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The river Dambovita, which crosses Bucharest city, is characterized by two superposed artificial riverbeds: the lower part, under Dambovita river floor, which is a channel containing sewage from the city and the upper part, which is cleaner and combines with the lower part when exiting Bucharest. This study aims to evaluate the anthropogenic impact on the water quality of the upper canal. Samples were collected from 10 points along the sector, during two sampling campaigns, between January and February 2015. These points were chosen based on the ease of access, the environmental characteristics and any possible human influence. Physico-chemical parameters were measured: the concentration and saturation of dissolved oxygen, temperature, pressure, pH, turbidity, conductivity, amount of ammonium, phosphorus and nitrates. In addition, fluorescence spectroscopy method was used to determine the presence and types of organic substances in water samples. The results showed significant differences between the urban sector of Dambovita and the final sampling point, situated downstream of the Glina wastewater treatment plant. Fluorescence measurements showed that the quantity of humic substances had a continuous increase along the sector. Regarding the microbial fraction, fluorescence spectroscopy revealed a sudden increase at the sample collected from the entrance of the river in Bucharest and at Glina sewage effluent discharge point. Fluorescence results evidenced the anthropogenic impact on the water quality of Dambovita River. In conclusion, the quality of Dambovita waters varies across space and time, depending on human influence affecting the areas from where samples were taken and also reflecting a temporal variation, with a drop in quality during January, caused by weather conditions that lead to the concentration and stagnation of pollutants.
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91
EVALUATION OF THE ANTHROPOGENIC IMPACT ON THE WATER QUALITY OF
DAMBOVITA RIVER
Gabriela Adina Morosanu1, Simona Dontu2, Olimpia Copacenaru1, Viorel Gavril1,
Florin-Alexandru Zaharia1, Elfrida Mihaela Carstea2
1University of Bucharest, Centre for Environmental Research and Impact Studies, Romania,
2National Institute of Research and Development for Optoelectronics INOE 2000, Tel: 021452.57.57 Romania,
Email: simona.dontu@inoe.ro,
ABSTRACT
The river Dambovita, which crosses Bucharest city, is characterized by two superposed artificial riverbeds: the lower part, under
Dambovita river floor, which is a channel containing sewage from the city and the upper part, which is cleaner and combines with the
lower part when exiting Bucharest. This study aims to evaluate the anthropogenic impact on the water quality of the upper canal.
Samples were collected from 10 points along the sector, during two sampling campaigns, between January and February 2015.
These points were chosen based on the ease of access, the environmental characteristics and any possible human influence.
Physico-chemical parameters were measured: the concentration and saturation of dissolved oxygen, temperature, pressure, pH,
turbidity, conductivity, amount of ammonium, phosphorus and nitrates. In addition, fluorescence spectroscopy method was used to
determine the presence and types of organic substances in water samples. The results showed significant differences between the
urban sector of Dambovita and the final sampling point, situated downstream of the Glina wastewater treatment plant. Fluorescence
measurements showed that the quantity of humic substances had a continuous increase along the sector. Regarding the microbial
fraction, fluorescence spectroscopy revealed a sudden increase at the sample collected from the entrance of the river in Bucharest
and at Glina sewage effluent discharge point. Fluorescence results evidenced the anthropogenic impact on the water quality of
Dambovita River. In conclusion, the quality of Dambovita waters varies across space and time, depending on human influence
affecting the areas from where samples were taken and also reflecting a temporal variation, with a drop in quality during January,
caused by weather conditions that lead to the concentration and stagnation of pollutants.
Keywords: water quality, fluorescence spectroscopy, dissolved organic matter, Dambovita River.
1 INTRODUCTION
The importance of Dambovita River, as a hydrographic artery, stems from the possibilities of using
its waters for various purposes and also from the need to establish a detailed research program on the
physical and chemical state of water and its polluting factors, including the solutions that can combat the
decreasing quality of water. Dambovita River has undergone numerous changes, which have led to the
creation of an entirely artificial water course in the sector that passes through Bucharest. This specific sector
of Dambovita River has a unique hydro-technical structure, which is represented by two superposed artificial
riverbeds: the upper part collects the clean waters from Morii Lake, built to attenuate the floods and to store
water for different uses, while the canal underneath accumulates all the wastewater from the city.
