Development of Dissolved Oxygen Model for a Highly Variable Flow River: A Case Study of Ravi River in Pakistan

A framework for dissolved oxygen (DO) modeling of the Ravi River has been developed based on a combination of laboratory measurements and field and monitoring data. Both the classical Streeter-Phelps (CSP) and the modified Streeter-Phelps (MSP) models are used for DO simulations. The MSP model considers the carbonaceous biochemical oxygen demand (CBOD) and nitrogenous biochemical oxygen demand (NBOD) separately, whereas the CSP model is evaluated considering only the CBOD and NBOD is incorporated in the overall BOD utilization rate. CBOD, NBOD and BOD rates have been determined through long-term BOD analysis of five main wastewater outfalls and two surface drains discharging into the Ravi River over a 98 km stretch. Analysis by Thomas Method manifests strong coefficient of determination “R²” between 0.72 and 0.98 for all the three types of BOD rates. Sensitivity analyses have also been carried out to find out a suitable reaeration rate formula for highly variable flows in the Ravi River. The CSP model results based on classical approach of considering only CBOD show significant difference between the model predictions and field measurements suggesting that NBOD needs to be incorporated for the model development. The dissolved oxygen values calculated using the MSP model and the CSP model based on overall BOD rate are in close agreement with field measurements and are thus suitable to model DO levels in the Ravi River.     

Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems

This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO₃, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH₃, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH₃, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.     

Analysis of Wet Precipitation of Air Pollutants in Mumbai (India)

Bulk precipitation samples at Mumbai (India) were collectedduring the monsoon seasons of 1991 to 1996 and analysed forionic concentrations using an Ion Chromatograph DIONEX model100. The variability of sulphate to nitrate ratio in rainwaterfluctuates in a wide range from 1.5 to 20 and governed by thesulphate concentrations in the sample. The regression analysisof the data reveals that in the bulk precipitation at Mumbai, SO₄ ^2- is becoming increasingly important relative toNO₃ ^-. The role of meteorological influences onscavenging of air pollutants by rain water has been tried toexplain the phenomena. The computed wet deposition rates for Sand N during 1991–1996 show that the S deposition is higherthan N in all the years. There is a wide fluctuation indeposition rates of S ranging from 2 to 55 kg km² per annum.     

Leachate Characterization and Assessment of Groundwater Pollution Near Municipal Solid Waste Landfill Site

Leachate and groundwater samples were collected from Gazipur landfill-site and its adjacent area to study the possible impact of leachate percolation on groundwater quality. Concentration of various physico-chemical parameters including heavy metal (Cd, Cr, Cu, Fe, Ni, Pb and Zn) and microbiological parameters (total coliform (TC) and faecal coliform (FC)) were determined in groundwater and leachate samples. The moderately high concentrations of Cl⁻, NO⁻ ₃, SO²⁻ ₄, NH⁺ ₄, Phenol, Fe, Zn and COD in groundwater, likely indicate that groundwater quality is being significantly affected by leachate percolation. Further they proved to be as tracers for groundwater contamination. The effect of depth and distance of the well from the pollution source was also investigated. The presence of TC and FC in groundwater warns for the groundwater quality and thus renders the associated aquifer unreliable for domestic water supply and other uses. Although some remedial measures are suggested to reduce further groundwater contamination via leachate percolation, the present study demand for the proper management of waste in Delhi.     

Water Quality Modeling of Municipal Discharges from Sea Outfalls,Mumbai

The island city of Mumbai with a population of about 10 million generates about 2000 million liters per day (mld) of sewage from the seven service areas of the city sewerage network and discharges it into the adjoining west coast and the two creeks in the Arabian Sea. This has resulted in degradation of coastal water quality, contamination of the adjoining beaches and seafronts. The Municipal Corporation of Greater Mumbai has therefore, undertaken the task of delineating appropriate sewage disposal system to achieve cleaner marine ecosystem through marine outfalls at specific locations. This paper presents the results of the mathematical simulations on the impacts of discharge is-a-vis the length of the outfall and level of land treatment apriori. The results of the simulation indicate the level of bacterial pollution to be higher near the diffuser locations as compared to nearshore regions. 48 hsimulation result analysis shows that FC counts nearthe diffuser location will be in the range of 2000–8000 counts per 100 ml.     

