Ten years of MARINA modeling: Multi-pollutant hotspots and their sources under global change

Ilaria Micella,Mengru Wang, Mirjam P. Bak,Nynke Hofstra,Carolien Kroeze,Yanan Li, Shiyang Li,Vita Strokal, Aslihan Ural-Janssen, Qi Zhang,Maryna Strokal

crossref(2024)

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摘要
Water quality has been deteriorating in many lakes, rivers and coastal waters. Climate change is one of the drivers that can further deteriorate water quality (e.g., droughts contribute to higher concentrations of pollutants). Meanwhile, human activities add more loadings of pollutants to water, e.g., intensified agriculture, more cities with poor wastewater treatment facilities, and low access to improved sanitation, especially in less developed countries. Examples are nutrients from overfertilized land leading to eutrophication issues in fresh and coastal waters. Pathogens in surface waters from poor sanitation facilities can make people sick. Plastics in surface waters can result from mismanaged solid waste (e.g., macroplastics) and untreated wastewater (e.g., microplastics from laundry, dust, car tires and personal care products). In general, human activities serve as common sources of multiple pollutants. For example, animal manure is often used as fertilizer in agriculture and contains nutrients, pathogens, antibiotics, and heavy metals. Therefore, it is important to better understand common sources of multiple pollutants in water across scales to identify effective solutions. We develop computer models for different scales covering grids, (sub)basins, regions and the globe. Our models are for multiple pollutants, i.e. nutrients, plastics, antibiotics, pathogens (Cryptosporidium) and pesticides. Therefore, in this abstract, we aim to compare our model results for multiple pollutants to identify robust water pollution hotspots and their sources across scales. This will contribute to and support the Fast Track initiative within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) platform. At the EGU conference, we will show examples of multi-pollutant modeling using our MARINA models (Models to Assess River Inputs of pollutaNts to seAs) family and GlowPa (Global Waterborne Pathogens) model developments. We will compare our model results for multiple pollutants by using different global climate models. Accordingly, we will discuss the impact of climate simulations on multi-pollutant hotspots. We will also show examples of identified robust multi-pollutant hotspots globally. We will zoom into regional analyses to better understand the impact of climate change on water pollution. Ultimately, we will highlight the need for such model intercomparisons for multiple pollutants and scales to better understand pollution hotspots and their sources under global change.
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