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The MATLAB (.mat) files (spatial grids of daily CDD data) are generated by a suit of WRF-UCM simulations over California at 4.5 km resolution (1.5 km resolution over cities) for 5 scenarios
Buildings present an opportunity for energy conservation and the modulation of peak energy demand through controlled Heating, Ventilation, and Air Conditioning (HVAC) energy use. The administrative and office building stock in the United States holds potential to achieve energy and demand savings through retrofits such as insulation, weatherization, and thermal energy storage. Specifically, there is a need to validate passive phase change material (PCM) applications in full scale in aging administrative buildings in the US to evaluate the energy benefits. Aim of this study was to conduct a whole building level thermal and energy validation of an operational building and explore an alternative method for evaluating energy efficiency. To accomplish this, the study employed PCMs in the drop ceiling and carry out an energy audit and on-site measurement of HVAC systems' energy demand and consumption. A full-scale EnergyPlus energy model, modeled by the authors, served as a baseline for evaluation. The results show that calibrated model's envelope temperature measures fall within the accepted errors. HVAC energy simulation results also fall within the accepted errors for monthly and hourly pre- and post- PCM retrofit electricity and natural gas data. The novelty of this study is that it employees energy scales per Heating Degree Hour and Cooling Degree Hour, in contrast to the commonly used Heating Degree Days and Cooling Degree Days as reported in the literature to analyze energy savings. These findings underscore the pivotal role of a calibrated model in assessing the efficacy of a singular energy measure, like a PCM-retrofitted ceiling, in an occupied office building.
Commercial buildings account for a significant amount of total energy produced in the US, and the Heating Ventilation and Cooling (HVAC) systems are one of the most significant components of their overall consumption. In this study, we proposed a new data-driven approach to evaluate HVAC cooling systems in commercial buildings and identify savings opportunities. The focus is an investigation of the impact of thermostat setpoint setback but using only whole building, electricity data taken at 15-min intervals for the analysis. We conducted a comparative study of setpoint setback characteristics on 432 commercial buildings with 5 building usage types across the United States. To accomplish this, both piecewise and Random Forest regression algorithms were employed using electricity and exterior temperature datasets to identify operational characteristics and the effective setpoints in the building to determine the corresponding savings opportunities. Both occupied and unoccupied time periods were studied across cooling degree days (CDD), when air conditioning is typically operational. Here the results show that in commercial buildings, on average, cooling systems account for 9.5% of total consumption. When a one degree setback during the cooling season is applied, an average of approximately 1.1% of annual consumption is achieved; retail and office buildings demonstrate the highest potential for savings. Additionally, we identified that the number of cooling degree days and base to peak ratio (BPR) are the most important variables for predicting the magnitude of the consumption of cooling systems.
Climate analysis for the Southeast U. S. has indicated that inland regions have experienced an average temperature increase of 2F since 1970. This trend is generally characterized by warmer winters with an indication of increased precipitation in the Fall season. Extended periods of limited rainfall in the Spring and Summer periods have had greater areal coverage and, at other times the number of precipitation events has been increasing. Climate model projections for the next 10-70 years indicate warmer temperatures for the Southeast U.S., particularly in the Spring and Summer, with some indication of more extremes in temperature and precipitation as shown in the table below. The realization of these types of regional climate changes in the form of extended heat waves and droughts and their subsequent stress on facilities, infrastructure, and workforce could have substantial impact on the activities and functions of NASA's Marshall Space Flight Center (MSFC) in Huntsville, Alabama. This presentation will present the results of an examination of the 100 year temperature and precipitation record for MSFC. Local warming has cause an increase in daily maximum and minimum temperatures by nearly 3F, with a substantial increase in the number of maximum temperatures exceeding 90F and a decrease in the number of days with minimum temperatures below freezing. These trends have substantial impact of the number of heating / cooling degree days for the area. Yearly precipitation totals are inversely correlated with the change in mean temperature and the frequency of heavy rain events has remain consistent with the changes in yearly totals. An extended heat wave index was developed which shows an increase in frequency of heat waves over the last 35 years and a subsequent reduction in precipitation during the heat waves. This trend will contribute to more intense drought conditions over the northern Alabama region, increasing the potential of destructive wildfires in and around the Center. MSFC has begun using this climate change information to adapt short-term and long-term plans for Center operations.
