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At least 91 records · Page 5

A statistical model to predict ignition probability

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. Here, this work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the model concepts and demonstrates its ability to recover the experimental ignition map with good accuracy.

42 ENGINEERING↗

Building a Healthy Urban Design Index (HUDI): how to promote health and sustainability in European cities

As global urbanisation accelerates, alongside declining environmental quality and increasing climate challenges, it is increasingly vital for urban planners and policy makers to integrate health and wellbeing considerations into urban planning. This study introduces the Healthy Urban Design Index (HUDI), a high-resolution spatial index developed for European cities. HUDI combines policy-relevant indicators related to urban design, sustainable transportation, environmental quality, and greenspace accessibility—key factors influencing human health and well-being. Unlike existing indices, which often focus on few or large metropolitan cities and lack spatial granularity, HUDI offers high resolution and extends its scope to small-sized and medium-sized cities, home to over 50% of Europe's population.

60 APPLIED LIFE SCIENCES↗

Maximized Hole Trapping in a Polystyrene Transistor Dielectric from a Highly Branched Iminobis(aminoarene) Side Chain

We synthesized highly branched and electron donating side chain subunits and attached them to polystyrene (PS) used as a dielectric layer in a pentacene field effect transistor. The influence of these groups on dielectric function, charge retention and threshold voltage shifts (ΔV th ) depending on their positions in dielectric multilayers was determined. We compared the observations made on an N-perphenylated iminobisaniline side chain with those from the same side chains modified with ZnO nanoparticles and with an adduct formed from tetracyanoethylene (TCNE). We also synthesized an analogue in which six methoxy groups are present instead of two amine nitrogens. At 6 mol % side chain, hopping transport was sufficient to cause shorting of the gate, while at 2 mol %, charge trapping was observable as transistor threshold voltage shifts (ΔV th ). Here, we created three types of devices: with the substituted PS layer as single layer dielectric, on top of a crosslinked PS layer but in contact with the pentacene (bilayers), and sandwiched between two PS layers in trilayers. Particularly large bias stress effects and ΔV th , larger than the hexamethoxy and previously studied dimethoxy analogs, were observed in the second case and the effects increased with the increasing electron donating properties of the modified side chains. The highest ΔV th was consistent with a majority of the side chains stabilizing trapped charge. Trilayer devices showed decreased charge storage capability compared to previous work in which we used less donating side chains but in higher concentrations. The ZnO and TCNE modifications resulted in slightly more and less negative ΔV th , respectively, when the side chain polystyrene was not in contact with the pentacene and isolated from the gate electrode. The results indicate a likely maximum combination of molecular charge stabilizing activity and side chain concentration that still allows gate dielectric function.

36 MATERIALS SCIENCE↗

Anion Selectivities in Zwitterion Grafted Nanopores: Effect of Zwitterion Architecture

The separation of ions of similar charge is a crucial challenge in many applications, from water treatment to precious metal recovery. Membranes with cross-linked zwitterionic amphiphilic copolymer (ZAC-X) selective layers, which feature self-assembled, zwitterion-lined nanodomains for permeation, offer unique permselectivity between monovalent anions (e.g. $\mathrm{Cl^-}$/$\mathrm{F^-}$). This has motivated studies on the mechanisms of transport and selectivity in this family of materials. In this study, we conducted molecular dynamics simulations of aqueous salt solutions within zwitterion-functionalized nanopores to elucidate the influence of dipole orientation of the ZI ligands on anion diffusivities, partitioning, and permeabilities. Here, our model compares systems with contrasting ZI organization: surface-cation-anion ($\mathrm{S\text{-}ZI^{+}\text{-}ZI^{-}}$, Motif A) and surface-anion-cation ($\mathrm{S\text{-}ZI^{-}\text{-}ZI^{+}}$, Motif B). Our results reveal that Motif A exhibits less pronounced ion pairing due to a spatial separation in the radial profiles of cations and anions. Motif B demonstrates prominent ion pairing for smaller anions owing to their overlap with cation distributions. Further, our potential of mean force profiles reveal that anion partitioning increases with anion size in both ligand motifs, whereas Motif B exhibits significantly higher partitioning selectivity towards larger anions compared to Motif A. Our results for ion diffusivities show that the self-diffusivities of both anions and cations are lower for Motif B compared to Motif A. Such trends in anion partitioning and diffusivities can be explained by differences in the interactions and steric hindrance experienced by the anionic species in Motifs A and B. Finally, our results for anion permselectivity, obtained by combining partitioning and diffusivity, indicate that partitioning trends dominate over diffusivity trends. Consequently, anion permeability increases with anion size, and ligand Motif B yields much higher permselectivity towards larger anions compared to ligand Motif A.

