scholarly journals Limnological Quality: Seasonality Assessment and Potential for Contamination of the Pindaré River Watershed, Pre-Amazon Region, Brazil

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 851
Author(s):  
Jamilly N. Muniz ◽  
Klinger G. Duarte ◽  
Fábio H. Ramos Braga ◽  
Neuriane S. Lima ◽  
Darlan F. Silva ◽  
...  
Keyword(s):  
Rainy Season ◽  
Principal Component ◽  
Dry Season ◽  
Water Drainage ◽  
Multivariate Statistical ◽  
Data Set ◽  
E Coli ◽  
Sampling Points ◽  
Microbiological Parameters ◽  
Nitrite Nitrate

Watersheds are defined as a set of lands where water drainage occurs through rivers and their tributaries. A large quantity of water resources exist in the state of Maranhão, Brazil, where rivers and their basins must meet environmental quality standards defined by the limits set out in national environmental council (CONAMA) legislation 357/05 for physicochemical and microbiological parameters, including parasites. Multivariate statistical techniques were applied to study the temporal and spatial variations in water quality of a segment of the Pindaré River. The data set included nine parameters for three sampling points over eleven months. Principal component analysis grouped the monitored sampling points into four clusters and identified electrical conductivity, temperature, total dissolved solids (TDS), pH, salinity, and Escherichia coli as being associated with the dry season and nitrite, nitrate, and turbidity as being associated with the rainy season. Three principal components explained 83.80% of the data variance during the rainy and dry seasons. The evaluated correlations indicated that during the rainy season, nitrite (~0.18 mg L−1) and turbidity (~46.00 NTU) levels were the highest, but pH was at its lowest (~6.61). During the dry season, TDS (~155.00 mg L−1) and pH (~8.10) were highest, and E. coli bacteria was more abundant.

scholarly journals Evaluation of the quality of superficial sediment using principal components analysis of the physical–chemical attributes of the Mearim River – Brazil

2020 ◽  
Vol 42 ◽  
pp. e5
Author(s):  
Neuriane Silva Lima ◽  
Darlan Ferreira da Silva ◽  
Wallace Ribeiro Nunes Neto ◽  
Delmo Matos da Silva ◽  
Leila Cristina Almeida de Sousa ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Rainy Season ◽  
Principal Component ◽  
Component Analysis ◽  
Dry Period ◽  
Data Set ◽  
Inorganic Matter ◽  
Sampling Points

The Mearim River is one of the main rivers of Maranhão, which, over the years, has been affected from pollution caused by human activities such as deforestation, disposal of domestic effluents, and agricultural activities, among others. The objective of this research was to evaluate the environmental quality of the Mearim River through the study of the sediment in different periods. In order to investigate this question, four sampling points (P1- Balneário, P2-Cais, P3-Trizidela, and P4-Matadouro) were submitted to particle size analysis (clay, silt, and fine sand) and physico-chemical analyses (pH, organic matter, and inorganic and organic carbon). Two principal components were generated in principal component analysis, explaining 73% of the total variance among the parameters within the studied periods. The overall analysis of the data set by principal component analysis highlighted two clusters: one relating the attributes to three sampling points analyzed in the rainy season and another relating the attributes to four sampling points analyzed in the dry period. Multivariate analysis of the data showed that the orga­­­­­­­nic matter, clay, and pH parameters were directly correlated with the dry period (correlation coefficients 0.41), and inorganic matter (correlation coefficient = | 0,414) was more sensitive in the rainy season.

scholarly journals Seasonal Variation of Rainy and Dry Season Per Capita Water Consumption in Freetown City Sierra Leone

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 499
Author(s):  
Salmatta Ibrahim A ◽  
Fayyaz Ali Memon ◽  
David Butler
Keyword(s):  
Seasonal Variation ◽  
Water Use ◽  
Water Consumption ◽  
Low Income ◽  
Rainy Season ◽  
Predictor Variable ◽  
Dry Season ◽  
Data Set ◽  
Per Capita ◽  
End Use

Ensuring a sustainable urban water supply for developing/low-income countries requires an understanding of the factors affecting water consumption and technical evidence of individual consumption which can be used to design an improved water demand projection. This paper compared dry and rainy season water sources available for consumption and the end-use volume by each person in the different income groups. The study used a questionnaire survey to gather household data for a total of 398 households, which was analysed to develop the relationship between per capita water consumption characteristics: Socio-economic status, demographics, water use behaviour around indoor and outdoor water use activities. In the per capita water consumption patterns of Freetown, a seasonal variation was found: In the rainy season, per capita water consumption was found to be about 7% higher than the consumption for the full sample, whilst in the dry season, per capita water consumption was almost 14% lower than the full survey. The statistical analysis of the data shows that the average per capita water consumption for both households increases with income for informal slum-, low-, middle- and high-income households without piped connection (73, 78, 94 and 112 L/capita/day) and with connection (91, 97, 113 and 133 L/capita/day), respectively. The collected data have been used to develop 20 statistical models using the multiple linear stepwise regression method for selecting the best predictor variable from the data set. It can be seen from the values that the strongest significant relationships of per capita consumption are with the number of occupants (R = −0.728) in the household and time spent to fetch water for use (R = −0.711). Furthermore, the results reveal that the highest fraction of end use is showering (18%), then bathing (16%), followed by toilet use (14%). This is not in agreement with many developing countries where toilet use represents the largest component of indoor end use.

scholarly journals What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages?

