Spatial and seasonal variation of organic pollutants in surface water using multivariate statistical techniques

The Diversity of Phytoplankton in a Combined Rice-Shrimp Farming System in the Coastal Area of the Vietnamese Mekong Delta

An assessment of varying density, species composition and dynamics of phytoplankton in a combined rice-shrimp culture was carried out in My Xuyen district, Soc Trang province in the Vietnamese Mekong delta. Water was sampled six times at six separate locations within the culture system, on days 1, 20, 34, 57, 68, and day 81 of the rice-shrimp crop cycle. The results showed the abundance of 95 phytoplankton species belonging to five phyla including Cyanophyta, Chlorophyta, Bacillariophyta, Euglenophyta, and Pyrrophyta. The values of Shannon–Wiener index indicated high phytoplankton diversity, while the water quality ranged from medium to good. A Cluster Analysis showed that the phytoplankton density variation can be divided into three distinct periods. The initial phase of crop growth was dominated by Pandorina morum, Pediastrum simplex, Eudorina elegans, Oscillatoria limosa, and Anabaena circinalis. The midstage, reproductive phase of crop growth was dominated by Scenedesnus acuminatus, Pediastrum duplex, Closterinm setaceum, Scenedesnus quadricauda, and Actinastnum hantzschii. Whereas Scenedesnus acuminatus, Scenedesnus quadricauda, Closterinm closterioides, Staurastrum arcuatum, Euglena nhrenbergii, and Phacus lnsmorensis were dominant at the end of crop cycle. The findings provide useful information on phytoplankton assemblages in a typical rice-shrimp culture, which has recently gained popularity as an adaptive livelihood system.

DNA damage of human derived liver cell line HL-7702 induced by organic extracts from surface water in Pearl River Delta, China

Many organic pollutants attract public health concern due to their genotoxicity. To investigate the genotoxicity of organic matter in surface water of the Pearl River Delta (PRD). Organic substances of 24 samples (dry and wet season) from North River, West River and East River were extracted from 60 L source water by XAD-2 macroporous resin. DNA damage effect of organic extracts was tested in human derived liver cells (HL-7702), using single cell gel electrophoresis (SCGE) assay. The results showed that 100% organic extracts (24/24) could induce DNA damage in HL-7702 cells when the concentration was above 1.0 L surface water/ml culture, no significant difference of DNA damage between dry and wet seasons was observed. The organic substance-induced DNA damage in HL-7702 cells was significantly (P < 0.05) correlated with the contents of Dissolved Organic Carbon in both seasons and Total Suspended Solids in dry season. In conclusion, organic extracts induced genetic damage in HL-7702 cells, indicating potential genotoxicity of organic pollutants of surface water from PRD, South China.

The assessment of the amount of water pollution and its suitability for drinking of the Tyśmienica River Basin, Poland

The quality and potability of waters of the Tyśmienica River Basin were determined in 2017 at eight measuring stations. The paper presents analyses of the physical and chemical parameters of surface waters of the basin. With regard to suspended solids, pH value, electric conductivity, sulphates, ammonia, chlorides and phosphate, the water was classified as having a very good ecological status. In the case of Kjeldahl nitrogen, the waters were classified as having a good ecological status. In the case of the remaining parameters, i.e. BOD, DO, TOC and COD, the status varied among stations. The values of all the physical and chemical parameters complied with the values for undisturbed conditions. Only ammonia and COD showed significant differences among stations. The WPI values for each measuring point ranged from 0.90 to 1.56, what corresponds to the descriptive indicators of moderately polluted water. The high concentrations of COD and TOC indicate that high-performance treatment processes (category A3) must be used to ensure that the water is suitable for drinking.

