Oxygen content in wine significantly influences wine stability and shelf life. Wine producers commonly use nitrogen sparging to modify the final oxygen content in the wine, however, it is not always clear how long the wine producer should operate the sparging in order to achieve the desired oxygen content. Oxygen removal during sparging is controlled by the volumetric oxygen transfer coefficient (K L a). This study investigated the effect of wine type (red, rosé, and white), temperature (5°C, 10°C, and 20°C), and carbon dioxide concentration on K L a during nitrogen-induced oxygen removal. By systematising these variables, the work bridges knowledge gaps and offers actionable insights for more effective oxygen management in diverse wine matrices. Results indicate that K L a values are significantly influenced by both wine type and temperature, with higher values observed in red wine compared to white and rosé wines, potentially due to variations in ethanol and other dissolved compounds’ concentrations. Temperature elevation enhanced mass transfer rates across all wine types, highlighting the temperature dependence of K L a. Moreover, the presence of carbon dioxide reduced K L a, likely affecting bubble coalescence and stability. This is the first study which has investigated the variability of K L a as a function of composition, temperature, and carbon dioxide concentration – an important set of parameters since these are the variable conditions which wine makers must contend with.

• Saturation with carbon dioxide nanobubbles increases concentration and stability • Salt content influences carbon dioxide concentration and stability in dispersions • Nanobubble saturation of growth media results in higher concentration and stability The application of nanobubbles (NBs) in materials research, water treatment, and chemical reactions is well documented, primarily due to their high stability, longevity, and enhanced mass transfer rates. Recently, oxygen and air nanobubbles have been employed in enhancing algal and plant growth. However, data on carbon dioxide nanobubbles remain scarce, particularly regarding their effects on concentration and retention. In this work, carbon dioxide was dissolved into aqueous solutions with varying salt concentrations, and the flow was depressurized through a needle valve to generate NBs dispersions. Particle number and carbon dioxide concentration were analyzed over a 10-day period and compared with a control solution generated via bubbling. The dispersions exhibited significant NBs concentrations and, more importantly, higher carbon dioxide levels than the bubbling solution. The highest concentrations were observed in 1 mM NaCl and distilled water, corresponding to increases of 136% and 97%, respectively. All dispersions maintained superior concentrations compared to the control. Furthermore, the dispersions retained elevated carbon dioxide levels for an average of five additional days relative to the bubbling solution. Finally, the experimental data were used to fit exponential models describing the evolution of the dispersions. These models revealed both the influence of the saturation methodology and the trade-off between salinity, particle size, and carbon dioxide retention. Overall, the results demonstrate that this methodology provides advantages over conventional carbon dioxide delivery strategies and may contribute to process optimization in algal biomass production.

This study examined how external thermal exposure affected the self-sustained smouldering behaviour of chromated copper arsenate (CCA)-treated wood. A Fire Propagation Apparatus was used, varying incident heat flux and exposure duration to emulate passing wildfire scenarios. Wood density and CCA retention were kept within narrow ranges. Responses from ignition through smouldering propagation were evaluated using mass loss, thermocouple temperature, and exhaust-gas carbon monoxide (CO) and carbon dioxide (CO 2 ) concentrations over time. The time to peak CO or CO 2 aligned with the time to peak mass-loss rate, providing a practical and robust indicator of smouldering severity. Smouldering severity was governed mainly by total incident energy rather than heat-flux intensity or duration alone; tests with comparable incident energy produced similar severities. Increasing total incident energy deepened char, increased thermal penetration, and increased mass loss at the onset of self-sustained smouldering after flameout. However, smouldering severity does not increase linearly with incident energy. At bench scale, smouldering propagation was not perfectly one-dimensional despite the initial heating being almost one-dimensional. These findings identify total incident energy as a practical control parameter for reproducing wildfire-analogue exposures and provide an operational severity metric to support development of monitoring protocols, severity-based fire classifications, product screening and targeted intervention strategies. • Smouldering severity is governed mainly by total incident energy • CO and CO 2 concentration peaks provide practical proxies for smouldering severity • Smouldering severity does not increase linearly with incident energy • Smouldering propagation is not perfectly 1D even with predominantly 1D heating

