Factsheet
PDF Generated On: Wed May 14 2025 03:32:43 GMT+0000 (Coordinated Universal Time)
1. Indicator name
Index of coastal eutrophication potential
2. Date of metadata update
2024-09-01 00:00:00 UTC
3. Goals and Targets addressed
3a. Goal
N/A
3a. Target
Headline Indicator for Target 7: Reduce pollution risks and the negative impact of pollution from all sources by 2030, to levels that are not harmful to biodiversity and ecosystem functions and services, considering cumulative effects, including: (a) by reducing excess nutrients lost to the environment by at least half, including through more efficient nutrient cycling and use; (b) by reducing the overall risk from pesticides and highly hazardous chemicals by at least half, including through integrated pest management, based on science, taking into account food security and livelihoods; and (c) by preventing, reducing, and working towards eliminating plastic pollution.
4. Rationale
1. Coastal areas are areas of high productivity where inputs from land, sea, air and people converge. With over 40 percent of the human population residing in coastal areas, ecosystem degradation in these areas can have disproportionate effects on society (IGOS, 2006). One of the largest pressures on coastal environments is eutrophication, resulting primarily from land-based nutrient input from agricultural runoff and domestic wastewater discharge. Coastal eutrophication can lead to serious damage to marine ecosystems and vital sea habitats and can cause the spread of harmful algal blooms.
5. Definitions, concepts and classifications
5a. Definition
2. The indicator is a subset of the indicators used for SDG 14.1.1. The indicator aims to measure the contribution to coastal eutrophication from countries and the state of coastal eutrophication. Therefore, two levels of indicators are recommended:
(a) Level 1: Globally available data from earth observations and modelling
(b) Level 2: National data collected from countries (through the relevant Regional Seas Programme where applicable, that is, for countries that are a member of a Regional Seas Programme)
3. Unit of measure: Indicator for Coastal Eutrophication Potential (ICEP): kilograms of carbon (from algae biomass) per square kilometre of river basin area per day (kg C km-2 day-1).
5b. Method of computation
Level 1: Indicator for coastal eutrophication potential
4. This indicator is based on loads and ratios of nitrogen, phosphorous and silica delivered by rivers to coastal waters (Garnier et al. 2010), which contribute to the ICEP. The basis for these loads is collected from land-based assessments of land use including fertilizer use, population density, socioeconomic factors and other contributors to nutrient pollution runoff. Given the land-based nature of the indicator, it provides a modelled number indicating the risk of coastal eutrophication at a specific river mouth. The indicator can be further developed by incorporating in situ monitoring to evaluate the dispersion of concentrations of nitrogen, phosphorous and silica to ground-truth the index. The indicator assumes that excess concentrations of nitrogen or phosphorus relative to silica will result in increased growth of potentially harmful algae (ICEP > 0). ICEP is expressed in kilograms of carbon (from algae biomass) per square kilometre of river basin area per day (kg C km-2 day-1).
5. The ICEP model is calculated using one of two equations depending on whether nitrogen or phosphorus is limiting. The equations (Billen and Garnier 2007) are:
Where PFlx, NFlx and SiFlx are respectively the mean specific values of total nitrogen, total phosphorus and dissolved silica delivered at the mouth of the river basin, expressed in kg P km-2 day-1, in kg N km-2 day-1 and in kg Si km-2 day-1.
Level 2: National ICEP modelling
6. Existing ICEP modelling at the national level is limited but could be further developed following the model of a current study analysing basin level data in Chinese rivers (Strokal et al. 2016). The study utilises Global NEWS – 2 (Nutrient Export from WaterSheds) and Nutrient flows in Food chains, Environment and Resources use (NUFER) as models. The Global NEWS-2 model is basin-scale and quantifies river export of various nutrients (nitrogen, phosphorus, carbon and silica) in multiple forms (dissolved inorganic, dissolved organic and particulate) as functions of human activities on land and basin characteristics (Strokal et al. 2016). Furthermore, the model shows past and future trends.
