Experiments for satellite and material recovery from orbit. Volume I - Summary Final report

Experiment missions for OSO satellite rendezvous, capture, material retrieval, refurbishment, and extravehicular operation wor

Experiments for Satellite and Material Recovery from Orbit. Volume III - Experiment Missions Final Report

Experiment missions for OSO satellite rendezvous, capture, material recovery, refurbishment, and extravehicular operation wor

Experiments for satellite and material recovery from orbit. Volume II - Technical Final report

Experiment missions for OSO satellite rendezvous, capture, material retrieval, refurbishment, and extravehicular operation wor

Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2

The activities that produce electric power typically range from extracting and transporting a fuel, to its conversion into electric power, and finally to the disposition of residual by-products. This chain of activities is called a fuel cycle. A fuel cycle has emissions and other effects that result in unintended consequences. When these consequences affect third parties (i.e., those other than the producers and consumers of the fuel-cycle activity) in a way that is not reflected in the price of electricity, they are termed ''hidden'' social costs or externalities. They are the economic value of environmental, health and any other impacts, that the price of electricity does not reflect. How do you estimate the externalities of fuel cycles? Our previous report describes a methodological framework for doing so--called the damage function approach. This approach consists of five steps: (1) characterize the most important fuel cycle activities and their discharges, where importance is based on the expected magnitude of their externalities, (2) estimate the changes in pollutant concentrations or other effects of those activities, by modeling the dispersion and transformation of each pollutant, (3) calculate the impacts on ecosystems, human health, and any other resources of value (such as man-made structures), (4) translate the estimates of impacts into economic terms to estimate damages and benefits, and (5) assess the extent to which these damages and benefits are externalities, not reflected in the price of electricity. Each step requires a different set of equations, models and analysis. Analysts generally believe this to be the best approach for estimating externalities, but it has hardly been used! The reason is that it requires considerable analysis and calculation, and to this point in time, the necessary equations and models have not been assembled. Equally important, the process of identifying and estimating externalities leads to a number of complex issues that also have not been fully addressed. This document contains two types of papers that seek to fill part of this void. Some of the papers describe analytical methods that can be applied to one of the five steps of the damage function approach. The other papers discuss some of the complex issues that arise in trying to estimate externalities. This report, the second in a series of eight reports, is part of a joint study by the U.S. Department of Energy (DOE) and the Commission of the European Communities (EC)* on the externalities of fuel cycles. Most of the papers in this report were originally written as working papers during the initial phases of this study. The papers provide descriptions of the (non-radiological) atmospheric dispersion modeling that the study uses; reviews much of the relevant literature on ecological and health effects, and on the economic valuation of those impacts; contains several papers on some of the more complex and contentious issues in estimating externalities; and describes a method for depicting the quality of scientific information that a study uses. The analytical methods and issues that this report discusses generally pertain to more than one of the fuel cycles, though not necessarily to all of them. The report is divided into six parts, each one focusing on a different subject area

Worker remittances and the global preconditions of ‘smart development’

With the growing environmental crisis affecting our globe, ideas to weigh economic or social progress by the ‘energy input’ necessary to achieve it are increasingly gaining acceptance. This question is intriguing and is being dealt with by a growing number of studies, focusing on the environmental price of human progress. Even more intriguing, however, is the question of which factors of social organization contribute to a responsible use of the resources of our planet to achieve a given social result (‘smart development’). In this essay, we present the first systematic study on how migration – or rather, more concretely, received worker remittances per GDP – helps the nations of our globe to enjoy social and economic progress at a relatively small environmental price. We look at the effects of migration on the balance sheets of societal accounting, based on the ‘ecological price’ of the combined performance of democracy, economic growth, gender equality, human development, research and development, and social cohesion. Feminism in power, economic freedom, population density, the UNDP education index as well as the receipt of worker remittances all significantly contribute towards a ‘smart overall development’, while high military expenditures and a high world economic openness are a bottleneck for ‘smart overall development’

Agglomeration, Inequality and Economic Growth (WP)

The impact of income inequality on economic growth is dependent on several factors, including the time horizon considered, the initial level of income and its initial distribution. Yet, as growth and inequality are also uneven across space, it is also pertinent to consider the effects of the geographical agglomeration of economic activity. Moreover, it would also seem pertinent to consider not just the levels of inequality and agglomeration, but also the changes they undergo -i.e., their within-country evolution- and how these two processes interact with each other. By applying different econometric specifications and by introducing different measures of agglomeration at country level -specifically, urbanization and urban concentration rates-, this study analyzes how inequality and agglomeration -both their levels and their evolution- influence economic growth in function of the country’s level of development and its initial income distribution. Our results suggest, in line with previous studies, that while high inequality levels are a limiting factor for long-run growth, increasing inequality and increasing agglomeration have the potential to enhance growth in low-income countries where income distribution remains relatively equal, but can result in congestion diseconomies in high-income countries, especially if income distribution becomes particularly unequal