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At least 469 records · Page 26

Using Satellite Surface Temperature Data to Monitor Urban Heat Island

Exposure to heat is a growing concern nationwide. Temperatures can be elevated in cities compared to surrounding rural areas, referred to as an “urban heat island” (UHI) effect, which is intensified during heat waves. The lack of dense networks of air temperature measurements results in few studies on urban heat. Now, a vast amount of high spatial and temporal satellite data on land surface temperature is available. We identified satellite datasets with the longest surface temperature records but different spatial and temporal resolutions: Landsat (1985-current, biweekly at 60 m and 100 m spatial resolution) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites (2000-current, daily at 1 km spatial resolution). We investigated how satellites with different spatial and temporal resolutions detect UHI effects differently. We hypothesized that 1) a dataset’s spatial resolution impacts the precision of detected UHIs spatially, since high spatial resolution Landsat data better captures spatial variability in temperature, and 2) daily surface temperature data can detect temporal patterns of UHIs and heatwave frequencies. We analyzed Landsat and MODIS satellite data in the Washington, D.C. and Baltimore region. We found that Landsat describes higher spatial variability of the UHI effect than MODIS data. However, MODIS data shows more consistent seasonal surface temperature patterns than Landsat when compared to in situ air temperature measurements. MODIS data was also able to consistently measure the frequency of heat waves. This study demonstrates the value of NASA satellite data for urban heat and climate change studies.

landsat↗

Photo-DAC: Light-Driven Ambient-Temperature Direct Air Capture by a Photobase

Direct air capture (DAC) may reduce atmospheric CO 2 concentrations to preindustrial levels, yet the high energies and temperatures involved in current DAC technologies hinder large-scale deployment. In the case of aqueous-based CO 2 absorbents, a large energetic penalty is associated with heating and boiling off water, as required for thermally driven solvent regeneration. This could be avoided via photochemically driven pH swings involving photoacids or photobases, and harnessing abundant and renewable solar energy, though efficient solvent regeneration and recycling in a realistic multicycle DAC process remains challenging. Herein, we report a photochemically driven DAC process (photo-DAC) in which atmospheric CO 2 capture by an aqueous glycylglycine (GlyGly) solution is enabled through a pH swing by a pyridine-substituted diiminoguanidine (PyDIG) photobase. Upon irradiation with UV light, the PyDIG photobase undergoes photoisomerization from the E,E to the Z,Z isomer, corresponding to a pK a increase of 2.8 units that activates GlyGly for DAC through deprotonation. After the GlyGly/PyDIG solvent is saturated with atmospheric carbon dioxide, leaving it in the dark under ambient conditions leads to the isomerization of PyDIG from the Z,Z back to the E,E isomer, which is accompanied by a pH drop and CO 2 release. To demonstrate the recyclability of the GlyGly/PyDIG solvent, we have completed six consecutive DAC cycles, with a measured average cyclic capacity in the range of 0.21–0.26 mol CO 2 per mol of GlyGly/PyDIG. These results open the prospect for energy-efficient DAC cycles completed entirely at ambient conditions, thereby avoiding the significant energy penalties associated with heating and boiling aqueous solvents.

Einkauf, Jeffrey D. [Oak Ridge National Laboratory↗

Combustion characteristics of gas turbine alternative fuels

An experimental investigation was conducted to obtain combustion performance values for specific heavyend, synthetic hydrocarbon fuels. A flame tube combustor modified to duplicate an advanced gas turbine engine combustor was used for the tests. Each fuel was tested at steady-state operating conditions over a range of mass flow rates, fuel-to-air mass ratio, and inlet air temperatures. The combustion pressure, as well as the hardware, were kept nearly constant over the program test phase. Test results were obtained in regards to geometric temperature pattern factors as a function of combustor wall temperatures, the combustion gas temperature, and the combustion emissions, both as affected by the mass flow rate and fuel-to-air ratio. The synthetic fuels were reacted in the combustor such that for most tests their performance was as good, if not better, than the baseline gasoline or diesel fuel tests. The only detrimental effects were that at high inlet air temperature conditions, fuel decomposition occurred in the fuel atomizing nozzle passages resulting in blockage. And the nitrogen oxide emissions were above EPA limits at low flow rate and high operating temperature conditions.

