Fundamental Measure Research Articles

Capturing autonomy, competence, and relatedness at work: further examining and validating an English language version of the work-related basic need satisfaction scale

Self-Determination Theory (SDT) maintains that the satisfaction of the basic psychological needs for autonomy, competence, and relatedness is associated with optimal individual functioning, including in the workplace. A self-report instrument, the Work-related Basic Need Satisfaction scale (W-BNS), has previously been developed and validated in Dutch and Italian. We aimed to validate an English version of the W-BNS. We also evaluated a bifactor model to assess the extent to which the item responses could be explained by a single, underlying general latent trait. A Rasch calibration was also carried out to assess the extent to which the scores conformed to the assumptions of ‘fundamental measurement’ and could be converted to a common metric. We used data from 141 staff employed by a large UK-based mental health service provider. The postulated three-factor structure provided a good fit to the data. However, a bifactor model, introducing an underlying general factor, provided a superior fit. The items generally conformed to the Rasch measurement model. Evidence of convergent/divergent validity was observed via the correlations between the W-BNS scores and those for the Basic Psychological Needs Satisfaction and Frustration Scale (BPNFS). Regarding construct validity, both the separate needs and total W-BNS scores statistically significantly predicted an individual’s reported intention to leave the current employer. Our findings foster research with the WBNS and have implications for how the W-BNS is optimally implemented in practice as a useful brief tool for assessing staff work-related need satisfaction.

Construction and Optimization Strategies for Rural Residential Spatial Models Based on the Concept of Resource Metabolism: A Case Study of Rural Areas in the Shandong Plain

Rural communities can be conceptualized as spatial organisms interconnected by optimized resource utilization systems. Investigating the efficient utilization of rural resources and spatial construction methods grounded in resource metabolism is a pivotal step toward achieving the ecological transformation of rural spaces. This paper examined rural settlements in the Shandong Plain as a case study, exploring the relationships among three scales: village, neighborhoods, and courtyards. This analysis was based on elucidating the interaction mechanisms between “space and resource” and the integration of key resources and spatial elements. From the perspective of resource circulation and metabolism, this study aimed to elucidate the equilibrium of each resource element within three resource metabolism subsystems: the agricultural production system (core element), the ecological technology system (technological link), and the human life system (spatial carrier) in Shandong Plain’s villages, considering general climatic conditions. To achieve this, this research utilized the resource production volume, the utilization and transformation volume of resource metabolism technology facilities per unit area, and the average per capita resource consumption as fundamental measurement units. The concept of a rationing relationship is introduced to clarify resource allocation. Combining the aforementioned research on spatial resource metabolism in ecological villages in Shandong Province with the material flow analysis method, this study constructed a bottom–up spatial model of resource metabolism at three scales, courtyards, neighborhoods, and villages, under various resource metabolism scenarios. This study is anticipated to significantly contribute to the theoretical understanding of rural habitat environments, offering novel methods and perspectives for constructing ecological rural settlements.

Web-based vs. conventional: a comprehensive analysis of visual acuity assessment using the PocDoc tool in a tertiary eye care centre.

Visual acuity (VA) represents a fundamental measure of visual function. The significant prevalence of underdiagnosed ocular disorders underscores the importance of effective VA assessment. This study evaluates the efficacy of a web-based VA assessment tool ("PocDoc") versus conventional VA testing. Prospective observational study including 353 participants recruited from various eye clinics in a tertiary referral centre. Age, diagnosis, and VA related information (i.e. VA measurements from PocDoc and conventional VA test [Snellen chart], test type, etc) were collected. Spearman's rank correlation, Intraclass Correlation, and Bland-Altman plot compared outcomes of both tests. One-way ANOVA and paired-T test were used to compare means. Most patients were males (59.2%) with a mean age of 52.2 ± 20.6 years. PocDoc had moderate positive correlation to conventional testing (rho = 0.50, p < 0.001). PocDoc led to higher logMAR scores compared to conventional testing (mean logMAR 0.19 and 0.13 respectively, p < 0.01). Moreover, PocDoc demonstrated a sensitivity of 82.8% and specificity of 79% for detecting visual impairment. The discrepancy between PocDoc and conventional VA testing increased with higher logMAR values, indicating greater inconsistency between the tests for patients with poorer VA. Age, test type, and disease type contributed to this variability. The concordance between PocDoc and conventional testing for VA measurement across various ages and conditions makes it a suitable screening tool. Future technological inventions should consider age, test type, and disease type as critical factors related to the level of agreement and correlation between digital and conventional VA testing methods.