The problem of pollution affecting Dambovita when passing through Bucharest, has been
investigated by various authors (e.g. Morcotet et al. 2011; Cocos 1998) and by specialized institutions from
numerous perspectives, including water resources management, with the goal of improving quality of life
and achieving a sustainable development (Order no. 161/2006 approving the Norms concerning the
classification of surface waters quality to establish ecological status of water bodies).
Hydrochemistry research and methods for assessing water quality represented a starting point for this
study, and we included both older works, studies and synthesis, as a theoretical foundation, and recent
research, valuable in terms of methodology both for Romania Ioja (2008) and at an international level:
Meratnia et al. (2000), Debels et al. (2005), Boyacioglu (2006), Said et al. (2007).
This study aims to create an inventory of data on water quality and to carry out a quantitative and
qualitative analysis, at spatial and temporal scale. The quantitative evaluation will include the measurement
of the concentration of dissolved oxygen, temperature, pressure, pH, turbidity, conductivity and the amount
of ammonium, phosphorus and nitrates. The qualitative component involves the use fluorescence
spectroscopy to assess the character of dissolved organic matter fractions and the type of organic pollution.
The present research is part of recent trends involving the study of water quality in rivers that cross major
urban areas, serving the goal of better understanding the temporal and spatial evolution of relevant
parameters and the economic or environmental significance of exceeding certain quality limits.
3rd International Conference - Water resources and wetlands. 8-10 September, 2014 Tulcea (Romania);
Available online at http://www.limnology.ro/wrw2016/proceedings.html
Editors: Petre Gâştescu, Petre Bretcan; ISSN: 2285-7923; Pages:91-98; Open access under CC BY-NC-ND license
92
2 STUDY AREA
Samples were collected along a sector of Dambovita River that crosses Bucharest, and involved a
field study on a distance of ~ 21 kilometers, from the entrance in a lake reservoir (Morii Lake) until the
effluent discharge point at Glina wastewater treatment plant (Fig. 1). The details regarding the sampling
points locations and the potential sources of contamination are presented in Table 1.
Figure 1. Location of sample collecting points
Table 1. Details of sampling points
Sample
name
Details of sampling points
P1
Land use: Mixed area with scattered houses and natural green spaces prone to flooding, on the
right, and open fields and scattered houses on the left side of the river. Possible sources of
contamination: riverine vegetation and agricultural runoff from upstream areas
P2
Land use: on the left - dump sites, no houses and fallow vegetation and on the right
households from Dudu village. Possible sources of contamination - Dudu Village storm drain
P3
Land use: open field, fallow vegetation and scattered houses in the distance. Possible sources
of contamination: village wastewater
P4
Land use: Residential area, open fields, greenhouses. Possible sources of contamination:
Dambovita Swimming pool, arable land and dump sites.
P5
Land use: residential, commercial and industrial areas. Possible contamination sources: heavy
traffic, households, commercial waste, rain that travel across CET Grozavesti
P6
Land use: green areas (Izvor Park upstream), residential, administrative and commercial area.
Possible sources of contamination: heavy traffic, passers-by, wastewater
P7
Land use: residential area, agriculture, commercial spaces (warehouses). Possible sources of
pollution: wastewater, agricultural drain water
P8
Land use: Agriculture (especially greenhouses), Industrial Area (CET Sud), Green areas and
wetlands (Vacaresti ”Delta”), open fields. Possible Sources of contamination: industrial waste,
wastewater, agricultural waste (greenhouses), traffic
P9
Land occupied by deposits of building materials, Agricultural area, open field and commercial
area. Possible contamination sources: industrial waste, city storm drain, agricultural waste
P10
Sources of contamination: industrial wastes, agricultural wastes, all the water coming from
Dambovita River underground water canal, containing all wastewater collected on the river’s
way through Bucharest
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3 RESULTS AND DISCUSSIONS
For all 10 points, the physical and chemical parameters of water were determined: dissolved oxygen
[mg/l and C%], water temperature at the moment when the sample was collected [oC], pH, conductivity [μS],
turbidity [mg/l] by using EPA 180 methods, and also the amounts of ammonium, phosphorus and nitrates
found in the water [mg/l]. Some values are presented in Table 2.
