Multivariate assessment of polycyclic aromatic hydrocarbons in surface sediments of the Beijiang, a tributary of the Pearl River in Southern China

To estimate the severity of polycyclic aromatic hydrocarbon (PAH) contamination in the upper sediment of the Beijiang River, 42 sediment samples were analyzed for the presence of 16 key PAHs using gas chromatography–mass spectrometry. The concentrations of PAH in the sediment ranged from 44 to 8,921 ng g^?1 dry weight. The four- to six-ring PAHs, contributing >50 % to PAHs in 34 of the 42 sites, were the dominant species. Based on a principal component analysis, combined with multivariate linear regression, it became clear that the most important contributors of PAH were fossil fuel combustion (48 %), diesel emissions plus oil spillage (33 %), and coke combustion (19 %). The surface sediments of Beijiang River were grossly contaminated by PAHs mainly derived from combustion.     

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.     

Assessment of trace element contamination in sediment cores from the Pearl River and estuary,South China: geochemical and multivariate analysis approaches

Twenty-four major and trace elements and the mineralogical composition of four sediment cores along the Pearl River and estuary were analyzed using ICP-AES, ICP-MS, and X-ray diffraction (XRD) to evaluate contamination levels. The dominant minerals were quartz, kaolinite, and illite, followed by montmorillonite and feldspars, while small amounts of halite and calcite were also observed in a few samples. Cluster analysis (CA) and principal component analysis (PCA) were performed to identify the element sources. The highest metal concentrations were found at Huangpu, primarily due to wastewater treatment plant discharge and/or the surreptitious dumping of sludge, and these data differed from those of other sources. Excluding the data from Huangpu, the PCA showed that most elements could be considered as lithogenic; few elements are the combination of lithogenic and anthropogenic sources. An antagonistic relationship between the anthropogenic source metals (K, Ba, Zn, Pb, Cd, Ag, Tl, and U) and marine source metals (Na, Mg, Ti, V, and Ca) was observed. The resulting normalized Al enrichment factor (EF) indicated very high or significant pollution of Cd, Ag, Cu, Zn, Mo, and Pb at Huangpu, which may cause serious environmental effects. Conflicting results between the PCA and EF can be attributed to the background values used, indicating that background values must be selected carefully.     

Water quality assessment and source identification of Daliao river basin using multivariate statistical methods

Multivariate statistical methods, such as cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA), were used to analyze the water quality dataset including 13 parameters at 18 sites of the Daliao River Basin from 2003-2005 (8424 observations) to obtain temporal and spatial variations and to identify potential pollution sources. Using Hierarchical CA it is classified 12 months into three periods (first, second and third period) and the 18 sampling sites into three groups (groups A, B and C). Six significant parameters (temperature, pH, DO, BOD(5), volatile phenol and E. coli) were identified by DA for distinguishing temporal or spatial groups, with close to 84.5% correct assignment for temporal variation analysis, while five parameters (DO, NH(4)(+)-N, Hg, volatile phenol and E. coli) were discovered to correctly assign about 73.61% for the spatial variation analysis. PCA is useful in identifying five latent pollution sources for group B and C (oxygen consuming organic pollution, toxic organic pollution, heavy metal pollution, fecal pollution and oil pollution). During the first period, sites received more oxygen consuming organic pollution, toxic organic pollution and heavy metal pollution than those in the other two periods. For group B, sites were mainly affected by oxygen consuming organic pollution and toxic organic pollution during the first period. The level of pollution in the second period was between the other two periods. For group C, sites were mainly affected by oil pollution during the first period and oxygen consuming organic pollution during the third period. Furthermore, source identification of each period for group B and group C provided useful information about seasonal pollution. Sites were mainly affected by fecal pollution in the third period for group B, indicating the character of non-point source pollution. In addition, all the sites were also affected by physical-chemistry pollution. In the second and third period for group B and second period for group C sites were also affected by natural pollution.     

Assessing Impact of Urbanization on River Water Quality In The Pearl River Delta Economic Zone, China

The Pearl River Delta Economic Zone is one of the most developed regions in China. It has been undergoing a rapid urbanization since the reformation and opening of China in 1978. This process plays a significant impact on the urban environment, particularly river water quality. The main goal of this present study is to assess the impact of urban activities especially urbanization on river water quality for the study area. Some Landsat TM images from 2000 were used to map the areas for different pollution levels of urban river sections for the study area. In addition, an improved equalized synthetic pollution index method was utilized to assess the field analytical results. The results indicate that there is a positive correlation between the rapidity of urbanization and the pollution levels of urban river water. Compared to the rural river water, urban river water was polluted more seriously. During the urban development process, urbanization and urban activities had a significant negative impact on the river water quality.     

