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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.

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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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Steam-electric power dominates global electricity production. Mitigating its environmental burdens relies on quantifying them globally, on a high resolution. Here, with an unprecedented combination of detail and coverage, the Rankine cycle was individually modelled for >21 000 geocoded steam-electric generating units globally. Accounting for different cooling systems and fuels enabled the calculation of three major environmental stressors on a generating unit level. Geographical, chronological, and technological patterns are examined, as are trade-offs and improvement scenarios. Greenhouse gases (GHG) emissions from young (>2000) Chinese coal-fuelled generating units are equal to the sum of GHG emissions from all steam-electric power plants of all ages in the U.S. and Europe, and occupy 5% of all GHG emissions from the entire global economy. Twenty-four per cent of freshwater consumed from steam-electric power originates from nuclear power units from the 1970s/1980s, mainly in the U.S. and Europe. One per cent of steam-electric generating units is responsible for 50% of global heat emissions to freshwater. The median carbon intensity of Indian coal-fired units (≥50 MW) is 7%–16% higher than that in any other region globally. As concerns GHGs, technology-related efficiency differences (Rankine cycle, cooling system) play a small role compared to the fuel, which dominates the carbon intensity (GHGs/GJ el.). With the highest shares of cogeneration, 1 GJ electricity from tower-cooled coal units in Russia consumes on average 8%–49% less freshwater compared to respective units globally. There is a small margin for improvement based on alternative steam-electric technologies: retiring inefficient units and replacing their demand by ramping up more efficient ones with the same fuel, within the same country results in, respectively, ∼1%, 6%, and 11% fewer GHG emissions, freshwater consumption, and heat emissions globally. The full environmental benefits of completely retiring old units (<1970) consist of 9% fewer GHG emissions, 7% less freshwater consumed, and 18% fewer thermal emissions globally.

Patients with inflammatory rheumatic diseases (IRD) are at increased risk for worse COVID-19 outcomes. Identifying whether mRNA vaccines differ in immunogenicity and examining the effects of immunomodulatory treatments may support COVID-19 vaccination strategies. We aimed to conduct a long-term, model-based comparison of the humoral immunogenicity following BNT162b2 and mRNA-1273 vaccination in a cohort of IRD patients. Patients from the Swiss IRD cohort (SCQM), who assented to mRNA COVID-19 vaccination were recruited between 3/2021-9/2021. Blood samples at baseline, 4, 12, and 24 weeks post second vaccine dose were tested for anti-SARS-CoV-2 spike IgG (anti-S1). We examined differences in antibody levels depending on the vaccine and treatment at baseline while adjusting for age, disease, and past SARS-CoV-2 infection. 565 IRD patients provided eligible samples. Among monotherapies, rituximab, abatacept, JAKi, and TNFi had the highest odds of reduced anti-S1 responses compared to no medication. Patients on specific combination therapies showed significantly lower antibody responses than those on monotherapy. Irrespective of the disease, treatment, and past SARS-CoV-2 infection, the odds of higher antibody levels at 4, 12, and 24 weeks post second vaccine dose were, respectively, 3.4, 3.8, and 3.8 times higher with mRNA-1273 versus BNT162b2 (p &lt; 0.0001). With every year of age, the odds ratio of higher peak humoral immunogenicity following mRNA-1273 versus BNT162b2 increased by 5% (p &lt; 0.001), indicating a particular benefit for elderly patients. Our results suggest that in IRD patients, two-dose vaccination with mRNA-1273 versus BNT162b2 results in higher anti-S1 levels, even more so in elderly patients.