Characterization and source apportionment of water pollution in Jinjiang River, China

Characterizing water quality and identifying potential pollution sources could greatly improve our knowledge about human impacts on the river ecosystem. In this study, fuzzy comprehensive assessment (FCA), pollution index (PI), principal component analysis (PCA), and absolute principal component score–multiple linear regression (APCS–MLR) were combined to obtain a deeper understanding of temporal–spatial characterization and sources of water pollution with a case study of the Jinjiang River, China. Measurement data were obtained with 17 water quality variables from 20 sampling sites in the December 2010 (withered water period) and June 2011 (high flow period). FCA and PI were used to comprehensively estimate the water quality variables and compare temporal–spatial variations, respectively. Rotated PCA and receptor model (APCS–MLR) revealed potential pollution sources and their corresponding contributions. Application results showed that comprehensive application of various multivariate methods were effective for water quality assessment and management. In the withered water period, most sampling sites were assessed as low or moderate pollution with characteristics pollutants of permanganate index and total nitrogen (TN), whereas 90 % sites were classified as high pollution in the high flow period with higher TN and total phosphorus. Agricultural non-point sources, industrial wastewater discharge, and domestic sewage were identified as major pollution sources. Apportionment results revealed that most variables were complicatedly influenced by industrial wastewater discharge and agricultural activities in withered water period and primarily dominated by agricultural runoff in high flow period.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Microbial source tracking: a forensic technique for microbial source identification?

As the requirements of the Water Framework Directive (WFD) and the US Clean Water Act (USCWA) for the maintenance of microbiological water quality in 'protected areas' highlight, there is a growing recognition that integrated management of point and diffuse sources of microbial pollution is essential. New information on catchment microbial dynamics and, in particular, the sources of faecal indicator bacteria found in bathing and shellfish harvesting waters is a pre-requisite for the design of any 'programme of measures' at the drainage basin scale to secure and maintain compliance with existing and new health-based microbiological standards. This paper reports on a catchment-scale microbial source tracking (MST) study in the Leven Estuary drainage basin, northwest England, an area for which quantitative faecal indicator source apportionment empirical data and land use information were also collected. Since previous MST studies have been based on laboratory trials using 'manufactured' samples or analyses of spot environmental samples without the contextual microbial flux data (under high and low flow conditions) and source information, such background data are needed to evaluate the utility of MST in USCWA total maximum daily load (TMDL) assessments or WFD 'Programmes of Measures'. Thus, the operational utility of MST remains in some doubt. The results of this investigation, using genotyping of Bacteroidetes using polymerase chain reaction (PCR) and male-specific ribonucleic acid coliphage (F + RNA coliphage) using hybridisation, suggest some discrimination is possible between livestock- and human-derived faecal indicator concentrations but, in inter-grade areas, the degree to which the tracer picture reflected the land use pattern and probable faecal indicator loading were less distinct. Interestingly, the MST data was more reliable on high flow samples when much of the faecal indicator flux from catchment systems occurs. Whilst a useful supplementary tool, the MST information did not provide quantitative source apportionment for the study catchment. Thus, it could not replace detailed empirical measurement of microbial flux at key catchment outlets to underpin faecal indicator source apportionment. Therefore, the MST techniques reported herein currently may not meet the standards required to be a useful forensic tool, although continued development of the methods and further catchment scale studies could increase confidence in such methods for future application.     

River water quality and pollution sources in the Pearl River Delta, China

Some physicochemical parameters were determined for thirty field water samples collected from different water channels in the Pearl River Delta Economic Zone river system. The analytical results were compared with the environmental quality standards for surface water. Using the SPSS software, statistical analyses were performed to determine the main pollutants of the river water. The main purpose of the present research is to investigate the river water quality and to determine the main pollutants and pollution sources. Furthermore, the research provides some approaches for protecting and improving river water quality. The results indicate that the predominant pollutants are ammonium, phosphorus, and organic compounds. The wastewater discharged from households in urban and rural areas, industrial facilities, and non-point sources from agricultural areas are the main sources of pollution in river water in the Pearl River Delta Economic Zone.     