Urban air quality degradation, driven by intensified urbanization and traffic, presents a critical public health challenge in most cities worldwide, such as Guelma, Algeria, where concentrations of fine particulate matter (PM2.5, PM10) and carbon dioxide (CO2) often exceed health standards. This study evaluates the efficacy of conventional greening by suggesting that the air purification potential of public gardens may be limited by suboptimal initial design. It is an exploratory modeling framework to propose a shift from qualitative landscaping to quantitative, performance-driven biophilic design. By simulating six parameterized intervention scenarios, this research indicates that simplistic canopy densification may be an insufficient strategy under high pollutant loads. Based on a specific summer field campaign and a limited temporal scope, the results identify a proposed design configuration protocol, where significant pollutant mitigation is achieved by a specific arrangement: a 60% urban forest index composed of high-efficiency species (Platanus × acerifolia, Acer saccharinum, Quercus spp.), combined with a 10% shrub layer and 40% grass cover to form a multilayered filter. This vegetative system is integrated with complementary engineered systems: linear water features covering 15% of the surface for particle wash-down, soil engineered to an aerodynamic roughness length (z0) of 0.15m across 65% of the site to enhance deposition, and pollutant-absorbing paving on 20% of the surface. This study suggests that enhancing the functional efficiency of urban gardens requires precise, multimechanism integration of biomass, water, and engineered surfaces, providing an exploratory framework for designing public spaces as potential infrastructure for sustainable air quality improvement.

Improving Chest Compression Quality in Cardiac Arrest: A Multimodal Intervention Project in the Emergency Department.

The unintended formation of solid carbon dioxide during the cryogenic processing of natural gas introduces severe operational hazards, pipeline blockages, and financial losses. To address this critical challenge, this study aims to develop a highly accurate, explainable data-driven framework capable of forecasting frosting temperatures based on operating pressures and mixture compositions. By utilizing a comprehensive dataset of 430 experimental data points comprising molar concentrations of methane, carbon dioxide, nitrogen, and ethane, ten distinct machine learning algorithms were trained and rigorously evaluated. The methodology specifically contrasted traditional linear techniques with advanced non-linear ensemble algorithms to identify the most robust predictive tool. Results clearly demonstrate the quantitative superiority of tree-based ensemble methods. Notably, the CatBoost algorithm emerged as the optimal model, achieving exceptional predictive accuracy with a coefficient of determination (R2) of 0.9918 and a Mean Relative Deviation (MRD) of only 0.55% on the unseen test set. To ensure physical reliability, SHapley Additive exPlanations (SHAP) were integrated, revealing that pressure and carbon dioxide concentration act as the primary positive drivers for frost formation, whereas methane concentration serves as the most significant mitigating factor. Ultimately, this research provides a novel, transparent, and highly deployable prognostic tool for chemical engineers. By successfully bridging the gap between high-accuracy machine learning and thermodynamic interpretability, this work establishes a trustworthy academic foundation for future predictive modeling and empowers industrial operators to proactively optimize natural gas purification, reduce energy expenditures, and ensure process safety.

Responsible for fixing 25% of carbon dioxide (CO2) globally, cyanobacteria use carboxysomes to house their CO2 fixing machinery. The formation and permeability of the proteinaceous shell of carboxysomes is an area of active study. While necessary in air (0.04% CO2), the shell is not required when cyanobacteria are in high CO2 levels representative of early Earth. To understand how the carboxysome shell responds to increased CO2 conditions, we used a Grx1-roGFP2 redox sensor and single cell timelapse fluorescence microscopy to track subcellular redox states of Synechococcus sp. PCC 7002. Comparing different levels of compartmentalization, we targeted the cytosol, a shell-less carboxysomal assembly intermediate called procarboxysomes, and carboxysomes. Carboxysome redox state was dynamic, and, under 3% CO2 conditions, procarboxysome-like structures formed which were only partially encapsulated and exposed the carboxysome contents to the cytosol. This work expands the adaptability of carboxysomes to environmental conditions and builds understanding of the selective forces that initially drove carboxysome evolution.