Passive air sampling of DDT, chlordane and HCB in the Pearl River Delta, South China: implications to regional sources

The Pearl River Delta (PRD) is one of the largest fast-developing economic zones in China. Hong Kong and the mainland part of the PRD differed in socio-economic development history and chemical management policies. Polyurethane foam (PUF)-passive air sampling (PAS) was deployed at 21 regional air quality monitoring stations across the PRD in summer and winter, respectively. Dichloro-diphenyl-trichloroethane (DDT), chlordane and hexachlorobenzene (HCB) were analyzed with GC-MS. High total DDT (240-3700 pg m(-3)) and chlordane (100-2600 pg m(-3)) concentrations were observed. Concentrations of DDTs and chlordane were higher in summer than winter; HCB vice versa. Spatially, the mainland part of the PRD generally displayed higher DDT concentrations than Hong Kong. Antifouling paint for fishing ships in coastal China was suggested to be an important current DDT source in the coast. The reason is unknown for the very low trans-/cis-chlordane (TC/CC) ratios (0.27) found in the mainland in winter. HCB concentrations were relatively uniform across the PRD, and long range transport of HCB from inland/North China to the PRD in winter was suggested.     

Assessment of surface water quality using multivariate statistical techniques in red soil hilly region: a case study of Xiangjiang watershed, China

In the study, multivariate statistical methods including factor, principal component and cluster analysis were applied to analyze surface water quality data sets obtained from Xiangjiang watershed, and generated during 7 years (1994-2000) monitoring of 12 parameters at 34 different profiles. Hierarchical cluster analysis grouped 34 sampling sites into three clusters, including relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) sites, and based on the similarity of water quality characteristics, the watershed was divided into three zones. Factor analysis/principal component analysis, applied to analyze the data sets of the three different groups obtained from cluster analysis, resulted in four latent factors accounting for 71.62%, 71.77% and 72.01% of the total variance in water quality data sets of LP, MP and HP areas, respectively. The PCs obtained from factor analysis indicate that the parameters for water quality variations are mainly related to dissolve heavy metals. Thus, these methods are believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality.     

Assessment of surface water quality using multivariate statistical techniques: a case study of Behrimaz Stream, Turkey

Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis, and factor analysis, were applied for the evaluation of temporal/spatial variations and for the interpretation of a water quality data set of the Behrimaz Stream, obtained during 1 year of monitoring of 20 parameters at four different sites. Hierarchical CA grouped 12 months into two periods (the first and second periods) and classified four monitoring sites into two groups (group A and group B), i.e., relatively less polluted (LP) and medium polluted (MP) sites, based on similarities of water quality characteristics. Factor analysis/principal component analysis, applied to the data sets of the two different groups obtained from cluster analysis, resulted in five latent factors amounting to 88.32% and 88.93% of the total variance in water quality data sets of LP and MP areas, respectively. Varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are mainly related to discharge, temperature, and soluble minerals (natural) and nutrients (nonpoint sources: agricultural activities) in relatively less polluted areas; and organic pollution (point source: domestic wastewater) and nutrients (nonpoint sources: agricultural activities and surface runoff from villages) in medium polluted areas in the basin. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and interpretation of data sets and, in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in water quality for effective stream water quality management.     

Water quality of Mediterranean coastal plains: conservation implications from the Akyatan Lagoon,Turkey

The water quality of the Akyatan Lagoon was characterized using hydrochemical methodology. The lagoon is located on the Mediterranean coast and is the largest wetland ecosystem in Turkey. In addition, the lagoon is classified as a hyper-salinity wetland. Water samples were collected monthly between December 2007 and November 2008. Eleven stations within the lagoon were determined, and triplicate grab samples were obtained from each station to characterize water quality as follows: T °C, pH, total alkalinity (TAlk), dissolved oxygen (DO), total dissolved solids (TDS), salinity, electrical conductivity (EC), and main anions, including chloride (Cl^?), nitrates (NO₃ ^?), and sulfate (SO₄ ^2?). Results from selected stations indicated varying TDS, EC, salinity, and Cl^? concentrations, from 20,892 to 175,824 mg/L, from 35.7 to 99.6 mS/cm, from 22.3 to 71.0 ppt, and from 14,819 to 44,198 mg Cl^?/L, respectively. Data indicated that the spatial distribution of water quality parameters was significantly affected by freshwater input via the constructed drainage channels which collect water from a catchment area and discharge water into the lagoon as a point source, thus preventing drainage water to reach the lagoon as a nonpoint source.