Origin and spatial–temporal distribution of faecal bacteria in a bay of Lake Geneva, Switzerland

The origin and distribution of microbial contamination in Lake Geneva's most polluted bay were assessed using faecal indicator bacteria (FIB). The lake is used as drinking water, for recreation and fishing. During 1 year, water samples were taken at 23 points in the bay and three contamination sources: a wastewater treatment plant (WWTP), a river and a storm water outlet. Analyses included Escherichia coli, enterococci (ENT), total coliforms (TC), and heterotrophic plate counts (HPC). E. coli input flux rates from the WWTP can reach 2.5 x 10(10) CFU/s; those from the river are one to three orders of magnitude lower. Different pathogenic Salmonella serotypes were identified in water from these sources. FIB levels in the bay are highly variable. Results demonstrate that (1) the WWTP outlet at 30 m depth impacts near-surface water quality during holomixis in winter; (2) when the lake is stratified, the effluent water is generally trapped below the thermocline; (3) during major floods, upwelling across the thermocline may occur; (4) the river permanently contributes to contamination, mainly near the river mouth and during floods, when the storm water outlet contributes additionally; (5) the lowest FIB levels in the near-surface water occur during low-flow periods in the bathing season.     

Monitoring, assessment and modelling using water quality data in the Saale River Basin, Germany

The European Water Framework Directive (WFD) is the overall driver for this environmental study and currently requires the identification of patterns and sources of pollution (monitoring) to support objective ecological sound decision making and specific measures to enhance river water quality (modelling). The purpose of this paper is to demonstrate in a case study the interrelationship between (1) hydrologic and water quality monitoring data for river basin characterization and (2) modelling applications to assess resources management alternatives. The study deals with monitoring assessment and modelling of river water quality data of the main stem Saale River and its principal tributaries. For a period of 6 years the data, which was sampled by Environmental Agencies of the German states of Thuringia, Saxony and Saxony-Anhalt, was investigated to assess sources and indicators of pollution. In addition to the assessment a modelling exercise of the routing of different pollutants was carried out in the lower part of the test basin. The modelling is a tool to facilitate the evaluation of alternative measures to reduce contaminant loadings and improve ecological status of a water body as required by WFD. The transport of suspended solids, salts and heavy metals was modelled along a selected Saale reach under strong anthropogenic influence in terms of contaminants and river morphology between the city of Halle and the confluence with the Elbe River. The simulations were carried out with the model WASP5 which is a dynamic flood-routing and water quality model package developed by the US Environmental Protection Agency.     

Using Multiple Antibiotic Resistance and land use characteristics to determine sources of fecal coliform bacterial pollution

Multiple Antibiotic Resistance (MAR) analysis and regression modeling techniques were used to identify surface water areas impacted by fecal pollution from human sources, and to determine the effects of land use on fecal pollution in Murrells Inlet, a small, urbanized, high-salinity estuary located between Myrtle Beach and Georgetown, South Carolina. MAR analysis was performed to identify areas in the estuary that are impacted by human-source fecal pollution. Additionally, regression analysis was performed to determine if an association exists between land use and fecal coliform densities over the ten-year period from 1989 to 1998. Land-use variables were derived using Geographic Information System (GIS) techniques and were used in the regression analysis.MAR analyses were conducted by comparing the frequency and patterns of antibiotic resistance found in Escherichia coli isolates derived from surface water samples and from sewage sources in the Murrells Inlet sewage collection system. The MAR results suggest that the majority of the fecal pollution detected in the Murrells Inlet estuary may be from non-human sources, including fecal coliforms isolated from areas in close proximity to high densities of active septic tanks.A MAR Index, which measures the frequency of antibiotic resistance, was calculated for each of twenty-three water samples and nine sewage samples. The antibiotic resistance pattern comparisons were performed using cluster analysis. Although the MAR indices indicated that several surface water sites had potential human-source contamination, the cluster analysis suggests that only one sampling site had MAR patterns that were similar to those found in the sewage samples. This site was in close proximity to several large pleasure boats as well as a sewage collection system lift station, but was not near areas with active septic tanks. The results of the regression analysis also suggest that sewage sources and rainfall runoff from urbanized areas may contribute to fecal pollution in the estuary.     

