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At least 1,369 records · Page 76

Non-parametric projections of national income distribution consistent with the Shared Socioeconomic Pathways

Understanding and projecting income distributions within countries and regions is important to understanding consumption trends and the distributional consequences of climate impacts and responses. Several global, country-level projections of income distribution are available but most project only the Gini coefficient (a summary statistic of the distribution) or utilize the Gini along with the assumption of a lognormal distribution. We test the lognormal assumption and find that it typically underestimates income in the highest deciles and over-estimates it in others. We find that a new model based on two principal components of national time series data for income distribution provides a better fit to the data for all deciles, especially for the highest and lowest. We also construct a projection model in which the first principal component is driven by the Gini coefficient and the second captures deviations from this relationship. We use the model to project income distribution by decile for all countries for the five shared socioeconomic pathways. We find that inequality is consistently higher than projections based on the Gini and the lognormal functional form, with some countries reaching ratios of the highest to lowest income deciles that are almost three times their value using the lognormal assumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Hennessy, Eleanor M. (ORCID:0000000294715765)↗

Measuring impacts of California agri-environmental programs using field-scale satellite data

In the past decade, California has invested over $\$$200 million in direct grants to growers to support the adoption of agricultural practices that save water and/or improve soil health while also reducing greenhouse gas emissions. Ex-post evaluation of agri-environmental outcomes of these grant programs, however, is limited. We use satellite data to monitor changes in field-level consumptive water use and greenness (i.e. normalized difference vegetation index), a proxy for agricultural productivity, for the most frequently funded crop-types (almonds, grapes, and walnuts) in two California Department of Food and Agriculture programs. Nearly 600 fields receiving funding during the 2014–2022 period were analyzed using two causal inference methods. Fields that received grants to both upgrade irrigation systems and install irrigation water management sensors showed reduced consumptive water use and greenness by an average of 3.5% and 4.2%, respectively (significant at the 10% level). In contrast, we find that the adoption of only irrigation water management sensors, which are designed to inform irrigation scheduling and management, resulted in an average increase of 4.1% and 4.8% in consumptive water use and greenness respectively (significant at the 5% level). We find negligible effects for either consumptive water use or greenness when both pump efficiency upgrades and sensors were implemented. We further find that grants for compost addition and cover cropping led to small greenness increases of 1.7% and 2.8% respectively (significant at the 10% level) and had insignificant effects on consumptive water use. Our analysis of five agri-environmental program interventions reveals that several practice outcomes may be at odds with stated program goals of reducing water use while maintaining or improving agricultural productivity.

agriculture↗

Critical percolation on the kagome hypergraph

In this report we study the percolation critical surface of the kagome lattice in which each triangle is allowed an arbitrary connectivity. Using the method of critical polynomials, we find points along this critical surface to high precision. This kagome hypergraph contains many unsolved problems as special cases, including bond percolation on the kagome and (3, 12 2 ) lattices, and site percolation on the hexagonal, or honeycomb, lattice, as well as a single point for which there is an exact solution. We are able to compute enough points along the critical surface to find a very accurate fit, essentially a Taylor series about the exact point, that allows estimations of the critical point of any system that lies on the surface to precision rivaling Monte Carlo and traditional techniques of similar accuracy. We find also that this system sheds light on some of the surprising aspects of the method of critical polynomials, such as why it is so accurate for certain problems, like the kagome and (3, 12 2 ) lattices. The bond percolation critical points of these lattices can be found to 17 and 18 digits, respectively, because they are in close proximity, in a sense that can be made quantitative, to the exact point on the critical surface. We also discuss in detail a parallel implementation of the method which we use here for a few calculations.

