The United Nations' 17 Sustainable Development Goals (SDGs) aim for a better and more sustainable future. However, the interrelationships between these goals, leading to synergies and tradeoffs, are not well understood. Ignoring these interactions can result in ineffective policies. Water pollution by nutrients, a significant issue globally and particularly in China, poses threats to society and ecosystems. Between 2000 and 2012, a substantial percentage of groundwater and river sections in China exceeded WHO's maximum contaminant levels, leading to issues like harmful algae blooms. This problem is projected to worsen due to socioeconomic development and climate change. Effective water pollution control is crucial, especially considering China's commitment to the SDGs. This study analyzes synergies and tradeoffs between SDGs related to nutrient pollution control in China, focusing on agriculture, sewage, food consumption, and climate mitigation. The research aims to inform water pollution control policies for sustainable development, benefiting China and other regions.

The paper draws upon existing literature to identify SDG targets relevant to nutrient pollution in Chinese water systems. A seven-point scale framework from Griggs et al. (2017) is used to assess interactions between SDGs. The framework categorizes interactions into seven levels: canceling (-3), counteracting (-2), constraining (-1), consistent (0), enabling (+1), reinforcing (+2), and indivisible (+3). The review highlights previous research on the increasing nutrient levels in rivers, their negative impacts on water quality globally and in China, and the existing challenges in meeting SDG targets related to clean water and sanitation in the country.

The study employs a multi-stage methodology. First, it identifies SDGs and their targets relevant to nutrient pollution in China, categorizing their relevance as high, moderate, or low based on literature and expert knowledge. The seven-point scale framework of Griggs et al. (2017) is used to quantify the interactions (synergies and tradeoffs) between SDG 6 (Clean Water and Sanitation) and SDG 14 (Life Below Water) and other SDGs. The analysis considers the directionality of interactions – unidirectional (one-way) or bidirectional (two-way). Six future scenarios are developed using the MARINA 2.0 model. The scenarios explore various interventions, including improved sewage treatment (SE), improved nutrient use efficiency in agriculture (AG), combinations of these, sustainable food consumption (SFC), and climate mitigation (CLI). The MARINA 2.0 model is used to quantify total dissolved nitrogen (TDN) and total dissolved phosphorus (TDP) inputs to six major Chinese rivers, and river export of TDN and TDP to the seas in 2012 and 2050. The SSP5-RCP8.5 pathway serves as the baseline scenario. The model's performance is evaluated using metrics like R², NSE, and RSR. A sensitivity analysis is conducted by varying 12 model inputs by ±10% under the most effective scenario to assess the robustness of the results. Two indicators are used to assess SDG achievement: (1) China's Environmental Quality Standard for Surface Water (grade III) for SDG 6 and (2) Indicator for Coastal Eutrophication Potential (ICEP) for SDG 14. The assessment considers the challenges of using existing standards (like NH3 concentration alone) and discusses the need for more comprehensive indicators.

The study reveals 319 interactions between SDGs 6 and 14 and other SDGs, with 286 synergies and 33 tradeoffs. Significant interactions are found between SDGs related to sustainable water management (SDGs 6 and 14) and those addressing drivers of nutrient pollution (SDGs 2, 11, 12, and 13). Potential tradeoffs exist between SDG 6/14 and SDGs aiming for increased agriculture (SDG 2) and urban expansion (SDG 11), but these can be mitigated by synergies through sustainable consumption and production (SDG 12). The analysis of six future scenarios shows that the baseline SSP5-RCP8.5 scenario projects high nutrient pollution levels in rivers and coastal waters in 2050. The alternative scenarios, particularly the AG + SE + SFC + CLI scenario (combining improved agriculture, sewage treatment, sustainable food consumption, and climate mitigation), significantly reduce nutrient pollution. In the most effective scenario (AG+SE+SFC+CLI), TDN and TDP inputs to rivers are 64% and 90% lower than in the baseline, respectively, leading to 68% and 91% reductions in river export to the seas. The scenario analysis demonstrates that achieving SDGs 6 and 14 simultaneously with SDGs 2, 11, 12, and 13 is possible. The scenario analysis highlights the effectiveness of integrated approaches across multiple sectors. Specific details regarding nutrient loads in rivers are presented in the paper. Results of DIN and TDP concentrations at subbasin outlets are compared against China's water quality standards (grade III), demonstrating progress in meeting SDG 6, with notable remaining challenges in reducing nitrogen pollution. ICEP values show the potential for coastal eutrophication, indicating the need for comprehensive measures to meet SDG 14.

The findings highlight the importance of considering SDG interactions for effective water pollution control in China. Ignoring these interactions can lead to policies that may achieve some SDGs but compromise others. The most effective scenario (AG + SE + SFC + CLI) demonstrates the potential of integrating measures across sectors for achieving multiple SDGs simultaneously. The study acknowledges the limitations of current indicators for assessing SDGs 6 and 14, advocating for more comprehensive indicators that consider various nutrient forms and water quality aspects. The study also notes the need for integrated modeling frameworks to better assess multiple SDGs under consistent conditions and quantify the impact of accounting for SDG interactions in policy-making. The scenarios presented show that meeting the SDGs by 2030 may be challenging but not impossible, with technological advancements and the consideration of nature-based solutions potentially playing crucial roles.

This study demonstrates the crucial role of accounting for interactions between SDGs in achieving effective water pollution control. The 319 identified interactions (primarily synergies) underscore the interconnectedness of these goals. The success of the AG + SE + SFC + CLI scenario highlights the effectiveness of integrated approaches targeting agriculture, sewage, food consumption, and climate mitigation. The study emphasizes the need for better indicators and integrated modeling frameworks for policy support. Future research should focus on developing more sophisticated integrated modeling tools, exploring the role of technological advancements and nature-based solutions, and investigating the challenges of implementing the suggested strategies in diverse regional contexts.

The study's quantitative assessments of SDG interactions and co-benefits rely on model simulations, which have inherent uncertainties. The assumptions within the scenarios might not entirely reflect the complexities of real-world implementation. The analysis focuses on six major rivers in China, limiting the generalizability of findings to other regions. The choice of indicators for SDGs 6 and 14 reflects existing national plans, but limitations of these indicators are acknowledged, necessitating the development of more comprehensive measures.