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This dataset contains raw data from the WFIP3 RHOD site supplementary meteorological sensors: T/RH and barometer; 1-sec average. The supplementary meteorological suite was added to PNNL Surface Flux Station to provide independent measurements of air temperature, relative humidity, and atmospheric pressure.
High-level coupled-cluster calculations in combination with two-dimensional master equation simulations were used to study the HO2 + CH3O2 reaction, which plays an important role in the oxidation of methane and hydrocarbons in the Earth’s atmosphere and low-temperature combustion. The main reaction pathways taking place on the lowest-lying triplet and singlet potential energy surfaces (PES) were characterized. Interestingly, methyl hydroperoxide (CH3OOH), the sole product, could be produced from both the triplet and singlet PESs, with a ratio of roughly 9:1. Formaldehyde is not made as a primary product, but can be formed via secondary chemistry. The formation of methyl tetraoxide (MTO) from the singlet PES is unimportant. The calculated reaction rate coefficients were found to be practically pressure-independent for p ≤ 760 Torr and can be given by k(T)=2.75×10−13×e+1.75 kcal mol−1/RT (in cm3/s), an expression useful for kinetics modeling over the range T = 200–800 K. The rate constant has a slight negative Arrhenius energy dependence of about −1.75 kcal mol–1, falling about a factor of 30 from 200 K to 800 K.
We report on Bayesian estimation of the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, conditional on pulse-profile modeling of Neutron Star Interior Composition Explorer X-ray Timing Instrument event data. We condition on informative pulsar mass, distance, and orbital inclination priors derived from the joint North American Nanohertz Observatory for Gravitational Waves and Canadian Hydrogen Intensity Mapping Experiment/Pulsar wideband radio timing measurements of Fonseca et al. We use XMM-Newton European Photon Imaging Camera spectroscopic event data to inform our X-ray likelihood function. The prior support of the pulsar radius is truncated at 16 km to ensure coverage of current dense matter models. We assume conservative priors on instrument calibration uncertainty. We constrain the equatorial radius and mass of PSR J0740+6620 to be ${12.39}_{-0.98}^{+1.30}$ km and ${2.072}_{-0.066}^{+0.067}$ M ⊙ respectively, each reported as the posterior credible interval bounded by the 16% and 84% quantiles, conditional on surface hot regions that are non-overlapping spherical caps of fully ionized hydrogen atmosphere with uniform effective temperature; a posteriori, the temperature is ${\mathrm{log}}_{10}(T\,[{\rm{K}}])={5.99}_{-0.06}^{+0.05}$ for each hot region. All software for the X-ray modeling framework is open-source and all data, model, and sample information is publicly available, including analysis notebooks and model modules in the Python language. Furthermore, our marginal likelihood function of mass and equatorial radius is proportional to the marginal joint posterior density of those parameters (within the prior support) and can thus be computed from the posterior samples.
Abstract. Stomata play a central role in regulating the exchange of carbon dioxide and water vapor between ecosystems and the atmosphere. Their function is represented in land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and physiological dynamics. To evaluate the effect of stomatal conductance model formulation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model – the Medlyn (MED) model – that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball–Woodrow–Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to climate forcing, including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit in the air (VPDa). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the stomatal intercept parameter (g0) constant for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPDa exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal changes of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Comparison of modeled soil water content from FATES to a reanalysis product showed that FATES captured soil drying well, but translation of drying soil to modeled physiology reduced the models' ability to match observations. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.
The Grand Challenge for the next generation of energy storage technologies is no longer the identification of electroactive cathode or anode materials thanks to extensive worldwide synthesis efforts along with theory and modeling like the Materials Project.1 Instead, the critical challenges revolve around assembling materials in the right architecture to achieve maximum performance and cell life at reasonable temperatures and pressures. Nowhere is this more critical than on the next generation of energy storage technologies revolving around all solid-state batteries. These batteries are the ultimate challenge for materials science requiring new ways to assemble multiple dissimilar materials such that: (1) interfaces are optimized to facilitate ion motion across the different compounds while (2) maintaining chemical stability and (3) simultaneously preserving the crystal structures of each phase during (4) large volume changes due to shuttling of lithium, at (5) room temperature and under (6) atmospheric pressure. To address these requirements will require insights and expertise from research fields outside the traditional lithium-ion battery community such as solid oxide fuel cells, synthesis science, barrier layers, interface formers, sintering, and mechanical properties.
Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.
Five bare kernels were selected from the U.S. Advanced Gas Reactor (AGR) 1 irradiation experiment Compact 5-3-1 to perform post-irradiation safety tests. The safety test involved heating the kernels in the Fuel Accident Condition Simulator (FACS) furnace in the inert atmosphere to a peak temperature of 1600°C and isothermally holding at this temperature for about 47 hours while collecting fission products released. This test was to assess the retention of fission products in bare kernels without the effects of the other TRISO layers (buffer, IPyC, SiC, and OPyC) or the graphitic matrix material. The bare kernels released nearly 100% of cesium and antimony, while they were able to maintain about 30% of europium, 50% of strontium, and the majority of cerium and ruthenium. In addition, about 48% of the calculated inventory of Kr-85 released during the test, indicating that kernels were capable of retaining a considerable fraction of fission gas K-85 during irradiation.
Uni- and bi-molecular reactions involving Criegee intermediates (CIs) have been the focus of many studies due to the role these molecules play in atmospheric chemistry. The reactivity of CIs is known to strongly depend on their structure. The reaction network of the second simplest CI, acetaldehyde oxide (CH 3 CHOO), is investigated in this work in an atmospheric pressure jet-stirred reactor (JSR) during the ozonolysis of trans-2-butene to explore the kinetic pathways relevant to atmospheric chemistry and low-temperature combustion. The mole fraction profiles of reactants, intermediates, and final products are determined by means of molecular-beam mass spectrometry in conjunction with single-photon ionization employing tunable synchrotron-generated vacuum ultraviolet radiation. A network of CI reactions is identified in the temperature region below 600 K, characterized by CI addition to trans-2-butene, water, formaldehyde, formic acid, and methanol. No sequential additions of the CH 3 CHOO CI are observed, in contrast with the reactivity of the simplest CI (H 2 COO) and the earlier observation of an extensive reaction network with up to four H 2 COO sequential additions (Phys. Chem. Chem. Phys., 2019, 21, 7341–7357). Experimental photoionization efficiency scans recorded at 300 K and 425 K and ab initio threshold energy calculations lead to the identification and quantification of previously elusive intermediates, such as ketohydroperoxide and hydroperoxide species. Specifically, the C 4 H 8 + O 3 adduct is identified as a ketohydroperoxide (KHP, 3-hydroperoxybutan-2-one, CH 3 C([double bond, length as m-dash]O)CH(CH 3 )OOH), while hydroxyacetaldehyde (glycolaldehyde, HCOCH 2 OH) formation is attributed to unimolecular isomerization of the CIs. Other hydroperoxide species such as methyl hydroperoxide (CH 3 OOH), ethyl hydroperoxide (C 2 H 5 OOH), butyl hydroperoxide (OOH), hydroperoxyl acetaldehyde (HOOCH 2 CHO), hydroxyethyl hydroperoxide (CH 3 CH(OH)OOH), but-1-enyl-3-hydroperoxide, and 4-hydroxy-3-methylpentan-2-one (HOCH(CH 3 )CH(CH 3 )C([double bond, length as m-dash]O)CH 3 ) are also identified. Detection of additional oxygenated species such as methanol, ethanol, ketene, and aldehydes suggests multiple active oxidation routes. Finally, these results provide additional evidence that CIs are key intermediates of the ozone-unsaturated hydrocarbon reactions providing critical inputs for improved kinetics models.
This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).
Using the Cosmology Large Angular Scale Surveyor, we measure the disk-averaged absolute Venus brightness temperature to be 432.3 ± 2.8 K and 355.6 ± 1.3 K in the Q and W frequency bands centered at 38.8 and 93.7 GHz, respectively. At both frequency bands, these are the most precise measurements to date. Furthermore, we observe no phase dependence of the measured temperature in either band. Our measurements are consistent with a CO 2 -dominant atmospheric model that includes trace amounts of additional absorbers like SO 2 and H 2 SO 4 .