anions↗

Atrazine Degradation Using Immobilized Triazine Hydrolase from Arthrobacter aurescens TC1 in Mesoporous Silica Nanomaterials

Triazine hydrolase fromArthrobacter aurescens TC1 (TrzN) was successfully immobilized on mesoporous silica nanomaterials (MSNs) for the first time. For both nonfunctionalized MSNs and MSNs functionalized with Zn(II), three pore sizes were evaluated for their ability to immobilize wild-type TrzN: Mobile composition of matter no. 41 (small, 3 nm pores), mesoporous silica nanoparticle material with 10 nm pore diameter (MSN-10) (medium, 6-12 nm pores), and pore-expanded MSN-10 (large, 15-30 nm pores). Of these six TrzN:MSN biomaterials, it was shown that TrzN:MSN-10 was the most active (3.8 +/- 0.4 x 10 -5 U/mg) toward the hydrolysis of a 50 uM atrazine solution at 25 degrees C. The TrzN:MSN-10 biomaterial was then coated in chitosan (TrzN:MSN-10:Chit) as chitosan has been shown to increase stability in extreme conditions such as low/high pH, heat shock, and the presence of organic solvents. TrzN:MSN-10:Chit was shown to be a superior TrzN biomaterial to TrzN:MSN-10 as it exhibited higher activity under all storage conditions, in the presence of 20% MeOH, at low and high pH values, and at elevated temperatures up to 80 degrees C. Finally, the TrzN:MSN-10:Chit biomaterial was shown to be fully active in river water, which establishes it as a functional biomaterial under actual field conditions. A combination of these data indicate that the TrzN:MSN-10:Chit biomaterial exhibited the best overall catalytic profile making it a promising biocatalyst for the bioremediation of atrazine.

09 BIOMASS FUELS↗

A Chimeric LBT-GFP Biosensor Exhibits Antithetical Fluorescence Responses to Ca 2+ and Dy 3+ Binding

Rare earth elements (REEs) are critical components in emerging technologies, but their mining and refining processes are often laborious, costly, and environmentally damaging. Developing green and efficient separation methods for REEs is crucial. Biomolecular approaches using lanthanide-binding proteins and peptides show promise for selective REE extraction and separation. In this study, we present the design and characterization of a genetically encoded fluorescence indicator (GEFI) construct that combines a superfolder green fluorescent protein (sfGFP) with a dual lanthanide-binding tag (2×dLBT). The 2×dLBT insert induces conformational changes in sfGFP upon lanthanide binding, modulating the fluorescence intensity. The sfGFP-2×dLBT biosensor exhibited distinct fluorescence responses to different lanthanide ions, with the highest dynamic range observed for heavy REEs like dysprosium (Dy 3+ ). Interestingly, the sensor displayed an antithetical response, where low concentrations of lanthanides initially quenched the fluorescence, but higher concentrations led to a significant fluorescence increase (1.5-fold). The Ca 2+ ion on the other hand showed only a dose-dependent quenching of the fluorescence response. Based on these observations, the biphasic response of the biosensor to lanthanides was eliminated by pretreating the sensor with calcium, which further expanded the dynamic range up to 3-fold for Dy 3+ . The lanthanide-selective and concentration-dependent fluorescence changes of the sfGFP-2×dLBT biosensor demonstrate its potential as a platform for developing specific sensors for various REEs. These sensors could enable rapid and cost-effective determination of REE composition in complex mixtures, facilitating the separation and recovery of critical REEs from electronic waste and other REE-containing sources.

59 BASIC BIOLOGICAL SCIENCES↗

Reversal of carbonate-silicate cation exchange in cold slabs in Earth’s lower mantle

The stable forms of carbon in Earth’s deep interior control storage and fluxes of carbon through the planet over geologic time, impacting the surface climate as well as carrying records of geologic processes in the form of diamond inclusions. However, current estimates of the distribution of carbon in Earth’s mantle are uncertain, due in part to limited understanding of the fate of carbonates through subduction, the main mechanism that transports carbon from Earth’s surface to its interior. Oxidized carbon carried by subduction has been found to reside in MgCO 3 throughout much of the mantle. Experiments in this study demonstrate that at deep mantle conditions MgCO 3 reacts with silicates to form CaCO 3 . In combination with previous work indicating that CaCO 3 is more stable than MgCO 3 under reducing conditions of Earth’s lowermost mantle, these observations allow us to predict that the signature of surface carbon reaching Earth’s lowermost mantle may include CaCO 3 .