7. A full methodology for this indicator is available in the “Global Manual on Ocean Statistics for Measuring SDG 14.1.1, 14.2.1 and 14.5.1”.
5c. Data collection method
8. National data are collected through the Regional Seas Programmes to reduce the reporting burden on countries. For countries that are not included in the Regional Seas Programme, UNEP contacts countries directly. For globally derived data, UNEP has established a partnership with NOAA and GEO Blue Planet and the Global Nutrient Management System (GNMS) to facilitate the production of global data products.
5d. Accessibility of methodology
9. The methodology for this indicator is published under the following link: https://wedocs.unep.org/bitstream/handle/20.500.11...
10. The data for this indicator is also available on the UN SDG Global database: https://unstats.un.org/sdgs/dataportal/database
5e. Data sources
11. For Level 1 indicators:
(a) Global models, which are based on official data from national governments as collected from UN organizations.
12. For Level 2 indicators:
(b) Data provided by national governments.
5f. Availability and release calendar
13. For Level 1 indicators:
(a) ICEP has been calculated for large marine ecosystems. River-basin scale information is expected in 2024. National models will be available beginning in late 2024 with the release of guidance from UNEP for preparing national models.
14. For Level 2 indicators:
(b) The first UNEP data collection is planned in 2023. After that, data collection will be synchronised with the Regional Seas data collection calendar.
5g. Time series
15. For Level 1 indicator:
(a) ICEP: 1900-2015: data are available for Global large marine ecosystems (LMEs) and River Basins. Data are available for N loading, not P loading.
16. For Level 2 indicator:
(b) The first UNEP data collection is planned in 2023. The plan is to align the data collection with Regional Seas every 4 years and the data will be yearly data, as used for SDG 14.1.1.
5h. Data providers
17. For Level 1 data:
(a) Geo Blue Planet, NOAA, Esri, IOC-UNESCO.
18. For Level 2 data:
(b) National governments, through the Regional Seas, or directly to UNEP.
5i. Data compilers
19. United Nations Environment Programme (UNEP), in collaboration with partners mentioned in the other sections of this metadata.
5j. Gaps in data coverage
20. Level 2 Data for ICEP is not yet available (forthcoming in 2024).
(a) With
the use of the index of coastal eutrophication potential (ICEP), freshwater
pollution is not addressed; the ICEP is only a marine indicator. There are two
related SDG indicators which may be considered as options to supplement
national reporting: SDG 6.6.1 looking at trophic state and turbidity, using chl
a, and SDG 6.3.2 on quality of freshwater (for which there are plans to
integrate information from citizen science monitoring).
5k. Treatment of missing values
21. For Level 1 data:
Not applicable.
22. For Level 2 data:
The United Nations Environment Programme (UNEP) and the Regional Seas do not make any estimation or imputation for missing values, so the number of data points provided are actual country data.
6. Scale
6a. Scale of use
Scale of application: Global, Regional, National
Scale of data disaggregation/aggregation: Regional and national level. *Sub-national level can also be derived upon request.
(a) Global/ regional scale indicator can be disaggregated to national level
(b) National data is collated to form global indicator:
(c) Additional Information: It is a Global LMEs and River Basins scale indicator. Yes
6b. National/regional indicator production
24. The methodology for global (Level 1) and national (Level 2) indicators(Global Manual on Ocean Statistics for Measuring SDG 14.1.1, 14.2.1 and 14.5.1) is available at the following link: https://wedocs.unep.org/handle/20.500.11822/3508z.
25. UNEP is preparing guidance for the development of national modelled values of the ICEP. Some countries are not coastal but do contribute to coastal nutrient loads via watersheds; however, the ICEP models are only designed for countries with mouths of river(s).
26. The national level data for this indicator will be data collected from countries and will measure the ICEP at the mouth of rivers in those countries. Modelled data will not be used unless countries are not able to measure ICEP; it is not yet clear if the use of modelled data will cover landlocked countries.
