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At least 883 records · Page 49

Long-term increase in atmospheric stagnant conditions over northeast Asia and the role of greenhouse gases-driven warming

We report the recent trend in the air quality degradation of urban South Korea prompted the authors to examine the long-term changes in the near-surface wind speed and its link with the lower atmospheric circulation, using modern reanalysis datasets. Analyses based on JRA-55 data show a negative correlation between near-surface wind speed and static stability over the Yellow Sea and the western part of South Korea. Near-surface wind speed shows a clear declining trend accompanied by increased static stability, while its negative correlation strengthened recently. Further investigations using CMIP5 single-forcing experiments suggest that global warming because of anthropogenic greenhouse gases probably increased static stability in the lower troposphere, implying further atmospheric stagnant conditions in the future.

54 ENVIRONMENTAL SCIENCES↗

A worldwide aerosol phenomenology: Elemental and organic carbon in PM 2.5 and PM 10

Elemental carbon (EC), organic carbon (OC), and particulate matter (PM) concentrations in the inhalable (PM 10 ) and fine (PM 2.5 ) size fractions are measured worldwide, albeit with different analytical methods. These measurements from many researchers were collected and analyzed for Africa, America, Asia, and Europe for 2012–2019. EC/PM, OC/PM, and OC/EC ratios were examined based on region, site type, and season to infer potential sources and impacts. These analyses demonstrate that carbonaceous materials are important PM constituents throughout the world. Mean EC/PM ratios were lowest in PM 10 in Sahelian Africa and Europe (∼0.01), highest (>0.07) in PM 2.5 at urban sites in North America, South America, and Japan. Mean OC/PM ratios were lowest in PM 10 in the Sahel (∼0.06) and in PM 2.5 in China and Thailand (0.10), and highest in central and eastern Europe (∼0.3) and North America (∼0.4). OC/EC ratios were elevated in western and northern Europe, and at regional background sites in North America. EC/PM increased with PM 10 in Thailand, while OC/PM increased with higher PM mass in Thailand, India, and North America, highlighting the specific contribution of carbonaceous aerosols to PM pollution in these regions. At European and North American background sites, OC/EC ratios increased with PM mass. Higher OC/EC ratios in dry periods indicate influence of wildfires, prescribed burns, and secondary aerosol formation. Elevated wintertime EC/PM ratios coincide with residential heating in temperate climate zones.

54 ENVIRONMENTAL SCIENCES↗

A heuristic tool to assess regional impacts of renewable energy infrastructure on conservation areas

Wind and hydropower are important renewable components of national energy portfolios, but their infrastructure negatively affects biodiversity. Regional development requires identification of scenarios that minimize the cumulative impacts of multiple facilities. We introduce the cumulative impact plot (CIP) to quantify cumulative impacts of renewable energy development within a region. Summed impacts of facilities are plotted as a function of the number of facilities, with facilities ranked by increasing (the best-case scenario) or decreasing (worst-case scenario) individual impact. These curves represent lower and upper bounds to which alternative development scenarios (e.g., facilities ranked by generating capacity) can be compared. We used CIPs to assess overlap of potential wind and hydropower facilities with two types of conservation area in the United States: (1) federally protected lands and (2) critical habitats of federally threatened and endangered species. Here, we evaluated two alternative scenarios: facilities ranked by (A) decreasing generating capacity and (B) increasing distance from urban centers. Differences between the best-case and worst-case scenarios were large, thus revealing opportunities to develop facilities with limited impact on conservation areas. Alternative scenarios maximizing energy density generally resulted in conservation area overlap intermediate to best-case and worst-case scenarios. CIPs can also identify the proportion of wind versus hydropower favored under alternative scenarios. Build-out scenarios aimed at minimizing conservation area overlap favor hydropower, whereas alternative scenarios favor wind power. We conclude that CIPs can (1) complement—but should not replace—project-level environmental impact assessment, (2) integrate strategic, cumulative, and scenario-based assessments, and (3) harness rapidly growing geospatial data.