Abstract Heatwaves are strongly associated with temperature distributions, but the mechanisms by which distributions are influenced by climate change remains unclear. Comparing simulations from a high‐spatial resolution Community Earth System Model (CESM‐HR) with those from low‐resolution models, we identify substantial improvements by CESM‐HR in reproducing observed Northern Hemisphere summer temperature skewness, as well as the frequency, intensity, persistence, and total heatwave days. Temperature skewness is strongly linked to land‐atmosphere interactions and atmospheric circulation. Under global warming projections, some regions exhibit enhanced temperature skewness, along with more frequent and persistent heatwaves of greater intensity. We find that in energy‐limited regimes, such as India, negative skewness in latent heat flux facilitates large positive skewness in sensible heat flux, which modulates near‐surface air temperatures. Skewness differences of latent and sensible heat fluxes are amplified under global warming, increasing the temperature skewness. We find that this contrasting flux mechanism is active in several heatwave‐prone regions.
This dataset, which contains ten csv files, reports several meteorological conditions such as temperature, wind speed, solar radiation, and net radiation measured in several urban parks in Knoxville, Tennessee, USA: Cumberland Estates Park (CEP), Socially Equal Energy Efficient Development (SEEED), West View Park (WVP), Victor Ashe Park (VAP), and West Hills Park (WHP). Also, hourly average of soil parameters such soil temperature, moisture, and matric potential measured in the five sites are included in this dataset. Air temperature, wind speed and direction, and solar radiation data were obtained from a METER ATMOS 41 All-in-One Weather Station (Pullman, Washington, USA). Soil moisture and temperature parameters were measured the METER Teros 12 probes embedded to a depth of 5 cm into the soil, while soil matric potential was measured with a METER Teros 21 probe. Incident and emitted radiation (shortwave and longwave) measurements were made using an Apogee (Logan, Utah, USA) net radiometer (Model SN-500-SS). This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.
Sea spray aerosol contains ice-nucleating particles (INPs), which affect the formation and proper ties of clouds. Here, we show that aerosols emitted from fast-growing marine phytoplankton produce effective immersion INPs, which nucleate at temperatures significantly warmer than the atmospheric homogeneous freezing (-38.0 °C) of pure water. Aerosol sampled over phytoplankton cultures grown in a Marine Aerosol Ref erence Tank (MART) induced nucleation and freezing at temperatures as high as -15.0 °C during exponential phytoplankton growth. This was observed in monospecific cultures representative of two major groups of phy toplankton, namely a cyanobacterium (Synechococcus elongatus) and a diatom (Thalassiosira weissflogii). Ice nucleation occurred at colder temperatures (-28.5 °C and below), which were not different from the freezing temperatures of procedural blanks, when the cultures were in the stationary or death phases of growth. Ice nucleation at warmer temperatures was associated with relatively high values of the maximum quantum yield of photosystem II ( Φ PSII ), an indicator of the physiological status of phytoplankton. High values of Φ PSII indicate the presence of cells with efficient photochemistry and greater potential for photosynthesis. For comparison, field measurements in the North Atlantic Ocean showed that high net growth rates of natural phytoplankton assemblages were associated with marine aerosol that acted as effective immersion INPs at relatively warm temperatures. Data were collected over 4 d at a sampling station maintained in the same water mass as the water column stabilized after deep mixing by a storm. Phytoplankton biomass and net phytoplankton growth rate (0.56 d -1 ) were greatest over the 24 h preceding the warmest mean ice nucleation temperature (-25.5 °C). Collectively, our laboratory and field observations indicate that phytoplankton physiological status is a useful predictor of effective INPs and more reliable than biomass or taxonomic affiliation. Ocean regions associated with fast phytoplankton growth, such as the North Atlantic during the annual spring bloom, may be significant sources of atmospheric INPs.
In this study, five different metal coupons were evaluated for gaseous iodine [I2(g)] adsorption including two stainless steels (i.e., SS304 and SS316), two Inconel® alloys (i.e., 625 and 718) and pure Ni (i.e., Ni-200) within a dynamic flow-through system where temperature, iodine concentration, flow rate, atmosphere, and relative humidity were controlled. Humidity was shown to be critical to iodine adsorption on SS304 and SS316 and Ni-200 at ambient temperatures. The results presented herein suggest that a moisture mediated reaction is occurring. However, higher humidity levels decrease the adsorption, suggesting an ideal range of humidity for highest corrosion. A comparison of the five metal substrates showed the highest I2(g) adsorption in the following descending order Ni-200 > SS304 > SS316 >718>625.The 625 and 718 Inconel alloys were fairly inert to iodine adsorption under the conditions tested. Characterization by scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray diffraction of the Ni-200 coupon indicates that NiI2 is formed and flakes off the surface as a black powder. The SS304 and SS316 coupons showed evidence of extensive reactions with I2(g) and formed a much more deliquescent corrosion product, which reacted with air when removed from the flow-through system for weighing on the analytical balance. These findings assist in predicting iodine adsorption behavior on a variety of metal surfaces under various conditions.
