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  • Author or Editor: Adrienne Clement x
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One and a half year long field sampling was established in order to evaluate the contamination of storm water runoff. The event means (EMC) total petroleum hydrocarbons (TPH) concentration of the runoff was a function of the actual traffic intensity and the rainfall depth. It was concluded that this TPH, of which dominant component is the engine-oil (characteristically C28) does not form an ‘oil-in-water’ type emulsion in the condition of normal motorway-operation, but is interlocked to asphalt, rubber and soot particles of maximum some ten microns size. This condition influences the possibility, way and extent of separation alike. The separation equipments and their sizing applied so far are not suitable to achieve efficient surface water protection. Practical prevention method of accidental type environment pollution was also suggested. On the basis of the international literature evaluation, technical solutions capable to decrease the runoff pollution were summarized. Among these, useful calculation method was developed for designers to determine the sufficient storage capacity (water quality volume) of reservoirs applied for water quality protection. Monitoring technique of runoffs, which are characterized time dependent, variable pollutant concentrations by their nature, was proposed. It was stated that the administrative regulation should aim at the EMC instead of current concentration. Beside TPH information was gained on polycyclic aromatic hydrocarbons (PAHs), suspended solids, heavy metals, pH, and nutrient (N, P) pollution of the runoff, which are valuable for the grounding of further research results.

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Abstract

With the introduction of the Water Framework Directive, the relative importance of smaller waterways increased. This statement is particularly true for Hungary, where water-quality monitoring of most smaller rivers only began 12 years ago. Due to their large number, and the lack of historical data concerning their state, systematic monitoring is a challenge.

In the current study, 101 creeks are characterized on the one hand by 13 physico-chemical quality parameters (pH, electric conductivity, chloride ion concentration, dissolved oxygen, oxygen saturation, biochemical oxygen demand, chemical oxygen demand, total organic carbon, ammonium nitrogen, total inorganic nitrogen, total nitrogen, orthophosphate and total phosphorus), on the other hand by their watershed's relief, land use, and point sources' pollution indicators. Euclidean distance between water bodies (henceforth WBs) is calculated according to normalized physico-chemical monitoring values. They are grouped into clusters using the hierarchical clustering method. Watershed characteristics are used to explain the clustering via linear discriminant analysis.

The investigation revealed that the main driver of cluster group creation is related to human impact: diffuse agricultural and point-source pollution. The first of the three clusters involved water bodies with low or no human impact; the second cluster contained those with medium-level anthropogenic disturbance, while waters with high pollution values formed the third cluster. Mean distance between heavily polluted waters was 1.5 times higher than that between those showing no or low disturbance, meaning that pristine waters are more similar to one another than polluted ones. The current number of samples per river is twice as high in cluster 1 as in cluster 3, revealing that there is room for optimization of the monitoring system. This contribution uses Hungary as a case study.

Open access

Abstract

With the introduction of the Water Framework Directive, the relative importance of smaller waterways increased. This statement is particularly true for Hungary, where water-quality monitoring of most smaller rivers only began 12 years ago. Due to their large number, and the lack of historical data concerning their state, systematic monitoring is a challenge.

In the current study, 101 creeks are characterized on the one hand by 13 physico-chemical quality parameters (pH, electric conductivity, chloride ion concentration, dissolved oxygen, oxygen saturation, biochemical oxygen demand, chemical oxygen demand, total organic carbon, ammonium nitrogen, total inorganic nitrogen, total nitrogen, orthophosphate and total phosphorus), on the other hand by their watershed's relief, land use, and point sources' pollution indicators. Euclidean distance between water bodies (henceforth WBs) is calculated according to normalized physico-chemical monitoring values. They are grouped into clusters using the hierarchical clustering method. Watershed characteristics are used to explain the clustering via linear discriminant analysis.

The investigation revealed that the main driver of cluster group creation is related to human impact: diffuse agricultural and point-source pollution. The first of the three clusters involved water bodies with low or no human impact; the second cluster contained those with medium-level anthropogenic disturbance, while waters with high pollution values formed the third cluster. Mean distance between heavily polluted waters was 1.5 times higher than that between those showing no or low disturbance, meaning that pristine waters are more similar to one another than polluted ones. The current number of samples per river is twice as high in cluster 1 as in cluster 3, revealing that there is room for optimization of the monitoring system. This contribution uses Hungary as a case study.

Open access