Editing IPCC:AR6/WGIII/Chapter-11 (section)

=== 11.2.3 Industrial Development Patterns and Supply Chains (Regional) ===

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The dramatic increase in industrial emissions after 2000 is clearly associated with economic growth in Asia, which dominated both absolute and incremental emissions ( a,b).

More recent 2010 to 2019 trends show that regional contributions to additional emissions are distributed more evenly, while a large part still comes from Asian countries, where both rates of economic growth and the share of industrial emissions much exceed the global average. All other regions also contributed to total industrial GHG emissions. Structural shifts towards emissions from industrial processes and products use are common for many regions ( a).

'''Economic development.''' Regional differences in emission trends are determined by the differences observed in economic development, trade and supply chain patterns. The major source of industrial emissions is production of energy-intensive materials, such as iron and steel, chemicals and petrochemicals, non-ferrous metals and non-metallic products. Steel and cement are key inputs to urbanisation and infrastructure development (buildings and infrastructure are responsible for about three fourths of the steel stock). Application of a ‘services-stock-flow-emissions’ perspective ( [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ; [[#Bashmakov--2021|Bashmakov 2021]] ; [[#Haberl--2021|Haberl et al. 2021]] ) shows that relationship patterns between stages of economic development, per capita stocks and flows of materials are not trivial with some clear transition points. [[#Cao--2017|Cao et al. (2017)]] mapped countries by four progressive stages in cement stock per capita S-shape evolution as a function of income and urbanisation: initial stage for developing countries with a low level and slow linear growth; take-off stage with accelerated growth; slowdown stage; and finally a shrinking stage (represented by just a few countries with very high incomes exceeding 40,000 USD2010 per capita) and urbanisation levels above 80%. [[#Bleischwitz--2018|Bleischwitz et al. (2018)]] use a similar approach with five stages to study material saturation effects for apparent consumption and stocks per capita for steel, cement, aluminium, and copper. This logic may be generalised to other materials from which in-use stock is built. While globally cement in-use stock is about 12 tonnes per capita, in developed countries it is 15–30 tonnes per capita, but the order of magnitude is lower in developing states with high per capita escalation rates ( [[#Cao--2017|Cao et al. 2017]] ). When stocks for some materials saturate – per capita stock peaks – the ‘scrap age’ is coming ( [[#Pauliuk--2013a|Pauliuk et al. 2013a]] ). Steel in-use stock has already saturated in advanced economies at 14 ± 2 tonnes per capita due to largely completed urbanisation and infrastructure developments, and a switch towards services-dominated economy. This saturation level is three to four times that of the present global average, which is below 4 tonnes per capita ( [[#Pauliuk--2013a|Pauliuk et al. 2013a]] ; [[#Graedel--2011|Graedel et al. 2011]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ). China is entering the maturing stage of steel and cement consumption, resulting in a moderate projection of additional demand followed by expected industrial emissions peaking in the next 10 to 15 years ( [[#Zhou--2013|Zhou et al. 2013]] ; [[#Bleischwitz--2018|Bleischwitz et al. 2018]] ; [[#OECD--2019a|OECD 2019a]] ; [[#Wu--2019|Wu et al. 2019]] ; [[#Zhou--2020|Zhou et al. 2020]] ). But many developing countries are still urbanising, and the growing need for infrastructure services results in additional demand for steel and cement. Materials intensity of the global economy is projected by [[#OECD--2019a|OECD (2019a)]] to decline at 1.3% yr –1 until 2060, driven by improving resource efficiency and the switch to circular economy, but with a projected tripling of global GDP it means a doubling of projected materials use ( [[#OECD--2019a|OECD 2019a]] ). Under the business-as-usual scenario, India’s demand for steel may more than quadruple over the next 30 years ( [[#de%20la%20Rue%20du%20Can--2019|de la Rue du Can et al. 2019]] ; [[#Dhar--2020|Dhar et al. 2020]] ). In the [[#IEA--2021a|IEA (2021a)]] net-zero-energy scenario, the saturation effect along with material efficiency counterbalances activity effects and keeps demand growth for basic materials modest while escalate demand for critical materials (copper, lithium, nickel, graphite, cobalt and others).