58 GEOSCIENCES↗

Hydrogen bonds and dispersion forces serving as molecular locks for tailored Group 11 bis(amidine) complexes

A flexible polydentate bis(amidine) ligand LH 2 , LH 2 = {CH 2 NH( t Bu)C=N-2-(6-MePy)} 2 , operates as a molecular lock for various coinage metal fragments and forms the dinuclear complexes [LH 2 (MCl) 2 ], M = Cu (1), Au (2), the coordination polymer [{(LH 2 ) 2 (py) 2 (AgCl) 3 }(py) 3 ] n (3), and the dimesityl-digold complex [LH 2 (AuMes) 2 ] (4) by formal insertion of MR fragments (M = Cu, Ag, Au; R = Cl, Mes) into the N–H∙∙∙N hydrogen bonds of LH 2 in yields of 43–95%. Complexes 1, 2, and 4 adopt C 2 -symmetrical structures in the solid state featuring two interconnected 11-membered rings that are locked by two intramolecular N–H∙∙∙R–M hydrogen bonds. QTAIM analyses of the computational geometry-optimized structures 1a, 2a, and 4a reveal 13, 11, and 22 additional bond critical points, respectively, all of which are related to weak intramolecular attractive interactions, predominantly representing dispersion forces, contributing to the conformational stabilization of the C2-symmetrical stereoisomers in the solid state. Variable-temperature 1 H NMR spectroscopy in combination with DFT calculations indicate a dynamic conformational interconversion between two C 2 -symmetrical ground state structures in solution (ΔG ‡ c = 11.1–13.8 kcal mol –1 ), which is accompanied by the formation of an intermediate possessing C i symmetry that retains the hydrogen bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of plasma start-up with high Z and low Z first wall in WEST

The choice of first wall material is of paramount importance for the plasma start-up conditions in ITER and future fusion power plants. In this context, the present work focuses on the correlations between first wall impurity sources and total radiated power during plasma start-up in the tungsten (W) Environment in Steady-state Tokamak (WEST). The objective is to highlight experimental indications for a preferable combination of start-up plasma scenario and first wall materials. Until 2019, WEST featured a full high Z first wall with all limiters exposing only W surfaces to the plasma. To study the impact of a low Z first wall in WEST, boron nitride tiles were installed in the central part of the inner and outer limiters in 2020. Although visible spectroscopy and bolometry measurements show respectively a strong weakening of the WI line intensity on the limiters and a reduction of radiated power after the changeover, a degradation occurs with the accumulation of plasma exposure. In addition, the different plasma facing elements of the main chamber do not influence equally the radiated power during start-up. In both high Z and low Z environments, a clear non-linear dependence is found between the start-up radiated power and the outer limiter W impurity source. Since W seems to be the main cause for core radiation, correlation between outer limiter W sources and other impurity sources are investigated. Finally, analysis of the legacy of B powder drops on a number of start-up plasmas suggests that it is less effective at reducing radiated power when the first wall is covered with W.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Zinc oxide (ZnO) hybrid metasurfaces exhibiting broadly tunable topological properties

Extreme light confinement observed in periodic photonic structures, such as the vortex singularities in momentum (k) space, has been associated with their topological nature. Consequently, by exploiting and tuning their topological properties, optical metasurfaces have been demonstrated as an attractive platform for active photonics. However, given the fact that most active media under external excitations can only provide limited refractive index change, the potential advancements offered by the topological character of active metasurfaces have remained mostly unexplored. Zinc oxide (ZnO), which has recently exhibited optically-induced extraordinarily large permittivity modulations at visible and near-infrared frequencies, is an excellent active material for dynamic metasurfaces exhibiting strong tuning. This work demonstrates that a hybrid metasurface consisting of an array of ZnO nanodisks on a silver backplane displays broadly tunable topological properties. In particular, by performing k-space scattering simulations using measured pump-fluence-dependent material properties of ZnO, we study in detail the light reflection from the hybrid metasurface. Our results validate that the large k-space topology tuning of the metasurface can result in enormously strong polarization manipulation of near-infrared light in the vicinity of the topological features. The observed polarization switching effect is highly sensitive to the polarization and wavelength of an incident wave, owing to the symmetry and dispersion characteristics of the proposed system. Our study indicates that leveraging a combination of the extraordinary material properties and the k-space topology, hybrid metasurfaces based on ZnO may open new avenues for creating all-optical switchable metadevices.

