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Motivation - Advanced propulsion and airframe concepts are being matured that could yield substantial reductions in fuel consumption and emissions to foster sustainable aviation - A need exists for an accurate, complementary but separate, physics-based acoustic assessment of these novel aircraft configurations
This guide is designed to assist community officials, volunteers, and regional planning agency staff in conducting preliminary community meetings to learn about attitudes towards solar energy in your community. The guide will provide the key steps, timelines, facilitators' guide, and tips for hosting successful focus groups. Focus groups are meetings with a small group that represent a diversity of perspectives in your community. These differ from an open meeting in that focus groups include very specific questions that are prepared in advance, and all participants are given time to respond and understand various perspectives about solar energy. The guide concludes with a suggested template for reporting the results of your focus group or community meeting to your community more broadly. Holding community focus groups is part of assessing community preferences, as part of the Community Planning for Solar toolkit (ag.umass.edu/solarplanning). This guide is designed to help municipalities in Massachusetts and other states proactively plan for solar development in their communities. For more information, visit the UMass Clean Energy Extension (CEE) website (ag.umass.edu/clean-energy).
The World Climate Research Programme’s (WCRP) Global Energy and Water Exchanges (GEWEX) program is an integrated program of research, observations, and science activities with the mission to “Observe, understand and model the hydrological cycle and energy fluxes in the Earth’s atmosphere and at the surface.” Since the public release in 2010 of SRB Release 3, GEWEX reorganized to formulate the Data and Assessments Panel (GDAP) aimed at performing community assessments of the long-term global data products with focus on integrating various data products to address issues in the closing of the global energy and water cycles. SRB Release 4 Intergrated Product (Rel4-IP) integrates data products from the cloud, aerosol, atmosphere, ocean surface, and land surface projects within GDAP to produce a long-term time series of Top-of-Atmosphere (TOA) and surface radiative estimates. This Algorithm Theoretical Basis Document (ATBD) describes the various inputs, algorithms and resulting top-of-atmosphere and surface flux products that span from July 1983 through June 2017. Comparisons of the TOA flux products are made to overlapping CERES data products when possible. The surface radiative flux products are assessed relative to the globally distribution Baseline Surface Radiation Network measurements sites. Variability of the various products are compared to ERBE and CERES during overlapping time periods. The variability of the product show excellent correspondent to CERES during overlap years and improved statistical agreement with surface measurements. This document also discusses known issues with the data products to help the user understand the uncertainty and known issues.
This research assesses community sentiment towards Carbon Capture and Storage (CCS) as depicted in digital media, focusing on themes such as emissions, transport, and storage. Utilizing the VADER sentiment analysis model, the study analyzed titles and descriptions from online news articles to capture immediate impressions and sentiments. Results indicate a predominantly positive sentiment towards CCS, with significant regional variations. States like Alabama and Texas exhibit high positive sentiment, likely due to economic ties to the energy industry, while states like Delaware and Utah show negative sentiment, potentially driven by environmental concerns. The significance of this study lies in its potential to inform policy and communication strategies for CCS implementation. Understanding public sentiment is crucial for the success of CCS projects as it helps to identify and address community concerns. Media influence plays a significant role in shaping public opinion, and this study highlights the need for effective communication strategies to promote the benefits of CCS while addressing any misconceptions. By providing insights into regional differences in sentiment, this research supports the development of tailored interventions that can enhance public acceptance and support for CCS initiatives, ultimately contributing to the success of efforts to mitigate climate change through reduced greenhouse gas emissions.
Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.
This guide is designed to aid in assessing community preferences for solar development and financing alternatives. To evaluate community preferences regarding solar, it is necessary to define the range of realistic options for solar development possible in a community, including potential future targets for solar capacity, the mixes of development possible based on the solar resources available, and potential community benefits and solar ownership structures. This guide can help community officials, volunteers, and regional planning agency staff in constructing a realistic suite of options for solar development, based on existing state and local laws, available solar resources and infrastructure, and economic and financial considerations.