Quantifying anthropogenic CO2 increments is vital for assessing emission reductions. Using a seamless XCO2 dataset over China reconstructed from OCO-2/3 satellite retrievals and machine learning, combined with EOF decomposition and LISA analysis, this study investigates XCO2 anomalies and local anthropogenic increments (dXCO2) at national and urban agglomeration scales. Nationally, XCO2 anomalies exhibit a “southeast positive, northwest negative” spatial pattern aligning with human activities and a “winter high, summer low” seasonal cycle. EOF analysis reveals four dominant modes: anthropogenic–natural trade-offs, East Asian summer monsoon modulation, local emissions, and baseline context. At the regional scale, multi-year mean dXCO2 (2015–2019) in Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are 3.46 ± 0.45 ppm, 1.30 ± 0.36 ppm, and 0.08 ± 0.14 ppm, respectively, showing higher values in northern heavy industrial zones. During the 2020–2022 pandemic, dXCO2 decreased in BTH (2.28 ± 0.73 ppm) and YRD (1.16 ± 0.43 ppm) but increased in PRD (0.28 ± 0.27 ppm). Compared to pre-pandemic levels, lockdowns saw dXCO2 decrease slightly in YRD while increasing in BTH and PRD, reflecting differential responses of regional industrial structures. This study demonstrates the potential of seamless XCO2 data for monitoring anthropogenic enhancement signals, and the proposed LISA-based method offers new support for regionally differentiated emission reduction assessments.

Precise regulation of carbon dioxide (CO 2 ) concentrations in plant growth chambers is critical for ensuring reproducible and physiologically relevant research outcomes. CO 2 assimilation varies significantly with plant genotype, growth conditions, crop density, and phenological stage. However, estimation and control approaches heavily dependent on mechanistic crop models are at odds with the objectives of plant characterization units (PCU), where model availability for specific crops may be lacking. Moreover, in Bioregenerative Life Support Systems (BLSSs), such methods may struggle with multiple crops, intercropping, staggered harvesting and unknown growth stages. We propose a real-time, crop-agnostic method to estimate photosynthetic and respiration rates from CO 2 concentration data, without relying on crop-specific mechanistic assumptions. This improves robustness against the time-varying conditions typical of BLSSs, and supports operation with crops lacking validated physiological models. The resulting rate estimates support diagnostic algorithms, supervisory logic and CO 2 concentration controllers, and provide the modeling foundation for our second contribution: a hybrid Model Predictive Control (MPC) strategy for CO 2 regulation. The controller employs a mixed-integer formulation to handle the disjoint operating ranges of injection valves and incorporates explicit compensation for CO 2 measurement delays, ensuring accurate mass balances under real operating conditions. We demonstrate the effectiveness of the approach through in vivo experiments in a PCU realized under the ESA-MELiSSA framework. • Real-time observer for estimating photosynthesis and respiration rates. • Hybrid Model Predictive Control to ensure highly precise CO 2 regulation. • Robustness to intercropping, staggered harvesting and unknown growth stages. • Control formulation favoring integration in Bioregenerative Life Support Systems. • Validation through in vivo experiments in a Plant Characterization Unit.

