated at least 2–3 times to produce high quality membranes. As environmental dust affects thin film formation, de Vos and Verweij  demonstrated that the quality of silica membranes was greatly improved by simply coating in a clean room environment.
4. Novel Silica Based Membranes in Desalination
4.1. Hydro-stability and Current Strategies
Owing to the affinity of amorphous silica for water adsorption, silica derived membranes undergo structural degradation when exposed to water, leading to a loss of selectivity . Briefly, silica surface materials are prone to rehydration via a mechanism of physisorption of H2O molecules on silanol groups (Si-OH), followed by reaction with a nearby siloxane (chemisorption) [57,58]. As a result, H2O assists the breakage of siloxane groups, allowing for dissociative chemisorption via the hydrolysis reaction (the reverse of Equation (5)) . Therefore, hydrolysed surface siloxanes may become strained, which act as strong acid–base sites, having a rapid uptake of water and becoming mobile . As the silica seeks to reduce its surface energy under hydrothermal conditions , Duke and co-workers  proposed that the mobile and strained hydrolysed siloxane groups migrate to smaller pores where they undergo re-condensation to block the pore, whilst the larger pores become even larger. Hydro-stability is therefore a serious problem for the deployment of silica based membranes for water desalination. To address this problem, researchers have attempted to modify the surface properties of the silica, to minimize the interaction of water molecules with the membrane structure. A summary of the main strategies employed is displayed in Figure 4.
One strategy to solve this challenging problem is introducing non-covalently bonded, organic templates into the pure silica matrix [62–64]. Indeed, the presence of carbon moieties embedded into the silica framework can prevent the mobility of soluble silica groups under hydrolytic attack and consequently inhibits micropore collapse. This was demonstrated by Duke et al.  who successfully prepared carbonized-template molecular sieve silica membranes (CTMSS) by introducing the ionic surfactant (C6 hexyltriethyl ammonium bromide) during the silica sol synthesis. The carbon moieties trapped in the CTMSS matrix were formed by carbonization of the surfactant under vacuum or an inert atmosphere, leading to a hybrid silica/carbon membrane. Although CTMSS membranes still retained their hydrophilic properties, the resultant membranes showed great potential for attaining hydro-stability without compromising the selectivity for wet gas separation . Based on this approach, CTMSS membranes were subsequently tested for desalination performance, demonstrating high salt rejection from seawater .
In a similar study, Wijaya et al.  investigated the effect of the carbon chain length of ionic surfactants in CTMSS membranes for desalination by preparing sol-gels with hexyltriethyl ammonium bromide (C6), dodecyltrimethyl ammonium bromide (C12) and hexadecyltrimethyl ammonium bromide (C16). It was found that the CTMSS membrane prepared with the surfactant with the longest carbon chain (C16) delivered the highest salt rejection, whilst also given the largest pore volume and surface area, although interestingly, the average pore sizes were similar for the three surfactants used. These results suggest that the embedded carbon has a beneficial role in silica matrices and the amount embedded has a direct impact in terms of desalination performance, since the carbon content of the added surfactant is directly related to the amount of carbon remaining following carbonization. However, if the concentration of ionic surfactants is too high they form micelles  which drastically limits the possibility of using the sol-gel to dip coat substrates. In order to increase the carbon content in the silica framework, Ladewig et al.  proposed the use of a non-ionic surfactant such as a tri-block copolymer like polyethylene glycol–polypropylene glycol–polyethylene glycol (PEG-PPG-PEG), a high molecular weight polymer. Silica samples were mixed with 1–20 wt % PEG-PPG-PEG, and increasing the loading of the tri-block copolymer to 10 wt % effectively doubled the pore volume and surface area compared to pure silica, whilst still maintaining microporosity. Further increases in tri-block copolymer loading to 20 wt % altered the structure of the CTMSS materials to produce mesopores. Of greatest relevance to both the preceding studies and future research directions, the CTMSS membranes prepared with 10 wt % PEG-PPG-PEG (i.e., the highest carbon content sample, whilst still remaining microporous) also delivered high salt rejections and water fluxes.
Figure 4. Schematic representation of various strategies for silica modification.
Another approach to increase the hydrothermal stability of the pure silica membrane is by incorporating terminal methyl groups (≡Si-CH3) via various precursors used during the sol-gel synthesis (Figure 5). This was firstly reported by de Vos et al.  who synthesized methylated silica membranes derived by the copolymerization of TEOS and methyltriethoxysilane (MTES) in the presence of ethanol and water, with an acid catalysis. Again, the membranes were calcined under a non-oxidising environment to retain the carbon moieties in the silica matrix. These membranes showed remarkable stability for alcohol dehydration for 18 months, though severe degradation occurred at testing temperatures of ≥95 °C thereafter . Although the addition of methyl ligand groups to silica rendered hydrophobicity, the counter effect was the formation of larger micropores. Duke et al.  investigated the effect of both methyl ligand and non-ligand C6 surfactant as templates in silica membranes for desalination. They found that the CTMSS membrane outperformed the methylated-silica membrane, suggesting that carbonizing the C6 surfactants led to the formation of smaller pores than the covalently attached methyl groups.
Figure 5. Precursors used for the preparation of pure (TEOS), methylated (MTES) and hybrids (BTESE) silica membranes.
Following on from the methyl ligand work, significant hydrothermal improvement can be achieved when the siloxane bridges (Si-O-Si) are partially replaced by organic bridges (Si-CH2-CH2-Si) such as BTESE in Figure 5. In this method, alkyl groups (ethylene groups in Figure 5) between Si atoms, which cannot be hydrolyzed, can be used as a “spacer” to control the silica network size while minimizing the hydrophilicity of the silica pore surface. The sol synthesis for such membrane layers was first developed by Castricum et al.  and consisted of a two-step acid hydrolysis of BTESE/MTES mixtures. In this work they showed that the durability of the membrane network for the dehydration of n-butanol by PV was greatly improved by incorporating hydrolytically stable organic groups as integral bridging components into the nanoporous silica. These hybrid organosilica membranes were able to withstand long-term PV operation of up to 2 years at 150 °C. Recently, Tsuru et al. reported the potential of such BTESE membranes in RO and PV desalination processes .
Alternate efforts have focused on modifying the silica structure through the addition of metal oxides [73–77]. Recently Lin et al.  reported for the first time the potential of cobalt oxide silica (CoOxSi) membranes for desalination of waters from brackish to brine concentrations. CoOxSi xerogels were synthesised via the sol-gel method using TEOS, cobalt nitrate hexahydrate and hydrogen peroxide, at a range of pH from 3 to 6. The pH was altered by addition of ammonia during the sol-gel process. Initial hydrothermal exposure (<2 days) at 75 °C of xerogels resulted in the reduction of pore volume and surface area, although subsequent exposure proved that the pore structure of the xerogels was no longer significantly altered. The CoOxSi synthesized at pH 5 was the most resistant to the hydrothermal degradation, remaining stable and delivering high salt rejections for 570 hours of testing at temperatures up to 75 °C and NaCl salt concentrations up to 15 wt %.
