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Worldwide riverine thermal pollution patterns were investigated by combining mean annual heat rejection rates from power plants with once-through cooling systems with the global hydrologicalwater temperature model variable infiltration capacity (VIC)-RBM. The model simulates both streamflow and water temperature on 0.5°×0.5°spatial resolution worldwide and by capturing their effect, identifies multiple thermal pollution hotspots. The Mississippi receives the highest total amount of heat emissions (62% and 28% of which come from coal-fuelled and nuclear power plants, respectively) and presents the highest number of instances where the commonly set 3°C temperature increase limit is equalled or exceeded. The Rhine receives 20% of the thermal emissions compared to the Mississippi (predominantly due to nuclear power plants), but is the thermally most polluted basin in relation to the total flow per watershed, with one third of its total flow experiencing a temperature increase 5°C on average over the year. In other smaller basins in Europe, such as the Weser and the Po, the share of the total streamflow with a temperature increase 3°C goes up to 49% and 81%, respectively, during July-September. As the first global analysis of its kind, this work points towards areas of high riverine thermal pollution, where temporally finer thermal emission data could be coupled with a spatially finer model to better investigate water temperature increase and its effect on aquatic ecosystems.
Energy systems support technical solutions fulfilling the United Nations' Sustainable Development Goal for clean water and sanitation (SDG6), with implications for future energy demands and greenhouse gas emissions. The energy sector is also a large consumer of water, making water efficiency targets ingrained in SDG6 important constraints for long-term energy planning. Here, we apply a global integrated assessment model to quantify the cost and characteristics of infrastructure pathways balancing SDG6 targets for water access, scarcity, treatment and efficiency with long-term energy transformations limiting climate warming to 1.5°C. Under a mid-range human development scenario, we find that approximately 1 trillion USD2010 per year is required to close water infrastructure gaps and operate water systems consistent with achieving SDG6 goals by 2030. Adding a 1.5°C climate policy constraint increases these costs by up to 8%. In the reverse direction, when the SDG6 targets are added on top of the 1.5°C policy constraint, the cost to transform and operate energy systems increases 2%-9% relative to a baseline 1.5°C scenario that does not achieve the SDG6 targets by 2030. Cost increases in the SDG6 pathways are due to expanded use of energy-intensive water treatment and costs associated with water conservation measures in power generation, municipal, manufacturing and agricultural sectors. Combined global spending (capital and operational expenditures) to 2030 on water, energy and land systems increases 92%-125% in the integrated SDG6-1.5°C scenarios relative to a baseline 'no policy' scenario. Evaluation of the multi-sectoral policies underscores the importance of water conservation and integrated water-energy planning for avoiding costs from interacting water, energy and climate goals.
A Life Cycle Impact Assessment method was developed to evaluate the environmental impact associated with salinity on biodiversity in a Spanish coastal wetland. The developed characterization factor consists of a fate and an effect factor and equals 3.16 × 10(-1) ± 1.84 × 10(-1) PAF · m(3) · yr · m(-3) (PAF: Potentially Affected Fraction of species) indicating a "potential loss of 0.32 m(3) ecosystem" for a water consumption rate of 1 m(3) · yr(-1). As a result of groundwater consumption with a rate of 1 m(3) · yr(-1), the PAF in the lost cubic meter of ecosystem equals 0.05, which has been proposed as the maximum tolerable effect to keep the ecosystem intact. The fate factor was calculated from seasonal water balances of the wetland Albufera de Adra. The effect factor was obtained from the fitted curve of the potentially affected fraction of native wetland species due to salinity and can be applied to other wetlands with similar species composition. In order to test the applicability of the characterization factor, an assessment of water consumption of greenhouse crops in the area was conducted as a case study. Results converted into ecosystem quality damage using the ReCiPe method were compared to other categories. While tomatoes are responsible for up to 30% of the impact of increased salinity due to water consumption on ecosystem quality in the studied area, melons have the largest impact per tonne produced.
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