We report radiative coatings are a promising strategy to implement passive cooling that provides an eco-friendly pathway to achieve energy efficiency in buildings. This study investigates the benefits and limitations of implementing radiative coatings on the building envelope, particularly the roof, of residential buildings in the United States. The analysis compares the performance of an ideal radiative coating with broadband surface properties to a realistic radiative coating with diffuse and semitransparent properties. To enhance the net energy efficiency of buildings, we carried out a comprehensive parametric analysis comprising key radiation surface properties to maximize cooling energy savings while minimizing heating energy penalties. A countrywide assessment for 68 locations across the United States showed that net energy savings are a strong function of the climatic and atmospheric conditions. Broadly, southern locations showed high overall energy savings whereas northern locations exhibited high overall energy penalties. Locations in International Energy Conservation Code (IECC) climate zones 1A, 2A, and 2B showed a net annual energy savings above 5%, whereas locations in IECC climate zones 5B, 6B, and 7 showed a net annual energy penalty greater than 3%. The hot and dry climate of Phoenix, Arizona, showed the highest overall energy savings of 426 kWh (6.2%). Additionally, the mathematical correlation reveals that the net energy savings of a location is positive only when its average cooling degree days is greater than 5.5 or its average heating degree days is less than 10.
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With its unique and trusted earth observations, NASA is a critical source in informing decisions that will help achieve the U.S. goal of Net-Zero Greenhouse Gas (GHG) Emissions by 2050. NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). As part of the development of new data products to support the energy and building heating/cooling design communities, we estimate the changes in energy required to heat and cool buildings in the future climate at 14 different NASA site locations spread throughout the continental United States, as projected by CMIP6 climate models under different emissions scenarios. Bias-corrected downscaled time series of meteorological variables are taken from NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP-CMIP6) downscaled climate model data. The spread between the different model projections is accounted for by analyzing both the ensemble average of 22 CMIP6 models and 6 representative models with different climate sensitivities and different interannual variability. Changes in energy use are estimated in two ways. First, changes in the total annual heating and cooling degree days (HDD and CDD, respectively) are calculated relative to the current climate. This is done at all 14 sites. Second, the downscaled time series are used as inputs into RETScreen(R), a clean energy management decision tool, to give an estimate of heating/cooling energy use for a typical office building. We use this estimation method with model data at Langley Research Center. In the next 50 years, the annual total of HDD (CDD) is projected to decrease by 8-38% (increase by 5-28%) at all sites, with the increase in CDD typically a larger magnitude the decrease in HDD. For a typical small office building at Langley Research Center, the amount of energy needed to cool increases by 33-54% and the amount of energy to heat decreases by 29-40%. POWER is working to develop long term climate data services based on these results to include in future data products to provide to users.
The remnants of Hurricane Ida caused major damage and death in the United States on September 1st, 2021, and 11 people drowned in flooded basement apartments within New York City (NYC). It was catastrophic because the maximum hourly precipitation intensity, recorded as 3.47 inches (88.1 mm) per hour at Central Park, was unprecedentedly high for the NYC region. The stormwater infrastructure in NYC is built for 1.75 inches (44.5 mm) per hour, and so understanding the dynamic risk associated with Ida can inform city planning efforts for climate change’s impact on short duration extreme precipitation events. We contextualize this storm’s record-breaking hourly intensity within the historical record as well as project its risk in the near- to medium-term future using nonstationary stochastic models. These models are conditioned on average temperature (T avg ) and cooling degree day (CDD) projections from three climate models as a covariate, each with a SSP 126 and SSP 370 scenario. The likelihood of such a storm was slowly increasing even before Ida happened, but the projected aggregate reoccurrence risk of an event of Ida’s magnitude over time from the non-stationary models ranges from 4 to 52 times higher than the risk given by the stationary model. Using CDD as a covariate resulted in risks that were more than twice the magnitude than when using T avg . Presenting both covariates provides a broader envelope of uncertainty, which highlights the importance and nuances in the choice of a regionally appropriate covariate for non-stationary risk analysis.
This presentation describes the preparation, validation and provision of MERRA-2 data products to the building industry for use in energy efficient designs, building codes and monitoring energy efficiency. It highlights efforts to use MERRA-2 surface meteorological data products for the derivation of quantities relevant to the energy and building industry such as heating and cooling degree days and building climate zones on a global basis for the past 30 years. A difference of the zones from the first 15 years and last 30 years shows that warming zones are creeping northward. The talk also presents work provide similar parameters for building energy performance assessment requiring data products closer to real time.
The future climate significantly impacts building performance and increases uncertainties in energy simulations. A rising temperature trend is expected to heighten cooling loads during summer and result in more carbon emissions. Understanding the impact of future climate on building performance is significant for policymakers to make informed decisions. Building retrofit measures can improve building energy efficiency and reduce operational carbon emissions, yet their effects under future climate conditions have not been fully investigated so far. Thus, we proposed an assessment methodology for evaluating long-term energy consumption and operational carbon reduction potential using a building stock dataset. For this study, commercial buildings in the northwestern (NW) region were utilized to assess the impacts of future climate and building retrofit. In addition, we selected Montana with a cold and dry climate as an example to analyze and discuss the carbon emission reduction potential in buildings. The main findings are: (1) Under future climate trends, changes in energy use intensity (EUI) will fluctuate due to variations in heating and cooling degree-days (HDDs and CDDs) and increasing HDDs will lead to increasing EUI. (2) After applying annual building retrofitting, the long-term EUI reduction potential of buildings in the NW region will decrease with the increasing retrofitting degree, and the short-term EUI reduction potential will be impacted by the change of heating and cooling degree days. (3) In Montana, the long-term carbon intensity reduction potential of retrofitted buildings will decrease under future climate trends with the increasing renewable energy penetration.
helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.