Monitoring and evaluating the spatiotemporal variations of the water quality of a stretch of the Bhagirathi-Hugli River, West Bengal, India, using geospatial technology and integrated statistical methods

Water quality is a critical environmental issue because all forms of life depend on the water. The present study primarily focused on the spatiotemporal trends of water quality in a section of the Bhagirathi-Hugli River, West Bengal, using geospatial technology and integrated statistical methods. For this purpose, 83 samples of 7 water parameters were analysed and compared them with Indian Standards (IS 2004), Environmental Protection Agency (EPA 2001) and World Health Organization (WHO 1993) for the protection of aquatic life and human consumption. Correlation, box and whisker plots, paired sample t test, water quality index (WQI), cluster analysis (CA) and principal component analysis (PCA) were applied as an integrated multivariate statistical approach to understanding the nature of water quality. Pollution sources were identified by PCA indicating different origins both naturally and anthropogenic sources. The box and whisker plots displayed the significantly spatiotemporal variations and concentration of the variables. The paired sample t test identified that the surface water quality varied significantly between the seasons with significant value p < 0.05. Cluster analysis grouped 83 monitoring sites into 4 clusters to identify the pollution status such as low, moderate, high and very high pollution sites. Principal component analysis confirmed that the first three PCs with eigenvalues are higher than 1 contributing 90.83% of total variability for various parameters. The conductivity, total dissolved solids (TDS), salt and pH were expressively influenced by the anthropogenic effect while the temperature, oxidation-reduction potential (ORP) and dissolved oxygen (DO) were affected by seasonal factors. Results of WQI ranged from 45.04 to 83.79, and an average value was 69.55 with 69% samples representing poor water quality for drinking and domestic purposes. It also indicates that the water quality of rural sites was better than industrial and urban sites in both seasons and also shows that it was better for the duration of the post-monsoon than pre-monsoon.

Spatiotemporal Analysis of Surface Water Quality in Dong Thap Province, Vietnam Using Water Quality Index and Statistical Approaches

The study was conducted to spatiotemporally analyze the quality, location and critical water variables influencing water quality using water monitoring data from the Department of Environment and Natural Resources, Dong Thap province in 2019. The water quality parameters including turbidity, pH, temperature, dissolved oxygen (DO), total suspended solids (TSS), biological oxygen demand (BOD), chemical oxygen demand (COD), nitrite (N-NO2−), nitrate (N-NO3−), ammonium (N-NH4+), total nitrogen (TN), orthophosphate (P-PO43−), chloride (Cl−), oil and grease, sulfate (SO42−), coliforms, and Escherichia coli (E. coli) were collected at 58 locations with the frequency of four times per year (February, May, August, and November). These parameters were compared with national technical regulation on surface water quality—QCVN 08-MT: 2015/BTNMT. Water quality index (WQI) was calculated and spatially presented by geographical information system (GIS) tool. Pearson correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the correlation among water quality parameters, group and reduce the sampling sites, and identify key parameters and potential water pollution sources. The results showed that TSS, BOD, COD, N-NH4+, P-PO43−, coliforms, and E. coli were the significant concerns impairing the water quality. Water quality was assessed from poor to medium levels by WQI analysis. CA suggested that the current monitoring locations could be reduced from 58 sites to 43 sites which can be saved the total monitoring budget up to 25.85%. PCA showed that temperature, pH, TSS, DO, BOD, COD, N-NH4+, N-NO2−, TN, P-PO43−, coliforms, and E. coli were the key water parameters influencing water quality in Dong Thap province’s canals and rivers; thus, these parameters should be monitored annually. The water pollution sources were possibly hydrological conditions, water runoff, riverbank erosion, domestic and urban activities, and industrial and agricultural discharges. Significantly, the municipal and agricultural wastes could be decisive factors to the change of surface water quality in the study area. Further studies need to focus on identifying sources of water pollution for implementing appropriate water management strategies.

Occurrence and partition of organochlorine pesticides (OCPs) in water, sediment, and organisms from the eastern sea area of Shandong Peninsula, Yellow Sea, China

To evaluate the occurrence and partition of organochlorine pesticides (OCPs), hexachlorocyclohexanes (HCHs) and dichlorodiphenyltrichloroethanes (DDTs), water, sediment, and organisms were sampled from the eastern sea area of Shandong Peninsula (Yellow Sea, China) across all four seasons in 2016. There were three OCP hotspots in the sediment, mainly caused by the transportation of lindane and dicofol from adjacent Swan Lake and Guhe River. Waterborne OCP levels were highest in winter and lowest in spring, without vertical variability, suggesting that the Yellow Sea Cold Water Mass was governing the spatio-temporal distribution of OCPs in seawater. There was substantial accumulation of HCHs and DDTs in organisms via sediment, as indicated by the relatively low fraction of sedimental fugacity, high bio-sediment accumulation factor, and a positive linear correlation between logΣHCHs and trophic level. This is the first study that has focused on the accumulation of OCPs in entire sediment-seawater-organism system involving multi-phyla of species.

