Five-day Biochemical Oxygen Demand Research Articles

Detoxification of pulping black liquor with Pleurotus ostreatus or recombinant Pichia pastoris followed by CuO/TiO2/visible photocatalysis

Cellulose-pulping requires chemicals such as Cl2, ClO2, H2O2, and O2. The black liquor (BL) generated exhibits a high chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), and chlorophenol content, along with an augmented colour and increased pH. BL is often discharged into water bodies, where it has a negative impact on the environment. Towards that end, laccases are of great interest for bioremediation, since they can degrade aromatic and non-aromatic compounds while reducing O2 to water instead of H2O2. As such, we evaluated Pleurotus ostreatus and Pichia pastoris (which produces rPOXA 1B laccase) in the treatment of synthetic BL (SBL) in an “in vitro” modified Kraft process followed by CuO/TiO2/visible light photocatalysis. Treating SBL with P. ostreatus viable biomass (VB) followed by CuO/TiO2/visible light photocatalysis resulted in 80.3% COD removal and 70.6% decolourisation. Toxic compounds such as 2-methylphenol, 4-methylphenol, and 2-methoxyphenol were eliminated. Post-treated SBL exhibited low phytotoxicity, as evidenced by a Lactuca sativa L seed germination index (GI) > 50%. Likewise, SBL treatment with P. pastoris followed by VB/CuO/TiO2/visible light photocatalysis resulted in 63.7% COD removal and 46% decolourisation. Moreover, this treatment resulted in the elimination of most unwanted compounds, with the exception of 4-chlorophenol. The Lactuca sativa L seed GI of the post-treated SBL was 40%, indicating moderate phytotoxicity.

Analysis of Basic Physical-Chemical Parameters, Nutrients and Heavy Metals Content in Surface Water of Small Catchment Area of Karašica and Vučica Rivers in Croatia

This paper deals with the surface water quality of a small catchment area of the Karašica and Vučica rivers based on the analysis of water physical and chemical parameters according to the national Decree on Water Quality Standards (2013). Water samples were collected and analysed monthly at five sampling stations situated along the watercourses in the period between 1998 and 2015. Analysed parameters were pH, chemical oxygen demand (COD-Mn), five-day biochemical oxygen demand (BOD5), nutrients: nitrate compounds (nitrates and total nitrogen), phosphorus compounds (orthophosphates and total phosphorus), and the content of heavy metals. The obtained results indicate a water quality status between moderate and good, depending on the parameter and sampling station.

Application of the water quality index in the Timok River basin (Serbia)

The paper presents an analysis of water pollution carried out on the basis of the combined physico-chemical Serbian Water Quality Index (WQI) in the Timok River basin. The analysis covers various parameters (oxygen saturation, Five-Day Biochemical Oxygen Demand or BOD 5 , ammonium ion concentration, pH value, Water Total Nitrogen or WTN, Total Suspended Solids or TSS, orthophosphate concentration, electrical conductivity, temperature and the fecal coliform bacteria parameter) the values of which were calculated for four hydrological stations within the basin. The data obtained at each measurement station were averaged using the annual arithmetic average mean. The annual WQI values were calculated for a twenty-five year period (1990–2014) and they were in the range between 12 and 92, which means that the quality of water varied, ranging from “very bad” to “excellent”. The obtained results were interpreted and the watercourse quality was assessed using the comparison of water quality indicators according to the Serbian Classification of Surface Waters and the WQI method. The worst water quality was recorded in the Borska Reka River. Certain SWQI values are the result of water quality changes caused by wastewater from human settlements, industrial facilities, agricultural sources and illegal waste disposal sites in the basin.

Spatio-temporal analysis of the Karun River water quality

The spatio-temporal variations of the water quality of the Karun River using national sanitation foundation water quality index (NSFWQI) are analysed in this paper using time series analysis and geographic information system (GIS). Monthly data including pH, temperature, dissolved oxygen (DO), five-day biochemical oxygen demand (BOD), total solids (TS), PO43–, NO3–, turbidity and fecal coliform are analysed for 2007-2012. Calculated NSFWQI time series during the study period shows that the water quality of the river lies in the medium class. The results of time series analysis show that periodicity and trend are not significant in the majority of stations. The spatial analysis results demonstrate that the water quality in Ahwaz urban area is slightly poorer than in the rest of the river. Overall, the spatio-temporal distribution of the NSFWQI values indicates that changes are negligible and show the balance between the pollutants input and self-purification capacity of the river.

