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At least 91 records · Page 5

Livability Assessment of Urban Communities considering the Preferences of Different Age Groups

Livability is one of the major guiding principles for urban planning and policymaking, of which the definition and evaluation have become the crucial research topic. As the progress in socioeconomic development accelerates, the microscale living conditions require more urgent attention. However, few researchers have addressed the assessment of urban livability at a finer spatial scale such as the community scale. Thus, this article aims to evaluate the urban environmental quality at the community level given the residential community as the basic unit of urban living areas. We select eighteen objective indicators from five dimensions to establish an objective indicator system. Taking the preferences of different age groups into account, a comprehensive evaluation framework for the livability of communities combining both subjective perceptions and objective indicator is constructed. Then, it is applied to evaluate the livability of 1,394 residential communities in Ningbo City. There are three significant results from the study. First, different age groups have diverse preferences of demands to the livability of an urban community. The indicators they valued most concentrated in the following two dimensions: the convenience of transportation and the completeness of supporting facilities. Second, there exists significant heterogeneity in the livability of communities among districts. Third, the livability of communities shows a decreasing spatial pattern from the city center to the surroundings. These empirical results can be advantageous to urban planning departments and other relevant stakeholders.

Liang, Xiaojin↗

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗

Efficacy of Hair Total Mercury Content as a Biomarker of Methylmercury Exposure to Communities in the Area of Artisanal and Small-Scale Gold Mining in Madre de Dios, Peru

Total mercury content (THg) in hair is an accepted biomarker for chronic dietary methylmercury (MeHg) exposure. In artisanal and small-scale gold mining (ASGM) communities, the validity of this biomarker is questioned because of the potential for contamination from inorganic mercury. As mining communities may have both inorganic and organic mercury exposures, the efficacy of the hair-THg biomarker needs to be evaluated, particularly as nations begin population exposure assessments under their commitments to the Minamata Convention. We sought to validate the efficacy of hair THg for public health monitoring of MeHg exposures for populations living in ASGM communities. We quantified both THg and MeHg contents in hair from a representative subset of participants (N = 287) in a large, population-level mercury exposure assessment in the ASGM region in Madre de Dios (MDD), Peru. We compared population MeHg-THg correlations and %MeHg values with demographic variables including community location, sex, occupation, and nativity. We observed that hair MeHg-THg correlations were high (r > 0.7) for all communities, regardless of location or nativity. Specifically, for individuals within ASGM communities, 81% (121 of 150 total) had hair THg predominantly in the form of MeHg (i.e., >66% of THg) and reflective of dietary exposure to mercury. Furthermore, for individuals with hair THg exceeding the U.S. EPA threshold (1.0 μg/g), 88 out of 106 (83%) had MeHg as the predominant form. As a result, had urine THg solely been used for mercury exposure monitoring, approximately 59% of the ASGM population would have been misclassified as having low mercury exposure. Our results support the use of hair THg for monitoring of MeHg exposure of populations in ASGM settings where alternative biomarkers of MeHg exposure are not feasible.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Extreme-scale workflows: A perspective from the JLESC international community

The Joint Laboratory for Extreme-Scale Computing (JLESC) focuses on software challenges in high-performance computing systems to meet the needs of today’s science campaigns, which often require large resources, consist of multiple tasks, and generate vast amounts of data. In this context, extreme-scale workflows have been the key factor in enabling scientific discoveries by helping scientists automate the dependencies and data exchanges between workflow tasks, instead of managing those manually. Here, in this paper, we present representative extreme-scale workflows and feature workflow systems developed by JLESC participating institutions. We present lessons learned while developing these tools, alongside with the open challenges and future research directions in the field of extreme-scale workflows.

97 MATHEMATICS AND COMPUTING↗

Functional capacities of microbial communities to carry out large scale geochemical processes are maintained during ex situ anaerobic incubation

