Journal of

Journal of Water

Current Issue Volume No: 1 Issue No: 2

ISSN: 2769-2264
share this page

Research Article Open Access
  • Available online freely Peer Reviewed
  • Multivariate Analysis of Amazonian Rivers Located in an Area of Intense Industrial Activity, Barcarena, Pará State, Brazil

    Iris Danielly da Silva Lopes 1 2   Adaelson Campelo Medeiros 2   Nuno Filipe Alves Correia de Melo 1   Marcelo de Oliveira Lima 2   Maria de Lourdes Souza Santos 1  

    1Universidade Federal Rural da Amazônia. Instituto Sócio Ambiental e Recursos Hídricos. Avenida Presidente Tancredo Neves, 2501-Terra Firme. Belém-PA. Brasil. CEP: 66077-530.

    2Instituto Evandro Chagas. Seção de Meio Ambiente. Rodovia BR-316, Km 07 S/N. Levilândia. Ananindeua-PA. Brasil. CEP: 67030-000.


    In this study, were multivariate analysis of the waters of the Arienga and Murucupí rivers located near an area of intense industrial activity in the Barcarena City, Pará State, Brazil. Were analyzed the variables temperature, pH, total dissolved solids, electrical conductivity, DO, BOD, ammoniacal-N, nitrite-N, nitrate-N, phosphate, sulfate and total hardness in four sampling campaigns in the year 2011. This amazon rivers presented physicochemical characteristics well heterogeneous, but similar behaviors for the variables pH, temperature and DO in the extensions evaluated, that is, increase in the source-mouth direction, with variations from 4.77 to 7.33 and 5.51 to 7.3, 25 to 31°C and 27 to 32°C and from 4.4 to 7.98 mg.L-1 and 1.17 to 6.55 mg.L-1 for the Arienga and Murucupi rivers respectively. In addition to these characteristics, the Arienga River also presented an increase for ammoniacal-N, nitrite-N, nitrate-N and hardness in the dry period, with variations from 0.014 to 6.336 mg.L-1, 0.005 to 0.334 mg.L-1, 0.009 to 4.818 mg.L-1 and 1.146 to 14.389 mg.L-1 respectively. In general, Murucupí River presented different physicochemical characteristics that are coherent with the local scenario, where the launch domestic effluents and the environmental impacts caused by industrial waste are visible and recurrent respectively.


    Author Contributions
    Received 15 Jun 2021; Accepted 28 Jun 2021; Published 01 Jul 2021;

    Academic Editor: Wei Zhang, State Key Laboratory of Polymer Materials Engineering Polymer Research Institute, Sichuan University Chengdu 610065, China.

    Checked for plagiarism: Yes

    Review by: Single-blind

    Copyright ©  2021 Iris Danielly da Silva Lopes, et al.

    Creative Commons License     This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Competing interests

    The authors have declared that no competing interests exist.


    Iris Danielly da Silva Lopes, Adaelson Campelo Medeiros, Nuno Filipe Alves Correia de Melo, Marcelo de Oliveira Lima, Maria de Lourdes Souza Santos (2021) Multivariate Analysis of Amazonian Rivers Located in an Area of Intense Industrial Activity, Barcarena, Pará State, Brazil. Journal of Water - 1(2):1-16.

    Download as RIS, BibTeX, Text (Include abstract )

    DOI 10.14302/issn.2769-2264.jw-21-3870


    The quality of surface water depends on many factors, and may undergo hydroclimatic influences such as natural weathering and environmental changes caused by anthropic actions1. The various environmental factors that modify the water quality of a given region are related to the geological structure, the mineralogy of the watersheds and the way in which the use and occupation of the soil occurs in the surroundings of these areas 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12.

    Household and industrial effluents generated from human activities may contain hazardous chemicals that can cause major impacts on aquatic ecosystems. These substances can last a long time in the environment and have the ability to percolate in the soil and reach the lower layers of the subterranean aquifers, for this reason, soil geochemistry has a great influence on water pollution/contamination13.

    In recent decades there has been a great increase in the levels of toxic chemicals in the environment, this event is a consequence of the lack of planning by the municipalities and industries installed in relation to the way the effluents are released in the water bodies generating immense release of compounds Harmful to animal and plant life 14, 15, 16.

    The Barcarena City in the Pará State-Brazil has in its territory an important industrial pole that works in the processing and export of kaolin, alumina, aluminum, cables for transmission of electric energy among other activities. Approximately 40,000 hectares were used for the installation of industries and the local population that previously used natural resources for their livelihoods, such as hunting and fishing, had to adopt other productive bases for their economic survival17. The local economy has a traditional base in agriculture, but also advances with tourism beyond industrial activities, generating economic growth18. The presence of these industries causes the rivers to become targets of recorrent environmental accidents, for example, the spillage of red mud in the springs of the Murucupí river in April 2009, a product from the beneficiation of bauxite that caused great environmental damages and to the local population19.

    The launch of untreated sanitary sewage and the recorrent environmental accidents have damaged the quality of the waters of that region. In this sense, the Murucupí River was chosen, which runs through the industrial area of Vila do Conde and urban agglomerates and the Arienga River, which is located in the territorial boundary between the cities of Barcarena and Abaetetuba, Pará State-Brazil, a little further away from industrial area.

    Material and Methods

    Study Area

    The Barcarena City belongs to the mesoregion Metropolitana de Belém, Pará State-Brazil, located under the geographical coordinates: 01º 30’ 24” of South latitude e 48º 37’ 12” Longitude west of Greenwich, with straight line distancing from the state capital (Belém, Pará) in approximately 30 km 20. This City is part of the Pará river basin and has a territorial area of 1,310 km2 in size; the estimated population for 2016 was 118,537 inhabitants21.

    The climate of the microregion is Köeppen wet type Am, with abundant rainfall and high temperature values reaching an annual average of 27º C, The annual rainfall is over 2,000 mm where two seasonal periods are well defined: The rainy season from December to May and dry from June to November 22. Table 1 shows some regional climate characteristics in 2011, according meteorological data base and tidal forecasts 23, 24.

