Model-independent Estimates Research Articles

Model independent estimation of expansion rate from low and high redshift SNIa

Understanding the expansion rate history is a primary goal in cosmology. There are various ways to measure the expansion rate at different redshifts and measuring it through the luminosity distance of SNIa is widely used in cosmology. In this work, we split the latest dataset of SNIa (the Pantheon+ sample) into several redshift bins and compute the expansion rate through a non-parametric technique. To do this, we use the Gaussian process to obtain the expansion rate considering data in different redshift bins. For the sake of comparison, we also consider the [Formula: see text]CDM model and find the expansion history through an MCMC analysis. Our results indicate that the degeneracy between free parameters prevents a good constraint using the low redshifts data but this is not the case in the GP scenario. Moreover, we study how high redshift SNIa can affect the current expansion rate and observe that data at [Formula: see text] has almost no impact on the current expansion rate in both approaches.

Listening to dark sirens from gravitational waves : Combined effects of fifth force, ultralight particle radiation, and eccentricity

We analyse the orbital period decay in compact binary systems influenced by a fifth force and ultralight particle radiation, considering a general eccentric Keplerian orbit. The analysis provides constraints on the axion decay constant when orbital period decay involves axionic fifth force and axion radiation. The bound on axion coupling improves by an order of magnitude for high eccentricity binaries like the Hulse–Taylor binary. These bounds become stronger when considering both axion mediation and radiation. We also derive constraints on the strengths of the fifth force and radiation from GW170817 by measuring the Chirp mass, which depends on initial eccentricity. The coalescence time increases with higher initial eccentricity compared to the gravity-only scenario, highlighting the importance of accurately selecting initial eccentricity for setting bounds on fifth force searches in precision gravitational wave detection. Additionally, we provide model-independent estimates for dark matter capture by a binary system. The derived constraints can be further strengthened with the use of second and third generation gravitational wave detectors.

Exploring Urban Sustainability: The Role of Geology and Hydrogeology in Numerical Aquifer Modelling for Open-Loop Geothermal Energy Development, the Case of Torino (Italy)

This research examines the integration of geological and hydrogeological data in numerical aquifer model simulations, with a particular focus on the urban area of Torino, Italy. The role of groundwater resources in urban sustainability is analysed. The objective is to integrate open-loop geothermal plants into the district heating network of IREN S.p.A. Two case studies are examined: the Torino Nord area and the Moncalieri area, both of which host district heating plants. The work entails the collection and analysis of data from a variety of sources, including geognostic surveys and permeability tests, in order to construct a three-dimensional numerical model of the surface aquifer. Models were built using the public MODFLOW 6 (model of groundwater flow) code and calibrated using PESTHP (High Performance of Model Independent Parameter Estimation and Uncertainty Analysis). Results indicate the potential of urban aquifers as renewable energy sources and the necessity of comprehensive geological and hydrogeological assessments for optimal ground water heat pump (GWHP) system installation. This paper emphasises the significance of sustainable water management in the context of climate change and urbanisation challenges.

Predicting post-fire forest recovery using the 3-PG model with bi-temporal Landsat imagery in high-severity burned areas of Great Xing’an Mountain

High-severity fire altered the landscape pattern and destroyed forest resilience in the Great Xing’an Mountain. Predicting the spatiotemporal patterns of forest recovery in high-severity burned areas is critical for formulating effective post-fire management measures. Previous studies attempted to address this topic by fitting the recovery trajectory based on time-series remote sensing vegetation indices. However, these methods typically require long-term time series of satellite images for prediction and have sometimes been demonstrated as an unrealistic representation of the post-fire forest patterns due to the saturation issues of vegetation indices. In this study, we proposed a novel approach to predict post-fire forest recovery patterns by coupling a process-based Physiological Principles in Predicting Growth (3-PG) model with bi-temporal satellite imagery. First, based on tree core data, we calibrated the physiological parameters of the 3-PG model using a Model-Independent Parameter Estimation (PEST) model. Second, we used vegetation indices derived from bi-temporal Landsat data to estimate site-specific parameters of the 3-PG model and extrapolated the meteorological factors by a Mountain Microclimate Simulation Model (MTCLIM). Third, we used these variables as input parameters to drive the 3-PG model, resulting in the simulation of the post-fire 50-year regeneration dynamic of the leaf area index (LAI). The calibrated 3-PG model was validated by the independent sites, providing good estimates of DBH and biomass components with R2 of greater than 0.994 and RRMSE of less than 15.7 %. The 3-PG model predicted LAI maps were evaluated by referenced LAI retrieved from Landsat data, showing a high correlation with reference but the accuracy decreased with the prediction time increased. The model predicted forest recovery to pre-fire LAI within 32 years where the longest recovery interval was observed in the low seedling density and soil fertility. This study shows great potential for reasonable prediction and assessment of forest recovery after the fire occurrence. By combining more simulated scenarios, our approach also facilitates the exploration of the impact of artificial measures and climate on post-forest recovery.

