Abstract:Replacing traditional technologies by renewables can lead to an increase of emissions during early diffusion stages if the emissions avoided during the use phase are exceeded by those associated with the deployment of new units. Based on historical developments and on counterfactual scenarios in which we assume that selected renewable technologies did not diffuse, we conclude that onshore and offshore wind energy have had a positive contribution to climate change mitigation since the beginning of their diffusi… Show more
“…The indirect CO2 emission factors (IEF) associated with the construction of power sector technologies have been calculated by means of input-output based hybrid LCA -a variant of EEIO analysis (full details of the method are reported in (Usubiaga et al 2017)). This method consists of a disaggregation of an input-output table and its environmental extension(s) based on data from lifecycle inventories (LCI), and the use of EEIO analysis to calculate consumption-based pressures (Suh and Huppes 2005) -in this case, CO2 emissions.…”
Section: Developing Indirect Emission Factors For Power Sector Technomentioning
confidence: 99%
“…As for the carbon emissions of each of these subproduct groups, the direct emission intensities from Ecoinvent have been multiplied by the corresponding product output. More details are provided in the original source (Usubiaga et al 2017).…”
Section: Developing Indirect Emission Factors For Power Sector Technomentioning
confidence: 99%
“…The indirect emissions factors generated by (Usubiaga et al 2017) were compared against emissions factors identified in the wider LCA literature (Masanet et al 2013). By making assumptions about average load factors, the CO2/MW factors generated by Usubiaga et al were compared with those from Masanet et al (which are expressed in terms of gCO2/kWh).…”
Section: Developing Indirect Emission Factors For Power Sector Technomentioning
confidence: 99%
“…Against this background, we have soft-linked an environmentally-extended input-output (EEIO) model to an ESOM. Indirect emissions from power sector technologies were obtained from a disaggregated EEIO model (see Usubiaga et al 2017) and were then incorporated into the UCL European TIMES Model (ETM-UCL; (Solano-Rodriguez and Pye 2014)) with the aim to address the following questions:…”
Section: Introductionmentioning
confidence: 99%
“…The energy demands -and hence emissions -arising from the manufacture of energy technologies are implicitly assumed to be constant across scenarios. Yet in the real world, the indirect emissions associated with processes such as the construction and manufacture of low-carbon energy technologies differs from their high-carbon alternatives, and structural shifts to low-carbon technologies (such as wind, for example) might be expected to lead to increases in activity and hence emissions from the industrial sector relative to the case in which fossil fuels continue to be used (at least during periods of installation and deployment of low-carbon technologies; (Usubiaga et al 2017)). Such endogenous changes in industrial production implied by energy transition scenarios have previously been ignored by most ESOMs (including dominant modelling systems such as MARKAL/TIMES and MESSAGE), suggesting that there is value in integrating life-cycle or similar approaches with ESOM analysis.…”
This paper first reviews previous relevant efforts to bring energy system models and life-cycle assessments together. In section 3, we set out the method we have used, including the details of the EEIO model, the TIMES model, the procedures for linking them, and the scenarios examined. Section 4 then provides results relating to each of the research questions, while section 5 draws key conclusions. The paper is accompanied by a supplementary file that includes considerable further detail on the modelling approach, the data used, and the results. 2 Literature review Bottom-up ESOMs (such as MARKAL [Loulou et al. 2004] and TIMES [Loulou et al. 2004]) and MESSAGE (Messner and Schrattenholzer 2000)) provide a detailed depiction of the energy system, with explicit representation of primary extraction of energy resources, processing and conversion, delivery to consumers, and end-use (DeCarolis et al. 2017). Such models account for some emissions associated with upstream extraction (flaring, for example), and they account for the efficiency losses and energy inputs associated with conversion and processing (e.g. in refineries and power stations), with transmission and distribution (losses in electricity transmission lines, energy use in fuel distribution, etc.), and efficiency losses in end use devices. Many sources of fossil fuel chain indirect emissions are thus already included in the default setup of TIMES (see the supplementary file for further details). ESOMs are "demand-driven" in the sense that the energy service demands across the economy are a key exogenous input into the models. Energy service demands associated with