Rollbuhler, R. James↗

Development and validation of a second-order thermal network model for residential buildings

Heating, Ventilation, and Air Conditioning (HVAC) systems can maintain the space air temperature of residential buildings, either directly by heating/cooling the air, or indirectly via heat transfer to and from the building structure that acts as a thermal mass. Hence, HVAC systems can help achieve load shifting, peak load reduction, and/or energy cost saving, thus enabling grid-interactive HVAC operation. A home thermal model that can accurately reflect the dynamics of the space air and interior wall surface temperatures, is therefore valuable. This paper develops such a model using the standard RC (resistance-capacitance) approach. The model contains a virtual envelope node and an internal space node and is thus second-order. A hybrid parameter identification scheme, made up of the least-squares and optimal search methods, is also developed. The proposed model and scheme were validated using data collected from a test home. It was found that a modest amount of training data was sufficient to yield reliable parameter estimates and accurate prediction. It was also found that when making 24-hour-ahead prediction of the space air temperature, both methods had comparable performances when the training data began in a transition season. However, when they began in an HVAC season, the optimal search method performed better. Furthermore, the least-squares method is recommended during a transition season due to its lower computational burden, while the optimal search method is recommended during an HVAC season due to its better estimation performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Temperature Crosstalk Sensitivity of the Kummerow Rainfall Algorithm

Even though the signal source for passive microwave retrievals is thermal emission, retrievals of non-temperature geophysical parameters typically do not explicitly take into account the effects of temperature change on the retrievals. For global change research, changes in geophysical parameters (e.g. water vapor, rainfall, etc.) are referenced to the accompanying changes in temperature. If the retrieval of a certain parameter has a cross-talk response from temperature change alone, the retrievals might not be very useful for climate research. We investigated the sensitivity of the Kummerow rainfall retrieval algorithm to changes in air temperature. It was found that there was little net change in total rainfall with air temperature change. However, there were non-negligible changes within individual rain rate categories.

Spencer, Roy W.↗

The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

Parkinson, Claire L.↗

Co-training of multiple neural networks for simultaneous optimization and training of physics-informed neural networks for composite curing

This paper introduces a Physics-Informed Neural Network (PINN) technique that co-trains neural networks (NNs) that represent each function in a system of equations to simultaneously solve equations representing an out-of-autoclave (OOA) cure process while conducting optimization in adherence to process requirements. Specifically, this co-training approach benefits from using NNs to represent OOA inputs (air temperature profile) and outputs (part and tool temperature profiles and degree of cure). Production requirements can then be levied on the inputs, such as maximum air temperature and minimum cure cycle, and simultaneously on the outputs, such as degree of cure, maximum part temperature, and part temperature rate limits. The technique is validated with finite element (FE) simulations and physical experiments for curing a Toray T830H-6 K/3900-2D composite panel. Furthermore, this novel approach efficiently models and optimizes the OOA cure process.

Composite curing↗

Effects of Climate Change on Capacity Expansion Decisions of an Electricity Generation Fleet in the Southeast U.S.

The electric power sector in the United States faces many challenges related to climate change. On the demand side, climate change could shift demand patterns due to increased air temperatures. On the supply side, climate change could lead to deratings of thermal units due to changes in air temperature, water temperature, and water availability. Past studies have typically analyzed these risks separately. Here, we developed an integrated, multimodel framework to analyze how compounding risks of climate-change impacts on demand and supply affect long-term planning decisions in the power system. In the southeast U.S., we found that compounding climate-change impacts could result in a 35% increase in installed capacity by 2050 relative to the reference case. Participation of renewables, particularly solar, in the fleet increased, driven mostly by the expected increase in summertime peak demand. Such capacity requirements would increase investment costs by approximately 31 billion (USD 2015) over the next 30 years, compared to the reference case. These changes in investment decisions align with carbon emission mitigation strategies, highlighting how adaptation and mitigation strategies can converge.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The effect of water injection on nitric oxide emissions of a gas turbine combustor burning ASTM Jet-A fuel

Tests were conducted to determine the effect of water injection on oxides of nitrogen (NOx) emissions of a full annular, ram induction gas turbine combustor burning ASTM Jet-A fuel. The combustor was operated at conditions simulating sea-level takeoff and cruise conditions. Water at ambient temperature was injected into the combustor primary zone at water-fuel ratios up to 2. At an inlet-air temperature of 589 K (600 F) water injection decreased the NOx emission index at a constant exponential rate: NOx = NOx (o) e to the -15 W/F power (where W/F is the water-fuel ratio and NOx(o) indicates the value with no injection). The effect of increasing combustor inlet-air temperature was to decrease the effect of the water injection. Other operating variables such as pressure and reference Mach number did not appear to significantly affect the percent reduction in NOx. Smoke emissions were found to decrease with increasing water injection.