Precise micro-perforated modified atmosphere packaging delayed winter jujube browning by regulation of reactive oxygen metabolism and energy metabolism

Since current opioid overdose deaths occur mainly from potent synthetic opioids with high affinity for the opioid receptor, such as fentanyl and carfentanil, it is important to determine the efficacy of naloxone, particularly the intranasal formulation, in reversing opioid-induced respiratory depression. This study evaluated effectiveness of 4 mg intranasal naloxone (Narcan; Adapt Pharma Inc., USA) in reversing moderate respiratory depression induced by fentanyl and sufentanil in opioid-naive individuals and self-reported daily opioid users. Sufentanil was compared to fentanyl because of its higher affinity for the opioid receptor. In this prospective, crossover trial, 12 opioid-naive individuals and 18 daily opioid users (morphine milligram equivalent, 291; range, 60 to 2,250 mg/day) received continuous fentanyl or sufentanil infusions, titrated to achieve 30 to 40% reduction in minute ventilation ( ). Participants were administered Narcan during steady-state respiratory depression. Primary endpoints included time to reversal of diminished and elevated end-tidal carbon dioxide concentration (pCO 2 ). Narcan restored within 2 to 4 min across all participants but showed delayed reversal of end-tidal pCO 2 (11 to 17 min), with pCO 2 recovery during sufentanil exposure in just 8 opioid-naive individuals and 10 daily opioid users. Hysteresis analysis showed for reversal onset/offset times (blood-effect-site equilibration half-lifes) of 0 to 1 min and for end-tidal pCO 2 2 to 11 min. Because of withdrawal symptoms, 7 of 18 daily opioid users participated once in the study. Study limitations included continuous opioid infusions that do not occur in real-world overdose settings. A single Narcan dose reversed moderate fentanyl- and sufentanil-induced respiratory depression, although effectiveness varied by endpoint and opioid receptor affinity. Rapid recovery suggests clinical utility of intranasal naloxone, but delayed and sometimes incomplete recovery of end-tidal pCO 2 , particularly during exposure to the high-affinity opioid sufentanil, indicates reversal inefficacy and persistence of respiratory instability. Further studies are needed to address optimal naloxone doses and alternative formulations to address high-dose potent opioid threats.

Building ventilation controls often combine demand control ventilation (DCV), which reduces ventilation during low occupancy, with economizer cooling, which increases outdoor air when conditions allow free cooling. However, these strategies overlook outdoor air pollution, and economizers can worsen indoor air quality (IAQ) when outdoor fine particulate matter (PM2.5) is high. This study evaluates the real-word operation of the IAQ-Energy Controller, a rule-based controller that enhances Economizer + DCV logic by limiting outdoor air and disabling the economizer when outdoor PM2.5 is elevated. To compensate, the system modulates an internet-connected portable air cleaner to meet ASHRAE Standard 241 for infectious aerosol control. Implemented in a repeated-measures crossover field study across two classrooms in California’s Central Valley, the controller consistently reduced carbon dioxide concentrations by 16% to 18% relative to fixed-rate ventilation, maintained or improved equivalent air changes per hour for infectious aerosol removal, and delivered comparable thermal comfort without increasing energy use. The infectious aerosol control benefits of the additional outside air provided by the IAQ-Energy controller increase as filtration efficiency of recirculated air decreases, which is important for applications with lower efficiency filters. The IAQ-Energy controller represents a low-cost, scalable retrofit solution for improving IAQ and resilience in school environments.

The increasing concentration of carbon dioxide (CO2) in the atmosphere is widely recognized as one of the main drivers of climate change [...]

Abstract Airborne infectious diseases, such as COVID-19, TB, MERS, and SARS, constitute a profound threat to public health and quality of life. These pathogens are transmitted primarily via atmospheric particles, especially within clinical environments, where they often circulate. Effective ventilation controls to mitigate pathogens and air pollution are thus essential for reducing hospital-based transmission of airborne infections. The purpose of this research is to assess the risk of airborne infectious diseases within a hospital in Thailand using a mathematical model. Specifically, the finite difference technique is employed to estimate carbon dioxide (CO 2 ) concentration as a proxy for indoor air quality to indicate and assess the risk of airborne infectious diseases. The hospital layout is categorized into waiting areas and circulation areas with disparate occupant densities. Three simulation scenarios are conducted, accounting for variations in ventilation rates and architectural structure of hospitals. The results of this research demonstrate that CO 2 concentration can be effectively quantified as a proxy for indoor air quality within hospital environments. These calculated CO 2 levels are subsequently used to model the risk of airborne infection at a hospital, providing a robust framework for assessing this risk. Crucially, by integrating ventilation dynamics that reflect the physical constraints and structure of the hospital, this research enables precise evaluation of infection risks. The findings indicate that ventilation control can reduce the incidence of airborne infection, with significant practical utility in real-world clinical settings.