    Table 1. Regional climate characteristics in 2011.
    Local characteristics Unit Months of Sampling
    February (Rainy) May (Rainy) August (Dry) November (Dry)
    Max. Min. Max. Min. Max. Min. Max. Min.
    Temperature oC 31.0 23.1 33.5 24.3 33.9 23.3 33.1 22.7
    Tides m 3.5 -0.2 3.2 -0.2 3.5 -0.1 3.2 -0.3
    *Rainfall mm 332.4 477.3 179.4 174.6

    *- Monthly precipitation; Max.: Maximum; Min.: Minimum.

    The geology of the Municipality is constituted by a set of aquifers belonging to the stratigraphic units Pirabas, Barreiras and Quaternary Coverage25, 26. Topographic levels are low, especially on islands where they are in part subject to floods 27, 28.

    Arienga River microbasin is located in the territorial area between the cities of Barcarena, Abaetetuba and Moju in the Pará State-Brazil. This river territorially delimits Barcarena and Abaetetuba cities, has their springs located within these cities, with the mouth in the right bank of the river Pará and also are used by the local population for recreation in existing beach resorts along the river. The microbasin of the Murucupí river is located in the territorial area of the Barcarena between the mining companies Albrás and Alunorte and the districts of Vila dos Cabanos and Laranjal. Its source is located near the tailings basin of the company Alunorte (Mud Red) and its mouth in the Furo do Arrozal River 19.

    The classification of the rivers in the Amazon fall into three categories: white, dark and clear waters. According to the classification of the waters as their colorations, the pH between 4.0 and 7.0 configures a clear water environment, while waters with pH around 4.0 are classified as black, therefore, the waters of the rivers Arienga and Murucupí present the two classifications 29, 30, 31.

    Based on the Brazilian legislation that provides for the classification of water bodies and environmental guidelines for their classification32, regarding the salinity of the water bodies, the Arienga and Murucupí rivers presented values consistent with the classification for freshwater.

    In the Arienga river, an extension of approximately 11,368 m was evaluated, considering six (06) sampling points with minimum and maximum distance between sampling points of 1,546 m and 2,672 m respectively. In the Murucupí River, seven (07) sampling points were evaluated in an extension of approximately 6,333 m, with minimum and maximum distance between the sampling points of 737 m and 1,725 m respectively. The sampling points (Figure 1) in the Arienga and Murucupí rivers were defined upstream and downstream of small tributary drains along the extensions evaluated from their source to their mouths, taking into account navigability, accessibility, field staff and financial cost to carry out the work.

    Figure 1. Study area and respective sampling points.
     Study area and respective sampling points.

    Sampling and Analysis Methodologies

    The samples and analyzes used to determine the variables obeyed the procedures and methodologies according to the recommendations described in the Standard Methods for Examination of Water and Wastewater 33.

    Sampling for the determination of the physico-chemical variables at the collection points was of the simple type and using the immersion technique of the collection vessels at a maximum depth of 30 cm from the water column. The water samples were collected in duplicates in polyethylene bottles with capacity for 1L and then transported in isothermal boxes preserved with recyclable ice and taken to the Laboratory of Toxicology Of the Environment Section of the Evandro Chagas Institute in Ananindeua-PA.

    The physicochemical variables determined were: temperature, pH, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), biochemical oxygen demand (BOD), ammoniacal-N, nitrite-N, nitrate-N, phosphate, sulfate and total hardness (CaCO3 and MgCO3).

    The temperature, pH, total dissolved solids, electrical conductivity and dissolved oxygen were determined at the moment of sampling with the HI 769828 equipment of the HANNA® previously calibrated with standard solutions. The determination of BOD5 at 20 ° C was performed on the BODTRAK of the HACH®.

    For analysis of ammoniacal-N, nitrite-N, nitrate-N, phosphate, sulfate and total hardness, the samples were filtered through a 0.45 μm pore Millipore filter and then analyzed via ion chromatography in a system ICS 2000 DUAL 34.

    Statistical Treatment

    Descriptive statistics and principal component analysis (PCA) were applied on the results of the physicochemical variables determined in the two rivers. Minitab 17 software (license 317201144883580098) was used for the application of the descriptive statistics and multivariate analysis about the data. The results were compared between rainy and dry seasons.


    This study, the water temperature of the Arienga and Murucupi rivers ranged from 25 to 31 °C and from 27 to 32 °C, respectively, with average variations from 26 to 30 °C. The pH values in this study ranged from 4.75 to 7.33 in the Arienga river and from 5.51 to 7.3 in the Murucupi river, with means ranging from 5.55 to 6.71.

    The electrical conductivity and total dissolved solids (TDS) determined in the rivers Arienga and Murucupí indicated a difference in its characteristics physicochemical, with values ranging from 4 to 49 µ and 25 to 122 µ e from 2 to 26 mg.L-1 and 12 to 57 mg.L-1 respectively, the mean electrical conductivity and TDS in the Arienga river were 21 to 25 µ and 11 to 13 mg.L-1 and Murucupi River from 38 to 83 µ and 19 to 38 mg.L-1.

    The DO concentrations in the Arienga and Murucupi rivers ranged from 4.40 to 7.98 mg.L-1 and from 1.17 to 6.55 mg.L-1 respectively, with averages from 5.21 to 6.29 mg.L-1 in the Arienga River and from 3.86 to 4.70 mg.L-1 in the Murucupi River. The BOD concentrations in the Arienga and Murucupi rivers ranged from 5 to 19 mg.L-1 and from 6 to 26 mg.L-1 respectively, with averages ranging from 9 to 15 mg.L-1 in the two rivers.

    The ammonia nitrogen, nitrite and nitrate concentrations in the Arienga and Murucupi rivers ranged from 0.014 to 6.336 mg.L-1, 0.003 to 0.334 mg.L-1 and 0.009 to 4.818 mg.L-1 and from 0.021 to 2.021 mg.L-1, 0.001 to 0.406 mg.L-1 and 0.025 to 4.201 mg.L-1 respectively, with averages from 0.062 a 1.496 mg.L-1 (ammonia nitrogen), 0.019 to 0.080 mg.L-1 (nitrite) and 0.075 to 0.679 mg.L-1 (nitrate) in the Arienga River and from 0.248 to 0.392 mg.L-1 (ammonia nitrogen), 0.047 to 0.121 mg.L-1 (nitrite) and 0.791 to 1.247 mg.L-1 (nitrate) in the Murucupi River.

