Precise Cation Separations with Composite Cation-Exchange Membranes: Role of Base Layer Properties.

Separation of specific ions from water could enable recovery and reuse of essential metals and nutrients, but established membrane technologies lack the high-precision selectivity needed to facilitate a circular resource economy. In this work, we investigate whether the cation/cation selectivity of a composite cation-exchange membrane (CEM), or a thin polymer selective layer on top of a CEM, may be limited by the mass transfer resistance of the underlying CEM. In our analysis, we utilize a layer-by-layer technique to modify CEMs with a thin polymer selective layer (∼50 nm) that has previously shown high selectivity toward copper over similarly sized metals. While these composite membranes have a CuCl2/MgCl2 selectivity up to 33 times larger than unmodified CEMs in diffusion dialysis, our estimates suggest that eliminating resistance from the underlying CEM could further increase selectivity twofold. In contrast, the CEM base layer has a smaller effect on the selectivity of these composite membranes in electrodialysis, although these effects could become more pronounced for ultrathin or highly conductive selective layers. Our results highlight that base layer resistance prevents selectivity factors from being comparable across diffusion dialysis and electrodialysis, and CEMs with low resistance are necessary for providing highly precise separations with composite CEMs.

Longitudinal monitoring of SARS-CoV-2 in wastewater using viral genetic markers and the estimation of unconfirmed COVID-19 cases.

In this study, wastewater-based surveillance was carried out to establish the correlation between SARS-CoV-2 viral RNA concentrations in wastewater and the incidence of corona virus disease 2019 (COVID-19) from clinical testing. The influent wastewater of three major water reclamation facilities (WRFs) in Northern Nevada, serving a population of 390,750, was monitored for SARS-CoV-2 viral RNA gene markers, N1 and N2, from June 2020 through September 2021. A total of 614 samples were collected and analyzed. The SARS-CoV-2 concentrations in wastewater were observed to peak twice during the study period. A moderate correlation trend between coronavirus disease 2019 (COVID-19) incidence data from clinical testing and SARS-CoV-2 viral RNA concentrations in wastewater was observed (Spearman r = 0.533). This correlation improved when using weekly average SARS-CoV-2 marker concentrations of wastewater and clinical case data (Spearman r = 0.790), presumably by mitigating the inherent variability of the environmental dataset and the effects of clinical testing artifacts (e.g., reporting lags). The research also demonstrated the value of wastewater-based surveillance as an early warning signal for early detection of trends in COVID-19 incidence. This was accomplished by identifying that the reported clinical cases had a stronger correlation to SARS-CoV-2 wastewater monitoring data when they were estimated to lag 7-days behind the wastewater data. The results aided local decision makers in developing strategies to manage COVID-19 in the region and provide a framework for how wastewater-based surveillance can be applied across localities to enhance the public health monitoring of the ongoing pandemic.

Spatial and temporal variability and data bias in wastewater surveillance of SARS-CoV-2 in a sewer system.

The response to disease outbreaks, such as SARS-CoV-2, can be constrained by a limited ability to measure disease prevalence early at a localized level. Wastewater based epidemiology is a powerful tool identifying disease spread from pooled community sewer networks or at influent to wastewater treatment plants. However, this approach is often not applied at a granular level that permits detection of local hot spots. This study examines the spatial patterns of SARS-CoV-2 in sewage through a spatial sampling strategy across neighborhood-scale sewershed catchments. Sampling was conducted across the Reno-Sparks metropolitan area from November to mid-December of 2020. This research utilized local spatial autocorrelation tests to identify the evolution of statistically significant neighborhood hot spots in sewershed sub-catchments that were identified to lead waves of infection, with adjacent neighborhoods observed to lag with increasing viral RNA concentrations over subsequent dates. The correlations between the sub-catchments over the sampling period were also characterized using principal component analysis. Results identified distinct time series patterns, with sewersheds in the urban center, outlying suburban areas, and outlying urbanized districts generally following unique trends over the sampling period. Several demographic parameters were identified as having important gradients across these areas, namely population density, poverty levels, household income, and age. These results provide a more strategic approach to identify disease outbreaks at the neighborhood level and characterized how sampling site selection could be designed based on the spatial and demographic characteristics of neighborhoods.

Removal of SARS-CoV-2 viral markers through a water reclamation facility.

There have been multiple reports of COVID-19 virus, SARS-CoV-2 RNA presence in influent wastewater of water reclamation facilities (WRFs) across the world. In this study, the removal of SARS-CoV-2 RNA was investigated in a WRF by collecting samples from various stages relayed to hydraulic retention time (HRT) and analyzed for viral RNA (N1 and N2) gene markers and wastewater characteristics. SARS-CoV-2 RNA was detected in 28 out of 28 influent wastewater and primary effluent samples. Secondary effluent showed 4 out of 9 positive samples, and all tertiary and final effluent samples were below the detection limit for the viral markers. The reduction was significant (p value < 0.005, one-way analysis of variance [ANOVA] test) in secondary treatment, ranging from 1.4 to 2.0 log10 removal. Adjusted N1 viral marker had a positive correlation with total suspended solids, total Kjeldahl nitrogen, and ammonia concentrations (Spearman's ρ = 0.61, 0.67, and 0.53, respectively, p value < 0.05), while demonstrating a strongly negative correlation with HRT (Spearman's ρ = -0.58, p value < 0.01). PRACTITIONER POINTS: Viral RNA was present in all samples taken from influent and primary effluent of a WRF. SARS-CoV-2 gene marker was detected in secondary effluent in 4 out of 9 samples. Tertiary and final effluent samples tested nondetect for SARS-CoV-2 gene markers. Up to 0.5 and 2.0 log10 virus removal values were achieved by primary and secondary treatment, respectively.