Statistical Study on Pollution of Surface Waters in Bucharest

Daily variation of heavy metal contamination and its potential sources along the major urban wastewater channel in Kampala, Uganda

“…Similarly to this study, they also found peak values that spiked from 1 day to the other, mostly on Mondays (Rule et al 2006). In another study of heavy metal pollution of urban rivers in Romania, a 7-day periodicity with lower Hg levels on the weekend has been found (Meghea et al 2012).…”

“…These concentrations were considerable different to another study 5 years later which measured Pb levels between 0.1 and 3.0 mg/L, even though the samples were taken at the same location and season (Fuhrimann et al 2015). These differences may be explained by a number of factors, such as varying rainfall patterns and long-term changes in industrial activities, but could also be due to short-term peaks introduced by daily and diel fluctuations of industrial wastewater generation or discharge (Rule et al 2006;Nimick et al 2011;Meghea et al 2012;Camacho-Muñoz et al 2014;Kao et al 2017;Swain and Sahoo 2017).…”

“…While these studies point at considerable seasonal fluctuations of these pollutants, little is known about their daily variation. The few studies assessing daily variations of heavy metals in urban wastewater have a strong focus on cities in high-and middle-income countries in Europe (Rule et al 2006;Meghea et al 2012;Deycard et al 2014). Hence, there is a lack of published literature on the daily variation of heavy metals in urban wastewater streams in low-income settings, such as Kampala, Uganda.…”

Statistical Methods and Models for Pollutant Control in Municipal Surface Waters

“…The author of this work used statistical methods in environmental monitoring, especially for atmospheric evaluation in [35][36][37][38][39][40][41] and control of water pollutants, in [42][43][44]. As specific methods applied in cited works, we can highlight the demonstrations that the analyzed data are under statistical control and use the most involved model of time series, with a lot of important properties of this powerful instrument.…”

“…In this paper, data, methods, and models from previous papers [42][43][44] are analyzed and discussed in order to deepen and systematize appropriate instruments and procedures to control the pollution of surface waters in or near a big town. The data collected for certain pollutants in two periods of time and analyzed in the above three cited papers, together with the statistical methods used there, have been discussed and compared in order to highlight mathematical models that can govern such phenomena, to capitalize on some statistical instruments that can be used to control such processes.…”