Measurement of biochemical oxygen demand of the leachates

Biochemical oxygen demand (BOD) of the leachates originally from the different types of landfill sites was studied based on the data measured using the two manometric methods. The measurements of BOD using the dilution method were carried out to assess the typical physicochemical and biological characteristics of the leachates together with some other parameters. The linear regression analysis was used to predict rate constants for biochemical reactions and ultimate BOD values of the different leachates. The rate of a biochemical reaction implicated in microbial biodegradation of pollutants depends on the leachate characteristics, mass of contaminant in the leachate, and nature of the leachate. Character of leachate samples for BOD analysis of using the different methods may differ significantly during the experimental period, resulting in different BOD values. This work intends to verify effect of the different dilutions for the manometric method tests on the BOD concentrations of the leachate samples to contribute to the assessment of reaction rate and microbial consumption of oxygen.     

Prediction of the effluent from a domestic wastewater treatment plant of CASP using gray model and neural network

When a domestic wastewater treatment plant (DWWTP) is put into operation, variations of the wastewater quantity and quality must be predicted using mathematical models to assist in operating the wastewater treatment plant such that the treated effluent will be controlled and meet discharge standards. In this study, three types of gray model (GM) including GM (1, N), GM (1, 1), and rolling GM (1, 1) were used to predict the effluent biochemical oxygen demand (BOD), chemical oxygen demand (COD), and suspended solids (SS) from the DWWTP of conventional activated sludge process. The predicted results were compared with those obtained using backpropagation neural network (BPNN). The simulation results indicated that the minimum mean absolute percentage errors of 43.79%, 16.21%, and 30.11% for BOD, COD, and SS could be achieved. The fitness was higher when using BPNN for prediction of BOD (34.77%), but it required a large quantity of data for constructing model. Contrarily, GM only required a small amount of data (at least four data) and the prediction results were analogous to those of BPNN, even lower than that of BPNN when predicting COD (16.21%) and SS (30.11%). According to the prediction, results suggested that GM could predict the domestic effluent variation when its effluent data were insufficient.     

Applicability of high rate transpiration system for treatment of biologically treated distillery effluent

The biologically treated distillery effluent (BTDE) contains intense colour, high total dissolved solids (TDS), chemical oxygen demand (COD) and biochemical oxygen demand (BOD). These properties even after primary, secondary and tertiary treatments contain high concentrations of TDS, COD and BOD. The paper highlights the safe disposal and treatment of BTDE on land through High Rate Transpiration System (HRTS). HRTS is a zero discharge, low cost, high-tech method for improving the quality of BTDE for potential reuse. The experiments conducted at bench and pilot scale showed that HRTS having coconut husk as a bedding material could successfully treat the BTDE with a hydraulic load of 200 m³ ha⁻¹ day⁻¹ having BOD of 100 mg l⁻¹ and 500 m³ ha⁻¹ day⁻¹ having BOD of 500 mg l⁻¹ with average COD load of 0.686 and 2.88 ton ha⁻¹ day⁻¹ during the post and pre monsoon periods respectively. There was no significant increase in the organic carbon of the soil irrigated with BTDE. The concentrations of various pollutants analyzed in the leachate were within the prescribed limit for the drinking water sources. The colour removal was 99 to 100% and BOD and COD were possible to treat with optimum hydraulic loading of BTDE through HRTS planted with Dendrocalamus strictus.     