Physicochemical Parameters and Fish Assemblages in the Downstream River of a Tropical Hydroelectric Dam Subjected to Diurnal Changes in Flow

The downstream river of the tropical Batang Ai Dam is experiencing diurnal flow fluctuation due to power generation operation. Three samplings were conducted to collect the water quality and fish assemblage data and one sampling was conducted to study the hydrological characteristics of the downstream river. The results show that the downstream river is extremely shallow and moves slowly when the power generation is halted and no water is discharged from the powerhouse. Significant correlations between river flow and pH, dissolved oxygen (DO), total suspended solids (TSS), and five-day biochemical oxygen demand (BOD5) indicated that those parameters were influenced by the water discharge regulation. Fish abundance was low in upstream segment but it gradually increased as distance from the dam increased and was significantly correlated with DO. Fish diversity in the downstream river was influenced by the river depth and chlorophyll a concentration. The most abundant fish species, Cyclocheilichthys apogon, exhibited a negative allometric growth pattern, while Hampala macrolepidota and Hemibagrus planiceps exhibited an isometric growth pattern. Fulton’s condition factor (K) values for 89.4% of H. planiceps were ≤1, indicating poor to extremely poor conditions.

Modelling of biochemical oxygen demand from limited water quality variable by ANFIS using two partition methods

Abstract This paper aims to: (1) develop models based on adaptive neuro-fuzzy inference system (ANFIS) able to predict five-day biochemical oxygen demand (BOD5) in Ouizert reservoir; (2) demonstrate the capability of the ANFIS in the practical issues of water quality management; (3) choose the optimal combination of input variables to improve the model performance; (4) compare two ANFIS partition methods, namely subtractive clustering called ANFIS-SC and grid partitioning, called ANFIS-GP. The models were developed using experimental data which were gathered during a ten-year period, at a mean monthly time step (scale). The input data used are total inorganic nitrogen, chemical oxygen demand (COD), total dissolved solid, dissolved oxygen and phosphate; the output is five-day biochemical oxygen demand (BOD5). Results reveal that ANFIS-SC models gave a higher correlation coefficient, a lower root mean square errors (RMSE) and mean absolute errors than the corresponding ANFIS-GP models. We can conclude that ANFIS-SC has supremacy over ANFIS-GP in terms of performance criteria and prediction accuracy for BOD5 estimation. The results showed that COD is the more effective variable for BOD5 estimating than other parameters, hence COD is the major driving factor for BOD5 modelling through ANFIS.

Predicting influent biochemical oxygen demand: Balancing energy demand and risk management

Ready access to comprehensive influent information can help water reclamation plant (WRP) operators implement better real-time process controls, provide operational reliability and reduce energy consumption. The five-day biochemical oxygen demand (BOD5), a critical parameter for WRP process control, is expensive and difficult to measure using hard-sensors. An alternative approach based on a soft-sensor methodology shows promise, but can be problematic when used to predict high BOD5 values. Underestimating high BOD5 concentrations for process control could result in an insufficient amount of aeration, increasing the risk of an effluent violation. To address this issue, we tested a hierarchical hybrid soft-sensor approach involving multiple linear regression, artificial neural networks (ANN), and compromise programming. While this hybrid approach results in a slight decrease in overall prediction accuracy relative to the approach based on ANN only, the underestimation percentage is substantially lower (37% vs. 61%) for predictions of carbonaceous BOD5 (CBOD5) concentrations higher than the long-term average value. The hybrid approach is also flexible and can be adjusted depending on the relative importance between energy savings and managing the risk of an effluent violation.