    The phosphate concentrations in the Arienga and Murucupi rivers ranged from 0.014 to 0.239 mg.L-1 and from 0.056 to 0.313 mg.L-1 respectively, with averages from 0.064 to 0.117 mg.L-1 in the Arienga River and from 0.109 to 0.187 mg.L-1 in the Murucupi River. The sulfate concentrations in the Arienga and Murucupi rivers ranged from 0.011 to 4.886 mg.L-1 and from 0.897 to 5.367 mg.L-1 respectively, with averages from 0.812 to 1.347 mg.L-1 in the Arienga River and from 1.743 to 2.474 mg.L-1 in the Murucupi River. The highest concentrations of total hardness in the Arienga and Murucupí rivers occurred in the dry period, with variations from 0.232 to 14.389 mg.L-1 and from 0.112 to 18.568 mg.L-1 respectively, with averages from 2.823 to 5.824 mg.L-1 in the Arienga River and from 3.101 to 8.769 mg.L-1 in the Murucupi River.

    From the analytical data obtained in this study it was possible to compare water quality of the Arienga and Murucupí rivers through groups formed by principal components in correlation matrices by degree of similarity.

    The physicochemical results of the rainy season for ebbing and flooding tide conditions provided the formation of 3 well defined groups as observed in Figure 2A, that is, in PC1 (43.5%), there was an optimal separation between groups 1 and 3 , in which most of the sampling points of the rivers Arienga and Murucupí are observed. Similar characteristics were observed in relation to group 2 formed in PC2 (20.4%) by sampling points close to the mouths of the Arienga and Murucupí rivers. In general, there is a transition in the physical-chemical characteristics of these waters between the sampling points in those of the extensions evaluated.

    In Figure 2B, referring to factorial load analyzes for two components, it was evidenced that the levels of dissolved oxygen and BOD represented the main factors for the formation of group 1 in the river Arienga, in this river a homogeneous characteristic was observed for BOD with higher values At the ends (springs and mouth) of the evaluated and heterogeneous extension to DO with increasing levels from the sources to its mouth in the Pará river, this behavior is probably related to several factors such as the presence and decomposition of organic matter introduced in the extension evaluated by other tributary water bodies, miscegenation and contribution of leachate materials in these waters due to the higher rainfall intensity in the seasonal period in question and the larger aeration area in its mouth.

    Figure 2. Analysis of main components of the score plot type (A) and loading plot (B) on the data of variables determined during the rainy season (February and May) under ebbing and flooding tide conditions in 2011. Note: AE (Arienga ebbing tide); AF (Arienga flooding Tide); ME (Murucupí ebbing tide); MF (Murucupí flooding tide).
     Analysis of main components of the score plot type (A) and loading plot (B) on the data of variables determined during the rainy season (February and May)   under ebbing and flooding tide conditions in 2011. Note: AE (Arienga ebbing tide); AF (Arienga flooding Tide); ME (Murucupí ebbing tide); MF (Murucupí flooding tide).

    In group 2, the physicochemical variables that had the same behavior were pH, temperature, DO, BOD and Hardness, therefore, the two rivers presented the same characteristics in their mouths for these variables. The variables that contributed most to the formation of group 3 were: electrical conductivity, total dissolved solids, ammoniacal nitrogen, nitrite, nitrate, sulfate and phosphate, showing that there is interference in the water quality of the river Murucupí by pollutants characteristic of domestic sewage originating from the communities located around this water body, especially at the sampling points closest to its sources. The environmental impacts caused by the spillage of chemical wastes in these waters over the years, can also have their degree of contribution in the water quality conditions of the Murucupí River from the release gradual of residues from the bottom sediment.

    Similar to the rainy season, the PC1 (43.4%) of Figure 3A (dry season) shows the formation of three groups (1, 2 and 3). Groups 1 and 2 presented similarity of 39.79% and were formed by most of the sampling points of the Arienga river, this time, in group 2, the sampling points located at the mouth of the river Arienga (AE6, AF5 and AF6) (ME1 and MF1), evidencing well heterogeneous characteristics in the waters of the Murucupí River, probably due to the lower influence of the rainfall in this seasonal period and consequently the greater concentration and dispersion of the variables analyzed.

    Figure 3. Analysis of main components of score plot type (A) and loading plot (B) on the data of the variables determined in the dry period (August and November) under ebbing and flooding tide and conditions in 2011. Note: AE (Arienga ebbing tide); AF (Arienga flooding tide); ME (Murucupí ebbing tide); MF (Murucupí flooding tide).
     Analysis of main components of score plot type (A) and loading plot (B) on the data of the variables determined in the dry period (August and November) under ebbing and flooding tide and conditions in 2011. Note: AE (Arienga ebbing tide); AF (Arienga flooding tide); ME (Murucupí ebbing tide); MF (Murucupí flooding tide).

    In the analyzes of factorial loads for two components on the data of the dry season (Figure 3B), it was observed that there was greater influence of the variables OD, BOD and ammonia nitrogen for the formation of group 1. In group 2, there was a greater influence of the BOD variable in the sampling points of the mouth of the river Arienga (AE5, AE6, AF4, AF5 and AF5) and of the nitrate and phosphate variables at the point of the Murucupí sources (ME1 and MF1). Group 3 repeated the same behavior of rainy season, where it was evidenced changes in concentration of variables, most likely by the influence of domestic sewage, a situation observed in field work through the visualization of emissaries (pipes) of wastewater located on the banks of the Murucupí River.

    Table 2 and Table 3 are the descriptive statistics (mean, standard deviation, maximum values and minimum values) applied to the values of the physicochemical variables determined in the rivers Arienga and Murucupí respectively, in the rainy (February and May) and dry (August and November) in ebbing and flooding tide conditions in 2011.

