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STATISTICAL STUDY ON POLLUTION OF SURFACE WATERS IN BUCHAREST

Assoc. Prof. Dr. Irina Meghea, Prof. Dr. Mihaela Mihai

First published: 2017-06-20https://doi.org/10.5593/sgem2017/52/s20.108View metrics

Abstract

In this study are presented and analyzed data resulted from monitoring of ions concentration: NO??, NO?? and PO?пїЅ? in surface waters from Bucharest during 2013 пїЅ 2016 period. The concentrations of these ions are an important indicator of the degree of eutrophication of lakes. The monitored surface waters are formed of 12 lakes rezulted by systematizing of Colentina River. The sources of pollution with nitrates and phosphates are coming from economic activities around lakes, from urban transport, and the initial pollution of the river Colentina. The statistical analysis of monitoring concentrations data of these ions, showed that they form time series. The main properties of these time series were determined. For all the lakes, time series data show the linear trend and seasonality. Based on the obtained data, a method for modeling the time series was proposed to forecast the evolution of the pollution of those surface waters. Another direction of data analysis aimed to establish whether there is a significant statistical difference among the concentrations of these pollutants in the surface waters analyzed. In this regard, the t test - two samples assuming equal variances from Excel was performed and the results showed that the pollution degrees of the lakes are similar, except for water surfaces from the beginning and the end of the lake chain. For these lakes, besides the mentioned sources, the agricultural activity also contributes to their pollution.

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Publication details

Title
STATISTICAL STUDY ON POLLUTION OF SURFACE WATERS IN BUCHAREST
Authors
Assoc. Prof. Dr. Irina Meghea, Prof. Dr. Mihaela Mihai
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 17th International Multidisciplinary Scientific GeoConference SGEM2017, Ecology, Economics, Education and Legislation
Publisher
STEF92 Technology
Year
2017
Pages
843-850
SWS Citekey
Meghea201720843850
ISSN
1314-2704
ISBN
978-619-7408-09-6
Language
en
Publication type
Conference Paper
Keywords
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