Purifying Selection Influences the Comparison of Heterozygosities between Populations.

Heterozygosity is a fundamental measure routinely used to compare between populations to infer the level of genetic variation and their relative effective population sizes. However, such comparison is highly influenced by the magnitude of selection pressure on the genomic regions used. Using over 2 million Single Nucleotide Variants (SNVs) from chimpanzee and mouse populations, this study shows that the heterozygosities estimated using neutrally evolving sites of large populations were two times higher than those of small populations. However, this difference was only ~1.6 times for the heterozygosities estimated using nonsynonymous sites. This suggests an excess in the nonsynonymous heterozygosities due to the segregation of deleterious variants in small populations. This excess in the nonsynonymous heterozygosities of the small populations was estimated to be 23-31%. Further analysis revealed that the magnitude of the excess is modulated by effective population size (Ne) and selection intensity (s). Using chimpanzee populations, this investigation found that the excess in nonsynonymous diversity in the small population was little (6%) when the difference between the Ne values of large and small populations was small (2.4 times). Conversely, this was high (23%) when the difference in Ne was large (5.9 times). Analysis using mouse populations showed that the excess in the nonsynonymous diversity of highly constrained genes of the small population was much higher (38%) than that observed for the genes under relaxed selective constraints (21%). Similar results were observed when the expression levels of genes were used as a proxy for selection intensity. These results emphasize the use of neutral regions, less constrained genes, or lowly expressed genes when comparing the heterozygosities between populations.

Density functional theory for responsive hard-sphere fluids

We investigate the equilibrium properties of responsive hard-sphere fluids, where the particle size is a coarse-grained property that fluctuates within an internal free-energy landscape, responding to changes in concentration or the application of external fields. For this purpose, we employ a generalised density functional theory for responsive colloids based on the fundamental measure theory for polydisperse hard-sphere mixtures. We find that increasing particle softness yields a substantial reduction in mean particle size, volume fraction and pressure. We also examine the density profiles and size segregation of responsive hard-sphere fluids subjected to three representative external potentials: a planar hard wall, gravitational and Archimedes buoyant fields. We observe that increasing stiffness or particle concentration enhances density oscillations, converging to the behaviour of a monodisperse fluid. In a gravitational field, size segregation occurs, with smaller particles accumulating at the bottom due to sedimentation. This effect is more pronounced when the Archimedes force is included, causing larger colloids to accumulate at the top, leading to density oscillations in this region that intensify with particle softness, an effect not observed in monodisperse systems. Finally, we demonstrate that responsiveness leads to distinct behaviour compared to conventional polydisperse non-responsive fluids, in which particle compression is not allowed.

The disruption index is biased by citation inflation

Abstract A recent analysis of scientific publication and patent citation networks by Park et al. (Nature, 2023) suggests that publications and patents are becoming less disruptive over time. Here we show that the reported decrease in disruptiveness is an artifact of systematic shifts in the structure of citation networks unrelated to innovation system capacity. Instead, the decline is attributable to ‘citation inflation’, an unavoidable characteristic of real citation networks that manifests as a systematic time-dependent bias and renders cross-temporal analysis challenging. One driver of citation inflation is the ever-increasing lengths of reference lists over time, which in turn increases the density of links in citation networks, and causes the disruption index to converge to 0. The impact of this systematic bias further stymies efforts to correlate disruption to other measures that are also time-dependent, such as team size and citation counts. In order to demonstrate this fundamental measurement problem, we present three complementary lines of critique (deductive, empirical and computational modeling), and also make available an ensemble of synthetic citation networks that can be used to test alternative citation-based indices for systematic bias. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_a_00333

