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://18.104.22.168/search?q=cache:tpTXJUjpiHgJ:globe.ucar.edu/trr-
Cleaning off the conductivity probe before testing the water. (Figure 2)
Testing the conductivity of the pond (Figure 3)
Results: Fall (November) : -Quarry Pond:
- .9 mg/L
-McFadden’s Pond (site A)*:
- 3.1 mg/L
-McFadden’s Pond (site B)*:
- 3.05 mg/L
Spring (May): (with ph/conductivity probe) -Quarry Pond:
- .83 mg/L
-McFadden’s Pond (Site A):
- 2.95 mg/L
-McFadden’s Pond (Site B):
- 2.02 mg/L
Spring (May): (LoggerPro Data) -Quarry Pond:
- .8 mg/L
-McFadden’s Pond (Site A):
- 3.1 mg/L
-McFadden’s Pond (Site B):
- 2.1 mg/L
Data Graph for Quarry Pond (Figure 4)
Data Graph for McFadden’s Pond Site A (Figure 5)
Data Graph for McFadden’s Pond Site B (Figure 6)
Data Graph for all three locations (Figure 7)
Discussion: Throughout our research, there was a general shift in the conductivity level in each site we tested. At Quarry Pond, the total dissolved solids reduced from .9 mg/L to .8 mg/L from November to May. This shift can be seen in the graph shown in Figure 4. McFadden’s Pond Site B also showed a substantial shift between the November and May readings, from 3.05 mg/L to 2.1 mg/L, as seen in Figure 6. Despite these significant changes, Site A at McFadden’s Pond did not change. This could potentially be due to its close proximity to moving water. A subtle, unnoticed under-current may have existed which may have caused the water to be mixed, and therefore diluted. The figures for this measurement can be seen in Figure 5.
The changes in conductivity at Quarry Pond may be the result of runoff from the parking lot and the roads in close proximity to it. Quarry Pond, unlike the other locations was close enough to a road that run-off affects the level of total dissolved solids. Although there was a significant change in conductivity between readings, the total dissolved solids were much lower than that of McFadden’s Pond. This may explain why the presence of algae was much higher in Quarry Pond than in McFadden’s Pond. McFadden’s Pond’s conductivity may have been higher due to a larger level of mineral deposits from soil runoff. One possible explanation for this shift in conductivity is the dilution of total dissolved solids in pond water due to rainfall and melting water from snow.
Conclusion: When comparing conductivity of water at a given point of time during the year, it is clear that there are noticeable differences. During the Fall and Winter, when there is more soil and road runoff, the conductivity level is higher. Conversely, during the spring, when there is more rainwater and melted snow and ice to dilute the ponds, the conductivity level drops. This would suggest that during fall and winter, the conditions of the pond are noticeably different. This suggests the possibility that there may be a shift in population from one group of organisms to another on a seasonal basis. Knowledge of these changes may help to explain why animals would migrate to a different habitat during different seasons. Because of the nature of soil runoff and road runoff, the level of Total Dissolved Solids in the water changes on a seasonal basis, and with that, the conductivity changes as well. In conclusion, conductivity does change over time of year in stagnant water, primarily because of external conditions such as runoff and wastewater.
(1)The GLOBE Program, “Electrical Conductivity Protocol.” Hydro-Electrical Conductivity. Ed. UCAR, Colorado State University, NASA.
We used the Power Point file linked to this page as our primary source of background information as well as a standard protocol for our field tests.
(2)Conductivity And Water Quality.
<[[http://kywater.org/ww/ramp/rmcond.htm%3C/span%3E%3Cspan|http://kywater.org/ww/ramp/rmcond.htm<span]] We used this website as our second source of data for finding out environmental impacts of change in conductivity and overall water quality. (Note: No Author, Publisher or Editor could be found for this web page.) __ *Site A is to the right of Mystery Bridge *Site B is to the left of Mystery Bridge *Note, this protocol was implemented both in the field and in a lab dependent on the time the data was collected *If the web page is difficult to view, a link to a .ppt file is available at the top of the page. The protocol can be found on slide #12.
Study authors: Margot Bennett and Rob Schwartz
Contributions to http://d-e-science11.wikispaces.com/ are licensed under a Creative Commons Attribution Share-Alike 3.0 License
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.
Study of Physico-Chemical Characteristics of Wastewater in an Urban Agglomeration in Romania – MyronLMeters.com
TweetStudy of Physico-Chemical Characteristics of Wastewater in an Urban Agglomeration in Romania Abstract This study investigates the level of wastewater pollution by analyzing its chemical characteristics at five wastewater collectors. Samples are collected before they discharge into the Danube during a monitoring campaign of two weeks. Organic and inorganic compounds, heavy metals, and biogenic compounds […]
Study of Physico-Chemical Characteristics of Wastewater in an Urban Agglomeration in Romania
This study investigates the level of wastewater pollution by analyzing its chemical characteristics at five wastewater collectors. Samples are collected before they discharge into the Danube during a monitoring campaign of two weeks. Organic and inorganic compounds, heavy metals, and biogenic compounds have been analyzed using potentiometric and spectrophotometric methods. Experimental results show that the quality of wastewater varies from site to site and it greatly depends on the origin of the wastewater. Correlation analysis was used in order to identify possible relationships between concentrations of various analyzed parameters, which could be used in selecting the appropriate method for wastewater treatment to be implemented at wastewater plants.
