FORCE Training: Tool for Economic AnaLysis (TEAL)
A presentation for an introduction to the Tool for Economic AnaLysis (TEAL) plugin.
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A presentation for an introduction to the Tool for Economic AnaLysis (TEAL) plugin.
Nimbus-7 cloud and Earth radiation budget data are compared in a study of the effects of clouds on the tropical radiation budget. The data consist of daily averages over fixed 500 sq km target areas, and the months of July 1979 and January 1980 were chosen to show the effect of seasonal changes. Six climate regions, consisting of 14 to 24 target areas each, were picked for intensive analysis because they exemplified the range in the tropical cloud/net radiation interactions. The normal analysis was to consider net radiation as the independent variable and examine how cloud cover, cloud type, albedo and emitted radiation varied with the net radiation. Two recurring themes keep repeating on a local, regional, and zonal basis: the net radiation is strongly influenced by the average cloud type and amount present, but most net radiation values could be produced by several combinations of cloud types and amount. The regions of highest net radiation (greater than 125 W/sq m) tend to have medium to heavy cloud cover. In these cases, thin medium altitude clouds predominate. Their cloud tops are normally too warm to be classified as cirrus by the Nimbus cloud algorithm. A common feature in the tropical oceans are large regions where the total regional cloud cover varies from 20 to 90 percent, but with little regional difference in the net radiation. The monsoon and rain areas are high net radiation regions.
Nimbus-7 cloud and earth radiation budget data are compared in a study of the effects of clouds on the tropical radiation budget. The data consist of daily averages over fixed 500 sq km target areas, and the months of July 1979 and January 1980 were chosen to show the effect of seasonal changes. Six climate regions, consisting of 14 to 24 target areas each, were picked for intensive analysis because they exemplified the range in the tropical cloud/net radiation interactions. It is found that the net radiation is strongly influenced by the average cloud type and amount present, but most net radiation values could be produced by several combinations of cloud types and amount. The regions of highest net radiation (greater than 125 W/sq m) tend to have medium to heavy cloud cover. In these cases, thin medium-altitude clouds predominate. Their cloud tops are normally too warm to be classified as cirrus by the Nimbus cloud algorithm. In the tropical oceans there are large regions where the total regional cloud cover varies from 20 to 90 percent, but with little regional difference in the net radiation. The monsoon and rain areas are high net radiation regions.
Increasing envelope facet albedos considerably reduces solar heat gain, thus yielding building cooling energy savings. Few studies have explored the potential benefits of utilizing cool coatings on building envelopes (“cool-coated buildings”) based on life-cycle cost analysis. A holistic approach integrating the field testing, building energy simulation, and a 20-year life-cycle-based optimization was developed to explore cool-coated building performance and the maximum net savings of optimal building envelope retrofit and design. Experimental results showed that applying cool coatings to a west wall of an office building in Chongqing, China reduced its exterior surface temperature by up to 9.3 °C in summer. Additionally, simulation results showed that in Chongqing, making the roof and walls cool could reduce annual HVAC electricity use by up to 11.9% in old buildings (with poorly insulated envelopes) and up to 5.9% in new buildings. Retrofitting old buildings with a cool roof provided the net savings per modified area with present values up to 42.8 CNY/m2; retrofitting a new building with a cool roof or cool walls was not cost-effective. Optimizing both envelope insulation and envelope albedo can achieve 5.6 times the net savings of optimizing the insulation only, and 1.6 times that of optimizing albedo only.
Estimates of the true atmospheric net fluxes at the four Pioneer Venus entry sites are presently obtained through corrections of measured values that are relatively small for the case of the clouds, but generally large deeper in the atmosphere. The correction procedure for both the small and large probe fluxes used model results near 14 km to establish the size of the correction. The thermal net fluxes obtained imply that the contribution of mode 3 particles to the IR opacity of the middle and lower clouds is smaller than indicated by the Pioneer Venus cloud particle spectrometer measurements, and the day probe results favor a reduction of only about 50 percent. The fluxes at all sites imply that a yet-undetermined source of considerable opacity is present in the upper cloud. Beneath the clouds, the thermal net fluxes generally increase with increasing latitude.