36 MATERIALS SCIENCE↗

Quantifying model prediction sensitivity to model-form uncertainty

Computational and mathematical models are essential to understanding complex systems and phenomena. However, when developing such models, limited knowledge and/or resources necessitates the use of simplifying assumptions. It is therefore crucial to quantify the impact of such simplifying assumptions on the reliability and accuracy of resulting model predictions. This work develops a first-of-its-kind approach to quantify the impact of physics modeling assumptions on predictions. Here, we leverage the emerging field of model-form uncertainty (MFU) representations, which are parameterized modifications to modeling assumptions, in combination with grouped Sobol’ indices to quantitatively measure an assumption’s importance. Specifically, we compute the grouped Sobol’ index for the MFU representation’s parameters as a single importance measure of the assumption for which the MFU representation characterizes uncertainty. To ensure this approach is robust to the subjective choice of how to parameterize a MFU representation, we establish bounds for the difference between sensitivity results for two different MFU representations based on differences in model prediction statistics. The capabilities associated with this approach are demonstrated on three exemplar problems: an upscaled subsurface contaminant transport problem, ablation modeling for hypersonic flight, and nuclear waste repository modeling. We found that our grouped approach is able to assess the impact of modeling assumptions on predictions and offers computational advantages over classical Sobol’ index computation while providing more interpretable results.

97 MATHEMATICS AND COMPUTING↗

Techno-Economic Analysis of a Nuclear Reactor System coupled with a Liquid Metal Battery

There is a need for nuclear reactor systems to become more dynamic as defossilization and renewable energy sources continue to reshape the energy grid. One option to meet these changing demands is to pair the reactor with an energy storage system. This work details a technoeconomic analysis and sensitivity analysis of a high temperature gas cooled microreactor, supercritical carbon dioxide power cycle, and liquid metal battery. Dynamic modeling has shown that these three systems compliment each other to provide load following and black-start capabilities to the grid. Current cost estimates for installing the systems yield a competitive levelized cost of electricity and levelized cost of storage, indicating that such a combined system may be economically viable as technological advances lead to them being technically feasible.

25 ENERGY STORAGE↗

Radiation effects on atherosclerosis in atomic bomb survivors: a cross-sectional study using structural equation modeling

Past reports indicated that total-body irradiation at low to moderate doses could be responsible for cardiovascular disease risks, but the mechanism remains unclear. The purpose of this study was to investigate the association between radiation exposure and atherosclerosis, an underlying pathology of cardiovascular diseases, in the Japanese atomic bomb survivors. We performed a cross-sectional study measuring 14 clinical-physiological atherosclerosis indicators during clinical exams from 2010 to 2014 in 3274 participants of the Adult Health Study cohort. Multivariable analyses were performed by using a structural equation model with latent factors representing underlying atherosclerotic pathologies: (1) arterial stiffness, (2) calcification, and (3) plaque as measured with indicators chosen a priori on the basis of clinical-physiological knowledge. Radiation was linearly associated with calcification (standardized coefficient per Gy 0.15, 95 % confidence interval: CI [0.070, 0.23]) and plaque (0.11, 95 % CI [0.029, 0.20]), small associations that were comparable to about 2 years of aging per Gy of radiation exposure, but not with arterial stiffness (0.036, 95 % CI [-0.025, 0.095]). The model fitted better and had narrower confidence intervals than separate ordinary regression models explaining individual indicators independently. The associations were less evident when the dose range was restricted to a maximum of 2 or 1 Gy. By combining individual clinical-physiological indicators that are correlated because of common, underlying atherosclerotic pathologies, we found a small, but significant association of radiation with atherosclerosis.

