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Identification of nitrates origin in Limia river basin and pollution-determinant factors.
- Source :
-
Agriculture, Ecosystems & Environment . Mar2020, Vol. 290, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- • 36.5 % of the analysed water samples showed a very good quality. • The highest nitrate levels (>25 mg/L) were observed in the Antela lagoon area. • The main source of nitrates seems be the organic inputs through livestock waste. • A relationship between the accumulated rainfall and nitrate levels in waters was found. • Nitrates were correlated with conductivity (+) and with alkalinity and chlorides (−). The aim of this work was to evaluate monthly the presence of pollutants, especially nitrates, in the Limia river and tributaries in order to evaluate the quality of surface water samples during 2018. An isotopic analysis (δ15N and δ18O) of nitrates was also done with the order to explain the primary sources of nitrate contamination. This area is characterised by intensive use of the soil for potato production over the past 50 years, and has a high livestock load, mainly of pigs. Obtained results show that, in general, water pollution in this area is low with 81.5 % of the samples having all their physicochemical parameters within the category of very good or good quality according to the water quality thresholds. The spatial and temporal distribution of nitrates has shown high variability in the interaction between various factors, such as season and sampling area. Values exceeding 25 mg L−1 of nitrates (moderate quality) were observed in seven samples taken in the Antela lagoon area. Besides, it was observed a relationship between the accumulated rainfall and the concentration of nitrates in surface waters due to the dragging effect from the surrounding land. According to the isotopic results, the primary source of nitrates seems to be the organic inputs to the soil through livestock waste. By applying the discriminant function method, nitrates concentration was correlated positively with the conductivity and negatively with the data of alkalinity and chloride content in waters. Moreover, with principal component analysis, it was possible to separate the water samples by their content in nitrates and other measured contaminants or chemical parameters. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01678809
- Volume :
- 290
- Database :
- Academic Search Index
- Journal :
- Agriculture, Ecosystems & Environment
- Publication Type :
- Academic Journal
- Accession number :
- 141028147
- Full Text :
- https://doi.org/10.1016/j.agee.2019.106775