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1. Virus reduction during advanced Bardenpho and conventional wastewater treatment processes

   Schmitz, B. ; Kitajima, M. ; Campillo, M. ; Gerba, C. ; Pepper, I. ( January 2016 , Environmental science & technology)

   The present study investigated wastewater treatment for the removal of 11 different virus types (pepper mild mottle virus; Aichi virus; genogroup I, II, and IV noroviruses; enterovirus;sapovirus; group-A rotavirus; adenovirus; and JC and BK polyomaviruses) by two wastewater treatment facilities utilizing advanced Bardenpho technology and compared the results with conventional treatment processes. To our knowledge, this is the first study comparing full-scale treatment processes that all received sewage influent from the same region. The incidence of viruses in wastewater was assessed with respect to absolute abundance, occurrence, and reduction in monthly samples collected throughout a 12 month period in southern Arizona. Samples were concentrated via an electronegative filter method and quantified using TaqMan-based quantitative polymerase chain reaction (qPCR). Results suggest that Plant D, utilizing an advanced Bardenpho process as secondary treatment, effectively reduced pathogenic viruses better than facilities using conventional processes. However, the absence of cell-culture assays did not allow an accurate assessment of infective viruses. On the basis of these data, the Aichi virus is suggested as a conservative viral marker for adequate wastewater treatment, as it most often showed the best correlation coefficients to viral pathogens, was always detected at higher concentrations, and may overestimate the potential virusmore »risk.« less
2. The Partitioning of Meridional Heat Transport from the Last Glacial Maximum to CO ₂ Quadrupling in Coupled Climate Models

   https://doi.org/10.1175/JCLI-D-19-0797.1  

   Donohoe, Aaron ; Armour, Kyle C. ; Roe, Gerard H. ; Battisti, David S. ; Hahn, Lily ( May 2020 , Journal of Climate)

   Meridional heat transport (MHT) is analyzed in ensembles of coupled climate models simulating climate states ranging from the Last Glacial Maximum (LGM) to quadrupled CO₂. MHT is partitioned here into atmospheric (AHT) and implied oceanic (OHT) heat transports. In turn, AHT is partitioned into dry and moist energy transport by the meridional overturning circulation (MOC), transient eddy energy transport (TE), and stationary eddy energy transport (SE) using only monthly averaged model output that is typically archived. In all climate models examined, the maximum total MHT (AHT + OHT) is nearly climate-state invariant, except for a modest (4%, 0.3 PW) enhancement of MHT in the Northern Hemisphere (NH) during the LGM. However, the partitioning of MHT depends markedly on the climate state, and the changes in partitioning differ considerably among different climate models. In response to CO₂quadrupling, poleward implied OHT decreases, while AHT increases by a nearly compensating amount. The increase in annual-mean AHT is a smooth function of latitude but is due to a spatially inhomogeneous blend of changes in SE and TE that vary by season. During the LGM, the increase in wintertime SE transport in the NH midlatitudes exceeds the decrease in TE resulting in enhanced total AHT.more »Total AHT changes in the Southern Hemisphere (SH) are not significant. These results suggest that the net top-of-atmosphere radiative constraints on total MHT are relatively invariant to climate forcing due to nearly compensating changes in absorbed solar radiation and outgoing longwave radiation. However, the partitioning of MHT depends on detailed regional and seasonal factors.

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3. Response of Green Lake, Wisconsin, to Changes in Phosphorus Loading, With Special Emphasis on Near-Surface Total Phosphorus Concentrations and Metalimnetic Dissolved Oxygen Minima

   https://doi.org/10.3133/sir20225003  

   Robertson, D.M. ( January 2022 , Scientific investigations report)