Table 2. Physico chemical parameters
Dissolved Oxygen
(mg/l)
Conductivity
(μS)
Turbidity
(mg/l)
Feb
Jan
Feb
Jan
Feb
P1
2.50
465.00
602.00
11.5
5.1
P2
3.30
499.00
547.00
6.35
3.72
P3
3.60
566.00
515.00
11.6
4.82
P4
3.50
495.00
467.00
6.87
4.4
P5
3.50
710.00
460.00
4.25
3.89
P6
3.60
559.00
461.00
4.35
4.29
P7
3.30
725.00
478.00
4.19
3.76
P8
3.40
365.00
486.00
4.43
3.54
P9
2.30
459.00
750.00
10.3
7.43
P10
0.20
525.00
699.00
266
31.5
For the sampling points situated upstream of Glina, the dissolved oxygen in the samples was
included into the 4th class of quality (poor water quality), and at the last point downstream of Glina, the water
sample was found to belong to the last category (Class 5 degraded water that cannot be used and is harmful
to humans and to aquatic organisms). The dissolved oxygen presented low values for sample P7 and the first
sampling point (P1) and very low values at the sample downstream of the Glina wastewater treatment plant
(P10). The concentration of dissolved oxygen is illustrated in Fig.2 for the samples collected in January
2015.
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
2
4
6
8
10
12
14
16
18
Temperature (0C)
Sample
Temperature
10
20
30
40
Dissolved Oxygen
concentration (%)
Concentration of dissolved Oxygen
Figure 2. Correlation between water temperature and concentration of dissolved oxygen
In addition, it was possible to establish an inversely proportional relation between these two physical
parameters, thus illustrating the importance of this relation of dependency and the increase of one parameter
(temperature) when the other one decreases, causing damage to the aquatic environment, which depends on
the presence of dissolved oxygen. We took notice of the water samples collected at Glina (P10), where water
temperature was above 10 degrees Celsius at the moment when they were collected, and dissolved oxygen
was less than 10%.
The concentration of several pollutants impacted upon the variation of pH, which is sensitive to
fluctuations when the surface of the water is covered by a layer of ice, and temperatures oscillate diurnally.
For this reason, although the increase was not alarming (max pH of 7.18 at the Grozavesti wharf, compared
to maximum admitted concentrations between 6.5 and 9.5), it marked an increase in the water’s alkalinity in
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January, accompanied by more homogenous values for conductivity (The minimum value for January was 25
μs, and the maximum was 365 μs, compared to 875 μs and 286 μs in December, a month characterized by
thermal inversions and potential stagnation of pollutants). Furthermore, January holds the record for the
number of points (9 out of 10) where pH values did not exceed the maximum legal limits. The inverse
proportionality between conductivity and the dissolved oxygen (Fig.3), can be explained by the increase of
dissolved oxygen that takes place when polluting substances that cause turbidity are eliminated from water.
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
0
1
2
3
4
5
Dissolved Oxygen (mg/L)
Sample
Dissolved Oxygen
200
300
400
500
600
700
800
900
Conductivity (S)
Conductivity
Figure 3. Correlation between conductivity and dissolved oxygen
The observations on pollution sources, the analysis of land use near Dambovita, the possible
connections to the sewage network and weather conditions during sampling, all become reference points for
interpreting the values taken by the water quality parameters. Thus, the results indicate an increase in
temperature, conductivity, ammonium content, turbidity and phosphorus as water moves closer to the Glina
sampling point, coinciding with a drop in the concentration and saturation of dissolved oxygen, water
pressure and nitrate content. In the context of increased conductivity and an accumulation of pollutants in
the water, turbidity also rises (Fig. 4).
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
0
20
40
380
390
400
410
420
430
Turbidity (mg/L)
Sample
Turbidity -January
Turbidity - Fevruary
Figure 4. Turbidity variation chart
The amount of organic and inorganic matter carried by water exhibited a sharp increase towards the
final sampling point at Glina, from a value of less than 190mg/l in samples taken upstream all the way to
420mg/l downstream of Glina. The analyzed organic compounds, the amounts of phosphorus, nitrates and
ammonium, were found to fall within two general intervals, in accordance with their water interaction
properties and their ability to react with other organic and inorganic compounds. On the one hand, mineral
phosphorus and ammonium increase as we move closer to Glina, due to high biochemical intake in the
context of exothermal and anaerobic reactions and of the water nutrient saturation. On the other hand, the
amount of nitrates registered the lowest values at Glina, since this compound is already used up by the
95
biological processes of phytoplankton that lives in cleaner waters upstream. In terms of water quality classes,
the three above mentioned compounds could be found to fall within each and every class at the 10 sampling
points.
