DBPapers

MONITORING AND STATISTICS OF HEAVY METALS DAYLY DATA IN SURFACE WATER

AUTHOR/S: I. MEGHEA, M. MIHAI, E. CRACIUN
Sunday 1 August 2010 by Libadmin2010

10th International Multidisciplinary Scientific GeoConference - SGEM2010, www.sgem.org, SGEM2010 Conference Proceedings/ ISBN 10: 954-91818-1-2, June 20-26, 2010, Vol. 2, 677-684 pp

ABSTRACT

Specific statistical methods can be used when monitor the degree of water pollution in a
target zone. The purpose of usage of time series properties is to understand the driving
forces and structures that produce the observed data and to fit the data into a model and
proceeds them to forecasting, monitoring or even feed back and feed forward control.
The essential difference between modelling data via time series methods and using the
process monitoring methods is that in time series analysis the data points taken over
time may have internal structure such as autocorrelation, trend or seasonal variation.
This paper uses some of the time series techniques for modelling and analysis of the
daily heavy metal monitoring data measured in some important lakes of Bucharest
during March – November 2007 – 2009. The daily registration of lead, mercury and
cadmium concentrations in surfaces water form a univariate time series that consists in
single scalar observations has been recorded sequentially over equal time increments.
These time series display periodicity that represents sinusoidal fluctuations over entire
week and seasonality over the year. The seasonal pattern was consistent with a wave
sine model. The autocorrelation function was used to identify the autocorrelation
structure of series.

Keywords: times series, heavy metals monitoring, autocorrelation structure