2018 ◽  
Vol 35 ◽  
pp. 1-12
Author(s):  
Cynthia Diniz Souza ◽  
Vandick S. Batista ◽  
Nidia Noemi Fabré
Keyword(s):  
Wind Speed ◽  
Rainy Season ◽  
Fish Assemblages ◽  
Principal Component ◽  
Dry Season ◽  
Community Diversity ◽  
Tropical Species ◽  
Coastal Fish ◽  
Wide Range ◽  
Diversity Profiles

Seasonal ecological effects caused by temperature and photoperiod are typically considered minimal in the tropics. Nevertheless, annual climate cycles may still influence the distribution and abundance of tropical species. Here, we investigate whether seasonal patterns of precipitation and wind speed influence the structure of coastal fish assemblages and fishing yields in northeast Brazil. Research trips were conducted during the rainy and dry seasons using commercial boats and gear to sample the fish community. Diversity was analyzed using abundance Whittaker curves, diversity profiles and the Shannon index. Principal Component Analysis (PCA) was used to analyze associations between the abundance of species and various environmental variables related to seasonality. A total of 2,373 fish were collected, representing 73 species from 34 families – 20 of which were classified as both frequent and abundant. Species richness was greater and more equitable during the rainy season than the dry season – driven by changes in the precipitation rather than to wind speed. Species diversity profiles were slightly greater during the rainy season than the dry season, but this difference was not statistically significant. Using PCA was identified three groups of species: the first associated with wind speed, the second with precipitation, and the third with a wide range of sampling environments. This latter group was the largest and most ecologically heterogeneous. We conclude that tropical coastal fish assemblages are largely influenced by local variables, and seasonally mediated by annual changes related to precipitation intensity and wind speed, which in turn influences fishery yields.

scholarly journals Seasonal study of contamination by metal in water and sediment in a sub-basin in the southeast of Brazil

2011 ◽  
Vol 71 (4) ◽  
pp. 833-843 ◽  
Author(s):  
WAC. Chiba ◽  
MD. Passerini ◽  
JAF. Baio ◽  
JC. Torres ◽  
JG. Tundisi
Keyword(s):  
Rainy Season ◽  
Principal Component ◽  
Dry Season ◽  
Seasonal Differences ◽  
Sediment Samples ◽  
Fluorescent Lamps ◽  
Water And Sediment ◽  
Temporal Occurrence ◽  
Bodies Of Water ◽  
Water And Sediment Samples

The spatial and temporal occurrence of heavy metals (Al, Cd, Pb, Zn, Cr, Co, Cu, Fe, Mn and Ni) in water and sediment samples was investigated in a sub-basin in the southeast of Brazil (São Carlos, SP). All samples were analysed using the USEPA adapted metal method and processed in an atomic absorption spectrophotometer. The discriminant analysis demonstrated that there are significant seasonal differences of metal distribution in the water data, but there are no differences to sediment. The basin studied has high levels of contamination by toxic metals in superficial water and sediment. The superficial water, in the rainy season, presented high levels of Cr, Ni, Pb and Cd, while in the dry season it presented high levels of Zn and Ni. The Principal Component Analysis demonstrated that the season has a huge influence on the levels, types and distribution of metals found in water. The source of contamination was probably diffuse, due to products such as batteries and fluorescent lamps, whose dump discharge can contaminate the bodies of water in the region in the rainy season. Due to fires from the harvest of sugar cane, high levels of Zn were found into the environment, in the dry season.

Principal Component Analyses of Potential Repository Groundwaters

1999 ◽  
Vol 556 ◽  
Author(s):  
H. Sasamoto ◽  
P. Salter ◽  
M. Apted ◽  
M. Yuiv
Keyword(s):  
Radioactive Waste ◽  
Principal Component ◽  
Chemical Components ◽  
Compacted Clay ◽  
Multivariate Statistical ◽  
Data Set ◽  
High Level Radioactive Waste ◽  
Scenario Analyses ◽  
Statistical Analysis Technique ◽  
High Level