Sources of wastewater in the selected area are microindustries (like laundries, hotels, hospitals, etc.), macroindustries (industrial wastewater) and household activities (domestic wastewater). Wastewater is collected through sewage systems (underground sewage pipes) to one or more centralized Sewage Treatment Plants (STPs), where, ideally, the sewage water is treated. However, in cities and towns with old sewage systems treatment stations sometimes simply do not exist or, if they exist, they might not be properly equipped for an efficient treatment. Even when all establishments are connected to the sewage system, the designed capacities are often exceeded, resulting in a less efficient sewage system and occasional leaks.
Studies of water quality in various effluents revealed that anthropogenic activities have an important negative impact on water quality in the downstream sections of the major rivers. This is a result of cumulative effects from upstream development but also from inadequate wastewater treatment facilities. Water quality decay, characterized by important modifications of chemical oxygen demand (COD), total suspended solids (TSSs), total nitrogen (TN), total phosphorous (TP), iron (Fe), nickel (Ni), copper (Cu), zinc (Zn), lead (Pb), and so forth  are the result of wastewater discharge in rivers. Water-related environmental quality has been shown to be far from adequate due to unknown characteristics of wastewater . Thus an important element in preventing and controlling river pollution by an effective management of STP is the existence of reliable and accurate information about the concentrations of pollutants in wastewater. Studies of wastewater in Danube basins can be found, for instance, in central and eastern European countries, but we are not aware of extensive studies of wastewater quality at regional/national level in Romania.
This paper analyses the chemical composition of wastewater at several collectors/stations in an important Romanian city, Galati, before being discharged into natural receptors, which in this case are the Danube and Siret Rivers. No sewage treatment existed when the monitoring campaign took place, except the mechanical separation. The study presented here is part of a larger project aiming at establishing the best treatment technology of wastewater at each station. Presently this project is in the implementation stage at all stations. Possible relationships between concentrations of various chemical residues in wastewater and with pollution sources are also investigated. The study is based on daily measurements of chemical parameters at five city collectors in Galati, Romania, during a two-week campaign in February 2010.
2. Experimental Analysis
2.1. Location of Sampling Sites
Galati-Braila area is the second urban agglomeration in Romania after Bucharest, which is located in Romania at the confluence of three major rivers: Danube, Siret, and Prut. The wastewater average flow is about 100000 m3/day . The drainage system covers an area of 2300 ha, serving approximately 99% of the population (approximately 300000 habitants). The basic drainage system is very old, dating back to the end of the 19th century, and was extended along with the expansion of the city due to demographic and industrial evolution. There are several collectors that collect wastewater and rainwater from various areas with very different characteristics, according to the existing water-pipe drainage system. There is no treatment at any station, except for simple mechanical separation. However, industrial wastewater is pretreated before being discharged in the city system. The five wastewater collectors are denoted in the following as S 1 , S 2 , … , S 5. Four of them discharge in the Danube River and the fifth discharges in the Siret River (which is an affluent of Danube River). Figure 1 shows the distribution of the monitoring sites and highlights the type of collecting area (domestic, industrial, or mixed). For the sake of brevity, these stations will be named in the present paper as “domestic,” “mixed,” and “industrial” stations, according to the type of collected wastewater. The mixture between domestic and industrial water at the two mixed collectors is the result of changes in city planning and various transformations of small/medium enterprises.
Figure 1: Monitoring sampling sites of wastewater from Galati city.
Technical details about each collector/station can be found in Table 1. The first station, S1, collects 10% of the total quantity of wastewater. A high percentage of the water collected at this station comes from domestic sources from the south part of the city (more than 96%). Station S2 collects 64% of the total daily flow of wastewater, out of which 30% comes from domestic sources and the rest (70%) is industrial. Most of the industrial sources in this area are food-production units (milk, braid, wine) while the domestic sources include 20 schools, 4 hospitals, and important social objectives. Station S3 is located in the old part of the city and collects 5% of the total wastewater and has domestic sources. At the fourth station, S4, 11% of the quantity of wastewater is collected from domestic (70%) and industrial (30%) sources. The last collector, S5, collects wastewater from the industrial area of the city, where the most important objectives are a shipyard, metallurgical, and mechanical plants and transport stations.
Table 1: Characteristics of collectors S 1 , … , S 5.
2.2. Physico-Chemical Parameters and Methods of Analysis
The physico-chemical parameters which were measured are the following:(i)pH;(ii)chemical oxygen demand (COD) and dissolved oxygen (DO);(iii)nutrients such as nitrate (N-NO3) and phosphate (P-PO4) (these were included due to their impact on the eutrophication phenomenon);(iv)metals such as aluminum (Al+3), soluble iron (Fe+2), and cadmium (Cd+2).
The pH and DO were determined in situ using a portable multiparameter analyzer. Other chemical parameters such as COD, metals and nutrients were determined according to the standard analytical methods for the examination of water and wastewater .