4.2. Membrane Performance: Effect of Testing Conditions
A summary of the reported membranes performance in term of water flux and salt rejection is listed in Table 1. It must be stressed that comparing these results gives an indication of the general performance only. One should be aware of that these results are dependent upon several parameters related to testing condition including feed concentration, salt used, feed temperature, feed flow rate, cross-flow velocity, permeate vapour pressure and fouling/scaling tendencies. In addition, these listed membranes may have different geometries (flat or tubular and sizes) and architecture (thickness of top film, number interlayers number, porosity and substrate). As such, all these factors play a role in the final performance of the tested membranes.
a Feed pressurizing up to 7 bar and permeate vacuum pumping; b Permeate vacuum pumping, resulting in a pressure difference ΔP across the membrane less than 1bar; * Sea water.
The majority of membranes listed in Table 1 were tested for feed synthetic solutions containing NaCl dissolved in deionised water with concentrations ranging from 0.3 to 3.5 wt % in order to simulate the typical salt concentration of brackish water (0.3–1 wt %) and sea water (3.5 wt %). CTMSS membranes gave similar water fluxes varying from 1.4 to 6.3 kg m−2 h−1 with high salt rejections greater than 84%, depending on the operating conditions. Hybrid membranes (i.e., those prepared with terminal methyl groups or covalently bound carbon bridges) also gave similar water fluxes and salt rejections. The hybrid membranes prepared with BTESE delivered considerable high water fluxes at 34 kg m−2 h−1 at 90 °C and excellent salt rejection 99.9%. However, these membranes were tested at very low salt concentration (NaCl 0.2 wt %) and high feed temperature and when cooler feed temperatures (30 °C) were used, the water fluxes reduced considerably (one order of magnitude). In the only study of its kind so far, CoOxSi based silica membranes were also investigated for brine
processing conditions where the salt concentrations ranged from 7.5 to 15 wt %. In this case, an increase in salt concentration in the feed from 0.3 to 15 wt % resulted in a decline of the permeate flux from 1.8 to 0.55 kg m−2 h−1 at 75 °C. However, despite the high salt feed concentrations, the salt rejection remained high suggesting they were stable under these harsh testing conditions.
Analyzing the results reported in Table 1, the trends are very clear with increasing temperature yielding increased water flux whilst increasing salt concentration results in decreasing water flux. For instance, at 0.3 wt % salt feed concentration, the water flux increased by 77% (from 0.4 to 1.8 kg m−2 h−1) as the feed temperature was raised from 20 °C to 75 °C. This can be explained through the thermodynamics of the system in that as the temperature increases, so does the water vapour pressure in the feed stream, leading to an increase in the driving force for water permeation across the membrane. Likewise the water vapour pressure decreases as a function of the salt concentration, partially explaining the decreased flux observed under seawater and brine feed concentrations. However, the water vapour pressure change as a function of the salt concentration at constant temperature is not large enough to justify the large reduction of flux as reported by several groups in Table 1. For instance, in the case of carbonized template CTMSS (ionic C6), experiment was conducted at a fixed temperature of 20 °C . Indeed, water flux was reduced by more than half (56%) by increasing the feed concentration from 0.3 wt % to 3.5 wt %. In that case, the change in vapour pressure driving force of an ideal salt solution will change from 2.3 kPa to 2.28 kPa, representing a decrease of 0.08%  far smaller than the decline in flux, thus demonstrating that salt and temperature polarization are also likely occurring. In this case a boundary layer of more concentrated salt forms at the membrane surface due to the permeation of water through the membrane being faster than the diffusion for fresh water from the bulk to the membrane surface. Likewise thermal boundary layers can form through the conduction and convection of sensible heat and the transfer of latent heat through the vapourisation of water through the membrane. This phenomenon, along with temperature polarization, is commonly observed for MD processes. Interestingly, temperature polarization, whereby the heat flow across the membrane from conduction and convection is sufficient to reduce the temperature at the membrane surface in comparison to the bulk feed, is the more commonly reported problem . The fact that salt concentration polarization is strongest suggest that (a) the silica-based membrane is more insulating than typical polymeric MD counterparts, and that (b) the cross flow velocities investigated were not sufficient to disturb or reduce the mass transfer boundary layer.
The purity of the water in the permeate stream is a fundamental parameter in terms of potable water. As the salt rejection is generally a ratio of salinities (Equation (2)), a high salt rejection for a high feed salt stream does not necessarily translating into potable water. According to the World Health Organization portable water should have a factor called total dissolved solids (TDS) < 600 ppm with an upper limit of TDS < 1000 ppm . To assess the performance of the membranes in Table 1 in terms of water quality, the permeate water concentration was calculated as shown in Figure 6. All the membranes listed in Table 1 produce good quality drinking water (TDS < 600 ppm) for slightly saline water conditions (0.3 wt %). However, only the CoOxSi silica base membranes were able to meet the requirement of 600 ppm for seawater and brine feed conditions. For those membranes with TDS in excess of 600 or 1000, a second pass becomes necessary to achieve potable water requirements. As discussed previously the theory of PV operation necessitates that the permeate stream should be free of salt, regardless of the feed conditions.
The observation that the vast majority of silica-based membranes tested under PV desalination conditions do not give pure water in the permeate stream is strong evidence that research focusing on improving the hydro-stability of the silica as well as the integrity of the membrane layer itself should continue to receive high priority. However, only a handful of authors have reported preliminary stability measurements as listed in Table 1. In the longest performance evaluation reported so far, Lin et al. sequentially tested cobalt oxide silica (CoOxSi) membranes with solutions containing salt at 1 wt % (288 h), 3.5 wt % (144 h), 7.5wt % (72 h) and 15 wt % (72 h), leading to a total of 575 hours . Despite a significant variation in water flux observed during the first 120 h, the water flux tended to stabilize after 5 days of measurement. This was attributed to initial textural and/or structural changes in the CoOxSi matrix and was also observed in nitrogen sorption and FTIR analyses. However, this long term testing successfully demonstrated the improved hydro-stability of CoOxSi membranes at several temperature points and feed concentrations. In the only other studies reported thus far, Duke et al. reported stable performance over 5 h of the CTMSS (Ionic 6) membrane ; and Ladewig et al. showed stable performance over 12 h, suggesting the benefit of the carbonized templating method to improve the hydro-stability of amorphous silica membranes .
Figure 6. Comparison of water quality in the permeate stream.
4.3. Future Challenges
Silica based membranes for desalination applications are still at the embryonic stages of research and development. Therefore, this type of membrane requires significant improvements to be able to compete against both alternate membranes and alternate technologies. Indeed, the RO process using polymeric membranes is now a mature technology, having undergone major research, development and deployment in the last 30 years. This developmental advantage implies that RO will continue to dominate the large desalination plants around the world. However, RO cannot process all feed concentrations, in particular the pressure requirements for brine processing are prohibitive and can even destroy the polymeric membranes. Thus silica based membranes (especially metal oxide silica membranes, such as CoOxSi) operating under PV conditions, could have a niche market in the processing of brines or even the processing or drying of mineral salts such as potash or lithium brines.
