Development of a method of assessment of ecological risk of surface water pollution by nitrogen compounds
DOI:
https://doi.org/10.15587/1729-4061.2021.243058Keywords:
risk of contamination with nitrogen compounds, sensitivity coefficient, risk assessment scaleAbstract
A method has been developed for quantitative and qualitative assessment of the risk of surface water pollution by nitrogen compounds based on the use of the indicator of the total content of inorganic nitrogen forms in water (Ninorg), that is, This indicator is considered as the sensitivity coefficient kn. The choice of the indicator is dictated by the need to protect waters from pollution caused by nitrogen compounds during their flow from agricultural sources (Directive 91/676 /EU). The experience of developed countries has shown that nitrogen compounds deteriorate the quality of water and prevent the achievement of a "good ecological state" of water bodies. For territories with developed agriculture, it is important to establish environmental risks of damage depending on the degree of nitrogen pollution. Quantitative assessments of environmental risk are provided on the basis of a probabilistic approach. The risk was calculated as the product of the probability of a hazardous event occurring multiplied by the consequences of this event. The consequences of river pollution with nitrogen compounds were assessed as the ratio of the total concentration of nitrogen compounds (sensitivity index kn) to its threshold value (50 mg/dm3 or 11.3 mgN/dm3). In order to develop a scale for qualitative and quantitative risk assessment, relationships were established between the sensitivity indicators kн and the risk indicators R' for individual rivers, and for the study area as a whole, by means of spatio-temporal generalization. The probabilistic characteristics of possible environmental damage were determined on the basis of the obtained regression equations of the form R'=f(kn) and the statistical law of distribution of the risk value R'. The developed method will make it possible to determine the rank of the risk zone and the probability of getting into it, depending on the given sensitivity indicator kn
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