6c. Sources of differences between global and national figures
27. For Level 1,
Global models are used.
28. For Level 2,
National data is used. National level models of the index of coastal eutrophication will be initiated beginning in 2024.
6d. Regional and global estimates & data collection for global monitoring
6d.1 Description of the methodology
29. The methodology for global (Level 1) and national (Level 2) indicators(Global Manual on Ocean Statistics for Measuring SDG 14.1.1, 14.2.1 and 14.5.1) is available at the following link: https://wedocs.unep.org/handle/20.500.11822/35086.
6d.2 Additional methodological details
30. UN Environment will continue to provide regional (at the scale of large marine ecosystems and at the scale of basins) data for the ICEP values. UNEP is working (starting in 2024) to provide national modelled values for ICEP, and it is these national values that will be used to feed into CBD reporting.
6d.3 Description of the mechanism for collecting data from countries
31. National data collection through the Regional Seas already exists for many Regional Seas, this data will be compiled for SDG reporting in 2023.
7. Other MEAs, processes and organisations
7a. Other MEA and processes
Sustainable Development Goals (SDG): indicator 14.1.1 (a) Index of coastal eutrophication
7b. Biodiversity Indicator Partnership
No
8. Disaggregation
32. A geospatial disaggregation of the state of pollution is proposed. For the ICEP loading indicators, this disaggregation should be at the sub-basin level.
33. The processes of assessing and reporting on this indicator should be inclusive, following the approach outlined in Section C for implementing the GBF. The planned data collection for this ICEP indicator does not collect or permit disaggregation by gender or indigenous peoples and local communities. The indicator does not assess the impact of pollution; rather, the indicator relies on environmental measurements or models of nutrient levels, human population levels, agricultural chemical use and other contributors to nutrient pollution runoff.
9. Related indicators
N/A
10. Data reporter
10a. Organisation
United Nations Environment Programme (UNEP)
10b. Contact person(s)
34. Dany Ghafari, dany.ghafari@un.org
11. References
Website
Regional Seas website: https://www.unenvironment.org/explore-topics/ocean...
References
UN Environment (2018). Global Manual on Ocean Statistics. Towards a definition of indicator methodologies. Nairobi (Kenya): UN Environment. 46 pp. plus four appendices.
Wang, M., X. Liu, L. Jiang and S. Son (2017), The VIIRS Ocean Color Product Algorithm Theoretical Basis Document, National Oceanic and Atmospheric Administration, National Environmental Satellite and Data Information Service, 68 pp., doi: TBD.
Wang, M., X. Liu, L. Jiang, S. Son, J. Sun, W. Shi, L. Tan, P. Naik, K. Mikelsons, X. Wang and V. Lance (2014), Evaluation of VIIRS Ocean Color Products, Proc. SPIE 9261, 92610E, doi: 10.1117/12.2069251.
Stumpf, Richard P., Holderied, Kristine, Sinclair, Mark, (2003), Determination of water depth with high-resolution satellite imagery over variable bottom types, Limnology and Oceanography, 1, part, 2, doi: 10.4319/lo.2003.48.1_part_2.0547
Garnier, J., Beusen, A., Thieu, V., Billen, G. and Bouwman, L. (2010) N:P:Si nutrient export ratios and ecological consequences in coastal seas evaluated by the ICEP approach
Billen, G. and Garnier, J. (2007) River basin nutrient delivery to the coastal sea: Assessing its potential to sustain new production of non-siliceous algae Marine Chemistry 106(1-2):148-160
Sathyendranath S., Grant M., Brewin R.J.W., Brockmann C., Brotas V., Chuprin A., Doerffer R., Dowell M., Farman A., Groom S., et al. ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 3.1 Data. Centre for Environmental Data Analysis; Harwell, UK: 2018. Technical Report.
Strokal, M., Kroeze, C., Wang, M., and Ma, L. (2016) Reducing future river export of nutrients to coastal waters of China in optimistic scenarios Science of the Total Environment 579.