The COD values reflect the organic and inorganic compounds oxidized by dichromate with the following exceptions: some heterocyclic compounds (e.g., pyridine), quaternary nitrogen compounds, and readily volatile hydrocarbons. The concentration of metals (Al+3, Cd+2, Fe+2) was determined as a result of their toxicity.
The value of pH was analyzed according to the Romanian Standard using a portable multiparameter analyzer, Consort C932.
COD parameter was measured using COD Vials (COD 25–1500 mg/L, Merck, Germany). The digestion process of 3 mL aliquots was carried out in the COD Vials for 2 h at 148°C. The absorbance level of the digested samples was then measured with a spectrophotometer at λ = 605 nm (Spectroquant NOVA 60, Merck, Germany), the method being analogous to EPA methods , US Standard Methods, and Romanian Standard Methods.
The DO parameter was analyzed according to Romanian Standard using a portable multiparameter analyzer, Consort C932.
Aluminum ions (Al+3) were determined using Al Vials (Aluminum Test 0.020–1.20 mg/L, Merck, Germany) in a way analogous to US Standard Methods. The absorbance levels of the samples were then measured with a spectrophotometer (Spectroquant NOVA 60; Merck, Germany) at λ = 550 nm. The method was based on reaction between aluminum ions and Chromazurol S, in weakly acidic-acetate buffered solution, to form a blue-violet compound that is determined spectrophotometrically. The pH of the sample must be within range 3–10. Where necessary, the pH will be adjusted with sodium hydroxide solution or sulphuric acid.
Iron concentration (Fe+2) was determined using Iron Vials (Iron Test 0.005–5.00 mg/L, Merck, Germany) and their absorbance levels were then measured using a spectrophotometer (Spectroquant NOVA 60; Merck, Germany) at λ = 565 nm. The method was based on reducing all iron ions (Fe+3) to iron ions (Fe+2). In a thioglycolate-buffered medium, these react with a triazine derivative to form a red-violet complex which is spectrophotometrically determined. The pH must be within range 3–11. Where necessary the pH was adjusted with sodium hydroxide solution or sulphuric acid.
Cadmium ions (Cd+2) were determined using Cadmium Vials (Cadmium Test 0.005–5.00 mg/L, Merck, Germany), their absorbance levels being measured with a spectrophotometer (Spectroquant NOVA 60; Merck, Germany) at λ = 525 nm. The method was based on the reaction of cadmium ions with a cadion derivative (cadion-trivial name for 1-(4-nitrophenyl)-3-(4-phenylazophenyl)triazene), in alkaline solution, to form a red complex that is determined spectrophotometrically. The pH must be within the range 3–11, and, if not, the pH will be adjusted with sodium hydroxide solution or sulphuric acid.
Nitrogen content was determined using Nitrate Vials (Nitrate Cell test in seawater 0.10–3.00 mg/L NO3-N or 0.4–13.3 mg/L N O3 −, Merck, Germany). The method being based on the reaction of nitrate ions with resorcinol, in the presence of chloride, in a strongly sulphuric acid solution, to form a red-violet indophenols dye that is determined spectrophotometrically. The absorbance levels of the samples were then measured with a spectrophotometer (Spectroquant NOVA 60; Merck, Germany) at λ = 500 nm.
Phosphorous content was determined using Phosphate Vials (Phosphate Cell Test 0.5–25.0 mg/L PO4-P or 1.5–76.7 mg/L P O4 − 3, Merck, Germany) with a method that was analogous to the US Standard Methods . The method was based on the reaction of orthophosphate anions, in a sulphuric solution, with ammonium vanadate and ammonium heptamolybdate to form orange-yellow molybdo-vanado-phosphoric acid that is determined spectrophotometrically (“VM” method). The absorbance levels of the samples were then measured with a spectrophotometer (Spectroquant NOVA 60; Merck, Germany) at λ = 410 nm.
All results were compared with standardized levels for wastewater quality found in accordance with European Commission Directive  and Romanian law .
3. Results and Discussion
3.1. The Acidity (pH)
The results for pH for all the investigated five collectors are shown in Figure 2.
Figure 2: Daily variation of pH at all sites.
Generally, the wastewater collected at the monitored sites is slightly alkaline. The pH varies between 6.8 and 8.3—average value 7.82—thus the pH values are within the accepted range for Danube River according to the Romanian law, which is between 6.5 and 9.0. The pH variation is relatively similar at collectors S1–S4 (domestic and/or mixed domestic-industrial contribution). Lower pH values are observed at S5, which is dominated by industrial wastewater, originating from major enterprises and heavy industry. However, these values are not too low, since usually pH values for industrial wastewater are smaller than 6.5.
A significant decrease in the pH value was observed during the 8th day of the analyzed period at each station. Interestingly, a heavy snowfall took place at that particular time, thus the decrease could be attributed to the mixing between wastewater and a high quantity of low pH water, resulted from the melting of snow . One could speculate that the snowfall, which has an acidic character, might have affected the pH of the wastewater through “run off” phenomena.
No other snowfall took place during the monitoring campaign, thus no definite conclusion can be drawn for a possible relationship between pH and snowfalls.
3.2. Results for Chemical Oxygen Demand (COD)
Detection of COD values in each sampling site of wastewater is presented in Figure 3.
