@@ -146,7 +146,7 @@ We used the EE-MRIO model EXIOBASE for 2015 (version3.7, industry-by-industry) [
To integrate HBS data into EXIOBASE we created correspondence tables between the EXIOBASE sectors and the matching COICOP consumption categories used in the HBS. To this end we used the relative expenditure shares of each income quintile on the COICOP consumption categories in the HBS to disaggregate the matching EXIOBASE national household final demand expenditure per sector by income quintile. Using standard input-output techniques we calculated 'total' (i.e. direct and indirect supply chain) energy and carbon intensities per EXIOBASE sector, and multiplied them with the income-stratified EXIOBASE national household final demand expenditure, to estimate the supply chain part of national household energy and carbon footprints by national income quintile.
We used the energy extension 'gross total energy use' from EXIOBASE, which converts final energy consumption in the International Energy Agency (IEA) energy balance data from the territorial to residence principle following the System of Environmental Economic Accounting (SEEA) [@stadler_exiobase_2018], and the EXIOBASE greenhouse gas (GHG) emission extensions CO2, CH4, N2O, SF6, HFCs, and PFCs (all in CO2-equivalence), from combustion, non-combustion, agriculture and waste, but not land-use change [@stadler_exiobase_2018]. Direct household energy use and carbon emissions are included in the environmental footprints.
We used the energy extension 'net energy use: total' from EXIOBASE, which includes final energy use and losses [@usubiagaliano_energy_2020]. The extended energy balances of the International Energy Agency (IEA) are split into gross energy supply and use tables, converted from the territorial to residence principle following the System of Environmental Economic Accounting (SEEA) [@stadler_exiobase_2018], and net energy use is then isolated from the gross energy use tables [@mastrucci_framework_2020]. For calculating the carbon footprint, we used the EXIOBASE greenhouse gas (GHG) emission extensions CO2, CH4, N2O, SF6, HFCs, and PFCs (all in CO2-equivalence), from combustion, non-combustion, agriculture and waste, but not land-use change [@stadler_exiobase_2018]. Direct household energy use and carbon emissions are included in the environmental footprints.
abstract={The global food system is a major energy user and a relevant contributor to climate change. To date, the literature on the energy profile of food systems addresses individual countries and/or food products, and therefore a comparable assessment across regions is still missing. This paper uses a global multi-regional environmentally extended input–output database in combination with newly constructed net energy-use accounts to provide a production and consumption-based stock-take of energy use in the food system across different world regions for the period 2000–2015. Overall, the ratio between energy use in the food system and the economy is slowly decreasing. Likewise, the absolute values point toward a relative decoupling between energy use and food production, as well as to relevant differences in energy types, users, and consumption patterns across world regions. The use of (inefficient) traditional biomass for cooking substantially reduces the expected gap between per capita figures in high- and low-income countries. The variety of energy profiles and the higher exposure to energy security issues compared to the total economy in some regions suggests that interventions in the system should consider the geographical context. Reducing energy use and decarbonizing the supply chains of food products will require a combination of technological measures and behavioral changes in consumption patterns. Interventions should consider the effects beyond the direct effects on energy use, because changing production and consumption patterns in the food system can lead to positive spillovers in the social and environmental dimensions outlined in the Sustainable Development Goals.},
language={en},
number={4},
urldate={2021-03-31},
journal={Journal of Industrial Ecology},
author={Usubiaga‐Liaño, Arkaitz and Behrens, Paul and Daioglou, Vassilis},
year={2020},
keywords={energy footprint, energy use, food system, industrial ecology, input–output analysis},
pages={830--840},
file={Full Text PDF:/home/jaccard/.mozilla/firefox/67kb6jd5.default/zotero/storage/V9X7K9MQ/Usubiaga‐Liaño et al. - 2020 - Energy use in the global food system.pdf:application/pdf;Snapshot:/home/jaccard/.mozilla/firefox/67kb6jd5.default/zotero/storage/EEM3JUH5/jiec.html:text/html}
}
@article{mastrucci_framework_2020,
title={A {Framework} for {Modelling} {Consumption}-{Based} {Energy} {Demand} and {Emission} {Pathways}},
volume={54},
issn={0013-936X},
url={https://doi.org/10.1021/acs.est.9b05968},
doi={10.1021/acs.est.9b05968},