ABSTRACT Carex siderosticta Hance is an advantageous understory and lawn greening resource due to its strong environmental adaptability and ornamental value, but extreme climates render soil moisture a key growth-limiting factor. Thus, this study explored the response strategies of C. siderosticta to drought and flooding via pot water control and double-pot flooding simulations. Results showed that all the water stresses significantly inhibited the growth of C. siderosticta with increasing stress intensity; leaf and root biomass, water content and root activity decreased gradually, and root architecture parameters such as root length and root surface area decreased concomitantly. At the photosynthetic level, the photosynthetic pigment contents decreased, net photosynthetic rate (A n ), stomatal conductance (g s ), and transpiration rate (T r ) declined in a stress-dependent manner, while intercellular carbon dioxide concentration (C i ) increased correspondingly. In terms of physiological metabolism, osmoregulatory substances, including soluble sugar (SS), soluble protein (SP) and proline (Pro) accumulated continuously, and the malondialdehyde (MDA) content increases, which in turn activates the antioxidant system, leading to elevated activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) as well as increased contents of ascorbic acid (ASA) and glutathione (GSH). Anatomically, differential adaptive strategies were developed: under drought stress, the thickness of the leaf blade and epidermal cells decreased, and leaf bulliform cells shrank to reduce water loss; the root xylem vessel diameter was optimized to improve water transport, and the cortex thickness increased to enhance water conduction and absorption capacity. Under flooding stress, aerenchyma developed to alleviate hypoxia stress. This synergistic response involving morphology, physiology and anatomy is the key mechanism enabling C. siderosticta to tolerate both water deficit and water excess simultaneously. Relying on the synergistic strategy of morphological plasticity adaptation, physiological metabolism regulation and anatomical structure specialization to cope with water stress, this species not only exhibits excellent drought and waterlogging tolerance but also serves as a high-quality groundcover resource for water-saving greening in arid and semi-arid regions. It is also suitable for landscape construction and ecological restoration in areas with highly variable precipitation and frequent drought‒flood alternations, thus providing crucial support for water-saving and stress‒resilient greening efforts under the context of climate change.

Onions (Allium cepa L.) represent a critical global food security crop, yet post-harvest losses of 25–40 % in developing nations severely compromise nutritional accessibility and farmer livelihoods. This systematic review critically evaluates traditional and modern storage technologies while assessing internet of things (IoT) integration potential for real-time quality monitoring and automated environmental control. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, comprehensive literature searches across Web of Science, Scopus, PubMed and IEEE Xplore databases (2000–2024) identified 847 potentially relevant publications. After applying rigorous inclusion criteria requiring quantitative performance data, peer-reviewed publication status and English language accessibility, 156 studies underwent detailed analysis. Traditional ambient storage methods including field curing, naturally ventilated structures and conventional godowns demonstrate economic accessibility advantages but experience storage losses of 15–40 % over 3–5 months due to uncontrolled temperature and humidity fluctuations that accelerate physiological deterioration and microbial proliferation. Modern refrigerated cold storage systems maintaining precise environmental conditions of 0–1 °C temperature and 65–70 % relative humidity achieve extended shelf life of 6–10 months with losses consistently below 5 %. However, substantial capital investment requirements of USD 400–800 per tonne storage capacity combined with technical operational expertise needs restrict adoption primarily to large-scale commercial operations. The IoT-enabled precision storage systems integrate distributed wireless sensor networks for continuous monitoring of temperature, relative humidity, carbon dioxide concentration and sprouting indices, coupled with automated actuator control optimising ventilation, refrigeration and humidity management. Techno-economic analyses indicate achievable loss reductions of 10–20 % with investment payback periods of 2–3 years, though these metrics exhibit substantial sensitivity to wholesale price volatility and regional electricity costs. Critical implementation barriers include inadequate rural telecommunications infrastructure affecting 58 % of agricultural facilities, insufficient technical support networks, sensor calibration drift in condensing environments and limited digital literacy. Hybrid retrofitting approaches combining traditional infrastructure with IoT monitoring and evaporative cooling demonstrate economic viability, achieving 15–30 % loss reduction at 70–85 % of full cold storage costs. Priority research directions include commercial-scale field validation across diverse agroclimatic zones, standardised interoperability framework development and farmer-centered participatory design approaches.