The chemistry and mineralogy of soils reflects the chemistry of the atmosphere below which they develop. Today the presence of a cover of land plants can obscure the signature of a highly oxidizing atmosphere. Prior to the advent of higher land plants ca. 400 m.y. ago the obscuring effect of a biological interface should have been minor. It can be shown that under such conditions the behavior of ferrous iron during weathering depends on the relationship between the ratio of the net concentration of oxidants to the concentration of acids in rainwater, and on the ratio of the oxygen demand to the acid demand for complete weathering of the parent rock. An analysis of the behavior of iron in some 15 paleosols between 1.0 and 2.9 b.y. in age showed some time ago that iron was retained, or largely retained, in paleosols developed on rocks with a low ratio of oxidant demand to acid demand (R value) and was lost from paleosols with a high R value. The results indicate that between 1.1 and 2.9 b.y.b.p. the ratio of the net concentration of oxidants to CO2 in rainwater was less than ca. 1/600 of the present-day value. Work during the past year has sought to extend the data base for paleosols and to define more precisely the relationships between the composition of paleosols and the chemistry of the atmosphere below which they developed.
The calculated value of net thrust of an aircraft powered by a General Electric F404-GE-400 afterburning turbofan engine was evaluated for its sensitivity to various input parameters. The effects of a 1.0-percent change in each input parameter on the calculated value of net thrust with two calculation methods are compared. This paper presents the results of these comparisons and also gives the estimated accuracy of the overall net thrust calculation as determined from the influence coefficients and estimated parameter measurement accuracies.
In the early 1990s, the first small, eye-safe, and autonomous lidar system was developed, the Micropulse Lidar (MPL). The MPL acquires signal profiles of backscattered laser light from aerosols and clouds. The signals are analyzed to yield multiple layer heights, optical depths of each layer, average extinction-to-backscatter ratios for each layer, and profiles of extinction in each layer. In 2000, several MPL sites were organized into a coordinated network, called MPL-Net, by the Cloud and Aerosol Lidar Group at NASA Goddard Space Flight Center (GSFC) using funding provided by the NASA Earth Observing System. tn addition to the funding provided by NASA EOS, the NASA CERES Ground Validation Group supplied four MPL systems to the project, and the NASA TOMS group contributed their MPL for work at GSFC. The Atmospheric Radiation Measurement Program (ARM) also agreed to make their data available to the MPL-Net project for processing. In addition to the initial NASA and ARM operated sites, several other independent research groups have also expressed interest in joining the network using their own instruments. Finally, a limited amount of EOS funding was set aside to participate in various field experiments each year. The NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project also provides funds to deploy their MPL during ocean research cruises. All together, the MPL-Net project has participated in four major field experiments since 2000. Most MPL-Net sites and field experiment locations are also co-located with sunphotometers in the NASA Aerosol Robotic Network. (AERONET). Therefore, at these locations data is collected on both aerosol and cloud vertical structure as well as column optical depth and sky radiance. Real-time data products are now available from most MPL-Net sites. Our real-time products are generated at times of AERONET aerosol optical depth (AOD) measurements. The AERONET AOD is used as input to our processing routines, which calculate the aerosol layer top height and extinction profile, and our MPL calibration value. A variety of other data products are available or under development. We present an overview of the MPL-Net project and discuss data products useful to the AERONET community. Results from several sites and field experiments will be presented.
The potential of passive 'manipulators' for altering the large scale turbulent structures in boundary layers was investigated. Utilizing smoke wire visualization and multisensor probes, the experiment verified that the outer scales could be suppressed by simple arrangements of parallel plates. As a result of suppressing the outer scales in turbulent layers, a decrease in the streamwise growth of the boundary layer thickness was achieved and was coupled with a 30 percent decrease in the local wall friction coefficient. After accounting for the drag on the manipulator plates, the net drag reduction reached a value of 20 percent within 55 boundary layer thicknesses downstream of the device. No evidence for the reoccurrence of the outer scales was present at this streamwise distance thereby suggesting that further reductions in the net drag are attainable. The frequency of occurrence of the wall events is simultaneously dependent on the two parameters, Re2 delta sub 2 and Re sub x. As a result of being able to independently control the inner and outer boundary layer characteristics with these manipulators, a different view of these layers emerged.
Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).