97 MATHEMATICS AND COMPUTING↗

Generalized Toeplitz–Hankel matrices and their application to a layered electron gas

We extend the standard result for the eigenspectrum of the Toeplitz matrix C ij = e –κ|i–j| with 0 ≤ i,j ≤ N and κ ϵ C to a combination of a Toeplitz matrix and a Hankel matrix. We apply this result to find the plasma modes of a layered assembly of a 2-dimensional electron gas. We find a sum rule relating the geometric mean of the frequencies of the plasma modes to the determinant of this Toeplitz matrix, for which an analytical expression is obtained. Here, we apply the same technique to the generalized case when the layers are not evenly spaced, where the corresponding matrix is not a Toeplitz-Hankel combination. Despite this fact, it is possible to find properties of the eigenspectrum, and the eigenmodes are localized to a few layers instead of extending across the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Grover-QAOA for 3-SAT: quadratic speedup, fair-sampling, and parameter clustering

Abstract The SAT problem is a prototypical NP-complete problem of fundamental importance in computational complexity theory with many applications in science and engineering; as such, it has long served as an essential benchmark for classical and quantum algorithms. This study shows numerical evidence for a quadratic speedup of the Grover Quantum Approximate Optimization Algorithm (G-QAOA) over random sampling for finding all solutions to 3-SAT (All-SAT) and Max-SAT problems. G-QAOA is less resource-intensive and more adaptable for these problems than Grover’s algorithm, and it surpasses conventional QAOA in its ability to sample all solutions. We show these benefits by classical simulations of many-round G-QAOA on thousands of random 3-SAT instances. We also observe G-QAOA advantages on the IonQ Aria quantum computer for small instances, finding that current hardware suffices to determine and sample all solutions. Interestingly, a single-angle-pair constraint that uses the same pair of angles at each G-QAOA round greatly reduces the classical computational overhead of optimizing the G-QAOA angles while preserving its quadratic speedup. We also find parameter clustering of the angles. The single-angle-pair protocol and parameter clustering significantly reduce obstacles to classical optimization of the G-QAOA angles.

Zhang, Zewen (ORCID:000000032258613X)↗

Synergizing human expertise and AI efficiency with language model for microscopy operation and automated experiment design

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

97 MATHEMATICS AND COMPUTING↗

Supplementing biofuel mandates with a carbon mitigation policy can lead to water quality co-benefits

Biofuel mandates can impact the environment in multiple ways that may be positive or negative, including affecting life-cycle greenhouse gas (GHG) emissions by displacing fossil fuels, affecting soil carbon stocks due to accompanying land use change, and water quality due to changes in fertilizer requirements and the mix of crops used as feedstocks. To achieve desired environmental outcomes in the presence of a biofuel mandate, additional policy instruments must be adopted to supplement the mandate. We develop an integrated and spatially explicit ecosystem-economic modeling framework to analyze the cost-effectiveness of alternative policies to achieve desired targets for GHG emissions reduction from the agricultural and fuel sectors in the USA and nitrate leaching reduction in the Gulf of Mexico below the levels that would be achieved by a corn ethanol and/or a cellulosic ethanol mandate in the USA. We find that while a corn ethanol mandate lowers GHG emissions, it increases nitrate leaching due to the expansion of corn production; a cellulosic ethanol mandate lowers both GHG emissions and nitrate leaching relative to a corn ethanol mandate, but the additional carbon and nitrate prices are needed to achieve anticipated GHG reduction and nitrate reduction targets. We also find that accompanying a biofuel mandate with a GHG reduction target alone leads to substantial nitrate reduction co-benefits, but a nitrate reduction target alone is less effective in reducing GHG emissions. Combining a GHG standard with a nitrate standard can achieve GHG and nitrate reduction targets at lower carbon and nitrate prices as compared to implementing each of these policies independently. Furthermore, our findings show that disregarding policy co-benefits can overestimate the GHG and nitrate prices needed to achieve policy targets and higher policy costs.

