Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India)

The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. Highlights ? The effectiveness of existing river water quality monitoring network is assessed ? Significance of seasonal redesign of the monitoring network is demonstrated ? Rationalization of water quality parameters is performed in a statistical framework     

Macroinvertebrate community as a biological indicator of ecological and toxicological factors in Lake Saint-François (Québec)

To assess the potential of the macroinvertebrate community for monitoring variation in the environmental quality of large rivers, the response of littoral macrobenthos in Lake Saint-Fran?ois, a fluvial lake of the St Lawrence River (Québec) are described. First, the composition of total macroinvertebrate communities and important taxonomic groups as well as the biotic ICI-SL index in 16 littoral stations varying in sedimentology, water chemistry and contamination are described to define indicator species groups and environmental quality ranks. Thereafter, the relative contribution of ecological and toxicological factors in explaining the variation observed in macroinvertebrate assemblages and biotic index were quantified using partial canonical correspondence analysis. Cluster analyses based on taxonomic composition separated five groups of stations where macroinvertebrate assemblages varied in density, composition and tolerance to pollution. The ICI-SL biotic index varied from 7.2 to 27.2 with a mean value of 19 +/- 6. The ICI-SL values determined for the macroinvertebrate communities in Lake Saint-Fran?ois did not reflect an important deterioration in environmental quality, and there was some agreement between the environmental quality ranking of the stations expressed either by the ICI-SL index or the community cluster analysis. Water conductivity and phosphorus concentration, followed by macrophyte types (Chara, Ceratophyllum) and sediment grain size, were the most significant ecological variables to explain variation in macroinvertebrate communities and derived ICI-SL index in Lake Saint-Fran?ois. Among the toxicological factors, metals in water (Fe, Cr, Pb, Mn, Zn) and sediment (Mn, Pb, Se), as well as the composite indices of metal and organic contamination (water CI, sediment CI, sediment total PAHs) were the most important factors. The contamination factors selected in our models represented contaminant sorption processes rather than direct toxicological effects. The lack of clear relationships between contaminants and macroinvertebrate variables reflected the relative low level of contamination in the stations sampled in Lake Saint-Fran?ois. There were some interactions between toxicological and ecological variables that should be considered in the planning of sampling and interpretation of biomonitoring studies. However, the large amount of unexplained variance (49.2-86.6%) in the CCA models underlined the limitations of the use of the indices of macroinvertebrate community structure that were assessed in this study for biomonitoring purposes in the absence of a contrasting pollution gradient.     

Heavy metal contamination in sediments of an artificial reservoir impacted by long-term mining activity in the Almadén mercury district (Spain)

Sediments from the Castilseras reservoir, located downstream on the Valdeazogues River in the Almadén mercury district, were collected to assess the potential contamination status related to metals(oids) associated with river sediment inputs from several decommissioned mines. Metals(oids) concentrations in the reservoir sediments were investigated using different physical and chemical techniques. The results were analyzed by principal component analysis (PCA) to explain the correlations between the sets of variables. The degree of contamination was evaluated using the enrichment factor (EF) and the geoaccumulation index (Igeo). PCA revealed that the silty fraction is the main metals(oids) carrier in the sediments. Among the potentially harmful elements, there is a group (Al, Cr, Cu, Fe, Mn, Ni, and Zn) that cannot be strictly correlated to the mining activity since their concentrations depend on the lithological and edaphological characteristics of the materials. In contrast, As, Co, Hg, Pb, and S showed significant enrichment and contamination, thus suggesting relevant contributions from the decommissioned mines through fluvial sediment inputs. As far as Hg and S are concerned, the high enrichment levels pose a question concerning the potential environmental risk of transfer of the organic forms of Hg (mainly methylmercury) from the bottom sediments to the aquatic food chain.     