The escalating atmospheric carbon dioxide (CO2) concentration and depletion of fossil fuels have spurred intensive research into sustainable CO2 conversion technologies. The photocatalytic CO2 reduction reaction (CO2RR) in gas-solid phase systems offers distinct advantages over liquid-phase counterparts, including enhanced mass transfer, simplified product separation and reduced side reactions. Notably, near-infrared (NIR) light constitutes approximately 50% of the solar spectrum; however, traditional photocatalysts rarely utilize this low-energy region, thereby limiting overall solar-to-chemical conversion efficiency. This review systematically summarizes the rationale, design strategies and catalytic performance of NIR-responsive photocatalysts for gas-solid phase CO2RR. Key approaches include the engineering of metallic/narrow-bandgap conductors, the introduction of defects/intermediate bands, the construction of plasmonic heterojunctions, atomic-level doping, the integration of single-atom active sites and the development of metal-free photothermal systems. These strategies address core challenges such as extending spectral response, enhancing charge separation and optimizing CO2 activation. Representative catalysts exhibit efficient NIR-driven CO2 reduction to value-added products (e.g., carbon monoxide, methane, methanol) with high selectivity and stability. This review provides critical insights into unlocking full-spectrum solar energy utilization and advancing practical CO2RR technologies for carbon neutrality.

As the world’s strongest zonal surface winds, changes in the Southern Hemisphere Westerlies (SHW) can profoundly affect atmospheric carbon dioxide (CO 2 ) concentrations, ocean-cryosphere domains and precipitation patterns in the Southern Hemisphere mid- to high-latitudes. The strengthening and poleward migration of the SHW in the last few decades points to an increase in Southern Ocean ventilation and CO 2 outgassing with significant implications for future global temperatures and Southern Hemisphere mid-latitude precipitation variability. A more in-depth and longer-term understanding of past SHW behaviour is required to improve projections of future SHW variability. Macquarie Island (54°S), located within the modern core belt of the SHW, is an ideal location because the influx of westerly wind-blown sea spray creates a strong conductivity gradient in lakes from west to east across the island. We used the known positive correlation between increasing wind-blown sea spray driven water conductivity and halophilic and halophobic diatoms preserved in lake sediments to reconstruct past changes in SHW influence on Macquarie Island over the last 2500 years. Low values in the accumulation rate of the dominant low-conductivity Aulacoseira principissa and Psammothidum taxa at ~2500–2300 cal. yr BP and after ~800 cal. yr BP suggest relatively stronger SHW over Macquarie Island at those times. Contrastingly, an increase in Psammothidum taxa at ~2300–800 cal. yr BP signals weaker SHW as a consequence of lower sea spray input. This is supported by the coeval, anti-phased changes observed in the relative abundance of high-conductivity species such as Platessa oblongella , Planothidium renei , Pinnularia sp. and Fragilaria capucina . This study provides a detailed and valuable record of SHW variability for the last few millennia in the Pacific sector of the Southern Ocean.