Figure 3: Daily variation of COD at all sites.
All COD values are higher than the maximum accepted values (125 mg O2/L) of the Romanian Law . Both organic and inorganic compounds have an effect on urban wastewater’s oxidability since COD represents not only oxidation of organic compounds, but also the oxidation of reductive inorganic compounds. That means some inorganic compounds interfere with COD determination through the consumption of C r2O7 − 2. Two different behaviors can be observed, which are associated with the type of the collected wastewater as follows.(i)The first group consists of stations S2, S4 and S5 where the wastewater has an important industrial component. At these stations, COD values are approximately between 150 and 300 mg O2/L, smaller, for instance, than COD values found by in the raw wastewater produced by an industrial coffee plant where COD values were between 4000 and 4600 mg O2/L. Also, the temporal variation of COD values at all three stations is similar with no significant deviations from the average value, which is about 250 mg O2/L. Interestingly, the lowest COD level can be seen, on the average, at S5, which has the highest percentage of industrial wastewater. The second group comprises the “domestic” stations S1 and S3. The COD levels are higher, with values of 500 mg O2/L or more. Also, the variability is clearly higher than at the industrial-type stations. No clear association between the variations at the two sites can be seen. A peak in COD was measured in the 14th day of the study at site S1 (1160 mg O2/L). Since S1 is a domestic type station, it is unlikely that some major discharge led to such a high variation of COD. Unfortunately, no other information exists that might indicate a possible cause for this increase.
3.3. Results for Dissolved Oxygen (DO)
The amount of DO, which represents the concentration of chemical or biological compounds that can be oxidized and that might have pollution potential, can affect a sum of processes that include re-aeration, transport, photosynthesis, respiration, nitrification, and decay of organic matter. Low DO concentrations can lead to impaired fish development and maturation, increased fish mortality, and underwater habitat degradation . No standards are given by Romanian or European Law for DO in wastewater. The DO values for the analyzed wastewater at all five sites are shown in Figure 4.
Figure 4: Daily variation of DO at all sites.
Concentration of DO varies at all sampling sites and has values between 0.96 (at S2) and 11.33 (at S4) mg O2/L with a mean value of 6.39 mg O2/L. These are clearly higher than DO values measured, for instance, in surface natural waters in China, where the Taihu watershed had the lowest DO level (2.70 mg/L), while in other rivers DO varied from 3.14 to 3.36 mg O2/L . On the other hand, such high values of DO (9.0 mg O2/L) could be found, for instance, in the Santa Cruz River , who argued that discharging industry and domestic wastewater induced serious organic pollution in rivers, since the decrease of DO was mainly caused by the decomposition of organic compounds. Extremely low DO content (DO < 2 mg O2/L) usually indicates the degradation of an aquatic system .
The DO levels vary similarly for all selected sampling sites. The DO levels cover a wide range, with a minimum value of 1.0 mg O2/L at S1 and S3 and a maximum value of 11.33 mg O2/L at S4. There is a drop in DO at all stations, observed is in the 8th day of the monitoring interval, which coincides with the day when a similar decrease in pH took place. The lowest values of DO are observed for S1, one of the two “domestic” stations. It is interesting to note that DO at S5 is low although the wastewater here comes only from industry sources.
The variation of Al+3, Fe+2, and Cd+2 concentrations in wastewater are shown in Figures 5, 6, and 7. Al+3 concentrations (Figure 5) were mostly within the 0.05–0.20 mg/L range at all the sampling sites. However, during the beginning and the end of the monitoring campaign, Al+3 concentration at station S2 is high (reaching even 0.65 mg/L), nonetheless below the limit imposed by the Romanian law, which is 5 mg/L . The fact that in the beginning of the time interval, the concentration of Al+3 is high at two neighboring stations (S1 and S2) suggests that some localized discharge affecting both runaway and waste water, might have happened in the southern part of the city, which led to the increase of Al+3concentration in the collected wastewater. This is supported by the fact that the concentration gradually decreases at S2.
Figure 5: Daily variation of Al at all sites.
Figure 6: Daily variation of Fe at all sites.
Figure 7: Daily variation of Cd at all sites.
The variation of Fe+2 concentrations is shown in Figure 6. Fe+2 concentration is within the 0.07–0.4 mg/L interval, below 5.0 mg/L, which is the maximum accepted value of the Romanian law . Two higher values were observed at S2 and S4 (both with industrial component) during the third and fourth days of the monitoring campaign.
Besides Al+3 and Fe+2, concentrations of Cd+2 were determined and the variations at the five stations are shown in Figure 7. Cd+2 is a rare pollutant, originating from heavy industry. Leakages in the sewage systems can also lead to Cd+2. Except for two days, Cd+2 varies between 0.005 and 0.04 mg/L. The two high values of 0.11 mg/L were observed in the first and fourth days at S5, which collects industrial wastewater. However, Cd+2 concentrations do not exceed the maximum accepted values of the Romanian law  for the monitoring interval which is 0.2 mg/L.