09 BIOMASS FUELS↗

Post-Transcriptional Mechanisms Respond Rapidly to Ecologically Relevant Thermal Fluctuations During Temperature-Dependent Sex Determination

An organism’s ability to integrate transient environmental cues experienced during development into molecular and physiological responses forms the basis for adaptive shifts in phenotypic trajectories. During temperature-dependent sex determination (TSD), thermal cues during discrete periods in development coordinate molecular changes that ultimately dictate sexual fate and contribute to patterns of inter- and intra-sexual variation. How these mechanisms interface with dynamic thermal environments in nature remain largely unknown. By deploying thermal loggers in wild nests of the American alligator (Alligator mississippiensis) over two consecutive breeding seasons, we observed that 80% of nests exhibit both male- and female-promoting thermal cues during the thermosensitive period, and of these nests, all exhibited both male- and female-promoting temperatures within the span of a single day. These observations raise a critical question—how are opposing environmental cues integrated into sexually dimorphic transcriptional programs across short temporal scales? To address this question, alligator embryos were exposed to fluctuating temperatures based on nest thermal profiles and sampled over the course of a daily thermal fluctuation. We examined the expression dynamics of upstream genes in the temperature-sensing pathway and find that post-transcriptional alternative splicing and transcript abundance of epigenetic modifier genes JARID2 and KDM6B respond rapidly to thermal fluctuations while transcriptional changes of downstream effector genes, SOX9 and DMRT1, occur on a delayed timescale. Our findings reveal how the basic mechanisms of TSD operate in an ecologically relevant context. We present a hypothetical hierarchical model based on our findings as well as previous studies, in which temperature-sensitive alternative splicing incrementally influences the epigenetic landscape to affect the transcriptional activity of key sex-determining genes.

59 BASIC BIOLOGICAL SCIENCES↗

Wobbly discs – corrugations seen in the dust lanes of edge-on galaxies

ABSTRACT We report the detection of small-scale bending waves, also known as corrugations, in the dust lanes of five nearby edge-on disc galaxies. This phenomenon, where the disc mid-plane bends to become wavy, just as in warps but on a smaller scale, is seen here for the first time, in the dust lanes running across the discs. Because they are seen in absorption, this feature must be present in the dust disc in the outskirts of these galaxies. We enhance the visibility of these features using unsharp masking, trace the dust mid-plane across the disc, measure the corrugation amplitude by eye and the corrugation wavelength using Fourier analysis. The corrugation amplitude is found to be in the range of 70–300pc and the wavelengths lie between 1 and 5 kpc. In this limited sample, we find that the amplitude of the corrugations tends to be larger for lower mass galaxies, whereas the wavelength of corrugation does not seem to depend on the mass of host galaxies. Linear stability analysis is performed to find out the dynamical state of these dust discs. Based on WKB analysis, we find that the dust corrugations in about half of our sample are stable. Further analysis, on a larger sample would be useful to strengthen the above results.

Narayan, Chaitra A.↗

Carbon-loud SDSS BOSS type II quasars at z > 2: high-density gas or secondary production of carbon?

ABSTRACT We study the ultraviolet (UV) emission-line ratios of a sample of 145 type II quasars (QSO2s) from Sloan Digital Sky Survey iii Baryon Oscillation Spectroscopic Survey, and compare against a grid of active galactic nucleus (AGN) photoionization models with a range in gas density, gas chemical abundances, and ionization parameter. Most of the quasars are ‘carbon-loud’, with C iv/He ii ratios that are unusually high for the narrow-line region, implying higher than expected gas density (>106 cm−3) and/or significantly supersolar-relative carbon abundance. We also find that solar or supersolar nitrogen abundance and metallicity are required in the majority of our sample, with potentially significant variation between objects. Compared to radio galaxies at similar redshifts (HzRGs; z > 2), the QSO2s are offset to higher N v/He ii, C iv/He ii, and C iii]/He ii, suggesting systematically higher gas density and/or systematically higher C and N abundances. We find no evidence for a systematic difference in the N/C abundance ratio between the two types of objects. Scatter in the N iv]/C iv ratio implies a significant scatter in the N/C abundance ratio among the QSO2s and HzRGs, consistent with differences in the chemical enrichment histories between objects. Interestingly, we find that adopting secondary behaviour for both N and C alleviates the long-standing ‘N iv] problem’. A subset of the QSO2s and HzRGs also appear to be ‘silicon-loud’, with Si iii] relative fluxes suggesting Si/C and Si/O are an order of magnitude above their solar values. Finally, we propose new UV-line criteria to select genuine QSO2s with low-density narrow-line regions.