Water quality of a tributary of the Pearl River, the Beijiang, Southern China: implications from multivariate statistical analyses

Water quality information of Beijiang River, a tributary of Pearl River in Guangdong, China, was analyzed to provide an overview of the hydrochemical functioning of a major agricultural/rural area and an industrial/urban area. Eighteen water quality parameters were surveyed at 13 sites from 2005 to 2006 on a monthly basis. A bivariate correlation analysis was carried out to evaluate the regional correlations of the water quality parameters, while the principal component analysis (PCA) technique was used to extract the most influential variables for regional variations of river water quality. Six principal components were extracted in PCA which explained more than 78% and 84% of the total variance for agricultural/rural and industrial/urban areas, respectively. Physicochemical factor, organic pollution, sewage pollution, geogenic factor, agricultural nonpoint source pollution, and accumulated pesticide usage were identified as potential pollution sources for agricultural/rural area, whereas industrial wastewaters pollution, mineral pollution, geogenic factor, urban sewage pollution, chemical industrial pollution, and water traffic pollution were the latent pollution sources for industrial/urban area. A multivariate linear regression of absolute principal component scores (MLR-APCS) technique was used to estimate contributions of all identified pollution sources to each water quality parameter. High coefficients of determination of the regression equations suggested that the MLR-APCS model was applicable for estimation of sources of most water quality parameters in the Beijiang River Basin.     

Characterization of Escherichia Coli Isolates from Different Fecal Sources by Means of Classification Tree Analysis of Fatty Acid Methyl Ester (Fame) Profiles

Microbial source tracking (MST) methods need to be rapid, inexpensive and accurate. Unfortunately, many MST methods provide a wealth of information that is difficult to interpret by the regulators who use this information to make decisions. This paper describes the use of classification tree analysis to interpret the results of a MST method based on fatty acid methyl ester (FAME) profiles of Escherichia coli isolates, and to present results in a format readily interpretable by water quality managers. Raw sewage E. coli isolates and animal E. coli isolates from cow, dog, gull, and horse were isolated and their FAME profiles collected. Correct classification rates determined with leaveone-out cross-validation resulted in an overall low correct classification rate of 61%. A higher overall correct classification rate of 85% was obtained when the animal isolates were pooled together and compared to the raw sewage isolates. Bootstrap aggregation or adaptive resampling and combining of the FAME profile data increased correct classification rates substantially. Other MST methods may be better suited to differentiate between different fecal sources but classification tree analysis has enabled us to distinguish raw sewage from animal E. coli isolates, which previously had not been possible with other multivariate methods such as principal component analysis and cluster analysis.     

Bacteriological quality of drinking water in Nyala, South Darfur, Sudan

The objective of this study was to determine the bacterial contaminations in drinking water in Nyala city, South Darfur, Sudan with special reference to the internally displaced people camps (IDPs). Two hundred and forty water samples from different sites and sources including bore holes, hand pumps, dug wells, water points, water reservoir and household storage containers were collected in 2009. The most probable number method was used to detect and count the total coliform, faecal coliform and faecal enterococci. Results revealed that the three indicators bacteria were abundant in all sources except water points. Percentages of the three indicators bacteria count above the permissible limits for drinking water in all samples were 46.4% total coliform, 45.2% faecal coliform and 25.4% faecal enterococci whereas the highest count of the indicators bacteria observed was 1,600 U/100 ml water. Enteric bacteria isolated were Escherichia coli (22.5%), Enterococcus faecalis (20.42%), Klebsiella (15.00%), Citrobacter (2.1%) and Enterobacter (3.33%). The highest contamination of water sources was observed in household storage containers (20%) followed by boreholes (11.25%), reservoirs (6.24%), hand pumps (5.42%) and dug wells (2.49%). Contamination varied from season to season with the highest level in autumn (18.33%) followed by winter (13.75%) and summer (13.32%), respectively. All sources of water in IDP camps except water points were contaminated. Data suggested the importance of greater attention for household contamination, environmental sanitation control and the raise of awareness about water contamination.     

Seasonal variation in heavy metal contamination in water and sediments of river Sabarmati and Kharicut canal at Ahmedabad, Gujarat

The objective of the study is to reveal the seasonal variations in the river water and sediment quality with respect to heavy metal contamination. To get the extent of trace metals contamination, water and sediment samples were collected from five different sites along the course of Sabarmati River and its tributary Kharicut canal in pre-monsoon, monsoon and post-monsoon seasons. The concentration of trace metals such as chromium, copper, lead, nickel and zinc was determined using inductively coupled plasma spectroscopy. The concentrations of heavy metals were found to be higher in the pre-monsoon season than in the monsoon and post-monsoon seasons in water samples. The pollution load index, contamination factor and degree of contamination (C _d) in sediments were calculated to know the extent of anthropogenic pressures. The values of C _d clearly indicated very high degree of contamination at Kharicut canal (S-4: 32.25 and S-5: 54.52) and considerable degree of contamination at three sites of Sabarmati river viz; S-1, S-2 and S-3 with values 14.30, 14.42 and 17.21, respectively. Lead and nickel could not be traced in any of the river water samples.     

