Светоизлучающие диоды белого света: состояние и основные тенденции развития

Проведен обзор состояния и тенденций развития технологии изготовления светоизлучающих диодов белого света. Систематизированы параметры сверхъярких белых светодиодов, светодиодных модулей и источников света

Wastewater Surveillance for SARS-CoV-2 on College Campuses: Initial Efforts, Lessons Learned, and Research Needs

Wastewater surveillance for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging approach to help identify the risk of a coronavirus disease (COVID-19) outbreak. This tool can contribute to public health surveillance at both community (wastewater treatment system) and institutional (e.g., colleges, prisons, and nursing homes) scales. This paper explores the successes, challenges, and lessons learned from initial wastewater surveillance efforts at colleges and university systems to inform future research, development and implementation. We present the experiences of 25 college and university systems in the United States that monitored campus wastewater for SARS-CoV-2 during the fall 2020 academic period. We describe the broad range of approaches, findings, resources, and impacts from these initial efforts. These institutions range in size, social and political geographies, and include both public and private institutions. Our analysis suggests that wastewater monitoring at colleges requires consideration of local information needs, sewage infrastructure, resources for sampling and analysis, college and community dynamics, approaches to interpretation and communication of results, and follow-up actions. Most colleges reported that a learning process of experimentation, evaluation, and adaptation was key to progress. This process requires ongoing collaboration among diverse stakeholders including decision-makers, researchers, faculty, facilities staff, students, and community members

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Decision Support for Multi-Benefit Urban Water Infrastructure

Urban water systems in the United States are poised for massive change. Water infrastructure built in the 20th century has promoted public health and has protected ecosystems from pollution. However, much of this infrastructure is now coming to the end of its design life, and requires substantial investments to keep it functional. Our water systems also face new challenges from shifting precipitation patterns, sea level rise, and contaminants of emerging concern, among others. Modernizing our nation’s aging water infrastructure is imperative – and to meet 21st century challenges, we must do better than simply repairing it. The next generation of urban water infrastructure can also provide other societal benefits like resource recovery from sewage, increased wildlife habitat, and improved resilience to climate change effects in addition to water supply and wastewater treatment. Yet there still is little guidance for how water managers can include broader societal goals for multi-benefit infrastructure into what have historically been singular fields of engineered water supply and wastewater treatment. Without a better understanding of how public policy ties in to water infrastructure goals, improvements may only be made in moments of crisis, and the opportunity to create multi-benefit water systems will be lost.This dissertation seeks to support decision-makers in designing and implementing more equitable, holistic, and environmentally-sound urban water infrastructure. Chapter I assesses historical precedents for recycling sewage into drinking water in California to contextualize current concerns and challenges. Water recycling has had a rich and varied history in California; currently, potable water reuse is on the rise. Chapter II develops a legitimacy framework for potable water reuse in California, which facilitates decision-making about technologies that fit into the unique social, political, and cultural contexts of a particular locale. Chapter III provides a popular science look at the practice of potable water reuse, which is unfamiliar to many people and has faced stark public opposition in some areas. Chapter IV focuses on stakeholder perspectives to identify goals and strategies for multi-benefit wastewater treatment, as well as analyzes barriers to achieving these goals. Chapter V employs a quantitative multi-criteria decision analysis paired with stakeholder analysis and scenario planning to evaluate potential nutrient management options for the San Francisco Bay Area in uncertain future conditions