Geografía del cáncer de mama en México

This research was aimed at locating and mapping the geographical regions where the cases of breast cancer among the female population of Mexico have been most prevalent, analyzing the predominant geographic factors and establishing if the relationship between these and the different environmental aspects may be conditioning the presence and development of this neoplasm. The delimitation was based primarily on the analysis of the temporal evolution of mortality and morbidity rates of this disease since 2000, by state, which allowed the identification of twelve entities that sustained the highest rates throughout twelve years, as well as the municipalities where the most relevant data of this disease were recorded during that period. Likewise, the twelve states with the lowest rates were delimited in this respect, to review which municipalities of these states presented the most significant mortality and morbidity data and to review in the subsequent analysis, the coincidences or divergences presented by both antagonistic spaces. In total, one hundred twenty municipalities were selected for the analysis of environmental factors that have been identified in various sources as potential sources of risk in the development of breast cancer. The variables analyzed are: contaminated surface waters, contaminated soils, contaminated groundwater, polluting industries and air pollution from thermoelectric plants and how they have been spatially and statistically expressed in the target municipalities. The methodology was based on the analysis of the spatial behavior of the variables indicated and was complemented with the application of the multiple regression models in the target or occurrence municipalities. Considering the statistical data of breast cancer and the selected variables, the relationship resulted positive in three variables: industries, contaminated groundwater and contaminated soils.Some of the most relevant results were: First, according with the indicators currently used by the National Water Commission (CONAGUA) regarding the severely contaminated water surface: five-day biochemical oxygen demand (BOD5), chemical oxygen demand (DQO) and The total suspended solids (SST), coincided the presence of them in seventy-four of the target municipalities that equal 61.6%. Second, by analyzing the COD index separately, as it shows contamination by industrial discharges and agricultural activity, it turned out that eighty-six sites (74%) contaminated with this indicator of a total of 116 points recorded by CONAGUA are located in the Municipalities. Concerning the presence of groundwater (aquifers) contaminated mainly with nitrates in concentrations greater than 45 mg / l; in the counts of spatial analysis, it is observed that in seventy-five of the target municipalities (65%), this variable is present. Another relevant result was to review the location of thermoelectric plants generating electric energy that run on fuels that affect air quality such as fuel oil, coal and disel, all three generate carcinogenic elements when they combust. In this case of the total of the eighty-four thermoelectric plants operating in the country, fifty-eight (69%) are located in thirty-nine of the target municipalities (32.5%). And of the total number of polluting industries that operate in the country, only five (4.1%) of the target municipalities did not have this type of industry, so this variable was very significant in the study areas. Finally, the presence of sites contaminated with hazardous wastes (RP), resulting from wastes generated by the mining, basic chemistry, petrochemical, oil refining and agribusiness industries, were also present in 112 (93.3%) of the target municipalities.It is concluded that it was relevant to delimit the main spaces where breast cancer has developed during the last twelve years, since this allowed the application of the physical variables to be able to identify several risk factors that have converged in them, a situation that can, possibly explain, in part, the presence of this neoplasm among the female population of certain regions of Mexico.This is of importance if one considers that the World Health Organization attributes to environmental factors as the cause of the development of more than eighty percent of the cancers that occur in the world, mainly lung and breast cancer.This analysis makes it possible to focus and implement public policies aimed at the prevention and detection of women who are currently exposed to the risk factors described in the study and in the designation of resources for the treatment and care of the population that already suffers this disease. The later, considering that breast cancer is currently a serious public health problem, due to the marked increase registered in this cancer among Mexican women every year.

Quantifying biodegradable organic matter in polluted water on the basis of coulombic yield

Biodegradable organic matter (BOM) in polluted water plays a key role in various biological purification technologies. The five-day biochemical oxygen demand (BOD5) index is often used to determine the amount of BOM. However, standard BOD5 assays, centering on dissolved oxygen detection, have long testing times and often show severe deviation (error ≥ 15%). In the present study, the coulombic yield (Q) of a bio-electrochemical degradation process was determined, and a new index for BOM quantification was proposed. The Q value represents the quantity of transferred electrons from BOM to oxygen, and the corresponding index was defined as BOMQ. By revealing Q-BOM stoichiometric relationship, we were able to perform a BOMQ assay in a microbial fuel cell involved technical platform. Experimental results verified that 5–500mgL−1 of BOMQ toward artificial wastewater samples could be directly obtained without calibration in several to dozens of hours, leaving less than 5% error. Moreover, the BOMQ assay remained accurate and precise in a wide range of optimized operational conditions. A ratio of approximately 1.0 between the values of BOMQ and BOD5 toward artificial and real wastewater samples was observed. The rapidity, accuracy, and precision of the measurement results are supported by a solid theoretical foundation. Thus, BOMQ is a promising water quality index for quantifying BOM in polluted water.