AbstractThe chemical composition of ambient groundwater for a geological, high level radioactive waste repository is of crucial significance to issues such as radioelement solubility limits, sorption, corrosion of the overpack, behavior of compacted clay buffers, and many other factors involved in repository safety assessment. At this time, there are no candidate repository sites established in Japan for the geological disposal of high-level radioactive waste, and only generic rock formations are under consideration. It is important that a small, but representative set of groundwater types be identified so that defensible models and data for generic repository performance assessment can be established. Over 15,000 separate analyses of Japanese groundwaters have been compiled into a data set for the purpose of evaluating the range of geochemical conditions for waste repositories in Japan. This paper demonstrates the use of a multivariate statistical analysis technique, principal component analysis (PCA), to derive a set of statistically based, representative groundwater categories from the multiple chemical components and temperature that characterize the deep Japanese groundwater analyses. PCA also can be used to guide the selection of groundwaters that could be used in scenario analyses of future geological events in Japan.

scholarly journals The Corrosivity Level of Rawa Pening Downstream Surface Water in the Dry and Rainy Season

2020 ◽  
Vol 17 (3) ◽  
pp. 215-222
Author(s):  
Purwono Purwono ◽  
Wiharyanto Oktiawan ◽  
Titik Istirokhatun ◽  
Agus Nurfaiz
Keyword(s):  
Surface Water ◽  
Rainy Season ◽  
Agricultural Land ◽  
Ph Value ◽  
Dry Season ◽  
Hydroelectric Power ◽  
Geological Material ◽  
Measurement Results ◽  
Microbiological Parameters

Corrosion is an important factor that can affect the quality of air used by humans. This has an impact on health and economic factors, damage to air distribution equipment. The level of corrosivity of surface water as raw water for drinking water is important to be examined before the water enters the processing process or other uses such as hydroelectric power (PLTA). This study aims to measure the level of water corrosivity on the surface of the Pening swamp during the dry and rainy seasons in 2018. Taking air samples on the surface of the Pening swamp, then carrying out laboratory tests on the parameters of air corrosivity. The results showed that the downstream surface of the Pening swamp was not corrosive in terms of pH, temperature, TDS, and chloride parameters. The pH value in the dry season (J1) is 7.00, while in the rainy (J2) it is 7.77 and is non-corrosive. The temperature values are 28.6oC and 29.3oC in the rainy and dry seasons, respectively. The TDS measurement results in the dry season are lower than the rainy season by a difference of 12 mg / l. In the dry season it is 141 mg / l and the rainy season is 153 mg / l. This increase probably came from geological material (geological material) such as rocks and soil around the Pening Swamp Lake. Other sources of TDS include urban land, road workers, agricultural land and pasture. Human activities also increase in the increase of TDS in water including domestic activities (bathing and washing), trade, and industry. Chloride levels were 2.19 mg / l and 3.19 mg / l. This research has implications for the users of Sungai Pening Swamp. The corrosivity of air measurement is also by microbiological parameters which need to be investigated further.

scholarly journals THE SUITABILITY OF THE LAND USAGE AND THE PRODUCTIVITY OF MELON FARMING IN THE FORMER LAGOON LAND IN PARANGTRITIS, KRETEK DISTRICT, BANTUL REGENCY, DIY 2010

2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Fenti Rahayu ◽  
Suparmini Suparmini ◽  
Sugiharyanto Sugiharyanto
Keyword(s):  
Data Collection ◽  
Rainy Season ◽  
Labor Cost ◽  
Dry Season ◽  
Land Suitability ◽  
Net Income ◽  
Water Drainage ◽  
Land Usage ◽  
Research Areas ◽  
Land Improvement

This research aims to know the suitability of land usage in the former lagoon plains in Parangtritis for melon cultivation; land border factors; land improvement efforts; the management of melon cultivation and the productivity of melon in the research areas. This research is descriptive quantitative research. The population in this research consists of physical and non-physical population. Physical population includes all former lagoon lands planted with melons or 6,300 m². Moreover, non-physical population consists of all melon farmers in the research areas which consist of 3 farmers. This research employs purposive sampling techniques to take the non-physical research samples i.e. the former lagoon soil from the southern plains in the form of sand and the soil from the former lagoons in the northern part in the form of clay. Moreover, the non-physical population samples were not taken because there are only 3 farmers in the research areas. The techniques of data collection include observation, laboratory testing, interviews and secondary data collection. The data analysis for the physical aspects was performed through laboratory analysis while for the non-physical aspects were conducted through descriptive statistical analysis. The findings show that (1) the southern parts of the research areas have a land suitability level of S3 (marginally suitable), and the northern parts of the research areas have a land suitability level of S2 (quite appropriate); (2) the factors which become the land borders are rainfall, drainage, soil texture, and content of C-organic and the danger of flood; (3) land improvement efforts were performed by planting melons in the dry season to cope with heavy rainfall in the rainy season, fertilizing plants using manure to inhibit drainage and increase the content of C-organic in the soil, making water drainage on farms to prevent from flood; (4) The crop management is performed using modern techniques, planting melon is only done once every year in the dry season so that the plants are not in danger of flooding during the rainy season, and the optimal results can be achieved; (5) The net production of melon per year performed with good management can reach 3.2 tons per 1,000 m² land. The gross income of farmers per 1,000 m² of land is Rp. 6,080,000.00. The production and labor cost for each planting is Rp. 2,348,775.00 per 1,000 m² of land. Therefore, net income of melon farmers in the research area reaches Rp. 3,731,225.00.Keywords: landuse, productivity, lagoon