Digitally accessible space: Discovery of the distinctive locational characteristics of restaurants with online reservation

The widespread adoption of ICT including mobile apps and their online services has significantly reshaped human activities in urban spaces. The complex interaction between ICT on urban space presents challenges in understanding their relationships. This study aims to discover the empirical evidence of the spatial variance of urban space linked to ICT. To pursue this objective, this study defines spaces that leverage ICT-based activities as Digitally Accessible Spaces (DAS), and choose restaurants that provide online reservation services through NAVER, which is the most dominant search engine in South Korea. Based on fundamental measurements in location theory, we stratified the entire area in Seoul into four groups in order of profitability. Using the location quotient (LQ), we quantified the locational characteristics of DAS compared to overall restaurants. Consequently, three measurements, which are density of marketplace, distance from public transit, and proper land use, indicate that the second-tier profitable areas commonly possess the largest portion of DAS. These characteristics provided empirical evidence supporting previous studies highlighting the liberation effect and altered travel behavior resulting from ICT-based activity through qualitative and theoretical approaches. We expect that this study can contribute to further research related to the interaction between digital space and physical space.

Data-Driven Modeling of DC–DC Power Converters

This article presents a data-driven methodology for modeling DC–DC power electronic converters. Using the proposed methodology, the dynamics of a converter can be captured, thereby eliminating the need for explicit theoretical modeling methods. This approach only requires the acquisition of fundamental measurements: currents through inductors and voltages across capacitors. The acquired data are used to construct a linear difference system, which is algebraically manipulated to form a state–space representation of the converter under analysis. Three DC–DC converter topologies were analyzed, and their resulting models were tested and compared with simulation data, yielding an average error deviation of approximately 2% for current signals and 4% for voltage signals, demonstrating precise tracking of the actual dynamics. The proposed data-driven methodology could simplify the implementation of adaptive control strategies in larger-scale solutions or in the interconnection of multiple converters.

Fingerprints of ordered self-assembled structures in the liquid phase of a hard-core, square-shoulder system.

We investigate the phase ordering (pattern formation) of systems of two-dimensional core-shell particles using Monte Carlo (MC) computer simulations and classical density functional theory (DFT). The particles interact via a pair potential having a hard core and a repulsive square shoulder. Our simulations show that on cooling, the liquid state structure becomes increasingly characterized by long wavelength density modulations and on further cooling forms a variety of other phases, including clustered, striped, and other patterned phases. In DFT, the hard core part of the potential is treated using either fundamental measure theory or a simple local density approximation, whereas the soft shoulder is treated using the random phase approximation. The different DFTs are benchmarked using large-scale grand-canonical-MC and Gibbs-ensemble-MC simulations, demonstrating their predictive capabilities and shortcomings. We find that having the liquid state static structure factor S(k) for wavenumber k is sufficient to identify the Fourier modes governing both the liquid and solid phases. This allows us to identify from easier-to-obtain liquid state data the wavenumbers relevant to the periodic phases and to predict roughly where in the phase diagram these patterned phases arise.

The Design and Validation of a High-Precision Angular Vibration Calibration System Based on a Laser Vibrometer.