Decision Support for Multi-Benefit Urban Water Infrastructure

Urban water systems in the United States are poised for massive change. Water infrastructure built in the 20th century has promoted public health and has protected ecosystems from pollution. However, much of this infrastructure is now coming to the end of its design life, and requires substantial investments to keep it functional. Our water systems also face new challenges from shifting precipitation patterns, sea level rise, and contaminants of emerging concern, among others. Modernizing our nation’s aging water infrastructure is imperative – and to meet 21st century challenges, we must do better than simply repairing it. The next generation of urban water infrastructure can also provide other societal benefits like resource recovery from sewage, increased wildlife habitat, and improved resilience to climate change effects in addition to water supply and wastewater treatment. Yet there still is little guidance for how water managers can include broader societal goals for multi-benefit infrastructure into what have historically been singular fields of engineered water supply and wastewater treatment. Without a better understanding of how public policy ties in to water infrastructure goals, improvements may only be made in moments of crisis, and the opportunity to create multi-benefit water systems will be lost.This dissertation seeks to support decision-makers in designing and implementing more equitable, holistic, and environmentally-sound urban water infrastructure. Chapter I assesses historical precedents for recycling sewage into drinking water in California to contextualize current concerns and challenges. Water recycling has had a rich and varied history in California; currently, potable water reuse is on the rise. Chapter II develops a legitimacy framework for potable water reuse in California, which facilitates decision-making about technologies that fit into the unique social, political, and cultural contexts of a particular locale. Chapter III provides a popular science look at the practice of potable water reuse, which is unfamiliar to many people and has faced stark public opposition in some areas. Chapter IV focuses on stakeholder perspectives to identify goals and strategies for multi-benefit wastewater treatment, as well as analyzes barriers to achieving these goals. Chapter V employs a quantitative multi-criteria decision analysis paired with stakeholder analysis and scenario planning to evaluate potential nutrient management options for the San Francisco Bay Area in uncertain future conditions

Towards a New Paradigm of Urban Water Infrastructure: Identifying Goals and Strategies to Support Multi-Benefit Municipal Wastewater Treatment

Over the past decade, water professionals have begun to focus on a new paradigm for urban water systems, which entails the recovery of resources from wastewater, the integration of engineered and natural systems, and coordination among agencies managing different facets of water systems. In the San Francisco Bay Area, planning for nutrient management serves as an exemplary model of this transition. We employed a variety of methodological approaches including stakeholder analysis, multi-criteria decision-making weight elicitation, and document analysis to understand and support decision-making in this context. Based on interviews with 32 stakeholders, we delineate goals that are considered to be important for achieving the new paradigm and we highlight management strategies that can help reach these goals. We identify and analyze the social, institutional, and technical impediments to planning and implementing multi-benefit wastewater infrastructure projects and identify strategies to overcome some of these challenges. Transitioning to a new paradigm for urban water infrastructure will require stakeholders to proactively forge collaborative relationships, jointly define a shared vision and objectives, and build new rules to overcome limitations of current institutional policies

The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: Considerations for model training data sets

During the COVID-19 pandemic, wastewater-based surveillance has been used alongside diagnostic testing to monitor infection rates. With the decline in cases reported to public health departments due to at-home testing, wastewater data may serve as the primary input for epidemiological models, but training these models is not straightforward. We explored factors affecting noise and bias in the ratio between wastewater and case data collected in 26 sewersheds in California from October 2020 to March 2022. The strength of the relationship between wastewater and case data appeared dependent on sampling frequency and population size, but was not increased by wastewater normalization to flow rate or case count normalization to testing rates. Additionally, the lead and lag times between wastewater and case data varied over time and space, and the ratio of log-transformed individual cases to wastewater concentrations changed over time. This ratio decreased between the Epsilon/Alpha and Delta variant surges of COVID-19 and increased during the Omicron BA.1 variant surge, and was also related to the diagnostic testing rate. Based on this analysis, we present a framework of scenarios describing the dynamics of the case to wastewater ratio to aid in data handling decisions for ongoing modeling efforts

Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be integrated with COVID-19 case data to inform timely pandemic response. However, more research is needed to apply and develop systematic methods to interpret the true SARS-CoV-2 signal from noise introduced in wastewater samples (e.g., from sewer conditions, sampling and extraction methods, etc.). In this study, raw wastewater was collected weekly from five sewersheds and one residential facility. The concentrations of SARS-CoV-2 in wastewater samples were compared to geocoded COVID-19 clinical testing data. SARS-CoV-2 was reliably detected (95% positivity) in frozen wastewater samples when reported daily new COVID-19 cases were 2.4 or more per 100,000 people. To adjust for variation in sample fecal content, four normalization biomarkers were evaluated: crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA. Of these, crAssphage displayed the least spatial and temporal variability. Both unnormalized SARS-CoV-2 RNA signal and signal normalized to crAssphage had positive and significant correlation with clinical testing data (Kendall's Tau-b (τ)=0.43 and 0.38, respectively), but no normalization biomarker strengthened the correlation with clinical testing data. Locational dependencies and the date associated with testing data impacted the lead time of wastewater for clinical trends, and no lead time was observed when the sample collection date (versus the result date) was used for both wastewater and clinical testing data. This study supports that trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence and presents tools that could be applied to make wastewater signal more interpretable and comparable across studies