3.1 Fluorescence characterization of organic matter
Examples of fluorescence EEMs sampled on Dambovita River are presented in Fig. 5. Fluorescence
spectra of environmental samples generally reveal the presence of 5 peaks, which correspond to different
fractions of organic matter. The peaks are located in the following excitation and emission wavelength
ranges: peak T- λex / λem: 260-280/325-350 nm, peak B- λex / λem: 240-250/300-310 nm, peak A- λex / λem: 240-
260/420-460 nm, peak C- λex / λem: 310-350/400-500 nm and peak M- λex / λem: 310 - 320/380420 nm. Peaks
T and B (protein-like) are associated with living and dead cellular material and their exudates, and indicate
microbial activity. These peaks present high fluorescence intensity when phenolic or indolic compounds are
found in the water sample. Peaks A, C and M (humic-like) are attributed to organic matter formed by
terrestrial, microbial and chemical processes. Usually, these three peaks display high fluorescence intensity
when humic substances are present in the sample (Carstea et al. 2014).
300 350 400 450 500
240
260
280
300
320
340
360
380
400
B
TM
A
Emission wavelength (nm)
Excitation wavelength (nm)
P 1
C
300 350 400 450 500
240
260
280
300
320
340
360
380
400
Emission wavelength (nm)
Excitation wavelength (nm)
P 2
300 350 400 450 500
240
260
280
300
320
340
360
380
400
Emission wavelength (nm)
Excitation wavelength (nm)
0
6667
1.333E4
2.000E4
2.667E4
3.333E4
4.000E4
4.667E4
5.333E4
6.000E4
6.667E4
7.333E4
8.000E4
8.667E4
9.333E4
1.000E5
P 5
300 350 400 450 500
240
260
280
300
320
340
360
380
400
Emission wavelength (nm)
Excitation wavelength (nm)
P 8
300 350 400 450 500
240
260
280
300
320
340
360
380
400
Emission wavelength (nm)
Excitation wavelength (nm)
P 9
300 350 400 450 500
240
260
280
300
320
340
360
380
400
Emission wavelength (nm)
Excitation wavelength (nm)
P 10
Figure 5. Examples of fluorescence excitation-emission matrices
The fluorescence spectra revealed the predominance of humic-like peaks, A, C and M, over the
protein-like fluorescence, at the samples collected before Bucharest main residential area (P1-P3). The
intensity of peaks T and B increased at samples towards Bucharest city centre (P4 and P5), indicating a
greater quantity of microbial components and a higher anthropogenic activity compared to upstream
samples. A slight decrease in intensity of all peaks was observed at samples P6 and P7 (Fig. 5), potentially
due to dilution of Dambovita River with surface runoff. It may be assumed that a larger coverage of
pavement produces a greater quantity of surface runoff that leaches into the river compared to unpaved areas
near the river banks, as seen at sample P4 and P5. Starting with sample P8, the fluorescence intensity,
especially for peak T increased and reached a maximum at sample P10, which was collected after the release
of wastewater effluents. Peak T fluorescence is dominant at P10 sample due to the high quantity of microbial
matter (proteins, peptides, amino acids), lignin degradation products or aromatic hydrocarbons that are
generally found in the composition of treated and untreated sewage (Carstea et al. 2016). As reviewed by
Carstea et al. (2016), peak T may be used to track domestic wastewater contamination in surface water, as
this component is prevalent at anthropogenically impacted samples. Overall, fluorescence spectra evidenced
that samples P1-P4, P6 and P7 showed similar characteristics: low protein contribution, more humic
material, indicating that the water presented almost no organic contamination. Samples P5, P8 and P9
showed both humic and protein-like content, and a possible contribution from hydrocarbons especially for
96
sample P5, indicating a mild anthropogenic impact. Sample P10 collected from a much polluted area (after
Glina wastewater treatment plant) with unpleasant odor, had predominant peak T fluorescence, revealing a
substantial influence from anthropogenic activities (Fig. 6).
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
0
20000
40000
60000
80000
100000
120000
140000
160000
PeakT
PeakB
PeakA
PeakC
PeakM
Fluorescence intensity (a.u.)