Satellite-based decadal change assessments of pan-Arctic environments

Remote sensing can advance the work of the Circumpolar Biodiversity Monitoring Program through monitoring of satellite-derived terrestrial and marine physical and ecological variables. Standardized data facilitate an unbiased comparison across variables and environments. Using MODIS standard products of land surface temperature, percent snow covered area, NDVI, EVI, phenology, burned area, marine chlorophyll, CDOM, sea surface temperature, and marine primary productivity, significant trends were observed in almost all variables between 2000 and 2017. Analysis of seasonal data revealed significant breakpoints in temporal trends. Within the terrestrial environment, data showed significant increasing trends in land surface temperature and NDVI. In the marine environment, significant increasing trends were detected in primary productivity. Significantly earlier onset of green up date was observed in bioclimate subzones C&E and longer end of growing season in B&E. Terrestrial and marine parameters showed similar rates of change with unidirectional change in terrestrial and significant directional and magnitude shifts in marine.     

Assessment of metal pollution based on multivariate statistical modeling of 'hot spot' sediments from the Black Sea

The paper deals with application of different statistical methods like cluster and principal components analysis (PCA), partial least squares (PLSs) modeling. These approaches are an efficient tool in achieving better understanding about the contamination of two gulf regions in Black Sea. As objects of the study, a collection of marine sediment samples from Varna and Bourgas "hot spots" gulf areas are used. In the present case the use of cluster and PCA make it possible to separate three zones of the marine environment with different levels of pollution by interpretation of the sediment analysis (Bourgas gulf, Varna gulf and lake buffer zone). Further, the extraction of four latent factors offers a specific interpretation of the possible pollution sources and separates natural from anthropogenic factors, the latter originating from contamination by chemical, oil refinery and steel-work enterprises. Finally, the PLSs modeling gives a better opportunity in predicting contaminant concentration on tracer (or tracers) element as compared to the one-dimensional approach of the baseline models. The results of the study are important not only in local aspect as they allow quick response in finding solutions and decision making but also in broader sense as a useful environmetrical methodology.     

Identification of redundant air quality measurements through the use of principal component analysis

This study aims to show how principal component analysis (PCA) can be used to identify redundant measurements in air quality monitoring networks. The minimum number of air quality monitoring sites in Oporto Metropolitan Area (Oporto-MA) was evaluated using PCA and then compared to the one settled by the legislation. Nine sites, monitoring NO₂, O₃ and PM₁₀, were selected and the air pollutant concentrations were analysed from January 2003 to December 2005. PCA was applied to the data corresponding to the first two years that were divided into annual quarters to verify the persistence of the PCA results. The number of principal components (PCs) was selected by applying two criteria: Kaiser (PCs with eigenvalues greater than 1) and ODV₉₀ (PCs representing at least 90% of the original data variance). Each pollutant was analysed separately. The two criteria led to different results. Using Kaiser criterion for the eight analysed periods, two PCs were selected in: (i) five periods for O₃ and PM₁₀; and (ii) six periods for NO₂. These PCs had important contributions of the same groups of monitoring sites. The percentage of the original data variance contained in the selected PCs using this criterion was always below 90%. Thus, the results obtained using ODV₉₀ were considered with more confidence. Using this criterion, only five monitoring sites for NO₂, three for O₃ and seven for PM₁₀ were needed to characterize the region. The number of monitoring sites for NO₂ and O₃ was in agreement with what was established by the legislation. However, for PM₁₀, Oporto-MA needed two more monitoring sites. To validate PCA results, statistical models were determined to estimate air pollutant concentrations at removed monitoring sites using the concentrations measured at the remaining monitoring sites. These models were applied to a year's data. The good performance obtained by the models showed that the monitoring sites selected by the procedure presented in this study were enough to infer the air pollutant concentrations in the region defined by the initial monitoring sites. Additionally, the air pollutant analysers corresponding to the redundant measurements can be installed in non-monitored regions, allowing the enlargement of the air quality monitoring network.     