54 ENVIRONMENTAL SCIENCES↗

Using high-throughput amplicon sequencing to determine diet of generalist lady beetles in agricultural landscapes

Determining feeding relationships is central to understanding biological control potential in the field. However, methods to differentiate actual (or realized) feeding relationships from potential feeding relationships is lacking especially for small, generalist predators such as lady beetles. In this study, we used DNA metabarcoding approaches to characterize actual feeding relationships of lady beetles (Coccinellidae) in the field and validated our methods with a lab study. We first asked whether high-throughput amplicon sequencing (HTS) can characterize diets of lady beetles ranging from monotypic diets to diverse diet mixtures in the lab. We then examined whether diet composition and breadth of lady beetles collected from different habitat types in southern WI varied between monocultures of soybean and corn, diverse tallgrass prairie, and urban habitats. Lastly, we asked whether different body or tissue types (partial-body versus whole-body specimens) would change the likelihood of prey detection for both studies. In our controlled lab study, we found that HTS can accurately assess diet composition and diet breadth for lady beetle populations, but at the individual level, HTS has limitation for individuals feeding on more than three species of prey at any given time. In our field study, we documented lower prey richness and diet breadth in corn compared to soybean and grassland, and greater prey DNA in regurgitants than in whole-body specimens. Finally, we found that reduced diet diversity was associated with an increased prevalence of intraguild predation, but that habitat and prey diversity are not necessarily correlated. The prey detection rates (proportion of specimens with prey DNA) in our study were comparable to other studies (55% in the lab study, 33% in field study) and varied with diet composition and habitat type. Furthermore, the relatively low detection rates suggest that many consumer individuals would need to be assayed to fully assess diet diversity, especially in diverse systems.

59 BASIC BIOLOGICAL SCIENCES↗

Biomass supply chain equipment for renewable fuels production: A review

The production of renewable fuels is a critical component of global strategies to reduce greenhouse gas (GHG) emissions. Moreover, the collection of raw materials for its production can provide added benefits such as reduction of wildfire risk, additional income for farmers, and decreased disposal costs. Although there is substantial literature on design and modeling of supply chains, the authors were unable to find a single reference with the information needed for the selection and cost estimation of each type of equipment involved in the supply chain. Therefore, the goal of this research is to gather information necessary for the construction and utilization of models that might drive the identification of a feasible supply chain to produce renewable fuels at a commercial scale. The primary objectives are to 1) understand the supply chain of critical feedstocks for renewable fuels production; 2) identify the equipment commercially available for collection and adequation of feedstock; and 3) consolidate information regarding equipment cost, energy consumption, and efficiency, as well as feedstock storage and transportation systems. This paper provides a compilation for five feedstock types studied for sustainable aviation fuel production: 1) agricultural residues and grasses, 2) forest residues, 3) urban wood waste, 4) oilseeds, 5) fats, oils & greases. All the technologies involved from the field to the gate of the preprocessing or conversion unit were reviewed. The information on fats, oils & greases supply chains and equipment purposely designed for forest thinning and pruning was very limited.

: Feedstock, Collection and Adequation, Renewable ↗

Opportunities in multiscale modeling of mosquito-borne flaviviruses

Mosquito-borne flaviviruses, such as Zika, dengue, West Nile, and yellow fever virus, represent a growing public health concern due to their widespread distribution and the severe diseases they cause. These viruses are difficult to control as climate change and urbanization help mosquitoes expand into new areas, increasing the risk of outbreaks. Mathematical models play a key role in understanding their spread, providing insights at every level—from how the virus multiplies inside cells to how it circulates through entire populations. This review examines various approaches used in modeling arboviruses, including microscale models that focus on cellular and molecular dynamics, mesoscale models that address within-host processes, and macroscale models that capture population-level transmission. We briefly summarize the methodology used for models at each scale, which primarily consists of sets of differential equations with parameters that represent physical rates of change for different subprocesses. We particularly highlight how temperature affects virus transmission, which is key to understanding the impact of climate change. We also show how multiscale models can connect viral replication, immune response, and the spread of infection at a larger scale. This is essential for developing better vaccines and treatments, evaluating disease control measures, predicting the impact of climate change, and improving public health responses to outbreaks.

