Structured Ethical Review for Wastewater-Based Testing in Support of Public Health.

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.

Structured Ethical Review for Wastewater-Based Testing.

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns. Synopsis: Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.

Teaching sustainability: does style matter?

Purpose: This paper aims to analyze how a tangram activity improved students' abilities to explain sustainability, articulate a positive perception of sustainable design and relate sustainability with innovation in engineering design. Design/methodology/approach: The concept of paradigm shift was introduced in the classroom by using a tangram activity to help students understand that sustainable design requires out-of-the-box thinking. Instructors from three institutions teaching various levels of sustainability courses to engineering majors used the activity to introduce sustainable design, then measured the understanding and appreciation of the concepts introduced through the tangram activity with pre- and post-activity surveys. Findings: Findings from the study indicate that students' perceptions of sustainability significantly improved due to the activity, without regard to the institution. The activity also significantly improved students understanding of the connection between sustainability and innovation, across all three institutions, across all majors and across all years of study except second-year students. Improving engineering students' views on sustainability may lead, over time, to changes in the industry, in which environmental performance is incorporated into the engineering design process. Originality/value: Active learning approaches are needed for affective-domain learning objectives in the sustainability field for students to learn the necessary attitudes, values and motivations to implement sustainability in engineering design. Simple, easily implemented active learning techniques, such as the tangram activity presented here, can be implemented across the curriculum or to the public to introduce the paradigm shift necessary with sustainable design.

Passive sampling to scale wastewater surveillance of infectious disease: Lessons learned from COVID-19.

Much of what is known and theorized concerning passive sampling techniques has been developed considering chemical analytes. Yet, historically, biological analytes, such as Salmonella typhi, have been collected from wastewater via passive sampling with Moore swabs. In response to the COVID-19 pandemic, passive sampling is re-emerging as a promising technique to monitor SARS-CoV-2 RNA in wastewater. Method comparisons and disease surveillance using composite, grab, and passive sampling for SARS-CoV-2 RNA detection have found passive sampling with a variety of materials routinely produced qualitative results superior to grab samples and useful for sub-sewershed surveillance of COVID-19. Among individual studies, SARS-CoV-2 RNA concentrations derived from passive samplers demonstrated heterogeneous correlation with concentrations from paired composite samples ranging from weak (R2 = 0.27, 0.31) to moderate (R2 = 0.59) to strong (R2 = 0.76). Among passive sampler materials, electronegative membranes have shown great promise with linear uptake of SARS-CoV-2 RNA observed for exposure durations of 24 to 48 h and in several cases RNA positivity on par with composite samples. Continuing development of passive sampling methods for the surveillance of infectious diseases via diverse forms of fecal waste should focus on optimizing sampler materials for the efficient uptake and recovery of biological analytes, kit-free extraction, and resource-efficient testing methods capable of rapidly producing qualitative or quantitative data. With such refinements passive sampling could prove to be a fundamental tool for scaling wastewater surveillance of infectious disease, especially among the 1.8 billion persons living in low-resource settings served by non-traditional wastewater collection infrastructure.

Combining anaerobic digestion and hydrothermal liquefaction in the conversion of dairy waste into energy: A techno economic model for New York state.

There is increasing global interest and policies being enacted to lower greenhouse gas emissions, especially from the agricultural sector. In the U.S. for example, states with large dairy operations may combine proven manure valorization technologies, such as anaerobic digestion and hydrothermal liquefaction. Sustainable manure treatment would increase the recovery of energy and other useful co-products, namely biogas, biocrude oil and hydro-char as well as lower the environmental impacts. In this study, the economic feasibility of implementing a centralized bioenergy system in New York State was investigated. The feasibility of this transformation depends on many factors, including capital costs, discount rates, and other financing arrangements, electricity selling prices, incentives and farm sizes and locations. For a large-scale implementation in New York State accounting for nearly 50% of the state's dairy farms, our model of a distributed, hybrid anaerobic/hydrothermal system was shown to treat 590 million liters of wet manure per day, producing 607 million kWh of electricity, 162,000 L of biocrude oil and 117,000 kg of hydro-char per day. Electricity selling price is a critical factor. Increasing the electricity selling price from wholesale ($0.06/kWh) to retail ($0.18/kWh) increased the net present value from $395 million to $1.5 billion (considering a 40-year project lifetime).

Residential proximity to high-density poultry operations associated with campylobacteriosis and infectious diarrhea.

