Energy Return on Investment: Toward a Consistent Framework

Mulder, Kenneth; Hagens, Nathan John

doi:10.1579/0044-7447(2008)37[74:eroita]2.0.co;2

Cited by 140 publications

(107 citation statements)

References 2 publications

Supporting

Mentioning

106

Contrasting

Unclassified

Order By: Relevance

“…ED in is the amount of direct input energy (Mulder & Hagens, 2008). As indirect energy was accounted for in the form of fertilizers, p k represents the amount of a certain type of fertilizer, whereas m k is the embodied energy of that particular fertilizer.…”

Section: Eroi Methods Used In This Studymentioning

confidence: 99%

A Comparative Analysis of the Energy Return on Investment of Organic and Conventional Icelandic Dairy Farms

Atlason¹,

Kjærheim²,

Davíðsdóttir³

et al. 2015

IAS

View full text Add to dashboard Cite

This study compares the energy return on investment (EROI) of organic and conventional farms in Iceland. It examines which farming method returns the highest amount of edible energy to society relative to the input required. Twenty farms were studied: two organic and 18 conventional. Real data were gathered directly from five farms (including both of the organic farms in the study). Further data from 15 conventional dairy farms of different sizes were collected from a database maintained by the Icelandic Farmers Association. One of the organic farms studied (Org1) was found to have an EROI of 2.68, whereas two conventional farms used as controls for comparison (Con1-a and Con1-b) had EROIs of 0.60 and 0.69, respectively. The second organic farm (Org2) had an EROI of 0.55, versus the control farm ratio of 0.27. On average, large (<170 hectares) conventional dairy farms had an EROI of 0.65, while medium (<70 hectares) and small (<40 hectares) conventional farms had average EROIs of 0.56 and 0.50, respectively. This limited analysis suggests that organic dairy farms may provide better EROIs than conventional farms, but that their dairy yields per hectare are lower. Keywords: Energy analysis, EROI, Agriculture YFIRLIT Samanburður á orkuarðsemi (EROI) lífraenna og hefðbundinna íslenskra kúabúa.Þessi rannsókn ber saman orkuarðsemi (EROI) lífraenna og hefðbundinna íslenskra kúabúa. Athugað er hvaða landbúnaðaraðferð skilar mestri orku til samfélagsins á móti þeirri orku sem notuð er. Tuttugu býli voru rannsökuð, þar sem raungögn voru fengin beint frá 5 býlum. Gögn sem lýsa 15 tilviljanakenndum kúabúum af mismunandi staerðum voru einnig fengin úr búreikningum. Niðurstöður sýna að fyrra lífraena býlið (Org1) skilaði EROI 2.68, hefðbundin samanburðarbýli þess skiluðu 0.60 (Con1-a) og 0.69 (Con1-b). Hitt lífraena býlið (Org2) skilaði EROI 0.55. Samanburðarbýli þess (Con2) skilaði EROI 0.27. EROI meðaltal stórra hefðbundinna býla valin af handahófi var 0.65, meðaltal miðlungs stórra býla var 0.56 og meðaltal lítilla býla var 0.50. Þessi rannsókn gefur til kynna að lífraen kúabú gefi betri orkuarðsemi en hefðbundin býli en að uppskera á hvern hektara sé minni.

show abstract

Section: Eroi Methods Used In This Studymentioning

confidence: 99%

A Comparative Analysis of the Energy Return on Investment of Organic and Conventional Icelandic Dairy Farms

Atlason¹,

Kjærheim²,

Davíðsdóttir³

et al. 2015

IAS

View full text Add to dashboard Cite

show abstract

“…For example, the integral of net power ratio (NPR) equals NER. For summaries of net energy analysis approaches and conceptual constructs, I direct the reader to the literature (Murphy et al 2011;King 2014;Brandt et al 2013;King et al 2015a;Bullard and Herendeen 1975;Mulder and Hagens 2008;Modahl et al 2013).…”

Section: Energy and Net Energymentioning

confidence: 99%

Information Theory to Assess Relations Between Energy and Structure of the U.S. Economy Over Time

King

2016

Biophys Econ Resour Qual

View full text Add to dashboard Cite

This paper describes the changing structure of the United States' (U.S.) domestic economy by applying information theory-based metrics to the U.S. input-output (I-O) tables from 1947 to 2012. Here the I-O tables are an economic network where the sectors are the nodes. The value of these metrics is that they describe the balance or trade-off between efficiency and redundancy of network flows as well as equality and hierarchy of flows through nodes in a network. I relate these metrics to the U.S. gross power consumption and annual intermediate spending by the food and energy sectors, the latter being a proxy for the inverse of the net power ratio (or net energy) of the economy, to test hypotheses of energy-economy structural linkages. The results of this paper show that increasing gross power consumption, as well as a decreasing share of intermediate expenditures of the food and energy sectors, correlates with increased distribution of money among economic sectors, and vice versa. The information theory metrics indicate two time periods at which major structural shifts occurred. The first was between 1967 and 1972, and the second was around the turn of the twenty-first century when food and energy expenditures no longer continued to decrease after 2002. In response to the latter, it is clear that the U.S. economy did trade off structural reserves (e.g., decreasing metrics of conditional entropy, redundancy, and equality) for structural efficiency (e.g., increasing metrics of efficiency, mutual constraint, and hierarchy) after food and energy expenditures increased post-2002. I also test the structural trends with increasingly simpler (e.g., fewer sectors) representations of the I-O tables, and the results are more consistent for I-O representations that account for inputs and outputs (e.g., value added and gross domestic product) rather than only the intermediate transactions among sectors. The findings of this paper have important implications for economic modeling in at least two ways. First, the paper helps explain how fundamental shifts in resources costs relate to economic structure and economic growth. Second, the paper shows that the number of sectors used to represent economic transactions influences the systemic metrics themselves.

show abstract

“…Ethanol from sugar-cane has a reported energy return on energy investment (EROI) of between 1.25 -8 and corn ethanol between 1 -1.34 (Beal 2011;Clarens et al 2011;Mulder and Hagens 2008;Hall and Klitgaard 2012;Twidell and Weir 2006). The growth of crops such as sugar-cane and corn for the production of sugar for bioethanol will be considerably constrained, as these compete directly with food production.…”

Section: Bioethanol Productionmentioning

confidence: 99%