60 APPLIED LIFE SCIENCES↗

Energy efficiency and thermal resilience analysis for row houses using representative building energy models

Row houses, a prevalent medium-density urban archetype, were popularized during industrial era to accommodate the working class in the U.S. cities. Today, many of these structures are deteriorating, exacerbating the energy cost for residents with limited economic resources. Moreover, many households that lack Air Conditioning (AC) are vulnerable to extreme summer heat, an issue expected to worsen in the future. Energy-efficient retrofits can help mitigate these challenges. However, current literature provides limited insight into how existing building energy codes impact the energy efficiency and thermal resilience of row houses in current and future weather scenarios. This study provides a detailed method to address this gap by employing calibrated representative energy models of row houses as a baseline, and evaluating the annual energy savings and summertime thermal safety improvements from code compliant retrofits under current and future typical weather conditions. Using Baltimore City as a case study, results show that under current weather, retrofitting row houses yields significant energy savings along with notable thermal resilience improvements. The end unit row house realizes higher energy savings, whereas the interior unit experiences greater thermal resilience improvement after retrofitting. In future, retrofitted row houses can still save energy, but residents will face numerous hours of fatal indoor temperatures without AC in summer. Additionally, findings reveal stark zone-wise variations in thermal safety, and elevated humidity risks in certain zones post-retrofit, emphasizing the need for zonal retrofit strategies and better natural ventilation strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Highly efficient, rapid, and concurrent removal of toxic heavy metals by the novel 2D hybrid LDH–[Sn 2 S 6 ]

According to a United Nations report, by 2050 nearly six billion people worldwide will suffer from clean water scarcity. This is mostly because of the exponential proliferation of world population, urbanization, industrialization, and water pollution. Heavy metals are common water pollutants that can pose grave public health consequences. Existing water purification systems are lack of materials that have the potential for quick, simultaneous, efficient, and cost-efficient removal of numerous toxic metals from wastewater. Here, in this work, we report the design and synthesis of an economically viable Layered Double Hydroxides - Stannic Sulfide, LDH–[Sn 2 S 6 ] that exhibits a rapid, efficient, selective, and concurrent removal of Cu 2+ , Ag + , Cd 2+ , Pb 2+ , and Hg 2+ from parts per million (ppm) level to below 5 parts per billion (ppb) satisfying World Health Organization’s (WHO) safe drinking water limit. Moreover, LDH–[Sn 2 S 6 ] shows exceptionally high removal efficiencies of the above metals in acidic, neutral, and basic conditions. LDH–[Sn 2 S 6 ] also demonstrates enormous sorption capacities of 378, 978, 332, 579, and 666 mg/g for Cu 2+ , Ag + , Cd 2+ , Pb 2+ , and Hg 2+ , respectively. Remarkably, LDH–[Sn 2 S 6 ] displays extraordinary tolerance to the concentrations of Na + , Ca 2+ , Mg 2+ , Cl - , CO 3 2– , NO 3 – ,and SO 4 2- , and other constituents in tap and river water, it efficiently sequestrates Cu 2+ , Ag + , Cd 2+ , Pb 2+ , and Hg 2+ from ppm to safe drinking water levels in minutes. LDH–[Sn 2 S 6 ] shows pseudo-second-order sorption kinetics suggesting chemisorption adsorption mechanism involving M–S bonding. Altogether, the regeneratable LDH–[Sn 2 S 6 ] becomes an exceptional material that shows ultrahigh removal, unprecedented selectivity, rapid adsorption kinetics, wide pH stability, and a massive adsorption capacity. The integration of these features places LDH–[Sn 2 S 6 ] at the top of all adsorbents known to date and thus could be used for wastewater purifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Agent-based simulation and child protection systems: Rationale, implementation, and verification

Simulation models are an important tool used in health care and other disciplines to support operational research and decision-making. In the child protection literature, simulation models are an under-utilized source of research evidence. Here, in this paper, we describe the rationale for and the development of an agent-based simulation of a child protection system in the US. Using the investigation, prevention service, and placement histories of 600,000 children served in an urban child welfare system, we walk the reader through the development of a prototype known as OSPEDALE. The governing equations built into OSPEDALE probabilistically simulate the onset of investigations. Then, drawing from empirical survival distributions, the governing equations trace the probability of subsequent interactions with the system (recurrence of maltreatment, service referrals, and placement) conditional on the characteristics of children, their assessed risk level, and prior child protection system involvement. As an initial test of OSPEDALE's utility, we compare empirical admission counts with counts generated from OSPEDALE. Though the verification step is admittedly simple, the comparison shows that OSPEDALE replicates the empirical count of new admissions closely enough to justify further investment in OSPEDALE. Management of public child protection systems is increasingly research evidence-dependent. The emphasis on research evidence as a decision-support tool has elevated evidence acquired through randomized clinical trials. Though important, the evidence from clinical trials represents only one type of research evidence. Properly specified, simulation models are another source of evidence with real-world relevance.