Poultry carry zoonotic bacteria that can cause gastroenteritis in humans. Environmental transmission of pathogens from poultry operations may increase gastrointestinal infection risk in surrounding communities. To evaluate associations between residential proximity to high-density poultry operations and individual-level diarrheal illnesses, we conducted a nested case-control study among 514,488 patients in Pennsylvania (2006-2015). Using electronic health records, we identified cases of five gastrointestinal outcomes: three pathogen-specific infections, including Escherichia coli (n = 1425), Campylobacter (n = 567), and Salmonella (n = 781); infectious diarrhea (n = 781); and non-specific diarrhea (2012-2015; n = 28,201). We estimated an inverse-distance squared activity metric for poultry operations based on farm and patient addresses. Patients in the second and fourth (versus first) quartiles of the poultry operation activity metric had increased odds of Campylobacter (AOR [CI], Q2: 1.36 [1.01, 1.82]; Q3: 1.38 [0.98, 1.96]; Q4: 1.75 [1.31, 2.33]). Patients in the second, third, and fourth quartiles had increased odds of infectious diarrhea (Q2: 1.76 [1.29, 2.39]; Q3: 1.76 [1.09, 2.85]; Q4: 1.60 [1.12, 2.30]). Stratification revealed stronger relations of fourth quartile and both Campylobacter and infectious diarrhea in townships, the most rural community type in the study geography. Increasing extreme rainfall in the week prior to diagnosis strengthened fourth quartile Campylobacter associations. The poultry operation activity metric was largely unassociated with E. coli, Salmonella, and non-specific diarrhea. Findings suggest high-density poultry operations may be associated with campylobacteriosis and infectious diarrhea in nearby communities, highlighting additional public health concerns of industrial agriculture.

Prospects for energy recovery during hydrothermal and biological processing of waste biomass.

Thermochemical and biological processes represent promising technologies for converting wet biomasses, such as animal manure, organic waste, or algae, to energy. To convert biomass to energy and bio-chemicals in an economical manner, internal energy recovery should be maximized to reduce the use of external heat and power. In this study, two conversion pathways that couple hydrothermal liquefaction with anaerobic digestion or catalytic hydrothermal gasification were compared. Each of these platforms is followed by two alternative processes for gas utilization: 1) combined heat and power; and 2) combustion in a boiler. Pinch analysis was applied to integrate thermal streams among unit processes and improve the overall system efficiency. A techno-economic analysis was conducted to compare the feasibility of the four modeled scenarios under different market conditions. Our results show that a systems approach designed to recover internal heat and power can reduce external energy demands and increase the overall process sustainability.

Target Cultivation and Financing Parameters for Sustainable Production of Fuel and Feed from Microalgae.

Production of economically competitive and environmentally sustainable algal biofuel faces technical challenges that are subject to high uncertainties. Here we identify target values for algal productivity and financing conditions required to achieve a biocrude selling price of $5 per gallon and beneficial environmental impacts. A modeling framework--combining process design, techno-economic analysis, life cycle assessment, and uncertainty analysis--was applied to two conversion pathways: (1) "fuel only (HTL)", using hydrothermal liquefaction to produce biocrude, heat and power, and (2) "fuel and feed", using wet extraction to produce biocrude and lipid-extracted algae, which can substitute components of animal and aqua feeds. Our results suggest that with supporting policy incentives, the "fuel and feed" scenario will likely achieve a biocrude selling price of less than $5 per gallon at a productivity of 39 g/m(2)/day, versus 47 g/m(2)/day for the "fuel only (HTL)" scenario. Furthermore, if lipid-extracted algae are used to substitute fishmeal, the process has a 50% probability of reaching $5 per gallon with a base case productivity of 23 g/m(2)/day. Scenarios with improved economics were associated with beneficial environmental impacts for climate change, ecosystem quality, and resource depletion, but not for human health.

Quantitative uncertainty analysis of Life Cycle Assessment for algal biofuel production.

As a result of algae's promise as a renewable energy feedstock, numerous studies have used Life Cycle Assessment (LCA) to quantify the environmental performance of algal biofuels, yet there is no consensus of results among them. Our work, motivated by the lack of comprehensive uncertainty analysis in previous studies, uses a Monte Carlo approach to estimate ranges of expected values of LCA metrics by incorporating parameter variability with empirically specified distribution functions. Results show that large uncertainties exist at virtually all steps of the biofuel production process. Although our findings agree with a number of earlier studies on matters such as the need for wet lipid extraction, nutrients recovered from waste streams, and high energy coproducts, the ranges of reported LCA metrics show that uncertainty analysis is crucial for developing technologies, such as algal biofuels. In addition, the ranges of energy return on (energy) invested (EROI) values resulting from our analysis help explain the high variability in EROI values from earlier studies. Reporting results from LCA models as ranges, and not single values, will more reliably inform industry and policy makers on expected energetic and environmental performance of biofuels produced from microalgae.