Water Quality Assessment and Modeling of an Effluent-Dominated Stream, the Notwane River, Botswana

In an effort to assess current and future water quality of the only perennial river in southeastern Botswana, this study presents water quality monitoring and modeling results for the effluent-dependent Notwane River. The water quality along the Notwane River, pre- and post-implementation of secondary wastewater treatment, was compared and results demonstrated that water quality improved after the new wastewater treatment plant (WWTP) went online. However, stream standards for chemical oxygen demand, total dissolved phosphorous, and fecal coliform were exceeded in most locations and the critical dissolved oxygen (DO) reached concentrations of less than 4 mg L⁻¹. High dissolved P concentrations and intense macrophyte growth at the impounding ponds and at sites within 30 km of the effluent waste stream confluence suggest that eutrophication was a function of P release from the ponds. Results of DO modeling demonstrated that an unpolluted inflow at approximately 10 km downstream of the confluence was responsible for raising DO concentrations by 2.3 mg L⁻¹, while SOD was responsible for a decline in DO concentrations of 1.4 mg L⁻¹ at 6 km downstream of the confluence. Simulations also showed higher DO concentrations during winter months, when water temperatures were lower. Simulations, in which the distributed biochemical oxygen demand (BOD) loading from cattle excrement was decreased, produced nominal increases in DO concentrations. An increase in WWTP BOD loadings to projected 2020 values resulted in a 1.3 mg L⁻¹ decrease in the critical DO concentration. Furthermore, a decrease in treatment plant efficiency, from 94% to 70% BOD removal, produced critical DO concentrations and anoxia along much of the modeled reach. This has significant implications for Gaborone, especially if decreased WWTP efficiency occurs as a result of the expected future increase in pollutant loadings.     

Optimizing the SO2 total emission control strategy: case study—Bor (Serbia)

Mumbai, a megacity of India, and its adjacent marine environment, though heavily stressed from various anthropogenic interferences, harbor ~146 km² of mangrove cover. Manori creek, in the close vicinity of Mumbai, sustains relatively better mangrove formations. A creek habitat had been evaluated for its biological and environmental characteristics, and is compared with similar but relatively lesser stressed Mandovi estuary (~475 km south of Mumbai). Several evidences of deteriorating environment of Manori creek have been described with respect to Water quality index and various biotic community structures. Water quality index of <55 indicated unacceptable aquatic conditions of Manori creek. Dominance of Avicennia marina and poor abundance and diversity of mangrove and associated biological features indicate highly stressed environment. Dominance of stress-tolerant phytoplankton spp. such as Skeletonema costatum and benthic fauna such as Polychaeta further supported the view. The data presented in the present document would help in developing rational approach towards conservation, protection, and sustainable development of mangrove-dominated creek and estuarine wetlands.     

Ecological study of river Suswa: modeling DO and BOD

In this paper limnological status of river Suswa was observed for a period of two years. A water quality Beck modified Khanna Bhutiani model (BMKB model) was developed to calculate DO (dissolved Oxygen) and BOD (biochemical oxygen demand). The model was developed to calculate DO and BOD by using DO/BOD of same place and upstream in previous season which results in Single output. This model gives the seasonal value on the basis of previously taken upstream and downstream observations/concentrations of DO and BOD. The model was calibrated and verified for the water quality data (Physico-chemical data) of samples collected from river Suswa in different seasons. The model gave good agreement between data observed by it and the data observed manually, thus substantiating the validity of the model. Only minor differences were observed in physical, chemical and heavy metals of all the four sampling stations during the course of study.     

Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff–erosion model in the Mamuaba catchment, Brazil

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha^?1 year^?1; most of the area of the catchment (60 %) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha^?1 year^?1) and, in 20 % of the catchment, the soil erosion was estimated to exceed >?12 t ha^?1 year^?1. Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.     

210-Polonium studies in some environmental and biological matrices of Domiasiat uranium deposit area, West Khasi Hills, Meghalaya, India

The study was performed using a silicon surface barrier alpha spectrometer at Bhabha Atomic Research Centre, Mumbai, India. Through the study, the observed ²¹⁰Po activity in water sample from different locations in the Domiasiat area ranges from 0.04 to 0.69 Bq/l. The daily and annual intake of ²¹⁰Po through water was also estimated and the mean value of 0.72 and 263.61 Bq, respectively, were observed. It is observed that the effective doses through water were higher than the World Health Organization recommended dose of 0.05 mSv/year. The total annual effective doses through terrestrial ingestion for all the locations was studied and the mean annual effective dose was observed to be 0.315 mSv, which, when compared to the worldwide and the Indian values, was observed to be slightly higher. The mean activity in soil is found to be 124.8 ±5.7 Bq/kg and in meat the activity is 0.43 ±0.05 Bq/kg. In fishes, an activity of 0.48 ±0.07 Bq/kg in Garra lamta, 0.29 ±0.02 Bq/kg in Neolissocheilus hexaganolepis, and 3.3 ±0.1 Bq/kg in Macrobrachium sp. is observed. Activity concentration in plant samples was analyzed and the activity ranges from 0.020 ±0.002 to 9.69 ±0.35 Bq/kg. Committed effective dose by the adult population of the Domiasiat area through intake of ²¹⁰Po through these food items was also determined and compared with the Indian average value and the worldwide average value.     

