Future coastal water pollution under global change: multi-pollutant modeling

Coastal waters receive multiple pollutants, such as nutrients, plastics, and chemicals. Rivers transport these pollutants often from rural and urban areas to seas. Many pollutants have common sources and cause multiple impacts (e.g., eutrophication and toxicity), decreasing the availability of clean water. Meanwhile, the global change adds to coastal water pollution. For example, cities are expected to expand in size and numbers, increasing future urban pollution. In addition, agriculture may intensify to satisfy the food demand for a growing global population. This intensification may, in turn, increase agricultural pollution in river export to coastal waters. In addition, climate change is expected to result in more floods and droughts. Floods may transport more pollutants from urbanised and agricultural areas to the seas. The effects of global change will likely differ among river basins depending on their characteristics.

Existing scenarios, such as the Representative Concentrative Pathways (RCPs) and Shared Socio-economic Pathways (SSPs), address global change challenges. However, these scenarios have yet to be implemented for a global multi-pollutant assessment of coastal waters. In addition, large-scale assessments of coastal water pollution are often for single pollutants, overlooking synergies and trade-offs in pollution control for multiple pollutants. Sustainable Development Goal (SDG) 14 (clean marine waterways) may be supported by considering multiple pollutants and sources, yet additional research in the field is needed.

Our study aims to better understand the influence of global change on the river export of multiple pollutants to coastal waters by source and sub-basins. To this end, we develop the MARINA-Multi (Model to Assess River Inputs of pollutaNts to the seAs) model for more than 10,000 sub-basins and for nutrients, chemicals, and plastics to estimate future pollution trends. For these pollutants, we consider point (such as sewage systems and open defecation) and diffuse (such as agriculture and improperly managed solid waste on land) sources. Finally, we consider the SGD coastal water quality targets and develop optimistic and pessimistic futures under global change.

Our model results show that, in 2010, more than 50% of the population lived in river basins where coastal waters experienced multi-pollution problems. Rivers exported considerable amounts of nutrients, chemicals, and plastics to coastal waters globally, two-thirds reaching the Atlantic and Pacific seas. Diffuse sources contributed by over 70% to nitrogen and macroplastics in global seas. Point sources contributed by 70- 90% to phosphorus and microplastics in global seas. Multi-pollution hotspots are often found in urbanised areas. Global change will alter those pollution hotspots. First, the pollution patterns are expected to shift due to climate change affecting temperature and the water cycle. Second, changes in socioeconomic drivers are expected. Our optimistic scenarios are associated with, for example, the technological progress that enhances waste collection and treatment. The MARINA-Multi model is useful for understanding the sources and spatial variability of the multiple pollutants in rivers and coastal waters under global change. Our model can support decision-makers and water managers in implementing mitigation and adaptation policies to achieve sustainable targets for the marine environment (SDG 14).