60 APPLIED LIFE SCIENCES↗

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics

Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.

54 ENVIRONMENTAL SCIENCES↗

Areal interpolation of population projections consistent with different SSPs from 1-km resolution to block level based on USA Structures dataset

Population data are normally collected at various census administrative levels, and areal interpolation of population is often required to transform population to the desired spatial resolution. Building footprint datasets, such as Microsoft building footprints, have proven to be useful in estimating population distribution and can therefore be used for areal interpolation of population. In addition to Microsoft building footprints, the recently released USA Structures dataset provides additional information such as building type and building height for some regions, which may provide valuable information for a better depiction of population distribution and improved population areal interpolation accuracy. In this study, we have conducted areal interpolation of population projections consistent with three different Shared Socioeconomic Pathways (SSP2, SSP3, and SSP5) from 1-km grid cells to block level in Washington state for every ten years from 2020 to 2040 based on USA Structures. We assessed USA Structures-based population downscaling accuracy using U.S. decennial survey data in 2020 under three different downscaling schemes, including population downscaling from census tracts to block groups, from census tracts to blocks, and from block groups to blocks. The resulting accuracies were compared with those based on Microsoft building footprints. The comparison showed that USA Structures achieved higher accuracies across different population density regions and areas with different urbanization extent within our study area.

99 GENERAL AND MISCELLANEOUS↗

Adaptive continuity-preserving simplification of street networks

Street network data is widely used to study human-based activities and urban structure. Often, these data are geared towards transportation applications, which require highly granular, directed graphs that capture the complex relationships of potential traffic patterns. While this level of network detail is critical for certain fine-grained mobility models, it represents a hindrance for studies concerned with the morphology of the street network. For the latter case, street network simplification — the process of converting a highly granular input network into its most simple morphological form — is a necessary, but highly tedious preprocessing step, especially when conducted manually. In this manuscript, we develop and present a novel adaptive algorithm for simplifying street networks that is both fully automated and able to mimic results obtained through a manual simplification routine. The algorithm — available in the neatnet Python package — outperforms current state-of-the-art procedures when comparing those methods to manually, human-simplified data, while preserving network continuity.

Python↗

Investigation of grid-based vorticity-velocity large eddy simulation off-body solvers for application to overset CFD

Accurately predicting unsteady wakes and vortex-dominated flows is essential to a wide range of engineering applications, including aircraft, rotorcraft, shipboard operations, bio-inspired unsteady flight and propulsion, wind turbines, and urban flows. While current CFD software can model the complete flow field and wake system, the computational costs incurred in high Reynolds number unsteady turbulent flow simulations often remain prohibitive for routine engineering use, particularly for applications involving moving components. Prior work has demonstrated that by adopting a vorticity-velocity formulation in a grid-based off-body flow solver (VorTran-M and VorTran-M2) one can lower these costs by several orders of magnitude when compared to conventional approaches. This paper describes the extensions made to VorTran-M2 to support turbulent flows, and associated benchmarking activity to assess its performance for problems involving strong stretching and diffusion processes, whose competing contributions to the vorticity field are core drivers of turbulent flow evolution. Predictions are presented for: (i) the Kida-Pelz problem whose inviscid form is of mathematical interest due to its apparent formation of singular flow in finite time; and (ii) the Taylor Green vortex arrangement, which has been extensively studied as a fundamental simulation challenge in the turbulent modeling community. Here, the results are used to evaluate the overall predictive ability and performance of two sub-grid scale models incorporated into VorTran-M2. Results indicate that the computational cost savings seen previously for inviscid and convection dominated problems extend to turbulent flow simulations supporting the viability of VorTran-M2 as a low cost means for accurately modeling the far-field and background flow, particularly when long duration vorticity evolution is of interest.