Mechanisms controlling CO 2 and CH 4 production in wetlands are central to understanding carbon cycling and greenhouse gas exchange. However, the volatility of these respiration products complicates quantifying their rates of production in the field. Attempts to circumvent the challenges through closed system incubations, from which gases cannot escape, have been used to investigate bulk in situ geochemistry. Efforts towards mapping mechanistic linkages between geochemistry and microbiology have raised concern regarding sampling and incubation-induced perturbations. Microorganisms are impacted by oxygen exposure, increased temperatures and accumulation of metabolic products during handling, storage, and incubation. We probed the extent of these perturbations, and their influence on incubation results, using high-resolution geochemical and microbial gene-based community profiling of anaerobically incubated material from three wetland habitats across a permafrost peatland. We compared the original field samples to the material anaerobically incubated over 50 days. Bulk geochemistry and phylum-level microbiota in incubations largely reflected field observations, but divergence between field and incubations occurred in both geochemistry and lineage-level microbial composition when examined at closer resolution. Despite the changes in representative lineages over time, inferred metabolic function with regards to carbon cycling largely reproduced field results suggesting functional consistency. Habitat differences among the source materials remained the largest driver of variation in geochemical and microbial differences among the samples in both incubations and field results. While incubations may have limited usefulness for identifying specific mechanisms, they remain a viable tool for probing bulk-scale questions related to anaerobic C cycling, including CO 2 and CH 4 dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of Microbial-Mineral Interactions on Organic Carbon Stabilization in a Ponderosa Pine Root Zone: A Micro-Scale Approach

Soil microbial communities affect the formation of micro-scale mineral-associated organic matter (MAOM) where complex processes, including adhesion, aggregate formation, microbial mineral weathering and soil organic matter stabilization occur in a narrow zone of large biogeochemical gradients. Here we designed a field study to examine carbon stabilization mechanisms by using in-growth mesh bags containing biotite that were placed in a ponderosa pine root zone for 6 months and compared to the surrounding bulk soil. We sought to determine the composition of the microbial community in the mesh bags compared to the surrounding soils, analyze the direct interactions between microbes and biotite, and finally identify the nature of the newly formed MAOM within the mesh-bags. Our results revealed that minerals in the mesh bags were colonized by a microbial community that produced organic matter in situ. The 16S rRNA gene sequencing and ITS2 region characterization showed phylogenetic similarity between the mesh bag and bulk soil archaea/bacteria and fungi microbiomes, with significant differences in alpha- and beta-diversity and species abundances. Organic matter pools in the mesh bags, analyzed by Fourier transform ion cyclotron resonance mass spectrometry, contained protein- (peptides) and lipid-like compounds while the bulk soil OM was comprised of lignin-like and carboxyl-rich alicyclic molecules. These results support that the newly formed biotite associated organic compounds have a microbial signature in the mesh bags. High-resolution electron microscopy documented strongly adhered organic compounds to biotite surfaces, formation of microaggregates, elemental uptake at the microbe (organic matter)-mineral interface, and distortion of biotite layers. Overall, this study shows the direct and indirect involvement of soil microbial communities from the root zone of ponderosa pine in the formation of MAOM, soil organic carbon stabilization, microaggregation, and mineral weathering at micro- and nano-scales.

58 GEOSCIENCES↗

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

Rapid deployment of residential photovoltaic (PV) systems helps decarbonize our electricity supplies, but under certain circumstances, high-penetration PV may pose challenges to the electrical distribution grid. In a project funded by the U.S. Department of Energy's Solar Energy Technologies Office and Building Technologies Office, the National Renewable Energy Laboratory and its partners studied how flexible building loads and battery storage, when coordinated at home-level and community-level scales, can be used to address those challenges and enhance grid resilience. In this webinar, we will discuss the methodology, simulation and field pilot results, insights from partners, and lessons learned from the project.

artificial intelligence↗

Hydraulic redistribution supplies a major water subsidy and improves water status of understory species in a longleaf pine ecosystem

Hydraulic redistribution (HR) is a common phenomenon in water-limited ecosystems; however, it remains unclear how the volume of water transported via HR compares to other components of the hydrologic budget and how HR influences water availability for understory plant communities. In this study, we investigate the absolute and relative magnitude of HR on a forest water budget and identify potential impacts of this water subsidy to understory plant communities. We scaled tree-level estimates of transpiration and HR of three common tree species naturally occurring in a longleaf pine woodland with plot-level measurements of basal area to determine their magnitude at the stand scale. We trenched plots containing understory vegetation but devoid of mature trees and their connected roots to exclude HR subsidies to understory plant species. We analysed soil water isotopes and assessed leaf water potential (Ψ L ) in trenched and control plots to determine if HR results in mixing of water among soil strata and improves understory plant moisture status. Water inputs from HR were equivalent to >30% of total rainfall for the site during the observation period and ~40% of total tree water uptake, depending on species. A stable isotope mixing model confirmed that soil water within HR-exposed plots was more similar to groundwater, whereas soil water within trenched plots was more similar to precipitation. Exclusion of HR via trenching decreased soil moisture and pre-dawn Ψ L for all understory species. These three lines of evidence suggest that HR from overstory trees redistributes a sizable portion of water from deeper to shallower soil profiles and that this water subsidy enhances understory plant water status.