This paper presents the design and validation of a high-precision angular vibration calibration system based on a laser vibrometer, aimed at meeting the high-precision requirements for measuring small angular vibrations. The system primarily consists of a self-driving angular vibration platform and a laser vibrometer. The platform is isolated from ground interference via an air-floating platform and uses a split-type motor to control the platform, generating specific angular vibrations. Detailed simulations of the platform's modal characteristics and the stability of the spring plates were conducted using the finite element analysis software ANSYS 11. Moreover, fundamental frequency testing and measurement accuracy testing were conducted on the system. Experimental results demonstrate that the system has a fundamental frequency of 2.69 Hz and a maximum measurement error of 0.00172″, confirming the system's effectiveness in dynamic characteristics, stability, and measurement accuracy. This research provides essential technical support for high-precision angular vibration control in spacecraft.

A multidisciplinary approach for the evaluation of the archaeological heritage of Borbona (Rieti, Italy)

The area of Borbona (Rieti, Italy) has been sparsely researched from a historical and archaeological perspective. In order to obtain new data on unexplored areas, a systematic study was carried out combining archaeological explorations, photogrammetric surveys and geophysical prospections. All data was stored in a Geographic Information System, which enabled spatial analysis and the creation of thematic maps. The aim of the research was to discover the unknown territory and trace its origins. The project identified ancient habitats and significant Roman architectural fragments. The research aims to pass on the history and culture of Borbona to future generations and promote a sense of belonging. The protection of historical heritage and archaeologically endangered areas as well as the enhancement and promotion of existing cultural assets are fundamental measures to increase the attractiveness of the land in the present and preserve its identity in the future.

Epidemiological analysis of a 10-year retrospective study of pediatric trauma in intensive care

Pediatric trauma plays a crucial role in pediatric mortality, with traffic injuries and falls frequently cited as leading causes of significant injuries among children. A comprehensive investigation, including geographical factors, is essential for developing effective strategies to prevent injuries and alleviate the burden of pediatric trauma. This study involved a retrospective analysis of clinical data from pediatric patients admitted to our hospital’s intensive care unit (ICU) due to trauma over a 10-year period. Comprehensive analyses were conducted to elucidate trends, demographics, injury patterns, and risk factors associated with these admissions. This retrospective study included 951 pediatric patients (mean age: 4.79 ± 3.24 years; mean weight: 18.45 ± 9.02 kg; median time to ICU admission post-injury: 10.86 ± 14.95 h). Among these patients, 422 (44.4%) underwent emergency surgery, and 466 (49%) required mechanical ventilation support, with a mean duration of 70.19 ± 146.62 h. The mean duration of ICU stay was 6.24 ± 8.01 days, and the overall mean hospitalization duration was 16.08 ± 15.56 days. The predominant cause of unintentional injury was traffic accidents (47.9%), followed by falls (42.5%) and burns/scalds (5.3%). Most incidents involved children aged 0–6 years (70.7%), with males comprising 60.0% of patients. Injury incidents predominantly occurred between 12 and 6 PM (44.5%) and on non-workdays (37.6%). The most common locations where injuries occurred were roadsides (49%) and rural areas (64.35%). Single-site injuries (58.78%) were more prevalent than multiple-site injuries (41.22%), and head injuries were the most common among single-site injuries (81.57%). At ICU admission, the mean injury severity score was 18.49 ± 8.86. Following active intervention, 871 patients (91.59%) showed improvement, while 80 (8.41%) succumbed to their injuries. Traffic injuries remain the primary cause of pediatric trauma leading to ICU admission, underscoring the importance of using appropriate child restraint systems and protective gear as fundamental preventive measures. The increased incidence of injuries among children aged < 6 years and those residing in rural areas highlights the need for targeted preventive strategies, necessitating tailored interventions and public policy formulations that address these high-risk populations.

The correlation between job stress, burnout, and cognitive performance in Iranian firefighters: A cross-sectional study.

