The aim of the present paper is to quantify water quality in the Lower Danube Region by using a series of multivariate techniques and the Water Quality Index (WQI). In this paper were measured 18 parameters upstream and downstream the city of Galati along the Danube River, namely: pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), N-NH4+, N-NO2−, N-NO3−, N total, P-PO43−, SO42−, Cl−, Fe-total, Cr-total, Pb2+, Ni2+, Mn2+, Zn2+, As2+, in the interval winter 2013–winter 2016. The samples were either analyzed on the field, or sent for testing to the laboratory. The physicochemical parameters mentioned above were analyzed in accordance with the Romanian and International standards in force. The WQI was calculated according to Weighted Arithmetic Water Quality Index Method. The interdependencies between the selected physicochemical parameters were used for determining potential sources of pollution. Monitoring water quality dynamics in the period mentioned above favoured a series of relevant conclusions about the anthropic influence on water quality. Water quality was assessed by processing the measurements results, by calculating the water quality index (WQI), and by using the principal component analyses (PCA) and the response surface method (RSM) with the aim of correlating the indices for the physico-chemical parameters.
Water quality indices are suitable tools used for assessing water quality because of their capacity to reduce a large number of water quality indicators into one value which defines the water quality class. In this study, Water Quality Index (WQI), Water Pollution Index (WPI) and Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) were applied in order to evaluate the seasonal and spatial variation of the water quality in the Romanian Lower Danube sector. Fourteen physico-chemical parameters, i.e., pH, DO, BOD5, COD, N-NH4+, N-NO3−, N-NO2−, N-total, P-total, SO42−, Cl−, Fe-total, Zn2+ and Cr-total, were monitored along the Danube course (on a distance of about 120 km), during the four seasons between the autumn of 2018 and the summer of 2019 in order to calculate the three indices mentioned above. Indices results showed that the water analysed was ranked into different water quality classes, although the same dataset was used. These differences were due to the contribution of each parameter taken into account in the calculation formula. Thus, the WQI scores were mostly influenced by those parameters whose maximum allowable concentration was low (e.g., heavy metals, N-NO2−), while the WPI and CCME-WQI scores were influenced by those parameters which exceeded the maximum allowable concentration (BOD5, DO, COD, N-NO3−, N-NO2−). Based on the WQI results, the water was ranked into quality classes II and III. WPI and CCME-WQI assessed water only in quality class II, with one exception in the case of CCME-WQI when water was ranked into quality class III. The temporal assessment identified the seasons in which the water quality was lower, namely summer and autumn. The variation of the indices values between the sampling stations demonstrates the existence of pollution sources in the study area. Moreover, the indices results illustrated the contribution of the main tributaries (Rivers Siret and Prut) to the Danube River water quality. The appropriate applicability of the three indices was also discussed in this study.
It is a well–known fact that heavy metal pollution in sediments causes serious problems not only in the Danube basin, but also in the large and small adjacent river streams. A suitable method for assessing the level of heavy metals and their toxicity in sediments is the calculation of pollution indices. The present research aims to assess heavy metal pollution in the Lower Danube surface sediments collected along the Danube course (between 180 and 60 km) up to the point where the Danube River flows into the Danube Delta Biosphere Reserve (a United Nations Educational, Scientific and Cultural Organization – UNESCO, protected area). In addition, this monitored area is one of the largest European hydrographic basins. Five heavy metals (Cd, Ni, Zn, Pb, Cu) were analyzed in two different seasons, i.e., the autumn of 2018 and the spring of 2019, using the Inductively Coupled Plasma Mass Spectrometry (ICP– MS) technique. Our assessment of heavy metal pollution revealed two correlated aspects: 1. a determination of the potential risks of heavy metals in sediments by calculating the Potential Ecological Risk Index (RI), and 2. an evaluation of the influence of anthropogenic activities on the level of heavy metal contamination in the surface sediments, using three specific pollution indices, namely, the Geo–Accumulation Index (Igeo), the Contamination Factor (CF), and the Pollution Load Index (PLI). The results of this pioneering research activity in the region highlighted the presence of moderate metal (Ni and Cd) pollution and a low potential ecological risk for the aquatic environment.
At present, the most commonly used method to evaluate the quality of a water stream is the application of the Water Quality Index, which may be determined by using different methods. The main purpose of this study is to describe four methods for calculating the Water Quality Index with their advantages and disadvantages: NFS-WQI (National Sanitation Foundation-Water Quality Index), OWQI (Oregon Water Quality Index), WAWQI (Weighted Arithmetic Water Quality Index) and CCME-WQI (Canadian Council of Ministers of the Environment-Water Quality Index). Choosing one of the four methods mentioned above should be based on the study purpose and on the nature of the water stream. These indices have already been used to determine the quality of the Danube water in the all the riverine states. Moreover, the present research reveals that two methods are proved to be useful in determining the Danube water quality, namely: WAWQI (Weighted Arithmetic Water Quality Index) and CCME-WQI (Canadian Council of Ministers of the Environment-Water Quality Index).
Researches and analysis of heavy metals concentrations in the fish species exploited as a food source are of great interest due to long term toxic effects on human health even at very low concentrations. Therefore, we have conducted this study in an area of great interest in terms of aquatic biodiversity, but also of tourism and trade. Depending on the degree of toxicity in delta aquatic ichtyofauna, five heavy metals (Cr, Cu, Hg, Ni, Pb) and a metalloid (As) concentrations were measured in the muscle tissue of fifteen commercial value fish species in order to assess their impact on human health. Samples were collected seasonally (twice a year) between 2013-2014 from Somova-Parches aquatic complex (situated near Tulcea -Romania industrial area in predeltaic area) and four representative aquatic complexes for Danube Delta, respectively Sontea-Fortuna, Matita-Merhei, Gorgova-Uzlina and Rosu-Puiu. The determination of elements from collected samples was done differently, mercury was analysed by cold vapor atomic absorption, while the other five elements (arsenic, chromium, copper, nickel and lead) were determined using mass spectrometry with inductively coupled plasma. The investigations of heavy metals revealed interspecific differences, important not only because of each specie particularities and food chain, but also for intraspecific variation caused by geographical location. The statistical analysis of the 4800 measurements in correlation with the analysis of the bioaccumulation factor (BCF) reflected the degree of contamination on the exploited Danube Delta Biosphere Reserve fish resources and also showed an irregular distribution of heavy metals and metalloids depending on anthropogenic pollutants.
The Waste Management activity (WM) is an urban action becoming more and more important in the municipal economy. In many cities, this activity is linked to significant revenues from the selective waste collection services. Because the current economic situation requires an increasing efficiency and profitability in order to succeed in cutting the operational costs, and as an important part of revenue comes from this selective waste collection activity, the effectiveness must be improved. In the specific case of Galati (250 000 inhabitants) which is presented in this article, the WM activity has been redesigned. The main aspect is given by the successful implementation of the selective collecting waste management system in order to succeed in reaching the current economic commands. In this article we present results obtained after 122 days of monitoring. Our approach has certain elements of novelty. Based on the data records we studied the possibility of obtaining a mathematical model which would be able to describe the time evolution of the amount of waste deposited in the collecting points. The simplest mathematical model was investigated, basing on the fact that a neural network approaching was not possible. For this purpose, we applied a set of three different methods of identifying the mathematical model which corresponds to the most accurate assessments. In the final part, is presented the related algorithm and the results obtainable by using this approach. The used procedure is based on a dynamical optimization process considering a specific Dijgistra algorithm. In this way, it could be build dynamical maps by eliminating a series of points whose contribution are not important for that moment. Finally, are presented specific results based on this dynamical optimization process.
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