Reducing nutrient pollution in water systems in China: challenges, trends and solutions

China has been developing fast over the last decades. Intensive human activities in food production and urbanization have led to increasing nitrogen (N) and phosphorus (P) losses to water systems, causing freshwater and coastal water pollution. Reducing water pollution is important in China, especially given its commitments to the Sustainable Development Goals (SDGs) (e.g., SDGs 6 – “clean water and sanitation” and 14 – “life below water”). Nutrient models have been used to analyze the causes of nutrient pollution in water systems and to explore solutions for China. Existing modeling studies focus on either nutrient flows in human activities (e.g., food production) at administrative (e.g., province, country) scales, or on nutrient fluxes from land to water systems at bio-geophysical scales (e.g., river basins). However, a better understanding of how human activities at the administrative scales affect nutrient fluxes at bio-geophysical scales of water systems is needed for China. Nutrient pollution in water systems may continue to increase in the future because of the expected changes in socio-economic development (e.g., population, economy) in China. Climate change may also influence hydrology (e.g., runoff, river discharges), and thus will influence nutrient transport in water systems (e.g., rivers). However, how socio-economic and climatic changes, together, will affect future nutrient pollution in water systems in China is not well studied. Such analysis can be done by implementing the global Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) in nutrient models for China. Moreover, many policies in China attempt to reduce future water pollution by nutrients. However, limited insights are available on the effectiveness of these policies for reducing future water pollution by nutrients. The objective of this PhD thesis is to improve our understanding of nutrient pollution in water systems in China, with a focus on the challenges, trends, and solutions. To this end, I formulated six sub-objectives for my research on nutrient pollution in water systems (sub-objectives 2, 4, and 6) from human activities on land (sub-objectives 1, 3, and 5). Sub-objectives focusing on the challenges: To identify hotspots for nutrient losses from food production (Chapter 2) To compare nutrient loads to Lake Taihu with the critical nutrient loads of the lake (Chapter 3, case study) Sub-objectives focusing on the trends: To analyze how socio-economic development affects future nutrient losses from food production (Chapter 4) To analyze how global change affects future river export of nutrients to seas (Chapter 5) Sub-objectives focusing on the solutions: To explore how current and improved nutrient management affects future nutrient losses from food production (Chapter 6) To explore future scenarios to reduce nutrient pollution in water systems and to meet the SDGs (Chapter 7) To meet the objectives, I developed and applied new versions of the NUFER (NUtrient flows in Food chains, Environment and Resources use) and MARINA (Model to Assess River Inputs of Nutrients to seAs) models. I analyzed nutrient flows in China’s food system for counties, provinces and China using the NUFER model. I analyzed river export of nutrients by 12 large Chinese rivers. The main findings are: In recent past, nutrient losses from food production increased dramatically in China (Chapter 2) Hotspots covered less than 10% of the Chinese land, but contributed by more than half to N and P losses to the environment in 2012 (Chapter 2) To meet critical loads, river export of TDN and TDP to Lake Taihu needs to be reduced by 46–92% (Chapter 3) Opportunities are reducing synthetic fertilizer and improving wastewater treatment (Chapter 3) Nitrogen losses from food production to water systems in the future may increase by up to 65% relative to today if nutrient management does not improve (Chapter 4) Climate change makes water pollution control in China more difficult (Chapter 5) Current policies aimed at zero growth in fertilizer use are not very effective in reducing nutrient pollution from food production in China (Chapter 6) SDG 6&14 can be met with improved nutrient management in agriculture and sewage systems, efficient food consumption, and climate mitigation (Chapter 7) Future scenarios contributing to SDGs 6 and 14 may also contribute to other SDGs (Chapter 7) I reflected on the research in this thesis, drew five main lessons for future nutrient modeling, and discussed the implications of this thesis on future policies (Chapter 8). The main lessons are: 1) linking NUFER and MARINA models can help to better explore solutions to reduce nutrient pollution in water systems at administrative and bio-geophysical scales, 2) preferred spatial scales of modeling depending on the research objectives, 3) indicators can help to better understand and communicate the modeling results, 4) combining different types of scenarios is useful in exploring solutions in environmental modeling, and 5) the modeling approach in this thesis can be used to analyze nutrient pollution in water systems in other world regions. The development of recent environmental policies in China confirms two main findings of this thesis: 1) nutrient pollution in water systems has increased dramatically in China, and 2) direct discharge of animal manure and human waste are the important sources of nutrient pollution in water systems in China. My PhD thesis supports the formulation of future environmental policies for water pollution control in China. The linked NUFER-MARINA approach provides novel insights to nutrient pollution at both administrative (e.g., county, province, and country) and bio-geophysical (e.g., sub-basin) scales. Such insights are useful for formulating policies that are often implemented at administrative scales to reduce water pollution at bio-geophysical scales. The potential options for reducing water pollution proposed in this thesis can be considered by policymakers as a starting point. Further improvement of these options using the participatory approach can be done to account for different perspectives and uncertainties for policy implementation. Quantitative indicators for water pollution in this thesis are helpful in understanding and communicating the modeling results with policymakers and stakeholders. All this hopefully will contribute to reducing water pollution by nutrients, and meeting the SDGs 6 and 14 in China