Understanding lowermost stratosphere (LMS) ozone variability is an important topic in the trends and climate assessment communities because of feedbacks among changing temperature, dynamics, water vapor and ozone. LMS evaluations are usually based on satellite observations. Free tropospheric (FT) ozone assessments typically rely on profiles from commercial aircraft. Ozonesonde measurements constitute an independent dataset encompassing both LMS and FT. We used Southern Hemisphere Additional Ozonesondes (SHADOZ) data from 1998-2019 in the GSFC Multiple Linear Regression (MLR) model to analyze monthly mean FT and LMS ozone across five well-distributed tropical sites, three based on combination of nearby individual stations (Figure 1). Our findings: (1) both FT (defined as 5-15 km) and LMS (15-20 km) ozone trends exhibit marked regional and seasonal variability. (2) Stations with the largest FT ozone increases, in the equatorial Americas and western Pacific/east Indian Ocean, show these trends most strongly in February-May when there is convectively-driven wave activity. (3) LMS ozone losses are greatest in the 2nd half of the year (solid lines in Figure 2) when the losses are correlated with an increase in tropopause height (TH) as derived from SHADOZ radiosonde data. ( 4) When the upper FT and LMS are defined by tropopause-relative coordinates, the LMS ozone trend calculated by MLR becomes insignificant, as shown in the dashed lines in Figure 2. Thus, the 20-year decline in tropical LMS ozone reported in recent satellite- and model-based studies does not point to a chemical loss but is rather a signature of a tropopause that has been perturbed by a changing climate. Output based on our regional and monthly averaged FT and LMS ozone trends will be available as a reference for satellite- and model-based analyses.
Offshore sand shoals are a coveted sand source for coastal restoration projects and as sites for wind energy development. Shoals often support unique fish assemblages but their habitat value to sharks is largely unknown due to the high mobility of most species in the open ocean. This study pairs multi-year longline and acoustic telemetry surveys to reveal depth-related and seasonal patterns in a shark community associated with the largest sand shoal complex in east Florida, USA. Monthly longline sampling from 2012–2017 yielded 2,595 sharks from 16 species with Atlantic sharpnose (Rhizoprionodon terraenovae), blacknose (Carcharhinus acronotus), and blacktip (C. limbatus) sharks being the most abundant species. A contemporaneous acoustic telemetry array detected 567 sharks from 16 species (14 in common with longlines) tagged locally and by researchers elsewhere along the US East Coast and Bahamas. PERMANOVA modeling of both datasets indicate that the shark species assemblage differed more across seasons than water depth although both factors were important. Moreover, the shark assemblage detected at an active sand dredge site was similar to that at nearby undisturbed sites. Water temperature, water clarity, and distance from shore were habitat factors that most strongly correlated to community composition. Both sampling approaches documented similar single-species and community trends but longlines underestimated the shark nursery value of the region while telemetry-based community assessments are inherently biased by the number of species under active study. Overall, this study confirms that sharks can be an important component of sand shoal fish communities but suggests that deeper water immediately adjacent to shoals (as opposed to shallow shoal ridges) is more valuable to some species. Potential impacts to these nearby habitats should be considered when planning for sand extraction and offshore wind infrastructure.
NASA's Short‐term Prediction Research and Transition (SPoRT) Center partners with the NWS to provide near realtime data in support of a variety of weather applications, including disasters. SPoRT supports NASA's Applied Sciences Program: Disasters focus area by developing techniques that will aid the disaster monitoring, response, and assessment communities. SPoRT has explored a variety of techniques for utilizing archived and near real‐time NASA satellite data. An increasing number of end‐users - such as the NWS Damage Assessment Toolkit (DAT) - access geospatial data via a Web Mapping Service (WMS). SPoRT has begun developing open‐standard Geographic Information Systems (GIS) data sets via WMS to respond to end‐user needs.
The inability to systematically predict community response to exposure to sonic booms (and other high energy impulsive sounds) is a major impediment to credible analyses of the environmental effects of supersonic flight operations. Efforts to assess community response to high energy impulsive sounds are limited in at least two important ways. First, a paucity of appropriate empirical data makes it difficult to infer a dosage-response relationship by means similar to those used in the case of general transportation noise. Second, it is unclear how well the 'equal energy hypothesis' (the notion that duration, number, and level of individual events are directly interchangeable determinants of annoyance) applies to some forms of impulsive noise exposure. Some of the issues currently under consideration by a CHABA working group addressing these problems are discussed. These include means for applying information gained in controlled exposure studies about different rates of growth of annoyance with impulsive and non-impulsive sound exposure levels, and strategies for developing a dosage-response relationship in a data-poor area.