    Table 2. Descriptive statistics of the physical-chemical variables determined in the Arienga River in 2011.
      Rainy Season   Dry Season
    Physicochemical Variables Unit N Tide x̄ ±SD Maximum Minimum N x̄ ±DP Maximum Minimum
    Temperature °C 12 Ebbing 27±1.16 29 25 12 28±1.24 30 26
    12 Flooding 26±1.31 29 25 12 28±1.47 31 26
    pH - 12 Ebbing 5.76±0.82 6.75 4.77 12 5.55±0.64 6.47 4.79
    12 Flooding 5.70±0.92 7.21 4.75 12 6.25±0.94 7.33 4.87
    Electric Conductivity µ 12 Ebbing 22±9.61 37 13 12 21±13.33 48 7
    12 Flooding 21±10.24 42 13 12 25±16.40 49 4
    Total Dissolved Solids mg.L-1 12 Ebbing 11±4.73 18 7 12 11±5.79 22 6
    12 Flooding 11±5.20 21 7 12 13±8.23 26 2
    Dissolved Oxygen mg.L-1 12 Ebbing 5.21±0.64 6.45 4.40 12 6.29±1.17 7.98 4.44
    12 Flooding 5.88±0.63 7.16 5.19 12 6.24±0.77 7.83 5.34
    BOD mg.L-1 12 Ebbing 14±3.48 19 9 12 10±2.75 16Physicochemical Variables 6
    12 Flooding 11±3.03 16 8 12 9±2.41 14 5
    Ammoniacal-N mg.L-1 12 Ebbing 0.062±0.021 0.101 0.037 12 1.496±1.646 6.336 0.118
    12 Flooding 0.340±0.314 1.032 0.026 12 1.090±1.689 6.233 0.014
    Nitrite-N mg.L-1 12 Ebbing 0.019±0.008 0.033 0.008 12 0.028±0.012 0.057 0.011
    12 Flooding 0.040±0.037 0.121 0.003 12 0.080±0.097 0.334 0.005
    Nitrate-N mg.L-1 12 Ebbing 0.075±0.063 0.192 0.019 12 0.679±1.352 4.818 0.009
    12 Flooding 0.266±0.245 0.808 0.021 12 0.490±0.659 2.226 0.035
    Phosphate mg.L-1 12 Ebbing 0.097±0.036 0.152 0.023 12 0.117±0.062 0.239 0.055
    12 Flooding 0.066±0.044 0.190 0.014 12 0.064±0.029 0.140 0.032
    Sulfate mg.L-1 12 Ebbing 0.666±0.618 1.570 0.109 12 0.812±0.929 2.519 0.029
    12 Flooding 0.775±0.626 1.547 0.110 12 1.347±1.479 4.886 0.011
    Total Hardness mg.L-1 12 Ebbing 2.899±2.220 6.331 0.481 12 4.765±3.263 14.389 2.301
    12 Flooding 2.823±1.989 5.377 0.232 12 5.824±3.498 14.389 1.146

    N: Number of data pertaining to six (06) sampling points, with 12 data for each seasonal period; : Average; SD: Standard Deviation.
    Table 3. Descriptive statistics of the physicochemical variables determined in the Murucupí River in 2011.
    Physicochemical Variables Unit N Tide Rainy Season N Dry Season
    x̄ ±SD Maximum Minimum x̄ ±DP Maximum Minimum
    Temperature °C 14 Ebbing 28±0.62 29 27 14 30±0.99 32 28
    14 Flooding 28±0.52 28 27 14 30±0.88 32 29
    pH - 14 Ebbing 6.22±0.33 6.6 5.51 14 6.61±0.49 7.23 5.54
    14 Flooding 6.19±0.47 7.12 5.51 14 6.71±0.48 7.3 5.54
    Electric Conductivity µ 14 Ebbing 38±5.02 45 30 14 83±33.14 122 43
        14 Flooding 40±6.83 48 25 14 80±32.34 119 42
    Total Dissolved Solids mg.L-1 14 Ebbing 19±2.70 23 15 14 38±15.51 57 19
    14 Flooding 20±3.44 24 12 14 37±15.01 56 19
    Dissolved Oxygen mg.L-1 14 Ebbing 4.70±1.09 6.55 1.95 14 3.86±1.68 6.18 1.17
    14 Flooding 4.08±1.03 5.4 1.46 14 4.52±1.24 6.06 2.33
    BOD mg.L-1 14 Ebbing 15±5.25 26 7 14 12±2.24 15 7
    14 Flooding 10±2.95 17 6 14 9±1.27 11 7
    Ammoniacal-N mg.L-1 14 Ebbing 0.283±0.507 2.021 0.027 14 0.248±0.170 0.684 0.021
    14 Flooding 0.273±0.235 0.776 0.025 14 0.392±0.209 0.770 0.026
    Nitrite-N mg.L-1 14 Ebbing 0.121±0.112 0.406 0.025 14 0.072±0.047 0.164 0.011
    14 Flooding 0.050±0.042 0.135 0.012 14 0.047±0.053 0.168 0.001
    Nitrate-N mg.L-1 14 Ebbing 0.791±0.649 2.346 0.168 14 1.025±1.004 3.510 0.033
    14 Flooding 1.247±1.039 3.368 0.294 14 1.168±1.336 4.201 0.025
    Phosphate mg.L-1 14 Ebbing 0.109±0.034 0.169 0.056 14 0.136±0.067 0.275 0.059
        14 Flooding 0.176±0.035 0.278 0.123 14 0.187±0.081 0.313 0.057
    Sulfate mg.L-1 14 Ebbing 2.137±1.061 5.293 1.063 14 1.743±0.925 3.550 0.897
    14 Flooding 2.474±1.241 5.367 1.188 14 1.992±0.935 3.983 1.027
    Total Hardness mg.L-1 14 Ebbing 3.415±1.170 5.311 1.241 14 8.769±4.962 18.568 1.832
    14 Flooding 3.101±1.291 4.671 0.112 14 8.186±5.694 17.731 1.792

    N: Number of data pertaining to seven (07) sampling points, with 14 data for each seasonal period; : Average; SD: Standard Deviation.