In order to be able to compete against polymeric RO membranes, the water fluxes of silica based membranes for processing seawater (NaCl 3.5 wt %) must be significantly increased, by an order of magnitude on average. At the moment high water fluxes in excess of 20 kg m−2 h−1 have been demonstrated for BTESE silica membranes only, although only for slightly saline feed concentrations (NaCl 0.2 wt %) and high temperatures at 90 °C. This raises the second major impediment to silica based membrane PV, the issue of temperature, and ultimately energy consumption. PV is a thermal process and raising the temperature of feed translates into higher vapour pressures which should likewise increase water flux and water production. The problem here is that heat must be generated to increase the temperature of the water (and ultimately vapourise it), which together with the energy required to condense the water vapour explains why the PV process uses more energy per liter of water produced than RO processes which use only pump energy to pressurize the saline water feed. If this heat is supplied through conventional means, the cost will be prohibitive. However, there are several options available to reduce the cost of energy by utilising waste heat from industrial sites and thermal power plants, salt gradient solar ponds or solar heat [80–84]. These options may be attractive to deploy PV using silica based membranes.
A vital aspect of any membrane technology is long term operation and stability. At the moment, CoOxSi silica membranes have demonstrated stability up to 575 hours of operation. Similar tests must also be undertaken for CTMSS and hybrid silica based membranes to show proof of concept. To some extent, the CoOxSi silica membranes showed superior performance than MFI zeolites, which may be viewed as a competing membrane technology. In a recent study, Dobrek and co-workers  reported the dissolution of both S-1 and ZSM-5 top layers in MFI zeolite membranes after 560 hours testing in PV desalination. This was attributed to the combined effects of ion exchange and water dissolution mechanisms. The loss of membrane performance due to the quality of the saline waters can therefore cause deterioration of the materials such as in zeolite membranes, or fouling and scaling as is the case of polymeric membranes . Currently, there is no fouling work reported for silica based membranes mainly due to the embryonic nature of the testing which has occurred under laboratory conditions using synthetic salt solutions. Given the scale of the problem for RO membranes, this is a problem that will require substantial research to ensure that silica based membranes can be deployed in an industrial context to process saline waters to potable quality.
Microporous silica based membranes have been shown to provide excellent molecular sieving properties for gas separation applications but their reported use in water treatment processes, such as desalination, have been limited, primarily due to the lack of stability when exposed to water. However, innovative concepts have been developed in the last two decades to realize the potential of silica based membranes for desalination via PV. In particular, research into silica based membrane desalination has focussed on three distinct methods of stabilising the structure including carbon templated silica, hybrid organic-inorganic silica and metal oxide silica. Whilst these methods have all been successfully trialed for desalination via PV, only metal oxide silica membranes have demonstrated significant potential with high salt rejections under all feed concentrations, reasonable fluxes and unaltered performance for over 575 hours of operation. Indeed they were the only membranes capable of producing potable water from highly concentrated brine feed streams. The target areas of research for membrane scientists is therefore on the materials development to further improve water fluxes (in order to compete with RO processes), to stabilize the silica structure to ensure no reductions in long term performance and to produce defect-free membranes to ensure high salt rejections, at low cost. The final challenge for the membrane research community is to establish the conditions under which PV desalination using silica based membranes is most technically and economically viable. The energy requirements of PV systems are considerable in comparison to RO processes and analysis of the thermodynamics indicates that parity will never be reached when utilizing primary energy sources. However, if PV processes are successfully integrated with waste heat or solar heat sources then the technology may be attractive for niche applications such as brine processing or salt recovery. Regardless, the separation and purification of potable water from desalination is a paramount task which the membrane research community must endeavour to address before water supply becomes a global crisis.
Muthia Elma specially thanks for the scholarship provided by the University of Queensland. The authors acknowledge financial support from the Australian Research Council (DP110101185). Simon Smart also acknowledges funding support from the Australian Research Council (DP110103440).
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Muthia Elma, Christelle Yacou, David K. Wang, Simon Smart and João C. Diniz da Costa *
Films and Inorganic Membrane Laboratory, School of Chemical Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia; E-Mails: firstname.lastname@example.org (M.E.); email@example.com (C.Y.); firstname.lastname@example.org (D.K.W.); email@example.com (S.S.)
* Author to whom correspondence should be addressed; E-Mail: firstname.lastname@example.org; Tel.: +62-7-33656960; Fax: +62-7-33654199.
© 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
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TweetSustainability in Water Supply Sustainable water systems should provide adequate water quantity and appropriate water quality for a given need, without compromising the future ability to provide this capacity and quality. Water systems in the realm of sustainable development may not literally include the use of water, but include systems where the use of water […]
Sustainability in Water Supply
Sustainable water systems should provide adequate water quantity and appropriate water quality for a given need, without compromising the future ability to provide this capacity and quality. Water systems in the realm of sustainable development may not literally include the use of water, but include systems where the use of water has traditionally been required. Examples include waterless toilets and waterless car washes, whose use helps to alleviate water stress and secure a sustainable water supply.
Accessing the sustainability features in water supply, that is to say, the three-fold goals of economic feasibility, social responsibility and environmental integrity, is linked to the purpose of water use. Sometimes, these purposes compete when resources are limited; for example, water needed to meet the demands of an increasingly urban population and those needs of rural agriculture. Water is used (1) for drinking as a survival necessity, (2) in industrial operations (energy production, manufacturing of goods, etc.), (3) domestic applications (cooking, cleaning, bathing, sanitation), and (4) agriculture. Sustainable water supply is a component of integrated water resource management, the practice of bringing together multiple stakeholders with various viewpoints in order to determine how water should best be managed. In order to decide if a water system is sustainable, various economical, social and ecological considerations must be considered.
Surface freshwater is unfortunately limited and unequally distributed in the world. Almost 50% of the world’s lakes are located in Canada alone (UNEP, 2002). In addition, pollution from various activities leads to surface water that is not drinking quality. Therefore, treatment systems (either large scale or at the household level) must be put in place.
Structures such as dams may be used to impound water for consumption. Dams can be used for power generation, water supply, irrigation, flood prevention, water diversion, navigation, etc. If properly designed and constructed, dams can help provide a sustainable water supply. The design should consider peak flood flows (historical and projected for climate change), earthquake faults, soil permeability, slope stability and erosion, silting, wetlands, water table, human impacts, ecological impacts (including wildlife), compensation for resettlement, and other site characteristics. There are various challenges that large-scale dam projects may present to sustainability: negative environmental impacts on wildlife habitats, fish migration, water flow and quality, and socioeconomic impacts resulting from resettled local communities. A sustainability impact assessment should therefore be performed to determine the environmental, economic and social consequences of the construction.
