Editing IPCC:AR6/WGIII/Chapter-2 (section)

=== Box 2.1 | Policy Applications of Consumption-based Emissions ===

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Consumption-based emissions provide additional or complementary information to production-based emissions that can be used for a variety of policy applications. These include:

'''•''' Complementary national-level emissions accounting and target or budget setting

'''•''' Raising awareness and increasing understanding of the GHG effects of consumption

'''•''' Accounting for and understanding of distributional and responsibility issues in GHG emissions mitigation, both nationally and internationally

'''•''' Incentives to change consumption patterns or reduce consumption (e.g., through taxation policies)

'''•''' Accounting for and understanding of carbon leakage and emissions embodied in trade*

'''•''' International emissions trading schemes or linked national schemes

'''•''' Trade policies addressing emissions embodied in trade and international supply chains (e.g., border tax adjustments and clean technology transfers, carbon offsetting or financing, etc.)

'''•''' Including embodied emissions in product performance standards and labelling

'''•''' Policies of public and private procurement

'''•''' Agreements with international suppliers

'''•''' Discussing the climate impacts of lifestyles and inequalities in consumption and associated emissions.

The points above are based on a synopsis of studies ( [[#Steininger--2014|Steininger et al. 2014]] ; [[#Afionis--2017|Afionis et al. 2017]] ; [[#Hubacek--2017b|Hubacek et al. 2017b]] ; [[#Wang--2018|Wang and Zhou 2018]] ; [[#Bolea--2020|Bolea et al. 2020]] ).

\* Note, however, that comparing embodied emissions in trade between countries is further complicated by the fact that emission intensities differ across countries. Approaches to adjust for these differences and facilitate comparisons have been suggested ( [[#Kander--2015|Kander et al. 2015]] ; [[#Baumert--2019|Baumert et al. 2019]] ; [[#Dietzenbacher--2020|Dietzenbacher et al. 2020]] ; [[#Jakob--2021|Jakob 2021]] ). Many different approaches on how to share responsibility between producers and consumers have been proposed in designing effective integrated global climate policies ( [[#Liu--2017|Liu and Fan 2017]] ; [[#Khajehpour--2019|Khajehpour et al. 2019]] ; [[#Jakob--2021|Jakob et al. 2021]] ). Ultimately, assigning responsibility is normative.

The dominant method for calculating nations’ CBEs is global multi-region input-output (GMRIO) analysis ( [[#Wiedmann--2018|Wiedmann and Lenzen 2018]] ). Other frequently used approaches include analysing bilateral trade flows of products and their lifecycle emission factors ( [[#Sato--2014|Sato 2014]] ). Generally, the uncertainties associated with CBEs depends on the choice of the dataset/model used for calculation, which differs according to: (i) the national economic and trade data used; (ii) the emissions data used; (iii) the sector or product-level aggregation; (iv) the regional aggregation; (v) the conceptual scope (e.g., residential vs territorial accounting principle); and (vi) the model construction techniques, which include table-balancing algorithms and ways of dealing with missing or conflicting data ( [[#Moran--2014|Moran and Wood 2014]] ; [[#Owen--2017|Owen, 2017]] ; [[#Wieland--2018|Wieland et al. 2018]] ; [[#Wood--2018|Wood et al. 2018]] , 2019). When excluding systematic error sources, research has shown that the stochastic relative standard deviation (RSD) of total national CBEs is not significantly different to that from PBEs accounts and in the region of 5–15% ( [[#Wood--2018|Wood et al. 2018]] , 2019).

Six global accounts for consumption-based GHG emissions at the country level are widely used (Table 2.2). Each dataset has been constructed by different teams of researchers, covering different time periods and containing CBEs estimates for different sets of countries and regions ( [[#Owen--2017|Owen 2017]] ).

[[#Wood--2019|Wood et al. (2019)]] present a comprehensive and systematic model intercomparison and find a variation of 5–10% for both PBE and CBE accounts of major economies and country groups (e.g., EU-28, OECD). The estimates for the USA were the most closely aligned, with 3.7% RSD. For smaller countries, variability is in the order of 20–30% and can reach more than 40% in cases of very small, highly trade-exposed countries such as Singapore and Luxembourg ( [[#Wood--2019|Wood et al. 2019]] ). It is recommended that CBEs results for such countries be interpreted with care.

Overall, production accounts showed a slightly higher convergence (8% average of RSD) than consumption-based accounts (12%). The variation across model results can be approximately halved, when normalising national totals to one common value for a selected base year. The difference between PBEs result variation (4% average RSD after normalisation) and CBEs results (7%) remains after normalisation.

In general, the largest contributors to uncertainty of CBEs results are – in descending order of priority – the total of territorial GHG emission accounts, the allocation of emissions to economic sectors, the total and composition of final demand, and lastly the structure of the economy. Harmonising territorial emissions across GMRIO datasets is the single most important factor that reduces uncertainty by about 50% ( [[#Tukker--2020|Tukker et al. 2020]] ). More work is required to optimise or even institutionalise the compilation of multi-region input-output data and models to enhance the accuracy of consumption-based accounting ( [[#Tukker--2018|Tukker et al. 2018]] ; [[#Wood--2018|Wood et al. 2018]] ).

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