Sample
Figure 6. Spatial variation of the fluorescence peaks
The temporal analysis of results showed that higher values for all fluorescence peaks were recorded
in January compared to February (Table 3). The difference in the quantity of organic matter between the two
months was probably caused by the weather conditions that lead to the concentration and stagnation of
pollutants. The fluorescence intensity values for the spatial and temporal analysis displayed inverse
correlation with dissolved oxygen. The inverse correlation is expected since a low dissolved oxygen value
indicates poor water quality, while the opposite rule is typical for fluorescence intensity. Excellent negative
correlation was obtained for peaks T and B (-0.95 and -0.92), very good negative correlation with peaks C
and M (-0.89 and -0.88) and good negative correlation with peak A (-0.79). Also, fluorescence values
presented excellent correlation with turbidity. The following correlation coefficients were obtained: peak T
(0.98), peak B (0.96), peak C (0.93), peak M (0.92), and peak A (0.83).
Table 3. Fluorescence intensity and indices for samples collected from Dambovita River
Sample
Fluorescence intensity (a.u.)
T
B
A
C
M
Jan
Feb
Jan
Feb
Jan
Feb
Jan
Feb
Jan
Feb
P1
13930
10670
8193
7214
51330
37440
25630
14160
26010
14480
P2
14000
10800
7875
7663
43410
35860
22210
13540
22510
14140
P3
14940
10050
7877
5245
44680
31820
21950
12600
22390
12960
P4
22860
11950
8887
6072
42670
33760
21040
13670
21540
14080
P5
24340
11750
18070
6404
45570
36300
23160
13430
23650
13770
P6
15190
11270
6782
6136
44700
34220
22080
13280
22560
13530
P7
15520
12070
7552
6158
43060
35310
21730
13580
22430
14010
P8
27650
11190
11260
6097
67240
34020
36850
13150
38160
13530
P9
28870
21350
14990
9542
65570
58440
36920
24080
38720
25350
P10
197900
86140
47580
38010
75920
106100
58040
53420
60350
59100
Fluorescence indices were calculated in order to obtain additional information on the characteristics
of organic matter fractions. Table 4 presents the values for the humification index (HIX), biological index
(BIX), fluorescence index (F450/500) and the ratio between peaks T and C (T/C). The fluorescence indices
were calculated based on the equations provided by Huguet et al. (2009). HIX was introduced by Zsolnay et
al. (1999) and describes the degree of maturation/humification of organic matter, while BIX represents an
indicator of autochthonous biological activity in water samples (Huguet et al. 2009).
97
Table 4. Fluorescence indices
Sample
Fluorescence indices
HIX
BIX
F450/500
T/C
Jan
Feb
Jan
Feb
Jan
Feb
Jan
Feb
P1
4.32
3.17
0.81
0.87
1.32
1.30
0.54
0.75
P2
3.56
2.91
0.85
0.89
1.34
1.35
0.63
0.80
P3
3.55
3.47
0.86
0.89
1.35
1.25
0.68
0.80
P4
2.67
3.26
0.87
0.91
1.36
1.39
1.09
0.87
P5
2.10
3.21
0.88
0.90
1.39
1.31
1.05
0.87
P6
3.77
3.28
0.87
0.91
1.37
1.31
0.69
0.85
P7
3.48
3.12
0.88
0.91
1.36
1.39
0.71
0.89
P8
3.44
3.22
0.95
0.90
1.49
1.36
0.75
0.85
P9
2.73
3.16
0.98
0.99
1.46
1.40
0.78
0.89
P10
0.71
1.51
0.98
1.12
1.28
1.51
3.41
1.61
According to the classifications for HIX given by Huguet et al. (2009), all samples with the
exception of P1, contain organic matter with biological or aquatic bacterial origin. Sample P1 presents a
weak humic character and an important recent autochthonous component. BIX provided similar results;
however, it separated better between P10 and the other samples. P10 was the only sample that presented
organic matter of biological or bacterial origin, while the other samples were classified as containing organic
matter of strong autochthonous component. F450/500 was introduced by McKnight et al. (2001) and helps
discriminate between the sources of organic matter. Values above 1.3 indicate microbial sources, while
values below suggest a terrestrial source. The parameter shows that most samples contain organic matter of
mixed sources. Nevertheless, the highest value was calculated for sample P10, collected in February,
indicating the anthropogenic impact from the sewage discharge at that sampling point. The last parameter,
T/C, can be used to identify the preponderance of organic matter fractions. As seen in Table 4, sample P10
contains a substantially higher quantity of protein-like matter compared to the other samples. This shows the
significant impact of anthropogenic activities on the quality of Dambovita River.