Groundwater accounts for greater than 50% of global freshwater; thus, it is critical for potable water (Lozan et al, 2007). Groundwater can be a sustainable water supply source if the total amount of water entering, leaving, and being stored in the system is conserved. There are three main factors which determine the source and amount of water flowing through a groundwater system: precipitation, location of streams and other surface-water bodies, and evapotranspiration rate; it is thus not possible to generalize a sustainable withdrawal or pumping rate for groundwater (USGS, 1999). Unsustainable groundwater use results in water-level decline, reduced streamflow, and low water quality, jeopardizing the livelihood of effected communities. Various practices of sustainable groundwater supply include changing rates or spatial patterns of ground-water pumpage, increasing recharge to the ground-water system, decreasing discharge from the groundwater system, and changing the volume of groundwater in storage at different time scales (USGS, 1999). A long-term vision is necessary when extracting groundwater since the effects of its development can take years before becoming apparent. It is important to integrate groundwater supply within adequate land planning and sustainable urban drainage systems.
Collecting water from precipitation is one of the most sustainable sources of water supply since it has inherent barriers to the risk of over-exploitation found in surface and groundwater sources, and directly provides drinking water quality. However, rainwater harvesting systems must be properly designed and maintained in order to collect water efficiently, prevent contamination and use sustainable treatment systems in case the water is contaminated. A number of drinking water treatments exist at point-of-use, each with advantages and disadvantages. These include solar treatment, boiling, using filters, chlorination, combined methods such as filtration and chlorination, flocculation and chlorination. Although technically given the Earth’s surface and precipitation, rainwater harvesting can meet global water demand, the solution can most practically be a supplement to sustainable water supply systems given a level of uncertainty (especially with climate change), and competing land-use applications.
Reclaimed water, or water recycled from human use, can also be a sustainable source of water supply. It is an important solution to reduce stress on primary water resources such as surface and groundwater. There are both centralized and decentralized systems which include greywater recycling systems and the use of microporous membranes. Reclaimed water must be treated to provide the appropriate quality for a given application (irrigation, industry use, etc.). It is often most efficient to separate greywater from blackwater, thereby using the two water streams for different uses. Greywater comes from domestic activities such as washing, whereas blackwater contains human waste. The characteristics of the two wastestreams thus differ.
Desalinisation has the potential to provide an adequate water quantity to those regions that are freshwater poor, including small island states. However, the energy demands of reverse osmosis, a widely-used procedure used to remove salt from water, are a challenge to the adaptation of this technology as a sustainable one. The costs of desalination average around 0.81 USD per cubic meter compared to roughly 0.16 USD per cubic meter from other supply sources (USGS, 2010). If desalination can be provided with renewable energies and efficient technologies, the sustainable features of this supply source would increase. Currently, desalination increases operational costs because of the needed energy (and also carbon dioxide emissions); this in turn raises the cost of the final product. In addition, desalination plants can have negative impacts on marine life, and cause water pollution due to the chemicals used to treat water and the discharge of brine.
Bottled water is a 21st century phenomenon whereby mostly private companies provide potable water in a bottle for a cost. In some areas, bottled water is the only reliable source of safe drinking water. However, often in these same locations, the cost is prohibitively expensive for the local population to use in a sustainable manner. Bottled water is not considered an “improved drinking water source” when it is the only potable source available (UN, 2010). When sustainability metrics are used to access bottled water, it falls short in many situations of being a sustainable water supply. Economic costs, pollution associated with its manufacturing (plastic, energy, etc.) and transportation, as well as extra water use, makes bottled water an unsustainable water supply system for many regions and for many brands. It takes 3-4 liters of water to make less than 1 liter of bottled water (Pacific Institute, 2008).
Potable water requires some of the strictest standards of quality in terms of bacteriological and chemical pollutants. These standards are often governed by national governments; international recommendations can be found from the World Health Organization (http://www.who.int/water_sanitation_health/dwq/guidelines/en/index.html). Drinking water must be freshwater and should be free of pathogens and free of harmful chemicals.
Water in Industry
Water is used in just about every industry. Industrial water withdrawls represent 22% of total global water use (significant regional differences). Its use is notable for manufacturing, processing, washing, diluting, cooling, transporting substances, sanitation needs within a facility, incorporating water into a final product, etc. (USGS, 2010). The food, paper, chemicals, refined petroleum, and primary metal industries use large amounts of water (USGS, 2010). A sustainable water supply in industry involves limiting water use through efficient appliances and methods adapted to the particular industry. Rainwater harvesting on-site (including the creation of large pond-like structures), as well as recycling water in industrial processes, can provide a sustainable water supply for industry without straining municipal water supplies. Industry releases organic water pollutants, heavy metals, solvents, toxic sludge, and other wastes into water supply sources. Industry thus has a dual responsibility for internal sustainable water supply and the protection of external water supply sources.
Water in Agriculture
Agriculture uses the largest amount of freshwater on a global scale. It represents roughly 70% of all water withdrawal worldwide, with various regional differences. In the United States, for example, agriculture accounts for over 80% of water consumption (USDA, 2010). The productivity of irrigated land is approximately three times greater than that of rain-fed land (FAO, 2010). Thus, irrigation is an important factor for sustainable agriculture systems. In addition, global food production is expected to increase by 60% from 2000 to 2030, creating a 14% increase in water demand for irrigation (UN, 2005). Agriculture is also responsible for some of the surface and groundwater degradation because of run-off (chemical and erosion-based). It thus has a dual role in sustainable water supply: (1) using water efficiently for irrigation and (2) protecting surface and groundwater supply sources. Techniques for sustainable water supply in agriculture include organic farming practices which limit substances that would contaminate water, efficient water delivery, micro-irrigation systems, adapted water lifting technologies, zero tillage, rainwater harvesting, runoff farming, and drip irrigation (efficient method that allows water to drip slowly to plant roots by using pipes, valves, tubes and emitters).
Domestic Water Uses
The average household needs an estimated 20-50 liters of water per person per day, depending on various assumptions and practices (Gleick, 1996). Reducing water use through waterless toilets, water efficient appliances, and water quantity monitoring, is an important part of sustainability for domestic water supply. Efficient piping systems that are leak-free and well insulated provide a network that is reliable and help to limit water waste. The aforementioned potable water supply sources, with their sustainability features and sustainability challenges, are all relevant to other domestic uses. Since water quality standards are not as strict for household uses as for drinking, there is more flexibility when considering sustainable domestic water supply (including the potential for reclaimed water use).
A water supply system will be sustainable only if it promotes efficiencies in both the supply and the demand sides. Initiatives to meet demand for water supply will be sustainable if they prioritize measures to avoid water waste. Avoiding wastage will contribute to reducing water consumption and, consequently, to delaying the need for new resources.
On the supply side, it is fundamental to enhance operation and maintenance capabilities of water utilities, reducing non-revenue water (NRW), leakages, and energy use, as well as improving the capacity of the workforce to understand and operate the system. It is also necessary to ensure cost-recovery through a fair tariff system and “intelligent” investment planning. In addition, all alternatives to increase the water supply must be analysed considering the entire life cycle.