1. Indicator name
Index of coastal eutrophication potential
2. Date of metadata update
2024-09-01 00:00:00 UTC
3. Goals and Targets addressed
3a. Goal
N/A
3a. Target
Headline Indicator for Target 7: Reduce pollution risks and the negative impact of pollution from all sources by 2030, to levels that are not harmful to biodiversity and ecosystem functions and services, considering cumulative effects, including: (a) by reducing excess nutrients lost to the environment by at least half, including through more efficient nutrient cycling and use; (b) by reducing the overall risk from pesticides and highly hazardous chemicals by at least half, including through integrated pest management, based on science, taking into account food security and livelihoods; and (c) by preventing, reducing, and working towards eliminating plastic pollution.
4. Rationale
1. Coastal areas are areas of high productivity where inputs from land, sea, air and people converge. With over 40 percent of the human population residing in coastal areas, ecosystem degradation in these areas can have disproportionate effects on society (IGOS, 2006). One of the largest pressures on coastal environments is eutrophication, resulting primarily from land-based nutrient input from agricultural runoff and domestic wastewater discharge. Coastal eutrophication can lead to serious damage to marine ecosystems and vital sea habitats and can cause the spread of harmful algal blooms.
5. Definitions, concepts and classifications
5a. Definition
2. The indicator is a subset of the indicators used for SDG 14.1.1. The indicator aims to measure the contribution to coastal eutrophication from countries and the state of coastal eutrophication. Therefore, two levels of indicators are recommended:
(a) Level 1: Globally available data from earth observations and modelling
(b) Level 2: National data collected from countries (through the relevant Regional Seas Programme where applicable, that is, for countries that are a member of a Regional Seas Programme)
3. Unit of measure: Indicator for Coastal Eutrophication Potential (ICEP): kilograms of carbon (from algae biomass) per square kilometre of river basin area per day (kg C km-2 day-1).
5b. Method of computation
Level 1: Indicator for coastal eutrophication potential
4. This indicator is based on loads and ratios of nitrogen, phosphorous and silica delivered by rivers to coastal waters (Garnier et al. 2010), which contribute to the ICEP. The basis for these loads is collected from land-based assessments of land use including fertilizer use, population density, socioeconomic factors and other contributors to nutrient pollution runoff. Given the land-based nature of the indicator, it provides a modelled number indicating the risk of coastal eutrophication at a specific river mouth. The indicator can be further developed by incorporating in situ monitoring to evaluate the dispersion of concentrations of nitrogen, phosphorous and silica to ground-truth the index. The indicator assumes that excess concentrations of nitrogen or phosphorus relative to silica will result in increased growth of potentially harmful algae (ICEP > 0). ICEP is expressed in kilograms of carbon (from algae biomass) per square kilometre of river basin area per day (kg C km-2 day-1).
5. The ICEP model is calculated using one of two equations depending on whether nitrogen or phosphorus is limiting. The equations (Billen and Garnier 2007) are:
Where PFlx, NFlx and SiFlx are respectively the mean specific values of total nitrogen, total phosphorus and dissolved silica delivered at the mouth of the river basin, expressed in kg P km-2 day-1, in kg N km-2 day-1 and in kg Si km-2 day-1.
Level 2: National ICEP modelling
6. Existing ICEP modelling at the national level is limited but could be further developed following the model of a current study analysing basin level data in Chinese rivers (Strokal et al. 2016). The study utilises Global NEWS – 2 (Nutrient Export from WaterSheds) and Nutrient flows in Food chains, Environment and Resources use (NUFER) as models. The Global NEWS-2 model is basin-scale and quantifies river export of various nutrients (nitrogen, phosphorus, carbon and silica) in multiple forms (dissolved inorganic, dissolved organic and particulate) as functions of human activities on land and basin characteristics (Strokal et al. 2016). Furthermore, the model shows past and future trends.