Plastic litter accumulation on high-water strandline of urban beaches in Mumbai, India

Today, almost every beach on every coastline is threatened by human activities. The inadequate recycling and poor management of waste in developing countries has resulted in considerable quantities of plastic contaminating beaches. Though India has long coastline of 5,420 km along the mainland with 43 % of sandy beaches, data on litter accumulation, particularly the plastics, which are one of the most common and persistent pollutants in marine environment, are scanty. The abundance and distribution of plastic litter was quantitatively assessed in four sandy beaches in Mumbai, India, bimonthly from May 2011 to March 2012. Triplicates of 2?×?2 m (4 m²) quadrats were sampled in each beach with a total of 72 quadrats. Overall, average abundance of 11.6 items m^?2 (0.25–282.5 items m^?2) and 3.24 g m^?2 (0.27–15.53 g m^?2) plastic litter was recorded in Mumbai beaches. Plastic litter accumulation significantly varied temporally and spatially at p?=?0.05. Significantly higher plastic litter accumulation was recorded in Juhu beach. Furthermore, the highest abundance by weight was recorded in November and May numerically. More than 80 % of plastic particles were within the size range of 5–100 mm both by number and weight. Moreover, coloured plastics were predominant with 67 % by number of items and 51 % by weight. Probably, the intense use of beaches for recreation, tourism, and religious activities has increased the potential for plastic contamination in urban beaches in Mumbai.     

Using the Flow Cytometry to Quantify the Giardia Cysts and Cryptosporidium Oocysts in Water Samples

The flow cytometry (FC) has been used to detect Giardia cysts and Cryptosporidium oocysts quantitatively and instantaneously in this study. The experimental results showed that FC is potential to become a more precise method for the detection of Giardia and Cryptosporidium in water. This study also evaluated the staining efficiencies for three commercial antibodies. After staining Cryptosporidium oocysts with direct immunofluorescent antibodies in water samples, two populations were detected in the scatter-plots (FL1 versus SSC) of the FC. The Cryptosporidium oocysts and Giardia cysts are significantly separated from other particles while stained with direct immunofluorescent antibodies produced by Meridian Diagnostics and Waterborne^TM Inc.     

Quantitative Analyses of Pollution-Indicator and Pathogenic Bacteria in Mumbai Waters from Ballast Water Exchange Perspective

As large numbers of ships either take in ballast from or discharge their ballast into the Mumbai Harbor region, it is pertinent to quantify microorganisms of health concerns and suggest on the suitability of water for ballasting purposes. To meet with this main aim, a selected set of general and pathogenic bacterial groups and their seasonal variations were studied from the Mumbai Harbor area. Sampling was carried out during postmonsoon (November 2001), pre-monsoon (April 2002) and monsoon (October 2002) periods. We quantified total coliforms and eight other groups of known human pathogenic bacteria from water, sediment, marine plant and animal samples collected in and around Mumbai Harbor. When compared with similar studies from other parts/harbors of the world, the Mumbai Harbor area has over 100-times higher levels of coliforms. The serotypes of Escherichia coli O157 and Shigella-Alkaligens Dispar group were abundant throughout the year. Even Vibrio cholerae, V. parahaemolyticus, Salmonella spp., campylobacters and aeromonads were present in large numbers. This comprehensive study, conducted with a view to quantify these bacterial groups and to evaluate the suitability of these waters for ballasting purposes, clearly suggests that both ballasting and deballasting be avoided in this region and alternative procedures should be developed for treating/handling ballast water.     