On the demand side, the adoption of water efficient technology can considerably reduce water consumption. Investments in less water intensive industrial processes and more efficient buildings lead to a more sustainable water supply. Concrete possibilities of economic savings, social benefits (such as the involvement of different sectors of society to reach a common objective, environmental awareness of the population, etc.) and a range of environmental gains make the adoption of water efficient technologies viable.
Sustainable water supply involves a sequence of combined actions and not isolated strategies. It depends on the individual’s willingness to save water, governmental regulations, changes in the building industry, industrial processes reformulation, land occupation, etc. The challenge is to create mechanisms of regulation, incentives and affordability to ensure the sustainability of the system.
Food and Agriculture Organization of the United Nations (FAO). (2010). Water Use in Agriculture. Retrieved from http://www.fao.org/ag/magazine/0511sp2.htm
Gleick, Peter H. (1996). Basic Water Requirements for Human Activities: Meeting Basic Needs.” Water International 21, 2: 83-92.
US Geological Survey. (2010). Industrial Water Use. Retrieved from http://ga.water.usgs.gov/edu/wuin.html
United States Department of Agriculture. (2010). Irrigation and Water Use. Retrieved from http://www.ers.usda.gov/Briefing/WaterUse/
Lozan, Grassl, et al. (2007). The water problem of our Earth: From climate and the water cycle to the human right for water.
UN Water for Life Decade. (2005). United Nations Department of Public Information (32948—DPI/2378—September 2005—10M).
UNEP. (2002). Vital Water Graphics: An Overview of the State of the World’s Fresh and Marine Waters. Retrieved from http://www.unep.org/dewa/assessments/ecosystems/water/vitalwater/.
Pacific Institute. Water Content of Things. The World’s Water 2008-2009.
United Nations (WHO and UNICEF). (2010). Progress on Sanitation and Drinking Water Update 2010. Retrieved from http://www.unicef.org/media/files/JMP-2010Final.pdf.
USGS. (2010). Thirsty? How ’bout a cool, refreshing cup of seawater? Retrieved from http://ga.water.usgs.gov/edu/drinkseawater.html.
USGS. (1999). Sustainability of Ground-Water Resources. Retrieved from http://pubs.usgs.gov/circ/circ1186/pdf/circ1186.pdf.
Waite, Marilyn. (2010). Sustainable Water Resources in the Built Environment. IWA Publishing: London.
Many of the issues in this article are covered in the book, Sustainable Water Resources in the Built Environment, published in 2010, written by Marilyn Waite.
Sustainable Water Resources in the Built Environment covers elements of water engineering and policy making in the sustainable construction of buildings with a focus on case studies from Panama and Kenya. It provides comprehensive information based on case studies, experimental data, interviews, and in-depth research.
The book focuses on the water aspects of sustainable construction in less economically developed environments. It covers the importance of sustainable construction in developing country contexts with particular reference to what is meant by the water and wastewater aspects of sustainable buildings, the layout, climate, and culture of sites, the water quality tests performed and results obtained, the design of rainwater harvesting systems and policy considerations.
The book is a useful resource for practitioners in the field working on the water aspects of sustainable construction (international aid agencies, engineering firms working in developing contexts, intergovernmental organizations and NGOs). It is also useful as a text for water and sanitation practices in developing countries.
Technology and Equipment for Water Loss Management – Malcolm Farley, Bambos Charalambous and Stuart Hamilton
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Best Practice Guide on the Control of Arsenic in Drinking Water
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Management of Change in Water Companies – Joaquim Pocas Martins
Publication Date: Jun 2013 – ISBN – 9781843391951
Arsenic in Groundwater: Poisoning and Risk Assessment – M. Manzurul Hassan, Peter J. Atkins
Publication Date: Apr 2013 – ISBN – 9781780400204
Microbial Growth in Drinking Water Distribution Systems – Dirk van der Kooij and Paul W.J.J. van der Wielen
Publication Date: Feb 2013 – ISBN – 9781780400402
Arsenic Contamination in the World – Susan Murcott
Publication Date: Oct 2012 – ISBN – 9781780400389
Internal Corrosion Control of Water Supply Systems – Colin Hayes
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Managing Climate Risk in Water Supply Systems – Casey Brown and M. Neil Ward
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admin 21 Mar, 2013
TweetAbstract Access to safe drinking water is important as a health and development issue at national, regional, and local levels. About one billion people do not have healthy drinking water. More than six million people (about two million children) die because of diarrhea which is caused by polluted water. Developing countries pay a high cost […]
Access to safe drinking water is important as a health and development issue at national, regional, and local levels. About one billion people do not have healthy drinking water. More than six million people (about two million children) die because of diarrhea which is caused by polluted water. Developing countries pay a high cost to import chemicals including polyaluminium chloride and alum. This is the reason why these countries need low-cost methods requiring low maintenance and skill. The use of synthetic coagulants is not regarded as suitable due to health and economic considerations. The present study was aimed to investigate the effects of alum as coagulant in conjunction with bean, sago, and chitin as coagulants on the removal of color, turbidity, hardness, and Escherichia coli from water. A conventional jar test apparatus was employed for the tests. The study was taken up in three stages, initially with synthetic waters, followed by testing of the efficiency of coagulants individually on surface waters and, lastly, testing of blended coagulants. The experiment was conducted at three different pH conditions of 6, 7, and 8. The dosages chosen were 0.5, 1, 1.5, and 2 mg/l. The results showed that turbidity decrease provided also a primary E. coli reduction. Hardness removal efficiency was observed to be 93% at pH 7 with 1-mg/l concentration by alum, whereas chitin was stable at all the pH ranges showing the highest removal at 1 and 1.5mg/l with pH 7. In conclusion, using natural coagulants results in considerable savings in chemicals and sludge handling cost may be achieved.
Alum; Chitin; Sago; Bean; Coagulation; Turbidity
The explosive growth of the world’s human population and subsequent water and energy demands have led to an expansion of standing surface water . Nowadays, the concern about contamination of aquatic environments has increased, especially when water is used for human consumption. About one billion people do not have healthy drinking water. More than six million people (about two million children) die because of diarrhea which is caused by polluted water[2,3].
In most of the cases, surface water turbidity is caused by the clay particles, and the color is due to the decayed natural organic matter. Generally, the particles that determine the turbidity are not separated by settling or through traditional filtration. Colloidal suspension stability in surface water is also due to the electric charge of particle surface. Thus, there is great importance in either the development of more sophisticated treatments or the improvement of the current ones .
The production of potable water from most raw water sources usually entails the use of a coagulation flocculation stage to remove turbidity in the form of suspended and colloidal material. This process plays a major role in surface water treatment by reducing turbidity, bacteria, algae, color, organic compounds, and clay particles. The presence of suspended particles would clog filters or impair disinfection process, thereby dramatically minimizing the risk of waterborne diseases [5,6].