7. A full methodology for this indicator is available in the “Global Manual on Ocean Statistics for Measuring SDG 14.1.1, 14.2.1 and 14.5.1”.
5c. Data collection method
8. National data are collected through the Regional Seas Programmes to reduce the reporting burden on countries. For countries that are not included in the Regional Seas Programme, UNEP contacts countries directly. For globally derived data, UNEP has established a partnership with NOAA and GEO Blue Planet and the Global Nutrient Management System (GNMS) to facilitate the production of global data products.
5d. Accessibility of methodology
9. The methodology for this indicator is published under the following link: https://wedocs.unep.org/bitstream/handle/20.500.11...
10. The data for this indicator is also available on the UN SDG Global database: https://unstats.un.org/sdgs/dataportal/database
5e. Data sources
11. For Level 1 indicators:
(a) Global models, which are based on official data from national governments as collected from UN organizations.
12. For Level 2 indicators:
(b) Data provided by national governments.
5f. Availability and release calendar
13. For Level 1 indicators:
(a) ICEP has been calculated for large marine ecosystems. River-basin scale information is expected in 2024. National models will be available beginning in late 2024 with the release of guidance from UNEP for preparing national models.
14. For Level 2 indicators:
(b) The first UNEP data collection is planned in 2023. After that, data collection will be synchronised with the Regional Seas data collection calendar.
5g. Time series
15. For Level 1 indicator:
(a) ICEP: 1900-2015: data are available for Global large marine ecosystems (LMEs) and River Basins. Data are available for N loading, not P loading.
16. For Level 2 indicator:
(b) The first UNEP data collection is planned in 2023. The plan is to align the data collection with Regional Seas every 4 years and the data will be yearly data, as used for SDG 14.1.1.
5h. Data providers
17. For Level 1 data:
(a) Geo Blue Planet, NOAA, Esri, IOC-UNESCO.
18. For Level 2 data:
(b) National governments, through the Regional Seas, or directly to UNEP.
5i. Data compilers
19. United Nations Environment Programme (UNEP), in collaboration with partners mentioned in the other sections of this metadata.
5j. Gaps in data coverage
20. Level 2 Data for ICEP is not yet available (forthcoming in 2024).
(a) With
the use of the index of coastal eutrophication potential (ICEP), freshwater
pollution is not addressed; the ICEP is only a marine indicator. There are two
related SDG indicators which may be considered as options to supplement
national reporting: SDG 6.6.1 looking at trophic state and turbidity, using chl
a, and SDG 6.3.2 on quality of freshwater (for which there are plans to
integrate information from citizen science monitoring).
5k. Treatment of missing values
21. For Level 1 data:
Not applicable.
22. For Level 2 data:
The United Nations Environment Programme (UNEP) and the Regional Seas do not make any estimation or imputation for missing values, so the number of data points provided are actual country data.
6. Scale
6a. Scale of use
Scale of application: Global, Regional, National
Scale of data disaggregation/aggregation: Regional and national level. *Sub-national level can also be derived upon request.
(a) Global/ regional scale indicator can be disaggregated to national level
(b) National data is collated to form global indicator:
(c) Additional Information: It is a Global LMEs and River Basins scale indicator. Yes
6b. National/regional indicator production
24. The methodology for global (Level 1) and national (Level 2) indicators(Global Manual on Ocean Statistics for Measuring SDG 14.1.1, 14.2.1 and 14.5.1) is available at the following link: https://wedocs.unep.org/handle/20.500.11822/3508z.
25. UNEP is preparing guidance for the development of national modelled values of the ICEP. Some countries are not coastal but do contribute to coastal nutrient loads via watersheds; however, the ICEP models are only designed for countries with mouths of river(s).
26. The national level data for this indicator will be data collected from countries and will measure the ICEP at the mouth of rivers in those countries. Modelled data will not be used unless countries are not able to measure ICEP; it is not yet clear if the use of modelled data will cover landlocked countries.
