Joao Alexandre Almeida dos Santos
@maretec.org
Instituto Superior Técnico, University of Lisbon
MARETEC - Marine, Environment and Technology Center
RESEARCH INTERESTS
Main research interests: Energy systems; energy accounting variables (focus on the thermodynamics concepts of exergy and useful work/exergy) and their links to economic growth and energy demand at the sectoral and country-level; energy and exergy efficiency analysis, namely primary-to-final and fina
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
João Gonçalves, João Santos, Matthew Heun, Paul E. Brockway, and Tiago Domingos
MDPI AG
Conventional economic growth models treat production/consumption as abstractions linked only by money flows, disregarding their connection to the physical world. Nevertheless, the existing literature suggests that energy flows can influence production and links useful exergy prices with economic growth. Useful exergy is energy measured at the stage where it produces an end-use (and is a measurement of energy quality). Not all approaches in the literature use this metric and they often consider energy as a primary input (despite it being an intermediate input). We explore the relationship between energy flows and economic growth for the US through a framework where useful exergy, the output of an “extended energy sector” (where all effects of increasing primary-to-final-to-useful exergy efficiency are located), is an intermediate input for a “non-energy sector”. Together, they encompass the entire economy. We conclude that the share of investment in the extended energy sector grew with the overall economic growth throughout 1960–2020, while the labour share decreased. The non-energy sector contributed the largest share of consumption, exports, imports and labour. In recent years, the energy sector has overtaken it in terms of investment. Our two-sector model has important implications for current climate policy, namely regarding the Integrated Assessment Models on which it is based.
Marco Vittorio Ecclesia, João Santos, Paul E. Brockway, and Tiago Domingos
MDPI AG
Energy return on investment (EROI) is a ratio of the energy obtained in relation to the energy used to extract/produce it. The EROI of fossil fuels is globally decreasing. What do the declining EROIs of energy sources imply for society as a whole? We answer this question by proposing a novel EROI measure that describes, through one parameter, the efficiency of a society in managing energy resources over time. Our comprehensive societal EROI measure was developed by (1) expanding the boundaries of the analysis up to the useful stage; (2) estimating the amount of energy embodied in the energy-converting capital; (3) considering non-conventional sources such as the muscle work of humans and draught animals; and (4) considering the influence of imported and exported energy. We computed the new EROI for Portugal as a case study. We find a considerably lower EROI value, at around 3, compared to those currently available, which is stable over a long-time range (1960–2014). This suggests an independence of EROI from economic growth. When estimated at the final stage, using conventional methods (i.e., without applying the four novelties here introduced), we find a declining societal EROI. Therefore, our results imply that the production of new and more efficient final-to-useful energy converting capital has historically kept societal EROI around a stable value by offsetting the effects of the changing returns of energy sources at the primary and final stages. This will be crucial in the successful transition to renewables.
João Santos, Afonso S. Borges, and Tiago Domingos
Elsevier BV
João Santos, Tiago Domingos, Tânia Sousa, and Miguel St. Aubyn
Elsevier BV
Matthew Heun, João Santos, Paul Brockway, Randall Pruim, Tiago Domingos, and Marco Sakai
MDPI AG
This dataset contains the empirical datasets undertaken for the following Energies journal article: Heun, M.K., J. Santos, Brockway, P.E., Prium, R., Domingos, T., Sakai, M. From theory to econometrics to energy policy: Cautionary tales for policymaking using aggregate production functions. Energies 2017, 10, 203. This data repository contains the following files Excel file • Cautionary_Tales.xlsx: the csv file sheets collated into one excel file csv files We also provide 10 individual csv files (which match those in the excel file): • Readme.txt: text file to be read at the start • Fig-3-PT-QA.csv: indexed k, l, and e, quality-adjusted factors of production for Portugal as shown in Figure 3 • Fig-3-PT-UA.csv: indexed k, l, and e, quality-adjusted factors of production for Portugal as shown in Figure 3 • Fig-3-UK-QA.csv: indexed k, l, and e, unadjusted factors of production for the United Kingdom as shown in Figure 3 • Fig-3-UK-UA.csv: indexed k, l, and e, unadjusted factors of production for the United Kingdom as shown in Figure 3 • Fig-4-GDP.csv: Data behind Figure 4 • Table-S-1.csv: Data from Table S.1 of the supplementary information • Table-S-2.csv: Data from Table S.2 of the supplementary information • Table-S-3.csv: Data from Table S.3 of the supplementary information. • PT-raw-data.csv: unadjusted portugal data (from which the indexed data was calculated) for QA labor, primary exergy, useful exergy, QA capital. • UK-raw-data.csv: unadjusted UK data (from which the indexed data was calculated) for QA labor, primary exergy, useful exergy. Data sources can be found in Table 3 of the paper. For clarity, the UK-QA capital service indexed data was calculated based on the growth rate data given in Table A1, VICS growth rates with RD
Paul Brockway, Matthew Heun, João Santos, and John Barrett
MDPI AG
Capital–labour–energy Constant Elasticity of Substitution (CES) production functions and their estimated parameters now form a key part of energy–economy models which inform energy and emissions policy. However, the collation and guidance as to the specification and estimation choices involved with such energy-extended CES functions is disparate. This risks poorly specified and estimated CES functions, with knock-on implications for downstream energy–economic models and climate policy. In response, as a first step, this paper assembles in one place the major considerations involved in the empirical estimation of these CES functions. Discussions of the choices and their implications lead to recommendations for CES empiricists. The extensive bibliography allows those interested to dig deeper into any aspect of the CES parameter estimation process.