**8. The multiregression analyze**

Correlations were also calculated between main pollutants of: surface water and ground water, surface water and wastewater, ground water and wastewater. Their values (0.695 ÷ 0,986) emphasize the strong interdependence between pollutants matrices. The correlations calculated between the main pollutants identified in national water supply during a five years period, 2005 – 2009, deliver a complex picture of the water quality in Romania. Surface water quality is most affected by the discharge of untreated or inadequately treated sewage. In this context, a key measure to protect surface water quality is to increase wastewater treatment, upgrading and improving the cleaning process (tables 11 – 15).


between Cl and nitrogen compounds (0.654), statistically distinct significant (P < 0.01). Between S, Pb, pesticides and nitrogen compounds were identified average correlation coefficients statistically significant (P < 0.05), with values within the interval 0.523 – 0.553

Phosphates 1.000 0.217ns 0.185ns 0.238ns 0.325ns 0.388ns 0.235ns 0.325ns 0.461ns Cl 1.000 0.795\*\*\* 0.856\*\*\* 0.865\*\*\* 0.845\*\*\* 0.835\*\*\* 0.917\*\*\* 0.920\*\*\* S 1.000 0.825\*\*\* 0.887\*\*\* 0.811\*\*\* 0.822\*\*\* 0.911\*\*\* 0.921\*\*\* Pb 1.000 0.869\*\*\* 0.901\*\*\* 0.905\*\*\* 0.908\*\*\* 0.799\*\*\* Cd 1.000 0.900\*\*\* 0.847\*\*\* 0.920\*\*\* 0.816\*\*\* Hg 1.000 0.891\*\*\* 0.915\*\*\* 0.836\*\*\* As 1.000 0.887\*\*\* 0.827\*\*\*

Pesticides 1.000

The correlation coefficients calculated in 2009 for the groundwater pollutants (Table 10), revealed very strong positive correlations, statistically very significant (P < 0.001) between phosphates and nitrogen compounds (0.917; R2 = 0.841), and also between Cl, S, Pb, Cd, Hg, As, oil products, pesticides (0.921 – 0.795), with an average R2 = 0.783. Weak positive correlations, statistically not significant (P > 0.05) were identified between Cl, S, Pb, Cd, Hg, As, oil products, pesticides and phosphates (0.185 – 0.461), and also between Cd, Hg, As, oil products and nitrogen compounds (0.298 – 0.453), while between Cl and nitrogen compounds, statistically distinct significant (P < 0.01) correlation was found (0.629), and average positive correlations (0.558, and 0.629 respectively), statistically significant (P < 0.05),

Correlations were also calculated between main pollutants of: surface water and ground water, surface water and wastewater, ground water and wastewater. Their values (0.695 ÷ 0,986) emphasize the strong interdependence between pollutants matrices. The correlations calculated between the main pollutants identified in national water supply during a five years period, 2005 – 2009, deliver a complex picture of the water quality in Romania. Surface water quality is most affected by the discharge of untreated or inadequately treated sewage. In this context, a key measure to protect surface water quality is to increase wastewater treatment, upgrading and improving the cleaning

Table 10. The correlation matrix between main pollutant components of groundwater in

Phosphates Cl S Pb Cd Hg As Oil

1.000 0.917\*\*\* 0.629\*\* 0.558\* 0.541\* 0.426ns 0.453ns 0.298ns 0.432ns 0.511\*

1.000 0.921\*\*\*

products

Pesticides

(Table 9).

Nitrogen compounds

> Oil products

2009 (mg/L)

Issue Nitrogen

compounds

between S, Pb and nitrogen compounds (Table 9).

**8. The multiregression analyze** 

process (tables 11 – 15).