59 BASIC BIOLOGICAL SCIENCES↗

Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological implications from two decades of spectroscopic surveys at the Apache Point Observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Lyα forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, r d , from eight different samples and six measurements of the growth rate parameter, fσ 8 , from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, ΛCDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization, under the same model, the BAO data provide nearly an order of magnitude improvement on curvature constraints relative to primary CMB constraints alone. Independent of distance measurements, the SDSS RSD data complement weak lensing measurements from the Dark Energy Survey (DES) in demonstrating a preference for a flat ΛCDM cosmological model when combined with Planck measurements. The combined BAO and RSD measurements indicate σ 8 =0.85±0.03, implying a growth rate that is consistent with predictions from Planck temperature and polarization data and with General Relativity. When combining the results of SDSS BAO and RSD, Planck, Pantheon Type Ia supernovae (SNe Ia), and DES weak lensing and clustering measurements, all multiple-parameter extensions remain consistent with a ΛCDM model. Regardless of cosmological model, the precision on each of the three parameters, Ω Λ , H 0 , and σ 8 , remains at roughly 1%, showing changes of less than 0.6% in the central values between models. In a model that allows for free curvature and a time-evolving equation of state for dark energy, the combined samples produce a constraint Ω K =-0.0022±0.0022. The dark energy constraints lead to w 0 =-0.909±0.081 and w a =$-0.49_{-0.30}^{+0.35}$, corresponding to an equation of state of w p =-1.018±0.032 at a pivot redshift z p =0.29 and a Dark Energy Task Force Figure of Merit of 94. The inverse distance ladder measurement under this model yields H 0 =68.18±0.79 km s -1 Mpc -1 , remaining in tension with several direct determination methods; the BAO data allow Hubble constant estimates that are robust against the assumption of the cosmological model. In addition, the BAO data allow estimates of H 0 that are independent of the CMB data, with similar central values and precision under a ΛCDM model. Our most constraining combination of data gives the upper limit on the sum of neutrino masses at Σm ν <0.115 eV (95% confidence). Finally, we consider the improvements in cosmology constraints over the last decade by comparing our results to a sample representative of the period 2000-2010. We compute the relative gain across the five dimensions spanned by w, Ω k , Σm ν , H 0 , and σ 8 and find that the SDSS BAO and RSD data reduce the total posterior volume by a factor of 40 relative to the previous generation. Finally, adding again the Planck, DES, and Pantheon SN Ia samples leads to an overall contraction in the five-dimensional posterior volume of 3 orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrated Metrics for County-Level Resilience Ranking Using Entropy and TOPSIS

In the face of atypical weather events, power infrastructure failures, and limited resources for resilience investment, energy decision-makers need data-driven metrics to allocate resilience investments and maximize the reduction of power outage impacts. For state-level planning, for instance, ranking the resilience of each county is key to ensuring effective distribution of resources. In such cases, resilience for each spatial unit is multifaceted and is captured by a set of indicators (i.e., metrics) that can be combined into an overall score that reduces the complexity of power outage dynamics to a single decision metric. However, weighting of these indicators is often addressed by simplifying assumptions (i.e., equal weights) or semi-subjective methods that rely on user-defined weights that can introduce biases (e.g., weighted average score). Within the disaster risk reduction and resilience engineering community, a recurring challenge in multicriteria decision-making is the objective weighting of indicators for composite indices. To address this issue, we have leveraged a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) combined with an entropy-based weighting approach to calculated the integrated scores. This method objectively determines the importance of each metric, better discerns between spatial units (i.e., counties), and offers a more reliable ranking of counties according to their relative resilience attributes. By improving methods for integrating resilience indicators, our approach helps planners and decision-makers prioritize resources more effectively for more efficient resilience investments.

Bhusal, Narayan [Oak Ridge National Laboratory (OR↗

A dataset of eco-evidence tools to inform early-stage environmental impact assessments of hydropower development

The datasets described herein provide the foundation for a decision support prototype (DSP) toolkit aimed at assisting stakeholders in determining evidence of which aspects of river ecosystems have been impacted by hydropower. The DSP toolkit and its application are presented and described in the article “Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development” [1]. Development of the DSP and the output for decision support centralize around 42 river function indicators describing the dimensionality of river ecosystems through six main categories: biota and biodiversity, water quality, hydrology, geomorphology, land cover, and river connectivity. Three main tools are represented in the DSP: A science-based questionnaire (SBQ), an environmental envelope model (EEM), and a river function linkage assessment tool (RFLAT). The SBQ is a structured survey-style questionnaire whose objective is to provide evidence of which indicators have been impacted by hydropower. Based on a global literature review, 140 questions were developed from general hypotheses regarding the impacts of dams on rivers. The EEM is a model to predict the likelihood of hydropower impacting indicators based on a several variables. The intended use of the EEM is for situations of new hydropower development where results of the SBQ are incomplete or highly uncertain. The EEM was developed through the compilation of a dataset containing attributes of dams, reservoirs, and geospatial information on environmental concerns, which was combined with data on ecological indicators documented at those sites through literature review. The model operates through 247 “envelopes” and weighting factors, representing the individual effect of each variable on each indicator, all available through spreadsheets. Finally, the RFLAT is a tool to examine causal relationships amongst indicators. Inter-indicator relationships were hypothesized based on literature review and summarized into node and edge datasets to represent the structure of a graphical network. Bayes theorem was used estimate conditional probabilities of inter-indicator relationships based on the output of the SBQ. Nodes and edges were imported into R programming environment to visualize ecological indicator networks. The datasets can be expanded upon and enriched with more detailed questions for the SBQ, building upon the EEM with to develop more sophisticated models, and identifying new relationships for the RFALT. Additionally, once the tools are applied to numerous hydropower developments, the output of the tools (e.g. evidence of impacted indicators) becomes a very useful dataset for meta-analyses of hydropower impacts.

13 HYDRO ENERGY↗

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↗

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