Many coagulants are widely used in conventional water treatment processes, based on their chemical characteristics. These coagulants are classified into inorganic, synthetic organic polymers, and natural coagulants . Alum has been the most widely used coagulant because of its proven performance, cost effectiveness, relatively easy handling, and availability. Recently, much attention has been drawn on the extensive use of alum. Aluminum is regarded as an important poisoning factor in dialysis encephalopathy. Aluminum is one of the factors which might contribute to Alzheimer’s disease [7-9]. Alum reaction with water alkalinity reduces water pH and its efficiency in cold water [10,11]. However, some synthetic organic polymers such as acrylamide have neurotoxicity and strong carcinogenic effect [8,12].
In addition, the use of alum salts is inappropriate in some developing countries because of the high costs of imported chemicals and low availability of chemical coagulants . This is the reason why these countries need low-cost methods requiring low maintenance and skill.
For these reasons, and also due to other advantages of natural coagulants/flocculants over chemicals, some countries such as Japan, China, India, and the United States have adopted the use of natural polymers in the treatment of surface water for the production of drinking water . A number of studies have pointed out that the introduction of natural coagulants as a substitute for metal salts may ease the problems associated with chemical coagulants.
Natural macromolecular coagulants are promising and have attracted the attention of many researchers because of their abundant source, low price, multi-purposeness, and biodegradation[11,14,15]. Okra, rice, and chitosan are natural compounds which have been used in turbidity removal [16-18]. The extract of the seeds has been mentioned for drastically reducing the amount of sludge and bacteria in sewage .
In view of the above discussion, the present work has been taken up to evaluate the efficiency of various natural coagulants on the physico-chemical contaminant removal of water. To date, most of the research has been concentrated on the coagulant efficiencies in synthetic water, but in this study, we move ahead making an attempt to test the efficiency of the natural coagulants on surface water. The efficiencies of the coagulants as stated by  might alter depending on many factors: nature of organic matter, structure, dimension, functional groups, chemical species, and others.
Natural coagulants and their preparation
Sago is a product prepared from the milk of tapioca root. Its botanical name is ‘Manihot esculentaCrantz syn. M. utilissima’. Hyacinth bean with botanical name Dolichos lablab is chosen as another coagulant. Both the coagulants were used in the form of powders (starches). Starch consists mainly of a homopolymer of α-D-glucopyranosyl units that comes in two molecular forms, linear and branched. The former is referred to as amylose and the latter as amylopectin . These have the general structure as per  (Figure 1) .
Figure 1. General structure of amylose and amylopectin.
The third coagulant was chitin ([C8H13O5N]n), which is a non-toxic, biodegradable polymer of high molecular weight. Like cellulose, chitin is a fiber, and in addition, it presents exceptional chemical and biological qualities that can be used in many industrial and medical applications. The two plant originated coagulants were taken in the form of powder or starch. Chitin was commercially procured.
The first stage included testing the efficiency of the four coagulants on the synthetic waters. Synthetic waters with turbidity of 70 and 100 nephelometric turbidity units (NTU) were prepared with fuller’s earth in the laboratory and were used in this part of the study. The experiment was carried out using a jar test apparatus. The experiments were conducted in duplicates to eliminate any kind of error. Efficiency was evaluated by determination of reduction in turbidity of both the synthetic samples.
In the second stage of the experiment, the individual coagulants were evaluated for their efficiency on the surface waters. The water samples for this stage and the preceding stage were collected from the surface reservoir, Mudasarlova, located at a distance of 5 km from the Environmental Monitoring Laboratory, GITAM University, where the experiments were carried out. This is the reservoir which serves as a source of domestic water for the nearby residents.
Care was taken while collecting the samples so that a representative sample is obtained. All samples were collected in sterile plastic containers. The samples were transported to the laboratory, and all the experiments were conducted within a duration of 24 h. The physical parameters like temperature and color were noted at the point of sample collection. The water samples were analyzed for the following parameters pre- and post-treatment with the coagulants (Table 1).
Table 1. Physico-chemical parameters tested (stage II)
The coagulants were tested at various concentrations like 0.5, 1, 1.5, and 2 mg/l at three pH ranges of 6, 7, and 8.
The results obtained from the second stage of the study have encouraged us to further extend the study in terms of blended coagulants. The blending of coagulants was taken up from the fact that alum was the most widely used coagulant, and hence, it was taken as one part. The remaining combinations were 2, 3, 4, and 5 parts of the natural coagulants, i.e., 1:2, 1:3, 1:4, and 1:5.
Testing of the following parameters was adopted for evaluating the efficiency of the blended coagulants (pre- and post-coagulation) (Table 2). All the analysis has been performed as per the standard methods given by APHA, 2005 .
Table 2. Physico-chemical parameters tested (stage III)
E. coli presence
The E. coli bacterial presence and absence were determined in the pre- and post-coagulated water using H2S strip bottle. The water sample was filled into the bottle and allowed to stand for 24 h at room temperature. After 24 h, the water sample was observed for color change; black color change indicates the presence of E. coli.
Coagulant actions onto colloidal particles take place through charge neutralization of negatively charged particles. If charge neutralization is the predominant mechanism, a stochiometric relation can be established between the particles’ concentration and coagulant optimal dose.
In the initial stage of the experiment, the coagulants were tested against synthetic turbid samples with 70 and 100 NTU. According to Figure 2a,b, the optimum dosage of alum was observed to be 1mg/l for both the turbid samples, and the optimum pH is observed to be 7.
Figure 2. Turbidity removal efficiency of alum with initial turbidities of (a) 100 and (b) 70 NTU.
It is understood from Figure 3a,b that the optimum dosage for chitin as coagulant is 1.5 mg/l (turbidity to 40 NTU) for 100 NTU, whereas not much difference was observed between pH 7 and 8 for both the turbid samples. The optimum pH is observed to be 7 for both 70 and 100 NTU samples.
Figure 3. Turbidity removal efficiency of chitin with initial turbidities of (a) 100 and (b) 70 NTU.
Figure 4a,b exemplifies the trends of sago on the turbidity removal of the synthetic solutions. It is observed that sago was effective at both 1 and 1.5 mg/l (turbidity reduced to 50 and 45 NTU, respectively) for 100 NTU solution, and the efficiency was stable at pH 7 and 8.
Figure 4. Turbidity removal efficiency of sago with initial turbidities of (a) 100 and (b) 70 NTU.
Figure 5a,b illustrates the effect of bean on the synthetic turbid samples and turbidity removal. It is observed that bean was effective at 1mg/l (turbidity reduced to 55 NTU) for 100 NTU solution, and the efficiency was stable at pH 7 and 8.
Figure 5. Turbidity removal efficiency of bean with initial turbidities of (a) 100 and (b) 70 NTU.
Implications from the stage 1 experiment articulate that the coagulants are quite stable at the pH ranges tested; hence, in the proceeding experiments, all the three pH ranges were considered. In the second stage of experiment, the environmental samples from the surface water source were collected and tested for the removal of turbidity and other chemical parameters. The dosages were the same as the previous stage. The results are graphically represented as shown in Figures 6, 7,8, 9.