Limnological Quality: Seasonality Assessment and Potential for Contamination of the Pindaré River Watershed, Pre-Amazon Region, Brazil

Watersheds are defined as a set of lands where water drainage occurs through rivers and their tributaries. A large quantity of water resources exist in the state of Maranhão, Brazil, where rivers and their basins must meet environmental quality standards defined by the limits set out in national environmental council (CONAMA) legislation 357/05 for physicochemical and microbiological parameters, including parasites. Multivariate statistical techniques were applied to study the temporal and spatial variations in water quality of a segment of the Pindaré River. The data set included nine parameters for three sampling points over eleven months. Principal component analysis grouped the monitored sampling points into four clusters and identified electrical conductivity, temperature, total dissolved solids (TDS), pH, salinity, and Escherichia coli as being associated with the dry season and nitrite, nitrate, and turbidity as being associated with the rainy season. Three principal components explained 83.80% of the data variance during the rainy and dry seasons. The evaluated correlations indicated that during the rainy season, nitrite (~0.18 mg L−1) and turbidity (~46.00 NTU) levels were the highest, but pH was at its lowest (~6.61). During the dry season, TDS (~155.00 mg L−1) and pH (~8.10) were highest, and E. coli bacteria was more abundant.

Analyzing the significant environmental factors on the spatial and temporal distribution of water quality utilizing multivariate statistical techniques: a case study in the Balihe Lake, China

The assessment of surface water quality is significant to the management of aquatic ecosystem. In this research, in Balihe Lake which is an agricultural watershed lake, 11 environmental parameters (pH, water temperature, water depth, turbidity, DO, COD, TN, NH₄⁺-N, NO₃^--N, TP, Chl-a) are monitored at 45 sampling sites in four seasons (winter of 2016, spring, summer, and autumn of 2017). With these monitoring data, two kinds of multivariate statistical methods including cluster analysis (CA) and principal component analysis (PCA) are applied to evaluate the spatial and temporal characteristics of the surface water quality. The results reveal that the spatial clusters (less, moderately, and highly polluted sections) of 45 sampling sites classified by the CA method are exactly consistent with the geographical distribution of these sampling sites, which rely on water quality meliorating downstream. From the perspective of time scale, the correlations between environmental parameters generated by the PCA method reveal that the main factors affecting the surface water quality are different in the four seasons. For the whole study period, which is a longer time scale rather than season, the main factors are also different to that of any season. Large time scale may weaken the effect and potential risk of nutrients on water quality, and it is therefore reasonable to select seasonal scale for the study of water quality in an agricultural watershed by using PCA. The results of this research may demonstrate significance to the identification of the main pollution factors and water quality assessment in freshwater lake with multivariate statistical methods.

Spatial and temporal variation of water quality of a segment of Marikina River using multivariate statistical methods

Payatas landfill in Quezon City, Philippines, releases leachate to the Marikina River through a creek. Multivariate statistical techniques were applied to study temporal and spatial variations in water quality of a segment of the Marikina River. The data set included 12 physico-chemical parameters for five monitoring stations over a year. Cluster analysis grouped the monitoring stations into four clusters and identified January-May as dry season and June-September as wet season. Principal components analysis showed that three latent factors are responsible for the data set explaining 83% of its total variance. The chemical oxygen demand, biochemical oxygen demand, total dissolved solids, Cl^- and PO₄^3- are influenced by anthropogenic impact/eutrophication pollution from point sources. Total suspended solids, turbidity and SO₄^2- are influenced by rain and soil erosion. The highest state of pollution is at the Payatas creek outfall from March to May, whereas at downstream stations it is in May. The current study indicates that the river monitoring requires only four stations, nine water quality parameters and testing over three specific months of the year. The findings of this study imply that Payatas landfill requires a proper leachate collection and treatment system to reduce its impact on the Marikina River.