    The more acidic pH values in surface water are due to the influence of soil leaching and riparian forest, which through organic decomposition releases humic and fulvic acids to these aquatic environments 35, 36, 37, 38. In the Caeté (Bragança) and Arari (Marajó Island) rivers in the Pará State-Brazil and other Amazonian rivers such as Solimões and Purus, in the Amazonas State, the values of pH and temperature were similar to those recorded in the rivers Arienga and Murucupí, with variations of 3.8 to 7.0 and 25 to 34 °C respectively 30, 39, 40, 38. The temperature of the surface waters in the Amazonian environments oscillates according to the thermal amplitude of daily and seasonal, being able to vary according in the depth of the river and time of day, with possibility of affecting the characteristics physical, chemical and biological of the aquatic ecosystem38(Alves et al., 2012). The study in the water bodies of Malawi in East Africa pointed to the influence of industrial effluent discharges, with pH values between 6.3 and 7.5 40, similar to the surface waters of the Murucupí River, which were also impacted by domestic and industrial sewage 41.

    The highest values of these variables were determined in the Murucupí River, indicating a higher presence of dissolved solids, possibly due to greater anthropic influence through the launching of sewage and deforestation in areas near to its banks. The transport of solid materials in different aquatic environments influences in the rates and types of chemical, biological processes and geomorphic transformations42, 43. As example of these different characteristics, it is observed the values of electrical conductivity in the waters of the Solimões and Purus rivers and their tributaries which had variations from 0.02 to 26.4 μ in the black waters and from 47 to 122.4 μ in the white waters31. In the Maracanã River, northeast Pará State-Brazil, TDS values ranged from 10 to 28 mg.L-1 in distinct seasonal periods and in the Madeirinha and Acará rivers on the left bank of the Madeira River in Amazonas State, this variation was 14.2 to 74.2 mg.L-1 44, 45.

    The concentrations of DO were higher in the waters of the Arienga River, while the Murucupí River presented less oxygenated water, a fact that can be explained by the greater amount of organic matter in this river due to the release of domestic sewage, biochemical decomposition of organic matter and respiration by the aquatic ecosystem contribute to the reduction of dissolved oxygen in water 46. Other studies corroborate this information, for example, DO values in water bodies located in the island of Marajó-PA ranged from 2.98 to 5.29 mg.L-1 in the rainy season and 2.59 to 5.88 mg.L-1 in the dry season, the authors consider that the dynamics of this gas in aquatic ecosystems is related to its non-conservative behavior, for example, the decrease of water levels of the rivers in the dry season and the introduction of semidiurnal tides favors the increase of the concentration of dissolved oxygen in surface waters38. Similar values of DO were also recorded in other rivers in Brazil, such as the case of the Cachoeira River in the Bahia State, with values between 4.1 and 7.7 mg.L-1 and higher values in the Turvo Limpo River in Minas Gerais State, that oscillated between 7.7 and 9.1 mg.L-1 47, 48.

    The Arienga and Murucupí rivers had a similar distribution in relation to the BOD concentration, the highest records occurred in the rainy season, this fact may be related to the greater amount of organic matter introduced through resuspension processes or by action of the high tides that flooding the river banks, as well as the discharge of domestic sewage in the region 38. The concentrations of BOD in the rivers Arienga and Murucupí had similar behavior to the waters of the Parauapebas River, southeastern Pará State-Brazil, the BOD values varied 2.2 and 9.79 mg.L-1 with largest records at points closest to the urban center where the discharges of effluent are more intense 49. Turvo Limpo River in Minas Gerais State presented higher values with ranging from 13.3 to 411 mg.L-1, for the authors of this study, high BOD values may be related to the presence of large amounts of biodegradable biomass and discharge of domestic effluents in the hydrographic basin 48.

    The Arienga River presented a distinct behavior in relation to the maximum values of ammonia nitrogen, nitrite and nitrate, with higher concentrations observed in the dry season, while in the Murucupí river, the maximum values were similar between the seasonal periods. The Arienga River may have been influenced by diffuse sources of natural or anthropogenic origin and the Murucupí River most likely suffered greater influence of domestic sewage besides the particulate material leached through rains. In aquatic ecosystems of the Brazil is perceived great anthropic influence, mainly in the dissolved inorganic forms, with emphasis of ammonia nitrogen and nitrate, a reality observed in this study. Table 4 shows the values of the nitrogen forms determined in the aquatic ecosystems of different regions of Brazil.

    Table 4. Ammonia nitrogen, nitrate and nitrite, values in Brazilian waters.
    Author Season/Year Ammonia(mg.L-1) Nitrite(mg.L-1) Nitrate(mg.L-1) Water Body/Location
    Horbe et al. (2005)30 RAINY (1998) 0.12 – 0.29 < LD 0.02 – 0.16 Igarapé Água Branca/ Amazonas State
    DRY (1998) 0.10 – 1.10 < LD 0.01 – 0.51 Puraquequara River/Amazonas State
    Richter et al. (2007)53 N.I (2002/2003) 0.3 – 33.8 N.A 0.80 – 2.70 Sistema Guarapiranga SP
    Jordão et al. (2007)48 DRY (2005) 2.8 – 28 N.A 0.8 – 7.4 Turvo Limpo River/Minas Gerais State
    Pinto et al. (2009)37 RAINY (2003) 0.32 – 0.49 < LD N.A Igarapé Tarumã and Porto da Ceasa/ Amazonas State
    1.12 – 9.25 0.01 – 8.23 N.A Igarapés São Raimundo and Educandos/ Amazonas State
    Aguiar Netto (2013)50 DRY and RAINY (2005/2006) < LD – 1.08 < LD – 0.08 0.02 – 1.04 Poxim River/Sergipe State

    N.I: Not Informed; <LD: Less Than Limit of Detection; N.A: Not Analyzed.