I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb; X – Hg; XI – As; XII - oil products; XIII - pesticides

Table 11. The correlation matrix between main pollutant components of surface water, groundwater and wastewater in 2005

Evolution of Water Quality in Romania 153

Surface water

I II III IV V VI VII VIII IX X XI XII XIII

Issue Groundwater

I 0.958

I 0.732

II 0.711

III 0.699

IV 0.811

V 0.758

X – Hg; XI – As; XII - oil products; XIII - pesticides

groundwater and wastewater in 2007

VI 0.698

VII 0.699

VIII 0.759

IX 0.775

X 0.783 XI 0.772

XII 0.748

I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb;

Table 13. The correlation matrix between main pollutant components of surface water,

XIII 0.757

II 0.842

III 0.917

IV 0.851

V 0.927

VI 0.968

VII 0.942

VIII 0.959

IX 0.963

X 0.895 XI 0.882

XII 0.839

XIII 0.884 Waste water


I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb; X – Hg; XI – As; XII - oil products; XIII - pesticides

Table 12. The correlation matrix between main pollutant components of surface water, groundwater and wastewater in 2006


Surface water

I II III IV V VI VII VIII IX X XI XII XIII

Issue Groundwater

I 0.977

I 0.733

II 0.701

III 0.733

IV 0.783

V 0.781

X – Hg; XI – As; XII - oil products; XIII - pesticides

groundwater and wastewater in 2006

VI 0.791

VII 0.725

VIII 0.767

IX 0.731

X 0.784 XI 0.772

XII 0.739

I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb;

Table 12. The correlation matrix between main pollutant components of surface water,

XIII 0.751

II 0.869

III 0.903

IV 0.835

V 0.955

VI 0.932

VII 0.947

VIII 0.961

IX 0.924

X 0.835 XI 0.858

XII 0.845

XIII 0.821 Waste water


I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb; X – Hg; XI – As; XII - oil products; XIII - pesticides

Table 13. The correlation matrix between main pollutant components of surface water, groundwater and wastewater in 2007

Evolution of Water Quality in Romania 155

Surface water

I II III IV V VI VII VIII IX X XI XII XIII

Issue Groundwater

I 0.963

I 0.729

II 0.697

III 0.705

IV 0.792

V 0.773

X – Hg; XI – As; XII - oil products; XIII - pesticides

groundwater and wastewater in 2009

VI 0.714

VII 0.751

VIII 0.749

IX 0.793

X 0.759 XI 0.739

XII 0.749

I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb;

Table 15. The correlation matrix between main pollutant components of surface water,

XIII 0.763

II 0.861

III 0.908

IV 0.831

V 0.947

VI 0.985

VII 0.955

VIII 0.928

IX 0.943

X 0.896 XI 0.875

XII 0.901

XIII 0.859 Waste water


I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb; X – Hg; XI – As; XII - oil products; XIII - pesticides

Table 14. The correlation matrix between main pollutant components of surface water, groundwater and wastewater in 2008


Surface water

I II III IV V VI VII VIII IX X XI XII XIII

Issue Groundwater

I 0.972

I 0.729

II 0.701

III 0.712

IV 0.721

V 0.753

X – Hg; XI – As; XII - oil products; XIII - pesticides

groundwater and wastewater in 2008

VI 0.763

VII 0.791

VIII 0.73925

IX 0.749

X 0.769 XI 0.734

XII 0.758

I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb;

Table 14. The correlation matrix between main pollutant components of surface water,

XIII 0.783

II 0.861

III 0.902

IV 0.931

V 0.912

VI 0.973

VII 0.971 VIII 0.986

IX 0.942

X 0.898 XI 0.875

XII 0.837

XIII 0.898 Waste water


I – Nitrogen compounds; II – Phosphates; III – Cu; IV – Cd; V - Mn; VI – Zn; VII – Cl; VIII – S; IX – Pb; X – Hg; XI – As; XII - oil products; XIII - pesticides

Table 15. The correlation matrix between main pollutant components of surface water, groundwater and wastewater in 2009