The rising atmospheric concentration of carbon dioxide (CO2) is assumed to be a key factor in global climate change, requiring robust and sustainable carbon conversion technologies. While carbonic anhydrase (CA) is a highly efficient enzyme for CO2 sequestration, its industrial application is limited by stability, cost, and scalability challenges. To address these limitations, we developed a CA-mimetic metal-amino acid (Phe-Zn(II)) bionanozyme featuring amyloid-like supramolecular cross-β-sheet architecture that provides high structural stability and recyclability. Gas chromatography (GC) analysis of a continuous flow bubble reactor charged with Phe-Zn(II) bionanozyme exhibits a CO2 conversion efficiency of approximately 18% in an aqueous medium (pH 7.0, 25 °C, ambient pressure), while maintaining remarkable structural integrity as confirmed by postcatalysis PXRD analysis. The amyloid-like supramolecular cross-β-sheet architecture, stabilized by π-π stacking and intermolecular hydrogen bonding, generates a confined catalytic microenvironment that enhances Zn(II) Lewis's acidity and promotes efficient CO2 hydration, which is crucial compared to previous reports. Next, density functional theory (DFT) calculations reveal a three-step catalytic pathway involving hydroxide ion generation, nucleophilic attack, and carbonic acid formation, with a rate-determining barrier of 12.3 kcal/mol, making the reaction feasible at room temperature. We also investigated the impact of different amino acids coordinated with Zn, finding that Phe-Zn(II) shows higher catalytic activity. This is due to the stronger electron-withdrawing effect of the phenyl group, which enhances the Lewis acidity of Zn2+, activates the Zn2+-OH2 bond, and lowers the rate-determining barrier. Taken together, the combination of experimental catalysis, structural robustness, and mechanistic validation highlights Phe-Zn(II) as a promising, cost-effective, and minimalistic catalyst yet efficient carbonic anhydrase mimic for CO2 conversion, paving the way for scalable and sustainable carbon sequestration strategies critical for mitigating climate change.

Abstract Climate models exhibit an approximately invariant surface warming pattern in typical end-of-century projections. This feature has been used extensively in climate impact assessments for fast calculations of local temperature anomalies, with a linear procedure known as pattern scaling . At the same time, emerging research has also shown that time-varying warming patterns are necessary to explain the time evolution of effective climate sensitivity in coupled models, a mechanism that is known as the pattern effect and that seemingly challenges the pattern scaling understanding. Here, we present a simple theory based on local energy balance arguments to reconcile this apparent contradiction. Specifically, we show that the pattern invariance arises from the combination of exponential forcing, linear feedbacks, a constant forcing pattern, and linear changes in heat transport. These conditions are approximately met in typical Coupled Model Intercomparison Project phase 6 (CMIP6) shared socioeconomic pathways (SSPs), except in the Arctic where nonlinear feedbacks are important and in regions where different aerosol projections alter the forcing pattern. In idealized experiments where concentrations of carbon dioxide (CO 2 ) are abruptly increased, such as those used to study the pattern effect, the warming pattern evolves considerably over time because of spatially inhomogeneous ocean heat uptake, even in the absence of nonlinear feedbacks. Our results illustrate why typical future projections are amenable to pattern scaling and provide a plausible explanation of why more complicated approaches, such as nonlinear emulators, have only shown marginal improvements in accuracy over simple linear calculations. Significance Statement In typical end-of-century climate projections from comprehensive models, the ratio between local and global surface temperature anomalies is approximately time and scenario invariant. This feature has enabled fast calculations of local temperature changes by scaling the global average with a constant pattern. At the same time, idealized quadrupling of CO 2 (4xCO 2 ) experiments show a different behavior and a considerable time evolution of the warming pattern. We present a simple theory based on local energy balance to reconcile this apparent contradiction. Specifically, we show that the pattern invariance arises under a set of conditions that are approximately satisfied typical end-of-century scenarios. Our findings clarify why scaling the global average to calculate local temperature anomalies is effective for most future projections.