Water systems are very vulnerable to nitrate pollution sources like septic systems, animal waste, commercial fertilizers, and decaying organic matter . Important quantities of nutrients, which are impossible to be removed naturally, can be found in rivers and this leads to the eutrophication of natural water (like Danube River). As a result, an increase in the lifetime of pathogenic microorganisms is expected. Measurement of nutrient (different forms of nitrogen (N) or phosphorous (P)) variations in domestic wastewater is strongly needed in order to maintain the water quality of receptors . Nitrogen by nitrate (Figure 8) and phosphorous by phosphate (Figure 9) are considered as representative for nutrients.
Figure 8: Daily variation of N-NO3 at all sites.
Figure 9: Daily variation of P-PO4 at all sites.
Figure 8 shows that N-NO3 concentrations vary, on the average, between 0 and 5.0 mg/L.
At all four stations with a domestic component, S1, S2, S3 and S4, the concentration of N-NO3 is low (between 0 and 1.5 mg/L) and the daily variation is relatively similar at all sites. Noticeable drops of the N-NO3 concentration are observed at all stations in the 8th day of the monitoring interval, coinciding with pH (Figure 2) and DO strong variations (Figure 4). This supports the conclusion that the heavy snowfall recorded at that period had an important impact on wastewater quality most likely due to the runoff joining the sewage system.
The behavior of N-NO3 clearly differs at station S5, which collects only industrial wastewater. Significantly higher values of N-NO3, ranging from 2.0 to 5.0 mg/L, were detected. However, the mean concentration of N-NO3 remained below the maximum concentration given by the Romanian law . Obviously, if treatment stations have to be set up, the priority for this particular nutrient component should concentrate on stations where industrial wastewater is collected.
Another nutrient that was analyzed for our study was orthophosphate expressed by phosphorous. The P-PO4 concentration varies, on the average, between 1.0 and 6.0 mg/L (Figure 9). For this component, concentrations are higher at domestic stations, S1 and S3, than at the other three stations. P-PO4 is expected to increase in domestic wastewater because of food, more precisely meat, processing, washing, and so forth. The lowest values were observed at S5, which has a negligible domestic component. Peaks in the P-PO4 concentration are observed at S1. Interestingly enough, P-PO4 temporal variations correlated pretty well at stations S2, S4, and S5 (which collect industrial wastewater). Unlike most of the other analyzed compounds, for which the concentrations were within the accepted ranges, the maximum level of P-PO4 is exceeded at all five collectors. Both Romanian law and the European law stipulate 2.0 mg/L total phosphorous for 10000–100000 habitants, and for more than 100000 habitants (as in Galati City’s case) 1.0 mg/L total phosphorus. Interestingly, domestic stations seem to require more attention with respect to the quality of water then industrial stations.
Our results regarding the variation and levels of the analyzed parameters are grouped below as the following.(1)The values of pH are within the accepted range for Danube, and their daily variations are relatively similar for both domestic and mixed wastewater. Significantly smaller pH values were measured in the wastewater with a high industrial load. A clear minimum was observed at all sites in the 8th day of the monitoring period, when a heavy snowfall took place. One could speculate that the snowfall, which has an acidic character, might have affected the pH of the wastewater through “run off” phenomena. However, a clear connection cannot be established relying on one event only.(2)The COD level clearly depends on the type of wastewater. Higher values were observed for domestic wastewater, while “pure” industrial wastewater has the lowest COD. This might be explained by the fact that industrial wastewater benefits from some treatment before being discharged into the city sewage system. However, COD does exceed the maximum accepted values according to the Romanian law  at all sites thus additional treatment is required at all stations.(3)Concentrations of all analysed metals, Al+3, Cd+2 and Fe+2, are within the limit of the Romanian law. No association with the type of wastewater could be inferred. Isolated peaks could not be linked with any specific polluting factors, except for Cd+2, for which accidental concentration increases are observed for pure industrial wastewater.(4)The level of P-PO4, one of the two nutrients that were analyzed, was high at all stations; however, the highest concentrations are associated with domestic loads.(5)Opposingly, the N-NO3 level is the highest, by far, in wastewater with a high industrial contribution.
3.6. Possible Relationships between Various Parameters
The experimental results have shown that some parameters might be related and that their behavior greatly depends on the type of collected wastewater. Differences between the behavior of physico-chemical parameters at the domestic sites (S1 and S3), on one hand, and at the other sites, on the other, was observed. Pearson correlation coefficients have been calculated between all parameters at all the selected five sites and corresponding significances. Although most of correlations were not significant, some interesting connections between various parameters at sites with similar characteristics were revealed. Table 2 shows correlation coefficients between various parameters for all five stations. Significant correlations at different types of stations are denoted as follows: italicized fonts for domestic stations, boldface italicized fonts for the industrial station and boldface fonts for mixed stations.
Table 2: Correlation coefficients calculated for station S1 to S5. Significant correlations at each type of stations are identified as follows: boldface italicized fonts for industrial station (S5), italicized fonts for domestic stations (S1 and S3) and boldface fonts for mixed stations (S2 and S4).
An important relationship seems to exist between pH and N-NO3 at all stations except for the industrial wastewater collecting site, S5 (i.e., at all stations collecting wastewater resulting from domestic activities). Similarly, pH correlates well with DO at all stations except the industrial one.