CONCLUSIONS
The weather conditions, and particularly the freezing of the river water, influenced the physical and
chemical parameters. A significant part of the pollution sources (most of them industrial and agricultural in
nature) were identified, and the substantial difference between the values measured at Glina and the values
observed upstream were highlighted. Chemical compounds exhibited different values, depending on the
pollution sources. The amount of phosphorus and ammonia increased as the sampling point approached
Glina, while nitrates decreased.
With regards to fluorescence spectroscopy, humic compounds dominated the upstream samples, up
to P7 sampling point. In the sector between P7 and upstream of Vacaresti Lake, humic acids dominated the
samples, with a weak presence of protein-like substances. Then, before passing through the Glina treatment
station, the water samples contained, in roughly equal proportions, protein-like and humic compounds.
Downstream of Glina, the microbial element became the most important.
According to the Order no. 161/2006, the quality of water found in the 10 sampling points differed
from one location to another for every parameter, and fitted into one of the 5 water quality classes
established by the Order. The methods for determining the quality of water are complementary and confirm
the link between organic substances found in water and the values of physical and chemical parameters.
Because of the nature of the data on water quality for Dambovita, we believe that this study will bring
significant advances in the level of knowledge on this subject, updating and completing the issue of water
quality management (the AGIR Bulletins, the hydrological protection plans for the city of Bucharest drafted
by the Mayor’s Office and ANAR, the analysis bulletins and the yearbooks compiled by the Argeş-Vedea
Basin Management Authority etc.).
98
ACKNOWLEDGEMENTS
This work was funded by Core Program, under the support of ANCS, project nr. PN 16.40.01.01 and by a
grant of the Romanian National Authority for Scientific Research, CNDI UEFISCDI, project number PN-
II-PT-PCCA-2011-3.2-0084.
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The isolation, characterization and study of the properties of aquatic dissolved organic matter (DOM) still represent a challenge because of the heterogeneity, complexity and low concentration of organic material in natural waters. Based on its ability to interact with contaminants and thus to modify their transport and bioavailability, DOM is of interest for environmental purposes. The objective of this work was to better characterize DOM in the Gironde Estuary (southwestern France). The estuary represents an exchange zone between the continent and the Atlantic Ocean and conditions the transfer of organic and inorganic substances from the continental to the oceanic environment. Several samples were collected along the estuary during three cruises in 2002 and 2006. They were analysed using excitation–emission matrix (EEM) spectroscopy, a sensitive technique that allows direct analysis of water samples. Fluorescent DOM and dissolved organic carbon (DOC) did not behave conservatively in this estuarine system, i.e. the organic material did not undergo simple dilution from the upstream to the downstream part of the estuary. A seasonal variability in DOC content was pointed out, whereas few seasonal variations in DOM fluorescence were observed. DOM sources and processing in the estuary were further evaluated by determining two fluorescence indices – the humification index (HIX) and the index of recent autochthonous contribution (BIX). By applying these indices, the relative degree of humification (HIX) and autotrophic productivity (BIX) could be assessed. Based on the fluorescence and DOC results, the estuary was divided into three zones depending on salinity (S) and characterized by specific DOM: (i) A turbid zone of low salinity (S
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The relative fluorescence, normalised on dissolved organic carbon (DOC), and a humification index, based on the location of the fluorescence emission spectra, were used to investigate the possible sources of the increase in dissolved organic matter (DOM) when a soil is dried. From these 2 parameters it could be seen that air drying resulted in a minor increase of more humified material in DOM while the effect of oven drying was mainly due to cell lysis.
Hydrographic systems and water management in Bucharest
  • O Cocos
Cocos, O. (1998). Hydrographic systems and water management in Bucharest, PhD thesis, University of Bucharest, Editura Editions du Goeland, Bucureşti, (147 pg.).
Methods and techniques for assessing the quality of the environment in Bucharest's metropolitan area
  • C Ioja
Ioja, C. (2008), Methods and techniques for assessing the quality of the environment in Bucharest's metropolitan area, Bucharest University Press, Bucharest, pages 1-243.