A study on the simulation of carbon and water fluxes of Dangxiong alpine meadow and its response to climate change

The alpine meadow ecosystem accounts for 27 % of the total area of the Tibetan Plateau and is also one of the most important vegetation types. The Dangxiong alpine meadow ecosystem, located in the south-central part of the Tibetan Plateau, is a typical example. To understand the carbon and water fluxes, water use efficiency (WUE), and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area, two parameter estimation methods, the Model-independent Parameter Estimation (PEST) and the Dynamic Dimensions Search (DDS), were used to optimize the Biome-BGC model. Then, the gross primary productivity (GPP) and evapotranspiration (ET) were simulated. The results show that the DDS parameter calibration method has a better performance. The annual GPP and ET show an increasing trend, while the WUE shows a decreasing trend. Meanwhile, ET and GPP reach their peaks in July and August, respectively, and WUE shows a “dual-peak” pattern, reaching peaks in May and November. Furthermore, according to the simulation results for the next nearly 100 years, the ensemble average GPP and ET exhibit a significant increasing trend, and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario. WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario. This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.摘要全球气候变化对青藏高原生态系统产生了深远影响, 暖湿化背景下青藏高原植被碳, 水通量变化趋势值得关注. 高寒草甸是青藏高原最主要的植被类型之一, 为理解青藏高原当雄地区高寒草甸生态系统碳, 水通量, 水分利用效率及其对未来气候变化的响应, 本研究利用PEST和DDS两种参数率定方法优化Biome-BGC模型, 进而模拟2000–2019年当雄站的总初级生产力 (GPP) 和蒸散量 (ET) . 研究结果表明: DDS参数率定方法具有更优的性能. GPP和ET在研究时段内呈上升趋势, 而水分利用效率 (WUE) 则呈下降趋势. 同时, ET和GPP分别在7月和8月达到峰值, 而WUE则呈“双峰”变化, 分别于5月和11月达到峰值. 此外, 未来近百年的模拟表明GPP和ET的集合平均结果呈显著增加趋势, 其中在SSP5–8.5情景下的增速大于SSP2–4.5情景. WUE在SSP2–4.5情景下呈增加趋势, 而在SSP5–8.5情景下呈显著增加趋势. 本研究结果可为青藏高原碳, 水循环预测研究和植被生态保护的应用研究提供参考和借鉴.

Overview of State Estimation Methods and Research Progress of Power Lithium Batteries for Electric Vehicles

This paper presents a comprehensive research framework for state estimation of power lithium batteries by summarizing both model-based and non-model-based approaches. It provides an in-depth analysis of various methods, supported by experimental results. In the first part, the paper surveys model-based state estimation techniques, including the ECM (Equivalent Circuit Model), electrochemical models, and data-driven models. It systematically explains the principles behind these models and their respective applications. Additionally, the study delves into model-independent state estimation, emphasizing the utilization of machine learning algorithms in battery state estimation and the advancements in artificial intelligence technology. The potential of hybrid methods and intelligent algorithms in state estimation is also explored, highlighting possible future directions. The findings indicate that while model-based methods can attain high estimation accuracy in specific scenarios, they are constrained by model complexity and parameter uncertainty. The application of fusion method and intelligent algorithm further improves the performance of state estimation and provides strong support for real-time monitoring and prediction of power lithium batteries.