Hybrid magnetic graphitic nanocomposites towards catalytic wet peroxide oxidation of the liquid effluent from a mechanical biological treatment plant for municipal solid waste

Magnetite, nickel and cobalt ferrites were prepared and encapsulated within graphitic shells, resulting in three hybrid magnetic graphitic nanocomposites. Screening experiments with a 4-nitrophenol aqueous model system (5gL−1) allowed to select the best performing catalyst, which was object of additional studies with the liquid effluent resulting from a mechanical biological treatment plant for municipal solid waste. Due to its high content in bicarbonates (14350mgL−1) and chlorides (2833mgL−1), controlling the initial pH was a crucial step to maximize the performance of the catalytic wet peroxide oxidation (CWPO) treatment. The catalyst load was 0.5gL−1, a very low dosage when compared to the high chemical oxygen demand (COD) of the effluent − 9206mgL−1. At the optimum operating pH (i.e., pH=6), ca. 95% of the aromaticity was converted and ca. 55% of COD and total organic carbon (TOC) of the liquid effluent was removed. The biodegradability of the liquid effluent was enhanced during the treatment by CWPO, as reflected by the 2-fold increase of the five-day biochemical oxygen demand (BOD5) to COD ratio (BOD5/COD), namely from 0.21 (indicating non-biodegradability) to 0.42 (suggesting biodegradability of the treated wastewater). In addition, the treated water revealed no toxicity against selected bacteria.Lastly, a magnetic separation system was designed for in-situ catalyst recovery after the CWPO reaction stage. The high catalyst stability was demonstrated through five reaction/separation sequential experiments in the same vessel with consecutive catalyst reuse.

Marrying Step Feed with Secondary Clarifier Improvements to Significantly Increase Peak Wet Weather Treatment Capacity: An Integrated Methodology.

The need to increase the peak wet weather secondary treatment capacity of the City of Akron, Ohio, Water Reclamation Facility (WRF) provided the opportunity to test an integrated methodology for maximizing the peak wet weather secondary treatment capacity of activated sludge systems. An initial investigation, consisting of process modeling of the secondary treatment system and computational fluid dynamics (CFD) analysis of the existing relatively shallow secondary clarifiers (3.3 and 3.7 m sidewater depth in 30.5 m diameter units), indicated that a significant increase in capacity from 416 000 to 684 000 m3/d or more was possible by adding step feed capabilities to the existing bioreactors and upgrading the existing secondary clarifiers. One of the six treatment units at the WRF was modified, and an extensive 2-year testing program was conducted to determine the total peak wet weather secondary treatment capacity achievable. The results demonstrated that a peak wet weather secondary treatment capacity approaching 974 000 m3/d is possible as long as secondary clarifier solids and hydraulic loadings could be separately controlled using the step feed capability provided. Excellent sludge settling characteristics are routinely experienced at the City of Akron WRF, raising concerns that the identified peak wet weather secondary treatment capacity could not be maintained should sludge settling characteristics deteriorate for some reason. Computational fluid dynamics analysis indicated that the impact of the deterioration of sludge settling characteristics could be mitigated and the identified peak wet weather secondary treatment capacity maintained by further use of the step feed capability provided to further reduce secondary clarifier solids loading rates at the identified high surface overflow rates. The results also demonstrated that effluent limits not only for total suspended solids (TSS) and five-day carbonaceous biochemical oxygen demand (cBOD5) could be maintained, but also for ammonia-nitrogen and total phosphorous (TP). Although hydraulic limitations in other parts of the WRP prevent this full capacity to be realized, the City is proceeding to implement the modifications identified using this integrated methodology.