Appropriate cognitive performance is vital for a firefighter, but many occupational factors can negatively affect it. This study assessed the correlation between job stress, burnout, and cognitive performance in firefighters. This descriptive-correlational study was conducted in three fire stations in Iran in 2023 with 61 participants, including 34 firefighters in the exposed group and 27 office workers in the control group. After ensuring the confidentiality of the obtained information and completing the demographic information checklist, Job stress and burnout levels were measured using standardized questionnaires, and cognitive functions were assessed using two computerized tests: Stroop and continuous performance. The mean age and work experience of firefighters were 33.29±9.44 and 10.42±3.51 years, respectively. The firefighters' job stress and burnout levels were, on average, 163.12±9.18 and 88.89±4.28, respectively, significantly higher than those of the control group (P < 0.05). The results of the Pearson correlation test revealed a strong correlation (r = 0.719) between job stress and burnout. Pearson correlation coefficient (r = -0.512-0.757), yielded from psychological tests, demonstrated that firefighters' job stress and burnout had moderate to strong associations with certain indicators of Stroop and continuous performance tests. According to the obtained results, it is recommended to take fundamental measures to reduce occupational stress and burnout of firefighters as a factor affecting cognitive performance.

Determining the Speed Reaction Time to the Lower Limbs in a Women’ a Volleyball Team (CSU Medicina Tg. Mures)

Speed reaction is an important concept in various fields like physiology, psychology and sports science. It refers to the time it takes to respond to a specific stimulus visual, auditory, tactile. Reaction speed is an important and fundamental measure in the study of human performance and cognitive processes. Methods. The testing was conducted on the female volleyball players, members of the CSU Medicine Târgu Mureș team. This testing took place at the beginning of the 2023-2024 competitive season. Objective. The objectives of this study are to identify the reaction time values obtained during the testing of the CSU Medicine Târgu Mureș team. Results. The analysis of the results was conducted after downloading the data from the Optojump software as follows: Test 1 Range: 0.532 - 0.393 = 0.139 seconds, test 2. Range: 0.531 - 0.425 = 0.106 seconds Test 3 Range: 0.750 - 0.597 = 0.153 seconds Conclusion. This statement suggests that, based on the data collected from the three tests, there is consistency in the performance of individual subjects. Some subjects consistently have low reaction speed values across all three tests, while others consistently have high reaction speed values. Keywords: Volleyball, Optojump, Speed Reaction

Stress-controlled medium-amplitude oscillatory shear (MAOStress) of PVA–Borax

We report the first-ever complete measurement of MAOStress material functions, which reveal that stress can be more fundamental than strain or strain rate for understanding linearity limits as a function of Deborah number. The material used is a canonical viscoelastic liquid with a single dominant relaxation time: polyvinyl alcohol (PVA) polymer solution cross-linked with tetrahydroborate (Borax) solution. We outline experimental limit lines and their dependence on geometry and test conditions. These MAOStress measurements enable us to observe the frequency dependence of the weakly nonlinear deviation as a function of stress amplitude. The observed features of MAOStress material functions are distinctly simpler than MAOStrain, where the frequency dependence is much more dramatic. The strain-stiffening transient network model was used to derive a model-informed normalization of the nonlinear material functions that accounts for their scaling with linear material properties. Moreover, we compare the frequency dependence of the critical stress, strain, and strain-rate for the linearity limit, which are rigorously computed from the MAOStress and MAOStrain material functions. While critical strain and strain-rate change by orders of magnitude throughout the Deborah number range, critical stress changes by a factor of about 2, showing that stress is a more fundamental measure of nonlinearity strength. This work extends the experimental accessibility of the weakly nonlinear regime to stress-controlled instruments and deformations, which reveal material physics beyond linear viscoelasticity but at conditions that are accessible to theory and detailed simulation.

Predicting Hydrocarbon Strain Energy via a Group Equivalent Machine Learning Approach.