Underlying each of the Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a Life-Cycle Cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample in order to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level financial data (Fujita, 2016). Major topics covered in this report include: Discount rate estimation methods and rationale; -Data sources used and data limitations; -Discount rate distributions for use in standards analysis; -Discount rate estimation methods and distributions specific to the small business subgroup analysis. Going forward, this report will be updated as data allow and analyses necessitate.
Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: -Discount rate estimation methods and rationale -Data sources used and data limitations -Discount rate distributions for use in standards analysis -Discount rate estimation methods and distributions specific to the small business subgroup analysis A version of this analysis was most recently released in 2022. Going forward, this report will be updated as data allow and analyses necessitate.
Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process relying on the Capital Asset Pricing Model (CAPM) to estimate a business’ cost of equity, and by adding a risk adjustment factor to the risk-free rate associated with long-term U.S. Treasury bonds to estimate their cost of debt. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: • Discount rate estimation methods and rationale • Data sources used and data limitations • Discount rate distributions for use in standards analysis • Discount rate estimation methods and distributions specific to the small business subgroup analysis.
An instance-based learning system is presented. SC-net is a fuzzy hybrid connectionist, symbolic learning system. It remembers some examples and makes groups of examples into exemplars. All real-valued attributes are represented as fuzzy sets. The network representation and learning method is described. To illustrate this approach to learning in fuzzy domains, an example of segmenting magnetic resonance images of the brain is discussed. Clearly, the boundaries between human tissues are ill-defined or fuzzy. Example fuzzy rules for recognition are generated. Segmentations are presented that provide results that radiologists find useful.
A four-step autoignition model was used to derive an expression for the ignition delay (ID) measured in ignition quality testers (IQT) with the derived cetane number (DCN) determined from this ID using the ASTM D6890 standard correlation. The model predicts DCN for individual compounds and blends as a function of each compound's global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in each compound. Measurement data for 125 compounds and 94 binary and ternary blends (including oxygenates: alcohols, aldehydes, esters, ethers, and ketones), from literature and from measurements performed in our lab, were used to obtain the dependence of the measured ignition delay on each functional group. The new kinetic model-based group contribution method was able to predict the ignition delay of both pure compounds and blends, with an average DCN error of 4.4 (19%) and 2.8 (11%), respectively. Here, the blend model was also used to develop an ID mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule gave an average DCN error of 3.6 (16%) for blends. Both the blend model and mixing rule were found to be superior compared to standard linear by volume fraction or mole fraction mixing rules commonly used to estimate the DCN of mixtures.
This Handbook summarizes the radiation data from the Soviet 'North Pole' drifting research stations operated in the Arctic from 1950 to 1991. The Handbook contains reduced mean monthly values of the fluxes of solar radiation for solar elevations up to 35 deg at 5 deg intervals, monthly totals of the net radiation and its constituents, and mean monthly values of the albedo of the sea-ice surfaces. The Handbook presents information of interest to specialists studying the physics of the atmosphere, climatology, geography, and related disciplines.
A simple four-step autoignition model was used to derive an expression for the ignition delay and derived cetane number (DCN) measured by ignition quality testers (IQT) for oxygenated compounds and blends as a function of each compound’s global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in a given compound. Measurements for 124 compounds and 94 binary and ternary blends, gathered from the literature and performed at UW-Madison, were used to obtain the explicit dependence of the measured ignition delay on each functional group. The new model was able to successfully describe the ignition behavior of both the compounds and blends, with an average DCN error of 5.0 (22%) and 3.5 (15%), respectively. Additionally, the blend model could naturally be modified into a mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule was found to offer improvements over the full prediction, with an average DCN error of 3.2 (14%).
A four-step autoignition model was used to derive an expression for the ignition delay and derived cetane number (DCN) measured by ignition quality testers (IQT) for oxygenated compounds and blends as a function of each compound’s global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in a compound. Measurements for 124 compounds and 94 binary and ternary blends, gathered from the literature and performed at UW-Madison, were used to obtain the dependence of the measured ignition delay on each functional group. The new model was able to describe the ignition behavior of both the compounds and blends, with an average DCN error of 5.0 (22%) and 3.5 (15%), respectively. Additionally, the blend model was transformed into a mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule was found to offer improvements over the full prediction, with an average DCN error of 3.2 (14%).