Characterization of Polycyclic Aromatic Hydrocarbon Profiles by Multivariate Statistical Analysis

2013 ◽  
pp. 102-116
Author(s):  
D. J. Marino ◽  
E. A. Castro ◽  
L. Massolo ◽  
A. Mueller ◽  
O. Herbarth ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Principal Component ◽  
Emission Sources ◽  
Multivariate Statistical ◽  
Data Set ◽  
Polycyclic Aromatic ◽  
The City ◽  
Sampling Times ◽  
Sample Identity

In the present study, statistical methods based on multivariate analyses such as the Descriptive Discriminant Analysis (DDA) and Principal Component Analysis (PCA) were applied to determine relationships between particle sizes and the composition of the associated semi-volatile compounds, in addition to evaluating these observations in relation to the emission sources, study areas, sampling campaigns and season. Results from the DDA showed that the PAHs distributions give the best discrimination capacity within the data set, whereas the PAH distribution in intermediate particle fractions incorporates noise in the statistical analysis. The PCA was useful in identifying the main emission sources in each study area. It showed that in the city of La Plata the most important pollution sources are traffic emissions and the industrial activity associated with oil and petrochemical plants. In Leipzig, the main sources are those associated with traffic and also a power plant. The combined PCA and DDA methods applied to PAH distributions is a valuable tool in characterizing types of emissions burdens and also in obtaining a differentiation of sample identity according to study areas and sampling times.

scholarly journals The 3Rs: Reduction and refinement through a multivariate statistical analysis approach in a behavioural study to unveil anxiolytic effects of natural extracts of Tilia tomentosa

2020 ◽  
Author(s):  
Guendalina Olivero ◽  
Federica Turrini ◽  
Matteo Vergassola ◽  
Raffaella Boggia ◽  
Paola Zunin ◽  
...  
Keyword(s):  
Statistical Approach ◽  
Principal Component ◽  
Experimental Protocol ◽  
Multivariate Statistical ◽  
Data Set ◽  
Natural Extracts ◽  
Multivariate Statistical Approach ◽  
Behavioural Tests ◽  
Tilia Tomentosa

We propose a multivariate statistical approach based on Principal Component Analysis (PCA) as an useful instrument to improve the Rules of Refinement and Reduction in in vivo animal experimentation. We analysed with PCA the preliminary data from a study on the effects of the oral administration of Tilia tomentosa bud extracts (TTBEs) on the behavioural skills of adult and aged male and female mice. PCA allows to rationalize the data set information and to dissect the results, showing connections among variables under study (behavioural parameters) and different trends in the experimental groups (control and TTBEs-administered animals). Our results show that PCA can give some important information that can be useful for the refinement of the experimental protocol, in order to reduce the number of the animals used in the experiments and/or the behavioural tests to get reliable information.

Characterization of Polycyclic Aromatic Hydrocarbon Profiles by Multivariate Statistical Analysis

2011 ◽  
Vol 1 (2) ◽  
pp. 1-14
Author(s):  
D. J. Marino ◽  
E. A. Castro ◽  
L. Massolo ◽  
A. Mueller ◽  
O. Herbarth ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Principal Component ◽  
Emission Sources ◽  
Multivariate Statistical ◽  
Data Set ◽  
Polycyclic Aromatic ◽  
The City ◽  
Sampling Times ◽  
Sample Identity

In the present study, statistical methods based on multivariate analyses such as the Descriptive Discriminant Analysis (DDA) and Principal Component Analysis (PCA) were applied to determine relationships between particle sizes and the composition of the associated semi-volatile compounds, in addition to evaluating these observations in relation to the emission sources, study areas, sampling campaigns and season. Results from the DDA showed that the PAHs distributions give the best discrimination capacity within the data set, whereas the PAH distribution in intermediate particle fractions incorporates noise in the statistical analysis. The PCA was useful in identifying the main emission sources in each study area. It showed that in the city of La Plata the most important pollution sources are traffic emissions and the industrial activity associated with oil and petrochemical plants. In Leipzig, the main sources are those associated with traffic and also a power plant. The combined PCA and DDA methods applied to PAH distributions is a valuable tool in characterizing types of emissions burdens and also in obtaining a differentiation of sample identity according to study areas and sampling times.

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