abstract={Energy demand in global climate scenarios is typically derived for sectors – such as buildings, transportation, and industry – rather than from underlying services that could drive energy use in all sectors. This limits the potential to model household consumption and lifestyles as mitigation options through their impact on economy-wide energy demand. We present a framework to estimate the economy-wide energy requirements and carbon emissions associated with future household consumption, by linking Industrial Ecology tools and Integrated Assessment Models (IAM). We apply the framework to assess final energy and emission pathways for meeting three essential and energy-intensive dimensions of basic well-being in India: food, housing and mobility. We show, for example, that nutrition-enhancing dietary changes can reduce emissions by a similar amount as meeting future basic mobility in Indian cities with public transportation. The relative impact of energy demand reduction measures compared to decarbonization differs across these services, with housing having the lowest and food the highest. This framework provides complementary insights to those obtained from IAM by considering a broader set of consumption and well-being-related interventions, and illustrating trade-offs between demand and supply-side options in climate stabilization scenarios.},
number={3},
urldate={2021-03-31},
journal={Environmental Science \& Technology},
author={Mastrucci, Alessio and Min, Jihoon and Usubiaga-Liaño, Arkaitz and Rao, Narasimha D.},
month=feb,
year={2020},
pages={1799--1807},
file={ACS Full Text Snapshot:/home/jaccard/.mozilla/firefox/67kb6jd5.default/zotero/storage/HAS7RG9L/acs.est.html:text/html;Full Text PDF:/home/jaccard/.mozilla/firefox/67kb6jd5.default/zotero/storage/QGUITQG3/Mastrucci et al. - 2020 - A Framework for Modelling Consumption-Based Energy.pdf:application/pdf}
}
@article{vita_durable_2021,
title={Durable {Goods} {Drive} {Two}-{Thirds} of {Global} {Households}’ {Final} {Energy} {Footprints}},
volume={55},
issn={0013-936X},
url={https://doi.org/10.1021/acs.est.0c03890},
doi={10.1021/acs.est.0c03890},
abstract={Sustainability endorses high quality, long-lasting goods. Durable goods, however, often require substantial amounts of energy during their production and use-phase and indirectly through complementary products and services. We quantify the global household’s final energy footprints (EFs) of durable goods and the complementary goods needed to operate, service and maintain durables. We calculate the EFs of 200 goods across 44 individual countries and 5 world regions for the period of 1995–2011. In 2011, we find 68\% of the total global household’s EF (218 EJ) is durable-related broken down as follows: 10\% is due to the production of durables per se, 7\% is embodied in goods complementary to durables (consumables and services) and 51\% is operational energy. At the product level, the highest durable-related EFs are: transport goods (148–648 MJ/cap), housing goods (40–811 MJ/cap), electric appliances (34–181 MJ/cap), and “gas stoves and furnaces” (40–100 MJ/cap). Between 1995 and 2011, the global household EF increased by 28\% (48 EJ), of which 72\% was added by durable-related energy. Globally, a 10\% income growth corresponded to an increase in EF by 9\% in durables, 11\% in complementary consumables and 13\% in complementary services—with even higher elasticities in the emerging economies. The average EF of the emerging economies (35 GJ/cap) is 2.5 times lower than in advanced economies (86 GJ/cap). Efficiency gains were detected in 47 out of 49 regions, but only 16 achieved net energy reductions. The large share of durable-related EF across regions (40–88\%) confirms the dominance of durables in driving EFs, but the diversity of patterns suggests that policy and social factors influence durable-dependency. Demand-side solutions targeting ownership and inter-linkages between durables and complements are key to reduce global energy demand.},
number={5},
urldate={2021-03-31},
journal={Environmental Science \& Technology},
author={Vita, Gibran and Rao, Narasimha D. and Usubiaga-Liaño, Arkaitz and Min, Jihoon and Wood, Richard},
month=mar,
year={2021},
pages={3175--3187},
file={Full Text PDF:/home/jaccard/.mozilla/firefox/67kb6jd5.default/zotero/storage/WFGP3P7L/Vita et al. - 2021 - Durable Goods Drive Two-Thirds of Global Household.pdf:application/pdf}
The environmental extensions we use are emissions of CO2-equivalence (in kilograms) and 'gross total energy use' (in terajoules). We create the CO2-equivalence extension by summing together the greenhouse gases CO2, CH4, N2O, SF6, HFCs, and PFCs, from combustion, noncombustion, agriculture and waste. We use Global Warming Potential (GWP) values for a 100-year time horizon taken from the IPCC Fifth Assessment Report [@myhre_g._anthropogenic_2013 (p.73-79)]: 28 for CH4, 265 for N2O and 23500 for SF6 (HFCs and PFCs are in CO2-equivalence already in the EXIOBASE environmental extensions).