High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns

Abstract. Satellite-derived spatiotemporal patterns of nitrogen oxide (NOx) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NOx emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO2) retrievals. The accuracy of the coupled method is validated through application to synthetic NO2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88±0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

Assessment of the Impact of Spatial Variability on Streamflow Predictions Using High-Resolution Modeling and Parameter Estimation: Case Study of Geumho River Catchment, South Korea

In this study, we analyzed the impact of model spatial resolution on streamflow predictions, focusing on high-resolution scenarios (<1 km) and flooding conditions at catchment scale. Simulation experiments were implemented for the Geumho River catchment in South Korea using Weather Research and the Forecasting Hydrological Modeling System (WRF-Hydro) with spatial resolutions of 100 m, 250 m, and 500 m. For the estimation of parameters, an automatic calibration tool based on the Model-Independent Parameter Estimation and Uncertainty Analysis (PEST) method was utilized. We assessed the hydrological predictions across different spatial resolutions considering calibrated parameters, calibration runtime, and accuracy of streamflow before and after calibration. For both Rainfall Events 1 and 2, significant improvements were observed after event-specific calibration in all resolutions. Particularly for 250 m resolution, NSE values of 0.8 or higher were demonstrated at lower gauging locations. Also, at a 250 m resolution, the changes in the calibrated parameter values (REFKDT) were minimized between Rainfall Events 1 and 2, implicating more effective calibration compared to the other resolutions. At resolutions of 100 m and 500 m, the optimal parameter values for the two events were distinctively different while more computational resources were required for calibration in Event 2 with drier antecedent conditions.

Model dependence of the number of participant nucleons and observable consequences in heavy-ion collisions

The centrality determination and the estimated fluctuations of number of participant nucleons N_{part} in Au–Au collisions at 1.23 AGeV beam kinetic energy suffers from severe model dependencies. Comparing the Glauber Monte Carlo (MC) and UrQMD transport models, it is shown that N_{part} is a strongly model dependant quantity. In addition, for any given centrality class, Glauber MC and UrQMD predicts drastically different N_{part} distributions. The impact parameter b and the number of charged particles N_{ch} on the other hand are much more correlated and give an almost model independent centrality estimator. It is suggested that the total baryon number balance, from integrated rapidity distributions, can be used instead of N_{part} in experiments. Preliminary HADES data show significant differences to both, UrQMD simulations and STAR data in this respect.

A recursive system identification inertia estimator for traditional and converter-interfaced generators

This paper proposes a method to estimate the inertia constant of synchronous generators (SGs) and the virtual inertia provided by converter-interfaced generators (CIGs). It can be applied when the system is under normal operating conditions or after power imbalance events. The algorithm is based on a recursive system identification approach and uses the active power and bus frequency measurements proceeding from phasor measurement units. The measurements are preprocessed to improve the estimation accuracy. Subsequently, a model-independent rotor speed estimator is used to compute rotor speed variations (or internal frequency variations, in the case of CIGs). Afterwards, a recursive least-square equation error formulation is implemented to compute the SG and CIG parameters in the z-domain, which are later converted into their respective counterparts in the s-domain. The method is applied to several generation devices in the IEEE 39-bus and IEEE 118-bus test systems, including traditional SGs and CIGs providing virtual inertia. Numerical results show the accuracy and the low computational burden of the proposed method.

A Method to Estimate the Primary Mass of Ultrahigh-energy Cosmic Rays from Measurements of the Depth of the Shower Maximum and the Muon Content

The origin and mass composition of ultrahigh-energy cosmic rays is one of the big open questions of modern physics. Estimating the mass of ultrahigh-energy cosmic rays always involves the comparison of data with simulations using hadronic interaction models. The state-of-the-art hadronic interaction models, however, fail to agree with each other on the expected depths of the shower maxima, and on the average number of muons produced in air showers initiated by the same primary particles. Thus the interpretation of data in terms of the primary masses of cosmic rays differs depending on which hadronic interaction model is considered as a reference. Good agreement, however, can be found in the implications from hadronic interaction models in the prediction of the change of the average depth of the shower maximum and in the relative change in the number of produced muons as a function of the nuclear mass of the primary cosmic ray. Considering these, a model-independent estimation of the primary mass of ultrahigh-energy cosmic rays can be given in relative terms. In this work we propose a method to estimate the primary mass of ultrahigh-energy cosmic rays from the depth of the shower maximum and the number of muons produced in the shower, utilizing the similarities of modern hadronic interaction models. We discuss a geometric approach that combines the depth of the shower maximum and the number of muons produced in a shower to estimate the mass of the primary particle.

