Oxygen consuming substances in European rivers

In European rivers, oxygen consuming substances decreased over the period 1992 to 2023, which is a consequence of the improvement in wastewater treatment. Biochemical oxygen demand (BOD) fell to half of the 1992 level, but has been fluctuating at 2.0-2.2mgO₂/l since 2010. Ammonium concentrations fell to 20% of the 1992 level and have stabilised at less than 0.08mgNH₄-N/l in the past few years. The economic crisis in central and eastern European countries during the 1990s also contributed to decreasing pollution from manufacturing industries.

Figure 1. Biochemical oxygen demand and ammonium in European Rivers

Organic pollution of rivers from wastewater, both municipal and industrial, negatively affect aquatic ecosystems, causing loss of oxygen and changes in species composition (i.e. deterioration of ecological status). Severe organic pollution may lead to rapid de-oxygenation of river water, high concentration of hazardous ammonia and disappearance of fish and aquatic invertebrates. It also affects the water use for human purposes such as consumption and bathing. Without treatment, organic pollution is slowly diluted and degraded naturally along the river course.

Biochemical oxygen demand (BOD) and ammonium are key indicators of organic pollution in water. BOD is the amount of dissolved oxygen needed by aerobic organisms to break down organic matter in water at a certain temperature, over a specific period. BOD and ammonium increase with higher loads of biologically degradable organic matter.

Key sources of organic pollution are municipal and industrial wastewater, especially from paper or food processing industries. Large contributions also stem from agricultural emissions, specifically surface run-off, manure and slurry from intensive livestock farms. Climate change is increasing water temperatures, resulting in higher decomposition rates and further deterioration of oxygen conditions.

BOD

In European rivers, BOD levels have generally been decreasing between 1992 and 2023, with an average annual decrease in BOD of -0.1mg/l (0.5% per year – see Annex). The BOD reached its lowest level (2.0 mgO₂/l) in 2010, yet fluctuated to up to 2.3mg/l in the later period. A notable decrease is evident at 55% of the river water bodies. A significantly increasing BOD trend is recorded at 17% of the water bodies. The shorter, more representative time series of 2007–2023 follows the longer one.

Ammonium

Annual ammonium concentrations decreased by 0.02mgNH4-N/l per year (-2.6% - see Annex) on average over the period 1992-2023. Significantly decreasing concentrations were observed at 80% of the water bodies. No change has been observed at 12% of the river water bodies. A significant increase was evident at 6% of the sites. The shorter, more representative time series of 2007–2023 shows higher concentrations, but a similar trend of overall decrease.

Figure 2. Status of biochemical oxygen demand in rivers in European countries

Countries with the highest share of river water bodies in the best BOD class (i.e. less than 1.61mg/l) are Slovenia (100%), Ireland (97%), Cyprus (79%), and Austria (75%). The share of monitored river water bodies with BOD in the worst BOD class is particularly high (50% or more) in Albania and Kosovo under UNSCR 1244/99.

High BOD levels are mainly observed in lowlands with high agricultural and industrial activity in Europe, such as the Po valley in Italy. Lower BOD levels are usually seen in highlands of Europe such as the Alps, and the Dinaric Alps.

Statistical trend analysis (see Annex table RW BOD) showed that the largest proportions of water bodies with significantly decreasing trends since 1992 (> 80%) were in Czechia, Slovakia and Slovenia. The largest proportion of significantly increasing trend was in Spain (30%). Since 2007, the largest proportions of significantly decreasing trends (> 70%) were found in Belgium, Cyprus and Slovenia. However, Estonia, Ireland, Kosovo, Latvia, Portugal and Spain had more than 30% water bodies with significantly increasing trends.

Supporting information

Definition

The key indicators for oxygenation of water bodies are biochemical oxygen demand (BOD) and ammonium. BOD is most commonly expressed in milligrams of oxygen consumed per litre of sample during five days of incubation at 20°C. This is the amount of oxygen needed by microorganisms for aerobic decomposition of organic matter. Ammonium, when oxygenated by bacteria to nitrate, is toxic to aquatic life at certain concentrations in relation to water temperature, salinity and pH levels. The indicator illustrates spatial variations in current state and temporal trends of BOD and ammonium concentration in rivers.

Methodology

A detailed methodology description is given in a separate document.

The indicator analysis is based on annual mean concentrations per monitoring site. The annual mean concentrations are calculated from sample data, unless the country has reported annual data only. The data undergo automatic and manual quality checks to remove errors and outliers.

Monitoring site time series from the same water body are combined and gap filled before further analysis. Gap filling is necessary to ensure that the average European time series represents the same water bodies every year. Water body time series are only included in the analysis if they have data within the first and last five years of the time range and data from at least 40% of the years in the time range. Two different time ranges are analysed: From 1992 for long-term trends and from 2007 for better spatial coverage (more water bodies meet the selection criteria).