The environmental extensions we use are emissions of CO2-equivalence (in kilograms) and 'net energy use: total' (in terajoules). We create the CO2-equivalence extension by summing together the greenhouse gases CO2, CH4, N2O, SF6, HFCs, and PFCs, from combustion, noncombustion, agriculture and waste. We use Global Warming Potential (GWP) values for a 100-year time horizon taken from the IPCC Fifth Assessment Report [@myhre_g._anthropogenic_2013 (p.73-79)]: 28 for CH4, 265 for N2O and 23500 for SF6 (HFCs and PFCs are in CO2-equivalence already in the EXIOBASE environmental extensions).
The 'gross total energy use' extension in EXIOBASE converts final energy consumption in the International Energy Agency (IEA) energy balance data from the territorial to residence principle following System of Environmental Economic Accounting (SEEA) energy accounting principles. In their Supporting Information 2, Stadler et al. (2018) [@stadler_exiobase_2018] describe the compilation of the energy extensions in EXIOBASE version3.7. Energy supply and use tables from the IEA are converted from the territory to the residence principle before being allocated to the EXIOBASE industries and final demand categories.
The creation of the 'net energy use: total' extension in EXIOBASE is explained in the supplementary information documents of [@usubiagaliano_energy_2020], [@mastrucci_framework_2020] and [@vita_durable_2021]. The extended energy balances of the International Energy Agency (IEA) are first split into gross energy supply and use tables, and converted from the territorial to residence principle following the System of Environmental Economic Accounting (SEEA). This first step was initially explained by Stadler et al. (2018) [@stadler_exiobase_2018] in their Supporting Information 2, where they describe the compilation of the EXIOBASE version 3 original energy extensions: primary energy supply, gross energy supply, gross energy use, and emission-relevant energy use.
The net energy use accounts were developed by [@usubiagaliano_energy_2020] and [@mastrucci_framework_2020] for later EXIOBASE 3 versions. They refer to the final use of energy products (i.e. energy used for transformation processes is excluded) plus all losses of energy (i.e. during extraction, transformation, storage and distribution) and minus exports of energy products [@mastrucci_framework_2020]. Net energy use is then isolated from the gross energy use tables, and allocated to the EXIOBASE industries, products and final demand categories as in the original energy extensions [@usubiagaliano_energy_2020; @mastrucci_framework_2020].
The conversion to the residence principle means that the EXIOBASE energy extensions refer to the functional border of a country's economy. In this case, the system border is defined by the 'residence' of the agent. This means that energy supply and use from international transport by ships, airplanes, fishing vessels, cars and trucks is allocated to the resident units of a country, independent from where these activities take place. In EXIOBASE version3.7, because emissions from these transport activities are estimated from the energy extensions via emission factors, the emissions extensions follow the residence principle as well.