Silva, M.↗

Including massive neutrinos in thermal Sunyaev Zeldovich power spectrum and cluster counts analyses

We consistently include the effect of massive neutrinos in the thermal Sunyaev Zeldovich (SZ) power spectrum and cluster counts analyses, highlighting subtle dependencies on the total neutrino mass and data combination. In particular, we find that using the transfer functions for cold dark matter (CDM) + baryons in the computation of the halo mass function, instead of the transfer functions including neutrino perturbations, as prescribed in recent work, yields an ≈0.25 percent downward shift of the σ 8 constraint from tSZ power spectrum data, with a fiducial neutrino mass Σm ν = 0.06 eV. In ΛCDM, with an X-ray mass bias corresponding to the expected hydrostatic mass bias, i.e. (1 - b) ≃ 0.8, our constraints from Planck SZ data are consistent with the latest results from SPT, DES-Y1, and KiDS+VIKING-450. In νΛCDM, our joint analyses of Planck SZ with Planck 2015 primary CMB yield a small improvement on the total neutrino mass bound compared to the Planck 2015 primary CMB constraint, as well as (1 - b) = 0.64 ± 0.04 (68 percent CL). For forecasts, we find that competitive neutrino mass measurements using cosmic variance limited SZ power spectrum require masking the heaviest clusters and probing the small-scale SZ power spectrum up to ℓ max ≈ 10 4 . Although this is challenging, we find that SZ power spectrum can realistically be used to tightly constrain intracluster medium properties: we forecast a 2 percent determination of the X-ray mass bias by combining CMB-S4 and our mock SZ power spectrum with ℓ max = 10 3 .

Astronomy & Astrophysics↗

The turbulence driving parameter of molecular clouds in disc galaxies

ABSTRACT Supersonic turbulence plays a pivotal role during the formation of molecular clouds and stars in galaxies. However, little is known about how the fraction of compressive and solenoidal modes in the velocity field evolves over time and how it depends on properties of the molecular cloud or the galactic environment. In this work, we carry out magnetohydrodynamical simulations of disc galaxies and study the time evolution of the turbulence driving parameter for an ensemble of clouds. We find that the time-averaged turbulence driving parameter is insensitive to the position of the cloud within the galaxy. The ensemble-averaged driving parameter is found to be rather compressive with b ∼ 0.5–0.7, indicating almost time-independent global star formation properties. However, each individual cloud shows a highly fluctuating driving parameter, which would strongly affect the cloud’s star formation rate. We find that the mode of turbulence driving can rapidly change within only a few Myr, both from solenoidal to compressive and vice versa. We attribute these changes to cloud collisions and to tidal interactions with clouds or overdensities in the environment. Last, we find no significant differences in the average driving parameter between hydrodynamic and initially strongly magnetized galaxies. However, the magnetic field tends to reduce the overall fluctuation of the driving parameter. The average driving and its uncertainty are seen to be in agreement with recent constraints on the turbulence driving mode for solar neighbourhood clouds.