COD correlates with two metals, Cd+2 and soluble Fe+2, which is expected , but only at S1 and S3, where the daily variations of the concentration for these two metals (Cd+2 and soluble Fe+2) were similar.
No conclusion can be drawn for the industrial wastewater collector that was analyzed, where both positive and negative correlations were observed. The lack of correlation between the two metals and COD at the industrial wastewater collectors suggests that other processes, that alter the chemical equilibrium between the two chemical compounds, must be taken into account. For example some metals are complexed by organic compounds that are present in the water and the pH values can influence these phenomena.
DO correlates with pH and N-NO3 at all four sampling stations with domestic component (S1–S4) but the relationship vanish at S5 (industrial). There is also a negative correlation between DO and Fe+2 and Cd+2 only for domestic wastewater, which is expected because of the natural oxidation of metals. The correlation vanishes at the other three stations which collect wastewater from industrial areas.
Heavy metals, Fe+2 and Cd+2 correlate only at domestic stations and no relationships can be defined to link the concentration of Al+3 with other components.
The P-PO4 variation is linked to the variation of soluble Fe+2 at the two stations that collect domestic wastewater. Interestingly, these two elements exist together in reductive domestic systems because these are dominated by proteins, lipids, degradation products. This relationship disappears at the other stations, where the industrial load is significant. The other metals, Al+3, seems to be linked with P-PO4at stations S5 and S2, which collect wastewater with the highest industrial load. No link is observed for the rest of stations and for Cd+2 which can be explained by a higher probability of iron (II) orthophosphate to form in wastewater compared to Al+3 or Cd+2 orthophosphates.
Positive correlations can also be seen between P-PO4 and COD for all sampling sites except S1, where the relationship is still positive but less significant. The other nutrient, N-NO3, is anticorrelated with COD but only at S3 and is well correlated with pH and DO at all four stations with domestic component. The only exception is station S5, which collects mostly industrial wastewater.
Concluding, positive correlations were observed between the following parameters.(1)pH and N-NO3 everywhere except “purely” industrial water.(2)COD and soluble Fe+2 at domestic stations.(3)DO and pH, on the one hand, and DO and N-NO3 at domestic stations.(4)P-PO4 and soluble Fe+2 at domestic stations.(5)P-PO4 and COD everywhere, which, taking into account the high level of P-PO4 at domestic stations, might suggest that one important contributor to water quality degradation are household discharges.(6)Al+3 and P-PO4.
In the present paper we have analyzed the daily variation of several physico-chemical parameters of the wastewater (pH, COD, DO, Al+3, Fe+2, Cd+2, N-NO3, and P-PO4) at five collectors that have been characterized as domestic, industrial and mixed, according to the type of collecting area. Different results have been obtained for domestic and industrial wastewater. Most of the chemical parameters are within accepted ranges. Nevertheless, their values as well as their behavior depend significantly on the type of collected wastewater.
The overall conclusion is that wastewater with a high domestic load has the highest negative impact on water quality in a river. On the other hand, industrial wastewater brings an important nutrient load, with potentially negative effect on the basins where it is discharged. Our results suggested that meteorological factors (snow) might modify some characteristics of wastewater, but a clear connection cannot be established relying on one event only.
Significantly smaller pH values were measured in the wastewater with a high industrial load. The COD level clearly depends on the type of wastewater. Higher values were observed for wastewater with domestic sources, while “pure” industrial wastewater has the lowest COD. This might be explained by the fact that industrial wastewater benefits from some treatment before being discharged into the city sewage system. COD does exceed the maximum accepted values according to the Romanian law at all sites thus additional treatment is required at all stations. Accidental increases of Cd+2 concentrations are observed for pure industrial wastewater. The highest concentrations of P-PO4 are associated with domestic loads. Opposing, the N-NO3 level is clearly the highest in wastewater with a high industrial contribution.
Correlation analysis has been used in order to identify possible relationships between various parameters for wastewater of similar origin.
Positive correlations between various physico-chemical parameters exist for the domestic wastewater (DO, pH and N-NO3, on the one hand, and P-PO4, COD and soluble Fe+2, on the other hand). Except for two cases, these relationships break when the industrial load is high. Some of the existing correlations are expected as discussed above, thus any removal treatment should be differentiated according to the type of collector, before discharging it into the natural receptors in order to be costly efficient. Correlations between DO and COD and nutrient load suggest that the most important threat for natural basins in the studied area, are domestic sources for the wastewater.
The different percentages of industrial and domestic collected wastewater vary at each station, which has a clear impact on concentrations of the selected chemical components. Our results show that domestic wastewater has a higher negative impact on water quality than wastewater with a high industrial load, which, surprisingly, seems to be cleaner. This might be related to the fact that most industries are forced, by law, to apply a pretreatment before discharging wastewater into the city sewage system. Industrial wastewater affects the nutrient content of natural water basins. Although the time period was relatively short, our study identified specific requirements of chemical treatment at each station. An efficient treatment plan should take into account the type of wastewater to be processed at each station. Results presented here are linked with another research topic assessing the level of water quality in the lower basin of the Danube before and after implementing the complete biochemical treatment plants.