    Phosphate concentrations were similar in the Arienga and Murucupí rivers, with higher values in the dry period, but without great variations. Values close to those recorded in the present study were observed in other rivers in Brazil, such as the phosphate values recorded in the Tibagi River between 0.02 and 0.35 mg.L-1, Paraná State51. The concentration of phosphate near the discharge of industrial effluents in the Igarapé Curuperê River in the municipality of Barcarena-Pará reached 0.220 mg.L-1, with values recorded in the margins of this water body varying between 0.050 mg.L-1 and 0.175 mg.L- 1. In all evaluated extension of this water body, the variations were from 0.062 mg.L-1 to 0.430 mg.L-1 at ebbing tide and from 0.124 mg.L-1 to 0.290 mg.L-1 in the flood tide. In the same area of study, in the Igarapé Dendê, values ranging from 0.010 mg.L-1 to 0.182 mg.L-1 were recorded at ebb tide and from 0.050 to 0.110 mg.L-1 in the flooding tide52. Among the main factors responsible for the increase of phosphate in surface water are the releases of domestic and industrial waste, therefore, the mainly responsible for levels of phosphate in aquatic environments47,51.

    The Arienga and Murucupí rivers presented similar concentrations of sulfate in their waters, however, their highest values were recorded in different periods. The highest concentrations in the Arienga river occurred in the dry period, while in the Murucupí river the maximum values were found in the rainy season. Sulphate concentrations in the two rivers were close to those reported by other authors in studies in Brazil, in most cases the presence of sulfate is related to the geology of the sites, such as those observed in rivers affluent to the rivers Solimões and Purus, with averages of 5.2 mg.L-1 and 7.7 mg.L-1, while in the Solimões and Purus rivers the averages were 7.1 mg.L-1 and 5.8 mg.L-1 (31). Other authors reported variations from 1.30 mg.L-1 to 26.5 mg.L-1 in the Guarapiranga system in São Paulo and from 0.00 mg.L-1 to 12.60 mg.L-1 in two rivers of the Federal District. Brazil 53,54.

    In another study on the Murucupí river, hardness ranged from 11 mg.L-1 to 21 mg.L-1 and according to the author, hardness concentrations are typical of the region and the fact that the highest concentrations are found in the period Dry is related to the intrusion of brackish waters of the Marajó Bay in the Barcarena estuarine system55. In the Água Branca stream, mean values of hardness of 0.40 mg.L-1 were recorded in the rainy season and of 0.29 mg.L-1 in the dry period and in the Puraquequara stream, the average found was 0.46 mg.L-1 (30).

    In study in the Ocoí River basin it was used the Principal Component Analysis (PCA), starting from obtained results found that diffuse sources of pollution were more evident and predominant in the rainy season56. The PCA also was used to evaluate the water quality of the Tibagi River in Ponta Grossa, allowed to observe the level of deterioration through point and diffuse sources near the industrial district of the city57. Other study carried in 2007 used this statistical tool to verify if the waters of the Tarumã-Açú River was polluted with the residues of the sanitary landfill near of this hydrographic basin and found that a differentiation in water quality occurred between the points sampled, well as they said that the water body was still able to reduce the impact of the sanitary landfill58. In aquatic systems studied in northern Greece, multivariate analysis helped identify four groups with different physicochemical characteristics and pollution levels59. Likewise, PCA significantly helped in the identification of similar and different quality groups in the extensions of the water bodies evaluated in this study.


    The variables studied in these water bodies have their concentrations with well-defined trends in relation to rainfall and variation in physicochemical characteristics in the extensions evaluated, either by the action of natural or anthropogenic agents. This environmental behavior is clearly observed for the variables temperature, pH and dissolved oxygen, which presented very similar characteristics in the two rivers, that is, lower values in their sources and increase in the mouths.

    From the multivariate analysis, it can be said that there is a physicochemical difference between the Arienga and Murucupí rivers, where it was possible to observe that the Murucupí River presented higher concentrations for most of the physical-chemical variables analyzed in relation to the Arienga river, indicating that the Arienga River may be more influenced by local geology, while in the Murucupí river both geology and anthropic factors are responsible for its physicochemical characteristics was visualized lower anthropic influence in surrounding of Arienga River, however, demand of the tourists in leisure areas during the dry season may have influenced the levels of nitrogen matter introduced in this water body. The information generated in this study allows us to say that the Murucupí river suffered a greater anthropogenic influence, mainly due to the domestic sewage released in this water body without due treatment, as well as other adjacent contributions that provided different physicochemical characteristics for these waters. The industrial activities developed in this region and other anthropogenic contributions have already caused great damage to certain environmental compartments, among them, the water bodies, through recurrent industrial waste leaks and untreated sewage launching. This information on the physicochemical characteristics of the rivers studied will serve for population, competent authorities and the scientific community in order to take more detailed measures and studies to evaluate the risk factors environmental and population health in region.


    Thanks to IEC/FIDESA/MPE-PA Project (Process 001/2007), Evandro Chagas Institute and Federal Rural University of Amazonia for funding, laboratory support, and academic contributions in the surveys. Thanks Dr. Ricardo de Deus for help with the map elaboration. 