Marchionna, N. R.↗

The toughest animals of the Earth versus global warming: Effects of long‐term experimental warming on tardigrade community structure of a temperate deciduous forest

Abstract Understanding how different taxa respond to global warming is essential for predicting future changes and elaborating strategies to buffer them. Tardigrades are well known for their ability to survive environmental stressors, such as drying and freezing, by undergoing cryptobiosis and rapidly recovering their metabolic function after stressors cease. Determining the extent to which animals that undergo cryptobiosis are affected by environmental warming will help to understand the real magnitude climate change will have on these organisms. Here, we report on the responses of tardigrades within a five‐year‐long, field‐based artificial warming experiment, which consisted of 12 open‐top chambers heated to simulate the projected effects of global warming (ranging from 0 to 5.5°C above ambient temperature) in a temperate deciduous forest of North Carolina (USA). To elucidate the effects of warming on the tardigrade community inhabiting the soil litter, three community diversity indices (abundance, species richness, and Shannon diversity) and the abundance of the three most abundant species ( Diphascon pingue , Adropion scoticum , and Mesobiotus sp.) were determined. Their relationships with air temperature, soil moisture, and the interaction between air temperature and soil moisture were tested using Bayesian generalized linear mixed models. Despite observed negative effects of warming on other ground invertebrates in previous studies at this site, long‐term warming did not affect the abundance, richness, or diversity of tardigrades in this experiment. These results are in line with previous experimental studies, indicating that tardigrades may not be directly affected by ongoing global warming, possibly due to their thermotolerance and cryptobiotic abilities to avoid negative effects of stressful temperatures, and the buffering effect on temperature of the soil litter substrate.

54 ENVIRONMENTAL SCIENCES↗

On the Trend of the Annual Mean, Maximum, and Minimum Temperature and the Diurnal Temperature Range in the Armagh Observatory, Northern Ireland, Dataset, 1844 -2012

Examined are the annual averages, 10-year moving averages, decadal averages, and sunspot cycle (SC) length averages of the mean, maximum, and minimum surface air temperatures and the diurnal temperature range (DTR) for the Armagh Observatory, Northern Ireland, during the interval 1844-2012. Strong upward trends are apparent in the Armagh surface-air temperatures (ASAT), while a strong downward trend is apparent in the DTR, especially when the ASAT data are averaged by decade or over individual SC lengths. The long-term decrease in the decadaland SC-averaged annual DTR occurs because the annual minimum temperatures have risen more quickly than the annual maximum temperatures. Estimates are given for the Armagh annual mean, maximum, and minimum temperatures and the DTR for the current decade (2010-2019) and SC24.

Wilson, Robert M.↗

Numerical Study of Coupled Water and Vapor Flow, Heat Transfer, and Solute Transport in Variably-Saturated Deformable Soil During Freeze-Thaw Cycles

As climate change intensifies, soil water flow, heat transfer, and solute transport in the active, unfrozen zones within permafrost and seasonally frozen ground exhibit progressively more complex interactions that are difficult to elucidate with measurements alone. For example, frozen conditions impede water flow and solute transport in soil, while heat and mass transfer are significantly affected by high thermal inertia generated from water-ice phase change during the freeze-thaw cycle. To assist in understanding these subsurface processes, the current study presents a coupled two-dimensional model, which examines heat conduction-convection with water-ice phase change, soil water (liquid water and vapor) and groundwater flow, advective-dispersive solute transport with sorption, and soil deformation (frost heave and thaw settlement) in variably saturated soils subjected to freeze-thaw actions. This coupled multiphysics problem is numerically solved using the finite element method. The model's performance is first verified by comparison to a well-documented freezing test on unsaturated soil in a laboratory environment obtained from the literature. Then based on the proposed model, we quantify the impacts of freeze-thaw cycles on the distribution of temperature, water content, displacement history, and solute concentration in three distinct soil types, including sand, silt and clay textures. The influence of fluctuations in the air temperature, groundwater level, hydraulic conductivity, and solute transport parameters was also comparatively studied. The results show that (a) there is a significant bidirectional exchange between groundwater in the saturated zone and soil water in the vadose zone during freeze-thaw periods, and its magnitude increases with the combined influence of higher hydraulic conductivity and higher capillarity; (b) the rapid dewatering ahead of the freezing front causes local volume shrinkage within the non-frozen region when the freezing front propagates downward during the freezing stage and this volume shrinkage reduces the impact of frost heave due to ice formation. This gradually recovers when the thawed water replenishes the water loss zone during the thawing stage; and (c) the profiles of soil moisture, temperature, displacement, and solute concentration during freeze-thaw cycles are sensitive to the changes in amplitude and freeze-thaw period of the sinusoidal varying air temperature near the ground surface, hydraulic conductivity of soil texture, and the initial groundwater levels. Our modeling framework and simulation results highlight the need to account for coupled thermal-hydraulic-mechanical-chemical behaviors to better understand soil water and groundwater dynamics during freeze-thaw cycles and further help explain the observed changes in water cycles and landscape evolution in cold regions.