Evaluation and estimation of surface water quality in an arid region based on EEM-PARAFAC and 3D fluorescence spectral index: A case study of the Ebinur Lake Watershed, China

Development of tools for real-time monitoring of water quality is crucial for management of stream water pollution. In this study, fluorescence excitation-emission matrix (EEM) with parallel factor analysis (PARAFAC) were used to estimate five-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), suspended sediment (SS), total nitrogen (TN), pH, total phosphorus (TP), ammonia nitrogen (NH3+-N), turbidity (NTU), and dissolved oxygen (DO) concentrations in inland freshwater streams. The study area was located in Ebinur Lake Watershed, Xinjiang Uygur Autonomous Region, China. Our results showed that the four fluorescence components were successfully extrapolated by the PARAFAC factor analysis modeling from the fluorescence EEM data including microbial humic-like (C1), terrestrial humic-like organic substances (C2, C4), and protein-like organic substances (C3). The four PARAFAC components were selected as the water quality monitoring index of river water samples. Three-dimensional fluorescence index analysis showed that terrigenous organic pollution was the main organic pollution type in the watershed. This indicates that the watershed is subject to human disturbance, given the large variation of organic pollution in the water body. There was a significant correlation between the three-dimensional fluorescence index, the fluorescence components, and surface water quality index. In addition, the application of three-dimensional fluorescence index and fluorescence component to establish water quality index produced a model fitting coefficient greater than 0.5, which demonstrated that the accuracy of the model was in line with monitoring requirements in practice. This implies that the use of three-dimensional fluorescence index and three-dimensional fluorescence component to monitor Ebinur Lake Watershed water quality has a great potential.

Remediation of synthetic greywater in mesocosm—Scale floating treatment wetlands

Two different chemical recipes comprising various pollutants were selected to create high (HC) and low (LC) levels of contaminated synthetic greywaters (SGW). Remediation in macrocosm–scale floating treatment wetlands (FTW) vegetated with Phragmites australis (Cav.) Trin. ex Steud. (common reed) was investigated under natural weather conditions. The presence or absence of vegetation, short or long contact time of treatment, and low or high contamination loads are the main operational variables in the experimental set-up design of the FTW. The focus on removal processes (other than sedimentation) such as the role of macrophytes in phytoremediation was achieved by agitation of the treated outflow before sampling. To assess the impact of interactions between the experimental operational variables on removal performances of FTW, different approaches of statistical analysis were applied. The results revealed that total suspended solids (TSS) and turbidity values dropped significantly (p<0.05) in the presence of vegetation compared with those values from unvegetated wetlands. The presence of vegetation can significantly (p<0.05) improve the biodegradation possibility of greywater by increasing the five-day biochemical oxygen demand (BOD) and decreasing the chemical oxygen demand (COD) concentrations. In vegetated FTW, higher removal rates of COD can be achieved when treating HC-SGS compared to LC-SGW. However, no significant differences (p>0.05) in the removal of BOD was noted. Significant increases (p<0.05) in BOD concentrations have been recorded with increasing contact time of treatment, while high removals of COD have been recorded. The presence of vegetation in wetlands affected significantly (p<0.05) the decrease of dissolved oxygen (DO) concentrations in outflow of both types of greywater. If limited sources of organic matter are available, vegetation has significantly (p<0.05) enhanced the nutrient balance with increasing nitrate-nitrogen (NO3-N) and decreasing ortho-phosphate-phosphorus (PO4-P) concentrations in the outflow. Furthermore, significant increases (p<0.05) in ammonia-nitrogen (NH4-N) and DO were observed with increasing contact time, while TSS, turbidity, and NO3-N concentrations significantly decreased (p<0.05). In addition, yellow leaves and considerably lower growth rates were observed for the hydroponic plant rhizomes of P. australis, which might be an effect of light-induced fluorescein degradation due to the relatively open water surfaces of the wetlands.

Application of Multivariate Statistical Analysis in Evaluation of Surface River Water Quality of a Tropical River

The present study evaluated the spatial variations of surface water quality in a tropical river using multivariate statistical techniques, including cluster analysis (CA) and principal component analysis (PCA). Twenty physicochemical parameters were measured at 30 stations along the Batang Baram and its tributaries. The water quality of the Batang Baram was categorized as “slightly polluted” where the chemical oxygen demand and total suspended solids were the most deteriorated parameters. The CA grouped the 30 stations into four clusters which shared similar characteristics within the same cluster, representing the upstream, middle, and downstream regions of the main river and the tributaries from the middle to downstream regions of the river. The PCA has determined a reduced number of six principal components that explained 83.6% of the data set variance. The first PC indicated that the total suspended solids, turbidity, and hydrogen sulphide were the dominant polluting factors which is attributed to the logging activities, followed by the five-day biochemical oxygen demand, total phosphorus, organic nitrogen, and nitrate-nitrogen in the second PC which are related to the discharges from domestic wastewater. The components also imply that logging activities are the major anthropogenic activities responsible for water quality variations in the Batang Baram when compared to the domestic wastewater discharge.