Summary As functional traits are conserved at different phylogenetic depths, the ability to detect community assembly processes can be conditional on the phylogenetic resolution; yet most previous work quantifying their influence has focused on a single level of phylogenetic resolution. Here, we have studied the ecological assembly of bacterial communities from an Antarctic wetland complex, applying null models across different levels of phylogenetic resolution (i.e. clustering ASVs into OTUs with decreasing sequence identity thresholds). We found that the relative influence of the community assembly processes varies with phylogenetic resolution. More specifically, selection processes seem to impose stronger influence at finer (100% sequence similarity ASV) than at coarser (99%–97% sequence similarity OTUs) resolution. We identified environmental features related with the ecological processes and propose a conceptual model for the bacterial community assembly in this Antarctic ecosystem. Briefly, eco‐evolutionary processes appear to be leading to different but very closely related ASVs in lotic, lentic and terrestrial environments. In all, this study shows that assessing community assembly processes at different phylogenetic resolutions is key to improve our understanding of microbial ecology. More importantly, a failure to detect selection processes at coarser phylogenetic resolution does not imply the absence of such processes at finer resolutions.
We present self-consistent three-dimensional climate simulations of possible habitable states for the newly discovered habitable-zone Earth-sized planet TOI-700 d. We explore a variety of atmospheric compositions, pressures, and rotation states for both ocean-covered and completely desiccated planets in order to assess the planet’s potential for habitability. For all 20 of our simulated cases, we use our climate model outputs to synthesize transmission spectra, combined-light spectra, and integrated broadband phase curves. These climatologically informed observables will help the community assess the technological capabilities necessary for future characterization of this planet—as well as similar transiting planets discovered in the future—and will provide a guide for distinguishing possible climate states if one day we do obtain sensitive spectral observations of a habitable planet around an M star. We find that TOI-700 d is a strong candidate for a habitable world and can potentially maintain temperate surface conditions under a wide variety of atmospheric compositions. Unfortunately, the spectral feature depths from the resulting transmission spectra and the peak flux and variations from our synthesized phase curves for TOI-700 d do not exceed 10 ppm. This will likely prohibit the James Webb Space Telescope from characterizing its atmosphere; however, this motivates the community to invest in future instrumentation that perhaps can one day reveal the true nature of TOI-700 d and to continue to search for similar planets around less distant stars.
We present self-consistent three-dimensional climate simulations of possible habitable states for the newly discovered habitable-zone Earth-sized planet TOI-700 d. We explore a variety of atmospheric compositions, pressures, and rotation states for both ocean-covered and completely desiccated planets in order to assess the planet's potential for habitability. For all 20 of our simulated cases, we use our climate model outputs to synthesize transmission spectra, combined-light spectra, and integrated broadband phase curves. These climatologically informed observables will help the community assess the technological capabilities necessary for future characterization of this planet—as well as similar transiting planets discovered in the future—and will provide a guide for distinguishing possible climate states if one day we do obtain sensitive spectral observations of a habitable planet around an M star. We find that TOI-700 d is a strong candidate for a habitable world and can potentially maintain temperate surface conditions under a wide variety of atmospheric compositions. Unfortunately, the spectral feature depths from the resulting transmission spectra and the peak flux and variations from our synthesized phase curves for TOI-700 d do not exceed 10 ppm. This will likely prohibit the James Webb Space Telescope from characterizing its atmosphere; however, this motivates the community to invest in future instrumentation that perhaps can one day reveal the true nature of TOI-700 d and to continue to search for similar planets around less distant stars.
Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from water filter collected across 8 locations along the East River Watershed, CO, and 1 nearby groundwater well. The purpose was to look for connectivity and similarities across the network and to see the impact of the groundwater. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed community composition and strain similarities between the sites and we also compared it to previous metagenomic studies within the watershed looking at floodplain (Matheus Carnevali et al. 2021) and hillslope (Lavy et al. 2019) microbiomes. Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from filters across 8 locations during August 2020 and July 2021. This resulted in 32 samples. The groundwater sample was sequenced at UC Berkley's QB3. The other 31 samples were sequenced at University of Maryland. Metagenomes were assembled using four autobinners and the best bins were selected using dasTool. The genomes were dereplicated at 95% with dRep and the subset of winning genomes were manually curated based on visual inspection of taxonomic profile, GC content, coverage, and a set of 51 bacterial single copy genes (BSCG), and 38 archaeal signal copy genes (ASCG). The dataset includes a zip file of 311 genomes (HZ_River_SW_MAGS_Dereplicated_95.zip). The dataset additionally includes a zipped file of ribosomal protein small subunit 3 (rpS3) proteins from the hyporheic zone and river data (rpS3_Proteins_HZ_River.zip), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a location metadata file (locations.csv). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.
Sphagnum (peatmoss) comprises a moss (Bryophyta) clade with approximately 300-500 species. The genus has unparalleled ecological importance because Sphagnum-dominated peatlands store almost a third of the terrestrial carbon pool and peatmosses engineer the formation and microtopography of peatlands. Genomic resources for Sphagnum are being actively expanded, but many aspects of their biology are still poorly known. Among these are the degree to which Sphagnum species reproduce asexually, and the relative frequencies of male and female gametophytes in these haploid-dominant plants. Here, we assess clonality and gametophyte sex ratios and test hypotheses about the local-scale distribution of clones and sexes in four North American species of the S. magellanicum complex. These four species are difficult to distinguish morphologically and are very closely related. We also assess microbial communities associated with Sphagnum host plant clones and sexes at two sites. 405 samples of the four species, representing 57 populations, were subjected to RADseq. Analyses of population structure and clonality based on the molecular data utilized both phylogenetic and phenetic approaches. Multi-locus genotypes (genets) were identified using the RADseq data. Sexes of sampled ramets were determined using a molecular approach that utilized coverage of loci on the sex chromosomes after the method was validated using a sample of plants that expressed sex phenotypically. Sex ratios were estimated for each species, and populations within species. Differences in fitness between genets was estimated as the numbers of ramets each genet comprised. Degree of clonality (numbers of genets/numbers of ramets [samples]) within species, among sites, and between gametophyte sexes were estimated. Sex ratios were estimated for each species, and populations within species. Sphagnum-associated microbial communities were assessed at two sites in relation to Sphagnum clonality and sex. All four species appear to engage in a mixture of sexual and asexual (clonal) reproduction. A single ramet represents most genets but 2-8 ramets were detected for some genets. Only one genet is represented by ramets in multiple populations; all other genets are restricted to a single population. Within populations ramets of individual genets are spatially clustered, suggesting limited dispersal even within peatlands. Sex ratios are male-biased in S. diabolicum but female-biased in the other three species, although significantly so only in S. divinum. Neither species nor males/females differ in levels of clonal propagation. At St. Regis Lake (NY) and Franklin Bog (VT), microbial community composition is strongly differentiated between the sites, but differences between species, genets, and sexes were not detected. Within S. divinum, however, female gametophytes harbored 2-3 times the number oi of microbial taxa as males. These four Sphagnum species all exhibit a similar reproductive patterns that result from a mixture of sexual and asexual reproduction. The spatial patterns of clonally replicated ramets of genets suggest that these species fall between the so-called phalanx patterns where genets abut one another but do not extensively mix, because of limited ramet fragmentation, and the guerrilla patterns where extensive genet fragmentation and dispersal results in greater mixing of different genets. Although sex ratios in bryophytes are most often female-biased, both male and female biases occur in this complex of closely related species. The association of far greater microbial diversity for female gametophytes in S. divinum, which has a female-biased sex ratio, suggests additional research to determine if levels of microbial diversity are consistently correlated with differing patterns of sex ratio biases.
Abstract Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.
Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO 2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO 2 emissions. By 2150, CO 2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO 2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO 2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66% for the present day to roughly 68% to 85% by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (~5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5°C warming on the other.