After significant increases in livestock productivity, China now needs to improve efficiency and environmental performance.

Most of the global population will live in urban areas in the 21st century. We study impacts of urbanization on future river pollution taking a multi-pollutant approach. We quantify combined point-source inputs of nutrients, microplastics, a chemical (triclosan) and a pathogen (Cryptosporidium) to 10,226 rivers in 2010, 2050 and 2100, and show how pollutants are related. Our scenarios consider socio-economic developments and varying rates of urbanization and wastewater treatment. Today, river pollution in Europe, South-East Asia and North America is severe. In the future, around 80% of the global population is projected to live in sub-basins with multi-pollutant problems in our high urbanization scenarios. In Africa, future river pollution is projected to be 11–18 times higher than in 2010, making it difficult to meet Sustainable Development Goals. Avoiding future pollution is technically possible with advanced wastewater treatment in many regions. In Africa, however, clean water availability is projected to remain challenging. Our multi-pollutant approach could support effective water pollution assessment in urban areas.

Meeting the United Nations’ (UN’s) 17 Sustainable Development Goals (SDGs) has become a worldwide mission. How these SDGs interrelate, however, is not well known. We assess the interactions between SDGs for the case of water pollution by nutrients in China. The results show 319 interactions between SDGs for clean water (SDGs 6 and 14) and other SDGs, of which 286 are positive (synergies) and 33 are negative (tradeoffs) interactions. We analyze six scenarios in China accounting for the cobenefits of water pollution control using a large-scale water quality model. We consider scenarios that benefit from synergies and avoid tradeoffs. Our results show that effective pollution control requires accounting for the interactions between SDGs. For instance, combining improved nutrient management, efficient food consumption, and climate mitigation is effective for simultaneously meeting SDGs 6 and 14 as well as other SDGs for food, cities and climate. Our study serves as an example of assessing SDG interactions in environmental policies in China as well as in other regions of the world.

Food production in China results in large losses of nitrogen (N) and phosphorus (P) to the environment. Our objective is to identify hotspots for N and P losses to the environment from food production in China at the county scale. To do this, we used the NUFER (Nutrient flows in Food chains, Environment and Resources use) model. Between 1990 and 2012, the hotspot area expanded by a factor of 3 for N, and 24 for P. In 2012 most hotspots were found in the North China Plain. Hotspots covered less than 10% of the Chinese land area, but contributed by more than half to N and P losses to the environment. Direct discharge of animal manure to rivers was an important cause of N and P losses. Food production was found to be more intensive in hotspots than in other counties. Synthetic fertilizer use and animal numbers in hotspots were a factor of 4–5 higher than in other counties in 2012. Also the number of people working in food production and the incomes of farmers are higher in hotspots than in other counties. This study concludes with suggestions for region-specific pollution control technologies for food production in China.