Evolution of Water Quality in Romania 157

Fe, Mn, Cu, Cd, Zn, pesticides and detergents. The surface waters are mainly contamined with metals (Cu, Cd, Mn, Zn), and contamination ranges between 15 – 22% of analyzed water bodies. The groundwater pollution frames within 20 – 25% of total ground water and the main pollutants are: NO2, NH4, P, PO42-, Cl, S, Pb, Cd, Hg, As, oil products, pesticides. 70.2 – 76.5% of total analyzed wastewater resulted from the main sources of pollution, have reached the natural receptors, especially rivers, not cleaned or insufficiently purified. Strong correlation (0.925) was identified between phosphates and nitrogen compounds in groundwaters. The same trait (strong correlation) can be attributed to the correlations between Cu, Cd, Mn, Zn (0.858 ÷ 0.921) in surface waters and NO2, NH4, Cl, S, Pb, Cd, Hg, As, oil products, pesticides (0.793 ÷ 0.921) in groundwater. Correlations were also calculated between main pollutants of: surface water and ground water, surface water and wastewater, ground water and wastewater. Their values (0.695 ÷ 0,986) emphasize the strong

Major issues that should be addressed in future research include the ability to simulate regional water quality and its sensitivity to social and economical realities. Research needs to be undertaken on the role of environmental management, particularly in view of increase the potential for diminishing the wastewater content in harmful pollutants, and extension of

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interdependence between pollutants matrices.

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cleaning process of these waters.

**10. References** 

version)

0333

83, ISSN: 0273-1223

The results of the multiregression analyze applied to water quality prediction in the future, show that only 0.07% of the original variability cannot be explained when dependent variable was represented by the nitrogen compounds, 0.05% when metals represented the dependent variable, 0.09% when phosphorus and/or phosphates were the dependent variable, and 0.11% when pesticides are dependent variable. This emphasizes the accuracy of this prediction model for explaining the approached water pollutants evolution.

Fig. 9. Scatter diagram depicting the multiple correlation analysis between variables. (a) correlation between nitrogen compounds and Cl, S, Pb, Cd, Hg, As, oil products, pesticides, phosphates (or P); (b) correlation between Pb, Cd, Hg, As, and Cl, S, oil products, pesticides, nitrogen compounds, phosphates (or P); (c) correlation between phosphates (or P) and nitrogen compounds, Cl, S, Pb, Cd, Hg, As, oil products, pesticides; (d) correlation between pesticides nitrogen compounds, Cl, S, Pb, Cd, Hg, As, oil products, phosphates (or P)

#### **9. Conclusion**

The main water pollutants identified during the analyzed time interval and all water categories (surface water, groundwater and wastewater) were: nitrogen compounds, Fe, P,

The results of the multiregression analyze applied to water quality prediction in the future, show that only 0.07% of the original variability cannot be explained when dependent variable was represented by the nitrogen compounds, 0.05% when metals represented the dependent variable, 0.09% when phosphorus and/or phosphates were the dependent variable, and 0.11% when pesticides are dependent variable. This emphasizes the accuracy

Residuals

Residuals

15 20 25 30 35 40 45 50 55 60


Y = 32.004 + 0.399X1 + 0.577X2 R = 0.999, R2 = 0.950

Y = 27.342 + 0.633X1 + 0.779X2 R = 0.999, R2 = 0.890

Observed values

Observed values

of this prediction model for explaining the approached water pollutants evolution.

Observed values

Observed values

Fig. 9. Scatter diagram depicting the multiple correlation analysis between variables. (a) correlation between nitrogen compounds and Cl, S, Pb, Cd, Hg, As, oil products,

pesticides, phosphates (or P); (b) correlation between Pb, Cd, Hg, As, and Cl, S, oil products, pesticides, nitrogen compounds, phosphates (or P); (c) correlation between phosphates (or P) and nitrogen compounds, Cl, S, Pb, Cd, Hg, As, oil products, pesticides; (d) correlation between pesticides nitrogen compounds, Cl, S, Pb, Cd, Hg, As, oil products, phosphates (or P)

The main water pollutants identified during the analyzed time interval and all water categories (surface water, groundwater and wastewater) were: nitrogen compounds, Fe, P,

(c) (d)

(a) (b)