54 ENVIRONMENTAL SCIENCES↗

Near-surface temperatures at proposed Mars Exploration Rover land sites

Minimum nighttime temperature at the Mars Exploration Rover (MER) landing sites may limit power available for science activities and thus mission lifetime. Here, 1 m air temperature at the end of the nominal 90 sol primary mission are derived for the four primary and three previously considered MER landing sites based on Mars Global Surveyor Thermal Emmision Spectrometer thermal inertia and albedo, estimated opacity, and predictions of air temperature from a one-dimensional atmospheric model.

Mars atmosphere Mars Exploration Rover (MER) surfa↗

Self-acting seals for helicopter engines

An experimental evaluation was conducted with NASA-designed self-acting face and circumferential seals for use in the main shaft positions of advanced gas turbine engines. The seals featured Rayleigh step pads (self-acting geometry) for lift augmentation. The tested seals incorporated design improvements over previous self-acting configurations. Self-acting face seals were tested to speeds of 214 m/s (700 ft/sec, 63700 rpm), air pressures of 216.8 N/sq cm abs (314.7 psia), and air temperatures of 688K (778 F). Self-acting circumferential seals were tested to speeds of 183 m/s (600 ft/sec, 47700 rpm), air pressures of 61.8 N/sq cm abs (89.7 psia), and air temperatures of 711 K (820 F). Self-acting face-seals are capable of operating at conditions exceeding conventional seal capability. The limit on speed capability was found to be the flatness of the seal-seat. The self-acting circumferential seal design tested requires further development for use in advanced engines.

Lynwander, P.↗

Building Model Calibration: Validation of GridLAB-D Thermal Dynamics Modeling

This report investigates how well GridLAB-D’s house model characterizes the thermal dynamics of buildings given the overpredicted diurnal electric load swing observed in the Distribution System Operation with Transactive (DSO+T) study. This study seeks to validate GridLAB-D’s house model by calibrating it to data from the well-instrumented Pacific Northwest National Laboratory Lab Homes in Richland, WA. The datasets chosen included multiple pre-cooling and pre-heating testing periods where the indoor air temperature was allowed to float over a multi-hour length of time to mimic diurnal behavior. The multi-season calibrations were evaluated by comparing the heating/cooling electric power, indoor air temperature, and the rise/decay time during temperature float periods with Lab Homes data. The default GridLAB-D assumptions for latent load fraction, air heat capacity, mass heat capacity, window-to-wall-ratio, overall envelope conductance (assumed as NORMAL thermal integrity level), and solar heat gain coefficient were compared with the calibrated model to confirm when the default assumptions were adequate and the impact of calibration on the accuracy of modeling the thermal dynamics of homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗

Winter to Spring Transition in Europe 48-45 degrees N: From Temperature Control by Advection to Control by Insolation

As established in previous studies, and analyzed further herein for the years 1988-1998, warm advection from the North Atlantic is the predominant control of the surface-air temperature in northern-latitude Europe in late winter. This thesis is supported by the substantial correlation Cti between the speed of the southwesterly surface winds over the eastern North Atlantic, as quantified by a specific Index Ina, and the 2-meter level temperature Ts over central Europe (48-54 deg N; 5-25 deg E), for January, February and early March. In mid-March and subsequently, the correlation Cti drops drastically (quite often it is negative). The change in the relationship between Ts and Ina marks a transition in the control of the surface-air temperature. As (a) the sun rises higher in the sky, (b) the snows melt (the surface absorptivity can increase by a factor of 3.0), (c) the ocean-surface winds weaken, and (d) the temperature difference between land and ocean (which we analyze) becomes small, absorption of insolation replaces the warm advection as the dominant control of the continental temperature. We define the onset of spring by this transition, which evaluated for the period of our study occurs at pentad 16 (Julian Date 76, that is, March 16). The control by insolation means that the surface is cooler under cloudy conditions than under clear skies. This control produces a much smaller interannual variability of the surface temperature and of the lapse rate than prevailing in winter, when the control is by advection. Regional climatic data would be of greatest value for agriculture and forestry if compiled for well-defined seasons. For continental northern latitudes, analysis presented here of factors controlling the surface temperature appears an appropriate tool for this task.

Otterman, J.↗