Comparative study of domestic wastewater treatment by mature vertical-flow constructed wetlands and artificial ponds

This study compares the performance, design and operation variables of two wetland technologies treating domestic wastewater: an experimental artificial pond system and a mature experimental vertical-flow constructed wetland system. The wetland system planted with Phragmites australis (Cav.) Trin. ex Steud. (common reeds) was operated between June 2011 and October 2015, while the pond system was only operated between July 2015 and October 2015. Three different types of ponds were compared: ponds with wastewater; ponds with wastewater and reeds; and ponds with wastewater, reeds and aeration. Findings regarding the performances of mature wetlands showed that the wetland systems improved the water quality except for ortho-phosphate-phosphorus (PO4−P), where the treatment performance reduced slightly over time. In general, the aerated pond systems showed better treatment performances in terms of ammonia-nitrogen (NH4−N) and PO4−P‎. Both systems were linked with medium to high levels of five-day biochemical oxygen demand (BOD) removal. The highest COD and SS removals were observed for wetlands in comparison to ponds. Moreover, mature wetlands were better in removing NH4−N and PO4−P than ponds unless the ponds were aerated. The nitrate-nitrogen (NO3−N) concentration increased in the aerated ponds reflecting the high oxygen availability.

Optimization of Industrial Wastewater Treatment Using Intuitionistic Fuzzy Goal Geometric Programming Problem

This paper describes a design of industrial wastewater treatment plant, operating on pulp and paper manufacturing waste. The main objective is to formulate cost effective biological treatment process on industrial wastewater. In terms of the percent of five-day bio-chemical oxygen demand removed, the required final effluent quality has been maximized. Also, the cost involved has been minimized in five-day bio-chemical oxygen demand removal. To optimize remaining five-day bio-chemical oxygen demand in wastewater spending minimum money, a goal geometric programming is used here. Moreover, goal geometric programming is described incorporating imprecision in it. A model of intuitionistic fuzzy goal geometric programming problem is given in this paper. We have solved intuitionistic fuzzy goal programming model using geometric programming technique. The algorithm of the approach is discussed in this paper. It is also shown that the usefulness of intuitive fuzzy environment in goal geometric programming is compared to fuzzy goal geometric programming using a numerical example.

ANALYSIS OF THE EFFECTS OF A WASTEWATER TREATMENT PLANT FAILURE ON THE DRAVA RIVER WATER QUALITY

1D model of the Drava River, between 00 + 543 rkm and 69 +118 rkm, was created by the MIKE 11 river-modeling tool. The aim of this model was to analyze the river water quality (WQ). Compared to the real Drava River section, the model was simplified to exclude any tributaries for the purpose of the water quality analysis. The inflow boundary was specified upstream, in addition to the WQ parameters (dissolved oxygen (DO), temperature, ammonia nitrogen, nitrate nitrogen, total phosphorus and orthophosphate, and five-day biochemical oxygen demand (BOD5)). The water level and open boundary conditions were specified at the downstream end of section. The WQ parameters, mentioned earlier, were also defined at the Belisce wastewater treatment plant (WWTP) (54 + 373 rkm) and at the wastewater outlet near Osijek (14 + 580 rkm). The model was then used to simulate the effect on the WQ of the Drava River in a hypothetical extreme scenario: the 2-day failure of the Belisce WWTP. It was assumed that during this time untreated wastewater would be discharged into the river. After running the simulation, the resulting concentrations of DO, BOD5, and ammonia nitrogen were analyzed. The results showed that, according to the concentration values of the untreated wastewater, the concentrations of BOD5 and ammonia nitrogen rapidly increased and the DO concentrations rapidly decreased with the initiation of the WWTP failure. Immediately after the WWTP was repaired, the parameters returned to their pre-failure values. The resulting analysis of the effects of this scenario highlighted the self-purification ability of the Drava River.