Abstract. Stellar occultation observations from space can probe the stratosphere and mesosphere at a fine vertical scale around the globe. Unlike other measurement techniques like radiosondes and aircraft, stellar occultation has the potential to observe the atmosphere above 30 km, and unlike radio occultation, stellar occultation probes fine-scale phenomena with potential to observe atmospheric turbulence. We imaged the refractive bending angle of a star centroid for a series of occultations by the atmosphere. Atmospheric refractivity, density, and then temperature are retrieved from the bending observations with the Abel transformation and Edlén's law, the hydrostatic equation, and the ideal gas law. The retrieval technique is applied to data collected by two nanosatellites operated by Terran Orbital. Measurements were primarily taken by the GEOStare SV2 mission, with a dedicated imaging telescope, supplemented with images captured by spacecraft bus sensors, namely the star trackers on other Terran Orbital missions. The bending angle noise floor is 10 and 30 arcsec for the star tracker and GEOStare SV2 data, respectively. The most significant sources of uncertainty are due to centroiding errors due to the fairly low-resolution stellar images and telescope pointing knowledge derived from noisy satellite attitude sensors. The former mainly affects the star tracker data, while the latter limits the GEOStare SV2 accuracy, with both providing low vertical resolution. This translates to a temperature profile retrieval up to roughly 20 km for both star tracker and GEOStare SV2 datasets. In preparation of an upcoming 2023 mission designed to correct these deficiencies, SOHIP, we simulated bending angle measurements with varying magnitudes of error. The expected maximum altitude of retrieved temperature is 41 km on average for these simulated measurements with a noise floor of 0.39 arcsec. Our work highlights the capabilities of stellar occultation observations from nanosatellites for atmospheric sounding. Future work will investigate high-frequency observations of atmospheric gravity waves and turbulence, mitigating the major uncertainties observed in these datasets.
This paper demonstrates a simultaneous Thomson scattering and rotational Raman scattering spectroscopy in a weakly ionized plasma in air. Thomson scattering was collected in the forward scattering direction, in order to compress the relative spectra width of Thomson scattering from the plasma. Simultaneous measurements of rotational Raman scattering were obtained in the same direction, which was not affected by the collection angles. The measurements thus yielded electron temperature (T e ) and electron number density (n e ) as well as gas temperature in a weakly ionized atmospheric pressure plasma. The separation of rotational Raman scattering and Thomson scattering occurred when the scattering angle decreased to 20 degrees in the plasma, where the air temperature was found to be 150 ± 25 °C, and electron temperature of the plasma was 0.587 ± 0.087 eV, and electron number density was (1.608 ± 0.416) × 1021 m-3. The technique could be used for various plasma and combustion diagnostics in realistic engineering environments.
Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as $2.24/MMBtu lower than the conventional production route that range between $3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization.
Abstract Stratospheric aerosol injection is a proposed method for offsetting greenhouse gas-induced warming by introducing scattering aerosols into the lower stratosphere to reflect sunlight. Here we explore a potentially more efficient alternative: weakening the Earth’s greenhouse effect by deploying absorptive aerosols in the upper stratosphere (~10 hPa). These aerosols warm the carbon dioxide emission level—where outgoing longwave radiation is most sensitive to temperature—thereby enhancing top-of-atmosphere infrared emission without altering atmospheric carbon dioxide concentrations. Idealized climate model simulations indicate that this approach can reduce global temperatures an order of magnitude more efficiently per unit aerosol mass than conventional scattering-based interventions. Although based on simplified model experiments lacking interactive aerosol processes and operational constraints, our results identify a distinct physical mechanism for climate intervention, arguing for further research into the impacts—especially potential unintended side effects—of injecting absorptive aerosols into the upper stratosphere as an alternative solar radiation management strategy.