The work of Catalin Trif was supported by Project SOP HRD-EFICIENT 61445/2009.
Copyright © 2012 Paula Popa 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 – original found here: http://www.hindawi.com/journals/tswj/2012/549028/
TweetHow many of these wastewater treatment technologies are you familiar with? What is the most effective combination of processes? How do you measure results? Who’s doing the best wastewater treatment research? Is this the best way? Or can the processes below be recombined, rethought, and retooled into something better? Activated sludge systems Advanced oxidation process […]
How many of these wastewater treatment technologies are you familiar with? What is the most effective combination of processes?
How do you measure results? Who’s doing the best wastewater treatment research?
Is this the best way? Or can the processes below be recombined, rethought, and retooled into something better?
Activated sludge systems
Advanced oxidation process
Aerobic granular reactor
Aerobic treatment system
API oil-water separator
Bioconversion of biomass to mixed alcohol fuels
Coarse bubble diffusers
Dissolved air flotation
Expanded granular sludge bed digestion
Fine bubble diffusers
Flocculation & sedimentation
Lamella clarifier (Inclined Plate Clarifier) 
Microbial fuel cell
NERV (Natural Endogenous Respiration Vessel)
Parallel plate oil-water separator
Rotating biological contactor
Sedimentation (water treatment)
Sequencing batch reactor
Submerged aerated filter
Upflow anaerobic sludge blanket digestion
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TweetEnvironmental Applications Keeping the water in our lakes, rivers, and streams clean requires monitoring of water quality at many points as it gradually makes its way from its source to our oceans. Over the years ever-increasing environmental concerns and regulations have heightened the need for increased diligence and tighter restrictions on wastewater quality. Control of […]
Keeping the water in our lakes, rivers, and streams clean requires monitoring of water quality at many points as it gradually makes its way from its source to our oceans. Over the years ever-increasing environmental concerns and regulations have heightened the need for increased diligence and tighter restrictions on wastewater quality. Control of water pollution was once concerned mainly with treating wastewater before it was discharged from a manufacturing facility into the nation’s waterways. Today, in many cases, there are restrictions on wastewater that is discharged to city sewer systems or to other publicly owned treatment facilities. Many jurisdictions even restrict or regulate the runoff of storm water — affecting not only industrial and commercial land, but also residential properties as well.
In its simplest form, water pollution management requires impoundment of storm water runoff for a specified period of time before being discharged. Normally, a few simple tests such as pH and suspended solids must be checked to verify compliance before release. If water is used in any way prior to discharge, then the monitoring requirements can expand significantly. For example, if the water is used for once-through cooling, testing may include temperature, pH, total dissolved solids (TDS), chemical oxygen demand (COD), and biochemical oxygen demand (BOD), to name a few.
Once water is used in a process, some form of treatment is often required before it can be discharged to a public waterway. If wastewater is discharged to a city sewer or publicly owned facility, and treatment is required, the quality is often measured and the cost is based not only on the quantity discharged, but also the amount of treatment required. As a minimum requirement suspended solids must be removed. Filtering or using clarifiers often accomplishes such removal. Monitoring consists of measuring total suspended solids (TSS) or turbidity.
If inorganic materials have been introduced into the water, their concentration must be reduced to an acceptable level. Inorganics, such as heavy metals, typically are removed by raising the pH to form insoluble metal oxides or metal hydroxides. The precipitated contaminants are filtered or settled out. Afterward, the pH must be adjusted back into a “normal” range, which often requires continuous monitoring of pH.
Organic materials by far require the most extensive treatment. Many different methods have been devised to convert soluble organic compounds into insoluble inorganic matter. Most of these involve some form of biological oxidation treatment. Bacteria are used to metabolize the organic materials into carbon dioxide and solids, which can be easily removed. To insure that these processes work smoothly and efficiently requires regular monitoring of the health of the biological organisms. The level of food (organic material), nutrients (nitrogen and phosphorous), dissolved oxygen, and pH are some of the parameters that must be controlled. After bio-oxidation the wastewater is filtered or clarified. Often the final effluent is treated with an oxidizing compound such as chlorine to kill any remaining bacterial agents, but any excess oxidant normally must be removed prior to discharge. Oxidation Reduction Potential (ORP)/Redox is ideal for monitoring the level of oxidants before and after removal. The final effluent stream must be monitored to make sure it meets all regulatory requirements.
The monitoring of wastewater pollution does not end there. Scientists are continuously testing water in streams, ground water, lakes, lagoons, and other bodies of water to determine if and what effects any remaining contamination is having on the receiving waters and its associated aquatic life. Measurements may include pH, conductivity, TDS, temperature, dissolved oxygen, TSS and organic levels (COD and BOD).
Environmental testing is not limited to monitoring of wastewater systems. Control of air emissions often includes gas-cleaning systems that involve the use of water. Wet scrubbers and wet electrostatic precipitators are included in this group. A flue gas desulfurization (FGD) system is one type of wet scrubber that uses slurry of lime, limestone, or other caustic material to react with sulfur compounds in the flue gas. The key to reliable operation of these units is proper monitoring of solids levels and pH. After use, the water in these systems must be treated or added to other wastewater from the plant, where it is treated by one of the methods previously discussed.