Ecological risk assessment of heavy metals and polycyclic aromatic hydrocarbons in sediments of rivers Niger and Benue confluence,Lokoja, Central Nigeria

The concentrations of six heavy metals (HMs) and 16 US EPA priority polycyclic aromatic hydrocarbons (PAHs) in sediment samples of the confluence of rivers Niger and Benue were investigated. The ecological risk assessment of the contaminants was carried out. The results showed that the sediment samples were heavily polluted with iron and moderately polluted with Cd while other metals posed no pollution problem when compared with USEPA sediment quality guidelines. Only six out of the 16 priority PAHs were detected in the samples, and source apportionment of the PAHs indicated that they are of pyrogenic origin. The ∑PAHs in the samples were lower than many of similar studies and were of no pollution risk. The ecological risk assessment result of the heavy metals showed that the sediments were of considerable risk due majorly to Cd levels. The HM concentration results statistically showed significant difference between seasons at probability value (P < .05). Data analysis by PCA classified the metals into three different components according to sources. The levels of HMS and PAHs detected in the sediments were correlated for source identification, and the correlation showed that the majority of the pollutants were mainly from anthropogenic sources. There is increasing level of anthropogenic activities at the vicinity of the confluence due to urbanization which may call for periodic monitoring of the sediment quality.     

Multivariate analysis of Almendares River waters.

The Almendares River is the most important surface water body of the Cuban capital, Havana. In the present work, the environmental quality of waters was studied as a function of the following 14 variables: content of calcium, cadmium, iron, potassium, magnesium, manganese, sodium, nickel, zinc, chlorine, bicarbonate, and sulfate; pH; and electric conductivity parameters, which were reduced to three new variables by means of principal component analysis (PCA). The content of metal increased in waters sampled at stations located near garbage dumps and decreased inside the Ejercito Rebelde dam. The variation of the river water environmental quality with rainy and dry seasons and the differentiation of samples in three groups along the river course were obtained by PCA and corroborated by discriminant analysis. Applied statistical techniques showed their ability for environmental interpretation of limited experimental data.     

Factors influencing the variability of SO2 concentrations in Istanbul

The correlation between sulfur dioxide (SO2) concentrations measured at the European and Asian sides of Istanbul and meteorological parameters is investigated using principal component analysis (PCA) and multiple regression analysis techniques. Several meteorological parameters are selected to represent the atmospheric conditions during two winter periods: 1993-1994 and 1994-1995. Six principal components are found to explain the majority of the observed meteorological variability. Surface pressure, 850-mb temperature, and surface zonal (east-west) and meridional (north-south) winds show high loadings on separate factors identified by PCA. We seek dominant meteorological parameters that control the SO2 levels at each monitoring station. Several multiple regression analysis models are fitted to the data from each monitoring station using six principal components and previous-day SO2 concentrations as independent variables. Results suggest that the most important parameters, highly correlated with SO2 concentrations in the Istanbul metropolitan area, are atmospheric pressure and surface zonal and meridional winds. These components have more influence on the determination of the air pollution levels at the Asian side than at the European side.     

Investigating hydrochemistry of groundwater in Indo-Gangetic alluvial plain using multivariate chemometric approaches

Groundwater hydrochemistry of an urban industrial region in Indo-Gangetic plains of north India was investigated. Groundwater samples were collected both from the industrial and non-industrial areas of Kanpur. The hydrochemical data were analyzed using various water quality indices and nonparametric statistical methods. Principal components analysis (PCA) was performed to identify the factors responsible for groundwater contamination. Ensemble learning-based decision treeboost (DTB) models were constructed to develop discriminating and regression functions to differentiate the groundwater hydrochemistry of the three different areas, to identify the responsible factors, and to predict the groundwater quality using selected measured variables. The results indicated non-normal distribution and wide variability of water quality variables in all the study areas, suggesting for nonhomogenous distribution of sources in the region. PCA results showed contaminants of industrial origin dominating in the region. DBT classification model identified pH, redox potential, total-Cr, and λ ₂₅₄ as the discriminating variables in water quality of the three areas with the average accuracy of 99.51 % in complete data. The regression model predicted the groundwater chemical oxygen demand values exhibiting high correlation with measured values (0.962 in training; 0.918 in test) and the respective low root mean-squared error of 2.24 and 2.01 in training and test arrays. The statistical and chemometric approaches used here suggest that groundwater hydrochemistry differs in the three areas and is dominated by different variables. The proposed methods can be used as effective tools in groundwater management.     

