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BACKGROUND: Water, as a natural resource, is the most basic substance of life that has immeasurable significance for the living world, ecosystems, and planet Earth. It is consumed by plants, animals, and humans.
AIM: We aimed to preform a trend analysis of total affected quantities of water and total discharged wastewater (TDWW) of Nišava district...
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Water, as a natural resource, is the most basic substance of life that has immeasurable significance for the living world, ecosystems, and planet earth. In this paper, a prediction of delivered quantities of drinking water (DQDW) and total discharged wastewater (TDWW) of the Nišava district (Serbia) for the period 2019-2023 is given. The prediction...
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... Natural resources (NR) are raw organic materials or substances, found in nature and representing the general natural wealth with its usable value for industrial production and/or consumption [1], [2], [3], [4], [5]. Statistical analysis of different NR is given in papers [6], [7], [8], [9]. ...
... Population in Nišava district was 381.757 (187.780 and 193.977, men and women, respectively) in 2002 and in 2018 it was 362.331 [26], which is less for 19.426 or CAGR=-0.33% and CGI=94.91% [1]. For the prediction of DQDW and total discharged waste-water (TDWW) of Nišava district (Serbia) for the period 2019-2023, polynomial regression models (PRM) are used. ...
... In Table 1, data are given about total affected quantities of water (TAQW), DQDW, and total discharged waste-water (TDWW) for Nišava district (Serbia) for the period 2006-2018 [1], [22], [22], [23], [24], [25], [26]. ...
Water, as a natural resource, is the most basic substance of life that has immeasurable significance for the living world, ecosystems, and planet earth. In this paper, a prediction of delivered quantities of drinking water (DQDW) and total discharged wastewater (TDWW) of the Nišava district (Serbia) for the period 2019-2023 is given. The prediction for DQDW for the period 2019-2023 was made based on linear regression model, quadratic regression model, and cubic regression model according to which the data on DQDW of the Nišava district (Serbia) for the period 2006-2018 were approximated. The prediction for TDWW for the period 2019–2023 was done based on the 4th-degree polynomial regression model, the 5th-degree polynomial regression model, and the 6th-degree polynomial regression model by which the DQDW data were approximated of the Nišava district (Serbia) for the period 2006–2018. The presented prediction is a continuation of the paper “Trend analysis of total affected water and total discharged wastewater of the Nišava district (Serbia)” by the same author, in which for data on DQDW and TDWW of the Nišava district (Serbia) for the period 2006–2018 trend analysis and selected regression models have been shown.
How to cite this article:
Pavićević, N.: Prediction of delivered quantities of drinking water and discharged wastewater of the Nišava district (Serbia). Open Access Macedonian Journal of Medical Sciences (OAMJMS), Vol. 8, No. E (December 2020), pp. 664–669. eISSN 1857-9655. doi: 10.3889/oamjms.2020.5561.
Rising trend of solid waste production particularly in town and city areas has caused numerous environmental pollutions. Population growth, economic and lifestyle patterns are the factors that lead to the alarming rate of solid waste production. Landfilling is widely used for disposal of wastes due to its low operation and maintenance costs. However, leachate discharged from landfill could be a problem to surface and groundwater if it is not adequately treated. So, the investigation of the transportation and transformation phenomena of micro pollutants along the river receiving discharge from landfill leachate is mandatory. This study is carried out to investigate the water quality as well as to detect the presence of endocrine disrupting compounds (EDCs) along Kinta river in Peninsular Malaysia. Water quality parameters i.e. biological oxygen demand, chemical oxygen demand, ammoniacal nitrogen, total suspended solids, dissolved oxygen and pH were recorded to calculate the water quality index (WQI). The identification of EDCs was carried out using gas chromatography–mass spectrometry analysis. Water quality index result showed that the status of the river in both months fall under good and medium status where it requires intensive/conventional treatment for consumable and drinking purposes. None of the EDCs was detected in any of the samples analysed in the present study. It is believed that the information gained are useful and beneficial for decision making authority.