Performance evaluation of the wastewater treatment plant of Pelareh Dairy Industry, Iran

Pelareh Dairy Industry (PDI) is located in the west of Iran. The aim of the present study was to assess the quality and quantity of PDI wastewater and compare the results with the regulations. PDI has a wastewater treatment plant that consists of sewage collection system, screening system, equalization tank, clarification tank, anaerobic system for pretreatment, activated sludge processing, disinfection, and solids drying beds. In this research, seven quality parameters, including chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD 5 ), nitrate (NO 3 ), total suspended solids (TSS), phosphate (PO 4 ), temperature (T o c), and pH, were measured as qualitative variables. Thus, 20 samples were collected from influent and effluent zones. Wastewater samples were collected using random grab sampling during peak hours. Based on the results, the average (SD) COD concentration of the raw wastewater in wet season and dry season was 2152.22 (1384.00) and 1813.38 (518.33) mg/l, respectively. The results revealed that the removal efficiency of BOD 5 , COD, and TSS at the studied plant was 89.22%, 88.79%, and 71.72%, respectively. Based on achieved results, the pollution load of PDI effluent wastewater was determined and presented. Based on the obtained results, the pollution load based on BOD 5 variable was 15.71 kg/day. The obtained results indicate that the treatment plant was not efficient enough to be considered as a treatment process for the removal of suspended solids and organic matter.

Constructed Wetlands for Agricultural Wastewater Treatment in Northeastern North America: A Review

Constructed wetlands (CW) are a treatment option for agricultural wastewater. Their ability to adequately function in cold climates continues to be evaluated as they are biologically active systems that depend on microbial and plant activity. In order to assess their performance and to highlight regional specific design considerations, a review of CWs in Eastern Canada and the Northeastern USA was conducted. Here, we synthesize performance data from 21 studies, in which 25 full-scale wetlands were assessed. Where possible, data were separated seasonally to evaluate the climatic effects on treatment performance. The wastewater parameters considered were five-day biochemical oxygen demand (BOD5), total suspended solids (TSS), E. coli, fecal coliforms, total Kjeldahl nitrogen (TKN), ammonia/ammonium (NH3/NH4+-N), nitrate-nitrogen (NO3−-N), and total phosphorus (TP). Average concentration reductions were: BOD5 81%, TSS 83%, TKN 75%, NH4+-N 76%, NO3−-N 42%, and TP 64%. Average log reductions for E. coli and fecal coliforms were 1.63 and 1.93, respectively. Average first order areal rate constants (ka, m·y−1) were: BOD5 6.0 m·y−1, TSS 7.7 m·y−1, E. coli 7.0 m·y−1, fecal coliforms 9.7 m·y−1, TKN 3.1 m·y−1, NH4+-N 3.3 m·y−1, NO3−-N 2.5 m·y−1, and TP 2.9 m·y−1. In general, CWs effectively treated a variety of agricultural wastewaters, regardless of season.

Spatio-Temporal Patterns and Source Identification of Water Pollution in Lake Taihu (China)

Various multivariate methods were used to analyze datasets of river water quality for 11 variables measured at 20 different sites surrounding Lake Taihu from 2006 to 2010 (13,200 observations), to determine temporal and spatial variations in river water quality and to identify potential pollution sources. Hierarchical cluster analysis (CA) grouped the 12 months into two periods (May to November, December to the next April) and the 20 sampling sites into two groups (A and B) based on similarities in river water quality characteristics. Discriminant analysis (DA) was important in data reduction because it used only three variables (water temperature, dissolved oxygen (DO) and five-day biochemical oxygen demand (BOD5)) to correctly assign about 94% of the cases and five variables (petroleum, volatile phenol, dissolved oxygen, ammonium nitrogen and total phosphorus) to correctly assign &gt;88.6% of the cases. In addition, principal component analysis (PCA) identified four potential pollution sources for Clusters A and B: industrial source (chemical-related, petroleum-related or N-related), domestic source, combination of point and non-point sources and natural source. The Cluster A area received more industrial and domestic pollution-related agricultural runoff, whereas Cluster B was mainly influenced by the combination of point and non-point sources. The results imply that comprehensive analysis by using multiple methods could be more effective for facilitating effective management for the Lake Taihu Watershed in the future.