54 ENVIRONMENTAL SCIENCES↗

Ice and Supercooled Liquid Water Distributions over the Southern Ocean based on In Situ Observations and Climate Model Simulations

Three climate models are evaluated using in situ airborne observations from the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) campaign. The evaluation targets cloud phases, microphysical properties, thermodynamic conditions, and aerosol indirect effects from –40°C to 0°C. Compared with 580-s averaged observations (i.e., 100 km horizontal scale), the Community Atmosphere Model version 6 (CAM6) shows the most similar result for cloud phase frequency distribution and allows more liquid-containing clouds below –10°C compared with its predecessor—CAM5. The Energy Exascale Earth System Model (E3SM) underestimates (overestimates) ice phase frequencies below (above) –20°C. CAM6 and E3SM show liquid and ice water contents (i.e., LWC and IWC) similar to observations from –25°C to 0°C, but higher LWC and lower IWC than observations at lower temperatures. Simulated in-cloud RH shows higher minimum values than observations, possibly restricting ice growth during sedimentation. As number concentrations of aerosols larger than 500 nm (Na 500 ) increase, observations show increases of LWC, IWC, liquid, and ice number concentrations (N liq , N ice ). Number concentrations of aerosols larger than 100 nm (Na 100 ) only show positive correlations with LWC and N liq . From –20°C to 0°C, higher aerosol number concentrations are correlated with lower glaciation ratio and higher cloud fraction. From –40°C to –20°C, large aerosols show positive correlations with glaciation ratio. CAM6 shows small increases of LWC and N liq with Na 500 and Na 100 . E3SM shows small increases of N ice with Na 500 . Altogether, CAM6 and E3SM underestimate aerosol indirect effects on ice crystals and supercooled liquid droplets over the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗

Harmonic analysis of discrete tracers of large-scale structure

It is commonplace in cosmology to analyze fields projected onto the celestial sphere, and in particular density fields that are defined by a set of points e.g. galaxies. When performing an harmonic-space analysis of such data (e.g. an angular power spectrum) using a pixelized map one has to deal with aliasing of small-scale power and pixel window functions. We compare and contrast the approaches to this problem taken in the cosmic microwave background and large-scale structure communities, and advocate for a direct approach that avoids pixelization. We describe a method for performing a pseudo-spectrum analysis of a galaxy data set and show that it can be implemented efficiently using well-known algorithms for special functions that are suited to acceleration by graphics processing units (GPUs). The method returns the same spectra as the more traditional map-based approach if in the latter the number of pixels is taken to be sufficiently large and the mask is well sampled. The method is readily generalizable to cross-spectra and higher-order functions. It also provides a convenient route for distributing the information in a galaxy catalog directly in harmonic space, as a complement to releasing the configuration-space positions and weights, and a route to spectral apodization. Finally, we make public a code enabling the application of our method to existing and upcoming datasets.

79 ASTRONOMY AND ASTROPHYSICS↗

Deep unsupervised learning using spike-timing-dependent plasticity

Abstract Spike-timing-dependent plasticity (STDP) is an unsupervised learning mechanism for spiking neural networks that has received significant attention from the neuromorphic hardware community. However, scaling such local learning techniques to deeper networks and large-scale tasks has remained elusive. In this work, we investigate a Deep-STDP framework where a rate-based convolutional network, that can be deployed in a neuromorphic setting, is trained in tandem with pseudo-labels generated by the STDP clustering process on the network outputs. We achieve 24.56% higher accuracy and 3.5 × faster convergence speed at iso-accuracy on a 10-class subset of the Tiny ImageNet dataset in contrast to a k -means clustering approach.