    1.G S Shil'krot, S V Yasinskii. (2002) Spatial and temporal variability of biogenic elements flow and water quality in a Small River. , Moscow, Russia, Water Resources 29, 312-318.
    2.Stamatis G, Gartzos E. (1999) The silica supersaturated waters of northern Evia and eastern central Greece. Hydrological Processes. 13, 2833-2845.
    3.Kelepertsis A, Alexakis D, Kita I. (2001) Environmental geochemistry of soils and waters of Susaki area. , Korinthos, Greece. Environmental Geochemistry and Health 23, 117-135.
    4.Appelo C A J, Postma D. (2005) Geochemistry, groundwater and pollution. , Leiden, New York: Balkema, 2ª 649, p..
    5.Lambrakis N. (2006) Multicomponent heterovalent chromatography in aquifers. Modelling salinization and freshening phenomena in field conditions. , Journal of Hydrology 323, 230-243.
    6.Stamatis G, Lambrakis N, Alexakis D, Zagana E. (2006) . Groundwater quality in eastern Attica (Greece). Hydrological Processes 20, 2803-2818.
    7.G D Bathrellos, H D Skilodimou, Kelepertsis A, Alexakis D, Chrisanthaki I et al. (2008) Environmental research of groundwater in the urban and suburban areas of Attica region. , Greece. Environmental Geology 58, 11-18.
    8.Alexakis D. (2008) Geochemistry of stream sediments as a tool for assessing contamination by arsenic, chromium and other toxic elements: East Attica region. , Greece. European Water 21(22), 57-72.
    9.Palma P, Alvarenga P, Palma V, R M Fernandes, Soares A M V M et al. (2010) Assessment of anthropogenic sources of water pollution using multivariate statistical techniques: A case study of the Alqueva’s reservoir. , Portugal. Environmental Monitoring and Assessment 165, 539-552.
    10.Saeedi M, Abessi O, Sharifi F, Meraji H. (2010) Development of groundwater quality index. Environmental Monitoring and Assessment163(1-4):. 327-335.
    11.Suthar S, Sharma J, Chabukdhara M, A K Nema. (2010) Water quality assessment of river Hindon at Ghaziabad, India: Impact of industrial and urban wastewater. Environmental Monitoring and Assessment. 165, 103-112.
    12.H, G H Karami, Saadat S. (2011) A study on chemical properties of groundwater and soil in ophiolitic rocks in Firuzabad, east of Shahrood, Iran: With emphasis to heavy metal contamination. Environmental Monitoring and Assessment. 174, 573-583.
    13.S P Pathak, Kumar S, P W Ramteke, R C Murthy, J W Bhattacherjee et al. (1994) Potability of water sources in relation to metal and bacterial contamination in some northern and northern-eastern districts of India. , Environmental Monitoring and Assessment 33, 151-160.
    14.Cotta J A O, Rezende M O O, M R Piovani. (2006) Avaliação do teor de metais em sedimento do rio Betari no Parque Estadual Turístico do Alto Ribeira-PETAR, São Paulo. , Brasil. Quimica Nova 29(1), 40-45.
    15.F A Jardim, Resende R M S, M, Giani A, D A Cerqueira et al. (2008) Cyanobacteria blooms in waters of river intake areas in Minas Gerais – Brazil, during the dry season of2007–Contingency Plants. In: Simpósio Ítalo-Brasileiro de Engenharia Sanitária e Ambiental. Florença (Itália).
    16.Belo A, S P Quináia, A L Pletsch. (2010) . Avaliação da Contaminação de Metais em Sedimentos Superficiais das Praias do Lago De Itaipu. Quimica Nova 33(3), 613-616.
    17. (2012) Instituto Internacional de Educação do Brasil-IEB. 62, p.
    18.Instituto Evandro Chagas-IEC (2008) Relatório Técnico. Interações de vigilância ambiental em saúde na área industrial e portuária dos Municípios de Abaetetuba e Barcarena. , Ananindeua-PA 46, 2008.
    19.Instituto Evandro Chagas-IEC (2009) Relatório técnico SAMAM 001: caracterização dos impactos ambientais, danos ao ecossistema e riscos a saúde decorrentes do lançamento no rio Murucupí de efluentes do processo de beneficiamento de bauxita. 32 p [on line]. , Barcarena-Pará. Ananindeua, PA, Brasil
    20.Souza A P S, Lisboa R C L. (2006) Aspectos florísticos e taxonômicos dos musgos do município de. , Barcarena, Pará. Bol. Mus. Para, Emílio Goeldi. Ciências Naturais Belém 1(1), 81-104.
    21.. Instituto Brasileiro de Geografia e Estatística-IBGE (2017). Informações gerais sobre as cidades de Abaetetuba e Barcarena no Estado do Pará. .
    22.Porto L J L S. (2009) Estudo da qualidade dos sedimentos de fundo do Rio Barcarena-PA. Dissertação de Mestrado. Universidade Federal do Pará. Centro de Geociências (geoquímica e petrologia). , Belém-Pará 91, p..
    23.Instituto Nacional de Metereologia-INMET (2009) Banco de dados metereológicos para ensino e pesquisa (BDMEP).
    24.Marinha do Brasil. (2011) Diretoria de Hidrografia e Navegação: Previsões de marés do porto de Vila do Conde-PA. Centro de Hidrografia da Marinha. Banco Nacional de Dados Oceanográficos.
    25.Matta M A S. (2002) Fundamentos Hidrogeológicos para a Gestão Integrada dos Recursos Hídricos da Região de. Belém/Ananindeua-Pará, Brasil. Tese de Doutorado. Ed. Universidade Federal do Pará. Centro de Geociências, Belém-Pará 584, p..
    26.F M Almeida, Matta M A S, J B Prado, Dias E R F, Bandeira I N et al. (2006) Análise geométrica e susceptibilidade à contaminação dos sistemas aquíferos da região de Barcarena/PA. XIV Congresso Brasileiro de Águas Subterrâneas.
    27.R D Oliveira. (2002) Zoneamento Agroambiental do Município de Barcarena-Pará. Dissertação de Mestrado. Faculdade de Ciências Agrárias do Pará. , Belém-Pará 220, p..
    28.APS Souza, RCL Lisboa. (2005) Musgos (Bryophyta) na Ilha Trambioca. , Barcarena, PA, Brasil, Acta bot. bras 19(3), 487-492.
    29.Sioli H, Klinge H. (1962) Solos, típicos de vegetação e águas na Amazônia. , Amazoniana 1, 27-41.