15 20 25 30 35 40 45 50 55 60

10 20 30 40 50 60

Y = 32.687 + 0.312X1 + 0.407X2 R = 0.999, R2 = 0.930

Y = 33.379 + 0.331X1 + 0.454X2 R = 0.999, R2 = 0.910

**9. Conclusion** 

Residuals

Residuals

Fe, Mn, Cu, Cd, Zn, pesticides and detergents. The surface waters are mainly contamined with metals (Cu, Cd, Mn, Zn), and contamination ranges between 15 – 22% of analyzed water bodies. The groundwater pollution frames within 20 – 25% of total ground water and the main pollutants are: NO2, NH4, P, PO42-, Cl, S, Pb, Cd, Hg, As, oil products, pesticides. 70.2 – 76.5% of total analyzed wastewater resulted from the main sources of pollution, have reached the natural receptors, especially rivers, not cleaned or insufficiently purified. Strong correlation (0.925) was identified between phosphates and nitrogen compounds in groundwaters. The same trait (strong correlation) can be attributed to the correlations between Cu, Cd, Mn, Zn (0.858 ÷ 0.921) in surface waters and NO2, NH4, Cl, S, Pb, Cd, Hg, As, oil products, pesticides (0.793 ÷ 0.921) in groundwater. Correlations were also calculated between main pollutants of: surface water and ground water, surface water and wastewater, ground water and wastewater. Their values (0.695 ÷ 0,986) emphasize the strong interdependence between pollutants matrices.

Major issues that should be addressed in future research include the ability to simulate regional water quality and its sensitivity to social and economical realities. Research needs to be undertaken on the role of environmental management, particularly in view of increase the potential for diminishing the wastewater content in harmful pollutants, and extension of cleaning process of these waters.

#### **10. References**


**7**

*Portugal* 

Helena M. Galvão et al.\*

**Ecological Tools for the Management**

**River Watershed, Southwest Iberia** 

*Center for Marine and Environmental Research (CIMA), Universidade do Algarve, Gambelas Campus, Faro,* 

**of Cyanobacteria Blooms in the Guadiana**

Strong water demand for irrigation, energy and drinking water production is responsible for an increasingly regulation of freshwater flow patterns and watersheds. In this context, the construction of dams allows water storage but seriously restricts freshwater flow downstream. Due to scarcity of freshwater resources, reservoir water management often promotes high hydraulic residence. This may cause strong impacts on biological components of aquatic ecosystems, influencing the development of cyanobacteria blooms

Aquatic cyanobacteria, a group of relatively slow growing photosynthetic organisms, are stimulated by high water residence times as well as increased temperatures and low N : P ratios, conditions that usually limit the growth of other competing phytoplankton groups (Carmichael et al., 1996; Chorus & Bartram, 1999; Kawara et al., 1998; Kononen et al., 1998; Paerl, 2008). Cyanobacteria blooms have been repeatedly associated with eutrophication processes (Berg et al., 1987; Carmichael et al., 1988; Codd, 2000; Chorus, 2005; Druvietis, 1997; Pinckney et al., 1998), but they might also dominate under oligotrophic conditions

Cyanobacteria blooms management became an emergent priority as a result of worldwide surveys of aquatic ecosystems affected by massive cyanobacteria blooms and their serious health and ecosystem risks (Blaha et al., 2009). Indeed, cyanobacteria are able to produce a wide range of secondary metabolites which are toxic to humans and wildlife, generally referred as cyanotoxins. From a toxicological perspective, cyanotoxins are classified as

\* Margarida P. Reis1, Rita B. Domingues1, Sandra M. Caetano1, Sandra Mesquita1, Ana B. Barbosa1,

*1Center for Marine and Environmental Research (CIMA), Universidade do Algarve, Gambelas Campus, Faro,*

*2Center for Environmental and Sustainability Research (CENSE), Universidade do Algarve, Gambelas Campus,* 

*Faro, Portugal 3International Center for Environmental Research (CIECEM), University of Huelva, Huelva, Spain* 

(Galvão et al., 2008; Havens et al., 2003; Mez et al., 1997; Sivonen & Jones, 1999).

Cristina Costa1, Carlos Vilchez3 and Margarida Ribau Teixeira2

**1. Introduction** 

*Portugal* 

and aggravating their harmful impacts.