   Green Lake is the deepest natural inland lake in Wisconsin, with a maximum depth of about 72 meters. In the early 1900s, the lake was believed to have very good water quality (low nutrient concentrations and good water clarity) with low dissolved oxygen (DO) concentrations occurring in only the deepest part of the lake. Because of increased phosphorus (P) inputs from anthropogenic activities in its watershed, total phosphorus (TP) concentrations in the lake have increased; these changes have led to increased algal production and low DO concentrations not only in the deepest areas but also in the middle of the water column (metalimnion). The U.S. Geological Survey has routinely monitored the lake since 2004 and its tributaries since 1988. Results from this monitoring led the Wisconsin Department of Natural Resources (WDNR) to list the lake as impaired because of low DO concentrations in the metalimnion, and they identified elevated TP concentrations as the cause of impairment. As part of this study by the U.S. Geological Survey, in cooperation with the Green Lake Sanitary District, the lake and its tributaries were comprehensively sampled in 2017–18 to augment ongoing monitoring that would further describe the low DO concentrations in the lake (especiallymore »in the metalimnion). Empirical and process-driven water-quality models were then used to determine the causes of the low DO concentrations and the magnitudes of P-load reductions needed to improve the water quality of the lake enough to meet multiple water-quality goals, including the WDNR’s criteria for TP and DO. Data from previous studies showed that DO concentrations in the metalimnion decreased slightly as summer progressed in the early 1900s but, since the late 1970s, have typically dropped below 5 milligrams per liter (mg/L), which is the WDNR criterion for impairment. During 2014–18 (the baseline period for this study), the near-surface geometric mean TP concentration during June–September in the east side of the lake was 0.020 mg/L and in the west side was 0.016 mg/L (both were above the 0.015-mg/L WDNR criterion for the lake), and the metalimnetic DO minimum concentrations (MOMs) measured in August ranged from 1.0 to 4.7 mg/L. The degradation in water quality was assumed to have been caused by excessive P inputs to the lake; therefore, the TP inputs to the lake were estimated. The mean annual external P load during 2014–18 was estimated to be 8,980 kilograms per year (kg/yr), of which monitored and unmonitored tributary inputs contributed 84 percent, atmospheric inputs contributed 8 percent, waterfowl contributed 7 percent, and septic systems contributed 1 percent. During fall turnover, internal sediment recycling contributed an additional 7,040 kilograms that increased TP concentrations in shallow areas of the lake by about 0.020 mg/L. The elevated TP concentrations then persisted until the following spring. On an annual basis, however, there was a net deposition of P to the bottom sediments. Empirical models were used to describe how the near-surface water quality of Green Lake would be expected to respond to changes in external P loading. Predictions from the models showed a relatively linear response between P loading and TP and chlorophyll-a (Chl-a) concentrations in the lake, with the changes in TP and Chl-a concentrations being less on a percentage basis (50–60 percent for TP and 30–70 percent for Chl-a) than the changes in P loading. Mean summer water clarity, quantified by Secchi disk depths, had a greater response to decreases in P loading than to increases in P loading. Based on these relations, external P loading to the lake would need to be decreased from 8,980 kg/yr to about 5,460 kg/yr for the geometric mean June–September TP concentration in the east side of the lake, with higher TP concentrations than in the west side, to reach the WDNR criterion of 0.015 mg/L. This reduction of 3,520 kg/yr is equivalent to a 46-percent reduction in the potentially controllable external P sources (all external sources except for precipitation, atmospheric deposition, and waterfowl) from those measured during water years 2014–18. The total external P loading would need to decrease to 7,680 kg/yr (a 17-percent reduction in potentially controllable external P sources) for near-surface June–September TP concentrations in the west side of the lake to reach 0.015 mg/L. Total external P loading would need to decrease to 3,870–5,320 kg/yr for the lake to be classified as oligotrophic, with a near-surface June–September TP concentration of 0.012 mg/L. Results from the hydrodynamic water-quality model GLM–AED (General Lake Model coupled to the Aquatic Ecodynamics modeling library) indicated that MOMs are driven by external P loading and internal sediment recycling that lead to high TP concentrations during spring and early summer, which in turn lead to high phytoplankton production, high metabolism and respiration, and ultimately DO consumption in the upper, warmer areas of the metalimnion. GLM–AED results indicated that settling of organic material during summer might be slowed by the colder, denser, and more viscous water in the metalimnion and thus increase DO consumption. Based on empirical evidence from a comparison of MOMs with various meteorological, hydrologic, water quality, and in-lake physical factors, MOMs were lower during summers, when metalimnetic water temperatures were warmer, near-surface Chl-a and TP concentrations were higher, and Secchi depths were lower. GLM–AED results indicated that the external P load would need to be reduced to about 4,060 kg/yr, a 57-percent reduction from that measured in 2014–18, to eliminate the occurrence of MOMs less than 5 mg/L during more than 75 percent of the years (the target provided by the WDNR). Large reductions in external P loading are expected to have an immediate effect on the near-surface TP concentrations and metalimnetic DO concentrations in Green Lake; however, it may take several years for the full effects of the external-load reduction to be observed because internal sediment recycling is an important source of P for the following spring.« less
4. The importance of system configuration for distributed direct potable water reuse

   https://doi.org/10.1038/s41893-020-0518-5  

   Liu, Lu ; Lopez, Evan ; Dueñas-Osorio, Leonardo ; Stadler, Lauren ; Xie, Yuefeng ; Alvarez, Pedro J. ; Li, Qilin ( April 2020 , Nature Sustainability)

