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• Global economic water scarcity risks were assessed for quantity and quality. • Water quality-driven local and cascading economic risks comprised 20–30 %. • China emerged as the foremost exporter/importer of water scarcity risks globally. • Improving water efficiency and quality are equally vital for economic resilience. Pollution from untreated wastewater discharges depletes clean water supply for humans and the environment. It poses adverse economic impacts by determining agricultural yields, manufacturing productivity, and ecosystem functionality. Current studies mainly focus on quantity-related water scarcity assessment. It is unknown how low water quality amplifies local water stress and induces cascading economic risks globally. In this study, we estimated both quality and quantity-related water scarcity index (WSI), local economic water scarcity risk (WSR), and cascading virtual WSR evident in global trade markets across 40 major economies from 1995 to 2010. We find developing countries, e.g., India and China, witnessed fast growth in both quantity and quality-related WSI. Major developed economies, e.g., the US and Germany, experienced a modest increase in water stress but alleviated quality-related risks. Local economic risk (WSR) grew from $116B to $380B, with quality-related risks rising from 20 % to 30 %. Virtual economic WSR in global supply chains increased from $39B to $160B, with quality-related risks increasing from 19 % to 27 %. China became the top exporter of economic WSR, ranked above the US, France, and Japan, and the second-largest position as an importer, trailing only the US. We finally conducted scenario modeling by 2030, assuming different progresses on SDG 6 targets. The findings suggest that only the most ambitious progress in both water quality enhancement and efficiency improvement helps to alleviate ∼20 % economic WSR globally. Our findings underscore the necessity for strategies that integrate management of untreated wastewater flows, improved water use efficiency, and diversification of supply chain networks to enhance global economic resilience to water challenges in the future. [Display omitted] [ABSTRACT FROM AUTHOR]

Nutrient pollution is a widespread problem in rivers in China. Managing nutrient pollution requires better knowledge of in-stream processes governing the surface water quality. As current nutrient models for China mainly focus on river export of nutrients to seas, in-stream surface water quality and their contributing sources and processes are, therefore not well understood. This requires accounting for combined effects of nutrient inputs to rivers from produced waste, biochemistry of different forms of nutrients and their transport by river network. Moreover, improvements can be made in evaluating the model performance of large-scale nutrient models based on water quality measurements in China (using the surface water quality classes from 1 to 6). The objective of this study is to quantify the spatial variation in in-stream water quality for nutrients, and associated sources, for water quality classes in China. Our new Model to Assess River Inputs of Nutrients to seAs (MARINA 3.0) for in-stream water quality distinguishes different nutrient forms including dissolved inorganic (DIN, DIP) and organic (DON, DOP) nitrogen and phosphorus and was applied for the year 2012. Our model simulations compare reasonably well with measurements across 155 river sections. Results show that between 12% and 66% of the streams are highly polluted (exceeding water quality class 3) and depending on nutrient form. Diffuse sources dominate in 76% of the streams for DIN. Point sources such as direct discharges of animal manure dominate in 46%–59% of the streams for DON, DIP and DOP. The dominant sources vary considerably between rivers and nutrient forms. This indicates the need account for nutrient forms in models and national monitoring programs. Our model results could support effective management to reduce nutrient pollution in China. • We model in-stream water quality explicitly in relation to water quality classes in China. • Between 12% and 66% of the streams are highly polluted (above water quality class III). • Diffuse sources dominate in more than two-thirds of the streams for DIN. • Point sources dominated in around half of the streams for DON, DIP and DOP. • Polluted streams contribute to coastal eutrophication along Chinese coasts, particular for Bohai Gulf. [ABSTRACT FROM AUTHOR]

Surface waters account for 77% of the total fresh water resources in China. Rivers areimportant fresh water resources for human needs, but severely polluted with nutrients inChina. This study addresses three challenges in nutrient modelling for rivers in China. First,the understanding of the impacts and the development of associated managementstrategies are still humbled by the traditional modelling scales. Existing models oftenquantify nutrient pollution on biophysical scales (e.g. basin, grid), whereas sources andmanagement strategies are from administrative scales (e.g. county, province levels).Second, the representation of locations of point sources in existing water qualitymodels is generally poor. The spatial characteristics of the point source locations(e.g. hydrology) can influence on the water quality. Third, the direct discharges ofmanure are not well represented in most existing water quality models. However,direct discharges of manure to rivers have a considerable contribution to the nutrientpollution in China. The objective of this study is, therefore, to quantify inputs ofnitrogen (N) and phosphorus (P) to Chinese rivers from different sources at multiplescales. We developed a novel multi-scale modelling approach based on three models: The Modelto Assess River Inputs of Nutrients to seAs (MARINA), NUtrient flows in Food chains,Environment and Resources use (NUFER) and the Variable Infiltration Capacity (VIC)hydrological model. Our multi-scale model is novel for (1) modelling on multiple scales fordifferent processes as appropriate, (2) producing the outputs (e.g. inputs of N and P to rivers)on multiple scales and (3) including a detailed, state-of-the art representation of point sourcesof nutrients in to rivers. Major improvements were made to the model inputs byusing the Chinese county database (2238 counties) and by including the location ofmanure discharges and of 4404 wastewater treatment plants (WWTPs) for the wholeChina. The model results show that the river pollution and source attributions differ amongspatial scales. Point sources account for 75% of the total dissolved phosphorus (TDP) inputsto rivers in China in 2012, and diffuse sources for 72% of total dissolved nitrogen (TDN)inputs. One-third of the sub-basins account for more than half of the nutrient pollution in theChinese rivers. Downscaling to the smallest scale (polygons) reveals that 14% and 9% ofthe area contribute to more than half of the calculated TDN and TDP pollution,respectively. Sources of nutrient pollution vary considerably among and within counties.Clearly, multi-scale modelling may help to develop effective policies to reduce riverpollution. PIC [ABSTRACT FROM AUTHOR]

Coal is the dominant fuel for electricity generation around the world. This type of electricity generation uses large amounts of water, increasing pressure on water resources. This calls for an in-depth investigation in the water-energy nexus of coal-fired electricity generation. In China, coal-fired power plants play an important role in the energy supply. Here we assessed water consumption of coal-fired power plants (CPPs) in China using four cooling technologies: closed-cycle cooling, once-through cooling, air cooling, and seawater cooling. The results show that water consumption of CPPs was 3.5 km 3 , accounting for 11% of total industrial water consumption in China. Eighty-four percent of this water consumption was from plants with closed-cycle cooling. China’s average water intensity of CPPs was 1.15 l/kWh, while the intensity for closed-cycle cooling was 3–10 times higher than that for other cooling technologies. About 75% of water consumption of CPPs was from regions with absolute or chronic water scarcity. The results imply that the development of CPPs needs to explicitly consider their impacts on regional water resources. [ABSTRACT FROM AUTHOR]