Seasonal and spatio-temporal distribution of faecal-indicator bacteria in Tyume River in the Eastern Cape Province, South Africa

We assessed the incidence of faecal-indicator bacteria in Tyume River over a 12-month period between August 2010 and July 2011. Total coliforms, faecal coliforms and enterococci were determined by the membrane filtration method. Total coliforms were detected in counts ranging from 2.1?×?10² to 3.4?×?10⁴?CFU/100 ml. Faecal coliform counts ranged from 1?×?10² to 1.6?×?10⁴?CFU/100 ml while enterococci counts were in the range of 3.3?×?10¹ to 5.1?×?10³?CFU/100 ml. Indicator bacteria counts increased from upstream to downstream sampling sites. Counts of indicator bacteria at all sites were significantly affected by seasonal changes. The bacteriological qualities of the river water were poor, exceeding the guideline of 200 CFU/100 ml and 33 CFU/100 ml for faecal coliforms and enterococci, respectively, for recreational water. Faecal coliform counts also exceeded the 1,000 CFU/100 ml guideline for water used in fresh produce irrigation. Microbial source tracking results showed that faecal pollution was predominantly of human origin during spring at all sampling sites. During other seasons, human faecal pollution was largely confined to midstream and downstream sampling sites. Generally, the presence of faecal-indicator bacteria in the river water samples suggests faecal pollution of this freshwater resource, raising the possibility of the presence of pathogenic microorganisms in the water and a threat to public health.     

四川省毛河流域污染综合治理方案探讨

分析了四川省毛河流域各类污染源分布状况及水质现状,采用一维稳态单组分水质模型、多宾斯-坎普稳态模型,引入水文数据、水质监测数据、环境统计数据、社会统计公报数据,以Excel作为数据平台,对毛河水环境进行了动态模拟,反演出主要污染物降解系数。总结了毛河水环境目前存在的问题,并模拟计算了2种污染综合治理方案实施后对毛河水质的影响,确定了毛河流域水污染综合治理的重点以及制约因子。     

Polycyclic aromatic hydrocarbons in river sediments from the western and southern catchments of the Bohai Sea, China: toxicity assessment and source identification

The concentration, distribution, and origin of 16 USEPA priority polycyclic aromatic hydrocarbons (PAHs) were investigated in river sediments from the western and southern catchments of the Bohai Sea, China. A toxicity assessment of 28 sediment samples collected from 15 main rivers was conducted by utilizing threshold and probable effect concentrations (TEC and PEC, respectively) derived from consensus-based sediment quality guidelines. The concentrations of total PAHs (∑PAH₁₆) ranged from 0.14 to 10,757 μg/kg dry weight (mean?=?1,368.6 μg/kg). The high concentrations of PAHs found in Binhai New Area of Tianjin and Binzhou City are likely the result of rapid population and heavy industry growth, resulting in elevated point and nonpoint source inputs of PAHs. Of the samples collected, samples 1 and 10 (7.1 % of the total) were categorized as toxic since some of the PAH concentrations exceeded the corresponding PECs. Twenty samples were classified as nontoxic, with both the individual PAH and the∑PAH₁₆ concentrations falling below the corresponding TECs. Analyses of selected PAH isomer ratios aided in the identification of PAH origins, allowing for a discrimination between pyrogenic and petrogenic sources. Spatial variability confirmed source heterogeneity within the study area. The most significant PAH-associated contamination was found in the Beitang River and Ji Canal, which are located in Binhai New Area. The magnitude of contamination and the likelihood of an ongoing influx of PAHs support the need for a better understanding of pollution sources and methods for both control and sediment restoration.     