Toxicity of sediment cores from Yangtze River estuary to zebrafish (<Emphasis Type="Italic">Danio rerio</Emphasis>) embryos

Toxicity evaluation is an important segment in sediment quality monitoring in order to protect aquatic organisms and human health. The purpose of this study is to assess the toxicity of sediments from three sediment cores in Yangtze River Estuary, China, using the zebrafish (Danio rerio) embryo tests. Fertilized zebrafish eggs were exposed to both whole sediments and sediment organic extracts prepared from collected sediments, in order to provide a comprehensive and realistic insight into the bioavailable toxicity potential of the sediments. As end points, development parameters (mortality, hatching rate, and abnormality) in the developing embryos were recorded during the 96-h exposure. The results showed that some samples increased mortality, inhibited the hatching of embryos, and induced morphological abnormalities. The embryonic toxicities presented serrated changes and irregular distribution with depth, which may be related to hydrodynamic effect and unstable environmental input. However, lethal and sub-lethal effects were more significant at the sub-surface sediments (10～40 cm), which indicated that the pollution is more serious in recent decades.     

Factors Influencing the Variability of SO2 Concentrations in Istanbul

ABSTRACT

The correlation between sulfur dioxide (SO₂) concentrations measured at the European and Asian sides of Istanbul and meteorological parameters is investigated using principal component analysis (PCA) and multiple regression analysis techniques. Several meteorological parameters are selected to represent the atmospheric conditions during two winter periods: 1993–1994 and 1994–1995. Six principal components are found to explain the majority of the observed meteorological variability. Surface pressure, 850-mb temperature, and surface zonal (east-west) and meridional (north-south) winds show high loadings on separate factors identified by PCA. We seek dominant meteorological parameters that control the SO₂ levels at each monitoring station. Several multiple regression analysis models are fitted to the data from each monitoring station using six principal components and previous day SO₂ concentrations as independent variables.

Results suggest that the most important parameters, highly correlated with SO₂ concentrations in the Istanbul metropolitan area, are atmospheric pressure and surface zonal and meridional winds. These components have more influence on the determination of the air pollution levels at the Asian side than at the European side.     

Designing ambient particulate matter monitoring program for source apportionment study by receptor modeling

Particulate matter (PM) receptor modeling requires specific intensive input data that is always a challenge to produce cost effectively. A well-designed monitoring program is important to collect such PM ambient data in urban areas with diverse and densely distributed sources. This paper presents a general framework for designing such a monitoring program while emphasizing appropriate quality assurance and quality control elements that are particularly applicable where limited resources are available. Topics for discussion include selection of monitoring sites, sampling and analytical techniques, and the uncertainty estimation for ambient concentration input data. The design framework is illustrated by a case study of a monitoring program for PM source apportionment in the Bangkok Metropolitan Region in which 24-h fine and coarse PM samples were collected using two collocated dichotomous samplers. Comparison between black carbon measurements by Smoke Stain reflectometry and Thermal Optical Transmittance method is highlighted.     

