Better energy indicators for sustainable development

Taylor, Peter; Abdalla, Kathleen L.; Quadrelli, Roberta; Vera, Ivan

doi:10.1038/nenergy.2017.117

Cited by 44 publications

(40 citation statements)

References 5 publications

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“…Of course, economic questions arise also in the interplay between SDG7 and the other SDGs (e.g., with SDG8, which promotes sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all). This is in line with the call by Taylor et al [2017] for researchers in this field to create better energy indicators for sustainable development and to address the key challenge to improve current indicator methodologies.…”

Section: Discussionsupporting

confidence: 77%

What drives total real unit energy costs globally? A novel LMDI decomposition approach

Kaltenegger

2020

Applied Energy

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractThis paper presents a novel logarithmic mean Divisia index (LMDI) decomposition framework that is tailor-made for unit cost indicators. It adds four new models to the existing LMDI model family. The main novelty of the new framework lies in the separation of quantity and price effects captured in unit cost indicators, while retaining the same desirable properties of traditional models. Four case studies apply the novel LMDI framework to the total real unit energy costs (total RUEC) indicator. Total RUEC represents the sum of direct energy costs (for energy products) and indirect energy costs (energy costs embedded in intermediate inputs and passed on along global value chains) as a fraction of value added. This yardstick allows for monitoring shifts in the burden of energy costs on industries. The first three case studies, based on the World Input-Output Database, cover the period between 1995 and 2009. For an up-to-date analysis, a fourth case study collects additional data for 2009-2016 from energy and economic statistics' institutions. Globally, up until 2009, rising costs for crude petroleum/natural gas and the rise of China in the global economy were the largest drivers of total RUEC. In general, increases of indirect energy costs were more substantial than were those of direct energy costs. The total RUEC of Chinese car manufacturers increased much more strongly than did that of American car manufacturers. After 2009 (until 2016), prices for crude petroleum/natural gas and value added generation were major decelerating factors of global direct RUEC, while increases in energy consumption had offsetting effects. This paper provides a suitable tool to scientists who want to build on unit cost indicators in their research in general and to all policy-oriented institutions concerned with monitoring and analysing the energy transition in particular. Highlights• This paper presents a novel logarithmic mean Divisia index decomposition framework.• It contributes four new models to the existing LMDI model family.• First LMDI models that separate quantity and price effects.• Four case studies apply the LMDI framework to the total RUEC indicator.• This paper provides a new tool, particularly for monitoring the energy transition.

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Section: Discussionsupporting

confidence: 77%

What drives total real unit energy costs globally? A novel LMDI decomposition approach

Kaltenegger

2020

Applied Energy

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“…There is also an increasing literature on assessing SDGs and their various interactions [18][19][20][21]. In particular, McCollum et al [21] explicitly link energy targets to other SDGs in a qualitative literature review of synergies (and in fewer cases, potential conflicts between goals).…”

Section: Introductionmentioning

confidence: 99%

Threshold Electricity Consumption Enables Multiple Sustainable Development Goals

Brecha

2019

Sustainability

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Access to sufficient amounts of energy is a prerequisite for the development of human well-being. The Sustainable Development Goals (SDGs) recognize the interconnectedness of climate change, energy access and development. However, not all SDG targets are quantified, leaving room for ambiguity in fulfilling, for example, the goal of ensuring access to affordable, reliable, sustainable and modern energy for all (SDG7). We show how specific sustainable development targets for health indicators are strongly correlated with electricity consumption levels in the poorest of countries. Clear thresholds in per capita electricity consumption of a few hundred kWh per year are identified by analyzing SDG indicator data as a function of per capita country electricity consumption. Those thresholds are strongly correlated with meeting of SDG 3 targets-below the identified thresholds, countries do not meet the SDG targets, while above the threshold there is a clear relationship between increasing consumption of electricity and improvement of SDG indicators. Electricity consumption of 400 kWh per capita is significantly higher than projections made by international agencies for future energy access, but only 5%–10% that of OECD countries. At the very least, the presence of thresholds and historical data patterns requires an understanding of how SDG targets would be met in the absence of this threshold level of electricity access.

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“…Therefore, it is difficult for energy intensity to measure whether the production process is efficient or not. Energy intensity is not a well-performing measurement or proxy for energy efficiency [14].…”

Section: Energy Intensitymentioning

confidence: 99%

Energy Efficiency Measurement: A VO TFEE Approach and Its Application

Diao

Wang

et al. 2021

Sustainability

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Energy efficiency is crucial to the 2030 UN Sustainable Development Goals (SDGs), but its widely measured indicator, energy intensity, is still insufficient. For this reason, in 2006, total factor energy efficiency (TFEE) was proposed with capital, labor, and energy as inputs and GDP as the desirable output. The later TFEE approach further incorporated pollution as the undesirable output. However, it is problematic to regard GDP (the total value of final products) as the desirable output, because GDP does not include the intermediate consumption, which accounts for a large part of the production activities and may even be larger than the value of GDP. GDP is more suitable for measuring distribution, while VO (value of output) is more appropriate for sustainable production analysis. Therefore, we propose a VO TFEE approach that takes VO as the desirable output instead and correspondingly incorporates the other intermediate materials and services except energy into inputs. Finally, the empirical analysis of the textile industry of EU member states during 2011–2017 indicates that the VO TFEE approach is more stable and convergent in measuring energy efficiency, and is more suitable for helping policymakers achieve the SDGs of energy saving, emissions reduction, and sustainable economic development.

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Better energy indicators for sustainable development

Cited by 44 publications

References 5 publications

What drives total real unit energy costs globally? A novel LMDI decomposition approach

What drives total real unit energy costs globally? A novel LMDI decomposition approach

Threshold Electricity Consumption Enables Multiple Sustainable Development Goals

Energy Efficiency Measurement: A VO TFEE Approach and Its Application

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