6c. Sources of differences between global and national figures
27. For Level 1,
Global models are used.
28. For Level 2,
National data is used. National level models of the index of coastal eutrophication will be initiated beginning in 2024.
6d. Regional and global estimates & data collection for global monitoring
6d.1 Description of the methodology
29. The methodology for global (Level 1) and national (Level 2) indicators(Global Manual on Ocean Statistics for Measuring SDG 14.1.1, 14.2.1 and 14.5.1) is available at the following link: https://wedocs.unep.org/handle/20.500.11822/35086.
6d.2 Additional methodological details
30. UN Environment will continue to provide regional (at the scale of large marine ecosystems and at the scale of basins) data for the ICEP values. UNEP is working (starting in 2024) to provide national modelled values for ICEP, and it is these national values that will be used to feed into CBD reporting.
6d.3 Description of the mechanism for collecting data from countries
31. National data collection through the Regional Seas already exists for many Regional Seas, this data will be compiled for SDG reporting in 2023.
7. Other MEAs, processes and organisations
7a. Other MEA and processes
Sustainable Development Goals (SDG): indicator 14.1.1 (a) Index of coastal eutrophication
7b. Biodiversity Indicator Partnership
No
8. Disaggregation
32. A geospatial disaggregation of the state of pollution is proposed. For the ICEP loading indicators, this disaggregation should be at the sub-basin level.
33. The processes of assessing and reporting on this indicator should be inclusive, following the approach outlined in Section C for implementing the GBF. The planned data collection for this ICEP indicator does not collect or permit disaggregation by gender or indigenous peoples and local communities. The indicator does not assess the impact of pollution; rather, the indicator relies on environmental measurements or models of nutrient levels, human population levels, agricultural chemical use and other contributors to nutrient pollution runoff.
9. Related indicators
N/A
10. Data reporter
10a. Organisation
United Nations Environment Programme (UNEP)
10b. Contact person(s)
34. Dany Ghafari, dany.ghafari@un.org
11. References
Website
Regional Seas website: https://www.unenvironment.org/explore-topics/ocean...
References
UN Environment (2018). Global Manual on Ocean Statistics. Towards a definition of indicator methodologies. Nairobi (Kenya): UN Environment. 46 pp. plus four appendices.
Wang, M., X. Liu, L. Jiang and S. Son (2017), The VIIRS Ocean Color Product Algorithm Theoretical Basis Document, National Oceanic and Atmospheric Administration, National Environmental Satellite and Data Information Service, 68 pp., doi: TBD.
Wang, M., X. Liu, L. Jiang, S. Son, J. Sun, W. Shi, L. Tan, P. Naik, K. Mikelsons, X. Wang and V. Lance (2014), Evaluation of VIIRS Ocean Color Products, Proc. SPIE 9261, 92610E, doi: 10.1117/12.2069251.
Stumpf, Richard P., Holderied, Kristine, Sinclair, Mark, (2003), Determination of water depth with high-resolution satellite imagery over variable bottom types, Limnology and Oceanography, 1, part, 2, doi: 10.4319/lo.2003.48.1_part_2.0547
Garnier, J., Beusen, A., Thieu, V., Billen, G. and Bouwman, L. (2010) N:P:Si nutrient export ratios and ecological consequences in coastal seas evaluated by the ICEP approach
Billen, G. and Garnier, J. (2007) River basin nutrient delivery to the coastal sea: Assessing its potential to sustain new production of non-siliceous algae Marine Chemistry 106(1-2):148-160
Sathyendranath S., Grant M., Brewin R.J.W., Brockmann C., Brotas V., Chuprin A., Doerffer R., Dowell M., Farman A., Groom S., et al. ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 3.1 Data. Centre for Environmental Data Analysis; Harwell, UK: 2018. Technical Report.
Strokal, M., Kroeze, C., Wang, M., and Ma, L. (2016) Reducing future river export of nutrients to coastal waters of China in optimistic scenarios Science of the Total Environment 579.
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