Nested hydrological modeling for flood prediction using CMIP6 inputs around Lake Tana, Ethiopia

Study regionTana basin is the origin of the Blue Nile Basin located in Ethiopia. The Lake Tana’s mean annual precipitation is approximately 1400 mm/yr and its outflow drains an area of about 15,096 km2. There is limited effort to apply nested hydrological models for flood prediction due to being poorly gauged for validation. Study focusThe objective of this study is to show how climate simulations can be used to generate reliable local predictions of flood and runoff for the Blue Nile in the Ethiopian highlands.In this study, outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to initialize a nested hydrological model to reveal long-term trends of runoff in flood-prone areas of the Lake Tana basin, Ethiopia. Available satellite and reanalysis datasets were used for selection of CMIP6 products and the five models with best validation were used to force a nested hydrological model: Known as Wflow_sbm. A model-independent multi-algorithm optimization estimation tool was implemented for calibration of Wflow with insitu observations. New hydrological insights for the regionIn terms of simulating runoff and flood events, application of Wflow_sbm to the Lake Tana basin gave promising results. This study serves as a major step towards the development and implementation of global model-driven nested hydrological assessments of flood risk in future projections for Lake Tana basin.

Revisiting the Hubble Constant, Spatial Curvature, and Cosmography with Strongly Lensed Quasar and Hubble Parameter Observations

It is well known that time delays due to strong lensing offer the opportunity of a one-step measurement of the Hubble constant H 0 that is independent of the cosmic distance ladder. In this paper, we go further and propose a cosmological model-independent approach to simultaneously determine the Hubble constant and cosmic curvature with measurements of the time delay due to strong lensing, without any prior assumptions regarding the content of the universe. The data we use comprise the recent compilation of six well studied strongly lensed quasars, while the cosmic chronometer data are utilized to reconstruct distances via cosmographic parameters. In the framework of third-order Taylor expansion and (2, 1) order Padé approximation for cosmographic analysis, our results provide model-independent estimations of the Hubble constant and , which are well consistent with that derived from the local distance ladder by the SH0ES collaboration. The measured cosmic curvature and shows that zero spatial curvature is supported by the current observations of time delays due to strong lensing and cosmic chronometers. Imposing the prior of spatial flatness leads to more precise (at 1.6% level) determinations of the Hubble constant and , values located between the results from Planck and the SH0ES collaboration. If a prior of local (SH0ES) H 0 measurement is adopted, the constraint on curvature parameter can be further improved to and , supporting no significant deviation from a flat universe. Finally, we also discuss the effectiveness of the Padé approximation in reconstructing the cosmic expansion history for redshifts up to z ∼ 2.3, considering its better performance in the Bayes information criterion.

Specifying the hydrogeological parameters range for a groundwater flow model in El-Qaa Plain aquifer, Sinai, Egypt

Hydrogeological parameters are very uncertain to specify in the groundwater flow models. Hence, it is important to specify a range for these parameters to be further utilized by the groundwater model users. In El-Qaa Plain, previous researchers have determined the hydrogeological parameters such as transmissivity, hydraulic conductivity, and mean annual recharge rate using geophysical methods, pumping tests, hydrological models, and groundwater flow models. However, they are also limited to specific locations and do not spatially distribute. In this paper, an effort has been accomplished to specify a specific range for the aquifer hydrogeological parameters using inverse groundwater modeling taking into account the spatial heterogeneity. These ranges could be taken into consideration during modeling groundwater flow. Hence, a finite-difference groundwater flow model has been applied using the ModFLOW model. Regularized pilot points method (RPPM) has been chosen as an inverse modeling technique to specify the accurate values of the aquifer parameters. Model-independent parameter estimation and uncertainty analysis (PEST) has been utilized to estimate the parameters. The results show that the geometric mean of the hydraulic conductivity in the study area ranges from proximity 1 to 2 m/day. Additionally, the geometric mean of the transmissivity ranges from nearly 200 to 500 m2/day. A relationship between the mean annual recharge rate and hydrogeological parameters has been determined. Besides, maps have been generated showing the spatial heterogeneity of the hydraulic conductivity. These maps could be further utilized by groundwater flow modelers to predict the potential of groundwater flow and pollution in the future.