MONITORING OF SPATIAL AND TEMPORAL HYDROCHEMICAL CHANGES IN GROUNDWATER UNDER THE CONTAMINATING EFFECTS OF ANTHROPOGENIC ACTIVITIES IN MERSIN REGION, TURKEY

The development of groundwater resources for water supply is a favored way in Turkey. The Berdan alluvial aquifer in Mersin is particularly productive, but little is known about the natural phenomena that govern the groundwater quality and the contamination sources in this region. During 2001 and 2002, water samples for chemical analysis were obtained from 27 wells and from two points of Berdan River and analyzed by ICP. Main chemical characteristics of sampled groundwater define two aquifers, which were also determined by hydrogeological investigations. The groundwater produced from some of the wells was affected by anthropogenic activities temporally and spatially by seawater intrusion. Berdan River is polluted with the wastewater discharges and river water also influences the groundwater quality.     

Potability of water sources in relation to metal and bacterial contamination in some northern and north-eastern districts of India

A total of 1094 water samples from 326 springs, 207 streams, 183 dug wells, 151 piped supplies, 90 tube wells, 75 hand pumps, 60 rivers and 2 lakes were collected from eight northern and six north-eastern districts of India. Samples were analysed to assess their potability by estimating the level of heavy metals and bacterial (coliform and faecal coliform) contaminations. Iron was found in a maximum number (53%) of water samples from hand pumps, followed by lead in 43% of the tube wells, chromium in 16% of dug wells, cadmium in 13% of streams and manganese in 7% of hand pumps above their maximum admissible concentrations (MACs). Maximum metal pollution has been observed in a considerable number of water samples from Doda, followed by Almora, Mirzapur and Bankura. Hand pump water samples exhibited maximum metal pollution followed by dug well, spring, stream and river water samples. Contamination of coliform and/or faecal coliform bacteria ranged between 41% and 67% of water samples from open water sources but it was also less, i.e. 6–15% of water samples from tube wells and hand pumps. In general, 42–85% of water samples from districts surveyed, except from Jammu (18%) and Mirzapur (27%), were found to be bacteriologically unsatisfactory. Since toxic metals and pathogenic bacteria pose a risk to public health, monitoring of drinking water sources is required.     

望虞河西岸河网区沉积物营养盐和重金属污染时空分布特征

以无锡市望虞河西岸河网区为研究区域,于2018年12月—2019年9月分冬、春、夏、秋4个季节采集了上覆水和沉积物样本,研究氮磷营养因子在沉积物-上覆水界面的释放规律,探究主要水质指标、沉积物氮磷和重金属含量的时空分布特征。结果表明:研究区域内的水质状况不佳,主要是氮含量超标,污染严重的点位集中在人类活动较为密集的市区和工业区;受上覆水氮磷浓度、溶解氧浓度等变化的影响,沉积物营养盐含量季节变化明显,污染状况较为严重,75%的点位属于中度和重度污染;沉积物重金属含量季节变化不显著,部分重金属的空间分布特征相似,污染程度排序为Zn>Cd>Cu>Pb>Ni>Cr>As。     

Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques

This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderate-pollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.     

入河排污口在总量控制中的作用

入河排污口在污染源与水环境间起桥梁作用,入河排污口的入河量是对水环境影响大小的最直接贡献值,作好入河排污口的监测工作,既可对污染源的排污起监督作用,也可得到某区域相对最为可靠的排污总量和河流纳污量,因此,入河排污口是目前总量管理的基础     

Assessment of animal impacts on bacterial water quality in a South Carolina, USA tidal creek system

Fecal pollution may adversely impact water quality in coastal ecosystems. The goal of this study was to determine whether cattle were a source of fecal pollution in a South Carolina watershed. Surface water samples were collected in June 2002 and February through March 2003 in closed shellfish harvesting waters of Toogoodoo Creek in Charleston County, SC. Fecal coliform concentrations in 70 % of the water samples taken for this study exceeded shellfish harvesting water standards. Ribotyping was performed in order to identify animal sources contributing to elevated fecal coliform levels. Escherichia coli isolates (n?=?253) from surface water samples were ribotyped and compared to a ribotype library developed from known sources of fecal material. Ribotypes from water samples that matched library ribotypes with 90 % maximum similarity or better were assigned to that source. Less than half of the unknown isolates (38 %) matched with library isolates. About half (53 %) of the matched ribotypes were assigned to cattle isolates and 43 % to raccoon. Ribotyping almost exclusively identified animal sources. While these results indicate that runoff from cattle farms was a likely source of fecal pollution in the watershed, wildlife also contributed. Given the small size of the library, ribotyping was moderately useful for determining the impact of adjacent cattle farms on Toogoodoo Creek. Increasing the number and diversity of the wildlife sources from the area would likely increase the usefulness of the method.