    30.Horbe A M C, Gomes I L F, S F Miranda, Silva M S R. (2005) Contribuição à hidroquímica de drenagens no Município de Manaus – AM. , Acta Amazônica 35(2), 119-124.
    31.Queiróz M M A, Horbe A M C, Seyler P, Moura C A V. (2009) Hidroquímica do rio Solimões na região entre Manacapuru e Alvarães-Amazonas-Brasil. , Acta Amazônica 39(4), 943-952.
    32. (2005) Conselho Nacional de Meio Ambiente-CONAMA. Alterada pelas Resoluções 410/2009 e 430/2011. Diário Oficial da República Federativa do Brasil , Brasília, DF 53, 58-63.
    33.Public American.Health Association-APHA (2005). Standard methods for the examination of water and wastewater. 21th. ed. Washington 1600.
    34. (2007) United States Environmental Protection Agency-USEPA. Method9056A:determination of inorganic anions by ion chromatography. , Revision 1, 19.
    35.Sioli H. (1985) Amazonia: fundamentos da ecologia da maior regiao de florestas tropicais. , Ed. Petrópolis: Vozes 72, p..
    36.F A Esteves. (1998) . Fundamentos de limnologia. 2. Ed. Rio de Janeiro: Interciência 602, p..
    37.Pinto A G N, Horbe A M C, Silva M S R, S A Fonseca, Miranda S A F et al. (2009) Efeitos da ação antrópica sobre a hidrogeoquímica do rio Negro na orla de Manaus/AM. , Acta Amazônica 39(3), 627-638.
    38.Alves I C C, El-Robrini M, Santos M L S, S M Monteiro, Barbosa L P F et al. (2012) Qualidade das águas superficiais e avaliação do estado trófico do Rio Arari (Ilha de Marajó, norte do Brasil). , Acta Amazônica 42(1), 115-124.
    39.Pereira L C C, M C, D O Guimarães, J B Matos, R M Costa. (2010) Seasonal effects of wastewater to the water quality of the Caeté river estuary, Brazilian Amazon. Anais da Academia Brasileira de Ciências. 82(2), 467-478.
    40.Phiri O, Mumba P, Moyo B H Z, Kadewa W. (2005) Assessment of the impact of industrial effluents on water quality of receiving rivers in urban areas of. , Malawi.International Journal of Environmental Science and Technology 2(3), 237-244.
    41.A C Medeiros, Faial K R F, Faial K C F, Lopes I D S, M O Lima et al. (2017) Quality index of the surface water of Amazonian rivers in industrial areas in Pará. , Brazil, Marine Pollution Bulletin 123, 156-164.
    42.Bolin B, R B Cook. (1983) The major biogeochemical cycles and their interactions (Scope Report 21). United States:. N. p., Web
    43.Mertes L A K, M O Smith, J B Adams. (1993) Estimating Suspended Sediment Concentrations in Surface Waters of the Amazon River Wetlands from Landsat Images. Remote Sensing of Environment. 43, 281-301.
    44.F, Lima W N L, J C Dias. (2009) Avaliação hidrogeoquímica de áreas selecionadas na bacia hidrográfica do rio maracanã (nordeste do Pará). Holos Environment. 9(2), 167-182.
    45.Horbe A M C, Queiroz M M A, Moura C A V, Toro M A G. (2013) Geoquímica das águas do médio e baixo rio Madeira e seus principais tributários - Amazonas -. , Brasil. IBGE 43(4), 489-504.
    46.G J Janzen, H E Schulz, A W Lamon. (2008) . Medidas da Concentração de Oxigênio Dissolvido na Superfície da Água. Revista de Engenharia Sanitária e Ambiental 13, 3.
    47.Lucio M Z T P Q L, S, Silva D M L. (2012) Hydrochemistry of Cachoeira River. , (Bahia State, Brazil), Acta Limnologica Brasiliensia 24(2), 181-192.
    48.C P Jordao, Ribeiro P R S, A T Matos, Fernandes R B A. (2007) Aquatic Contamination of the Turvo Limpo River Basin at the Minas Gerais State. , Brazil.Journal of The Brazilian Chemical Society 18(1), 116-125.
    49.G W Siqueira, Aprile F, A M Miguéis. (2012) Diagnóstico da qualidade da água do rio Parauapebas (Pará –. , Brasil). Acta Amazonica 42(3), 413-422.
    50.O Aguiar Netto A, Garcia C A B, Alves J P H, R A Ferreira, M G Silva. (2013) Physical and chemical characteristics of water from the hydrographic basin of the Poxim River, Sergipe State, Brazil.Environmental Monitoring and Assessment. 185, 4417-4426.
    51.M C Bisinoti, Yabe M J S, Gimenez S M N. (2005) Using principal component analysis to characterize the Tibagi River hydrographic basin. , Paraná State, Brazil, Journal of Food, Agriculture and Environment.3(3and4): 153-160.
    52.M O Lima, Santos E C O, I M Jesus, A C Medeiros, Faial K C F et al. (2011) Assessment of Surface Water in Two Amazonian Rivers Impacted by Industrial Wastewater. , Barcarena City, Pará State (Brazil), Journal of the Brazilian Chemical Society 22(8), 1493-1504.
    53.E M Richter, Fornaro A, C L Lago, Agnes L. (2007) Avaliação da composição química de águas do Sistema Guarapiranga: estudo de caso nos anos de. , Quimica Nova 30(5), 1147-1152.
    54.Muniz D H F, A S Moraes, I S Freire, Cruz C J D, Lima J E F W et al. (2011) Evaluation of water quality parameters for monitoring natural, urban, and agricultural areas in the Brazilian Cerrado. , Acta Limnologica Brasiliensia 23(3), 307-317.
    55.Pereira S F P, M A Lima, K H Freitas, C S Mescouto, A F Saraiva. (2007) Estudo químico ambiental do rio Murucupí-Barcarena, PA, Brasil, área impactada pela produção de alumínio. , Revista Ambi-Água 2(3), 62-82.
    56.G S Silva, G S Silva, E R Sousa, Konrad C, C et al. (2009) Phosphorus and nitrogen in waters of the Ocoí River Sub-basin, Itaipu Reservoir Tributary.Journal of The Brazilian Chemical Society. 20(9), 1580-1588.
    57.C M Zimmermann. (2008) Avaliação da qualidade do corpo hídrico do rio tibagi na região de ponta grossa utilizando análise de componentes principais (PCA). , Quimica Nova 31(7), 1727-1732.
    58.G P Santana, Barroncas P S R. (2007) Estudo de metais pesados (Co. Pb e Zn) na Bacia do Tarumã-Açu Manaus-(AM). Acta Amazonica , Cu, Fe, Cr, Ni, Mn 37(1), 111-118.
    59.Simeonov V, J A Stratis, Samara C, Zachariadis G, Voutsa D et al. (2003) Assessment of the surface water quality in Northern Greece. , Water Research 37, 4119-4124.