   Water and wastewater infrastructure worldwide faces unprecedented demand and supply conflicts that require unconventional solutions. In this study, we develop a novel modelling framework to assess the environmental and economic implications of a hybrid water supply system that supplements a centralized surface water supply with distributed direct potable reuse (DPR) of municipal wastewater, as a strategy to address such challenges. The model is tested with real water and wastewater systems data from the City of Houston, Texas. Results show that supplementing the conventional centralized water supply with distributed DPR would reduce water age in the drinking-water distribution network and hence improve water quality; properly designed system configurations attain system-wide net energy savings even with the high energy consumption of existing technologies used for advanced treatment of the wastewater. A target energy efficiency for future advanced treatment technologies is identified to achieve net energy saving with all hybrid system configurations. Furthermore, distributed DPR remains financially competitive compared with other unconventional water supply solutions. The modelling framework and associated databases developed in this study serve an important research need for quantitatively characterizing distributed and hybrid water systems, laying the necessary foundation for rational design of integrated urban water systems.
5. Evaluation of bias correction methods for current and future RCM projections in hydrological regional applications

   https://doi.org/10.5194/egusphere-egu22-10600  

   Brighenti, T. ; Gassman, P. ; Gutowski, W. ; Thompson, J. ( May 2022 , European Union General Assembly 2022 Abstracts)

   RCMs produced at ~0.5° (available in the NA-CORDEX database esgf-node.ipsl.upmc.fr/search/cordex-ipsl/) address issues related to coarse resolution of GCMs (produced at 2° to 4°). Nevertheless, due to systematic and random model errors, bias correction is needed for regional study applications. However, an acceptable threshold for magnitude of bias correction that will not affect future RCM projection behavior is unknown. The goal of this study is to evaluate the implications of a bias correction technique (distribution mapping) for four GCM-RCM combinations for simulating regional precipitation and, subsequently, streamflow, surface runoff, and water yield when integrated into Soil and Water Assessment Tool (SWAT) applications for the Des Moines River basin (31,893 km²) in Iowa-Minnesota, U.S. The climate projections tested in this study are an ensemble of 2 GCMs (MPI-ESM-MR and GFDL-ESM2M) and 2 RCMs (WRF and RegCM4) for historical (1981-2005) and future (2030-2050) projections in the NA-CORDEX CMIP5 archive. The PRISM dataset was used for bias correction of GCM-RCM historical precipitation and for SWAT baseline simulations. We found bias correction improves historical total annual volumes for precipitation, seasonality, spatial distribution and mean error for all GCM-RCM combinations. However, improvement of correlation coefficient occurred only for the RegCM4 simulations. Monthly precipitation was overestimated formore »all raw models from January to April, and WRF overestimated monthly precipitation from January to August. The bias correction method improved monthly average precipitation for all four GCM-RCM combinations. The ability to detect occurrence of precipitation events was slightly better for the raw models, especially for the GCM-WRF combinations. Simulated historical streamflow was compared across 26 monitoring stations: Historical GCM-RCM outputs were unable to replicate PRISM KGE statistical results (KGE>0.5). However, the Pbias streamflow results matched the PRISM simulation for all bias-corrected models and for the raw GFDL-RegCM4 combination. For future scenarios there was no change in the annual trend, except for raw WRF models that estimated an increase of about 35% in annual precipitation. Seasonal variability remained the same, indicating wetter summers and drier winters. However, most models predicted an increase in monthly precipitation from January to March, and a reduction in June and July (except for raw WRF models). The impact on hydrological simulations based on future projected conditions was observed for surface runoff and water yield. Both variables were characterized by monthly volume overestimation; the raw WRF models predicted up to three times greater volume compared to the historical run. RegCM4 projected increased surface runoff and water yield for winter and spring by two times, and a slight volume reduction in summer and autumn. Meanwhile, the bias-corrected models showed changes in prediction signals: In some cases, raw models projected an increase in surface runoff and water yield but the bias-corrected models projected a reduction of these variables. These findings underscore the need for more extended research on bias correction and transposition between historical and future data.« less