The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].
The software provides a measure selection technique indicating cost effective retrofit activities that can be applied to a home using a standard Savings to Investment Ratio (SIR). Users must provide an input file describing the characteristics of the home to be evaluated. The software takes the input data provided and calculates energy savings and cost savings predicted for a standard set of measures given the input parameters. The Weatherization Assistant computes estimates of pre-retrofit whole building space heating and cooling energy consumptions based on the house description data supplied by the user. The consumptions are computed using a monthly heating and cooling variable base degree-day method by algorithms similar to those developed for the CIRA program [LBL, 1982]. The building consumptions are needed in computing the energy savings from measures affecting the efficiencies of the heating and cooling equipment. Weatherization Assistant then computes the energy savings and costs for each individual measure applicable to the building described as if it were the only measure installed in the house. From these energy savings, a discounted dollar savings over the life of each measure is computed. The ratio of this dollar savings to the cost of installing the measure, the "savings-to-investment ratio" (SIR), is used in an initial ranking of the measures' effectiveness. The "interacted" savings and SIR of measures are then determined assuming the measures are added to the house collectively, in order of their ranking, e.g., the second ranked measure is installed in the house initially described by the user after having been modified by the first ranked measure. If this second-ranked measure's updated SIR is greater than a user-defined limit, the measure is left implemented, else it is removed so that the next measure's effectiveness is not dependent on it. The choice between two mutually exclusive measures (such as different levels of insulation) is made on the basis of their "net present value" (NPV), the difference of life-time savings and installation cost, rather than their SIR. This has been shown to be the more correct criterion on which to base the selection between two measures, both of which cannot be installed. The audit computes and reports to the user the energy savings, discounted dollar savings, installation cost, and SIR for each measure considered cost-effective. For those with SIR greater than the user-designated cutoff, a materials list gives the material name, type, and quantity required for installation of the measure. Weatherization Assistant permits entry of pre-retrofit billing data for gas or electrically heated homes or homes with electric air-conditioning. The user may then make the decision to have the savings of the measures adjusted to reflect the difference in billed consumption and that predicted by the program.
A one dimensional model of cloud microphysics was used to simulate the formation and evolution of polar stratospheric ice clouds. Some of the processes which are included in the model are outlined. It is found that the clouds must undergo preferential nucleation upon the existing aerosols just as do tropospheric cirrus clouds. Therefore, there is an energy barrier between stratospheric nitric acid particles and ice particles implying that nitric acid does not form a continuous set of solutions between the trihydrate and ice. The Kelvin barrier is not significant in controlling the rate of formation of ice particles. It was found that the cloud properties are sensitive to the rate at which the air parcels cool. In wave clouds, with cooling rates of hundreds of degrees per day, most of the existing aerosols nucleate and become ice particles. Such clouds have particles with sizes on the order of a few microns, optical depths on order of unity and are probably not efficient at removing materials from the stratosphere. In clouds which form with cooling rates of a few degrees per day or less, only a small fraction of the aerosols become cloud particles. In such clouds the particle radius is larger than 10 microns, the optical depths are low and water vapor is efficiently removed. Seasonal simulations show that the lowest water vapor mixing ratio is determined by the lowest temperature reached, and that the time when clouds disappear is controlled by the time when temperatures begin to rise above the minimum values.
The Zaoyang ordinary chondrite fell as a single 14.15-kg mass in Hubey province (China) in October 1984 and was classified as a non-brecciated H5 chondrite, shock facies b. Cooling rate in pyroxenes can be calculated down to about 1000 C by using fine textures and at still lower temperatures (700 to 200 C) by intracrystalline ordering processes. The crystal chemistry of clinopyroxene and orthopyroxene from the matrix of the H5 Zaoyang chondrite has been investigated by X-ray structure refinement and detailed microprobe analysis. By comparison with terrestrial pyroxenes cell and polyhedral volumes in clino- and orthopyroxenes show a low crystallization pressure. Fe(2+) and Mg are rather disordered in M1 and M2 sites of clino- and orthopyroxenes; the closure temperatures of the exchange reaction are 600 and 512 C respectively, which is consistent with a quite fast cooling rate, estimated of the order of one degree per day. The closure temperature for the intercrystalline Ca-Mg exchange reaction for clino- and orthopyroxene showing clinopyroxene lamellae about 10 microns thick. Kinetic evaluations based on the thickness of exolved lamellae give a cooling rate of not more than a few degrees per 10(exp 4) years. The different cooling rates obtained from Fe(2+)-Mg intracrystalline partitioning and exolution lamellae suggest an initial episode of slow cooling at 900 C, followed by faster cooling at temperatures of 600-500 C at low pressure conditions. The most probable scenario of the meteorite history seems that the exolved orthopyroxene entered the parental chondrite body after exolution had taken place at high temperature. Subsequent fast cooling occurred at low temperature after the formation of the body.