Figure 6. Turbidity removal efficiency of individual coagulants.
Figure 7. Total hardness removal efficiency of individual coagulants.
Figure 8. Calcium hardness removal efficiency of individual coagulants.
Figure 9. Chloride removal efficiency of coagulants.
The turbidity removal efficiencies of the individual coagulants are depicted in Figure 6 wherein there was a broad variation among the pH ranges. The maximum reduction was observed with 1 mg/l (87%) of bean at pH 6 followed by 1 mg/l (82%) sago at the same pH. At pH 7, the maximum efficiency was shown by bean with 1.5 mg/l dosage (85.37%) followed by bean and sago with 1 (82.49%) and 1.5 mg/l (82.49%), respectively. Removal efficiencies of 41.46% and 36.59% were reported by 1 mg/l of bean and sago, respectively, at pH 8. The minimum reductions are not reported as there was a negative competence of the coagulants at different doses and pH variations. It can be observed from the graph that there was an increase in the turbidity of the water at these dosages like with 2 g of chitin the turbidity removal was −19.51. In the entire study, the best results were obtained with total hardness removal wherein no negative competence was reported as shown in Figure 7. The utmost removal was observed with 0.5-mg/l (97.67%) sago at pH 7. At pH 6, it was (90.70%) with 1.5 mg/l of bean. At pH 8, the reduction was (93.02%) with 0.5 mg/l of alum. Apart from these, the general observation was that all the coagulants were effective in an average removal of 65% total hardness at all pH variations and doses. The tracking for the least efficiency has showed chitin at pH 6 with 2-mg/l dose (34.88%).
The calcium hardness removal efficiencies are directly proportional with the total hardness removal; the highest removal was recorded by chitin (93.33%) at pH 7 with 1.5-mg/l dose as shown in Figure 8. Removal of 90% is at pH 8 and 7 with 0.5-mg/l alum and 1-mg/l chitin, respectively. Minimum effectiveness was observed by chitin (6.67%) at pH 6 with 2-mg/l dose. On an average, the removal competence was more than 60% with all coagulants at doses at all the pH conditions.
Figure 8 illustrates the chloride removal efficiency of the coagulants tested. The average competence was observed to be 40%. The maximum competence was noted at pH 7 by chitin (83.64%) at 1.5 mg/l followed by sago (81.82%) at 1 mg/l. Indeed at pH 7, the removal was observed to be superior as a whole. Similarly, pH has shown inferior effectiveness in the amputation of chloride. The remarkable point that was noted is that at pH 8, where the removal was superior, the increase in doses of sago and bean (1.5 and 2 mg/l) has shown a depressing outcome.
With the results obtained from the second stage experimentation, the study was carried forward for the evaluation of blended coagulants. From the literature, it was understood that blended coagulants show improved competence than that of the individual ones.
The regular test of turbidity was substituted with conductivity to establish a relation and test the difference with these parameters. The conductivity diminution was observed to be preeminent at the ratio of 1:2 of all the blended coagulants 26.12%, 26.00%, and 21.35% with alum/bean, alum/chitin, and alum/sago, respectively. The highest reduction was observed with alum/sago at pH 8 with 1:2 ratio (32.28%) (Figure 10).
Figure 10. Conductivity removal efficiency of blended coagulants.
The total hardness reduction trend of the blended coagulants was recorded as follows: at pH 7, all combinations of alum/bean have resulted in negative competence. Amputation of 100% was observed with alum/chitin and alum/sago at 1:2 and 1:4 and 1:5 doses, respectively (Figure 11). The overall competence of the alum/chitin and alum/sago were registered to be more than 80%. The calcium hardness efficiencies of the blended coagulants were similar to that of the total hardness. The highest removal efficiency was shown by alum/chitin with 1:5 ratio at pH 7 (Figure 12).
Figure 11. Total hardness removal efficiency of blended coagulants.
Figure 12. Calcium hardness removal efficiency of blended coagulants.
As said earlier, the turbidity was replaced by color determination taking into account the fact that turbidity is directly related to the color. pH 7 has been remarkably effective in the highest removal of color from the water. The blended coagulant alum/sago was found to be very effective with 98% to 100% reduction in color at all the ratios of dosage (Figure 13). The blended coagulants alum/chitin and alum/sago were relatively successful at an average rate of 80% decline in the color at almost all ratios of dosage at pH 7 and 8.
Figure 13. Color removal efficiency of blended coagulants.
Alum/sago blend has a noteworthy effect on the removal of chloride from the water samples in which no negative result was noted. The highest reduction was observed with alum/chitin with dose of 1:5 (85.71%) at pH 7. Indeed, pH 7 can be optimized as perfect pH for this blend as all the ratios of dosages were quite efficient in the removal of chloride (Figure 14).
Figure 14. Chloride removal efficiency of blended coagulants.
Although many studies have used synthetic water in the experiments, this work chose to use raw water collected directly from the surface source. Therefore, it is important to consider that the natural compounds may cause variations in their composition, which interfere in the treatment process. All those factors are taken into account when evaluating the obtained results.
The characteristics of the superficial water used in this study are observed as that the water used has apparent color, turbidity, solids, and amount of compounds with a relatively high absorption in UV (254 nm). It is noticeable that the water has high turbidity and color.
The effectiveness of alum, commonly used as a coagulant, is severely affected by low or high pH. In optimum conditions, the white flocs were large and rigid and settled well in less than 10 min. This finding is in agreement with other studies at optimum pH [24,25]. The optimum pH was 7 and was similar to the obtained results by Divakaran . At high turbidity, a significant improvement in residual water turbidity was observed. The supernatant was clear after about 20-min settling. Flocs were larger and settling time was lower. The results showed that above optimum dosage, the suspensions showed a tendency to restabilize.
The effectiveness of the chitin in the present study in the removal of various contaminants with varied pH individually and also in blended form can be traced to the explanation from the literature that chitin has been studied as biosorbent to a lesser extent than chitosan; however, the natural greater resistance of the former compared to the last, due to its greater crystallinity, could mean a great advantage. Besides, the possibility to control the degree of acetylation of chitin permits to enhance its adsorption potential by increasing its primary amine group density. Recent studies regarding the production of chitin-based biocomposites and its application as fluoride biosorbents have demonstrated the potential of these materials to be used in continuous adsorption processes. Moreover, these biocomposites could remove many different contaminants, including cations, organic compounds, and anions .
Chitosan has high affinity with the residual oil and excellent properties such as biodegradability, hydrophilicity, biocompability, adsorption property, flocculating ability, polyelectrolisity, antibacterial property, and its capacity of regeneration in many applications . It has been used as non-toxic floccules in the treatment of organically polluted wastewater .
The effects of coagulation process on hardness are observed for varying levels of hardness, which resulted in significant decrease of hardness removal. The study correlates with the results obtained by , wherein they had a maximum hardness removal of 84.3% by chitosan in low turbid water with initial hardness of about 204 mg/l as CaCO3.
