A series of hypotheses is presented about the relation of national energy use to national economic activity (both time series and cross-sectional) which offer a different perspective from standard economics for the assessment of historical and current economic events. The analysis incorporates nearly 100 years of time series data and 3 years of cross-sectional data on 87 sectors of the United States economy. Gross national product, labor productivity, and price levels are all correlated closely with various aspects of energy use, and these correlations are improved when corrections are made for energy quality. A large portion of the apparent increase in U.S. energy efficiency has been due to our ability to expand the relative use of high-quality fuels such as petroleum and electricity, and also to relative shifts in fuel use between sectors of the economy. The concept of energy return on investment is introduced as a major driving force in our economy, and data are provided which show a marked decline in energy return on investment for all our principal fuels in recent decades. Future economic growth will depend largely on the net energy yield of alternative fuel sources, and some standard economic models may need to be modified to account for the biophysical constraints on human economic activity.

Brazilian free‐tailed bats (Tadarida brasiliensis) form enormous summer breeding colonies, mostly in caves and under bridges, in south‐central Texas and northern Mexico. Their prey includes several species of adult insects whose larvae are known to be important agricultural pests, including the corn earworm or cotton bollworm (Helicoverpa zea). We estimate the bats' value as pest control for cotton production in an eight‐county region in south‐central Texas. Our calculations show an annual value of $741 000 per year, with a range of $121 000–$1 725 000, compared to a $4.6–$6.4 million per year annual cotton harvest.

Abstract:The main objective of this manuscript is to provide a formal methodology, structure, and nomenclature for EROI analysis that is both consistent, so that all EROI numbers across various processes can be compared, and also flexible, so that changes or additions to the universal formula can focus analyses on specific areas of concern. To accomplish this objective we address four areas that are of particular interest within EROI analysis: (1) boundaries of the system under analysis, (2) energy quality corrections, (3) energy-economic conversions, and (4) alternative EROI statistics. Lastly, we present step-by-step instructions outlining how to perform an EROI analysis.

No abstract

No abstract