With proper monitoring, systems that maintain cleaner air and water can be operated efficiently and effectively. Such operation will go a long way toward maintaining a cleaner environment for future generations.
Myron L Meters offers a full line of handheld instruments and in-line monitor/controllers that can be used to measure or monitor many of the parameters previously mentioned. The following table lists some of the model numbers for measuring, monitoring, or controlling pH, conductivity, TDS and ORP. For additional information, please refer to our data sheets or Ask An Expert at MyronLMeters.com.
Note: When using a monitor/controller to measure pH in streams that contain heavy metals, sulfides, or other materials that react with silver, Myron L Meters recommends using a double junction pH sensor with a potassium nitrate (KNO3) reference gel to avoid fouling the silver electrode. See our 720II Sensor Selection Guide for pH and ORP Monitor/controllers for more information.
Ultrameter II 6P
Multi-Parameter: Conductivity, TDS, Resistivity, pH, ORP, Temperature, Free Chlorine (FCE)
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TweetA TDS Meter indicates the Total Dissolved Solids (TDS) of a solution (the concentration of dissolved solids in it). Since dissolved ionized solids such as salts and minerals increase the conductivity of a solution, a TDS meter measures the conductivity of the solution and estimates the TDS from that. Dissolved organic solids such as sugar […]
A TDS Meter indicates the Total Dissolved Solids (TDS) of a solution (the concentration of dissolved solids in it). Since dissolved ionized solids such as salts and minerals increase the conductivity of a solution, a TDS meter measures the conductivity of the solution and estimates the TDS from that.
Dissolved organic solids such as sugar and colloids don’t affect the conductivity of a solution much so a TDS meter does not include them in its reading.
Units of TDS
A TDS meter usually displays TDS in parts per million (ppm). For example, a TDS reading of 1 ppm would indicate there is 1 milligram of dissolved solids in each kilogram of water.
The two chief methods of measuring total dissolved solids are gravimetry and conductivity. Gravimetric methods are the most accurate and involve evaporating the liquid solvent and measuring the mass of residues left. This method is generally the best but time-consuming. If inorganic salts comprise the majority of TDS, gravimetric methods are recommended.
Electrical conductivity of water is directly related to the concentration of dissolved ionized solids in the water. Ions from the dissolved solids in water create the water’s ability to conduct an electrical current, which can be measured using a conventional conductivity meter or TDS meter. When correlated with laboratory TDS measurements, conductivity provides an approximate value for the TDS concentration.
Total Dissolved Solids (TDS) is a measure of the combined content of all inorganic and organic substances contained in a liquid in: molecular, ionized or micro-granular (colloidal sol) suspended form. The operational definition is that the solids must be small enough to survive filtration through a two micrometer sieve. Total dissolved solids are normally discussed only for freshwater systems, as salinity comprises some of the ions constituting the definition of TDS. The principal application of TDS is in the study of water quality for streams, rivers and lakes, although TDS is not generally considered a primary pollutant (e.g. it is not deemed to be associated with health effects) it is used as an indication of aesthetic characteristics of drinking water and as an aggregate indicator of the presence of a broad array of chemical contaminants.
Primary sources for TDS in receiving waters are agricultural and residential runoff, leaching of soil contamination and point source water pollution discharge from industrial or sewage treatment plants. The most common chemical constituents are calcium, phosphates, nitrates, sodium, potassium and chloride, which are found in nutrient runoff, storm water runoff and runoff from snowy climates where road de-icing salts are applied. The chemicals may be cations, anions, molecules or agglomerations on the order of one thousand or fewer molecules, so long as a soluble micro-granule is formed. More exotic and harmful elements of TDS are pesticides arising from surface runoff. Certain naturally occurring total dissolved solids arise from the weathering and dissolution of rocks and soils. The United States has established a secondary water quality standard of 500 mg/l to provide for palatability of drinking water.
TDS Measurement Applications
High TDS levels indicate hard water, which can cause scale buildup in pipes, valves, and filters, reducing performance and adding to system maintenance costs. These effects can be seen in aquariums, spas, swimming pools, and reverse osmosis water treatment systems. Typically, in these applications, total dissolved solids are tested frequently, and filtration membranes are checked in order to prevent adverse effects.
In the case of hydroponics and aquaculture, TDS is often monitored in order to create a water quality environment favorable for organism productivity. For freshwater oysters, trouts, and other high value seafood, highest productivity and economic returns are achieved by mimicking the TDS and pH levels of each species’ native environment. For hydroponic uses, TDS is considered one of the best indices of nutrient availability for the aquatic plants being grown.
Because the threshold of acceptable aesthetic criteria for human drinking water is 500 mg/l, there is no general concern for odor, taste, and color at a level much lower than is required for harm. A number of studies have been conducted and indicate various species’ reactions range from intolerance to outright toxicity due to elevated TDS. The numerical results must be interpreted cautiously, as true toxicity outcomes will relate to specific chemical constituents. Nevertheless, some numerical information is a useful guide to the nature of risks in exposing aquatic organisms or terrestrial animals to high TDS levels. Most aquatic ecosystems involving mixed fish fauna can tolerate TDS levels of 1000 mg/l.
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