Data underlying the publication: ‘Wang et al (2022) Accounting for interactions between Sustainable Development Goals is essential for water pollution control in China. Nature Communications’

The data that are collected or generated include: literature, methods to identify the SDGs' interactions, and identified SDGs' interactions. Next, we conduct a scenarios analysis to explore the co-benefits of water pollution control, based on the MARINA (Model to Assess River Inputs of Nutrients to seAs) 2.0 model.

The data that are generated include: model equations, model inputs, and model outputs. Last, we perform a sensitivity analysis to evaluate the impacts of the quantitative assumptions on the effectiveness of our scenarios. The data generated from this include: changes in model inputs, and model outputs of the sensitivity analysis.