Characterization of surface marine sediments from Ría de Arousa estuary according to extractable humic matter content

Surface marine sediments from Ría de Arousa estuary were analyzed for humic and fulvic acids by UV-visible spectrometry and have been characterized using elemental analysis (carbon, hydrogen and nitrogen elemental composition) and spectrometric data (A2/A4 ratio, absorbancies at 270 and 407 nm and E4/E6 ratio, absorbancies at 465 and 665 nm). These variables have been used as discriminating factors to distinguish of marine and terrestrial origin of humic and fulvic acids in Ría de Arousa surface marine sediments. Principal component analysis, PCA, and cluster analysis, CA, have been used as unsupervised pattern recognition procedures. The half-range central value transformation was used as data pre-treatment to homogenize data. After a Varimax rotation, PCA applied to humic acid data has reveled that spectrometric A2/A4 and E4/E6 ratios are the main dominating features in the first principal component (48.6% of total variance), the humic acid content is the feature with the highest weight in the second principal component (22.9% of the total variability) and the carbon elemental composition domain in the third principal component (13.3% of total variance). Results from PCA have revealed that surface sediments collected at inner-left part of the estuary and at the mouth of the river Ulla belong to the same group. Similarly, PCA has shown that surface sediments from the right mouth of the estuary form a compact group. Taking in account the water circulation in Ría de Arousa estuary, these findings mean that the organic matter in surface sediments from the inner-left part of the estuary derived mainly from terrestrial organic matter while the organic matter in surface sediments from the right mouth of the estuary is mainly derived from marine sources. Finally, it must be noticed that any classification of surface sediments was assessed when applying of PCA and CA from fulvic acids data.     

Analysis of marine sediment, water and biota for selected organic pollutants

The concentrations of various organic pollutants (benzo(a)pyrene (BaP), hexachlorobenzene (HCB) and pentachlorophenol (PCP)) were determined in samples of water, sediment and biota (flounder, killifish, shrimp, crabs and squid) from San Luis Pass, Texas. Sediment was also analyzed for polychlorinated biphenyls (PCBs), phthalic acid esters (PAEs) and various pesticides. Only PCP was detectable in water. In sediment, the relative concentrations were PAEs > BaP > (PCBs HCB) > PCP. In biota, BaP was not detectable in any animal; HCB was highest in crabs and PCP was highest in all others (flounder, killifish, shrimp and squid). The relative concentrations of HCB and PCP were different in the different organisms. The differences between the relative concentrations in the biota and in sediment are discussed. The results of this study are compared to values measured at other sites. This study is part of a larger effort to identify and quantitate pollutants in various Texas estuaries and to serve as a basis for monitoring marine pollution.     

Spatial distribution and source apportionment of water pollution in different administrative zones of Wen-Rui-Tang (WRT) river watershed, China

Water quality degradation in river systems has caused great concerns all over the world. Identifying the spatial distribution and sources of water pollutants is the very first step for efficient water quality management. A set of water samples collected bimonthly at 12 monitoring sites in 2009 and 2010 were analyzed to determine the spatial distribution of critical parameters and to apportion the sources of pollutants in Wen-Rui-Tang (WRT) river watershed, near the East China Sea. The 12 monitoring sites were divided into three administrative zones of urban, suburban, and rural zones considering differences in land use and population density. Multivariate statistical methods [one-way analysis of variance, principal component analysis (PCA), and absolute principal component score—multiple linear regression (APCS-MLR) methods] were used to investigate the spatial distribution of water quality and to apportion the pollution sources. Results showed that most water quality parameters had no significant difference between the urban and suburban zones, whereas these two zones showed worse water quality than the rural zone. Based on PCA and APCS-MLR analysis, urban domestic sewage and commercial/service pollution, suburban domestic sewage along with fluorine point source pollution, and agricultural nonpoint source pollution with rural domestic sewage pollution were identified to the main pollution sources in urban, suburban, and rural zones, respectively. Understanding the water pollution characteristics of different administrative zones could put insights into effective water management policy-making especially in the area across various administrative zones.     