Using FTIR spectroscopy to model alkaline pretreatment and enzymatic saccharification of six lignocellulosic biomasses.

Fourier transform infrared, attenuated total reflectance (FTIR-ATR) spectroscopy, combined with partial least squares (PLS) regression, accurately predicted solubilization of plant cell wall constituents and NaOH consumption through pretreatment, and overall sugar productions from combined pretreatment and enzymatic hydrolysis. PLS regression models were constructed by correlating FTIR spectra of six raw biomasses (two switchgrass cultivars, big bluestem grass, a low-impact, high-diversity mixture of prairie biomasses, mixed hardwood, and corn stover), plus alkali loading in pretreatment, to nine dependent variables: glucose, xylose, lignin, and total solids solubilized in pretreatment; NaOH consumed in pretreatment; and overall glucose and xylose conversions and yields from combined pretreatment and enzymatic hydrolysis. PLS models predicted the dependent variables with the following values of coefficient of determination for cross-validation (Q²): 0.86 for glucose, 0.90 for xylose, 0.79 for lignin, and 0.85 for total solids solubilized in pretreatment; 0.83 for alkali consumption; 0.93 for glucose conversion, 0.94 for xylose conversion, and 0.88 for glucose and xylose yields. The sugar yield models are noteworthy for their ability to predict overall saccharification through combined pretreatment and enzymatic hydrolysis per mass dry untreated solids without a priori knowledge of the composition of solids. All wavenumbers with significant variable-important-for-projection (VIP) scores have been attributed to chemical features of lignocellulose, demonstrating the models were based on real chemical information. These models suggest that PLS regression can be applied to FTIR-ATR spectra of raw biomasses to rapidly predict effects of pretreatment on solids and on subsequent enzymatic hydrolysis.

Using FTIR to predict saccharification from enzymatic hydrolysis of alkali-pretreated biomasses.

Fourier transform infrared, attenuated total reflectance (FTIR-ATR) spectroscopy combined with partial least squares (PLS) regression accurately predicted 72-h glucose and xylose conversions (g sugars/100 g potential sugars) and yields (g sugars/100 g dry solids) from cellulase-mediated hydrolysis of alkali-pretreated lignocellulose. Six plant biomasses that represent a variety of potential biofuel feedstocks--two switchgrass cultivars, big bluestem grass, a low-impact, high-diversity mixture of 32 species of prairie biomasses, mixed hardwood, and corn stover--were subjected to four levels of low-temperature NaOH pretreatment to produce 24 samples with a wide range of potential digestibility. PLS models were constructed by correlating FTIR spectra of pretreated samples to measured values of gluose and xylose conversions and yields. Variable selection, based on 90% confidence intervals of regression-coefficient matrices, improved the predictive ability of the models, while simplifying them considerably. Final models predicted sugar conversions with coefficient of determination for cross-validation (Q(2)) values of 0.90 for glucose and 0.89 for xylose, and sugar yields with Q(2) values of 0.92 for glucose and 0.91 for xylose. The sugar-yield models are noteworthy for their ability to predict enzymatic saccharification per mass dry solids without a priori knowledge of the composition of the solids. All peaks retained in the final regression coefficient matrices were previously assigned to chemical bonds and functional groups in lignocellulose, demonstrating that the models were based on real chemical information. This study demonstrates that FTIR spectroscopy combined with PLS regression can be used to rapidly estimate sugar conversions and yields from enzymatic hydrolysis of pretreated plant biomass.

Assessment of commercial hemicellulases for saccharification of alkaline pretreated perennial biomass.

The objective of this research was to measure the effects of different cellulase and hemicellulase mixtures on fermentable sugar production from two different perennial biomasses--switchgrass and a low-impact, high-diversity prairie biomass mixture (LIHD). Each was subjected to NaOH pretreatment, followed by hydrolysis with a commercial cellulase and ß-glucosidase mixture [CB] supplemented with either of two hemicellulases. For both biomasses, there was little gain in sugar yield when using CB alone beyond 20-25 mg/g TS; further gain in yield was possible only through hemicellulase supplementation. An equation that modeled CB and hemicellulase effects as occurring independently fit the data reasonably well, except at the lowest of cellulase loadings with hemicellulase, where synergistic interactions were evident. Examination of the marginal effectiveness of enzyme loadings (incremental grams sugar per incremental mg enzyme) over a broad range of loadings suggests that there is no need to customize enzymatic hydrolysis for NaOH-pretreated switchgrass and LIHD.