Strain energy is a fundamental measure of the steric and configurational properties of organic molecules. The ability to estimate strain energy through quantum chemical simulations requires at minimum the knowledge of an initial set of nuclear coordinates. In general, such knowledge is not categorically known when screening or generating large numbers of molecule candidates in the context of molecular design. We present a machine learning approach to predict hydrocarbon strain energies using Benson group equivalents. A featurization strategy is crafted by concatenating the molecule group equivalent counts with easily computable molecular fingerprints. The data are obtained from electronic structure calculations we performed on a set of 166 previously synthesized strained hydrocarbons. These data are provided and include gas phase enthalpies of formation and associated optimized atomic coordinates. The strain energy prediction accuracy of several statistical learning methods is evaluated, and their respective merits and limitations are discussed.

Exploring Probability of Detection (POD) Analysis in Nondestructive Testing: A Comprehensive Review and Potential Applications in Phased Array Ultrasonic Corrosion Mapping

In nondestructive testing (NDT), ensuring defect detection, measurement accuracy, and reliability guarantees various components’ structural integrity and safety. The Probability of Detection (POD) concept has emerged as a fundamental measure of the effectiveness of an inspection technique in identifying defects. Since NDT plays a crucial role in aerospace, manufacturing, and infrastructure industries, enhancing POD has become critical. POD refers to the likelihood that a flaw or defect of a certain size will be detected using the NDT technique. The “â versus a” and the “hit/miss” methods are particularly notable among the commonly employed POD estimation methods. The POD curve is determined based on crack size measurements in the “â versus a” approach, typically used in ultrasonic testing. On the other hand, the “hit/miss” method establishes the POD curve by analysing binary outcomes, where a “hit” signifies successful detection and a “miss” denotes detection failure. This review focuses on POD in the context of NDT, specifically in phased array ultrasonic corrosion mapping (PAUCM), to uncover current uncertainty parameters and explore an innovative avenue for enhancing POD assessment by incorporating the material surface temperature as an additional parameter.

Material Changes of Bimetallic Ag–Cr, Fe, Co, Ni, Cu, Sn Electrocatalysts during Alkaline Oxygen Reduction in Fundamental Versus Alkaline Membrane Exchange Fuel Cell Conditions

The more apparent challenges of climate change drastically increase the global demand for sustainable fuel production and usage.1 In this context, hydrogen fuel cells (FCs) powered by renewable electricity are among the promising technologies.2 Addressing the sluggish cathode reaction in FCs, the oxygen reduction reaction (ORR), these devices hold immense potential for sustainable energy conversion and storage. An alkaline environment allows for the utilization of more abundant and cost-effective metals in contrast to current platinum-based catalysts. Silver (Ag), for instance, exhibits high selectivity for the ORR, i.e., forming hydroxide instead of peroxide.3 When combined with secondary metals, bimetallic Ag catalysts show enhanced activity, making them viable alternatives to platinum-group materials for ORR.In our highly collaborative research, we investigated the material transformations of bimetallic Ag thin films with chromium (Cr), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), and tin (Sn) as secondary metals for ORR electrocatalysis in fundamental rotating disk electrode (RDE) setups and the application device, anion-exchange membrane FC (AEMFC). Grazing-incidence X-ray diffraction (GI-XRD) conducted prior to electrochemical testing reveals no evidence of alloying except for the Ag-Sn bimetallic thin film. However, X-ray photoelectron spectroscopy (XPS) indicates a shift of the Ag 3d peaks to higher binding energies for all catalysts, suggesting a hybridization of Ag and the secondary metals. The composition of the metal surface, native oxide formation, ORR performance, and material changes post-RDE testing vary distinctly among the Ag bimetallic catalysts depending on the secondary metal. Intriguingly, performance is either enhanced (Ag-Co, Ag-Sn), maintained with reduced Ag content (Ag-Fe, Ag-Cr), or falls in between the two monometallic materials (Ag-Ni) compared to monometallic Ag thin films. Density functional theory (DFT) calculations offer insights into the catalyst performances and changes in metal oxidation states and surface composition prior and post electrocatalysis. AEMFC tests reveal promising performances under device conditions contradicting our fundamental RDE measurements. The integration of fundamental and application device tests, along with material characterization and DFT calculations, enables a comprehensive exploration of material changes under varying electrochemical conditions. This underscores the complexity of bimetallic catalysts and the importance of testing under device conditions, positioning Ag-bimetallic catalysts as highly promising alternatives to platinum-group metal catalysts for alkaline ORR.