Several experiments were carried out to determine the comparative performance of chitosan on E. coli in different turbidities. E. coli negative is present in the chitin-treated waters in all of the turbidities. The conclusive evidence was found for the negative influence of chitosan on E. coli. The regrowth of E. coli was not observed in the experiments after 24 h, which was similar to the observations by .
As far as sago is considered, the starch was effective both individually and as blended coagulant. Unlike polyaluminium chloride, the efficiency of the natural coagulants is not affected by pH. The pH increased their efficiency, which is one of the advantages of natural coagulants. The principle behind the efficiency of the sago from the literature can be stated as follows: Sago starch is a natural polymer that is categorized as polyelectrolyte and can act as coagulant aid. Coagulant aid can be classified according to the ionization traits, which are the anions, cations, and amphoteric (with dual charges). Bratskaya et al.  mentioned that among the three groups, cation polymer is normally used to remove adsorbed negatively charged particles by attracting the adsorbed particles through electrostatic force. They discovered that anion polymer and those non-ionized cannot be used to coagulate negatively charged particles.
The chemical oxygen demand (COD) reduction is influenced by the concentration of sago used; the lower the concentration the better the removal of the COD. Using less than 1.50 g L-1, better COD reduction is observed. At this low concentration, settling time did not influence the COD reduction. Similarly, concentration of sago used at lower than 1.50 g L-1 reduced the turbidity in less than 15 min of settling time. Sago concentration higher than 1.50 g L-1 increased the turbidity; however, settling time has an influence on the turbidity reduction at higher sago concentrations. This pattern is congruent with the COD removal .
The sago starch-graft-polyacrylamide (SS-g-PAm) coagulants were found to achieve water turbidity removal up to 96.6%. The results of this study suggest that SS-g-PAm copolymer is a potential coagulant for reducing turbidity during water treatment .
At its optimum concentration, D. lablab seed powder does not affect the pH of the water. Total and calcium hardness remained almost constant and were within acceptable levels according to World Health Organization standards for drinking water. Moreover, coagulation of medium to high turbidity water with D. lablab seed powder with the finest grain size reduced turbidity further. The best performance of the finest seed powder could be due to its large total surface area, whereby most of the water-soluble proteins are at the solid–liquid interface during the extraction process as stated by Gassenschmidtet al. . This might have increased the concentration of active coagulation polymer in the extract, which improved the coagulation process. The coagulant extract from seeds has shown antimicrobial activity in the comparative culture test, which was also observed in the study of Tandonet al. .
D. lablab demonstrated the best performance with turbid water, in which a turbidity removal efficiency of 87% was observed. The restabilization of destabilized colloidal particles, which was associated with higher residual turbidities, occurred at dosages above the optimum. It is commonly observed that particles are destabilized by small amounts of hydrolyzing metal salts and that optimum destabilization corresponds with neutralization of the particles’ charge. Larger amounts of coagulants cause charge reversal so that the particles become positively charged and, thus, restabilization occurs, which results in elevated turbidity levels . It has also been observed that the reduction in turbidity is associated with significant improvements in bacteriological quality. The effect of natural coagulants on turbidity removal and the antimicrobial properties against microorganisms may render them applicable for simultaneous coagulation and disinfection of water for rural and peri-urban people in developing countries .
It is observed that blended coagulants gave utmost efficiency as compared to the traditional alum coagulants. Here in this blending process, we reduce the alum dose up to 80%; thus, we reduce the drawbacks of the alum. Also, we can reduce the cost of the treatment using the natural coagulants instead of the traditional coagulant.
E. coli is the best coliform indicator of fecal contamination from human and animal wastes. E. colipresence is more representative of fecal pollution because it is present in higher numbers in fecal material and generally not elsewhere in the environment . Results showed the absence of E. coli increases with increasing time. A greater percentage of E. coli was eliminated in higher turbidities. The aggregation and, thus, removal of E. coli was directly proportional to the concentration of particles in the suspension. Chitosan and other natural coagulants showed antibacterial effects of 2 to 4 log reductions.
Antimicrobial effects of water-insoluble chitin and coagulants were attributed to both its flocculation and bactericidal activities. A bridging mechanism has been reported for bacterial coagulation by chitosan . Especially with reference to chitosan, molecules can stack on the microbial cell surface, thereby forming an impervious layer around the cell that blocks the channels, which are crucial for living cells . On the other hand, cell reduction in microorganisms, such as E. coli, occurred without noticeable cell aggregation by chitosan.
This indicates that flocculation was not the only mechanism by which microbial reduction occurred. It was found that when samples were stored during 24 h, regrowth of E. coli was not observed for all turbidities. It should be noted that the test water contained no nutrient to support regrowth of E. coli, and chitosan is not a nutrient source for it. Another experiment was designed to check the effect of alum alone. Regrowth of E. coli was not observed for unaided alum after 24 h. The number of E. coli after resuspension of sediment reached to the initial numbers after 24 h and showed that it cannot be inactivated by alum. Such findings have been previously reported by Bina.
Access to clean and safe drinking water is difficult in rural areas of India. Water is generally available during the rainy season, but it is muddy and full of sediments. Because of a lack of purifying agents, communities drink water that is no doubt contaminated by sediment and human feces. Thus, the use of natural coagulants that are locally available in combination with solar radiation, which is abundant and inexhaustible, provides a solution to the need for clean and safe drinking water in the rural communities of India. Use of this technology can reduce poverty, decrease excess morbidity and mortality from waterborne diseases, and improve overall quality of life in rural areas.
The application of coagulation treatment using natural coagulants on surface water was examined in this study. The surface water was characterized by a high concentration of suspended particles with a high turbidity. At a varied range of pH, the suspended particles easily dissolved and settled along with the coagulants added. Research has been undertaken to evaluate the performance of natural starches of sago flour, bean powder, and chitin to act as coagulants individually and in blended form. In all three cases, the main variable was the dosage of the coagulant. The study shows that natural characteristics of starch and other coagulants can be an efficient coagulant for surface water but would need further study in modifying it to be efficient to the maximum. Thus, it can be concluded that the blended coagulants are the best which give maximum removal efficiency in minimum time.
It is chitin and chitosan which can readily be derivatized by utilizing the reactivity of the primary amino group and the primary and secondary hydroxyl groups to find applications in diversified areas. In this work, an attempt has been made to increase the understanding of the importance and effects of chitin at various doses and pH conditions, upon the chemical and biological properties of water. In view of this, this study will attract the attention of academicians and environmentalists.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
International Journal of Energy and Environmental Engineering 2012, 3:29 doi:10.1186/2251-6832-3-29
Department of Environmental Studies, GITAM Institute of Science, GITAM University, Visakhapatnam, Andhra Pradesh 530045, India
The electronic version of this article is the complete one and can be found online at:http://www.journal-ijeee.com/content/3/1/29
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© 2012 Vara; licensee BioMed Central Ltd.