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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The differential impact of low-carbon technologies on climate change mitigation cost under a range of socioeconomic and climate policy scenarios.

This paper considers the effect of several key parameters of low carbon energy technologies on the cost of abatement. A methodology for determining the minimum level of performance required for a parameter to have a statistically significant impact on CO2 abatement cost is developed and used to evaluate the impact of eight key parameters of low carbon energy supply technologies on the cost of CO2 abatement. The capital cost of nuclear technology is found to have the greatest impact of the parameters studied. The cost of biomass and CCS technologies also have impacts, while their efficiencies have little, if any. Sensitivity analysis of the results with respect to population, GDP, and CO2 emission constraint show that the minimum performance level and impact of nuclear technologies is consistent across the socioeconomic scenarios studied, while the other technology parameters show different performance under higher population, lower GDP scenarios. Solar technology was found to have a small impact, and then only at very low costs. These results indicate that the cost of nuclear is the single most important driver of abatement cost, and that trading efficiency for cost may make biomass and CCS technologies more competitive.

climate change↗
DOE OSTI2018

Using the Atmospheric Radiation Measurement (ARM) Datasets to Evaluate Climate Models in Simulating Diurnal and Seasonal Variations of Tropical Clouds

We use the long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three Tropical Western Pacific (TWP) sites as a tropical testbed to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. We conducted a series of CAM5 simulations at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean total cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in the frequency of ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m-2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, feedback on clouds. Both the CAM5 model and ARM observations show distinct diurnal cycles in total, stratiform and convective cloud fractions; however, they are out-of-phase by 12 hours and the biases vary by site. Our results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. We also found that the modelled gridmean surface longwave fluxes are systematically larger than site measurements when the grid that the ARM sites reside in is partially covered by ocean. The modeled longwave fluxes at such sites also lack a discernable diurnal cycle because the ocean part of the grid is warmer and less sensitive to radiative heating/cooling compared to land. Higher spatial resolution is more helpful is this regard. Our testbed approach can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional model simulations at high spatial resolutions.

Wang, Hailong↗
DOE OSTI2015

How does increasing horizontal resolution in a global climate model improve the simulation of aerosol-cloud interactions?

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25 degrees, with the meteorology nudged towards the Year Of Tropical Convection analysis, and cloud simulators and the collocated A-Train satellite observations are used to explore the resolution dependence of aerosol-cloud interactions. The higher-resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the northern hemisphere mid-latitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m⁻² (-30%) compared to the 2° model, leading to a 0.26 W m⁻² reduction (-15%) in the global annual average AIF.

Ma, Po -Lun↗
DOE OSTI2017

Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model

Here, we alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ~8–50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the global average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation

This paper provides projections of water withdrawals and consumption for electricity generation in India through 2050. Based on the results from five energy-economic modeling teams, the paper explores the implications of economic growth, power plant cooling policies, and electricity CO2 emissions reductions on water withdrawals and consumption. To isolate modeling differences, the five teams used harmonized assumptions regarding economic and population growth, the distribution of power plants by cooling technologies, and withdrawals and consumption intensities. The results demonstrate the different but potentially complementary implications of cooling technology policies and efforts to reduce CO2 emissions. The application of closed-loop cooling technologies substantially reduces water withdrawals but increases consumption. The water implications of CO2 emissions reductions, depend critically on the approach to these reductions. Focusing on wind and solar power reduces consumption and withdrawals; a focus on nuclear power increases both; and a focus on hydroelectric power could increase consumptive losses through evaporation.

electricity generation↗
DOE OSTI2018

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

Urban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (City-BEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa. First, 28 commercial and 6 residential building prototypes were designed by combing Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S. Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal variations of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.

CityBEUM, Urban building energy use, High spatiote↗