Körtgen, Bastian↗

Properties of five z ∼ 0.3–0.4 confirmed LyC leakers: VLT/XShooter observations

ABSTRACT Using new Very Large Telescope (VLT)/XShooter spectral observations we analyse the physical properties of five z ∼ 0.3–0.4 confirmed Lyman continuum (LyC) leakers. Strong resonant Mg ii λλ2796, 2803 Å emission lines (I(λλ2796, 2803)/I(Hβ) ≃ 10–38 per cent) and non-resonant Fe ii* λλ2612, 2626 Å emission lines are observed in spectra of five and three galaxies, respectively. We find high electron densities Ne ∼ 400 cm−3, significantly higher than in typical low-z, but comparable to those measured in z ∼ 2–3 star-forming galaxies (SFGs). The galaxies have a mean value of log N/O = –1.16, close to the maximum values found for SFGs in the metallicity range of 12 + log O/H ≃ 7.7–8.1. All 11 low-z LyC emitting galaxies found by Izotov et al., including the ones considered in this study, are characterized by high equivalent width (EW) (Hβ) ∼ 200–400 Å, high ionization parameter (log(U) = –2.5 to –1.7), high average ionizing photon production efficiency ξ = 1025.54 Hz erg−1, and hard ionizing radiation. On the Baldwin–Phillips–Terlevich (BPT) diagram we find the same offset of our leakers from low-z main-sequence SFGs as that for local analogues of Lyman-break galaxies (LBGs) and extreme SFGs at z ∼ 2–3. We confirm the effectiveness of the He i emission lines diagnostics proposed by Izotov et al. in searching for LyC leaker candidates and find that their intensity ratios correspond to those in a median with low neutral hydrogen column density N(H i) = 1017–5 × 1017 cm−2 that permit leakage of LyC radiation, likely due to their density-bounded H ii regions.

Guseva, N. G.↗

Comparison of stellar populations in simulated and real post-starburst galaxies in MaNGA

ABSTRACT Recent integral field spectroscopic (IFS) surveys have revealed radial gradients in the optical spectral indices of post-starburst (PSB) galaxies, which can be used to constrain their formation histories. We study the spectral indices of post-processed mock IFS datacubes of binary merger simulations, carefully matched to the properties of the MaNGA IFS survey, with a variety of black hole (BH) feedback models, progenitor galaxies, orbits, and mass ratios. Based on our simulation sample, we find that only major mergers on prograde–prograde or retrograde–prograde orbits in combination with a mechanical BH feedback model can form galaxies with weak enough ongoing star formation, and therefore absent H α emission, to be selected by traditional PSB selection methods. We find strong fluctuations in nebular emission line strengths, even within the PSB phase, suggesting that H α selected PSBs are only a subsample of the underlying population. The global PSB population can be more robustly identified using stellar continuum-based approaches. The difficulty in reproducing the very young PSBs in simulations potentially indicates that new sub-resolution star formation recipes are required to properly model the process of star formation quenching. In our simulations, we find that the starburst peaks at the same time at all radii, but is stronger and more prolonged in the inner regions. This results in a strong time evolution in the radial gradients of the spectral indices that can be used to estimate the age of the starburst without reliance on detailed star formation histories from spectral synthesis models.

Zheng, Yirui↗

The consequences of gamma-ray burst jet opening angle evolution on the inferred star formation rate

ABSTRACT Gamma-ray burst (GRB) data suggest that the jets from GRBs in the high redshift universe are more narrowly collimated than those at lower redshifts. This implies that we detect relatively fewer long GRB progenitor systems (i.e. massive stars) at high redshifts, because a greater fraction of GRBs have their jets pointed away from us. As a result, estimates of the star formation rate (SFR; from the GRB rate) at high redshifts may be diminished if this effect is not taken into account. In this paper, we estimate the SFR using the observed GRB rate, accounting for an evolving jet opening angle. We find that the SFR in the early universe (z > 3) can be up to an order of magnitude higher than the canonical estimates, depending on the severity of beaming angle evolution and the fraction of stars that make long GRBs. Additionally, we find an excess in the SFR at low redshifts, although this lessens when accounting for evolution of the beaming angle. Finally, under the assumption that GRBs do, in fact, trace canonical forms of the cosmic SFR, we constrain the resulting fraction of stars that must produce GRBs, again accounting for jet beaming-angle evolution. We find this assumption suggests a high fraction of stars in the early universe producing GRBs – a result that may, in fact, support our initial assertion that GRBs do not trace canonical estimates of the SFR.