Chemometric characterization of river water quality

Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box–whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO ₄ ^2? ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward’s method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson’s correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO ₄ ^2? ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson’s correlation (r) values that indicated significant and positive correlation between variables in the same group. Box–whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO ₄ ^2? ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March–June) and the lowest during monsoon season (July–October). Temperature was the highest in summer and the lowest in winter (November–February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in summer season.     

Predicting field capacity,wilting point,and the other physical properties of soils using hyperspectral reflectance spectroscopy: two different statistical approaches

In this study, we examined the ability of reflectance spectroscopy to predict some of the most important soil parameters for irrigation such as field capacity (FC), wilting point (WP), clay, sand, and silt content. FC and WP were determined for 305 soil samples. In addition to these soil analyses, clay, silt, and sand contents of 145 soil samples were detected. Raw spectral reflectance (raw) of these soil samples, between 350 and 2,500-nm wavelengths, was measured. In addition, first order derivatives of the reflectance (first) were calculated. Two different statistical approaches were used in detecting soil properties from hyperspectral data. Models were evaluated using the correlation of coefficient (r), coefficient of determination (R ²), root mean square error (RMSE), and residual prediction deviation (RPD). In the first method, two appropriate wavelengths were selected for raw reflectance and first derivative separately for each soil property. Selection of wavelengths was carried out based on the highest positive and negative correlations between soil property and raw reflectance or first order derivatives. By means of detected wavelengths, new combinations for each soil property were calculated using rationing, differencing, normalized differencing, and multiple regression techniques. Of these techniques, multiple regression provided the best correlation (P?<?0.01) for selected wavelengths and all soil properties. To estimate FC, WP, clay, sand, and silt, multiple regression equations based on first(2,310)-first(2,360), first(2,310)-first(2,360), first(2,240)-first(1,320), first(2,240)-first(1,330), and raw(2,260)-raw(360) were used. Partial least square regression (PLSR) was performed as the second method. Raw reflectance was a better predictor of WP and FC, whereas first order derivative was a better predictor of clay, sand, and silt content. According to RPD values, statistically excellent predictions were obtained for FC (2.18), and estimations for WP (2.0), clay (1.8), and silt (1.63) were acceptable. However, sand values were poorly predicted (RDP?=?0.63). In conclusion, both of the methods examined here offer quick and inexpensive means of predicting soil properties using spectral reflectance data.     

Microbiological water quality of the Mfoundi River watershed at Yaoundé, Cameroon, as inferred from indicator bacteria of fecal contamination

Using the membrane filtration technique to count total coliform (TC), fecal coliform (FC) and fecal streptococci (FS), the microbiological water quality of the Mfoundi River and four of its representative tributaries at Yaoundé, Cameroon, was assessed for human use and contact. Sampling was conducted so as to examine the potential origin of fecal contamination and how rainfall affects the measured concentrations of indicators organisms. Our results revealed that waters were not safe for human use or primary contact according to the standards for water quality established by the Word Health Organization (WHO). Indeed, these waters exhibited high concentrations of TC (Mean ± SD=5.6 × 10⁸ ± 2.5 × 10⁶ CFU/100 ml), FC (Mean ± SD=6.8 × 10⁵ ± 2.4 × 10³ CFU/100 ml) and FS (Mean ± SD=7.3 × 10⁵ ± 2.1 × 10³ CFU/100 ml) that varied with the sampling sites and points. FC/FS ratio suggested that this contamination was more from warm-blooded animals than humans and correlation analysis points to the role of rainfall as a contributing factor, which enhanced the bacterial numbers detected. We conclude that there is a great potential risk of infection for users of waters from the Mfoundi River and its tributaries at Yaoundé.     

微生物燃料电池型传感器在BOD检测中的应用进展

介绍了微生物燃料电池型BOD传感器的原理与构建方式,分析了影响响应时间、电池转化率、稳定性等性能的因素,指出微生物燃料电池型BOD传感器响应时间短,适用范围广,稳定性好,操作简单,能实现BOD实时在线检测,提出构建低成本、高性能的微生物燃料电池型BOD传感器与BOD在线检测装置是该领域研究的重要方向。