Temporal variability of bioavailable Cd,Hg, Zn,Mn and Al in an upwelling regime

Monthly variability of Cd, Hg, Zn, Mn and Al concentrations in mussels (Mytilus californianus) soft tissue and brown seaweed (Macrocystis pyrifera) was studied at a pristine rocky shore off San Quintin Bay, Baja California, México. The results were related to climatic and hydrographic conditions and to the physiological state of the mussels (condition index) by correlation analysis and principal component analysis (PCA). A "normalization" to account for the variability induced by the physiological state of the mussel was performed. The PCA was performed in two ways to relate the environmental variables and the condition index to: (1) the metal concentrations in mussels, and (2) the "normalized" mussel concentrations. The association of the variability of Cd with the upwelling season was revealed in both PCAs. The temporal variability of this metal in mussels was highly correlated to that in seaweed, suggesting that the dissolved phase determined the variability of Cd in mussels. However, for Hg, Zn, Mn and Al the results from both PCAs were different. The first PCA showed the relationship of these metals to pluvial precipitation and to the condition index. The PCA for the normalized mussel concentrations showed that, after eliminating the effect of the condition index, only Al was related to pluvial precipitation. Manganese, and to a less degree Zn, were related to these metals in seaweed. Because zinc is an essential element in mussels, some regulation of their internal concentrations is likely. Mercury was not detected in seaweed, but because of its reactive nature, it is not expected that the dissolved fraction could be a significant pathway; therefore, it can be concluded that its temporal variability was determined by the variability in the condition index only.     

Distribution,Sources, and Possible Adverse Biological Effects of Trace Metals in Surface Sediments of a Tropical Estuary

Metal (Cu, Zn, Pb, Cd, Ni, Co, and Fe) contamination in sediments from a tropical estuary (Ébrié Lagoon, Ivory Coast) was assessed using pollution indices, multivariate analyses and sediment quality guidelines (SQGs). The results demonstrate that increased input of the studied metals occurred over the past 6 years compared to that from 20 years ago, due to rapid population growth, along with the increase of industrial and agricultural activities in the vicinity of the estuary. Ébrié Lagoon was also found to be one of the most contaminated tropical coastal estuaries. Very high average total organic carbon (TOC) content was found (1.9–3.70%) with significant spatial variation as a result of the influence of anthropogenic activities. This study also found that TOC plays an important role in the distribution of Cu, Zn, Co, and Cd in the Ébrié Lagoon sediments. Moderate to high sediment contamination was observed for Cd and Cu, moderate contamination was observed for Zn and Pb, while low contamination was observed for Ni, Co, and Fe. Cluster analysis (CA) and principal component analysis (PCA) investigation revealed that Cu, Zn, Cd, and Co result mainly from anthropogenic sources while Pb, Ni, and Fe may be of natural origin. The pollution-loading index (PLI) indicated that all of the sites close to wastewater discharges were highly polluted. The sediments are likely to be an occasional threat to aquatic organisms due to Cu, Zn, Pb, Cd, and Ni contents, based on the SQGs approach.     

Sediment quality guidelines: challenges and opportunities for improving sediment management

During the International Conference on Deriving Environmental Quality Standards for the Protection of Aquatic Ecosystems held in Hong Kong in December 2011, an expert group, comprising scientists, government officials, and consultants from four continents, was formed to discuss the important scientific and regulatory challenges with developing sediment quality guidelines (SQGs). We identified the problems associated with SQG development and made a series of recommendations to ensure that the methods being applied were scientifically defensible and internationally applicable. This document summarizes the key findings from the expert group. To enable evaluation of current SQG derivation and application systems, a feedback mechanism is required to communicate confounding factors and effects in differing environments, while field validation is necessary to gauge the effectiveness of SQG values in sediment quality assessments. International collaboration is instrumental to knowledge exchange and method advancement, as well as promotion of ‘best practices’. Since the paucity of sediment toxicity data poses the largest obstacle to improving current SQGs and deriving new SQGs, a standardized international database should be established as an information resource for sediment toxicity testing and monitoring data. We also identify several areas of scientific research that are needed to improve sediment quality assessment, including determining the importance of dietary exposure in sediment toxicity, mixture toxicity studies, toxicity screening of emerging chemicals, how climate change influence sediments and its biota, and possible use of new toxicity study approaches such as high throughput omic-based toxicity screenings.