Data are aggregated from site to water body level and gap-filled using generalized additive models (GAM) in the free software R , using the mgcv package. For water bodies with more than one site, a GAM model with concentration as response variable, year as fixed effect and site as random effect is used to estimate annual concentrations per site. Annual values for the water body are subsequently estimated by averaging the annual site predictions. For water bodies with only one site, or where the random effect for site is non-significant, a GAM without a random site effect is used to estimate annual values and for gap filling. The gap-filled water body time series are averaged by country and a weighted average of the country time series (weighting by the total length of rivers in the country) is calculated to give the time series for Europe. A 95% confidence interval for the weighted average is calculated using of the formula for standard error of a weighted mean recommended in Gatz and Smith (1995).

Trends are analysed with the Mann-Kendall method in the free software R, using the wql package. This is a non-parametric test suggested by Mann (1945) and has been extensively used for environmental time series. Mann-Kendall is a test for a monotonic trend in a time series y(x), which in this analysis is nutrient concentration (y) as a function of year (x). The size of the change is estimated by calculating the Sen slope (Theil, 1992; Sen, 1968). Absolute and relative Sen slopes are summarized across Europe and countries by averaging. The same water body time series as for the aggregated time series plots are used, but without the gap-filled values. Note that the smoothed GAM output makes it more likely to get significant trends.

In the present state analysis, the value per river water body is calculated as the average of available annual mean concentrations for the last 6 years. Any water body with at least one data point within the last 6 years can be used, giving far more water bodies than in the time series analysis. The water bodies are assigned to quintile classes based on the distribution of the 6-year average concentrations, and the results are summarised per country as percentage of water bodies per quintile class. The purpose of the analysis is to compare the distribution of concentrations among countries. Note that natural concentration levels vary between regions, so lower proportion of water bodies in the lowest concentration classes does not necessarily imply higher anthropogenic pollution pressure.

Policy/environmental relevance

Several EU directives aim at improving water quality and reducing the loads and impacts of organic matter. Water Framework Directive (WFD) requires the achievement of good ecological status or good ecological potential of surface waters across the EU by 2015 and repeals step by step several older water-related directives. The following directives are complementary to the WFD: the Urban Waste Water Treatment Directive (91/271/EEC), aimed at reducing pollution from sewage treatment works and certain industries; the Nitrates Directive (91/676/EEC), aimed at reducing nitrate and organic matter pollution from agricultural land; and the Industrial Emissions Directive (2010/75/EU), aimed at reducing emissions from industry to air, water and land.

Accuracy and uncertainties

Methodological uncertainty

Organic and oxygen conditions vary throughout the year, depending especially on flow conditions, affected by weather events etc. Hence, the annual average concentrations should ideally be based on samples collected as often as possible. Using annual averages representing only part of the year introduces some uncertainty, but it also makes it possible to include more river sites, which reduces the uncertainty in spatial coverage. Moreover, the majority of the annual averages represent the whole year. The GAM modelling introduces uncertainty, but this too increases the spatial coverage.

Data sets uncertainty

The indicator is meant to give a representative overview of oxygenation availability conditions in European rivers. This means it should reflect the variability in conditions in space and time. Countries are asked to provide data long time series without gaps and as complete geographic coverage as possible.

The datasets for rivers include almost all countries within the EEA, but the time coverage varies from country to country, both through the analysed period and within the year for which the aggregated mean value is provided. It is assumed that the data from each country represents the variability in space in their country. Likewise, it is assumed that the sampling frequency is sufficiently high to reflect variability in time. In practice, the representativity will vary between countries, and this introduces uncertainty to the analysis.

Each annual update of the indicator is based on the updated dataset. This also means that due to changes in the database, the derived results of the assessment vary in comparison to previous assessments. Such changes include changes in the quality procedure that excludes or re-includes individual sites or samples and retroactive reporting of data for the past periods, which may re-introduce lost time series that were not used in the recent indicator assessments, the derived results of the assessment vary in comparison to previous assessments.

Waterbase contains a large amount of data collected throughout many years. Ensuring the quality of the data has always been a high priority. Still, suspicious values or time series are sometimes detected and the automatic QC routines exclude some of the data. Through the communication with the reporting countries, the quality of the database can be further improved.

There is uncertainty in the spatial data used for calculating the weighted European average (WISE Spatial) related to the delineation of water bodies, especially for rivers. E.g. countries including a finer network of rivers in their river water bodies (and thus larger total length) will get a higher weight in the European average.

Rationale uncertainty

Biochemical oxygen demand and ammonium are well suited for indicating organic pollution. However, using annual average values does not reflect the variability during the year and can therefore underestimate the severity of short-term low oxygen conditions.

Data sources and providers

Metadata

DPSIRTagsTemporal coverageGeographic coverage

TypologyUN SDGsUnit of measureFrequency of dissemination

Oxygen consuming substances in European rivers

Figure 1. Biochemical oxygen demand and ammonium in European Rivers

Figure 2. Status of biochemical oxygen demand in rivers in European countries

Supporting information

Metadata

References and footnotes