Lu, Sen↗

A global comparison of surface and subsurface microbiomes reveals large-scale biodiversity gradients, and a marine-terrestrial divide

Subsurface environments are among Earth’s largest habitats for microbial life. Yet, until recently, we lacked adequate data to accurately differentiate between globally distributed marine and terrestrial surface and subsurface microbiomes. Here, we analyzed 478 archaeal and 964 bacterial metabarcoding datasets and 147 metagenomes from diverse and widely distributed environments. Microbial diversity is similar in marine and terrestrial microbiomes at local to global scales. However, community composition greatly differs between sea and land, corroborating a phylogenetic divide that mirrors patterns in plant and animal diversity. In contrast, community composition overlaps between surface to subsurface environments supporting a diversity continuum rather than a discrete subsurface biosphere. Differences in microbial life thus seem greater between land and sea than between surface and subsurface. Diversity of terrestrial microbiomes decreases with depth, while marine subsurface diversity and phylogenetic distance to cultured isolates rivals or exceeds that of surface environments. We identify distinct microbial community compositions but similar microbial diversity for Earth’s subsurface and surface environments.

54 ENVIRONMENTAL SCIENCES↗

Distribution Substation Planning Toolkit (dsp-toolkit) v1.0

The Distribution Substation Planning Toolkit (DSP Toolkit) is a software suite designed to streamline the planning and optimization of distribution substations. This toolkit offers a comprehensive set of tools and APIs for data curation, short-term electric load forecasting, and weather-sensitive load adjustment, making it an essential resource for utility companies, engineers, and researchers. Features • Data Preprocessing and Curation: Efficiently manage and preprocess large datasets to ensure high-quality input for analysis. • Short-Term Load Forecasting: Utilize data-driven models to predict short-term electric loads accurately. • Weather-Sensitive Modeling: Automatically adjust load forecasts based on weather data to predict future peak demands more precisely. Uses The DSP Toolkit is ideal for planning and optimizing distribution substations, providing a user-friendly interface and comprehensive documentation. It is suitable for both novice and experienced users, facilitating efficient and accurate planning processes. Advantages • Efficiency: Automates complex planning tasks, reducing manual effort and minimizing errors. • Scalability: Handles large datasets and complex models, making it suitable for large-scale projects. • Community and Support: Open-source with active community contributions, ensuring continuous improvement and support. • Extensibility: Easily extendable with custom modules and plugins, allowing users to tailor the toolkit to their specific needs. The DSP Toolkit stands out by offering a robust, flexible, and user-friendly solution for distribution substation planning. Public Abstract

Li, Han [Lawrence Berkeley National Laboratory (LB↗

An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Geothermal Behavior with Example Simulations on The Treasure Island and UC Berkeley Campus

This submission contains the source code of the Hydrothermal Finite Element Simulator used for the Treasure Island and UC Berkeley campus geothermal simulation. It contains a report that summarizes the development and validation of this Hydrothermal Finite Element Simulator, with a case study on Treasure Island site. It also contains a report that investigates the feasibility of upgrading the existing campus energy delivery system at UC Berkeley to a fifth-generation district heating and cooling system that includes geothermal heat/cold storage.

15 GEOTHERMAL ENERGY↗

Multiscale Aerosol Modeling Across Space and Composition (Final Report)

The objective of this project was to harness the capabilities of our unique particle-resolved aerosol model PartMC as an integrating tool between models and measurements across scales. This particle-resolved model explicitly resolves aerosol aging processes that must be approximated in large-scale models, making it ideal for quantifying structural uncertainty and rigorously deriving simplified parameterizations (“coarse graining”) to be used in large-scale models. It also directly connects with laboratory and field measurements at both particle and bulk scales. The significant accomplishments of this project are as follows: 1. Advancing the state of the art in particle-resolved modeling; 2. Connecting modeling with ASR/ARM measurements; 3. Bridging from the process level to aerosol impacts on the global scale; 4. Community engagement through leading and participating in ASR program activities and publishing a review paper on aerosol mixing state that synthesizes experimental and modeling perspectives.

58 GEOSCIENCES↗

DC Solar for All: Implementation Plan to Scale Low- and Moderate- Income Community Solar + Storage Resilience Hubs in the District of Columbia

This implementation plan discusses the District of Columbia's strategy to combine low-income community solar projects with resilience technologies. Through the technical and financial support offered by the Inclusive Shared Solar Initiative and building on extensive stakeholder engagement in LMI neighborhoods around the District, the District of Columbia team expects to reduce energy burdens for LMI residents, address barriers to and streamline SfA program enrollment, and support the development of innovative benefit delivery models, including a community solar-supported climate resilience center.

14 SOLAR ENERGY↗