Research on the outdoor thermal comfort of children in Hangzhou and Its influence on the underlying surface reflectance.

The outdoor thermal comfort (OTC) of children is more specific than that of adults, and the complex influence of outdoor activity spaces on children's thermal comfort warrants further investigation. To investigate the outdoor thermal comfort baseline (OTCB) of children in Hangzhou and explore the thermal impact of outdoor surfaces on children, a survey was conducted in six typical outdoor activity spaces in Hangzhou, China, during spring and summer utilizing physical measurements, questionnaire surveys, and the universal thermal climate index (UTCI). This study analyzed the differences in thermal perception among children in Hangzhou in different seasons, their OTCB, and the impact of surface reflectance (Rs) on children's OTC. The results indicated the following: 1) In spring, children in Hangzhou generally felt comfortable, but their discomfort with heat noticeably increased in summer. 2) The neutral UTCIs (NUTCIs) for Hangzhou children were 11.6°C (spring) and 27.7°C (summer), and the NUTCI ranges (NUTCIRs) were 9.7-17.5°C (spring) and 25.7-30.0°C (summer); additionally, the thermal acceptability ranges (TARs) were 13.2-25.2°C (spring) and 11.8-34.8°C (summer). 3) A high Rs made children feel more uncomfortable with heat, which was primarily due to the space's total shortwave and longwave radiation, which peaked between 14:00 and 15:00. 4) Based on the research findings, corresponding bioclimatic design strategies were proposed. Recommendations include using high Rs underlays with shading, composite underlays, or the future adoption of thermochromic coatings. Keeping permeable underlays moist is essential for activating their cooling mechanisms. Fundamental safety measures are imperative. This study provides valuable data for urban planners and landscape designers to create public spaces suitable for children's outdoor activities, contributing to a harmonious and unified living environment.

Toward Low‐Latency Estimation of Atmospheric CO2 Growth Rates Using Satellite Observations: Evaluating Sampling Errors of Satellite and In Situ Observing Approaches

AbstractThe atmospheric CO2 growth rate is a fundamental measure of climate forcing. NOAA's growth rate estimates, derived from in situ observations at the marine boundary layer (MBL), serve as the benchmark in policy and science. However, NOAA's MBL‐based method encounters challenges in accurately estimating the whole‐atmosphere CO2 growth rate at sub‐annual scales. Here we introduce the Growth Rate from Satellite Observations (GRESO) method as a complementary approach to estimate the whole‐atmosphere CO2 growth rate utilizing satellite data. Satellite CO2 observations offer extensive atmospheric coverage that extends the capability of the current NOAA benchmark. We assess the sampling errors of the GRESO and NOAA methods using 10 atmospheric transport model simulations. The simulations generate synthetic OCO‐2 satellite and NOAA MBL data for calculating CO2 growth rates, which are compared against the global sum of carbon fluxes used as model inputs. We find good performance for the NOAA method (R = 0.93, RMSE = 0.12 ppm year−1 or 0.25 PgC year−1). GRESO demonstrates lower sampling errors (R = 1.00; RMSE = 0.04 ppm year−1 or 0.09 PgC year−1). Additionally, GRESO shows better performance at monthly scales than the NOAA method (R = 0.76 vs. 0.47, respectively). Due to CO2's atmospheric longevity, the NOAA method accurately captures growth rates over 5‐year intervals. GRESO's robustness across partial coverage configurations (ocean or land data) shows that satellites can be promising tools for low‐latency CO2 growth rate information, provided the systematic biases are minimized using in situ observations. Along with accurate and calibrated NOAA in situ data, satellite‐derived growth rates can provide information about the global carbon cycle at sub‐annual scales.