42 ENGINEERING↗

Computational and experimental study of different brines in temperature swing solvent extraction desalination with amine solvents

Rapid global urbanization and high-salinity wastewater disposal from industrial activities have exerted significant pressure on water resources. Over the past few years, temperature swing solvent extraction (TSSE) has been identified as a promising technique to desalinate hypersaline brines. Despite its potential, the TSSE desalination literature has been mainly based on empirical insights, and the limited molecular simulation studies have primarily focused on NaCl brines. Herein, we use molecular dynamics (MD) simulations to study the TSSE desalination of four different brines, namely, KCl, KBr, NaCl, and NaBr using diisopropylamine as the solvent. Based on both bulk and interfacial brine-diisopropylamine MD results, here we investigate the qualitative and quantitative performance of the simulations by benchmarking these results against our experimental evaluations of these same systems. MD results provide satisfactory qualitative agreement with the experimental data of water solubilization in the organic phase and amine solubilization in the aqueous phase for the KBr, KCl, and NaBr brines. Also, the molecular mechanism of solvation of ionic species by water molecules over diisopropylamine suggested by the MD simulations is in agreement with our experimental data. However, larger qualitative and quantitative deviations were observed for the NaCl brines, and this is likely due to polarization and charge transfer effects, as quantified by our quantum chemical calculations.

42 ENGINEERING↗

A U.S. scientific community review of carbon cycle science gaps and opportunities to better support earth system science and carbon management

Greenhouse gas (GHG) emissions continue to grow, while natural carbon reservoirs are becoming increasingly vulnerable to anthropogenic pressures, climate extremes, and disturbance. These changes are impacting humans, ecosystems, and natural resources worldwide. Tracking and mitigating GHG emissions require a pivot to operational monitoring of regional carbon flux and stock changes. The current GHG observing system is addressing needs at two distinct scales: 1) Local scale (< 1 km), related to anthropogenic point source emissions, and 2) global scales (> 1000 km), related to land and ocean carbon sinks. More focus on intermediate (10–1000 km) scales is needed to more effectively monitor progress in reducing carbon emissions, enhancing removals, and maintaining sinks. Representatives from carbon cycle biomass and flux communities across United States government agencies and academic institutions met in September 2024 to discuss the rationale and scientific context for more effectively implementing an operational system for GHG monitoring in support of urban and national carbon management needs. To guide development of this system, we propose a multi-tiered global spaceborne observing framework for carbon flux and stock, prioritizing: 1) frequent GHG partial columns for carbon emissions and removals; 2) continuous time series and data fusion of biomass from Lidar and Synthetic Aperture Radar (SAR) for carbon stocks, and 3) expanded coverage of tropical, high latitude, and oceanic regions to monitor carbon cycle tipping points and feedbacks. This system should be complemented by expanded surface and airborne networks for oceanic and terrestrial/aquatic ecosystems for calibration, ground truthing, and study of under-sampled regions.

54 ENVIRONMENTAL SCIENCES↗

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advocating for view and daylight in buildings: Next steps

With the exponential growth in population and commensurate increased density in urban cities, access to daylight and views to nature is being severely curtailed in buildings. In parallel, increasingly urgent demands to sharply reduce building energy use and associated greenhouse gas emissions are being made to mitigate climate change. There are many challenges and performance tradeoffs associated with the building facade (i.e., daylight and view versus solar and glare control); increased prioritization of health and well-being as a fundamental human requirement could adversely affect building energy-efficiency. Given the current state of knowledge on the effects of daylight and view on health and well-being in buildings, we identify critical needs in research, tools and technologies that if satisfied may enable more effective use of daylight and view in buildings within the constraints of climate change. Lack of knowledge regarding the complex causal mechanisms of window views on human factors is a severely limiting factor in forward progress. Current models and methods to derive bidirectional scattering distribution functions (BSDFs) will need to be modified. Developers of energy-efficient window technologies will need more guidance to shape product development. Advanced window technologies and integrated design can enable attainment of both health and well-being and net zero energy goals, but considerable work will be needed to make such options turnkey and broadly available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