'''International trade and supply chain.''' In Equation 11.1 the share of allocated emissions ( ''Dm'' ) equals unity when territorial emission is considered, and to the ratio of domestically used materials to total material production for consumption-based emission accounting. Tracking consumption-based emissions provides additional insights in the global effectiveness of national climate policies. Carbon emissions embodied in international trade are estimated to account for 20–30% of global carbon emissions ( [[#Meng--2018|Meng et al. 2018]] ; [[#OECD.Stat--2019|OECD.Stat 2019]] ) and are the reason for different emissions patterns of OECD versus non-OECD countries (Chapter 2).

Based on [[#OECD.Stat--2019|OECD.Stat (2019)]] datasets, 2015 CO 2 emissions embodied in internationally traded industrial products (manufacturing and mining, excluding fuels) by all countries are assessed at 3 GtCO 2 , or 30% of direct CO 2 emissions in the industrial sector as reported by [[#Crippa--2021|Crippa et al. (2021)]] . OECD countries collectively have reduced territorial emissions (shares of basic materials in direct emissions in those regions decline ( b), but demonstrated no progress in reducing outsourced emissions embedded in imported industrial products ( [[#Arto--2014|Arto and Dietzenbacher 2014]] ; [[#OECD.Stat--2019|OECD.Stat 2019]] ). Accounting for net carbon emissions embodied in international trade of only industrial products (1283 million tCO 2 in 2015) escalates direct OECD industrial CO 2 emissions (1333 million tCO 2 of energy-related and 502 million tCO 2 of industrial processes) 1.7 fold, 2.3-fold for the US, 1.5-fold for the EU, and more than triples it for the UK, while cutting ( ''Dm'' ) by a third for China and Russia ( [[#OECD.Stat--2019|OECD.Stat 2019]] ; [[#IEA--2020f|IEA 2020f]] ). In most OECD economies, the amount of CO 2 embodied in net import from non-OECD countries is equal to, or even greater than, the size of their Paris 2030 emissions reduction commitments. In the UK, the Parliament Committee on Energy and Climate Change requested that a consumption-based inventory be complementarily used to assess the effectiveness of domestic climate policy in delivering absolute global emissions reductions ( [[#Barrett--2013|Barrett et al. 2013]] ; [[#UKCCC--2019a|UKCCC 2019a]] ). It should be noted that the other side of the coin is that exports from countries with lower production carbon intensities can lead to overall less emissions than if production took place in countries with high carbon intensities, which may become critical in the global evolution toward lower emissions. The evolution of ''Dm'' to the date was driven mostly by factors other than carbon regulation often equipped with carbon leakage prevention tools. Empirical tests have failed to date to detect meaningful ‘carbon leakage’ and impacts of carbon prices on net import, direct foreign investments, volumes of production, value added, employment, profits, and innovation in industry ( [[#Sartor--2013|Sartor 2013]] ; [[#Branger--2016|Branger et al. 2016]] ; Saussay and Sato 2018; [[#Ellis--2019|Ellis et al. 2019]] ; [[#Naegele--2019|Naegele and Zaklan 2019]] ; [[#Acworth--2020|Acworth et al. 2020]] ; [[#Carratù--2020|Carratù et al. 2020]] ; [[#Pyrka--2020|Pyrka et al. 2020]] ; [[#Zachmann--2020|Zachmann and McWilliams 2020]] ). In the coming years, availability of large low-cost renewable electricity potential and cheap hydrogen may become a new driver for relocation of such carbon intensive industries as steel production ( [[#Bataille--2020a|Bataille 2020a]] ; [[#Gielen--2020|Gielen et al. 2020]] ; [[#Bataille--2021a|Bataille et al. 2021a]] ; [[#Saygin--2021|Saygin and Gielen 2021]] ).

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