Compositeness of S-wave weakly-bound states from next-to-leading order Weinberg’s relations

We discuss a model-independent estimator of the likelihood of the compositeness of a shallow S-wave bound or virtual state. The approach is based on an extension of Weinberg’s relations in Weinberg (Phys Rev 137:B672, 1965) and it relies only on the proximity of the energy of the state to the two-hadron threshold to which it significantly couples. The scheme only makes use of the experimental scattering length and the effective range low energy parameters, and it is shown to be fully consistent for predominantly molecular hadrons. As explicit applications, we analyse the case of the deuteron, the ^1mathrm{S}_0 nucleon-nucleon virtual state and the exotic D^{*}_{s0}(2317)^pm , and find strong support to the molecular interpretation in all cases. Results are less conclusive for the D^{*}_{s0}(2317)^pm , since the binding energy of this state would be significantly higher than that of the deuteron, and the approach employed here is at the limit of its applicability. We also qualitatively address the case of the recently discovered T_{cc}^+ state, within the isospin limit to avoid the complexity of the very close thresholds D^0D^{*+} and D^+D^{*0}, which could mask the ingredients of the approach proposed in this work.

A foreground model independent estimation of joint posterior of CMB E-mode polarization over large angular scales

The advent of precision cosmology has led to a very accurate observational data. In order to extract cosmological information, we therefore need robust and accurate Cosmic Microwave Background (CMB) reconstruction techniques with reliable statistical error estimates associated with them. We show the performance of our algorithm using simulations of the future Probe of Inflation and Cosmic Origins (PICO) missions. To generate samples from the joint distribution, we employ the internal linear combination (ILC) technique with prior information of CMB E-mode covariance matrix augmented by a Gibbs sampling technique of Sudevan and Saha 2020. We estimate the marginalized densities of [Formula: see text] and [Formula: see text] using the samples from full-posterior. The best-fit cleaned E-mode map and the corresponding angular power spectrum are consistent with the input E-mode map and the sky power spectrum implying accurate reconstruction. Using the samples [Formula: see text] of all Gibbs chains, we estimate the likelihood function [Formula: see text]) of any arbitrary [Formula: see text] given simulated observed maps (data, D) of PICO mission using a Blackwell–Rao estimator. The likelihood function can be seamlessly integrated to the cosmological parameter estimation method. Apart from producing an accurate estimate of E-mode signal over large angular scales, our method also builds a connection between the component reconstruction and reliable cosmological parameter estimation using CMB E-mode observations over large angular scales. The entire method does not assume any explicit models for E-mode foreground components in order to remove them, which is an attractive property since foreground modeling uncertainty does not pose as a challenge in this case.

A Dynamic Calibration of Optical Fiber DTS Measurements Using PEST and Reference Thermometers.

Temperature measurements are widely used in structural health monitoring. Optical fiber distributed temperature sensors (DTS) are developed, based on Raman spectroscopy, to measure temperature with relatively high accuracy and short temporal and spatial resolutions. DTS systems provide an extensive number of temperature measurements along the entire length of an optical fiber that can be extended to tens of kilometers. The efficiency of the temperature measurement strongly depends on the calibration of the DTS data. Although DTS systems internally calibrate the data, manual calibration techniques were developed to achieve more accurate results. Manual calibration employs reference sections or points with known temperatures and the DTS scattering data to estimate the calibration parameters and calculate temperature along the optical fiber. In some applications, manual calibration is subjected to some shortages, based on the proposed fiber installation configuration and continuity of calibration. In this article, the manual calibration approach was developed using the model-independent Parameters Estimation (PEST), together with the external temperature sensors as references for the DTS system. The proposed method improved manual calibration in terms of installation configuration, continuity of dynamic calibration, and estimation of the calibration parameters.