79 ASTRONOMY AND ASTROPHYSICS↗

Extensions to models of the galaxy–halo connection

ABSTRACT We explore two widely used empirical models for the galaxy–halo connection, subhalo abundance matching (SHAM) and the halo occupation distribution (HOD), and compare them with the hydrodynamical simulation IllustrisTNG (TNG) for multiple statistics quantifying the galaxy distribution at $n_{\rm gal}\approx 1.3\times 10^{-3}\, ({\rm Mpc}\,h^{-1})^{-3}$. We observe that in their most straightforward implementations, both models fail to reproduce the two-point clustering measured in TNG. We find that SHAM models that use the relaxation velocity, Vrelax, and the peak velocity, Vpeak, perform best, and match the clustering reasonably well, although neither captures adequately the one-halo clustering. Splitting the total sample into sub-populations, we discover that SHAM overpredicts the clustering of high-mass, blue, star-forming, and late-forming galaxies and underpredicts that of low-mass, red, quiescent, and early-forming galaxies. We also study various baryonic effects, finding that subhaloes in the dark-matter-only simulation have consistently higher values of their SHAM-proxy properties than their full-physics counterparts. We then consider a 2D implementation of the HOD model augmented with a secondary parameter (environment, velocity anisotropy, σ2Rhalf-mass, and total potential) tuned so as to match the two-point clustering of the IllustrisTNG galaxies on large scales. We analyse these galaxy populations adopting alternative statistical tools such as galaxy–galaxy lensing, void–galaxy cross-correlations, and cumulants of the density field, finding that the hydrodynamical galaxy distribution disfavours σ2Rhalf-mass and the total potential as secondary parameters, while the environment and velocity anisotropy samples are consistent with full physics across all statistical probes examined. Our results demonstrate the power of examining multiple statistics for determining the secondary parameters that are vital for understanding the galaxy–halo connection.

79 ASTRONOMY AND ASTROPHYSICS↗

Skip Nav Destination The effect of environment on Type Ia supernovae in the Dark Energy Survey three-year cosmological sample

Analyses of Type Ia supernovae (SNe Ia) have found puzzling correlations between their standardized luminosities and host galaxy properties: SNe Ia in high-mass, passive hosts appear brighter than those in lower mass, star-forming hosts. We examine the host galaxies of SNe Ia in the Dark Energy Survey 3-yr spectroscopically confirmed cosmological sample, obtaining photometry in a series of ‘local’ apertures centred on the SN, and for the global host galaxy. We study the differences in these host galaxy properties, such as stellar mass and rest-frame U − R colours, and their correlations with SN Ia parameters including Hubble residuals. We find all Hubble residual steps to be >3σ in significance, both for splitting at the traditional environmental property sample median and for the step of maximum significance. For stellar mass, we find a maximal local step of 0.098 ± 0.018 mag; ∼0.03 mag greater than the largest global stellar mass step in our sample (0.070 ± 0.017 mag). When splitting at the sample median, differences between local and global U − R steps are small, both ∼0.08 mag, but are more significant than the global stellar mass step (0.057 ± 0.017 mag). We split the data into sub-samples based on SN Ia light-curve parameters: stretch (x_1) and colour (c), finding that redder objects (c > 0) have larger Hubble residual steps, for both stellar mass and U − R, for both local and global measurements, of ∼0.14 mag. Additionally, the bluer (star-forming) local environments host a more homogeneous SN Ia sample, with local U − R rms scatter as low as 0.084 ± 0.017 mag for blue (c < 0) SNe Ia in locally blue U − R environments.

79 ASTRONOMY AND ASTROPHYSICS↗