“…The indirect CO2 emission factors (IEF) associated with the construction of power sector technologies have been calculated by means of input-output based hybrid LCA -a variant of EEIO analysis (full details of the method are reported in (Usubiaga et al 2017)). This method consists of a disaggregation of an input-output table and its environmental extension(s) based on data from lifecycle inventories (LCI), and the use of EEIO analysis to calculate consumption-based pressures (Suh and Huppes 2005) -in this case, CO2 emissions.…”
Section: Developing Indirect Emission Factors For Power Sector Technomentioning
confidence: 99%
“…As for the carbon emissions of each of these subproduct groups, the direct emission intensities from Ecoinvent have been multiplied by the corresponding product output. More details are provided in the original source (Usubiaga et al 2017).…”
Section: Developing Indirect Emission Factors For Power Sector Technomentioning
confidence: 99%
“…The indirect emissions factors generated by (Usubiaga et al 2017) were compared against emissions factors identified in the wider LCA literature (Masanet et al 2013). By making assumptions about average load factors, the CO2/MW factors generated by Usubiaga et al were compared with those from Masanet et al (which are expressed in terms of gCO2/kWh).…”
Section: Developing Indirect Emission Factors For Power Sector Technomentioning
confidence: 99%
“…Against this background, we have soft-linked an environmentally-extended input-output (EEIO) model to an ESOM. Indirect emissions from power sector technologies were obtained from a disaggregated EEIO model (see Usubiaga et al 2017) and were then incorporated into the UCL European TIMES Model (ETM-UCL; (Solano-Rodriguez and Pye 2014)) with the aim to address the following questions:…”
Section: Introductionmentioning
confidence: 99%
“…The energy demands -and hence emissions -arising from the manufacture of energy technologies are implicitly assumed to be constant across scenarios. Yet in the real world, the indirect emissions associated with processes such as the construction and manufacture of low-carbon energy technologies differs from their high-carbon alternatives, and structural shifts to low-carbon technologies (such as wind, for example) might be expected to lead to increases in activity and hence emissions from the industrial sector relative to the case in which fossil fuels continue to be used (at least during periods of installation and deployment of low-carbon technologies; (Usubiaga et al 2017)). Such endogenous changes in industrial production implied by energy transition scenarios have previously been ignored by most ESOMs (including dominant modelling systems such as MARKAL/TIMES and MESSAGE), suggesting that there is value in integrating life-cycle or similar approaches with ESOM analysis.…”
This paper first reviews previous relevant efforts to bring energy system models and life-cycle assessments together. In section 3, we set out the method we have used, including the details of the EEIO model, the TIMES model, the procedures for linking them, and the scenarios examined. Section 4 then provides results relating to each of the research questions, while section 5 draws key conclusions. The paper is accompanied by a supplementary file that includes considerable further detail on the modelling approach, the data used, and the results. 2 Literature review Bottom-up ESOMs (such as MARKAL [Loulou et al. 2004] and TIMES [Loulou et al. 2004]) and MESSAGE (Messner and Schrattenholzer 2000)) provide a detailed depiction of the energy system, with explicit representation of primary extraction of energy resources, processing and conversion, delivery to consumers, and end-use (DeCarolis et al. 2017). Such models account for some emissions associated with upstream extraction (flaring, for example), and they account for the efficiency losses and energy inputs associated with conversion and processing (e.g. in refineries and power stations), with transmission and distribution (losses in electricity transmission lines, energy use in fuel distribution, etc.), and efficiency losses in end use devices. Many sources of fossil fuel chain indirect emissions are thus already included in the default setup of TIMES (see the supplementary file for further details). ESOMs are "demand-driven" in the sense that the energy service demands across the economy are a key exogenous input into the models. Energy service demands associated with
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