Model-Independent Observer-Based Current Sensorless Speed Servo Systems with Adaptive Feedback Gain

This study proposes a solution to the speed control problem of servo machines in the form of multi-loop current sensorless control with a reduction in the system model dependence level and the number of feedback loops, which provides the two contributions: first, a model-independent observer estimates speed and acceleration using only the position measurement, thereby ensuring the first-order estimation error dynamics; second, the active damping acceleration stabilizes the inner loop with the adaptive feedback gain increasing and decreasing automatically according to the transient and steady-state operation modes. The experimental study highlighted the effectiveness of the acceleration loop adaptation technique, which used an actual servo system comprising the QUBE-servo2 and myRIO-1900.

Mixed forest specific calibration of the 3-PGmix model parameters from site observations to predict post-fire forest regrowth

Fire disturbance has been one of the main reasons for the alteration of forest succession trajectory and forest composition in the Daxing’anling Mountain of Inner Mongolia. Therefore, predicting the dynamic process of post-fire regrowth is critical for understanding the specific forest succession trajectory of this region. The 3-PGmix model (i.e., Physiological Principles in Predicting Growth for mixed stands) has been reported as a powerful tool for predicting the growth of mixed forest species. However, simulating post-fire regrowth of mixed forest with 3-PGmix remains challenging due to the uncertainty of species-specific as well as site-specific model parameters. Based on the field measurements from a wide range of environmental conditions, the 3-PGmix model was calibrated by conducting the sensitivity analysis and optimization of species-specific parameters for mixed forest stands of larch (Larix gmelinii) and birch (Betula platyphylla) with the PEST model (Model-Independent Parameter Estimation), and by using our newly developed methods to accurately estimating site-specific parameters (e.g., fertility rating, stand density, climate factors). The calibrated 3-PGmix model was tested against the independent sites and predicted the characteristic of post-fire forest regrowth. The sensitivity analysis shows that the parameters describing the forest canopy are more sensitive to the objective function of the PEST model. The calibrated 3-PGmix model performed well on independent sites, resulting in agreement with the field-measured diameter at breast height (DBH), the biomass of components, and stand density with a bias of less than 15% on most sites. The 3-PGmix model prediction of post-fire forest recovery characteristics found that the highest recovery rate of 5.5% per year was predicted from the moderate burn severity scenarios. A higher fertility rating was predicted to accelerate the process of post-fire forest successional and shorten the duration time when the species proportion achieves balance. The mixed-forest specific calibration of the 3-PGmix model in this study enables the explicit prediction of post-fire forest succession, and more simulations over different spatial scales with a wide range of environmental conditions by coupling with remote sensing observations can be expected.

Exploring the Hubble Tension and Spatial Curvature from the Ages of Old Astrophysical Objects

Abstract We use the age measurements of 114 old astrophysical objects (OAO) in the redshift range 0 ≲ z ≲ 8 to explore the Hubble tension. The age of the universe at any z is inversely proportional to the Hubble constant, H 0, so requiring the universe to be older than the OAO it contains at any z will lead to an upper limit on H 0. Assuming flat ΛCDM and setting a Gaussian prior on the matter density parameter Ωm = 0.315 ± 0.007 informed by Planck, we obtain a 95% confidence level upper limit of H 0 < 70.6 km s−1 Mpc−1, representing a 2σ tension with the measurement using the local distance ladder. We find, however, that the inferred upper limit on H 0 depends quite sensitively on the prior for Ωm, and the Hubble tension between early-time and local measurements of H 0 may be due in part to the inference of both Ωm and H 0 in Planck, while the local measurement uses only H 0. The age-redshift data may also be used for cosmological model comparisons. We find that the R h = ct universe accounts well for the data, with a reasonable upper limit on H 0, while Einstein–de Sitter fails to pass the cosmic-age test. Finally, we present a model-independent estimate of the spatial curvature using the ages of 61 galaxies and the luminosity distances of 1048 Pantheon Type Ia supernovae. This analysis suggests that the geometry of the universe is marginally consistent with spatial flatness at a confidence level of 1.6σ, characterized as Ω k = 0.43 − 0.27 + 0.27 .