Overview This dataset contains XML input files for the IM3 Phase 2 version of GCAM-USA. The files are organized into two categories: Scenario-specific inputs represent hydroclimate and socioeconomic effects on water availability, heating and cooling degree-hours, and agricultural productivity. They support eight IM3 canonical scenarios: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Model-improvement inputs extend GCAM-USA v5.3 with updated representations of coal and nuclear power plant retirements, electricity trade among U.S. interconnections, offshore carbon storage costs, and groundwater depletion constraints. Data structure Scenario-specific inputs rcp45_runoff/ and rcp85_runoff/XML files describing water availability by HUC2 basin under the RCP 4.5 and RCP 8.5 scenarios. rcp45_hdcd/ and rcp85_hdcd/XML files containing monthly-day and monthly-night heating and cooling degree-hours at the U.S. state level for different RCP-SSP combinations. rcp45_agyields/ and rcp85_agyields/XML files describing changes in agricultural productivity at the intersection of GCAM regions and HUC2 water basins for different RCP-SSP combinations. rcp45_emissions_pathway/The emissions-constraint XML file used to represent the RCP 4.5 pathway. Model-improvement inputs core_retire/Updates coal-fired power plant retirement schedules based on New England ISO. GCAMUSA_IM3_elec_trade_interconnect.xmlRestricts electricity trade to occur within the ERCOT, WECC, and IE interconnections. nuclear_USA.xmlUpdates the retirement schedules of the Diablo Canyon and Palisades nuclear power plants. high_cost_offshore_carbon.xmlUpdates the assumed cost of offshore carbon storage. water_supply_constrained_gleeson_5pct.xmlReplaces WaterGAP historical groundwater-depletion estimates with data from the Gleeson dataset and limits groundwater extraction to 5% of the available groundwater in each Superwell grid cell. How to use the data This dataset is designed for use with the IM3 version of GCAM-USA. Download or clone GCAM-USA from the IM3 GCAM GitHub repository at https://github.com/IMMM-SFA/gcam-core and check out the gcam-usa-im3 branch. Place the downloaded folder im3scenarios in the gcam-core/input directory while preserving the provided folder structure.
The nuclear hyperfine doublets of Fe-57 at the two nonequivalent octahedrally coordinated positions M1 and M2 in an olivine from lunar basalt 12018 have been analyzed in the temperature range between 250 and 450 C. The Mg(2+), Fe(2+) is somewhat ordered, the Fe(2+) occupancy being greater at one of the two M positions by approximately 20%. After heating at 1155 C for seven days, the distribution was almost completely disordered. Studies of natural and heated olivines from terrestrial rocks show that the Mg(2+), Fe(2+) exchange reaction in olivines is considerably more sluggish than in chain silicates. Generally no change in site occupancy can be observed after heating at temperatures of approximately 900 C over several days. The observed degree of ordering in the lunar olivine is indicative of slow cooling during crystallization.
In crystal growth, the quality of the final material may depend, among other factors, on its interaction with the walls of the ampoule during and after the growth, and on the rate of the crystal cool-down at the end of ate the process. To investigate the above phenomena, a series of CdTe crystal growth processes was carried out, The crystals were grown by physical vapor transport without contact with the side walls of the silica glass ampoules, applying the Low Supersaturation Nucleation technique. The source temperature was 930 C, the undercooling was a few degrees. The crystals, having the diameter of 25 mm, grew at the rate of a few mm per day. The post-growth cool-down to the room temperature was conducted at different rates, and lasted from a few minutes to four days. The crystals were characterized using chemical etching low temperature luminescence, and Synchrotron White Beam X-ray Topography techniques. The dislocation (etch pit) density was measured and its distribution was analyzed by comparison with Poisson curves and with the Normalized Radial Distribution Correlation Function. It was found that the contact of the crystal with silica leads to a strain field and high (in the 105 sq cm range) dislocation (etch pit) density. Similar defect concentrations were found in crystals subjected to fast post-growth cool-down. Typical EPD values for lower cool-down rates and in regions not affected by wall interactions are in the lower 10(exp 4) sq cm range. In some areas the actual dislocation density was about 10(exp 3) sq cm or even less. No apparent effect of the cool-down rate on polygonization was observed. A fine structure could be discerned in low-temperature PL spectra of crystals with low dislocation density.